Package 'magpie4'

Title: MAgPIE outputs R package for MAgPIE version 4.x
Description: Common output routines for extracting results from the MAgPIE framework (versions 4.x).
Authors: Benjamin Leon Bodirsky [aut, cre], Florian Humpenoeder [aut], Jan Philipp Dietrich [aut], Miodrag Stevanovic [aut], Isabelle Weindl [aut], Kristine Karstens [aut], Xiaoxi Wang [aut], Abhijeet Mishra [aut], Felicitas Beier [aut], Jannes Breier [aut], Amsalu Woldie Yalew [aut], David Chen [aut], Anne Biewald [aut], Stephen Wirth [aut], Patrick von Jeetze [aut], Debbora Leip [aut], Michael Crawford [aut], Marcos Alves [aut], Pascal Sauer [aut], Markus Bonsch [ctb], Singh Vartika [ctb], Patrick Rein [aut]
Maintainer: Benjamin Leon Bodirsky <[email protected]>
License: LGPL-3 | file LICENSE
Version: 2.76.3
Built: 2026-06-04 16:59:27 UTC
Source: https://github.com/pik-piam/magpie4

Help Index

MAgPIE outputs R library for MAgPIE version 4.x

Description

Common output routines for extracting results from the MAgPIE framework (versions 4.x).

Author(s)

Maintainer: Jan Philipp Dietrich <[email protected]>

See Also

Useful links:

addGeometry

Description

Enriches land use data on cluster resolution geometry information as required for conversion by magclass::as.SpatVector

Usage

addGeometry(x, clustermap)

Arguments

x

Landuse data on cluster/cell resolution as a magclass object
clustermap

A dataframe mapping with columns cluster, cell, and optionally country

Value

A magclass object enriched with geometry information

Author(s)

Jan Philipp Dietrich, Pascal Sauer

See Also

Other Spatial: clusterOutputToTerraVector(), gdxAggregate(), mappingToLongFormat(), superAggregateX()

Examples

## Not run: 
landUse <- magpie4::land("fulldata.gdx", level = "cell")
clustermap <- readRDS(Sys.glob("clustermap_*.rds"))
landUseEnriched <- magpie4::addGeometry(landUse, clustermap)
attr(landUseEnriched, "geometry")
attr(landUseEnriched, "crs")

## End(Not run)

addToDataChangelog

Description

Prepend data from the given report to the changelog.

Usage

addToDataChangelog(
  report,
  changelog,
  versionId,
  years = changelogYears(),
  variables = changelogVariables(),
  ...,
  maxEntries = 15,
  roundDigits = 2
)

Arguments

report

data.frame as obtained by readRDS("report.rds")
changelog

Path to the changelog file
versionId

The model version identifier, e.g. a release number like 4.9.1 or a date like 2025-02-01
years

For which years the variables should be read and put into the changelog
variables

named vector of which variables to read from the report
...

Reserved for future expansion.
maxEntries

The maximum number of versionIds to keep in the changelog, the oldest one is removed first.
roundDigits

Numbers are rounded to this many decimal places before being written to the changelog.

Value

Invisibly, the written changelog as data.frame

Author(s)

Pascal Sauer

See Also

Other Data Changelog: changelogVariables(), changelogYears()

agEmployment

Description

returns employment in crop+livestock production from MAgPIE results

Usage

agEmployment(gdx, type = "absolute", detail = TRUE, level = "reg", file = NULL)

Arguments

gdx

GDX file
type

"absolute" for total number of people employed, "share" for share out of working age population
detail

if TRUE, employment is disaggregated to crop products, livestock products and (if available) mitigation measures, if FALSE only aggregated employment is reported, if
level

spatial aggregation to report employment ("iso", "reg", "glo" or "regglo", if type is "absolute" also "grid")
file

a file name the output should be written to using write.magpie

Value

employment in agriculture as absolute value or as percentage of working age population

Author(s)

Debbora Leip, David M Chen

Examples

## Not run: 
x <- agEmployment(gdx)

## End(Not run)

AgGDP

Description

Reads data to calculate the agricultural GDP

Usage

AgGDP(gdx, file = NULL, level = "reg")

Arguments

gdx

GDX file
file

a file name the output should be written to using write.magpie
level

Level of regional aggregation; "reg" (regional), "glo" (global), "regglo" (regional and global) or any other aggregation level defined in superAggregate

Value

A MAgPIE object containing values related with overall value of production [million US$17]

Author(s)

Edna Molina Bacca

Examples

## Not run: 
    x <- AgGDP(gdx)
  
## End(Not run)

AgriResearchIntensity

Description

calculates Agricultural Research Intensity (Investment in AgR&D/Total GDP) from a MAgPIE gdx file

Usage

AgriResearchIntensity(gdx, file = NULL, level = "reg")

Arguments

gdx

GDX file
file

a file name the output should be written to using write.magpie
level

aggregation level, reg, glo or regglo, cell or grid

Author(s)

David M Chen

Examples

## Not run: 
x <- AgriResearchIntensity(gdx)

## End(Not run)

anthropometrics

Description

Calculates anthropometic indicators from the food demand model

Usage

anthropometrics(
  gdx,
  indicator = "bodyheight",
  age = "adults",
  sex = FALSE,
  bmi_groups = FALSE,
  level = "iso",
  final = TRUE,
  file = NULL,
  calibrated = TRUE
)

Arguments

gdx

GDX file
indicator

bodyheight, bodyweight, bodyweight_healthy, BMI(Body Mass Index) or PAL (physical activity level)
age

if TRUE, demand is scaled down to age-groups and sex using food requirements
sex

if FALSE, female and male are aggregated, if sex, results are divided into males and females
bmi_groups

if TRUE, data is provided by BMI group
level

Level of regional aggregation; "iso" ISO country codes, "reg" (regional), "glo" (global)
final

final results or preliminary results (the latter are the ones magpie uses for optimization before last iteration with demand model)
file

a file name the output should be written to using write.magpie
calibrated

if TRUE, uses the calibrated intake estimates for bodyweight estimation

Details

Demand definitions are equivalent to FAO Food supply categories

Value

bodyweight (kg), bodyheight (cm), BMI or PAL as magpie objects

Author(s)

Benjamin Leon Bodirsky

Examples

## Not run: 
    x <- anthropometrics(gdx)
  
## End(Not run)

Biodiversity intactness index

Description

calculates the area weighted biodiversity intactness index (BII) out of a MAgPIE gdx file

Usage

BII(
  gdx,
  file = NULL,
  level = "glo",
  mode = "auto",
  landClass = "sum",
  spatialWeight = NULL,
  adjusted = FALSE,
  bii_coeff = NULL,
  side_layers = NULL
)

Arguments

gdx

GDX file
file

a file name the output should be written to using write.magpie
level

level of regional aggregation; "cell" (magpie cluster level), "reg" (regional), "glo" (global), "regglo" (regional and global), "iso" (country level), "grid" (0.5 degree grid cell level).
mode

"auto" (default), "from_grid", "MAgPIE" or "postprocessing".

  • "MAgPIE" reports the BV based on values from the MAgPIE biodiversity module.

  • "postprocessing" calculates the BV based on land information from MAgPIE (for versions where biodiversity module was not available yet).

  • "auto" uses "MAgPIE" if available and falls back to "postprocessing" otherwise.

  • "from_grid" calculates BII values from BII output and returns aggregated values at the aggregation level specified.

landClass

"all" returns average BII values for all land classes of ov_bv, "sum" returns the weighted BII over all land classes of ov44_bv_weighted.
spatialWeight

Spatial weight for aggregating BII values. Only relevant if mode is "from_grid", adjusted is TRUE, or level is either "grid" or "iso".
adjusted

if "TRUE", function returns adjusted BII values (results have been adjusted for primary and secondary other land).
bii_coeff

file containing BII coefficients. Only needed for mode = "postprocessing". NULL tries to automatically detected the file.
side_layers

file containing LUH2 side layers. NULL tries to automatically detected the file.

Details

Calculates global, regional and cluster-level biodiversity intactness index (BII)

Value

Biodiversity intactness index (unitless)

Author(s)

Patrick v. Jeetze, Florian Humpenoeder, Felicitas Beier

Examples

## Not run: 
x <- BII(gdx)

## End(Not run)

biochar

Description

Calculates biochar-related indicators from a MAgPIE gdx file. This function provides all indicators for biochar-related material flows and conversion, including biochar production, feedstock demand, and long-term stable carbon storage in soils.

Usage

biochar(
  gdx,
  indicator,
  level = "reg",
  feedstockAggr = FALSE,
  systemAggr = FALSE,
  attributes = "c",
  file = NULL
)

Arguments

gdx

GDX file
indicator

Indicator types: bc_production, bc_feedstock_dem or bc_stable_carbon
level

Spatial aggregation: "reg", "glo", or "regglo"
feedstockAggr

If TRUE, aggregates over feedstock types. If not applicable for the selected indicator, set to FALSE (default).
systemAggr

If TRUE, aggregates over bc_sys63 or biopyr_all63. If not applicable for the selected indicator, set to FALSE (default).
attributes

Available output attributes: dry matter: Mt ("dm"), gross energy: PJ ("ge"), carbon: Mt C ("c"). Can also be a vector. The availability of attributes depends on the selected indicator.
file

File name the output should be written to using write.magpie

Value

Selected biochar-related indicator as MAgPIE object:

  • bc_production: Biochar production (unit depends on attributes). Available attributes are "dm", "ge", and "c".

  • bc_feedstock_dem: Biomass feedstock demand for biochar (unit depends on attributes). Available attributes are "dm", "ge", and "c".

  • bc_stable_carbon: Stable C in soil from biochar after 100 years (mio. tC per yr). Available attribute is "c".

Author(s)

Isabelle Weindl

Examples

## Not run: 
  x <- biochar(gdx, indicator = "bc_production", level = "regglo", feedstockAggr = TRUE)

## End(Not run)

bioplasticDemand

Description

returns demand for bioplastic or demand for substrate for bioplastic production

Usage

bioplasticDemand(
  gdx,
  type = "bioplastic",
  detail = FALSE,
  level = "regglo",
  file = NULL
)

Arguments

gdx

GDX file
type

"bioplastic" for bioplastic demand, "substrate" for biomass demand as substrate for bioplastic production
detail

only relevant for type = "substrate". If TRUE, substrate demand is disaggregated by crop type, if FALSE only the aggregated demand is reported.
level

spatial aggregation to report bioplastic/substrate demand (only "reg" or "regglo")
file

a file name the output should be written to using write.magpie

Author(s)

Debbora Leip

Examples

## Not run: 
x <- bioplasticDemand(gdx)

## End(Not run)

bodyweight

Description

Calculates the prevalence of underweight, normalweight, overweight (excluding obesity) and obesity. For more detailed body mass classifications see functions population or anthropometrics.

Usage

bodyweight(
  gdx,
  level = "reg",
  age = FALSE,
  sex = FALSE,
  share = FALSE,
  population = NULL
)

Arguments

gdx

GDX file
level

Level of regional aggregation; "iso" ISO country codes, "reg" (regional), "glo" (global)
age

if TRUE, demand is scaled down to age-groups and sex using food requirements
sex

if FALSE, female and male are aggregated, if sex, results are divided into males and females
share

if TRUE, data is provided by BMI group
population

population information from GDX. Can be provided to speed up calculation process. Will be read from GDX, if not provided.

Details

Demand definitions are equivalent to FAO Food supply categories

Value

MAgPIE object with mio people or share of people in each weight category

Author(s)

Benjamin Leon Bodirsky

Examples

## Not run: 
    x <- bodyweight(gdx)
  
## End(Not run)

carbonHWP

Description

reads carbon stored in harvested timber out of a MAgPIE gdx file

Usage

carbonHWP(
  gdx,
  file = NULL,
  level = "cell",
  unit = "element",
  half_life = 35,
  cumulative = FALSE,
  baseyear = 1995
)

Arguments

gdx

GDX file
file

a file name the output should be written to using write.magpie
level

Level of regional aggregation; "cell", "reg" (regional), "glo" (global), "regglo" (regional and global) or any secdforest aggregation level defined in superAggregate
unit

element" or "gas"; "element": co2_c in Mt C/yr, n2o_n in Mt N/yr, ch4 in Mt CH4/yr; "gas": co2_c Mt CO2/yr, n2o_n in Mt NO2/yr, ch4 in Mt CH4/yr
half_life

Half life in years for decay in wood products loosing half theor carbon content. (35 yrs is deafault)
cumulative

Logical; Determines if cHWP emissions are reported annually (FALSE) or cumulative (TRUE). The starting point for cumulative emissions is y1995.
baseyear

Baseyear used for cumulative emissions (default = 1995)

Details

Annual (and cumulative) Carbon stored in harvested wood products as well as slow emissions from half life deacy.

Value

carbon stocks in MtC from harvested timber

Author(s)

Abhijeet Mishra, Florian Humpenoeder

Examples

## Not run: 
    x <- carbonHWP(gdx)
  
## End(Not run)

carbonLTS

Description

reads carbon stored in harvested timber out of a MAgPIE gdx file

Usage

carbonLTS(
  gdx,
  file = NULL,
  level = "cell",
  unit = "element",
  cumulative = FALSE,
  baseyear = 1995
)

Arguments

gdx

GDX file
file

a file name the output should be written to using write.magpie
level

Level of regional aggregation; "cell", "reg" (regional), "glo" (global), "regglo" (regional and global) or any secdforest aggregation level defined in superAggregateX
unit

element" or "gas"; "element": co2_c in Mt C/yr, n2o_n in Mt N/yr, ch4 in Mt CH4/yr; "gas": co2_c Mt CO2/yr, n2o_n in Mt NO2/yr, ch4 in Mt CH4/yr
cumulative

Logical; Determines if cHWP emissions are reported annually (FALSE) or cumulative (TRUE). The starting point for cumulative emissions is y1995.
baseyear

Baseyear used for cumulative emissions (default = 1995)

Details

Annual (and cumulative) Carbon stored in harvested wood products, as well as, slow emissions from half life deacy.

Value

carbon stocks in MtC from harvested timber

Author(s)

Abhijeet Mishra, Florian Humpenoeder

Examples

## Not run: 
x <- carbonLTS(gdx)

## End(Not run)

carbonstock

Description

reads carbon stocks out of a MAgPIE gdx file

Usage

carbonstock(
  gdx,
  file = NULL,
  level = "cell",
  sum_cpool = TRUE,
  sum_land = TRUE,
  subcategories = NULL,
  stockType = "actual"
)

Arguments

gdx

GDX file
file

a file name the output should be written to using write.magpie
level

Level of regional aggregation; "cell", "reg" (regional), "glo" (global), "regglo" (regional and global) or any secdforest aggregation level defined in superAggregate
sum_cpool

sum over carbon pool dimension (default = TRUE)
sum_land

sum over land type dimension (default = TRUE)
subcategories

NULL or vector of strings. If NULL, no subcategories are returned. Meaningful options are "crop, "forestry" and "other"
stockType

carbon stock type (default = "actual"). Options: "actual", "previousLandPattern" and "previousCarbonDensity".

Details

carbon pools consist of vegetation carbon (vegc), litter carbon (litc) and soil carbon (soilc)

Value

carbon stocks in MtC

Author(s)

Florian Humpenoeder

Examples

## Not run: 
x <- carbonstock(gdx)

## End(Not run)

cellular fit

Description

cellular fit/error/bias calculations at regional and global level

Usage

cellularFit(
  gdx,
  file = NULL,
  level = "cell",
  statistic = "MAE",
  variable = "land",
  dataset = "LUH3",
  water_aggr = FALSE
)

Arguments

gdx

GDX file
file

a file name the output should be written to using write.magpie
level

level at which the regional and global bias should be calculated. Options "cell" or "grid"
statistic

R2, MAE, MPE (mean percentage error - bias), MAPE (mean absolute percentage error)
variable

variable to be evaulated: land (land types) or crop (crop types)
dataset

dataset to compare with. LUH3 only option for variable land. LUH3 and MAPSPAM for the crop variable.
water_aggr

if irrigation types for crops should be agregated or not

Value

returns selected statistic at regglo level for the historical part of the time horizon

Author(s)

Edna J. Molina Bacca, Patrick v. Jeetze

Examples

## Not run: 
    x <- cellularFit(gdx)
  
## End(Not run)

changelogVariables

Description

Returns a named vector of variables to put into the data changelog, see addToDataChangelog.

Usage

changelogVariables()

Author(s)

Pascal Sauer

See Also

Other Data Changelog: addToDataChangelog(), changelogYears()

changelogYears

Description

Returns the years to put into the data changelog, see addToDataChangelog.

Usage

changelogYears()

Author(s)

Pascal Sauer

See Also

Other Data Changelog: addToDataChangelog(), changelogVariables()

modelstat

Description

Function to check if the library functions work with the newest magpie version

Usage

checkLibrary(gdx, level = NULL)

Arguments

gdx

GDX file
level

Level of regional aggregation; "reg" (regional), "glo" (global), "regglo" (regional and global) or any other aggregation level defined in superAggregate

Details

This function simply tries to run all functions in the magpie library on the provided gdx file.

Value

A list with three entries:

  • notest Testing these functions was impossible because there wer missing arguments.

  • error These functions could not be executed properly.

  • fine Everything was fine with these functions.

Author(s)

Markus Bonsch

Examples

## Not run: 
    x <- modelstat(gdx)
  
## End(Not run)

clearCacheMagpie4

Description

Clear memoise cache for all memoised functions in magpie4

Usage

clearCacheMagpie4()

Value

no return, but cache cleared

Author(s)

Benjamin Leon Bodirsky

Examples

## Not run: 
x <- clearCacheMagpie4()

## End(Not run)

Convert cluster output to terra vector

Description

Enriches land use data on cluster resolution with explicit spatial information by creating a terra polygon for each cluster according to the given clustermap.

Usage

clusterOutputToTerraVector(x, clustermap)

Arguments

x

Landuse data on cluster/cell resolution as a magclass object
clustermap

A dataframe mapping with columns cluster, cell, and country

Value

A SpatVector with the following columns: c("clusterId", "country", "region", "year", "landtype", "value")

Author(s)

Pascal Führlich, Patrick v. Jeetze

See Also

Other Spatial: addGeometry(), gdxAggregate(), mappingToLongFormat(), superAggregateX()

Examples

## Not run: 
landUse <- magpie4::land("fulldata.gdx", level = "cell")
clustermap <- readRDS(Sys.glob("clustermap_*.rds"))
clusterPolygons <- magpie4::clusterOutputToTerraVector(landUse, clustermap)
terra::writeVector(clusterPolygons, "cluster_resolution.shp")

## End(Not run)

consumptionValue

Description

calculates consumption value of different types based on a MAgPIE gdx file.

Usage

consumptionValue(
  gdx,
  file = NULL,
  level = "reg",
  products = "kall",
  product_aggr = TRUE,
  type = NULL,
  type_aggr = TRUE
)

Arguments

gdx

GDX file
file

a file name the output should be written to using write.magpie
level

Level of regional aggregation; "reg" (regional), "glo" (global), "regglo" (regional and global) or any other aggregation level defined in superAggregate
products

Selection of products (either by naming products, e.g. "tece", or naming a set,e.g."kcr")
product_aggr

aggregate over products or not (boolean, default TRUE)
type

Consumption type(s): "food", "feed", "processed", "other_util", "bioenergy", "seed", "waste", "dom_balanceflow; NULL returns all types
type_aggr

aggregate over demand types or not (boolean, default TRUE)

Value

A MAgPIE object containing consumption value in million $US.

Author(s)

Miodrag Stevanovic

Examples

## Not run: 
    x <- consumptionValue(gdx)
  
## End(Not run)

CostCapital

Description

Reads data to calculate capital stocks

Usage

CostCapital(gdx, type = "stocks", file = NULL, level = "cell")

Arguments

gdx

GDX file
type

either capital stocks ("stocks") or overall capital investment "investment"
file

a file name the output should be written to using write.magpie
level

Level of regional aggregation; "reg" (regional), "glo" (global), "regglo" (regional and global) or any other aggregation level defined in superAggregate

Value

A MAgPIE object containing values related with overall value of production [million US$17]

Author(s)

Edna Molina Bacca

Examples

## Not run: 
    x <- CostCapital(gdx)
  
## End(Not run)

CostOverall

Description

Gross value of productions

Usage

CostOverall(gdx, file = NULL, level = "reg")

Arguments

gdx

GDX file
file

a file name the output should be written to using write.magpie
level

Level of regional aggregation; "reg" (regional), "glo" (global), "regglo" (regional and global) or any other aggregation level defined in superAggregate

Value

A MAgPIE object containing values related with overall value of production [million US$17]

Author(s)

Edna Molina Bacca

Examples

## Not run: 
x <- CostOverall(gdx)

## End(Not run)

costs

Description

reads costs entering the objective function from a MAgPIE gdx file

Usage

costs(gdx, file = NULL, level = "reg", type = "annuity", sum = TRUE)

Arguments

gdx

GDX file
file

a file name the output should be written to using write.magpie
level

Level of regional aggregation; "reg" (regional), "glo" (global), "regglo" (regional and global) or any other aggregation level defined in superAggregate
type

either "annuity" (as it enters the objetive function) or "investment" (investment)
sum

total costs (TRUE) or detailed costs (FALSE)

Value

A MAgPIE object containing the goal function costs including investments [million US$17]

Author(s)

Jan Philipp Dietrich, Markus Bonsch, Misko Stevanovic, Florian Humpenoeder, Edna J. Molina Bacca, Michael Crawford

Examples

## Not run: 
x <- costs(gdx)

## End(Not run)

CostsAEI

Description

reads AEI costs entering the objective function from a MAgPIE gdx file

Usage

CostsAEI(gdx, file = NULL, level = "regglo")

Arguments

gdx

GDX file
file

a file name the output should be written to using write.magpie
level

Level of regional aggregation ("reg", "glo", "regglo")

Value

MAgPIE object containing costs for AEI [million US$17]

Author(s)

Felicitas Beier

Examples

## Not run: 
    x <- CostsAEI(gdx)
  
## End(Not run)

CostsFertilizer

Description

reads costs entering the objective function from a MAgPIE gdx file

Usage

CostsFertilizer(gdx, file = NULL, level = "regglo", disagg = TRUE)

Arguments

gdx

GDX file
file

a file name the output should be written to using write.magpie
level

Level of regional aggregation ("reg", "glo", "regglo")
disagg

whether costs should be disaggregated into the different crop types

Value

MAgPIE object containing fertilizer costs [million US$17]

Author(s)

Debbora Leip

Examples

## Not run: 
    x <- CostsFertilizer(gdx)
  
## End(Not run)

costsMACCS

Description

reads costs entering the objective function from a MAgPIE gdx file

Usage

costsMACCS(gdx, file = NULL, level = "regglo")

Arguments

gdx

GDX file
file

a file name the output should be written to using write.magpie
level

Level of regional aggregation ("reg", "glo", "regglo")

Value

MAgPIE object containing mitigation costs [million US$17]

Author(s)

Debbora Leip

Examples

## Not run: 
    x <- costsMACCS(gdx)
  
## End(Not run)

costsPresolve

Description

reads presovle costs (i.e. without bioenergy demand) entering the objective function from a MAgPIE gdx file

Usage

costsPresolve(gdx, file = NULL, level = "reg")

Arguments

gdx

GDX file
file

a file name the output should be written to using write.magpie
level

Level of regional aggregation; "reg" (regional), "glo" (global), "regglo" (regional and global) or any other aggregation level defined in superAggregate

Details

Presolve is without bioenergy demand. Hence costs from a MAgPIE run with bioenergy demand minus costs from presolve reflect costs that can be attributed to bioenergy production

Value

A MAgPIE object containing the goal function costs in presolve mode [million US$17]

Author(s)

Florian Humpenoeder

Examples

## Not run: 
    x <- costsPresolve(gdx)
  
## End(Not run)

costsWholesale

Description

Reads data to calculate wholesale costs

Usage

costsWholesale(gdx, file = NULL, level = "regglo")

Arguments

gdx

GDX file
file

a file name the output should be written to using write.magpie
level

Level of regional aggregation; "reg" (regional), "glo" (global), "regglo" (regional and global) or any other aggregation level defined in superAggregateX

Value

A MAgPIE object containing values related with costs wholesale trade [million US$17/tDM]

Author(s)

David M Chen

Examples

## Not run: 
x <- costsWholesale(gdx)

## End(Not run)

CostsWithoutIncentives

Description

calculates agricultural costs without taxes, incentives and technical penalty costs (i.e. GHG taxes and BII incentives)

Usage

CostsWithoutIncentives(gdx, file = NULL, level = "regglo")

Arguments

gdx

GDX file
file

a file name the output should be written to using write.magpie
level

aggregation level, reg, glo or regglo

Value

A MAgPIE object containing the costs without taxes, incentives and technical penalty costs [million US$17]

Author(s)

David M Chen

Examples

## Not run: 
  x <- CostsWithoutIncentives(gdx)

## End(Not run)

CostTC

Description

Reads data on TC costs

Usage

CostTC(gdx, file = NULL, level = "reg")

Arguments

gdx

GDX file
file

a file name the output should be written to using write.magpie
level

Level of regional aggregation; "reg" (regional), "glo" (global), "regglo" (regional and global) or any other aggregation level defined in superAggregate

Value

A MAgPIE object containing values related with overall value of production [million US$17]

Author(s)

David Chen

Examples

## Not run: 
    x <- CostTC(gdx)
  
## End(Not run)

CostTransport

Description

reads costs entering the objective function from a MAgPIE gdx file

Usage

CostTransport(gdx, file = NULL, level = "cell", sum = FALSE)

Arguments

gdx

GDX file
file

a file name the output should be written to using write.magpie
level

Level of regional aggregation; "reg" (regional), "glo" (global), "regglo" (regional and global) or any other aggregation level defined in superAggregate.
sum

total costs (TRUE) or detailed costs (FALSE)

Value

A MAgPIE object containing the transport costs [million US$17]

Author(s)

David Chen

Examples

## Not run: 
    x <- CostTransport(gdx)
  
## End(Not run)

croparea

Description

reads croparea out of a MAgPIE gdx file. Croparea excludes fallow land.

Usage

croparea(
  gdx,
  file = NULL,
  level = "reg",
  products = "kcr",
  product_aggr = TRUE,
  water_aggr = TRUE
)

Arguments

gdx

GDX file
file

a file name the output should be written to using write.magpie
level

Level of regional aggregation; "reg" (regional), "glo" (global), "regglo" (regional and global) or any other aggregation level defined in gdxAggregate
products

Selection of products (either by naming products, e.g. "tece", or naming a set,e.g."kcr")
product_aggr

aggregate over products or not (boolean)
water_aggr

aggregate irrigated and non-irriagted production or not (boolean).

Value

production as MAgPIE object (unit depends on attributes)

Author(s)

Jan Philipp Dietrich, Florian Humpenoeder

See Also

reportCroparea

Examples

## Not run: 
x <- croparea(gdx)

## End(Not run)

CropareaDiversityIndex

Description

calculates an index that measures the croparea diversity

Usage

CropareaDiversityIndex(
  gdx,
  index = "shannon",
  level = "reg",
  measurelevel = "cell",
  groupdiv = "agg1"
)

Arguments

gdx

GDX file
index

can be "shannon", "gini" or "invsimpson" for different types of diversitiy indices
level

Level of regional aggregation; "reg" (regional), "glo" (global), "regglo" (regional and global) or any other aggregation level defined in superAggregate
measurelevel

level at which diversity is measured. "cell" means diversity
groupdiv

should crop groups be split up into several individual items or not? Choose either FALSE or different (dis)aggregation methods "agg1", "agg2"

Value

MAgPIE object (unit depends on attributes)

Author(s)

Benjamin Leon Bodirsky

See Also

CropareaDiversityIndex

Examples

## Not run: 
x <- CropareaDiversityIndex(gdx)

## End(Not run)

cropland

Description

reads cropland out of a MAgPIE gdx file. Cropland includes croparea plus fallow plus cropland with tree cover

Usage

cropland(gdx, level = "reg", types = NULL, sum = FALSE)

Arguments

gdx

GDX file
level

Level of regional aggregation; "reg" (regional), "glo" (global), "regglo" (regional and global) or any other aggregation level defined in gdxAggregate
types

NULL or a vector of strings. If NULL, all land types are used. Options are "crop_area", "crop_fallow", "crop_treecover"
sum

determines whether output should be land-type-specific (FALSE) or aggregated over all types (TRUE).

Value

land as MAgPIE object (Mha)

Author(s)

Benjamin Leon Bodirsky

See Also

reportLandUse

Examples

## Not run: 
x <- cropland(gdx)

## End(Not run)

croplandTreeCover

Description

calculates tree cover on cropland (Mha) from a MAgPIE gdx file

Usage

croplandTreeCover(gdx, level = "reg", sum_ac = TRUE, debug = FALSE)

Arguments

gdx

GDX file
level

aggregation level, reg, glo or regglo, cell or grid
sum_ac

sum over age classes TRUE / FALSE
debug

debug mode TRUE makes some consistency checks between estimates for different resolutions

Author(s)

Florian Humpenoeder

Examples

## Not run: 
x <- fallow(gdx)

## End(Not run)

cshare

Description

Calculates soil carbon share in relation to potential natural vegetation based on a MAgPIE gdx file

Usage

cshare(
  gdx,
  file = NULL,
  level = "reg",
  reference = "actual",
  noncrop_aggr = TRUE
)

Arguments

gdx

GDX file
file

a file name the output should be written to using write.magpie
level

Level of regional aggregation; "reg" (regional), "glo" (global), "regglo" (regional and global) or any other aggregation level defined in superAggregate
reference

default is "actual" (cshare in actual carbon stocks). Other option is "target" (cshare in target carbon stocks).
noncrop_aggr

aggregate non cropland types to 'noncropland' (if FALSE all land types of pools59 will be reported)

Value

A MAgPIE object containing som values

Author(s)

Kristine Karstens

Examples

## Not run: 
x <- cshare(gdx)

## End(Not run)

deco

Description

Function that quantifies the influences of the underlying drivers to a dependent output variable. It attributes the changes of the output variable (A) to changes of several drivers (B, B/C, C/A). The output must be the product of the drivers.

Usage

deco(data, names_factor = NULL, plot = FALSE)

Arguments

data

Decomposition Data as a magpie object. The first column of the third dimension has to be the output (A), while the subsequent columns are the coefficients of the drivers (B,C,...). Example: Area = Population x Supply/Population x Area/Supply. 3rd-dimension column order then has to be: Area, Population, Supply.
names_factor

Names of the output (A) and the Decomposition-Factors (B,B/C,C/A), if names_factor=NULL the names for the third column will be generated like the factors for decomposition (above example: Area, Population, Supply/Population, Area/Supply)
plot

TRUE or FALSE

Details

Use function deco_plot in library luplot to make a plot out of this. It is only usable for the decomposition of 5 or less drivers. For documentation, see paper Huber, Veronika, Ina Neher, Benjamin L. Bodirsky, Kathrin Hoefner, and Hans Joachim Schellnhuber. 2014. "Will the World Run out of Land? A Kaya-Type Decomposition to Study Past Trends of Cropland Expansion." Environmental Research Letters 9 (2): 024011. https://doi.org/10.1088/1748-9326/9/2/024011. Or see master Thesis of Ina Neher (2013)

Value

Decomposes the impact of certain drivers to an output (A) value.

Author(s)

Ina Neher, Benjamin Leon Bodirsky

Examples

Data<-array(c(1,1.1,1.15,1,1.05,1.1,1,1.05,1.15),c(3,3))
 dimnames(Data)<-list(paste("y",2000:2002,sep=""),c("Area","Population","Supply"))
 Data <- as.magpie(Data)
 deco(Data)

demand

Description

Calculates MAgPIE demand out of a gdx file

Usage

demand(
  gdx,
  file = NULL,
  level = "reg",
  products = "kall",
  product_aggr = FALSE,
  attributes = "dm",
  type = NULL,
  type_aggr = FALSE
)

Arguments

gdx

GDX file
file

a file name the output should be written to using write.magpie
level

Level of regional aggregation ("reg", "glo", "regglo")
products

Selection of products (either by naming products, e.g. "tece", or naming a set,e.g."kcr")
product_aggr

aggregate over products or not (boolean, default FALSE)
attributes

dry matter: Mt ("dm"), gross energy: PJ ("ge"), reactive nitrogen: Mt ("nr"), phosphor: Mt ("p"), potash: Mt ("k"), wet matter: Mt ("wm"). Can also be a vector.
type

Demand type(s): "food", "feed", "processed", "other_util", "bioenergy", "seed", "waste", "dom_balanceflow; NULL returns all types
type_aggr

aggregate over demand types or not (boolean, default FALSE)

Details

Demand definitions are equivalent to FAO CBS categories

Value

demand as MAgPIE object (Unit depends on attributes)

Author(s)

Benjamin Leon Bodirsky, Abhijeet Mishra, Miodrag Stevanovic

Examples

## Not run: 
    x <- demand(level="regglo", products="kcr")
  
## End(Not run)

demandBioenergy

Description

reads bioenergy demand from a MAgPIE gdx file

Usage

demandBioenergy(gdx, file = NULL, level = "reg", sum = FALSE, round = NULL)

Arguments

gdx

GDX file
file

a file name the output should be written to using write.magpie
level

Level of regional aggregation; "reg" (regional), "glo" (global), "regglo" (regional and global) or any other aggregation level defined in superAggregate
sum

1st and 2nd generation bioenergy demand (FALSE) or total bioenergy demand (TRUE)
round

NULL or number of digits

Value

A MAgPIE object containing bioenergy demand in EJ/yr

Author(s)

Jan Philipp Dietrich, Florian Humpenoeder

Examples

## Not run: 
    x <- demandBioenergy(gdx)
  
## End(Not run)

disaggregateLandConservation

Description

Read land conservation data from a fulldata.gdx and disaggregate to high resolution (0.5 deg).

Usage

disaggregateLandConservation(gdx, cfg, mapping, wdpaHr, conservationPrioHr)

Arguments

gdx

character, path to a fulldata.gdx
cfg

list, config data usually obtained with gms::loadConfig("config.yml")
mapping

dataframe, must include columns cell and cluster
wdpaHr

magclass, World Database on Protected Areas data in high resolution
conservationPrioHr

magclass, high resolution data on conservation priority areas

Value

magclass, high resolution land conservation area

Author(s)

Patrick v. Jeetze, Pascal Sauer

discountRates

Description

reads discount rates from a MAgPIE gdx file

Usage

discountRates(gdx, file = NULL, level = "reg")

Arguments

gdx

GDX file
file

a file name the output should be written to using write.magpie
level

Level of regional aggregation; "reg" (regional), "glo" (global), "regglo" (regional and global) or any other aggregation level defined in superAggregate

Value

A MAgPIE object containing discount rates used in the model

Author(s)

Xiaoxi Wang

Examples

## Not run: 
    x <- discountRates(gdx)
  
## End(Not run)

embodiedBiodiversity

Description

Calculates production-based and consumption-based (embodied) biodiversity impact accounting using bilateral trade flows. Biodiversity values (BII-weighted area) are allocated to traded products based on cropland and pasture area shares, similar to how CO2 LUC emissions are allocated.

Usage

embodiedBiodiversity(
  gdx,
  file = NULL,
  level = "reg",
  type = "all",
  indicator = "bv",
  bilateral = FALSE
)

Arguments

gdx

GDX file
file

a file name the output should be written to using write.magpie
level

Level of regional aggregation; "reg" (regional), "glo" (global), "regglo" (regional and global) or any other aggregation level defined in superAggregate. Only used when bilateral=FALSE.
type

Type of accounting: "production" (production-based), "consumption" (consumption-based), "trade" (export, import, and net-trade), "all" (all five), or "flows" (bilateral flows, requires bilateral=TRUE)
indicator

Which biodiversity indicator to use: "bv" (biodiversity value, BII-weighted area in Mha), "bii_loss" (1-BII, representing biodiversity loss)
bilateral

Logical; if TRUE, returns bilateral flows with dimensions (exporter.importer, year, product) instead of regional totals (default FALSE)

Details

Biodiversity is measured via the Biodiversity Intactness Index (BII) which ranges from 0 to 1. BII is calculated at the land cover class level (crop_ann, crop_per, manpast, rangeland, etc.) and not directly per product. This function allocates the biodiversity impact from cropland to individual crop products based on their area shares.

The indicator "bv" returns the BII-weighted area (higher = more biodiversity preserved), allocated to each crop by its share of total cropland area.

The indicator "bii_loss" returns the biodiversity loss ((1-BII) * area) for aggregate cropland/pasture, then allocates to individual products by area share. This represents "share of biodiversity loss attributable to this crop based on its area share."

Value

Embodied biodiversity impact as MAgPIE object. When bilateral=FALSE: dimensions are (region, year, accounting.product). When bilateral=TRUE: dimensions are (exporter.importer, year, product).

Author(s)

David M Chen

See Also

BII, land, croparea, trade

Examples

## Not run: 
  x <- embodiedBiodiversity(gdx, type = "all")
  # Bilateral flows
  xBilat <- embodiedBiodiversity(gdx, type = "flows", bilateral = TRUE)

## End(Not run)

embodiedEmissions

Description

Calculates production-based and consumption-based (embodied) emissions accounting using bilateral trade flows. For livestock products, emissions are attributed where livestock is produced (enteric fermentation, AWMS). For crop products, primary equivalents can be used. This uses the Kastner bilateral trade adjustment method.

Usage

embodiedEmissions(
  gdx,
  file = NULL,
  level = "reg",
  type = "all",
  unit = "GWP100AR6",
  pollutants = "all",
  aggregation = "pollutant",
  kastner = TRUE,
  bilateral = FALSE,
  disaggLivestock = FALSE
)

Arguments

gdx

GDX file
file

a file name the output should be written to using write.magpie
level

Level of regional aggregation; "reg" (regional), "glo" (global), "regglo" (regional and global) or any other aggregation level defined in superAggregate
type

Type of accounting: "production" (production-based), "consumption" (consumption-based), "trade" (export, import, and net-trade), "all" (all five), or "flows" (bilateral flows, requires bilateral=TRUE)
unit

GWP metric: "GWP100AR5", "GWP100AR6", "GWP*AR5", "GWP*AR6", "gas", or "element"
pollutants

Selection of pollutants: "co2", "ch4", "n2o", "nh3", "no2", "no3" or "all"
aggregation

Aggregate over products ("product"), pollutants ("pollutant"), both ("both"), or none (FALSE)
kastner

Logical; apply Kastner bilateral trade adjustment (default TRUE)
bilateral

Logical; if TRUE, returns bilateral flows with dimensions (exporter.importer, year, product) instead of regional totals (default FALSE)
disaggLivestock

Logical; if TRUE, the feed pathway retains the livestock product dimension, so crop-based emissions are attributed per animal product × feed crop. Passes disaggLivestock to tradedPrimariesBilateral. Use dimSums(x[kli_items], dim=3.1) to collapse to feed crops, or dimSums(x[kli_items], dim=3.2) to collapse to animal products. Default is FALSE (current behaviour: feed attributed to crops). Note: direct livestock emissions (enteric fermentation, AWMS) are always attributed to the animal product regardless of this setting.

Value

Embodied emissions as MAgPIE object (unit depends on unit). When bilateral=FALSE: dimensions are (region, year, accounting.product). When bilateral=TRUE: dimensions are (exporter.importer, year, product). When disaggLivestock=TRUE: feed items have dimensions kli_product.kve instead of feed.kve; prim/secd items and all aggregated accounting outputs are unchanged.

Author(s)

David M Chen

Examples

## Not run: 
  x <- embodiedEmissions(gdx, type = "all", unit = "GWP100AR6")
  # Bilateral flows
  xBilat <- embodiedEmissions(gdx, type = "flows", bilateral = TRUE)

## End(Not run)

embodiedLabor

Description

Calculates production-based and consumption-based (embodied) labor footprint accounting using bilateral trade flows. Employment (number of people) is allocated to traded products based on production ratios and bilateral trade patterns.

Usage

embodiedLabor(gdx, file = NULL, level = "reg", type = "all", bilateral = FALSE)

Arguments

gdx

GDX file
file

a file name the output should be written to using write.magpie
level

Level of regional aggregation; "reg" (regional), "glo" (global), "regglo" (regional and global) or any other aggregation level defined in superAggregate. Only used when bilateral=FALSE.
type

Type of accounting: "production" (production-based), "consumption" (consumption-based), "trade" (export, import, and net-trade), "all" (all five), or "flows" (bilateral flows, requires bilateral=TRUE)
bilateral

Logical; if TRUE, returns bilateral flows with dimensions (exporter.importer, year, product) instead of regional totals (default FALSE)

Value

Embodied employment as MAgPIE object (number of people). When bilateral=FALSE: dimensions are (region, year, accounting.product). When bilateral=TRUE: dimensions are (exporter.importer, year, product).

Author(s)

David M Chen

See Also

agEmployment, trade, embodiedLand

Examples

## Not run: 
  x <- embodiedLabor(gdx, type = "all")
  # Bilateral flows
  xBilat <- embodiedLabor(gdx, type = "flows", bilateral = TRUE)

## End(Not run)

embodiedLand

Description

Calculates production-based and consumption-based (embodied) land footprint accounting using bilateral trade flows. Land use is allocated to traded products based on production ratios and bilateral trade patterns.

Usage

embodiedLand(
  gdx,
  file = NULL,
  level = "reg",
  type = "all",
  landType = "all",
  bilateral = FALSE,
  disaggLivestock = FALSE
)

Arguments

gdx

GDX file
file

a file name the output should be written to using write.magpie
level

Level of regional aggregation; "reg" (regional), "glo" (global), "regglo" (regional and global) or any other aggregation level defined in superAggregate. Only used when bilateral=FALSE.
type

Type of accounting: "production" (production-based), "consumption" (consumption-based), "trade" (export, import, and net-trade), "all" (all five), or "flows" (bilateral flows, requires bilateral=TRUE)
landType

Type of land to report: "crop" (cropland), "past" (pasture), "all" (total agricultural land), or a vector of specific land types
bilateral

Logical; if TRUE, returns bilateral flows with dimensions (exporter.importer, year, product) instead of regional totals (default FALSE)
disaggLivestock

Logical; if TRUE, the feed pathway retains the livestock product dimension, so land is attributed per animal product × feed crop combination. Passes disaggLivestock to tradedPrimariesBilateral. Use dimSums(x[kli_items], dim=3.1) to collapse to feed crops, or dimSums(x[kli_items], dim=3.2) to collapse to animal products. Default is FALSE (current behaviour: feed attributed to crops).

Value

Embodied land use as MAgPIE object. When bilateral=FALSE and disaggLivestock=FALSE: dim 3 = accounting.product (2 subdims). When bilateral=FALSE and disaggLivestock=TRUE: dim 3 = accounting.{prim,secd,kli_*}.product (3 subdims); production/consumption have prim = crop+pasture land and kli_* = feed chain land per animal product (secd=0 in production); trade types retain the full secd pathway. Note: prim and kli_* items overlap (feed crops appear in both), so they should not be summed — use one or the other for attribution. When bilateral=TRUE: dim 3 = {prim,secd,kli_*}.product (pathway.product).

Author(s)

David M Chen

Source

tradSecondaryToPrimary.R

See Also

land, croparea, trade

Examples

## Not run: 
  x <- embodiedLand(gdx, type = "all", landType = "all")
  # Bilateral flows
  xBilat <- embodiedLand(gdx, type = "flows", bilateral = TRUE)

## End(Not run)

embodiedWater

Description

Calculates production-based and consumption-based (embodied) water footprint accounting using bilateral trade flows. Water use is allocated to traded products based on production ratios and bilateral trade patterns.

Usage

embodiedWater(
  gdx,
  file = NULL,
  level = "reg",
  type = "all",
  waterType = "consumption",
  bilateral = FALSE,
  disaggLivestock = FALSE
)

Arguments

gdx

GDX file
file

a file name the output should be written to using write.magpie
level

Level of regional aggregation; "reg" (regional), "glo" (global), "regglo" (regional and global) or any other aggregation level defined in superAggregate. Only used when bilateral=FALSE.
type

Type of accounting: "production" (production-based), "consumption" (consumption-based), "trade" (export, import, and net-trade), "all" (all five), or "flows" (bilateral flows, requires bilateral=TRUE)
waterType

Type of water to report: "withdrawal" (water withdrawal), "consumption" (consumptive water use)
bilateral

Logical; if TRUE, returns bilateral flows with dimensions (exporter.importer, year, product) instead of regional totals (default FALSE)
disaggLivestock

Logical; if TRUE, the feed pathway retains the livestock product dimension, so water is attributed per animal product × feed crop combination. Passes disaggLivestock to tradedPrimariesBilateral. Use dimSums(x[kli_items], dim=3.1) to collapse to feed crops, or dimSums(x[kli_items], dim=3.2) to collapse to animal products. Default is FALSE (current behaviour: feed attributed to crops).

Value

Embodied water use as MAgPIE object (unit depends on waterType). When bilateral=FALSE: dimensions are (region, year, accounting.product). When bilateral=TRUE: dimensions are (exporter.importer, year, pathway.product). When disaggLivestock=TRUE: feed items have dimensions kli_product.kve instead of feed.kve; prim/secd items and all aggregated accounting outputs are unchanged.

Author(s)

David M Chen

See Also

water_usage, trade

Examples

## Not run: 
  x <- embodiedWater(gdx, type = "all", waterType = "consumption")
  # Bilateral flows
  xBilat <- embodiedWater(gdx, type = "flows", bilateral = TRUE)

## End(Not run)

emisCO2

Description

reads detailed CO2 emissions out of a MAgPIE gdx file

Usage

emisCO2(
  gdx,
  file = NULL,
  level = "cell",
  unit = "gas",
  sum_cpool = TRUE,
  sum_land = TRUE
)

Arguments

gdx

GDX file
file

a file name the output should be written to using write.magpie
level

Level of regional aggregation; "reg" (regional), "glo" (global), "regglo" (regional and global) or any other aggregation level defined in superAggregateX
unit

"element" or "gas"; "element": co2_c in Mt C/yr "gas": co2_c Mt CO2/yr
sum_cpool

aggregate carbon pools (TRUE), below ground (soilc) and above ground (vegc and litc) will be reported, if FALSE
sum_land

TRUE (default) or FALSE. Sum over land types (TRUE) or report land-type specific emissions (FALSE).

Value

CO2 emissions as MAgPIE object (unit depends on unit)

Author(s)

Florian Humpenoeder, Michael Crawford

Examples

## Not run: 
x <- emisCO2(gdx)

## End(Not run)

Emissions

Description

reads GHG emissions out of a MAgPIE gdx file

Usage

Emissions(
  gdx,
  file = NULL,
  level = "reg",
  type = "co2_c",
  unit = "element",
  subcategories = TRUE,
  cumulative = FALSE,
  lowpass = NULL,
  inorg_fert_split = TRUE
)

Arguments

gdx

GDX file
file

a file name the output should be written to using write.magpie
level

Level of regional aggregation; "reg" (regional), "glo" (global), "regglo" (regional and global) or any other aggregation level defined in superAggregate
type

emission type(s): "co2_c", "n2o_n" or "ch4"
unit

"element", "gas", "GWP100AR5", "GWP100AR6", "GWP*AR5", or "GWP*AR6" "element": co2_c in Mt C/yr, n2o_n in Mt N/yr, ch4 in Mt CH4/yr "gas": co2_c in Mt CO2/yr, n2o_n in Mt NO2/yr, ch4 in Mt CH4/yr "GWP": co2_c in Mt CO2/yr, n2o_n in Mt CO2eq/yr, ch4 in Mt CO2eq/yr
subcategories

FALSE (default) or TRUE
cumulative

Logical; Determines if emissions are reported annually (FALSE) or cumulative (TRUE). The starting point for cumulative emissions is y1995.
lowpass

number of lowpass filter iterations
inorg_fert_split

if TRUE then inorganic fertilizer emissions are further disaggregated into pasture- and cropland-related emissions. Both the aggregated ("inorg_fert") and disaggregated values ("inorg_fert_crop", "inorg_fert_past)" are reported

Value

emissions as MAgPIE object (unit depends on unit)

Author(s)

Florian Humpenoeder, Benjamin Leon Bodirsky

Examples

## Not run: 
    x <- Emissions(gdx)
  
## End(Not run)

EmissionsBeforeTechnicalMitigation

Description

reads GHG emissions before technical abatement out of a MAgPIE gdx file. Technical abatement includes all abatement done in the MACC curves, but exclude endogenous mitigation. These emissions are NOT the standard reporting emissions, but used for special purposes like remind-magpie coupling.

Usage

EmissionsBeforeTechnicalMitigation(
  gdx,
  file = NULL,
  level = "reg",
  type = "co2_c",
  unit = "element",
  subcategories = FALSE
)

Arguments

gdx

GDX file
file

a file name the output should be written to using write.magpie
level

Level of regional aggregation; "reg" (regional), "glo" (global), "regglo" (regional and global) or any other aggregation level defined in superAggregate
type

emission type(s): "co2_c", "n2o_n" or "ch4" and in the case of unit="gas" "co2" and "n2o"
unit

"element", "gas" or "co2eq"; "element": co2_c in Mt C/yr, n2o_n in Mt N/yr, ch4 in Mt CH4/yr; "gas": co2_c Mt CO2/yr, n2o_n in Mt NO2/yr, ch4 in Mt CH4/yr; "co2eq": co2_c in Mt CO2/yr, n2o_n in Mt CO2eq/yr, ch4 in Mt CO2eq/yr
subcategories

FALSE (default) or TRUE

Value

emissions as MAgPIE object (unit depends on unit)

Author(s)

Florian Humpenoeder; Benjamin Leon Bodirsky

Examples

## Not run: 
    x <- EmissionsBeforeTechnicalMitigation(gdx)
  
## End(Not run)

emisSOC

Description

Reads detailed CO2 soil emissions out of a MAgPIE gdx file using Shapley-style decomposition with interaction terms

Usage

emisSOC(gdx, file = NULL, sumLand = FALSE)

Arguments

gdx

GDX file
file

a file name the output should be written to using write.magpie
sumLand

TRUE (default) or FALSE. Sum over land types (TRUE) or report land-type specific emissions (FALSE).

Details

This function uses a structural decomposition approach (Shapley decomposition) to attribute soil carbon emissions to different drivers and their interactions. The framework is based on counterfactual analysis where all possible combinations of driver states are evaluated following the inclusion-exclusion principle.

For four drivers, the total emission is decomposed as:

totEmissions = main_effects + first_order_interactions + second_order_interactions + third_order_interactions + residual

This creates 16 counterfactual scenarios (2^4) to isolate individual and combined effects. Main effects capture changes when one driver varies while others stay constant. Interaction terms capture synergies where driver combinations amplify or dampen effects beyond simple addition.

Drivers included: - Climate (C): Changes in reference soil carbon density - Land-use (LU): Transitions between land types - Management (M): Changes in crop type shares, fallow, and treecover * Can be split into treecover vs other management in attribution - Soil Carbon Management (SCM): Enhanced soil carbon practices

Legacy effects are incorporated using exponential decay (85 over 100 years. Interaction terms are proportionally attributed back to main drivers in the final output.

Value

CO2 emissions as MAgPIE object

Author(s)

Kristine Karstens

Examples

## Not run: 
x <- emisSOC(gdx)

## End(Not run)

expectVariablesPresent

Description

Checks whether a set of expected variable names is present in a MAgPIE report object. Variable names are normalized in that summation symbols are removed.

Usage

expectVariablesPresent(report, variableNames)

Arguments

report

A MAgPIE object containing the report to check.
variableNames

A character vector of variable names that are expected to be present in report.

Value

NULL invisibly. Issues a warning if expected variables are not present.

Author(s)

Patrick Rein

See Also

Other Infrastructure: metadata_comments(), out(), tryList(), tryReport()

expenditureIndexFood

Description

calculates food expenditure index (baseyear = 100) corrected for ghg emission costs based on a MAgPIE gdx file

Usage

expenditureIndexFood(
  gdx,
  file = NULL,
  level = "reg",
  products = "kfo",
  basketyear = "y2010",
  baseyear = "y2010",
  round = TRUE,
  ghgtax = TRUE,
  valueAdded = FALSE
)

Arguments

gdx

GDX file
file

File the output should be written to using write.magpie
level

Level of regional aggregation; "reg" (regional), "glo" (global), "regglo" (regional and global) or any other aggregation level defined in mapping
products

Selection of products (either by naming products, e.g. "tece", or naming a set, e.g."kcr")
basketyear

Year of reference food basket (should be in the past for comparison of different runs to have identical and comparable food basket)
baseyear

Baseyear of the price index
round

Rounded result (TRUE or FALSE)
ghgtax

Correction of food price expenditure for ghg emission costs (TRUE or FALSE)
valueAdded

whether to include value added

Value

A MAgPIE object containing food price expenditure index, in 2017Int$PPP

Author(s)

Felicitas Beier, David Chen

Examples

## Not run: 
x <- expenditureIndexFood(gdx)

## End(Not run)

factorCosts

Description

reads factor costs for crops, livestock, residues or pasture entering the objective function from a MAgPIE gdx file. Depending on the product and the MAgPIE version (and factor cost realization), factor costs are either already split into labor and capital, will be split in this function, or are kept as the aggregate

Usage

factorCosts(gdx, products = "kli", file = NULL, level = "regglo")

Arguments

gdx

GDX file
products

products for which factor costs should be reported ("kcr", "kli", "kres", "fish", or "pasture")
file

a file name the output should be written to using write.magpie
level

Level of regional aggregation ("reg", "glo", "regglo")

Value

MAgPIE object containing factor costs [million US$17]

Author(s)

Debbora Leip

Examples

## Not run: 
x <- factorCosts(gdx)

## End(Not run)

factorCostShares

Description

returns labor and capital cost share out of factor costs (i.e. labor + capital)

Usage

factorCostShares(
  gdx,
  type = "optimization",
  products = "kcr",
  level = "reg",
  file = NULL
)

Arguments

gdx

GDX file
type

  • "requirements": shares from factor requirements

  • "optimization": cost shares between labor and capital costs in optimization

  • "accounting": cost shares based on accounting of labor and capital costs

products

products for which cost shares should be reported, kcr or kli
level

spatial aggregation to report employment ("reg", "glo" or "regglo")
file

a file name the output should be written to using write.magpie

Value

labor and capital cost share out of factor costs

Author(s)

Debbora Leip

Examples

## Not run: 
x <- factorCostShares(gdx)

## End(Not run)

fallow

Description

calculates fallow land (Mha) from a MAgPIE gdx file

Usage

fallow(gdx, level = "reg", debug = FALSE)

Arguments

gdx

GDX file
level

aggregation level, reg, glo or regglo, cell or grid
debug

debug mode TRUE makes some consistency checks between estimates for different resolutions

Author(s)

Benjamin Leon Bodirsky

Examples

## Not run: 
x <- fallow(gdx)

## End(Not run)

feed

Description

calculates feed demand by animal type out of a gdx file

Usage

feed(
  gdx,
  file = NULL,
  level = "reg",
  detail = TRUE,
  nutrient = "dm",
  balanceflow = TRUE
)

Arguments

gdx

GDX file
file

a file name the output should be written to using write.magpie
level

Level of regional aggregation; "reg" (regional), "glo" (global), "regglo" (regional and global) or any other aggregation level defined in superAggregate
detail

if FALSE, only total feed demand per animal type is calculated without details on the type of feed
nutrient

The nutrient in which the results shall be calculated
balanceflow

If true, feed includes the calibration balanceflow

Value

feed demand by animal type as MAgPIE object (unit depends on selected nutrient attributes)

Author(s)

Isabelle Weindl

Examples

## Not run: 
    x <- feed(gdx)
  
## End(Not run)

FoodDemandModuleConsumerPrices

Description

Calculates food prices that enter demand module

Usage

FoodDemandModuleConsumerPrices(gdx, level = "iso", valueAdded = FALSE)

Arguments

gdx

GDX file
level

reg or iso
valueAdded

whether to add the value-added marketing margin to the total expenditures

Value

magpie object

Author(s)

Benjamin Leon Bodirsky

Examples

## Not run: 
    x <- FoodDemandModuleConsumerPrices(gdx)
  
## End(Not run)

FoodExpenditure

Description

Calculates the food expenditure in USD per year

Usage

FoodExpenditure(
  gdx,
  level = "reg",
  after_shock = TRUE,
  products = "kfo",
  product_aggr = TRUE,
  per_capita = TRUE,
  valueAdded = FALSE
)

Arguments

gdx

GDX file
level

spatial aggregation. can be "iso","reg","regglo","glo"
after_shock

FALSE is using the exogenous real income and the prices before a shock, TRUE is using the endogeenous real income that takes into account food price change on real income, "after_price_before_demand" takes into account price changes on real income, but assumes no demand adjustment
products

selected products or sets of products
product_aggr

if true, aggregation over products
per_capita

per capita or total population
valueAdded

whether to add the value-added marketing margin to the total expenditures

Value

magpie object with per capita consumption

Author(s)

Benjamin Leon Bodirsky

Examples

## Not run: 
    x <- FoodExpenditure(gdx)
  
## End(Not run)

FoodExpenditureShare

Description

Calculates the livestock share from the food demand model

Usage

FoodExpenditureShare(
  gdx,
  level = "reg",
  after_shock = TRUE,
  products = "kfo",
  product_aggr = TRUE,
  valueAdded = FALSE
)

Arguments

gdx

GDX file
level

spatial aggregation. can be "iso","reg","regglo","glo"
after_shock

FALSE is using the exogenous real income and the prices before a shock, TRUE is using the endogeenous real income that takes into account food price change on real income
products

selected products or sets of products
product_aggr

if true, aggregation over products
valueAdded

TRUE to include post farmgate value added in the expenditure share

Value

magpie object with per capita consumption

Author(s)

Benjamin Leon Bodirsky

Examples

## Not run: 
    x <- FoodExpenditureShare(gdx)
  
## End(Not run)

foodmodelstat

Description

MAgPIE food model statistics with information about convergence and number of iterations

Usage

foodmodelstat(gdx, file = NULL)

Arguments

gdx

GDX file
file

a file name the output should be written to using write.magpie

Value

A MAgPIE object containing number of iterations and convergence information for each time step

Author(s)

Jan Philipp Dietrich

Examples

## Not run: 
x <- foodmodelstat(gdx)

## End(Not run)

ForestYield

Description

Calculates the average growing stock density of harvested forest areas (m3/ha). This is the ratio of timber production volume to harvested area, i.e. the average standing volume removed per hectare harvested. Values are comparable to growing stock (typically 100-300 m3/ha) and should NOT be confused with forestry yield in the MAI sense (5-20 m3/ha/yr).

Usage

ForestYield(gdx, file = NULL, level = "cell")

Arguments

gdx

GDX file
file

a file name the output should be written to using write.magpie
level

Level of regional aggregation; "cell", "reg" (regional), "glo" (global), "regglo" (regional and global) or any secdforest aggregation level defined in superAggregate

Details

Average growing stock of harvested areas = timber production (m3) / harvested area (ha). Differences to overall growing stock arise from selective harvesting of specific age classes.

Value

Average growing stock density of harvested areas in m3/ha

Author(s)

Abhijeet Mishra, Florian Humpenoeder

Examples

## Not run: 
    x <- ForestYield(gdx)
  
## End(Not run)

gdxAggregate

Description

aggregates and disaggregates on spatial scales using mappings from the gdx files.

Usage

gdxAggregate(gdx, x, weight = NULL, to, absolute = TRUE, ...)

Arguments

gdx

gdx file
x

object to be aggrgeagted or disaggregated
weight

weight can be either an object or a functionname in "", where the function provides the weight
to

either a fixed target aggregation level (grid, cell, iso, reg, glo, regglo) or the name of a mapping based on regions
absolute

is it a absolute or a relative value (absolute: tons, relative: tons per hectare)
...

further parameters handed on to weight function.

Value

List of magpie objects with results on country level, weight on country level, unit and description.

Author(s)

Benjamin Leon Bodirsky, Edna J. Molina Bacca, Florian Humpenoeder

See Also

Other Spatial: addGeometry(), clusterOutputToTerraVector(), mappingToLongFormat(), superAggregateX()

Examples

## Not run: 
gdp_pc <- income(gdx, level = "reg")
is.function(population)
gdp_pc_iso <- gdxAggregate(gdx = gdx, x = gdp_pc, weight = "population", to = "iso",
                           absolute = FALSE)
gdp_pc_glo <- gdxAggregate(gdx = gdx, x = gdp_pc, weight = "population", to = "glo",
                           absolute = FALSE)
gdp <- income(gdx, level = "reg", per_capita = FALSE)
gdp_iso <- gdxAggregate(gdx = gdx, x = gdp, weight = "population", to = "iso", absolute = TRUE)
gdp_glo <- gdxAggregate(gdx = gdx, x = gdp, weight = "population", to = "glo", absolute = TRUE)

## End(Not run)

getReport

Description

Puts together a report based on a MAgPIE gdx file

Usage

getReport(
  gdx,
  file = NULL,
  scenario = NULL,
  filter = c(1, 2, 7),
  detail = TRUE,
  level = "regglo",
  ...
)

Arguments

gdx

GDX file
file

a file name the output should be written to using write.report. If NULL the report is returned instead as a MAgPIE object.
scenario

Name of the scenario used for the list-structure of a reporting object (x$scenario$MAgPIE). If NULL the report is returned instead as a MAgPIE object.
filter

Modelstat filter. Here you have to set the modelstat values for which results should be used. All values for time steps in which the modelstat is different or for which one of the previous modelstats were different are set to NA.
detail

Crop specific (TRUE) or aggregated outputs (FALSE)
level

An aggregation level (currently "regglo" or "iso") or the name of a mapping that should be used by default to aggregate the report. The mapping can only map from reg to other regions. Not all parts of the report will necessarily adhere to this default aggregation level.
...

additional arguments for write.report. Will only be taken into account if argument "file" is not NULL.

Details

Reports are organize with '|' as level delimiter and summation symbols for grouping subcategories into entities e.g. for stackplots. Notice the following hints for the summation symbol placement:

  • Every name should just contain one summation symbol (mostly '+').

  • The position of the symbol (counted in '|' from left side) will determine the level.

  • Every subitem containing the same summation symbol in the same level with the same supercategory name will be summed.

  • Items without any summation symbol will ge ignored.

  • Items with different summation symbols will be summed up separately.

  • In most of the cases a summation symbol will be just placed before the last level (counted in '|' from left side).

  • It is helpful to think about which group of items should be stacked in a stackplot.

An example how a summation symbol placement could look like: 

  Toplevel
  Toplevel|+|Item 1
  Toplevel|+|Item 2
  Toplevel|Item 2|+|Subitem 1
  Toplevel|Item 2|+|Subitem 1
  Toplevel|++|Item A
  Toplevel|++|Item B
  Toplevel|Item ?

Value

A MAgPIE object containing the report in the case that "file" is NULL.

Author(s)

Florian Humpenoeder

Examples

## Not run: 
x <- getReport(gdx)

## End(Not run)

getReportAgMIP

Description

Puts together a report for the Agricultural Model Intercom- parison and Improvement Project (AgMIP) based on a MAgPIE gdx file

Usage

getReportAgMIP(
  gdx,
  file = NULL,
  scenario = NULL,
  filter = c(1, 2, 7),
  detail = TRUE,
  ...
)

Arguments

gdx

GDX file
file

a file name the output should be written to using write.report. If NULL the report is returned instead as a MAgPIE object.
scenario

Name of the scenario used for the list-structure of a reporting object (x$scenario$MAgPIE). If NULL the report is returned instead as a MAgPIE object.
filter

Modelstat filter. Here you have to set the modelstat values for which results should be used. All values for time steps in which the modelstat is different or for which one of the previous modelstats were different are set to NA.
detail

Crop specific (TRUE) or aggregated outputs (FALSE)
...

additional arguments for write.report. Will only be taken into account if argument "file" is not NULL.

Details

Reports are organize with '|' as level delimiter and summation symbols for grouping subcategories into entities e.g. for stackplots. Notice the following hints for the summation symbol placement:

  • Every name should just contain one summation symbol (mostly '+').

  • The position of the symbol (counted in '|' from left side) will determine the level.

  • Every subitem containing the same summation symbol in the same level with the same supercategory name will be summed.

  • Items without any summation symbol will ge ignored.

  • Items with different summation symbols will be summed up separately.

  • In most of the cases a summation symbol will be just placed before the last level (counted in '|' from left side).

  • It is helpful to think about which group of items should be stacked in a stackplot.

An example how a summation symbol placement could look like: 

  Toplevel
  Toplevel|+|Item 1
  Toplevel|+|Item 2
  Toplevel|Item 2|+|Subitem 1
  Toplevel|Item 2|+|Subitem 1
  Toplevel|++|Item A
  Toplevel|++|Item B
  Toplevel|Item ?

Value

A MAgPIE object containing the report in the case that "file" is NULL.

Author(s)

Florian Humpenoeder, Isabelle Weindl, Felicitas Beier

Examples

## Not run: 
x <- getReportAgMIP(gdx)

## End(Not run)

getReportDemandStandalone

Description

Puts together a report based on a MAgPIE gdx file

Usage

getReportDemandStandalone(
  gdx,
  file = NULL,
  scenario = NULL,
  detail = FALSE,
  ...
)

Arguments

gdx

GDX file
file

a file name the output should be written to using write.report. If NULL the report is returned instead as a MAgPIE object.
scenario

Name of the scenario used for the list-structure of a reporting object (x$scenario$MAgPIE). If NULL the report is returned instead as a MAgPIE object.
detail

Crop specific (TRUE) or aggregated outputs (FALSE)
...

additional arguments for write.report. Will only be taken into account if argument "file" is not NULL.

Value

A MAgPIE object containing the report in the case that "file" is NULL.

Author(s)

Florian Humpenoeder

Examples

## Not run: 
    x <- getReportDemandStandalone(gdx)
  
## End(Not run)

getReportDietaryIndicators

Description

reports dietary indicators on the country level. These are formatted as data.frames describing: 1. population, anthropometrics, and intake 2. caloric intake by food category (without food waste)

Usage

getReportDietaryIndicators(gdx, scenario)

Arguments

gdx

filepath of the GDX file
scenario

character string describing the scenario configuration

Value

list of data.frames for the dietary indicators

Author(s)

Michael Crawford, Felicitas Beier, Benjamin Bodirsky

Examples

## Not run: 
    getReportDietaryIndicators(gdx, scenario)
  
## End(Not run)

getReportFableScenathon

Description

Collects outputs from MAgPIE runs for FABLE Scenathon.

Usage

getReportFableScenathon(gdx, file = NULL, iso = NULL)

Arguments

gdx

a GDX file
file

a file name the output should be written to using write.report. If 'NULL' the report is returned instead as a MAgPIE object. For the easier reporting in Scenathon tabs, a .csv file extension is recommenended.
iso

country/region selection. Default 'NULL', i.e. all 'regglo' reporting

Author(s)

Miodrag Stevanovic

Examples

## Not run: 
    x <- getReportFableScenathon(gdx, file = "magpie2scenathon.csv", iso = "IND")
  
## End(Not run)

getReportFSECAlessandroPassaro

Description

Collects reports for Alessandro Passaro's analysis

Usage

getReportFSECAlessandroPassaro(gdx, reportOutputDir = NULL, scenario = NULL)

Arguments

gdx

gdx file
reportOutputDir

a folder name for the output to be written to. If NULL the report is not saved to disk, and only returned to the calling function.
scenario

the name of the scenario used. If NULL the report is not saved to disk, and only returned to the calling function.

Value

A list of reports

Author(s)

Michael Crawford

Examples

## Not run: 
    x <- getReportFSECAlessandroPassaro()
  
## End(Not run)

getReportFSECCosts

Description

Reports cost indicators for the FSEC project

Usage

getReportFSECCosts(gdx, reportOutputDir = NULL, scenario = NULL)

Arguments

gdx

a GDX file
reportOutputDir

a folder name for the output to be written to. If NULL the report is not saved to disk, and only returned to the calling function.
scenario

the name of the scenario used. If NULL the report is not saved to disk, and only returned to the calling function.

Value

A .csv containing the summed output of reportCostsAccounting on the region level

Author(s)

Michael Crawford

Examples

## Not run: 
    x <- getReportFSECCosts(gdx)
  
## End(Not run)

getReportFSECCropDiversityGrid

Description

Reports grid cell level crop diversity for the FSEC project

Usage

getReportFSECCropDiversityGrid(gdx, reportOutputDir = NULL, scenario = NULL)

Arguments

gdx

a GDX file
reportOutputDir

a folder name for the output to be written to. If NULL the report is not saved to disk, and only returned to the calling function.
scenario

the name of the scenario used. If NULL the report is not saved to disk, and only returned to the calling function.

Value

A list of MAgPIE objects containing the reports

Author(s)

Patrick v. Jeetze

Examples

## Not run: 
x <- getReportFSECCropDiversityGrid(gdx)

## End(Not run)

getReportFSECPollution

Description

Reports nutrient surplus indicators for the FSEC project

Usage

getReportFSECPollution(gdx, reportOutputDir = NULL, scenario = NULL)

Arguments

gdx

GDX file
reportOutputDir

a folder name for the output to be written to. If NULL the report is not saved to disk, and only returned to the calling function.
scenario

the name of the scenario used. If NULL the report is not saved to disk, and only returned to the calling function.

Value

A list of MAgPIE objects containing the reports

Author(s)

Michael Crawford

Examples

## Not run: 
    x <- getReportFSECPollution(gdx)
  
## End(Not run)

getReportFSECSimonDietz

Description

Collects reports for Simon Dietz' social welfare function analysis

Usage

getReportFSECSimonDietz(gdx, reportOutputDir = NULL, scenario = NULL)

Arguments

gdx

GDX file
reportOutputDir

a folder name for the output to be written to. If NULL the report is not saved to disk, and only returned to the calling function.
scenario

the name of the scenario used. If NULL the report is not saved to disk, and only returned to the calling function.

Value

A list of reports

Author(s)

Michael Crawford

Examples

## Not run: 
    x <- getReportFSECSimonDietz()
  
## End(Not run)

getReportFSECStevenLord

Description

Collects reports for Steven Lord's cost of action / cost of inaction analysis.

Usage

getReportFSECStevenLord(gdx, reportOutputDir, scenario)

Arguments

gdx

gdx file
reportOutputDir

a folder name for the output to be written to. If NULL the report is not saved to disk, and only returned to the calling function.
scenario

the name of the scenario used. If NULL the report is not saved to disk, and only returned to the calling function.

Author(s)

Michael Crawford

Examples

## Not run: 
    x <- getReportFSECStevenLord()
  
## End(Not run)

getReportGridINMS

Description

Generates and saves a list of reports relevant to the INMS context

Usage

getReportGridINMS(
  gdx,
  reportOutputDir = NULL,
  scenario = NULL,
  filter = c(2, 7),
  version = "v13"
)

Arguments

gdx

GDX file
reportOutputDir

Directory in which the reports are to be saved. If NULL, a list of reports (MAgPIE objects) is returned instead
scenario

Name of the scenario used for the list-structure of a reporting object (x$scenario$MAgPIE). If NULL a list of reports ( MAgPIE objects) is returned instead.
filter

Modelstat filter. Here you have to set the modelstat values for which results should be used. All values for time steps in which the modelstat is different or for which one of the previous modelstats were different are set to NA.
version

Version number for this analysis

Value

A list of reports (MAgPIE objects)

Author(s)

Benjamin Leon Bodirsky, Florian Humpenoeder, Michael Crawford

Examples

## Not run: 
x <- getReportGridINMS(gdx)

## End(Not run)

getReportGridNitrogenPollution

Description

Reports nutrient surplus indicators as well as exceedance of the critical nitrogen surplus at the grid level

Usage

getReportGridNitrogenPollution(gdx, reportOutputDir = NULL, scenario = NULL)

Arguments

gdx

gdx file
reportOutputDir

a folder name for the output to be written to. If NULL the report is not saved to disk, and only returned to the calling function.
scenario

the name of the scenario used. If NULL the report is not saved to disk, and only returned to the calling function.

Value

A list of MAgPIE objects containing the reports

Author(s)

Michael Crawford

Examples

## Not run: 
    x <- getReportGridNitrogenPollution()
  
## End(Not run)

getReportINMS

Description

Puts together a report for the INMS project based on a MAgPIE gdx file

Usage

getReportINMS(
  gdx,
  file = NULL,
  scenario = NULL,
  filter = c(2, 7),
  detail = TRUE,
  ...
)

Arguments

gdx

GDX file
file

a file name the output should be written to using write.report. If NULL the report is returned instead as a MAgPIE object.
scenario

Name of the scenario used for the list-structure of a reporting object (x$scenario$MAgPIE). If NULL the report is returned instead as a MAgPIE object.
filter

Modelstat filter. Here you have to set the modelstat values for which results should be used. All values for time steps in which the modelstat is different or for which one of the previous modelstats were different are set to NA.
detail

Crop specific (TRUE) or aggregated outputs (FALSE)
...

additional arguments for write.report. Will only be taken into account if argument "file" is not NULL.

Value

A MAgPIE object containing the report in the case that "file" is NULL.

Author(s)

Benjamin Bodirsky, Florian Humpenoeder

Examples

## Not run: 
x <- getReport(gdx)

## End(Not run)

getReportIso

Description

Puts together a report based on a MAgPIE gdx file

Usage

getReportIso(
  gdx,
  file = NULL,
  scenario = NULL,
  filter = c(1, 2, 7),
  detail = FALSE,
  ...
)

Arguments

gdx

GDX file
file

a file name the output should be written to using write.report. If NULL the report is returned instead as a MAgPIE object.
scenario

Name of the scenario used for the list-structure of a reporting object (x$scenario$MAgPIE). If NULL the report is returned instead as a MAgPIE object.
filter

Modelstat filter. Here you have to set the modelstat values for which results should be used. All values for time steps in which the modelstat is different or for which one of the previous modelstats were different are set to NA.
detail

Crop specific (TRUE) or aggregated outputs (FALSE)
...

additional arguments for write.report. Will only be taken into account if argument "file" is not NULL.

Details

Reports are organize with '|' as level delimiter and summation symbols for grouping subcategories into entities e.g. for stackplots. Notice the following hints for the summation symbol placement:

  • Every name should just contain one summation symbol (mostly '+').

  • The position of the symbol (counted in '|' from left side) will determine the level.

  • Every subitem containing the same summation symbol in the same level with the same supercategory name will be summed.

  • Items without any summation symbol will ge ignored.

  • Items with different summation symbols will be summed up separately.

  • In most of the cases a summation symbol will be just placed before the last level (counted in '|' from left side).

  • It is helpful to think about which group of items should be stacked in a stackplot.

An example how a summation symbol placement could look like: 

  Toplevel
  Toplevel|+|Item 1
  Toplevel|+|Item 2
  Toplevel|Item 2|+|Subitem 1
  Toplevel|Item 2|+|Subitem 1
  Toplevel|++|Item A
  Toplevel|++|Item B
  Toplevel|Item ?

Value

A MAgPIE object containing the report in the case that "file" is NULL.

Author(s)

Florian Humpenoeder

Examples

## Not run: 
x <- getReport(gdx)

## End(Not run)

getReportMAgPIE2GAINS

Description

Puts together a report for the IIASA GAINS model based on a MAgPIE gdx file

Usage

getReportMAgPIE2GAINS(
  gdx,
  folder = NULL,
  scenario = NULL,
  filter = c(2, 7),
  ...
)

Arguments

gdx

GDX file
folder

a folder name the output should be written to using write.report. If NULL the report is returned instead as a MAgPIE object.
scenario

Name of the scenario used for the list-structure of a reporting object (x$scenario$MAgPIE). If NULL the report is returned instead as a MAgPIE object.
filter

Modelstat filter. Here you have to set the modelstat values for which results should be used. All values for time steps in which the modelstat is different or for which one of the previous modelstats were different are set to NA.
...

additional arguments for write.report. Will only be taken into account if argument "file" is not NULL.

Value

A MAgPIE object containing the report in the case that "file" is NULL.

Author(s)

Benjamin Leon Bodirsky, Florian Humpenoeder

getReportMAgPIE2LPJmL

Description

Puts together a report for LPJmL or other biophysical models based on a MAgPIE gdx file

Usage

getReportMAgPIE2LPJmL(
  gdx,
  folder = NULL,
  scenario = NULL,
  filter = c(2, 7),
  ...
)

Arguments

gdx

GDX file
folder

a folder name the output should be written to using write.report. If NULL the report is returned instead as a MAgPIE object.
scenario

Name of the scenario used for the list-structure of a reporting object (x$scenario$MAgPIE). If NULL the report is returned instead as a MAgPIE object.
filter

Modelstat filter. Here you have to set the modelstat values for which results should be used. All values for time steps in which the modelstat is different or for which one of the previous modelstats were different are set to NA.
...

additional arguments for write.report. Will only be taken into account if argument "file" is not NULL.

Value

A MAgPIE object containing the report in the case that "file" is NULL.

Author(s)

Benjamin Leon Bodirsky, Florian Humpenoeder

Examples

## Not run: 
x <- getReportMAgPIE2LPJmL(gdx)

## End(Not run)

getReportMAgPIE2REMIND

Description

Based on a MAgPIE gdx file, a report is generated containing only the variables relevant for the coupling with REMIND. Basically a copy of getReport, but calling less 'reportXY()' functions.

Usage

getReportMAgPIE2REMIND(gdx, file = NULL, scenario = NULL)

Arguments

gdx

GDX file
file

A file name the output should be written to using write.report. If NULL the report is returned instead as a MAgPIE object.
scenario

Name of the scenario used for the list-structure of a reporting object (x$scenario$MAgPIE). If NULL the report is returned instead as a MAgPIE object.

Details

Reports are organized with '|' as level delimiter and summation symbols for grouping subcategories into entities e.g. for stackplots. Notice the following hints for the summation symbol placement:

  • Every name should just contain one summation symbol (mostly '+').

  • The position of the symbol (counted in '|' from left side) will determine the level.

  • Every subitem containing the same summation symbol in the same level with the same supercategory name will be summed.

  • Items without any summation symbol will be silently ignored.

  • Items with different summation symbols will be summed up separately.

  • In most of the cases a summation symbol will be just placed before the last level (counted in '|' from left side).

  • It is helpful to think about which group of items should be stacked in a stackplot.

An example how a summation symbol placement could look like: 

  Toplevel
  Toplevel|+|Item 1
  Toplevel|+|Item 2
  Toplevel|Item 2|+|Subitem 1
  Toplevel|Item 2|+|Subitem 1
  Toplevel|++|Item A
  Toplevel|++|Item B
  Toplevel|Item ?

Value

A MAgPIE object containing the report.

Author(s)

Florian Humpenoeder, David Klein

Examples

## Not run: 
x <- getReportMAgPIE2REMIND(gdx)

## End(Not run)

getReportPBindicators

Description

Puts together all reporting variables for planetary boundary indicators of MAgPIE

Usage

getReportPBindicators(
  gdx,
  file = NULL,
  scenario = NULL,
  filter = c(1, 2, 7),
  ...
)

Arguments

gdx

GDX file
file

a file name the output should be written to using write.report. If NULL the report is returned instead as a MAgPIE object.
scenario

Name of the scenario used for the list-structure of a reporting object (x$scenario$MAgPIE). If NULL the report is returned instead as a MAgPIE object.
filter

Modelstat filter. Here you have to set the modelstat values for which results should be used. All values for time steps in which the modelstat is different or for which one of the previous modelstats were different are set to NA.
...

additional arguments for write.report. Will only be taken into account if argument "file" is not NULL.

Details

Reports are organize with '|' as level delimiter and summation symbols for grouping subcategories into entities e.g. for stackplots. Notice the following hints for the summation symbol placement:

  • Every name should just contain one summation symbol (mostly '+').

  • The position of the symbol (counted in '|' from left side) will determine the level.

  • Every subitem containing the same summation symbol in the same level with the same supercategory name will be summed.

  • Items without any summation symbol will ge ignored.

  • Items with different summation symbols will be summed up separately.

  • In most of the cases a summation symbol will be just placed before the last level (counted in '|' from left side).

  • It is helpful to think about which group of items should be stacked in a stackplot.

An example how a summation symbol placement could look like: 

  Toplevel
  Toplevel|+|Item 1
  Toplevel|+|Item 2
  Toplevel|Item 2|+|Subitem 1
  Toplevel|Item 2|+|Subitem 1
  Toplevel|++|Item A
  Toplevel|++|Item B
  Toplevel|Item ?

Value

A MAgPIE object containing the report in the case that "file" is NULL.

Author(s)

Felicitas Beier

Examples

## Not run: 
x <- getReport(gdx)

## End(Not run)

GrowingStock

Description

reads woody growing stock out of a MAgPIE gdx file

Usage

GrowingStock(gdx, file = NULL, level = "regglo", indicator = "relative")

Arguments

gdx

GDX file
file

a file name the output should be written to using write.magpie
level

Level of regional aggregation; "cell", "reg" (regional), "glo" (global), "regglo" (regional and global) or any secdforest aggregation level defined in superAggregate
indicator

If the reported numbers are relative (mio m3/ha) or absolute (mio. m3). Default is relative.

Details

Growing stock for producing woody materials consist of growing stock from plantations (forestry), secondary and primary forest as well as other land (natveg)

Value

Growing stock in m3 per ha

Author(s)

Abhijeet Mishra

Examples

## Not run: 
x <- GrowingStock(gdx)

## End(Not run)

harvested_area_timber

Description

Reads wood harvest area separated by source (primforest, secdforest, forestry, other) and age classes from a gdx. The data is on cluster level and the unit is Mha per year.

Usage

harvested_area_timber(
  gdx,
  file = NULL,
  level = "cell",
  aggregateAgeClasses = TRUE,
  annualized = TRUE
)

Arguments

gdx

A fulldata.gdx of a magpie run, usually with endogenous forestry enabled
file

a file name the output should be written to using write.magpie
level

Level of regional aggregation; "cell", "reg" (regional), "glo" (global), "regglo" (regional and global) or any secdforest aggregation level defined in superAggregate
aggregateAgeClasses

If TRUE, age classes are aggregated
annualized

If TRUE, Mha per year. If FALSE, Mha per time step

Value

Area harvested for wood in Mha per year (annualized = TRUE) or Mha per time step (annualized = FALSE) as a magpie object

Author(s)

Abhijeet Mishra, Pascal Sauer, Florian Humpenoeder

hourlyLaborCosts

Description

returns hourly labor costs in agriculture from MAgPIE results

Usage

hourlyLaborCosts(gdx, level = "reg", file = NULL)

Arguments

gdx

GDX file
level

spatial aggregation to report employment ("iso", "reg", "glo", or "regglo")
file

a file name the output should be written to using write.magpie

Value

hourly labor costs in agriculture

Author(s)

Debbora Leip

Examples

## Not run: 
x <- hourlyLaborCosts(gdx)

## End(Not run)

Hunger

Description

Calculates the share of people living in hunger.

Usage

Hunger(
  gdx,
  level = "reg",
  after_shock = TRUE,
  calibrated = FALSE,
  share = TRUE
)

Arguments

gdx

GDX file
level

spatial aggregation. can be "iso","reg","regglo","glo"
after_shock

FALSE is using the exogenous real income and the prices before a shock, TRUE is using the endogeenous real income that takes into account food price change on real income
calibrated

if calibrated is TRUE, kcal values are calibrated to better match historical years
share

share of population that is undernourished

Value

magpie object with hunger (mio people) or hunger share

Author(s)

Benjamin Leon Bodirsky

Examples

## Not run: 
    x <- Hunger(gdx)
  
## End(Not run)

income

Description

Calculates income based on a MAgPIE gdx file

Usage

income(
  gdx,
  file = NULL,
  level = "reg",
  per_capita = TRUE,
  type = "ppp",
  after_shock = FALSE
)

Arguments

gdx

GDX file
file

a file name the output should be written to using write.magpie
level

level of regional aggregation; "reg" (regional), "glo" (global), "regglo" (regional and global) or any other aggregation level defined in superAggregate
per_capita

income per capita or aggregated for the total population
type

ppp for purchase power parity, mer for market exchange rate
after_shock

FALSE is using the exogenous real income, TRUE is using the endogeenous real income that takes into account food price change on real income

Value

annual income as MAgPIE object (unit depends on per_capita: US$2017 MER/cap/yr (TRUE), US$2017 MER/yr (FALSE))

Author(s)

Florian Humpenoeder, Benjamin Bodirsky, Felicitas Beier

Examples

## Not run: 
x <- income(gdx)

## End(Not run)

Intake

Description

Calculates the per-capita kcal intake from the food demand model

Usage

Intake(
  gdx,
  file = NULL,
  level = "reg",
  calibrated = TRUE,
  pregnancy = FALSE,
  per_capita = TRUE,
  age = FALSE,
  sex = FALSE,
  bmi_groups = FALSE
)

Arguments

gdx

GDX file
file

a file name the output should be written to using write.magpie
level

Level of regional aggregation; "iso" ISO country codes, "reg" (regional), "glo" (global)
calibrated

if FALSE, the true regression outputs are used, if TRUE the values calibrated to the start years are used
pregnancy

if TRUE, adding the intake requirements for lactation and pregnancy
per_capita

per capita or aggregated for the population
age

if FALSE age and sex is aggregated
sex

if TRUE, data is provided by sex
bmi_groups

if TRUE data is proided by BMI group

Details

Demand definitions are equivalent to FAO Food supply categories

Value

calories as MAgPIE object (unit depends on per_capita: kcal/cap/day (TRUE), kcal/day (FALSE))

Author(s)

Benjamin Leon Bodirsky

Examples

## Not run: 
    x <- Intake(gdx)
  
## End(Not run)

IntakeDetailed

Description

Calculates detailed or aggregated per-capita kcal intake including exogenous scenarios

Usage

IntakeDetailed(gdx, file = NULL, level = "reg", product_aggr = FALSE)

Arguments

gdx

GDX file
file

a file name the output should be written to using write.magpie
level

Level of regional aggregation; "reg" (regional), "glo" (global), "regglo" (regional and global) or any other aggregation level defined in superAggregate
product_aggr

aggregate over products or not (boolean)

Details

Calculation of kcal food intake is possible for both exogenous diet scenarios and endogenous estimation from food demand model

Value

Calories as MAgPIE object (unit: kcal/cap/day)

Author(s)

Isabelle Weindl

Examples

## Not run: 
    x <- IntakeDetailed(gdx)
  
## End(Not run)

IntakeDetailedProtein

Description

Calculates food-specific per-capita protein intake from magpie results in grams.

Usage

IntakeDetailedProtein(gdx, file = NULL, level = "reg", product_aggr = FALSE)

Arguments

gdx

GDX file
file

a file name the output should be written to using write.magpie
level

Level of regional aggregation; "reg" (regional), "glo" (global), "regglo" (regional and global) or any other aggregation level defined in superAggregate
product_aggr

aggregate over products or not (boolean)

Value

Protein intake as MAgPIE object (unit: grams/cap/day)

Author(s)

Vartika Singh, Isabelle Weindl

Examples

## Not run: 
    x <- IntakeDetailedProtein(gdx)
  
## End(Not run)

kayaFractions

Description

Calculates the elements t, d1, d2/d1, ..., dn/dn-1, t/dn in a kaya-like identity of the form t = d1 * d2/d1 * ... * dn/dn-1 * t/dn, based on the variables t, d1, d2, ..., dn.

Usage

kayaFractions(data, driverNames = NULL, fixTimeSteps = FALSE)

Arguments

data

MAgPIE object with target variable and variables to calculate drivers. Needs to have the target variable as first column in the data dimension, and the variables to calculate the drivers in the following columns. I.e. getItems(data, dim = 3) should return c(t, d1, d2, ..., dn). If decomposition is to be calculated for multiple scenarios, the data object can have a scenario dimension in 3.2.
driverNames

Names of the drivers in the data object. If NULL, names of the drivers are set based on the names of the variables d1, d2, ..., dn in the data object (i.e. "d2/d1", "d3/d2", ..., "t/dn"). Name of the target variable is always kept as provided in the data object. Default is NULL.
fixTimeSteps

Logical. For a consistent decomposition, the time steps in the data object need to be of equal length. If fixTimeSteps is TRUE, the function will check if the time steps are of equal length and if not, will interpolate the data linearly to have equal time steps. If fixTimeSteps is FALSE, the function will only throw a warning if the time steps are not of equal length. Default is TRUE.

Value

The function returns a magpie object containing the target variable t and the drivers of the target variable

Author(s)

Debbora Leip

See Also

kayaLaspeyres

Examples

## Not run: 
data <- new.magpie(cells_and_regions = c("EUR", "SSA", "USA", "LAM", "IND", "OAS"),
                   years = c(2000, 2005, 2010),
                   names = as.vector(outer(c("Area", "Population", "Supply"),
                                           c("SSP1", "SSP2"), paste, sep = ".")),
                   sets = c("Region", "Year", "Variable", "Scenario"), fill = runif(108))
kayaFractions(data)

## End(Not run)

kayaLaspeyres

Description

Calculates the Laspeyres decomposition of a changes in a target variable t into drivers based on a kaya-like identity. The kaya-like identity needs to be of the form t = d1 * d2/d1 * d3/d2 * ... * dn/dn-1 * t/dn, where d1, d2/d1, ..., dn/dn-1, t/dn are the drivers of change in the target variable t. The Laspeyres decomposition calculates an additive decomposition of the change over time in the target variable based on the changes in the drivers (for formula of the laspeyres decomposition see comment in .laspeyresDriver). The function returns the change in the target variable and the decomposition of the change into the drivers.

Usage

kayaLaspeyres(data, driverNames = NULL, type = "relative", fixTimeSteps = TRUE)

Arguments

data

MAgPIE object with target variable and variables to calculate drivers. Needs to have the target variable as first column in the data dimension, and the variables to calculate the drivers in the following columns. I.e. getItems(data, dim = 3) should return c(t, d1, d2, ..., dn). If decomposition is to be calculated for multiple scenarios, the data object can have a scenario dimension in 3.2.
driverNames

Names of the drivers in the data object. If NULL, names of the drivers are set based on the names of the variables d1, d2, ..., dn in the data object (i.e. "d2/d1", "d3/d2", ..., "t/dn"). Name of the target variable is always kept as provided in the data object. Default is NULL.
type

Type of the output. "relative" returns the relative change in the target variable from each time step to the next and its decomposition by drivers, "absolute" returns the absolute change over time and its decomposition. Default is "absolute".
fixTimeSteps

Logical. For a consistent decomposition, the time steps in the data object need to be of equal length. If fixTimeSteps is TRUE, the function will check if the time steps are of equal length and if not, will interpolate the data linearily to have equal time steps. If fixTimeSteps is FALSE, the function will only throw a warning if the time steps are not of equal length. Default is TRUE.

Value

The function returns the change in the target variable and the decomposition of the change into the drivers either in percentage points or absolute values (unit of target variable).

Author(s)

Debbora Leip

See Also

kayaFractions

Examples

## Not run: 
data <- new.magpie(cells_and_regions = c("EUR", "SSA", "USA", "LAM", "IND", "OAS"),
                   years = c(2000, 2005, 2010),
                   names = as.vector(outer(c("Area", "Population", "Supply"),
                                           c("SSP1", "SSP2"), paste, sep = ".")),
                   sets = c("Region", "Year", "Variable", "Scenario"), fill = runif(108))
kayaLaspeyres(data)

## End(Not run)

Kcal

Description

Calculates the per-capita kcal consumption from the food demand model

Usage

Kcal(
  gdx,
  file = NULL,
  level = "reg",
  products = "kfo",
  product_aggr = TRUE,
  after_shock = TRUE,
  calibrated = TRUE,
  magpie_input = FALSE,
  attributes = "kcal",
  per_capita = TRUE
)

Arguments

gdx

GDX file
file

a file name the output should be written to using write.magpie
level

Level of regional aggregation; "iso" ISO country codes, "reg" (regional), "glo" (global)
products

Selection of products (either by naming products, e.g. "tece", or naming a set,e.g."kcr")
product_aggr

aggregate over products or not (boolean)
after_shock

FALSE is using the exogenous real income and the prices before a shock, TRUE is using the endogenous real income that takes into account food price change on real income
calibrated

if FALSE, the true regression outputs are used, if TRUE the values calibrated to the start years are used
magpie_input

TRUE or FALSE. This setting is only activate if arguments "calibrated" and "after_shock" are set to TRUE and else ignored. If set as TRUE, the per-capita kcal consumption values finally entering MAgPIE as input are used, which drive the behaviour of the MAgPIE model, excluding countries not listed in FAO. If set as FALSE, the per-capita kcal consumption values as calculated in the food demand model are used, including countries not listed in FAO.
attributes

unit: kilocalories per day ("kcal"), g protein per day ("protein"). Mt reactive nitrogen ("nr").
per_capita

per capita or aggregated for the population

Details

Demand definitions are equivalent to FAO Food supply categories

Value

calories as MAgPIE object (unit depends on per_capita: kcal/cap/day (TRUE), kcal/day (FALSE))

Author(s)

Benjamin Leon Bodirsky, Isabelle Weindl

Examples

## Not run: 
    x <- Kcal(gdx)
  
## End(Not run)

laborCostsEndo

Description

reads MAgPIE endogenous labor costs for crop and livestock production from gdx file

Usage

laborCostsEndo(gdx, products = "kcr", file = NULL, level = "grid")

Arguments

gdx

GDX file
products

products for which labor costs should be reported ("kcr" or "kli", for other products use factorCosts())
file

a file name the output should be written to using write.magpie
level

Level of regional aggregation ("grid" or "iso", for regional/global use factorCosts())

Value

MAgPIE object containing labor costs [million US$17]

Author(s)

Debbora Leip

Examples

## Not run: 
x <- laborCostsEndo(gdx)

## End(Not run)

laborProductivity

Description

calculates labor productivity in crop sector (kg DM per hour) from a MAgPIE gdx file

Usage

laborProductivity(gdx, level = "reg", productAggr = TRUE)

Arguments

gdx

GDX file
level

spatial aggregation to report productivity ("cell","reg", "regglo", "glo")
productAggr

Aggregate over products or not (boolean)

Value

labor productivity in crop sector (kg DM per hour)

Author(s)

Xiaoxi Wang, Ruiying Du, Debbora Leip

Examples

## Not run: 
x <- laborProductivity(gdx)

## End(Not run)

land

Description

reads land out of a MAgPIE gdx file

Usage

land(
  gdx,
  file = NULL,
  level = "reg",
  types = NULL,
  subcategories = NULL,
  sum = FALSE
)

Arguments

gdx

GDX file
file

a file name the output should be written to using write.magpie
level

Level of regional aggregation; "reg" (regional), "glo" (global), "regglo" (regional and global) or any other aggregation level defined in gdxAggregate
types

NULL or a vector of strings. If NULL, all land types are used. Options are "crop", "past", "forestry", "primforest","secdforest, "urban", "other", "primother" and "secdother"
subcategories

NULL or vector of strings. If NULL, no subcategories are returned. Meaningful options are "crop, "forestry" and "other"
sum

determines whether output should be land-type-specific (FALSE) or aggregated over all types (TRUE).

Value

land as MAgPIE object (Mha)

Author(s)

Jan Philipp Dietrich, Florian Humpenoeder, Benjamin Leon Bodirsky, Patrick v. Jeetze

See Also

reportLandUse

Examples

## Not run: 
x <- land(gdx)

## End(Not run)

land_price

Description

Calculates MAgPIE MAgPIE land shadow prices based on a gdx file

Usage

land_price(
  gdx,
  file = NULL,
  level = "reg",
  ignore_lowbound = FALSE,
  absolute = TRUE,
  digits = 4
)

Arguments

gdx

GDX file
file

a file name the output should be written to using write.magpie
level

Level of regional aggregation; "reg" (regional), "glo" (global), "regglo" (regional and global) or any other aggregation level defined in superAggregate
ignore_lowbound

Some shadow prices are positive (see Details), corresponding to a lower bound for that pool. TRUE sets them to 0. Default value: FALSE.
absolute

Should the absolute value of all the marginals be taken into calculations? TRUE (default) of FALSE. See Details.
digits

rounding accuracy for the output

Details

The land price is obtained through marginals of the "oq_cropland" constraint. The majority of these marginals are negative values, and a negligible number of them are positive. This is the consequence of the constraint binding either on upper or lower level. The parameter ignore_lowbound removes all the positive marginals from land price calculation (negligible), and parameter absolute transforms them into negative values (to be all together reported as positive values at the final calculation).

Value

A MAgPIE object containing the land shadow prices (US$2017/ha).

Author(s)

Markus Bonsch, Misko Stevanovic

Examples

## Not run: 
    x <- land_price(level="regglo", products="kcr")
  
## End(Not run)

Land Carbon Sink Adjustment Factors

Description

Indirect human-induced emissions in the land use system

Usage

landCarbonSink(
  gdx,
  file = NULL,
  level = "reg",
  cumulative = FALSE,
  baseyear = 1995,
  source = "Grassi"
)

Arguments

gdx

GDX file
file

a file name the output should be written to using write.magpie
level

level of regional aggregation; "reg" (regional), "glo" (global), "regglo" (regional and global).
cumulative

Logical; Determines if emissions are reported annually (FALSE) or cumulative (TRUE). The starting point for cumulative emissions is y1995.
baseyear

Baseyear used for cumulative emissions (default = 1995)
source

Currently only "Grassi", which uses pre-calculated adjustment factors from Grassi et al 2021 (DOI 10.1038/s41558-021-01033-6). Can be extended in the future to also include "PIK", based on data from LPJmL.

Details

Calculates global and regional Land Carbon Sink Adjustment Factors

Value

Land Carbon Sink Adjustment Factors (Mt CO2 per year or cumulative)

Author(s)

Florian Humpenoeder

Examples

## Not run: 
x <- landCarbonSink(gdx)

## End(Not run)

landConservation

Description

reads land conservation information out of a MAgPIE gdx file. Land restoration 'restore' is reported in Mha/yr by default but can be also reported both over the time step length and cumulatively.

Usage

landConservation(
  gdx,
  file = NULL,
  level = "cell",
  cumuRestor = FALSE,
  baseyear = 1995,
  annualRestor = FALSE,
  sum = FALSE
)

Arguments

gdx

GDX file
file

a file name the output should be written to using write.magpie
level

Level of regional aggregation; "cell", "grid", "iso, "reg" (regional), "glo" (global), "regglo" (regional and global) or any secdforest aggregation level defined in superAggregate
cumuRestor

Logical; Whether function should report cumulative land restoration.
baseyear

Base year used for cumulative land restoration reporting (default = 1995)
annualRestor

Logical; Whether function should report annual land restoration.
sum

sum over land pools (default = FALSE)

Details

protected areas in primforest, secdforest and other land

Value

protected area in Mha

Author(s)

Florian Humpenoeder, Patrick v. Jeetze

Examples

## Not run: 
x <- landConservation(gdx)

## End(Not run)

landForestry

Description

reads and compiles forestry land subcategories from a MAgPIE gdx file

Usage

landForestry(gdx, file = NULL, level = "reg")

Arguments

gdx

GDX file
file

a file name the output should be written to using write.magpie
level

Level of regional aggregation; "reg" (regional), "glo" (global), "regglo" (regional and global) or any other aggregation level defined in superAggregate

Value

land as MAgPIE object (Mha)

Author(s)

Florian Humpenoeder

See Also

reportLandUse

Examples

## Not run: 
    x <- land(gdx)
  
## End(Not run)

landTransitionMatrix

Description

reads the land transition matrix out of a MAgPIE gdx file. The transition matrix from module 10 (ov_lu_transitions) only captures optimization-driven land conversions. Two processes in module 35 (natveg) shift area across land types in the presolve (before the optimization), bypassing the transition matrix: (1) disturbance losses transferring primary forest to secondary forest (p35_disturbance_loss_primf), and (2) natural regrowth on other land being reclassified as secondary forest once carbon density exceeds 20 tC/ha (p35_maturesecdf). This function adds both flows to the transition matrix to ensure consistency with land stock changes.

Usage

landTransitionMatrix(gdx, file = NULL, level = "reg")

Arguments

gdx

GDX file
file

a file name the output should be written to using write.magpie
level

Level of regional aggregation; "reg" (regional), "glo" (global), "regglo" (regional and global) or any other aggregation level defined in gdxAggregate

Value

land transition matrix as MAgPIE object (Mha/yr). The full 7x7 matrix including diagonal (persistence) is returned.

Author(s)

Florian Humpenoeder

See Also

reportLandTransitionMatrix

Examples

## Not run: 
x <- landTransitionMatrix(gdx)

## End(Not run)

lastIter

Description

Returns the value of a parameter in the last iteration

Usage

lastIter(gdx, param, MagpieOutput = TRUE)

Arguments

gdx

GDX file
param

Parameter to be returned
MagpieOutput

In inelastic model runs, the food demand model is run once in iter1 based on exo prices prescribed in iter0, then the magpie model in iter1. The magpie results therefore appear in iter1. In elastic model runs, iter2 is started by rerunning the food demand model, but if convergence is reached, MAgPIE does not run again. MAgPIE results are therefore still in iter1, even if the iteration is in iter2.

Value

magpie object

Author(s)

Benjamin Leon Bodirsky

Examples

## Not run: 
x <- lastIter(gdx)

## End(Not run)

LivestockDemStructure

Description

Calculates the share of different livestock commodities in total livestock product consumption on the basis of chosen attribute

Usage

LivestockDemStructure(
  gdx,
  file = NULL,
  level = "reg",
  after_shock = TRUE,
  calibrated = TRUE,
  attributes = "kcal",
  fish = FALSE
)

Arguments

gdx

GDX file
file

a file name the output should be written to using write.magpie
level

Level of regional aggregation; "iso" ISO country codes, "reg" (regional), "glo" (global)
after_shock

FALSE is using the exogenous real income and the prices before a shock, TRUE is using the endogeenous real income that takes into account food price change on real income
calibrated

if FALSE, the true regression outputs are used, if TRUE the values calibrated to the start years are used
attributes

unit: kilocalories per day ("kcal"), g protein per day ("protein"). Mt reactive nitrogen ("nr").
fish

if true, livestock share includes fish, otherwhise not

Value

magpie object with the livestock demand structure in a region or country. Unit is dimensionsless, but value depends on chosen attribute

Author(s)

Isabelle Weindl

Examples

## Not run: 
    x <- LivestockDemStructure(gdx)
  
## End(Not run)

LivestockShare

Description

Calculates the livestock share from the food demand model

Usage

LivestockShare(
  gdx,
  file = NULL,
  level = "reg",
  after_shock = TRUE,
  calibrated = TRUE,
  attributes = "kcal",
  fish = TRUE
)

Arguments

gdx

GDX file
file

a file name the output should be written to using write.magpie
level

Level of regional aggregation; "iso" ISO country codes, "reg" (regional), "glo" (global)
after_shock

FALSE is using the exogenous real income and the prices before a shock, TRUE is using the endogeenous real income that takes into account food price change on real income
calibrated

if FALSE, the true regression outputs are used, if TRUE the values calibrated to the start years are used
attributes

unit: kilocalories per day ("kcal"), g protein per day ("protein"). Mt reactive nitrogen ("nr").
fish

if true, livestock share includes fish, otherwhise not

Value

magpie object with the livestock share in a region or country. Unit is dimensionsless, but value depends on chosen attribute

Author(s)

Benjamin Bodirsky

Examples

## Not run: 
    x <- LivestockShare(gdx)
  
## End(Not run)

m_yeardiff

Description

Calculates the parameter m_yeardiff, which is a macro within MAgPIE.

Usage

m_yeardiff(gdx)

Arguments

gdx

GDX file

Value

a magpie object with the length of each timestep

Author(s)

Benjamin Leon Bodirsky

Examples

## Not run: 
    x <- m_yeardiff(gdx)
  
## End(Not run)

malmquist

Description

calcluates malmquist index based on a MAgPIE gdx file

Usage

malmquist(gdx, file = NULL)

Arguments

gdx

GDX file
file

a file name the output should be written to using write.magpie

Value

A MAgPIE object containing the malmquist index

Author(s)

Xiaoxi Wang

Examples

## Not run: 
    x <- malmquist(gdx)
  
## End(Not run)

ManureExcretion

Description

downscales Manure Excretion

Usage

ManureExcretion(
  gdx,
  level = "reg",
  products = "kli",
  awms = c("grazing", "stubble_grazing", "fuel", "confinement"),
  agg = TRUE
)

Arguments

gdx

GDX file
level

aggregation level: glo, reg, cell, grid, iso
products

livestock products
awms

large animal waste management categories: "grazing","stubble_grazing","fuel","confinement"),
agg

aggregation over "awms" or over "products".

Value

MAgPIE object

Author(s)

Benjamin Leon Bodirsky

Examples

## Not run: 
    x <- ManureExcretion(gdx)
  
## End(Not run)

mappingToLongFormat

Description

Derives a report aggregation mapping (sourceRegion to targetRegion) from a country-level region mapping. The input must have at least the columns countryname, country, and region. Any additional columns are treated as definitions of aggregated macro regions: each unique non-empty value defines a target region, and all source regions containing at least one country assigned to that value are mapped to it.

The output mapping has three blocks (each sorted by sourceRegion):

  1. each source region mapped to itself (regional resolution)

  2. each source region mapped to "GLO" (global aggregate)

  3. source regions mapped to every additional aggregated region they belong to

Usage

mappingToLongFormat(mappingOrFileName)

Arguments

mappingOrFileName

Either a data frame containing the country-level region mapping, or a character string giving the path to a CSV-file.

Value

A data frame with columns sourceRegion and targetRegion.

Note

This function is a workaround as in magpie4 we can not use the same mapping formulas that we could use in madrat functions. If the magpie4 aggregation logic is ever rewritten, this function may become obsolete.

Author(s)

Kristine Karstens, Patrick Rein

See Also

Other Spatial: addGeometry(), clusterOutputToTerraVector(), gdxAggregate(), superAggregateX()

metadata_comments

Description

set metadata comments to magpie4 objects

Usage

metadata_comments(x, unit, description, comment, note)

Arguments

x

magpie object (magpie4)
unit

provide unit
description

provide short description
comment

optional comment
note

optional note

Value

vector of comments following order of input (unit, description, comment, note - further: origin, creation data)

Author(s)

Benjamin Bodirsky, Jannes Breier

See Also

Other Infrastructure: expectVariablesPresent(), out(), tryList(), tryReport()

Examples

## Not run: 
    x <- metadata_comments(x,unit,description,comment,note)
  
## End(Not run)

modelstat

Description

MAgPIE model stat of all optimizations - main optimization and (if used) presolve optimization.

Usage

modelstat(gdx, file = NULL)

Arguments

gdx

GDX file
file

a file name the output should be written to using write.magpie

Value

A MAgPIE object containing the modelstat

Author(s)

Jan Philipp Dietrich

Examples

## Not run: 
    x <- modelstat(gdx)
  
## End(Not run)

NetForestChange

Description

Calculates net and gross forest area change based on a MAgPIE gdx file

Usage

NetForestChange(gdx, file = NULL, level = "cell", lowpass = NULL)

Arguments

gdx

GDX file
file

a file name the output should be written to using write.magpie
level

Level of regional aggregation; "reg" (regional), "glo" (global), "regglo" (regional and global) or any other aggregation level defined in superAggregateX
lowpass

number of lowpass filter iterations (default = NULL)

Value

Net Forest Change as MAgPIE object (Mha per year)

Author(s)

Florian Humpenoeder

Examples

## Not run: 
x <- NetForestChange(gdx)

## End(Not run)

NitrogenBudget

Description

calculates projections of Nitrogen Budgets for Croplands (Tg Nr per) from a MAgPIE gdx file

Usage

NitrogenBudget(
  gdx,
  include_emissions = FALSE,
  level = "reg",
  debug = FALSE,
  cropTypes = FALSE,
  threshold = 0.05,
  progress = TRUE
)

Arguments

gdx

GDX file
include_emissions

TRUE also divides the N surplus into different emissions
level

aggregation level, reg, glo or regglo, cell, iso or grid
debug

debug mode TRUE makes some consistency checks between estimates for different resolutions.
cropTypes

FALSE for aggregate results; TRUE for crop-specific results
threshold

passed to mstools::toolFertilizerDistribution
progress

passed to mstools::toolFertilizerDistribution

Author(s)

Benjamin Leon Bodirsky, Michael Crawford, Edna J. Molina Bacca, Florian Humpenoeder

Examples

## Not run: 
x <- NitrogenBudget(gdx)

## End(Not run)

NitrogenBudgetNonagland

Description

calculates projections of Nitrogen Budgets for non-agricutlural land from a MAgPIE gdx file

Usage

NitrogenBudgetNonagland(gdx, level = "reg")

Arguments

gdx

GDX file
level

aggregation level, reg, glo or regglo

Author(s)

Benjamin Leon Bodirsky, Edna J. Molina Bacca

Examples

## Not run: 
    x <- NitrogenBudgetNonagland(gdx)
  
## End(Not run)

NitrogenBudgetPasture

Description

calculates projections of Nitrogen Budgets for Croplands from a MAgPIE gdx file

Usage

NitrogenBudgetPasture(gdx, include_emissions = FALSE, level = "reg")

Arguments

gdx

GDX file
include_emissions

TRUE also divides the N surplus into different emissions
level

aggregation level, reg, glo or regglo, cell, grid, iso

Author(s)

Benjamin Leon Bodirsky, Edna J. Molina Bacca

Examples

## Not run: 
x <- NitrogenBudgetPasture(gdx)

## End(Not run)

NitrogenBudgetWithdrawals

Description

calculates projections of Nitrogen Budgets withdrawals for Croplands from a MAgPIE gdx file

Usage

NitrogenBudgetWithdrawals(gdx, kcr = "sum", net = TRUE, level = "reg")

Arguments

gdx

GDX file
kcr

"sum" provides the totals over all crops, "kcr" provides outputs by kcr
net

TRUE only provides total net-withdrawals, otherwise all categories are returned (fixation and seed are returned positive, not negative)
level

aggregation level, reg, glo or regglo, cell, grid or iso

Author(s)

Benjamin Leon Bodirsky, Michael Crawford

Examples

## Not run: 
x <- NitrogenBudgetWithdrawals(gdx)

## End(Not run)

OtherLand

Description

Disaggregation of other land into initial, restored and recovered land based on a MAgPIE gdx file

Usage

OtherLand(gdx, level = "reg")

Arguments

gdx

GDX file
level

Level of regional aggregation; "cell", "reg" (regional), "glo" (global), "regglo" (regional and global) or any aggregation level defined in superAggregateX. In addition "climate" for the 3 climate regions tropical, temperate and boreal is available.

Details

initial, restored and recovered land

Value

Other land area in Mha

Author(s)

Florian Humpenoeder

Examples

## Not run: 
    x <- PeatlandArea(gdx)
  
## End(Not run)

out

Description

Function to safely returns parameters. Function returns either the output or writes it to a file. Please use this function when you write own GDX output functions.

Usage

out(x,file)

Arguments

x

an object that can be converted to a MAgPIE object
file

file name of a file it should be written to. NULL, if x should be returned instead to be written to a file.

Value

NULL or x as MAgPIE object

Author(s)

Jan Philipp Dietrich

See Also

Other Infrastructure: expectVariablesPresent(), metadata_comments(), tryList(), tryReport()

outputCheck

Description

Function to check a MAgPIE gdx file for known problems (e.g. non-zero dummy variables). The function will throw warnings for problem found in the outputs.

Usage

outputCheck(gdx)

Arguments

gdx

GDX file

Author(s)

Jan Philipp Dietrich

Examples

## Not run: 
outputCheck(gdx)

## End(Not run)

outputPerWorker

Description

returns output per worker in crop+livestock production

Usage

outputPerWorker(gdx, level = "reg", file = NULL)

Arguments

gdx

GDX file
level

spatial aggregation to report employment ("reg", "glo", "regglo", or custom region aggregation)
file

a file name the output should be written to using write.magpie

Value

output per worker as magpie object

Author(s)

Debbora Leip

Examples

## Not run: 
x <- outputPerWorker(gdx)

## End(Not run)

PeatlandArea

Description

reads peatland area out of a MAgPIE gdx file

Usage

PeatlandArea(gdx, file = NULL, level = "cell", sum = TRUE)

Arguments

gdx

GDX file
file

a file name the output should be written to using write.magpie
level

Level of regional aggregation; "cell", "reg" (regional), "glo" (global), "regglo" (regional and global) or any aggregation level defined in superAggregateX. In addition "climate" for the 3 climate regions tropical, temperate and boreal is available.
sum

sum over land types TRUE (default) or FALSE

Details

Intact, degraded and rewettet peatland area

Value

Peatland area in Mha

Author(s)

Florian Humpenoeder

Examples

## Not run: 
    x <- PeatlandArea(gdx)
  
## End(Not run)

PeatlandEmissions

Description

reads peatland GHG emissions out of a MAgPIE gdx file

Usage

PeatlandEmissions(
  gdx,
  file = NULL,
  level = "cell",
  unit = "gas",
  cumulative = FALSE,
  baseyear = 1995,
  lowpass = 0,
  sum = TRUE,
  intact = FALSE
)

Arguments

gdx

GDX file
file

a file name the output should be written to using write.magpie
level

Level of regional aggregation; "cell", "reg" (regional), "glo" (global), "regglo" (regional and global) or any aggregation level defined in superAggregateX. In addition "climate" for the 3 climate regions tropical, temperate and boreal is available.
unit

global warming potential (GWP100AR6) or gas (gas)
cumulative

FALSE (default) or TRUE
baseyear

Baseyear used for cumulative emissions (default = 1995)
lowpass

number of lowpass filter iterations (default = 0)
sum

sum over land types TRUE (default) or FALSE
intact

report GHG emissions from intact peatlands FALSE (default) or TRUE

Details

Peatland GHG emissions: CO2, DOC, CH4 and N2O

Value

Peatland GHG emissions in Mt CO2eq (if unit="gwp") or Mt of the respective gas (if unit="gas")

Author(s)

Florian Humpenoeder

Examples

## Not run: 
    x <- PeatlandArea(gdx)
  
## End(Not run)

PlantationEstablishment

Description

reads carbon stocks in harvested timber out of a MAgPIE gdx file

Usage

PlantationEstablishment(gdx, file = NULL, level = "cell")

Arguments

gdx

GDX file
file

a file name the output should be written to using write.magpie
level

Level of regional aggregation; "cell", "reg" (regional), "glo" (global), "regglo" (regional and global), custom regation aggregation or any secdforest aggregation level defined in superAggregateX

Details

Area newly established in current time step for future timber production

Value

Area newly for timber production

Author(s)

Abhijeet Mishra

Examples

## Not run: 
    x <- PlantationEstablishment(gdx)
  
## End(Not run)

population

Description

reads population out of a MAgPIE gdx file

Usage

population(
  gdx,
  file = NULL,
  level = "reg",
  age = FALSE,
  sex = FALSE,
  bmi_groups = FALSE
)

Arguments

gdx

GDX file
file

a file name the output should be written to using write.magpie
level

Level of regional aggregation; "reg" (regional), "glo" (global), "regglo" (regional and global) or any other aggregation level defined in superAggregate
age

if TRUE, population is split up by age groups
sex

if TRUE, population is split up by sex
bmi_groups

if TRUE, the population will be split up in body-mass-index groups.

Value

population as MAgPIE object (million people)

Author(s)

Florian Humpenoeder, Benjamin Bodirsky, Isabelle Weindl

See Also

reportPopulation

Examples

## Not run: 
x <- population(gdx)

## End(Not run)

PriceElasticities

Description

Calculates the physical elasticity for food demand

Usage

PriceElasticities(
  gdx,
  file = NULL,
  level = "reg",
  calibrated = TRUE,
  products = "kfo"
)

Arguments

gdx

GDX file
file

a file name the output should be written to using write.magpie
level

Level of regional aggregation; "iso" ISO country codes, "reg" (regional), "glo" (global)
calibrated

if FALSE, the true regression outputs are used, if TRUE the values calibrated to the start years are used
products

set of the products for which the elasticity should be estimated. Please note that this stills remains an elasticity relative to total food expenditure. So its the change in consumption of one good when the prices of all products change according to the scenario.

Value

magpie object with the livestock share in a region or country. Unit is dimensionsless, but value depends on chosen attribute

Author(s)

Benjamin Bodirsky

Examples

## Not run: 
    x <- PriceElasticities(gdx)
  
## End(Not run)

PriceGHG

Description

reads GHG emission prices out of a MAgPIE gdx file

Usage

PriceGHG(gdx, file = NULL, level = "reg", aggr = "weight")

Arguments

gdx

GDX file
file

a file name the output should be written to using write.magpie
level

Level of regional aggregation; "reg" (regional), "glo" (global), "regglo" (regional and global) or any other aggregation level defined in superAggregate
aggr

aggregation used, currently only "weight" (weighted by population) (max is deprecated)

Value

GHG emission prices as MAgPIE object (US$2017/tCO2, US$2017/tN2O, US$2017/tCH4)

Author(s)

Florian Humpenoeder, Amsalu W. Yalew

See Also

reportPriceGHG

Examples

## Not run: 
    x <- PriceGHG(gdx)
  
## End(Not run)

priceIndex

Description

calcluates price indicies based on a MAgPIE gdx file

Usage

priceIndex(
  gdx,
  file = NULL,
  level = "reg",
  products = "kall",
  index = "lasp",
  chain = FALSE,
  baseyear = "y2005",
  round = TRUE,
  type = "consumer",
  product_aggr = TRUE
)

Arguments

gdx

GDX file
file

a file name the output should be written to using write.magpie
level

Level of regional aggregation; "reg" (regional), "glo" (global), "regglo" (regional and global) or any other aggregation level defined in superAggregate
products

Selection of products (either by naming products, e.g. "tece", or naming a set,e.g."kcr")
index

"lasp" (Laspeyres-Index: baseyear weighting), "paas" (Paasche-Index: current weighting), "fish" (Fisher-Index: geometric mean of "lasp" and "paas")
chain

Chain Index: if true, the base period for each time period is the immediately preceding time period. Can be combined with all of the above indices
baseyear

baseyear of the price index
round

shall the results be rounded?
type

For whom are the prices important? "producer" are the prices that farmer face, as they also produce intermediate products (seed, feed). "consumer" are the prices for the end consumer faces (supermarket, bioenergy plant). Currently, the only difference is the basket composition (ideally, also prices should differ between regions)
product_aggr

aggregate over products or not (boolean)

Value

A MAgPIE object containing price indices for consumers or producers (depending on type)

Author(s)

Jan Philipp Dietrich, Florian Humpenoeder, Benjamin Bodirsky

Examples

## Not run: 
    x <- priceIndex(gdx)
  
## End(Not run)

priceIndexFood

Description

calcluates price indicies based on a MAgPIE gdx file

Usage

priceIndexFood(
  gdx,
  file = NULL,
  level = "reg",
  index = "lasp",
  chain = FALSE,
  baseyear = "y2005",
  round = TRUE,
  product_aggr = TRUE
)

Arguments

gdx

GDX file
file

a file name the output should be written to using write.magpie
level

Level of regional aggregation; "reg" (regional), "glo" (global), "regglo" (regional and global) or any other aggregation level defined in superAggregate
index

"lasp" (Laspeyres-Index: baseyear weighting), "paas" (Paasche-Index: current weighting), "fish" (Fisher-Index: geometric mean of "lasp" and "paas")
chain

Chain Index: if true, the base period for each time period is the immediately preceding time period. Can be combined with all of the above indices
baseyear

baseyear of the price index. type model to take baseyear 2010 with literature prices
round

shall the results be rounded?
product_aggr

aggregate over products or not (boolean)

Value

A MAgPIE object containing price indices for consumers or producers (depending on type)

Author(s)

Jan Philipp Dietrich, Florian Humpenoeder, Benjamin Bodirsky

Examples

## Not run: 
    x <- priceIndexFood(gdx)
  
## End(Not run)

prices

Description

calcluates prices based on a MAgPIE gdx file

Usage

prices(
  gdx,
  file = NULL,
  level = "reg",
  products = "kall",
  product_aggr = FALSE,
  attributes = "dm",
  type = "consumer",
  glo_weight = "production"
)

Arguments

gdx

GDX file
file

a file name the output should be written to using write.magpie
level

Level of regional aggregation; "reg" (regional), "glo" (global), "regglo" (regional and global) or any other aggregation level defined in superAggregate
products

Selection of products (either by naming products, e.g. "tece", or naming a set,e.g."kcr")
product_aggr

aggregate over products or not (boolean)
attributes

USD17MER per ton X (dm,nr,p,k,wm) except gross energy (ge) where it is USD17MER per GJ
type

"consumer" or "producer" prices. Producers' prices are calculated on the regional level as a sum of regional trade equation marginal values and respective global trade equation marginal values.For the non traded commodities, both global and regional producers prices are set to zero instead of NaN.
glo_weight

Decides the calculation of global prices. Weighting schemes are applied for estimation of global producer price. If "export" prices are calculated as average of regional exporters' prices, weighted by the export volumes. If "production" (default), prices are calculated as average of regional prices weighted by regional production. If "free_trade", the global prices are directly taken from the shadow prices of the global trade constraint, and no averaging is performed.

Value

A MAgPIE object containing the consumer's or producers' prices (unit depends on attributes)

Author(s)

Misko Stevanovic, Florian Humpenoeder, Jan Philipp Dietrich, Xiaoxi Wang, Edna J. Molina Bacca

Examples

## Not run: 
x <- prices(gdx)

## End(Not run)

primaryPerSecondary

Description

Calculates the amount of primary products needed per unit of secondary (and tertiary) product, accounting for processing chains and co-product allocation. This function traces back from secondary/tertiary products through processing stages to the original primary crop inputs.

Usage

primaryPerSecondary(gdx, file = NULL, level = "reg", allocation = "mass")

Arguments

gdx

GDX file
file

a file name the output should be written to using write.magpie
level

Level of regional aggregation; "reg" (regional), "glo" (global), "regglo" (regional and global) or any other aggregation level defined in gdxAggregate
allocation

Method for allocating primary product use when co-products are produced. Options: "mass" (default): Allocation based on dry matter content of outputs "value": Allocation based on economic value of outputs "none": No allocation - full primary input attributed to each output (sum of allocations > 100 percent when co-products exist)

Value

MAgPIE object containing the amount of primary product needed per unit of secondary product (tDM/tDM)

Author(s)

Kristine Karstens, David M Chen

See Also

production, trade

Examples

## Not run: 
x <- primaryPerSecondary(gdx)

## End(Not run)

PrimSecdOtherLand

Description

Calculates share of primary and secondary non-forest vegetation for different aggregation levels based on gridded magpie output and initial shares of primary and secondary non-forest vegetation.

Usage

PrimSecdOtherLand(
  x,
  ini_file,
  ini_year = "y1995",
  file = NULL,
  level = "grid",
  unit = "Mha"
)

Arguments

x

Time series of land pools (model output) containing only one aggregated class for other land. Can be a file or magclass object.
ini_file

Initialisation file for primary and secondary other land (e.g. based on 1995 MAgPIE land-use initialisation values). Must have the same spatial resolution as x.
ini_year

Reference year for estimating primary and secondary other land shares, must be included in ini_file.
file

a file name the output should be written to using write.magpie
level

Level of regional aggregation; "reg" (regional), "glo" (global), "regglo" (regional and global) or any other aggregation level defined in superAggregate. The unit of output for the cases above is Mha. If level "grid" is specified the unit of output can be chosen between "share" and "Mha".
unit

"Mha" or "share". Defines the unit of the gridded output, see also level.

Value

x including land area for primary and secondary non-forested vegetation in MAgPIE (other land) as MAgPIE object; either as unit of area (Mha) or as fraction of total land per grid cell (share).

Author(s)

Patrick v. Jeetze, Kristine Karstens

Examples

## Not run: 
x <- "./cell.land_0.5.nc"
land <- PrimSecdOtherLand(x)

# direct use of disaggregation output
land <- PrimSecdOtherLand(land_hr)

## End(Not run)

processing

Description

Calculates MAgPIE disaggregated processing out of a gdx file

Usage

processing(gdx, level = "reg", indicator = "secondary_from_primary")

Arguments

gdx

GDX file
level

Level of regional aggregation ("reg", "glo", "regglo")
indicator

process or secondary product output

Details

Demand definitions are equivalent to FAO CBS categories

Value

processing as MAgPIE object (Unit depends on attributes)

Author(s)

David Chen, Benjamin Leon Bodirsky

Examples

## Not run: 
    x <- processing(gdx = gdx, level="regglo", products="kcr", indicator="primary_to_process")
  
## End(Not run)

productEmissions

Description

Calculates GHG emissions by product, allocating emissions from different sources (land-use change, enteric fermentation, manure management, etc.) to specific agricultural products based on cropland shares, livestock feed demand, and other factors. This is an improved version with better code style and documentation.

Usage

productEmissions(gdx, unit = "GWP100AR6", level = "reg", perTonne = TRUE)

Arguments

gdx

GDX file
unit

"element", "gas", "GWP100AR5", "GWP100AR6", "GWP*AR5", or "GWP*AR6" "element": co2_c in Mt C/yr, n2o_n in Mt N/yr, ch4 in Mt CH4/yr "gas": co2_c in Mt CO2/yr, n2o_n in Mt N2O/yr, ch4 in Mt CH4/yr "GWP": co2_c in Mt CO2eq/yr, n2o_n in Mt CO2eq/yr, ch4 in Mt CO2eq/yr
level

Level of regional aggregation; "reg" (regional), "glo" (global), "regglo" (regional and global)
perTonne

If TRUE, returns emissions intensity (per tonne of production); if FALSE, returns total emissions

Value

GHG emissions as MAgPIE object (Unit depends on unit parameter)

Author(s)

David M Chen

See Also

Emissions, emisCO2

Examples

## Not run: 
  x <- productEmissions(gdx, unit = "GWP100AR6", level = "reg")
  xIntensity <- productEmissions(gdx, unit = "GWP100AR6", perTonne = TRUE)

## End(Not run)

production

Description

reads production out of a MAgPIE gdx file

Usage

production(
  gdx,
  file = NULL,
  level = "reg",
  products = "kall",
  product_aggr = FALSE,
  attributes = "dm",
  water_aggr = TRUE,
  cumulative = FALSE,
  baseyear = 1995
)

Arguments

gdx

GDX file
file

a file name the output should be written to using write.magpie
level

Level of regional aggregation; "reg" (regional), "glo" (global), "regglo" (regional and global) or any other aggregation level defined in gdxAggregate
products

Selection of products (either by naming products, e.g. "tece", or naming a set,e.g."kcr")
product_aggr

aggregate over products or not (boolean)
attributes

dry matter: Mt ("dm"), gross energy: PJ ("ge"), reactive nitrogen: Mt ("nr"), phosphor: Mt ("p"), potash: Mt ("k"), wet matter: Mt ("wm"). Can also be a vector.
water_aggr

aggregate irrigated and non-irriagted production or not (boolean).
cumulative

Logical; Determines if production is reported annually (FALSE, default) or cumulative (TRUE)
baseyear

Baseyear used for cumulative production (default = 1995)

Value

production as MAgPIE object (unit depends on attributes and cumulative)

Author(s)

Benjamin Leon Bodirsky

See Also

reportProduction, demand

Examples

## Not run: 
x <- production(gdx)

## End(Not run)

productionProfit

Description

calcluates aggregate producer profit based on a MAgPIE gdx file.

Usage

productionProfit(gdx, file = NULL, level = "reg")

Arguments

gdx

GDX file
file

a file name the output should be written to using write.magpie
level

Level of regional aggregation; "reg" (regional), "glo" (global), "regglo" (regional and global) or any other aggregation level defined in superAggregate

Value

A MAgPIE object containing producers profit in million $US.

Author(s)

Miodrag Stevanovic

Examples

## Not run: 
    x <- productionProfit(gdx)
  
## End(Not run)

productionRevenue

Description

calcluates production revenue based on a MAgPIE gdx file.

Usage

productionRevenue(
  gdx,
  file = NULL,
  level = "reg",
  products = "kall",
  product_aggr = TRUE
)

Arguments

gdx

GDX file
file

a file name the output should be written to using write.magpie
level

Level of regional aggregation; "reg" (regional), "glo" (global), "regglo" (regional and global) or any other aggregation level defined in superAggregate
products

Selection of products (either by naming products, e.g. "tece", or naming a set,e.g."kcr")
product_aggr

ggregate over products or not (boolean, default TRUE)

Value

A MAgPIE object containing prodcution revenues.

Author(s)

Miodrag Stevanovic

Examples

## Not run: 
    x <- productionRevenue(gdx)
  
## End(Not run)

readGDXBilateral

Description

Internal support function to read bilateral spatial data from GDX files.

Usage

readGDXBilateral(gdx, symbol)

Arguments

gdx

gdx file to report from
symbol

name of the symbol to read from gdx

Author(s)

David M Chen

relativeHourlyLaborCosts

Description

calculates labor costs per ag. worker in relation to GDP pc

Usage

relativeHourlyLaborCosts(gdx, level = "reg", file = NULL)

Arguments

gdx

GDX file
level

spatial aggregation to report ("iso", "reg", "glo", "regglo", or custom region aggregation)
file

a file name the output should be written to using write.magpie

Value

labor costs per ag. worker in relation to GDP pc

Author(s)

Debbora Leip

Examples

## Not run: 
x <- relativeHourlyLaborCosts(gdx)

## End(Not run)

reportAAI

Description

reports area actually irrigated

Usage

reportAAI(gdx, level = "regglo")

Arguments

gdx

GDX file
level

aggregation level of returned data ("regglo" by default)

Value

Area actually irrigated as MAgPIE object. Unit: see names

Area actually irrigated variables

Name Unit Meta
Resources|Land Cover|Cropland|Area actually irrigated million ha Cropland area actually receiving irrigation

Author(s)

Stephen Wirth, Anne Biewald

Examples

## Not run: 
x <- reportAEI(gdx)

## End(Not run)

reportAEI

Description

reports Area equipped for Irrigation

Usage

reportAEI(gdx, level = "regglo")

Arguments

gdx

GDX file
level

aggregation level of returned data ("regglo" by default)

Value

Area equipped for Irrigation as MAgPIE object. Unit: see names

Area equipped for irrigation variables

Name Unit Meta
Resources|Land Cover|Cropland|Area equipped for irrigation million ha Cropland area equipped with irrigation infrastructure

Author(s)

Stephen Wirth

Examples

## Not run: 
    x <- reportAEI(gdx)
  
## End(Not run)

reportAgEmployment

Description

reports employment in crop+livestock production from MAgPIE results

Usage

reportAgEmployment(gdx, type = "absolute", detail = FALSE, level = "regglo")

Arguments

gdx

GDX file
type

"absolute" for total number of people employed, "share" for share out of working age population
detail

if TRUE, employment is disaggregated to crop and livestock production, if FALSE only aggregated employment is reported
level

spatial aggregation: "reg", "glo", "regglo", "iso"

Value

agricultural employment as MAgPIE object

Agricultural employment variables

Name Unit Meta
Labor|Employment|Agricultural employment mio people Total agricultural employment
Labor|Employment|Agricultural employment|+|Crop products mio people Employment in crop production
Labor|Employment|Agricultural employment|+|Livestock products mio people Employment in livestock production
Labor|Employment|Share of working age population employed in agriculture % Agricultural employment as share of working age population

Author(s)

Debbora Leip

Examples

## Not run: 
    x <- reportAgEmployment(gdx)
  
## End(Not run)

reportAgGDP

Description

reports MAgPIE Agricultural GDP Mio. USD05 MER

Usage

reportAgGDP(gdx, level = "regglo")

Arguments

gdx

GDX file
level

aggregation level of returned data ("regglo" by default)

Value

Magpie object

Agricultural GDP variables

Name Unit Meta
Value|Agriculture GDP million US$2017/yr Agricultural value added (GDP from agriculture sector)

Author(s)

Edna J. Molina Bacca

Examples

## Not run: 
x <- reportAgGDP(gdx)

## End(Not run)

reportAgriResearchIntensity

Description

reports Agricultural Research Intensity as % of total GDP

Usage

reportAgriResearchIntensity(gdx, level = "regglo")

Arguments

gdx

GDX file
level

aggregation level of returned data ("regglo" by default)

Value

magpie object

Agricultural research intensity variables

Name Unit Meta
Agricultural Research Intensity % of Total GDP Share of GDP spent on agricultural research

Author(s)

David Chen

Examples

## Not run: 
x <- reportAgriResearchIntensity(gdx)

## End(Not run)

reportAnthropometrics

Description

reports Underweight, Normalweight, Overweight and Obesity as well as body height for males and females

Usage

reportAnthropometrics(gdx, level = "regglo")

Arguments

gdx

GDX file
level

spatial aggregation: "reg", "glo", "regglo", "iso"

Value

Magpie object

Anthropometrics variables

Name Unit Meta
Nutrition|Anthropometrics|People underweight million people Population with underweight BMI
Nutrition|Anthropometrics|People normalweight million people Population with normal BMI
Nutrition|Anthropometrics|People overweight million people Population with overweight BMI
Nutrition|Anthropometrics|People obese million people Population with obesity
Nutrition|Anthropometrics|Body height of female adults cm/capita Average body height of adult females
Nutrition|Anthropometrics|Body height of male adults cm/capita Average body height of adult males

Author(s)

Benjamin Leon Bodirsky

Examples

## Not run: 
x <- reportBodyweight(gdx)

## End(Not run)

reportBII

Description

reports biodiversity intactness index

Usage

reportBII(gdx, level = "regglo")

Arguments

gdx

GDX file
level

An aggregation level for the spatial dimension. Can be any level available via superAggregateX.

Value

Biodiversity intactness index as MAgPIE object

Biodiversity Intactness Index variables

Name Unit Meta
Biodiversity|BII unitless Terrestrial biodiversity measured with Biodiversity Intactness Index (BII). The BII summarises the change in ecological communities in response to human pressures. It is an estimated percentage of the original number of species that remain and their abundance in any given area.
Biodiversity|Cropland Landscapes BII unitless Terrestrial biodiversity in landscapes containing cropland measured with Biodiversity Intactness Index (BII)
Biodiversity|BII in 30x30 Landscapes unitless Terrestrial biodiversity in 30 by 30 conservation target landscapes measured with Biodiversity Intactness Index (BII)
Biodiversity|Biodiversity Hotspot BII unitless Terrestrial biodiversity in biodiversity hotspot landscapes measured with Biodiversity Intactness Index (BII)
Biodiversity|Biodiversity Hotspot and Intact Forest Landscapes BII unitless Terrestrial biodiversity in biodiversity hotspot and intact forest landscapes measured with Biodiversity Intactness Index (BII)
Biodiversity|BII in areas outside Biodiversity Hotspots, Intact Forest & Cropland Landscapes unitless Terrestrial biodiversity in areas outside biodiversity hotspot, intact forest and cropland landscapes measured with Biodiversity Intactness Index (BII)
Biodiversity|Key Biodiversity Area BII unitless Terrestrial biodiversity in key biodiversity areas measured with Biodiversity Intactness Index (BII)

Author(s)

Patrick v. Jeetze, Florian Humpenoeder

Examples

## Not run: 
x <- reportBII(gdx)

## End(Not run)

reportBiochar

Description

reports production and carbon storage of biochar

Usage

reportBiochar(gdx, level = "regglo")

Arguments

gdx

GDX file
level

The aggregation level to be used ("regglo" by default)

Value

Biochar production and carbon storage as MAgPIE object

Author(s)

Kristine Karstens, Isabelle Weindl

Examples

## Not run: 
    x <- reportBiochar(gdx)
  
## End(Not run)

reportBiogasFeedstock

Description

Reports biogas feedstock from a MAgPIE GDX file at ISO country level. Currently covers two sources: manure allocated to digesters and fodder crops (placeholder, all zeros until MAgPIE tracks foddr/forage crop allocation to biogas). Manure is converted from nitrogen mass (Mt N) to energy (PJ) using livestock-specific heating values and nitrogen contents from Hoyos-Sebá et al. (2024).

Usage

reportBiogasFeedstock(gdx, file = NULL)

Arguments

gdx

GDX file
file

a file name the output should be written to using write.magpie

Value

MAgPIE object with biogas feedstock potential ("manure", "fodder") at ISO level in PJ.

Author(s)

Kristine Karstens

Examples

## Not run: 
  x <- reportBiogasFeedstock(gdx)

## End(Not run)

reportBioplasticDemand

Description

reports demand for bioplastic and demand for substrate for bioplastic production from MAgPIE results

Usage

reportBioplasticDemand(gdx, detail = TRUE, level = "regglo")

Arguments

gdx

GDX file
detail

only relevant for substrate demand. If TRUE, substrate demand is disaggregated by crop type, if FALSE only the aggregated demand is reported.
level

spatial aggregation to report bioplastic/substrate demand (only "reg" or "regglo")

Value

bioplastic and bioplastic substrate demand as MAgPIE object

Bioplastic demand variables

Name Unit Meta
Demand for bioplastic Mt/yr Total bioplastic demand
Demand for bioplastic substrate|Total Mt DM/yr Total substrate demand for bioplastic production

Author(s)

Debbora Leip

Examples

## Not run: 
    x <- reportBioplasticDemand(gdx)
  
## End(Not run)

reportCarbonstock

Description

Reports the carbon stocks for future MAgPIE projections

Usage

reportCarbonstock(gdx, level = "regglo")

Arguments

gdx

GDX file
level

aggregation level of returned data ("regglo" by default)

Carbon stock variables

Name Unit Meta
Resources|Carbon Mt C Total terrestrial carbon stocks
Resources|Carbon|+|Soil Mt C Soil carbon stocks
Resources|Carbon|+|Litter Mt C Litter carbon stocks
Resources|Carbon|+|Vegetation Mt C Vegetation carbon stocks (above and below ground biomass)

Author(s)

Kristine Karstens

Examples

## Not run: 
    x <- reportSOM(gdx)
  
## End(Not run)

reportConsumVal

Description

reports MAgPIE consumption value

Usage

reportConsumVal(gdx, level = "regglo")

Arguments

gdx

GDX file
level

aggregation level of returned data ("regglo" by default)

Value

Magpie object associated with the consumption value

Consumption value variables

Name Unit Meta
Value|Consumption Value million US$2017/yr Total value of agricultural consumption

Author(s)

Edna J. Molina Bacca

Examples

## Not run: 
x <- reportConsumVal(gdx)

## End(Not run)

reportCostCapitalInvestment

Description

reports MAgPIE capital investments

Usage

reportCostCapitalInvestment(gdx, level = "regglo")

Arguments

gdx

GDX file
level

An aggregation level for the spatial dimension. Can be any level available via superAggregateX.

Value

Magpie object associated with overall costs and value of production

Capital investment cost variables

Name Unit Meta
Costs|Capital Investments million US$2017 Capital investments (sticky cost implementation)

Author(s)

Edna J. Molina Bacca

Examples

## Not run: 
x <- reportCostCapitalInvestment(gdx)

## End(Not run)

reportCostCapitalStocks

Description

reports MAgPIE capital stocks

Usage

reportCostCapitalStocks(gdx, level = "regglo")

Arguments

gdx

GDX file
level

An aggregation level for the spatial dimension. Can be any level available via superAggregateX.

Value

Magpie object associated with overall costs and value of production

Capital stock variables

Name Unit Meta
Capital Stocks|Arable farm capital million US$2017 Capital stocks used in cropland (sticky cost implementation)

Author(s)

Edna J. Molina Bacca

Examples

## Not run: 
x <- reportCostCapitalStocks(gdx)

## End(Not run)

reportCostOverall

Description

reports MAgPIE costs

Usage

reportCostOverall(gdx, level = "regglo")

Arguments

gdx

GDX file
level

An aggregation level for the spatial dimension. Can be any level available via superAggregateX.

Value

Magpie object associated with overall costs and value of production

Overall cost variables

Name Unit Meta
Costs|Gross value of production million US$2017/yr Total gross value of agricultural production

Author(s)

Edna J. Molina Bacca

Examples

## Not run: 
    x <- reportCostOverall(gdx)
  
## End(Not run)

reportCosts

Description

reports MAgPIE costs

Usage

reportCosts(gdx, level = "regglo")

Arguments

gdx

GDX file
level

An aggregation level for the spatial dimension. Can be any level available via gdxAggregate.

Value

consumption value as MAgPIE object Unit: see names

Cost variables

Name Unit Meta
Costs million US$2017/yr Total production costs
Costs|+|Input Factors million US$2017/yr Costs for input factors (labor, capital, materials)
Costs|+|Land Conversion million US$2017/yr Costs for land conversion
Costs|+|Transport million US$2017/yr Transport costs
Costs|+|TC million US$2017/yr Technology costs (research and development)
Costs|+|GHG Emissions million US$2017/yr Costs from GHG emission pricing
Costs|MainSolve w/o GHG Emissions million US$2017/yr Total costs excluding GHG emission costs

Author(s)

Florian Humpenoeder

Examples

## Not run: 
    x <- reportCosts(gdx)
  
## End(Not run)

reportCostsAccounting

Description

reports MAgPIE costs including total investments

Usage

reportCostsAccounting(gdx, level = "regglo")

Arguments

gdx

GDX file
level

An aggregation level for the spatial dimension. Can be any level available via superAggregateX.

Value

Costs accounting including total investments

Cost accounting variables

Name Unit Meta
Costs Accounting million US$2017/yr Total cost accounting including investments
Costs Accounting|+|Land Conversion million US$2017/yr Investment costs for land conversion
Costs Accounting|+|Transport million US$2017/yr Transport cost investments
Costs Accounting|+|TC million US$2017/yr Technological change investment costs

Author(s)

Edna J. Molina Bacca

Examples

## Not run: 
x <- reportCostsAccounting(gdx)

## End(Not run)

reportCostsAEI

Description

reports MAgPIE AEI costs

Usage

reportCostsAEI(gdx)

Arguments

gdx

GDX file

Value

magpie object containing AEI costs

AEI cost variables

Name Unit Meta
Costs|AEI million US$2017/yr Costs for area equipped for irrigation

Author(s)

Felicitas Beier

Examples

## Not run: 
    x <- reportCostsAEI(gdx)
  
## End(Not run)

reportCostsFertilizer

Description

reports MAgPIE nitrogen fertilizer costs disaggregated to crop categories

Usage

reportCostsFertilizer(gdx, level = "regglo")

Arguments

gdx

GDX file
level

An aggregation level for the spatial dimension. Can be any level available via superAggregateX.

Value

magpie object with fertilizer costs

Nitrogen fertilizer cost variables

Name Unit Meta
Costs|N Fertilizer million US$2017/yr Total nitrogen fertilizer costs
Costs|N Fertilizer|+|Crops million US$2017/yr N fertilizer costs for crops
Costs|N Fertilizer|+|Pasture million US$2017/yr N fertilizer costs for pasture

Author(s)

Debbora Leip

Examples

## Not run: 
    x <- reportCostsFertilizer(gdx)
  
## End(Not run)

reportFactorCosts

Description

reports MAgPIE factor costs (split into labor and capital for sticky realization)

Usage

reportCostsInputFactors(gdx, level = "regglo")

Arguments

gdx

GDX file
level

An aggregation level for the spatial dimension. Can be any level available via superAggregateX.

Value

magpie object with factor costs

Input factor cost variables

Name Unit Meta
Costs|Input Factors million US$2017/yr Total input factor costs (labor + capital)
Costs|Input Factors|+|Crops million US$2017/yr Factor costs for crop production
Costs|Input Factors|+|Livestock million US$2017/yr Factor costs for livestock production
Costs|Input Factors|+|Fish million US$2017/yr Factor costs for fish production
Costs|Input Factors|+|Pasture million US$2017/yr Factor costs for pasture management
Costs|Input Factors|+|Residues million US$2017/yr Factor costs for residue handling
Costs|Input Factors|++|Labor costs million US$2017/yr Total labor costs
Costs|Input Factors|++|Capital costs million US$2017/yr Total capital costs

Author(s)

Debbora Leip

Examples

## Not run: 
x <- reportCostsInputFactors(gdx)

## End(Not run)

reportCostsMACCS

Description

reports MAgPIE mitigation costs disaggregated into labor and capital

Usage

reportCostsMACCS(gdx, level = "regglo")

Arguments

gdx

GDX file
level

aggregation level of returned data ("regglo" by default)

Value

magpie object with mitigation costs

MACC cost variables

Name Unit Meta
Costs|MACCS|+|Labor costs million US$2017/yr Labor costs for MACC implementation
Costs|MACCS|+|Capital costs million US$2017/yr Capital costs for MACC implementation

Author(s)

Debbora Leip

Examples

## Not run: 
    x <- reportCostsMACCS(gdx)
  
## End(Not run)

reportCostsPresolve

Description

reports MAgPIE costs

Usage

reportCostsPresolve(gdx, level = "regglo")

Arguments

gdx

GDX file
level

An aggregation level for the spatial dimension. Can be any level available via superAggregateX.

Value

consumption value as MAgPIE object Unit: see names

Presolve cost variables

Name Unit Meta
Costs|PreSolve|Total million US$2017 Cumulative costs from presolve phase

Author(s)

Florian Humpenoeder

Examples

## Not run: 
    x <- reportCostsPresolve(gdx)
  
## End(Not run)

reportCostsTrade

Description

Reports MAgPIE bilateral trade cost components

Usage

reportCostsTrade(gdx, level = "regglo", sum = FALSE)

Arguments

gdx

GDX file
level

Level of regional aggregation; "reg" (regional), "glo" (global), "regglo" (regional and global) or any other aggregation level defined in superAggregate
sum

whether to sum across subcategories

Value

A MAgPIE object containing values related to trade costs (million US$2017/yr)

Author(s)

David M Chen

reportCostsWholesale

Description

Reads data to calculate wholesale costs

Usage

reportCostsWholesale(gdx, level = "regglo")

Arguments

gdx

GDX file
level

Level of regional aggregation; "reg" (regional), "glo" (global), "regglo" (regional and global) or any other aggregation level defined in superAggregate

Value

A MAgPIE object containing values related with costs wholesale trade (million US$2017/yr)

Wholesale cost variables

Name Unit Meta
Costs|Wholesale Costs million US$2017/yr Total wholesale trade costs

Author(s)

David M Chen

Examples

## Not run: 
x <- reportCostsWholesale(gdx)

## End(Not run)

reportCostsWithoutIncentives

Description

reports Costs Without Incentives

Usage

reportCostsWithoutIncentives(gdx, level = "regglo")

Arguments

gdx

GDX file
level

An aggregation level for the spatial dimension. Can be any level available via superAggregateX.

Value

magpie object

Costs without incentives variables

Name Unit Meta
Costs Accounting|Costs without incentives million US$2017/yr Total costs excluding policy incentives

Author(s)

David Chen

Examples

## Not run: 
x <- reportCostsWithoutIncentives(gdx)

## End(Not run)

reportCostTC

Description

reports MAgPIE TC costs

Usage

reportCostTC(gdx)

Arguments

gdx

GDX file

Value

magpie object with TC costs

TC cost variables

Name Unit Meta
Costs|TC million US$2017/yr Technological change investment costs

Author(s)

David Chen

Examples

## Not run: 
x <- reportCostTC(gdx)

## End(Not run)

reportCostTransport

Description

reports MAgPIE costs

Usage

reportCostTransport(gdx, level = "regglo")

Arguments

gdx

GDX file
level

An aggregation level for the spatial dimension. Can be any level available via superAggregateX.

Value

consumption value as MAgPIE object Unit: see names

Transport cost variables

Name Unit Meta
Costs|Transport million US$2017/yr Total transport costs for agricultural commodities
Costs|Transport|+|Crops million US$2017/yr Transport costs for crop products
Costs|Transport|+|Livestock products million US$2017/yr Transport costs for livestock products

Author(s)

David Chen

Examples

## Not run: 
    x <- reportCostTransport(gdx)
  
## End(Not run)

reportCroparea

Description

reports croparea

Usage

reportCroparea(gdx, detail = FALSE, level = "regglo")

Arguments

gdx

GDX file
detail

if detail=FALSE, the subcategories of groups are not reported (e.g. "soybean" within "oilcrops")
level

aggregation level of returned data ("regglo" by default)

Value

Croparea as MAgPIE object (million ha/yr)

Croparea variables

Name Unit Meta
Resources|Land Cover|Cropland|Croparea million ha Total physical cropland area used for crop production
Resources|Land Cover|Cropland|Croparea|+|Crops million ha Cropland area for food and feed crops
Resources|Land Cover|Cropland|Croparea|Crops|+|Cereals million ha Cropland for cereals (maize, rice, temperate cereals and tropical cereals)
Resources|Land Cover|Cropland|Croparea|Crops|+|Oil crops million ha Cropland for oil crops (cotton seed, groundnuts, oilpalms, other oil crops, soybean, sunflower)
Resources|Land Cover|Cropland|Croparea|Crops|+|Sugar crops million ha Cropland for sugar crops (sugar beet, sugar cane)
Resources|Land Cover|Cropland|Croparea|Crops|+|Other crops million ha Cropland for other crops (fruits, vegetables, nuts, potatoes, pulses, tropical roots)
Resources|Land Cover|Cropland|Croparea|+|Bioenergy crops million ha Cropland for second-generation bioenergy crops (short rotation grasses, short rotation trees)
Resources|Land Cover|Cropland|Croparea|++|Irrigated million ha Irrigated cropland (physical area)
Resources|Land Cover|Cropland|Croparea|++|Rainfed million ha Rainfed cropland (physical area)

Author(s)

Florian Humpenoeder

Examples

## Not run: 
x <- reportCroparea(gdx)

## End(Not run)

reportCropareaGrid

Description

reports croparea

Usage

reportCropareaGrid(gdx)

Arguments

gdx

GDX file

Value

Croparea as MAgPIE object (million ha/yr)

Grid-level croparea

This function produces grid-level (0.5 degree) croparea data for individual crops. Variable names follow the reportingnames mapping (e.g., Cereals, Oilcrops, etc.).

Author(s)

Benjamin Bodirsky

Examples

## Not run: 
x <- reportCropareaGrid(gdx)

## End(Not run)

reportCropDiversity

Description

reports crop diversity

Usage

reportCropDiversity(gdx, level = "regglo")

Arguments

gdx

GDX file
level

An aggregation level for the spatial dimension. Supports "reg", "glo", "regglo", "grid" or a custom region aggregation level.

Value

Crop diversity as MAgPIE object

Crop diversity variables

Name Unit Meta
Biodiversity|Shannon crop area diversity index unitless Crop type diversity based on area shares (higher = more diverse)
Biodiversity|Inverted Simpson crop area diversity index unitless Crop type diversity based on area shares (higher = more diverse)

Author(s)

Patrick v. Jeetze

Examples

## Not run: 
x <- reportCropDiversity(gdx)

## End(Not run)

reportCropResidues2ndBE

Description

Reports crop residues available for 2nd generation bioenergy from a MAgPIE GDX file at ISO country level. Applies soil cover constraints (minimum 30% soil cover retained, Lutz et al. 2019) and a collection fraction to estimate sustainably harvestable residue biomass, converted to energy (PJ).

Usage

reportCropResidues2ndBE(
  gdx,
  file = NULL,
  collectionFraction = 0.25,
  minDensityForExtraction = 0.1
)

Arguments

gdx

GDX file
file

a file name the output should be written to using write.magpie
collectionFraction

fraction of available residues that can be physically collected (default: 0.25)
minDensityForExtraction

minimum residue density (tDM/ha) below which extraction is not economic (default: 0.1)

Value

MAgPIE object with crop residue potential for 2nd gen bioenergy (res_cereals, res_fibrous, res_nonfibrous) at ISO level in PJ.

Author(s)

Kristine Karstens

References

Lutz et al. (2019), GMD, https://gmd.copernicus.org/articles/12/2419/2019/

See Also

ResidueBiomass, ResidueUsage

Examples

## Not run: 
  x <- reportCropResidues2ndBE(gdx)

## End(Not run)

reportDemand

Description

reports Demand for Food, Feed, Processing, Material, Bioenergy, Seed and Supply Chain Loss

Usage

reportDemand(gdx, detail = FALSE, agmip = FALSE, level = "regglo")

Arguments

gdx

GDX file
detail

if detail=F, the subcategories of groups are not reported (e.g. "soybean" within "oilcrops")
agmip

if agmip=T, additional sector aggregates required for agmip are reported (e.g. "AGR")
level

The level at which the report data should be aggregated.

Value

demand as MAgPIE object (Mt DM)

Demand variables

Name Unit Meta
Demand Mt DM/yr Total demand for agricultural products including food, feed, processing, material, bioenergy, seed and supply chain loss
Demand|++|Crops Mt DM/yr Demand for crops including food, feed products and bioenergy (1st and 2nd generation crops)
Demand|++|Livestock products Mt DM/yr Demand for livestock products (excluding fish)
Demand|++|Secondary products Mt DM/yr Demand for secondary products (processed agricultural goods)
Demand|++|Pasture Mt DM/yr Demand for pasture biomass
Demand|++|Bioenergy crops Mt DM/yr Demand for second-generation bioenergy crops

Demand by use variables

Name Unit Meta
Demand|Food Mt DM/yr Demand for food consumption
Demand|Feed Mt DM/yr Demand for animal feed
Demand|Processing Mt DM/yr Demand for food processing
Demand|Material Mt DM/yr Demand for material use (non-food, non-feed)
Demand|Bioenergy Mt DM/yr Demand for bioenergy production
Demand|Seed Mt DM/yr Demand for seeds
Demand|Supply Chain Loss Mt DM/yr Losses in the supply chain

Author(s)

Benjamin Leon Bodirsky, Isabelle Weindl

Examples

## Not run: 
    x <- reportDemand()
  
## End(Not run)

reportDemandBioenergy

Description

reports Bioenergy Demand in EJ/yr

Usage

reportDemandBioenergy(gdx, detail = FALSE, level = "regglo")

Arguments

gdx

GDX file
detail

if detail=F, the subcategories of groups are not reported (e.g. "soybean" within "oilcrops")
level

An aggregation level for the spatial dimension. Can be any level available via superAggregateX.

Value

Bioenergy demand as MAgPIE object (EJ/yr)

Bioenergy demand variables

Name Unit Meta
Demand|Bioenergy EJ/yr Total bioenergy demand
Demand|Bioenergy|++|2nd generation EJ/yr Second generation bioenergy demand (dedicated crops and residues)
Demand|Bioenergy|++|1st generation EJ/yr First generation bioenergy demand (oils, ethanol)
Demand|Bioenergy|++|Traditional Burning EJ/yr Traditional biomass burning demand

Author(s)

Florian Humpenoeder, Kristine Karstens

Examples

## Not run: 
    x <- reportDemandBioenergy()
  
## End(Not run)

reportDemandNr

Description

Similar to reportDemand, but for nitrogen. reports Demand for Food, Feed, Processing, Material, Bioenergy, Seed and Supply Chain Loss

Usage

reportDemandNr(gdx, detail = FALSE)

Arguments

gdx

GDX file
detail

if detail=F, the subcategories of groups are not reported (e.g. "soybean" within "oilcrops")

Value

demand as MAgPIE object (Mt DM)

Nitrogen demand variables

Name Unit Meta
Demand|Food Mt Nr/yr Nitrogen demand for food
Demand|Feed Mt Nr/yr Nitrogen demand for feed
Demand|Processing Mt Nr/yr Nitrogen demand for processing
Demand|Bioenergy Mt Nr/yr Nitrogen demand for bioenergy
Demand|Material Mt Nr/yr Nitrogen demand for materials

Author(s)

Benjamin Leon Bodirsky

Examples

## Not run: 
    x <- reportDemand()
  
## End(Not run)

reportEmissions

Description

reports GHG emissions

Usage

reportEmissions(gdx, level = "regglo", storageWood = TRUE)

Arguments

gdx

GDX file
level

An aggregation level for the spatial dimension. Can be any level available via superAggregateX.
storageWood

Accounting for long term carbon storage in wood products. Default is TRUE.

Value

GHG emissions as MAgPIE object (Unit: Mt CO2/yr, Mt N2O/yr, and Mt CH4/yr, for cumulative emissions Gt CO2)

CO2 land-use change emissions (yearly)

Name Unit Meta
Emissions|CO2|Land Mt CO2/yr Net CO2 flux from land use and land management, including environmental effects on managed land
Emissions|CO2|Land|+|Indirect Mt CO2/yr Carbon sink on managed land from environmental change (CO2 fertilization, climate, N deposition); managed land proxy following Grassi et al. 2021
Emissions|CO2|Land|+|Land-use Change Mt CO2/yr Net CO2 flux from land-use change, harvest and regrowth
Emissions|CO2|Land|Land-use Change|+|Deforestation Mt CO2/yr CO2 emissions from permanent deforestation
Emissions|CO2|Land|Land-use Change|Deforestation|+|Primary forests Mt CO2/yr CO2 emissions from deforestation of primary forests
Emissions|CO2|Land|Land-use Change|Deforestation|+|Secondary forests Mt CO2/yr CO2 emissions from deforestation of secondary forests
Emissions|CO2|Land|Land-use Change|Deforestation|+|Forestry plantations Mt CO2/yr CO2 emissions from deforestation of forestry plantations
Emissions|CO2|Land|Land-use Change|Deforestation|+|Cropland Tree Cover Mt CO2/yr CO2 emissions from removal of trees on cropland
Emissions|CO2|Land|Land-use Change|+|Forest degradation Mt CO2/yr CO2 emissions from forest degradation and shifting cultivation
Emissions|CO2|Land|Land-use Change|Forest degradation|+|Primary forests Mt CO2/yr CO2 emissions from degradation of primary forests
Emissions|CO2|Land|Land-use Change|Forest degradation|+|Secondary forests Mt CO2/yr CO2 emissions from degradation of secondary forests
Emissions|CO2|Land|Land-use Change|+|Other land conversion Mt CO2/yr CO2 emissions from conversion of other natural land
Emissions|CO2|Land|Land-use Change|+|Regrowth Mt CO2/yr CO2 removals from forest regrowth (negative values)
Emissions|CO2|Land|Land-use Change|Regrowth|+|CO2-price AR Mt CO2/yr CO2 removals from afforestation/reforestation driven by CO2 price
Emissions|CO2|Land|Land-use Change|Regrowth|+|NPI_NDC AR Mt CO2/yr CO2 removals from afforestation/reforestation under national policies
Emissions|CO2|Land|Land-use Change|Regrowth|+|Timber Plantations Mt CO2/yr CO2 removals from timber plantation regrowth
Emissions|CO2|Land|Land-use Change|Regrowth|+|Secondary Forest Mt CO2/yr CO2 removals from secondary forest regrowth
Emissions|CO2|Land|Land-use Change|Regrowth|+|Cropland Tree Cover Mt CO2/yr CO2 removals from trees on cropland
Emissions|CO2|Land|Land-use Change|Regrowth|+|Other Land Mt CO2/yr CO2 removals from regrowth on other land
Emissions|CO2|Land|Land-use Change|+|Peatland Mt CO2/yr Net CO2 flux from managed peatlands
Emissions|CO2|Land|Land-use Change|Peatland|+|Positive Mt CO2/yr CO2 emissions from drained peatlands
Emissions|CO2|Land|Land-use Change|Peatland|+|Negative Mt CO2/yr CO2 removals from rewetted peatlands
Emissions|CO2|Land|Land-use Change|+|Soil Mt CO2/yr Net CO2 flux from soil organic matter changes
Emissions|CO2|Land|Land-use Change|Soil|++|Emissions Mt CO2/yr CO2 emissions from soil carbon loss
Emissions|CO2|Land|Land-use Change|Soil|++|Withdrawals Mt CO2/yr CO2 removals from soil carbon accumulation
Emissions|CO2|Land|Land-use Change|Soil|+|Land Conversion Mt CO2/yr Net soil CO2 flux from land-use conversion
Emissions|CO2|Land|Land-use Change|Soil|+|Cropland management Mt CO2/yr Net soil CO2 flux from cropland management changes
Emissions|CO2|Land|Land-use Change|Soil|+|Soil Carbon Management Mt CO2/yr Net soil CO2 flux from explicit soil carbon management
Emissions|CO2|Land|Land-use Change|+|Wood Harvest Mt CO2/yr CO2 emissions from wood harvest
Emissions|CO2|Land|Land-use Change|Wood Harvest|+|Timber Plantations Mt CO2/yr CO2 emissions from harvest in timber plantations
Emissions|CO2|Land|Land-use Change|Wood Harvest|+|Primary Forest Mt CO2/yr CO2 emissions from harvest in primary forests
Emissions|CO2|Land|Land-use Change|Wood Harvest|+|Secondary Forest Mt CO2/yr CO2 emissions from harvest in secondary forests
Emissions|CO2|Land|Land-use Change|Wood Harvest|+|Other Land Mt CO2/yr CO2 emissions from harvest on other land
Emissions|CO2|Land|Land-use Change|+|Timber Mt CO2/yr Net CO2 flux from harvested wood products (storage minus release)
Emissions|CO2|Land|Land-use Change|Timber|+|Storage in HWP Mt CO2/yr CO2 stored in harvested wood products (negative values)
Emissions|CO2|Land|Land-use Change|Timber|+|Release from HWP Mt CO2/yr CO2 released from decay of harvested wood products
Emissions|CO2|Land|Land-use Change|+|Residual Mt CO2/yr Residual CO2 flux not captured in other categories
Emissions|CO2|Land|Land-use Change|Residual|+|Positive Mt CO2/yr Positive residual CO2 flux
Emissions|CO2|Land|Land-use Change|Residual|+|Negative Mt CO2/yr Negative residual CO2 flux
Emissions|CO2|Land|++|Above Ground Carbon Mt CO2/yr CO2 flux from above ground carbon pools
Emissions|CO2|Land|++|Below Ground Carbon Mt CO2/yr CO2 flux from below ground carbon pools

CO2 land carbon sink (yearly)

Name Unit Meta
Emissions|CO2|Land Carbon Sink|Grassi|Managed Land|Managed Forest Mt CO2/yr Carbon sink in managed forests following Grassi et al. 2021
Emissions|CO2|Land Carbon Sink|LPJmL Mt CO2/yr Total carbon sink from LPJmL vegetation model
Emissions|CO2|Land Carbon Sink|LPJmL|+|Managed Land Mt CO2/yr Carbon sink on managed land from LPJmL
Emissions|CO2|Land Carbon Sink|LPJmL|+|Unmanaged Land Mt CO2/yr Carbon sink on unmanaged land from LPJmL

CO2 land-use change emissions (cumulative)

Name Unit Meta
Emissions|CO2|Land|Cumulative Gt CO2 Cumulative net CO2 flux from land use and land management, including environmental effects on managed land
Emissions|CO2|Land|Cumulative|+|Indirect Gt CO2 Cumulative carbon sink on managed land from environmental change
Emissions|CO2|Land|Cumulative|+|Land-use Change Gt CO2 Cumulative net CO2 flux from land-use change, harvest and regrowth
Emissions|CO2|Land|Cumulative|Land-use Change|+|Deforestation Gt CO2 Cumulative CO2 emissions from deforestation and degradation
Emissions|CO2|Land|Cumulative|Land-use Change|+|Regrowth Gt CO2 Cumulative CO2 removals from regrowth
Emissions|CO2|Land|Cumulative|Land-use Change|+|Other land conversion Gt CO2 Cumulative CO2 emissions from other land conversion
Emissions|CO2|Land|Cumulative|Land-use Change|+|Peatland Gt CO2 Cumulative net CO2 flux from peatland
Emissions|CO2|Land|Cumulative|Land-use Change|+|Soil Gt CO2 Cumulative net CO2 flux from soil
Emissions|CO2|Land|Cumulative|Land-use Change|+|Wood Harvest Gt CO2 Cumulative CO2 emissions from wood harvest
Emissions|CO2|Land|Cumulative|Land-use Change|+|Timber Gt CO2 Cumulative net CO2 flux from harvested wood products
Emissions|CO2|Land|Cumulative|Land-use Change|+|Residual Gt CO2 Cumulative residual CO2 flux

N2O emissions variables

Name Unit Meta
Emissions|N2O|Land Mt N2O/yr Total N2O emissions from agriculture, forestry and other land use (IPCC category 3)
Emissions|N2O|Land|+|Agriculture Mt N2O/yr N2O emissions from the agriculture sector
Emissions|N2O|Land|Agriculture|+|Animal Waste Management Mt N2O/yr N2O emissions from animal waste management systems
Emissions|N2O|Land|Agriculture|+|Agricultural Soils Mt N2O/yr N2O emissions from agricultural soils
Emissions|N2O|Land|Agriculture|Agricultural Soils|+|Inorganic Fertilizers Mt N2O/yr N2O emissions from inorganic fertilizer application
Emissions|N2O|Land|Agriculture|Agricultural Soils|Inorganic Fertilizers|+|Cropland Mt N2O/yr N2O emissions from fertilizer on cropland
Emissions|N2O|Land|Agriculture|Agricultural Soils|Inorganic Fertilizers|+|Pasture Mt N2O/yr N2O emissions from fertilizer on pasture
Emissions|N2O|Land|Agriculture|Agricultural Soils|+|Manure applied to Croplands Mt N2O/yr N2O emissions from manure applied to croplands
Emissions|N2O|Land|Agriculture|Agricultural Soils|+|Decay of Crop Residues Mt N2O/yr N2O emissions from decay of crop residues
Emissions|N2O|Land|Agriculture|Agricultural Soils|+|Soil Organic Matter Loss Mt N2O/yr N2O emissions from soil organic matter loss
Emissions|N2O|Land|Agriculture|Agricultural Soils|+|Pasture Mt N2O/yr N2O emissions from pasture soils (manure deposited by grazing animals)
Emissions|N2O|Land|+|Peatland Mt N2O/yr N2O emissions from managed peatlands
Emissions|N2O|Land|Peatland|+|Managed Mt N2O/yr N2O emissions from managed peatlands (excluding intact)
Emissions|N2O|Land|+|Biomass Burning Mt N2O/yr N2O emissions from biomass burning
Emissions|N2O|Land|Biomass Burning|+|Burning of Crop Residues Mt N2O/yr N2O emissions from burning of crop residues

CH4 emissions variables

Name Unit Meta
Emissions|CH4|Land Mt CH4/yr Total CH4 emissions from agriculture, forestry and other land use
Emissions|CH4|Land|+|Agriculture Mt CH4/yr CH4 emissions from agriculture sector
Emissions|CH4|Land|Agriculture|+|Rice Mt CH4/yr CH4 emissions from flooded rice cultivation
Emissions|CH4|Land|Agriculture|+|Animal waste management Mt CH4/yr CH4 emissions from animal waste management systems
Emissions|CH4|Land|Agriculture|+|Enteric fermentation Mt CH4/yr CH4 emissions from enteric fermentation of livestock
Emissions|CH4|Land|+|Peatland Mt CH4/yr CH4 emissions from managed peatlands
Emissions|CH4|Land|Peatland|+|Managed Mt CH4/yr CH4 emissions from managed peatlands (excluding intact)
Emissions|CH4|Land|+|Biomass Burning Mt CH4/yr CH4 emissions from biomass burning
Emissions|CH4|Land|Biomass Burning|+|Burning of Crop Residues Mt CH4/yr CH4 emissions from burning of crop residues

GWP emissions variables

Name Unit Meta
Emissions|GWP100AR6|Land Gt CO2e/yr Total GHG emissions from land use in CO2-equivalents using AR6 GWP100
Emissions|GWP100AR6|Land|Cumulative Gt CO2e Cumulative total GHG emissions from land use
Emissions|CH4_GWP100AR6|Land Mt CO2e/yr CH4 emissions in CO2-equivalents using AR6 GWP100 (factor 27)
Emissions|N2O_GWP100AR6|Land Mt CO2e/yr N2O emissions in CO2-equivalents using AR6 GWP100 (factor 273)

Author(s)

Florian Humpenoeder, Benjamin Leon Bodirsky, Michael Crawford

Examples

## Not run: 
x <- reportEmissions(gdx)

## End(Not run)

reportEmissionsBeforeTechnicalMitigation

Description

reports GHG emissions before technical mitigation. Technical abatement includes all abatement done in the MACC curves, but exclude endogenous mitigation. These emissions are NOT the standard reporting emissions, but used for special purposes like remind-magpie coupling.

Usage

reportEmissionsBeforeTechnicalMitigation(gdx, level = "regglo")

Arguments

gdx

GDX file
level

aggregation level of returned data ("regglo" by default)

Value

MAgPIE object (Unit: Mt CO2/yr, Mt N2O/yr and Mt CH4/yr)

Emissions before technical mitigation variables

Name Unit Meta
Emissions before technical mitigation|N2O|Land|+|Agriculture Mt N2O/yr N2O emissions before MACC abatement
Emissions before technical mitigation|N2O|Land|Agriculture|+|Animal Waste Management Mt N2O/yr N2O from animal waste before mitigation
Emissions before technical mitigation|N2O|Land|Agriculture|+|Agricultural Soils Mt N2O/yr N2O from agricultural soils before mitigation
Emissions before technical mitigation|CH4|Land|+|Agriculture Mt CH4/yr CH4 emissions before MACC abatement
Emissions before technical mitigation|CH4|Land|Agriculture|+|Enteric fermentation Mt CH4/yr CH4 from enteric fermentation before mitigation

Author(s)

Florian Humpenoeder, Benjamin Leon Bodirsky

Examples

## Not run: 
    x <- reportEmissionsBeforeTechnicalMitigation(gdx)
  
## End(Not run)

reportExpenditureFoodIndex

Description

reports food expenditure index and food expenditure index corrected for emission costs

Usage

reportExpenditureFoodIndex(
  gdx,
  baseyear = "y2010",
  basketyear = "y2010",
  level = "regglo"
)

Arguments

gdx

GDX file
baseyear

Baseyear of the price index
basketyear

Year of reference food basket (should be in the past for comparison of different runs to have identical and comparable food basket)
level

aggregation level of returned data ("regglo" by default)

Value

Food expenditure index as MAgPIE object

Food expenditure index variables

Name Unit Meta
Prices|Food Expenditure Index Index 2010=100 Food expenditure index (all food products)
Prices|Food Expenditure Index|Plant-based food products Index 2010=100 Food expenditure index for plant-based products
Prices|Food Expenditure Index|Livestock food products Index 2010=100 Food expenditure index for livestock products
Prices|Food Expenditure Index corrected for ghg costs Index 2010=100 Food expenditure index corrected for GHG costs
Prices|Agricultural Primary Products Expenditure Index Index 2010=100 Agricultural primary products expenditure index

Author(s)

Felicitas Beier

Examples

## Not run: 
x <- reportPriceFoodIndex(gdx)

## End(Not run)

reportExtraResidueEmissions.R

Description

reads residue biomass from a MAgPIE gdx file and multiplies DM by emission factors from GFED

Usage

reportExtraResidueEmissions(gdx, level = "reg")

Arguments

gdx

GDX file
level

Level of regional aggregation; "reg" (regional), "glo" (global), "regglo" (regional and global)

Value

emissions as MAgPIE object (unit: Mt X/yr, plus cumulative Mt X/yr)

Residue burning emission variables

Name Unit Meta
Emissions|CO2|Land|Biomass Burning|+|Burning of Crop Residues Mt CO2/yr CO2 emissions from residue burning
Emissions|CO|Land|Biomass Burning|+|Burning of Crop Residues Mt CO/yr CO emissions from residue burning
Emissions|BC|Land|Biomass Burning|+|Burning of Crop Residues Mt BC/yr Black carbon from residue burning
Emissions|VOC|Land|Biomass Burning|+|Burning of Crop Residues Mt VOC/yr VOC emissions from residue burning
Emissions|CO2|Land|Cumulative|Biomass Burning|+|Burning of Crop Residues Mt CO2 Cumulative CO2 from residue burning

Author(s)

Michael Crawford

Examples

## Not run: 
    x <- reportExtraResidueEmissions(gdx, level = "glo")
  
## End(Not run)

reportFactorCostShares

Description

reports labor and capital cost share out of factor costs from MAgPIE results

Usage

reportFactorCostShares(gdx, type = "optimization", level = "regglo")

Arguments

gdx

GDX file
type

  • "requirements": shares from factor requirements

  • "optimization": cost shares between labor and capital costs in optimization

  • "accounting": cost shares based on accounting of labor and capital costs

level

spatial aggregation: "reg", "glo", "regglo"

Value

labor and capital cost shares as MAgPIE object

Factor cost share variables

Name Unit Meta
Factor cost shares optimization|Crop products|+|Labor cost share % Labor cost share in crop production
Factor cost shares optimization|Crop products|+|Capital cost share % Capital cost share in crop production
Factor cost shares optimization|Livestock products|+|Labor cost share % Labor cost share in livestock production
Factor cost shares optimization|Livestock products|+|Capital cost share % Capital cost share in livestock production

Author(s)

Debbora Leip

Examples

## Not run: 
x <- reportFactorCostShares(gdx)

## End(Not run)

reportFeed

Description

reportes feed demand by animal type

Usage

reportFeed(gdx, detail = TRUE, level = "regglo")

Arguments

gdx

GDX file
detail

if detail=F, the subcategories of groups are not reported (e.g. "soybean" within "oilcrops")
level

An aggregation level for the spatial dimension. Can be any level available via superAggregateX.

Value

feed demand as MAgPIE object (Mt DM)

Feed demand variables

Name Unit Meta
Demand|Feed|++|Feed for Ruminant meat Mt DM/yr Feed demand for ruminant meat production
Demand|Feed|++|Feed for Dairy Mt DM/yr Feed demand for dairy production
Demand|Feed|++|Feed for Pig meat Mt DM/yr Feed demand for pig meat production
Demand|Feed|++|Feed for Poultry meat Mt DM/yr Feed demand for poultry meat production
Demand|Feed|++|Feed for Eggs Mt DM/yr Feed demand for egg production
Demand|Feed|++|Feed for Aquaculture Mt DM/yr Feed demand for aquaculture

Author(s)

Isabelle Weindl

Examples

## Not run: 
    x <- reportFeed()
  
## End(Not run)

reportFeedConversion

Description

reportes feed demand by animal type

Usage

reportFeedConversion(gdx, livestockSystem = TRUE, balanceflow = FALSE)

Arguments

gdx

GDX file
livestockSystem

if TRUE, ruminant products and poultry products are aggregated
balanceflow

If true, feed includes the calibration balanceflow

Value

feed demand as MAgPIE object (Mt DM)

Feed conversion variables

Name Unit Meta
Productivity|Feed conversion GE per GE Overall feed conversion efficiency (gross energy)
Productivity|Feed conversion|Ruminant meat and dairy GE per GE Feed conversion for ruminant products
Productivity|Feed conversion|Poultry meat and eggs GE per GE Feed conversion for poultry products
Productivity|Feed conversion|Pig meat GE per GE Feed conversion for pig meat
Productivity|Roughage share|Ruminant meat and dairy GE per GE Share of roughage in ruminant feed
Productivity|Pasture share|Ruminant meat and dairy GE per GE Share of pasture in ruminant feed

Author(s)

Benjamin Bodirsky

Examples

## Not run: 
    x <- reportFeed()
  
## End(Not run)

reportFertilizerNitrogen

Description

Reports inorganic nitrogen application on crops

Usage

reportFertilizerNitrogen(gdx, level = "regglo")

Arguments

gdx

GDX file
level

level of output

Fertilizer nitrogen variables

Name Unit Meta
Resources|Nitrogen|Inorganic Fertilizer Application Mt Nr/yr Total inorganic nitrogen fertilizer application
Resources|Nitrogen|Inorganic Fertilizer Application|+|Cereals Mt Nr/yr Nitrogen fertilizer application on cereals
Resources|Nitrogen|Inorganic Fertilizer Application|+|Oilcrops Mt Nr/yr Nitrogen fertilizer application on oilcrops

Author(s)

David M Chen

See Also

NitrogenBudget

Examples

## Not run: 
x <- reportFertilizerNitrogen(gdx)

## End(Not run)

reportFireEmissions.R

Description

reads land cover data and deforestation data to produce future estimates of fire emissions based on extrapolating GFED data from 2003-2016

Usage

reportFireEmissions(gdx, level = "reg")

Arguments

gdx

GDX file
level

Level of regional aggregation; "reg" (regional), "glo" (global), "regglo" (regional and global)

Value

emissions as MAgPIE object (unit: Mt X/yr, plus cumulative Mt X/yr)

Fire emission variables

Name Unit Meta
Emissions|CO2|AFOLU|Land|Fires Mt CO2/yr Total CO2 emissions from fires
Emissions|CO2|AFOLU|Land|Fires|+|Forest Burning Mt CO2/yr CO2 from forest fires
Emissions|CO2|AFOLU|Land|Fires|Forest Burning|+|Boreal Forest Mt CO2/yr CO2 from boreal
forest fires
Emissions|CO2|AFOLU|Land|Fires|Forest Burning|+|Tropical Forest Mt CO2/yr CO2 from tropical
deforestation fires
Emissions|CO2|AFOLU|Land|Fires|+|Grassland Burning Mt CO2/yr CO2 from grassland/savanna
fires
Emissions|CO2|AFOLU|Land|Fires|+|Peat Burning Mt CO2/yr CO2 from peat fires

Author(s)

Michael Crawford

Examples

## Not run: 
    x <- reportFireEmissions(gdx, level = "glo")
  
## End(Not run)

reportFit

Description

reports fit and error indicators compared to initial values

Usage

reportFit(gdx, type = "MAPE", level = "cell")

Arguments

gdx

GDX file
type

type of indicator. Options: R2, MAE, MPE (mean percentage error - bias), MAPE (mean absolute percentage error)
level

level at which the regional and global bias should be reported. Options "cell" or "grid"

Value

Selected error indicator

Cluster-level fit indicator variables

Name Unit Meta
Fit|Cluster|Land Cover MAPE/MAE/MPE Fit indicator for overall land cover
Fit|Cluster|Land Cover|Cropland MAPE/MAE/MPE Fit indicator for cropland
Fit|Cluster|Land Cover|Pastures and Rangelands MAPE/MAE/MPE Fit indicator for pasture (when no range distinction)
Fit|Cluster|Land Cover|Managed pastures MAPE/MAE/MPE Fit indicator for managed pastures (when range available)
Fit|Cluster|Land Cover|Rangelands MAPE/MAE/MPE Fit indicator for rangelands (when range available)
Fit|Cluster|Land Cover|Urban Area MAPE/MAE/MPE Fit indicator for urban area
Fit|Cluster|Land Cover|Other Land MAPE/MAE/MPE Fit indicator for other land
Fit|Cluster|Land Cover|Forest|Natural Forest|Primary Forest MAPE/MAE/MPE Fit indicator for primary forest
Fit|Cluster|Land Cover|Forest|Natural Forest|Secondary Forest MAPE/MAE/MPE Fit indicator for secondary forest
Fit|Cluster|Land Cover|Forest|Planted Forest MAPE/MAE/MPE Fit indicator for planted forest
Fit|Cluster|Land Cover|Cropland|{crop} MAPE/MAE/MPE Fit indicator for individual crop types

Grid-level fit indicator variables

Name Unit Meta
Fit|Grid|Land Cover MAPE/MAE/MPE Grid-level fit indicator for overall land cover
Fit|Grid|Land Cover|Cropland MAPE/MAE/MPE Grid-level fit indicator for cropland
Fit|Grid|Land Cover|Pastures and Rangelands MAPE/MAE/MPE Grid-level fit indicator for pasture
Fit|Grid|Land Cover|Managed pastures MAPE/MAE/MPE Grid-level fit indicator for managed pastures (when range available)
Fit|Grid|Land Cover|Rangelands MAPE/MAE/MPE Grid-level fit indicator for rangelands (when range available)
Fit|Grid|Land Cover|Urban Area MAPE/MAE/MPE Grid-level fit indicator for urban area
Fit|Grid|Land Cover|Other Land MAPE/MAE/MPE Grid-level fit indicator for other land
Fit|Grid|Land Cover|Forest|Natural Forest|Primary Forest MAPE/MAE/MPE Grid-level fit indicator for primary forest
Fit|Grid|Land Cover|Forest|Natural Forest|Secondary Forest MAPE/MAE/MPE Grid-level fit indicator for secondary forest
Fit|Grid|Land Cover|Forest|Planted Forest MAPE/MAE/MPE Grid-level fit indicator for planted forest

Author(s)

Edna Molina Bacca, Patrick v. Jeetze

Examples

## Not run: 
    x <- reportFit(gdx,type)
  
## End(Not run)

reportFoodExpenditure

Description

reports per-capita calories food supply (including household waste)

Usage

reportFoodExpenditure(gdx, detail = FALSE, level = "regglo")

Arguments

gdx

GDX file
detail

if detail=F, the subcategories of groups are not reported (e.g. "soybean" within "oilcrops")
level

spatial aggregation: "reg", "glo", "regglo", "iso"

Value

per-capita calories as MAgPIE object (kcal/cap/day)

Food expenditure variables

Name Unit Meta
Household Expenditure|Agricultural Primary Products|Expenditure US$2017/capita Per-capita expenditure on agricultural primary products
Household Expenditure|Agricultural Primary Products|Expenditure Share US$2017/US$2017 Share of income spent on agricultural primary products
Household Expenditure|Food|Expenditure US$2017/capita Per-capita food expenditure (value added)
Household Expenditure|Food|Expenditure Share US$2017/capita Share of income spent on food (value added)

Author(s)

Benjamin Leon Bodirsky

Examples

## Not run: 
    x <- reportFoodExpenditure(gdx)
  
## End(Not run)

reportForestYield

Description

reports MAgPIE harvested area for timber.

Usage

reportForestYield(gdx, level = "regglo")

Arguments

gdx

GDX file
level

aggregation level of returned data ("regglo" by default)

Value

Yield from Forests for timber production

Forest yield variables

Name Unit Meta
Timber Yields|Harvest|Forestry m3 per ha Timber yield from plantation forestry
Timber Yields|Harvest|Primary forest m3 per ha Timber yield from primary forest harvesting
Timber Yields|Harvest|Secondary forest m3 per ha Timber yield from secondary forest harvesting

Author(s)

Abhijeet Mishra, Florian Humpenoeder

Examples

## Not run: 
    x <- reportForestYield(gdx)
  
## End(Not run)

reportGridCroparea

Description

reports Croparea from gridded (disaggregated) output

Usage

reportGridCroparea(gdx)

Arguments

gdx

GDX file

Value

area of cropland as MAgPIE object (million ha)

Grid-level croparea by irrigation

This function produces grid-level (0.5 degree) croparea data by crop type and irrigation system. Variable names follow the reportingnames mapping (e.g., Cereals.Rainfed, Oilcrops.Irrigated).

Author(s)

Jannes Breier

Examples

## Not run: 
    x <- reportGridCroparea(gdx)
  
## End(Not run)

reportGridLand

Description

reports land-use from gridded (disaggregated) output

Usage

reportGridLand(gdx)

Arguments

gdx

GDX file

Value

land-use as MAgPIE object (million ha)

Grid-level land use

This function produces grid-level (0.5 degree) land use data for land cover categories (cropland, pasture, forest, urban, other land). Variable names follow the reportingnames mapping.

Author(s)

Jannes Breier

Examples

## Not run: 
    x <- reportGridLand(gdx)
  
## End(Not run)

reportGridManureExcretion

Description

reports Manure with reprting names on grid level.

Usage

reportGridManureExcretion(gdx)

Arguments

gdx

GDX file

Value

MAgPIE object

Grid-level manure excretion

This function produces grid-level (0.5 degree) manure excretion and management data. Includes total manure, breakdown by AWMS and livestock type, and losses from confinement.

Author(s)

Benjamin Leon Bodirsky

Examples

## Not run: 
x <- reportGridManureExcretion(gdx)

## End(Not run)

reportGrowingStock

Description

reports Growing stocks for woody materials

Usage

reportGrowingStock(
  gdx,
  indicator = "relative",
  detail = FALSE,
  level = "regglo"
)

Arguments

gdx

GDX file
indicator

If the reported numbers are relative (mio m3/ha) or absolute (mio. m3). Default is relative.
detail

if detail=FALSE, the subcategories of groups are not reported.
level

aggregation level of returned data ("regglo" by default)

Value

production as MAgPIE object. Unit: see names

Growing stock variables

Name Unit Meta
Resources|Growing Stock|relative|Forest m3/ha Relative growing stock in forests
Resources|Growing Stock|relative|Plantations m3/ha Relative growing stock in plantations
Resources|Growing Stock|absolute|Forest Mm3 Absolute growing stock in forests
Resources|Growing Stock|absolute|Plantations Mm3 Absolute growing stock in plantations

Author(s)

Abhijeet Mishra

Examples

## Not run: 
    x <- reportGrowingStock(gdx)
  
## End(Not run)

reportharvested_area_timber

Description

reports MAgPIE harvested area for timber.

Usage

reportharvested_area_timber(gdx, level = "regglo")

Arguments

gdx

GDX file
level

aggregation level of returned data ("regglo" by default)

Value

Area harvested for timber production

Timber harvested area variables

Name Unit Meta
Resources|Timber operations|Harvested area for timber|Forestry Mha per yr Area harvested from managed forests
Resources|Timber operations|Harvested area for timber|Primary forest Mha per yr Area harvested from primary forests
Resources|Timber operations|Harvested area for timber|Secondary forest Mha per yr Area harvested from secondary forests

Author(s)

Abhijeet Mishra

Examples

## Not run: 
    x <- reportharvested_area_timber(gdx)
  
## End(Not run)

reportHourlyLaborCosts

Description

reports hourly labor costs in agriculture from MAgPIE results

Usage

reportHourlyLaborCosts(gdx, level = "regglo")

Arguments

gdx

GDX file
level

spatial aggregation: "reg", "glo", "regglo"

Value

hourly labor costs as MAgPIE object

Hourly labor cost variables

Name Unit Meta
Labor|Wages|Hourly labor costs US$2017/h Hourly labor costs in agriculture

Author(s)

Debbora Leip

Examples

## Not run: 
    x <- reportHourlyLaborCosts(gdx)
  
## End(Not run)

reportHunger

Description

Calculates the share of people living in hunger.

Usage

reportHunger(gdx)

Arguments

gdx

GDX file

Value

magpie object with hunger (mio people) or hunger share

Hunger variables

Name Unit Meta
Food Supply|Calorie Supply|Undernourished Mio People Number of undernourished people
Food Supply|Calorie Supply|Share of population undernourished People/People Share of population undernourished

Author(s)

Benjamin Leon Bodirsky

Examples

## Not run: 
    x <- reportHunger(gdx)
  
## End(Not run)

reportIncome

Description

reports income

Usage

reportIncome(gdx, type = "ppp", level = "regglo")

Arguments

gdx

GDX file
type

ppp for purchase power parity, mer for market exchange rate
level

spatial aggregation: "reg", "glo", "regglo", "iso"

Value

Annual per capita and total income as MAgPIE object (US$2017 MER/cap/yr and million US$17 PPP/yr)

Income variables

Name Unit Meta
Income per capita PPP US$2017 PPP/cap/yr GDP per capita converted to US$2017 using purchasing power parity (PPP)
Income PPP million US$2017 PPP/yr GDP converted to US$2017 using purchasing power parity (PPP)
Income per capita MER US$2017 MER/cap/yr GDP per capita converted to US$2017 at market exchange rate (MER)
Income MER million US$2017 MER/yr GDP converted to US$2017 at market exchange rate (MER)

Author(s)

Florian Humpenoeder, Isabelle Weindl, Felicitas Beier

Examples

## Not run: 
x <- reportIncome(gdx)

## End(Not run)

reportIntakeDetailed

Description

reports detailed or aggregated per-capita kcal intake including exogenous scenarios

Usage

reportIntakeDetailed(gdx, detail = TRUE, level = "regglo")

Arguments

gdx

GDX file
detail

if detail=F, the subcategories of groups are not reported (e.g. "soybean" within "oilcrops")
level

spatial aggregation: "reg", "glo", "regglo", "iso"

Value

per-capita calorie intake as MAgPIE object (kcal/cap/day)

Calorie intake variables

Name Unit Meta
Nutrition|Calorie Intake kcal/capita/day Total per-capita calorie intake (excluding waste)
Nutrition|Calorie Intake|+|Crops kcal/capita/day Calorie intake from crops
Nutrition|Calorie Intake|+|Livestock products kcal/capita/day Calorie intake from livestock products
Nutrition|Calorie Intake|+|Secondary products kcal/capita/day Calorie intake from secondary/processed products

Author(s)

Isabelle Weindl

Examples

## Not run: 
    x <- reportIntakeDetailed(gdx)
  
## End(Not run)

reportKcal

Description

reports per-capita calories food supply (including household waste)

Usage

reportKcal(gdx, detail = FALSE, level = "regglo")

Arguments

gdx

GDX file
detail

if detail=F, the subcategories of groups are not reported (e.g. "soybean" within "oilcrops")
level

spatial aggregation: "reg", "glo", "regglo", "iso"

Value

per-capita calories as MAgPIE object (kcal/cap/day)

Calorie supply variables

Name Unit Meta
Nutrition|Calorie Supply kcal/capita/day Total per-capita calorie supply (including household waste)
Nutrition|Calorie Supply|+|Crops kcal/capita/day Calorie supply from crops
Nutrition|Calorie Supply|+|Livestock products kcal/capita/day Calorie supply from livestock products
Nutrition|Calorie Supply|+|Secondary products kcal/capita/day Calorie supply from secondary/processed products

Author(s)

Benjamin Leon Bodirsky, Kristine karstens, Abhijeet Mishra

Examples

## Not run: 
    x <- reportKcal(gdx)
  
## End(Not run)

reportLaborCostsEmpl

Description

reports MAgPIE labor costs that go into employment calculation

Usage

reportLaborCostsEmpl(gdx, level = "regglo")

Arguments

gdx

GDX file
level

aggregation level of returned data ("regglo" by default)

Value

magpie object with labor costs

Labor costs for employment variables

Name Unit Meta
Labor|Employment|Labor costs linked to employment million US$2017/yr Total labor costs used for employment calculation

Author(s)

Debbora Leip

Examples

## Not run: 
    x <- reportLaborCostsEmpl(gdx)
  
## End(Not run)

reportLaborProductivity

Description

reports labor productivity in crop production

Usage

reportLaborProductivity(
  gdx,
  productAggr = TRUE,
  type = "physical",
  level = "regglo"
)

Arguments

gdx

GDX file
productAggr

Aggregate over products or not (boolean)
type

type of labor productivity, so far only physical (kg DM / h)
level

spatial aggregation: "reg", "glo", "regglo", "iso"

Value

labor productivity as MAgPIE object

Labor productivity variables

Name Unit Meta
Labor|Productivity|Physical labor productivity|Crop products kg DM per hour Physical labor productivity for crops

Author(s)

Debbora Leip

Examples

## Not run: 
    x <- reportLaborProductivity(gdx)
  
## End(Not run)

reportLandConservation

Description

reports land conservation areas

Usage

reportLandConservation(gdx, level = "regglo")

Arguments

gdx

GDX file
level

aggregation level of returned data ("regglo" by default)

Value

land conservation area in Mha

Total conserved land variables

Name Unit Meta
Resources|Land Cover Conserved|Cropland million ha Total conserved cropland area (protected + restored)
Resources|Land Cover Conserved|Pastures and Rangelands million ha Total conserved pasture area (protected + restored)
Resources|Land Cover Conserved|Forest|Planted Forest million ha Total conserved planted forest area (protected + restored)
Resources|Land Cover Conserved|Forest|Natural Forest|Primary Forest million ha Total conserved primary forest area (protected + restored)
Resources|Land Cover Conserved|Forest|Natural Forest|Secondary Forest million ha Total conserved secondary forest area (protected + restored)
Resources|Land Cover Conserved|Urban Area million ha Total conserved urban area (protected + restored)
Resources|Land Cover Conserved|Other Land million ha Total conserved other natural land area (protected + restored)

Protected land variables

Name Unit Meta
Resources|Land Cover Conserved|Cropland|+|Protected million ha Protected cropland area
Resources|Land Cover Conserved|Pastures and Rangelands|+|Protected million ha Protected pasture area
Resources|Land Cover Conserved|Forest|Planted Forest|+|Protected million ha Protected planted forest area
Resources|Land Cover Conserved|Forest|Natural Forest|Primary Forest|+|Protected million ha Protected primary forest area
Resources|Land Cover Conserved|Forest|Natural Forest|Secondary Forest|+|Protected million ha Protected secondary forest area
Resources|Land Cover Conserved|Urban Area|+|Protected million ha Protected urban area
Resources|Land Cover Conserved|Other Land|+|Protected million ha Protected other natural land area

Restored land variables

Name Unit Meta
Resources|Land Cover Conserved|Cropland|+|Restored million ha Restored cropland area
Resources|Land Cover Conserved|Pastures and Rangelands|+|Restored million ha Restored pasture area
Resources|Land Cover Conserved|Forest|Planted Forest|+|Restored million ha Restored planted forest area
Resources|Land Cover Conserved|Forest|Natural Forest|Primary Forest|+|Restored million ha Restored primary forest area
Resources|Land Cover Conserved|Forest|Natural Forest|Secondary Forest|+|Restored million ha Restored secondary forest area
Resources|Land Cover Conserved|Urban Area|+|Restored million ha Restored urban area
Resources|Land Cover Conserved|Other Land|+|Restored million ha Restored other natural land area

Annual restoration variables

Name Unit Meta
Resources|Land Cover Conserved|Cropland|Restored annually million ha/yr Annual cropland restoration rate
Resources|Land Cover Conserved|Pastures and Rangelands|Restored annually million ha/yr Annual pasture restoration rate
Resources|Land Cover Conserved|Forest|Planted Forest|Restored annually million ha/yr Annual planted forest restoration rate
Resources|Land Cover Conserved|Forest|Natural Forest|Primary Forest|Restored annually million ha/yr Annual primary forest restoration rate
Resources|Land Cover Conserved|Forest|Natural Forest|Secondary Forest|Restored annually million ha/yr Annual secondary forest restoration rate
Resources|Land Cover Conserved|Urban Area|Restored annually million ha/yr Annual urban area restoration rate
Resources|Land Cover Conserved|Other Land|Restored annually million ha/yr Annual other land restoration rate

Cumulative restoration variables

Name Unit Meta
Resources|Land Cover Conserved|Cropland|Restored cumulatively million ha since 2025 Cumulative cropland restoration since 2025
Resources|Land Cover Conserved|Pastures and Rangelands|Restored cumulatively million ha since 2025 Cumulative pasture restoration since 2025
Resources|Land Cover Conserved|Forest|Planted Forest|Restored cumulatively million ha since 2025 Cumulative planted forest restoration since 2025
Resources|Land Cover Conserved|Forest|Natural Forest|Primary Forest|Restored cumulatively million ha since 2025 Cumulative primary forest restoration since 2025
Resources|Land Cover Conserved|Forest|Natural Forest|Secondary Forest|Restored cumulatively million ha since 2025 Cumulative secondary forest restoration since 2025
Resources|Land Cover Conserved|Urban Area|Restored cumulatively million ha since 2025 Cumulative urban area restoration since 2025
Resources|Land Cover Conserved|Other Land|Restored cumulatively million ha since 2025 Cumulative other land restoration since 2025

Author(s)

Patrick v. Jeetze, Florian Humpenoeder

Examples

## Not run: 
x <- reportLandConservation(gdx)

## End(Not run)

reportLandTransitionMatrix

Description

reports land transition matrix with gross land-use change flows between all land types

Usage

reportLandTransitionMatrix(gdx, level = "regglo")

Arguments

gdx

GDX file
level

The aggregation level to be used ("regglo" by default)

Value

land transition matrix as MAgPIE object (Mha/yr)

Total land transition variables

Name Unit Meta
Resources|Land Transitions Mha/yr Total gross land-use change (sum of all off-diagonal transitions)

From Cropland variables

Name Unit Meta
Resources|Land Transitions|+|From Cropland Mha/yr Total annual gross land-use change from cropland to other land types
Resources|Land Transitions|From Cropland|+|To Pastures and Rangelands Mha/yr Annual gross transition from cropland to pastures and rangelands
Resources|Land Transitions|From Cropland|+|To Urban Area Mha/yr Annual gross transition from cropland to urban area
Resources|Land Transitions|From Cropland|+|To Other Land Mha/yr Annual gross transition from cropland to other land
Resources|Land Transitions|From Cropland|+|To Forest Mha/yr Annual gross transition from cropland to forest (sum of planted, primary, and secondary forest)
Resources|Land Transitions|From Cropland|To Forest|+|To Planted Forest Mha/yr Annual gross transition from cropland to planted forest
Resources|Land Transitions|From Cropland|To Forest|+|To Primary Forest Mha/yr Annual gross transition from cropland to primary forest (structurally zero)
Resources|Land Transitions|From Cropland|To Forest|+|To Secondary Forest Mha/yr Annual gross transition from cropland to secondary forest

From Pastures and Rangelands variables

Name Unit Meta
Resources|Land Transitions|+|From Pastures and Rangelands Mha/yr Total annual gross land-use change from pastures and rangelands to other land types
Resources|Land Transitions|From Pastures and Rangelands|+|To Cropland Mha/yr Annual gross transition from pastures and rangelands to cropland
Resources|Land Transitions|From Pastures and Rangelands|+|To Urban Area Mha/yr Annual gross transition from pastures and rangelands to urban area
Resources|Land Transitions|From Pastures and Rangelands|+|To Other Land Mha/yr Annual gross transition from pastures and rangelands to other land
Resources|Land Transitions|From Pastures and Rangelands|+|To Forest Mha/yr Annual gross transition from pastures and rangelands to forest (sum of planted, primary, and secondary forest)
Resources|Land Transitions|From Pastures and Rangelands|To Forest|+|To Planted Forest Mha/yr Annual gross transition from pastures and rangelands to planted forest
Resources|Land Transitions|From Pastures and Rangelands|To Forest|+|To Primary Forest Mha/yr Annual gross transition from pastures and rangelands to primary forest (structurally zero)
Resources|Land Transitions|From Pastures and Rangelands|To Forest|+|To Secondary Forest Mha/yr Annual gross transition from pastures and rangelands to secondary forest

From Planted Forest variables

Name Unit Meta
Resources|Land Transitions|+|From Planted Forest Mha/yr Total annual gross land-use change from planted forest to other land types
Resources|Land Transitions|From Planted Forest|+|To Cropland Mha/yr Annual gross transition from planted forest to cropland
Resources|Land Transitions|From Planted Forest|+|To Pastures and Rangelands Mha/yr Annual gross transition from planted forest to pastures and rangelands
Resources|Land Transitions|From Planted Forest|+|To Urban Area Mha/yr Annual gross transition from planted forest to urban area
Resources|Land Transitions|From Planted Forest|+|To Other Land Mha/yr Annual gross transition from planted forest to other land
Resources|Land Transitions|From Planted Forest|+|To Forest Mha/yr Annual gross transition from planted forest to other forest types (sum of primary and secondary forest)
Resources|Land Transitions|From Planted Forest|To Forest|+|To Primary Forest Mha/yr Annual gross transition from planted forest to primary forest (structurally zero)
Resources|Land Transitions|From Planted Forest|To Forest|+|To Secondary Forest Mha/yr Annual gross transition from planted forest to secondary forest

From Primary Forest variables

Name Unit Meta
Resources|Land Transitions|+|From Primary Forest Mha/yr Total annual gross land-use change from primary forest to other land types
Resources|Land Transitions|From Primary Forest|+|To Cropland Mha/yr Annual gross transition from primary forest to cropland
Resources|Land Transitions|From Primary Forest|+|To Pastures and Rangelands Mha/yr Annual gross transition from primary forest to pastures and rangelands
Resources|Land Transitions|From Primary Forest|+|To Urban Area Mha/yr Annual gross transition from primary forest to urban area
Resources|Land Transitions|From Primary Forest|+|To Other Land Mha/yr Annual gross transition from primary forest to other land
Resources|Land Transitions|From Primary Forest|+|To Forest Mha/yr Annual gross transition from primary forest to other forest types (sum of planted and secondary forest)
Resources|Land Transitions|From Primary Forest|To Forest|+|To Planted Forest Mha/yr Annual gross transition from primary forest to planted forest
Resources|Land Transitions|From Primary Forest|To Forest|+|To Secondary Forest Mha/yr Annual gross transition from primary forest to secondary forest

From Secondary Forest variables

Name Unit Meta
Resources|Land Transitions|+|From Secondary Forest Mha/yr Total annual gross land-use change from secondary forest to other land types
Resources|Land Transitions|From Secondary Forest|+|To Cropland Mha/yr Annual gross transition from secondary forest to cropland
Resources|Land Transitions|From Secondary Forest|+|To Pastures and Rangelands Mha/yr Annual gross transition from secondary forest to pastures and rangelands
Resources|Land Transitions|From Secondary Forest|+|To Urban Area Mha/yr Annual gross transition from secondary forest to urban area
Resources|Land Transitions|From Secondary Forest|+|To Other Land Mha/yr Annual gross transition from secondary forest to other land
Resources|Land Transitions|From Secondary Forest|+|To Forest Mha/yr Annual gross transition from secondary forest to other forest types (sum of planted and primary forest)
Resources|Land Transitions|From Secondary Forest|To Forest|+|To Planted Forest Mha/yr Annual gross transition from secondary forest to planted forest
Resources|Land Transitions|From Secondary Forest|To Forest|+|To Primary Forest Mha/yr Annual gross transition from secondary forest to primary forest (structurally zero)

From Urban Area variables

Name Unit Meta
Resources|Land Transitions|+|From Urban Area Mha/yr Total annual gross land-use change from urban area to other land types
Resources|Land Transitions|From Urban Area|+|To Cropland Mha/yr Annual gross transition from urban area to cropland
Resources|Land Transitions|From Urban Area|+|To Pastures and Rangelands Mha/yr Annual gross transition from urban area to pastures and rangelands
Resources|Land Transitions|From Urban Area|+|To Other Land Mha/yr Annual gross transition from urban area to other land
Resources|Land Transitions|From Urban Area|+|To Forest Mha/yr Annual gross transition from urban area to forest (sum of planted, primary, and secondary forest)
Resources|Land Transitions|From Urban Area|To Forest|+|To Planted Forest Mha/yr Annual gross transition from urban area to planted forest
Resources|Land Transitions|From Urban Area|To Forest|+|To Primary Forest Mha/yr Annual gross transition from urban area to primary forest (structurally zero)
Resources|Land Transitions|From Urban Area|To Forest|+|To Secondary Forest Mha/yr Annual gross transition from urban area to secondary forest

From Other Land variables

Name Unit Meta
Resources|Land Transitions|+|From Other Land Mha/yr Total annual gross land-use change from other land to other land types
Resources|Land Transitions|From Other Land|+|To Cropland Mha/yr Annual gross transition from other land to cropland
Resources|Land Transitions|From Other Land|+|To Pastures and Rangelands Mha/yr Annual gross transition from other land to pastures and rangelands
Resources|Land Transitions|From Other Land|+|To Urban Area Mha/yr Annual gross transition from other land to urban area
Resources|Land Transitions|From Other Land|+|To Forest Mha/yr Annual gross transition from other land to forest (sum of planted, primary, and secondary forest)
Resources|Land Transitions|From Other Land|To Forest|+|To Planted Forest Mha/yr Annual gross transition from other land to planted forest
Resources|Land Transitions|From Other Land|To Forest|+|To Primary Forest Mha/yr Annual gross transition from other land to primary forest (structurally zero)
Resources|Land Transitions|From Other Land|To Forest|+|To Secondary Forest Mha/yr Annual gross transition from other land to secondary forest

Author(s)

Florian Humpenoeder

Examples

## Not run: 
    x <- reportLandTransitionMatrix(gdx)
  
## End(Not run)

reportLandUse

Description

reports land-use

Usage

reportLandUse(gdx, level = "regglo")

Arguments

gdx

GDX file
level

The aggregation level to be used ("regglo" by default)

Value

land-use as MAgPIE object (million ha)

Total land cover variables

Name Unit Meta
Resources|Land Cover million ha Total land cover
Resources|Land Cover|Agricultural land million ha Agricultural land including cropland and pastures

Cropland variables

Name Unit Meta
Resources|Land Cover|+|Cropland million ha Arable land, i.e. land in bioenergy crop, food, and feed/fodder crops, permanent crops as well as other arable land (physical area)
Resources|Land Cover|Cropland|+|Croparea million ha Physical cropland area used for crop production
Resources|Land Cover|Cropland|+|Fallow million ha Fallow cropland
Resources|Land Cover|Cropland|+|Tree Cover million ha Trees on cropland for agroforestry

Pasture and urban variables

Name Unit Meta
Resources|Land Cover|+|Pastures and Rangelands million ha Pasture and range land based on FAO definition of permanent meadows and pastures
Resources|Land Cover|+|Urban Area million ha Built-up land associated with human settlements

Other natural land variables

Name Unit Meta
Resources|Land Cover|+|Other Land million ha Non-forest natural land including primary non-forest, restored and recovered natural land
Resources|Land Cover|Other Land|Initial million ha Primary non-forest natural land without clearly visible indications of human activities
Resources|Land Cover|Other Land|Recovered million ha Recovered natural land due to the abandonment of agricultural or forestry land without intention for nature/biodiversity conservation
Resources|Land Cover|Other Land|Restored million ha Intentionally restored natural land for the purpose of nature and/or biodiversity conservation

Forest variables

Name Unit Meta
Resources|Land Cover|+|Forest million ha Sum of primary, secondary and planted forest (FAO definition)
Resources|Land Cover|Forest|+|Natural Forest million ha Naturally regenerated forest including primary and secondary forest
Resources|Land Cover|Forest|Natural Forest|+|Primary Forest million ha Naturally regenerated forest of native tree species where there are no clearly visible indications of human activities (FAO definition)
Resources|Land Cover|Forest|Natural Forest|+|Secondary Forest million ha Forest predominantly composed of trees established through natural regeneration excluding primary forest (based on FAO definition)
Resources|Land Cover|Forest|Natural Forest|Secondary Forest|Young million ha Young secondary forest
Resources|Land Cover|Forest|Natural Forest|Secondary Forest|Mature million ha Mature secondary forest
Resources|Land Cover|Forest|+|Planted Forest million ha Forest predominantly composed of trees established through planting and/or deliberate seeding (FAO definition)
Resources|Land Cover|Forest|Planted Forest|+|Plantations million ha Intensively managed planted forests with one or two species, even age class, and regular spacing (FAO definition)
Resources|Land Cover|Forest|Planted Forest|Plantations|+|Timber million ha Plantations for timber production
Resources|Land Cover|Forest|Planted Forest|Plantations|+|CO2-price AR million ha Reforestation and/or afforestation for carbon sequestration with non-native species and/or as monoculture plantation
Resources|Land Cover|Forest|Planted Forest|+|Natural million ha Planted forest not classified as plantation forest
Resources|Land Cover|Forest|Planted Forest|Natural|+|CO2-price AR million ha Reforestation and/or afforestation for carbon sequestration with native tree species resembling natural vegetation
Resources|Land Cover|Forest|Planted Forest|Natural|+|NPI_NDC AR million ha Afforestation/reforestation under national policies and NDC commitments

Author(s)

Florian Humpenoeder, Kristine Karstens, Isabelle Weindl

Examples

## Not run: 
    x <- reportLandUse(gdx)
  
## End(Not run)

reportLandUseChange

Description

reports land-use change

Usage

reportLandUseChange(gdx, baseyear = 1995, level = "regglo")

Arguments

gdx

GDX file
baseyear

baseyear for calculating land-use change
level

An aggregation level for the spatial dimension. Can be any level available via superAggregateX.

Value

land-use change as MAgPIE object (million ha wrt to baseyear)

Land-use change variables

Name Unit Meta
Resources|Land Cover Change|Cropland million ha wrt baseyear Change in cropland area relative to baseyear
Resources|Land Cover Change|Pastures and Rangelands million ha wrt baseyear Change in pasture area relative to baseyear
Resources|Land Cover Change|Forest million ha wrt baseyear Change in forest area relative to baseyear
Resources|Land Cover Change|Other Land million ha wrt baseyear Change in other land area relative to baseyear

Author(s)

Florian Humpenoeder

Examples

## Not run: 
    x <- reportLandUseChange(gdx)
  
## End(Not run)

reportLandUseForSEALS

Description

Writes MAgPIE land use projections to a specific NetCDF that can be read by the Spatial Economic Allocation Landscape Simulator (SEALS) model for generating high resolution land use maps.

Usage

reportLandUseForSEALS(
  outputdir = ".",
  magCellLand = "cell.land_0.5_share.mz",
  outFile = NULL,
  selectyears = c(2020, 2030, 2050)
)

Arguments

outputdir

output directory which contains cellular magpie output
magCellLand

Disaggregated land use (grid-cell land area share) as magclass object or file (.mz) from a MAgPIE run.
outFile

a file name the output should be written to using ncdf4::nc_create and ncdf4::ncvar_put
selectyears

Numeric vector of years to provide data for.

Value

Proportions of different land use classes per grid sell in a NetCDF format.

SEALS land use output

This function produces NetCDF files (not MAgPIE reporting variables) with land use proportions for crop, past, primforest, secdforest, forestry, urban, and other land types.

Author(s)

Patrick v. Jeetze

Examples

## Not run: 
x <- reportLandUseForSEALS(
  magCellLand = "cell.land_0.5_share.mz",
  outFile = "cell.land_0.5_SEALS.nc",
  selectyears = c(2020, 2030, 2050)
)

## End(Not run)

reportLivestockDemStructure

Description

reports the share of different livestock products (excluding fish) in total livestock calorie food supply

Usage

reportLivestockDemStructure(gdx, level = "regglo")

Arguments

gdx

GDX file
level

An aggregation level for the spatial dimension. Can be any level available via superAggregateX.

Value

livestock demand structure as MAgPIE object (kcal/kcal)

Livestock demand structure variables

Name Unit Meta
Nutrition|Dietary Composition|Livestock Demand Structure|+|Ruminant meat kcal/kcal Share of ruminant meat in livestock calorie supply
Nutrition|Dietary Composition|Livestock Demand Structure|+|Poultry meat and eggs kcal/kcal Share of poultry and eggs in livestock calorie supply
Nutrition|Dietary Composition|Livestock Demand Structure|+|Dairy kcal/kcal Share of dairy in livestock calorie supply
Nutrition|Dietary Composition|Livestock Demand Structure|+|Monogastric meat kcal/kcal Share of monogastric meat in livestock calorie supply

Author(s)

Isabelle Weindl

Examples

## Not run: 
    x <- reportLivestockDemStructure(gdx)
  
## End(Not run)

reportLivestockShare

Description

reports the share of livestock products (including fish) in total calorie food supply

Usage

reportLivestockShare(gdx, level = "regglo")

Arguments

gdx

GDX file
level

An aggregation level for the spatial dimension. Can be any level available via superAggregateX.

Value

per-capita calories as MAgPIE object (kcal/cap/day)

Livestock share variables

Name Unit Meta
Nutrition|Dietary Composition|Livestock Share kcal/kcal Share of livestock products (incl. fish) in total calorie supply

Author(s)

Benjamin Leon Bodirsky

Examples

## Not run: 
    x <- reportLivestockShare(gdx)
  
## End(Not run)

reportManure

Description

Reports the Nitrogen in Manure of all animals for future MAgPIE projections

Usage

reportManure(gdx, nutrient = "nr", level = "regglo")

Arguments

gdx

GDX file
nutrient

nr, p, c...
level

aggregation level of returned data ("regglo" by default)

Manure variables

Name Unit Meta
Resources|Nitrogen|Manure Mt Nr/yr Total manure nitrogen production
Resources|Nitrogen|Manure|++|Confinement Mt Nr/yr Manure from confined livestock
Resources|Nitrogen|Manure|++|Grazing Mt Nr/yr Manure deposited during grazing
Resources|Nitrogen|Manure|+|Ruminants Mt Nr/yr Manure from ruminant animals
Resources|Nitrogen|Manure|+|Monogastric Mt Nr/yr Manure from monogastric animals

Author(s)

Benjamin Leon Bodirsky

Examples

## Not run: 
    x <- reportManure(gdx)
  
## End(Not run)

reportManureFuel

Description

Reports manure used as direct combustion fuel from a MAgPIE GDX file at ISO country level. Converts from nitrogen mass (Mt N) to energy (PJ) using livestock-specific heating values and nitrogen contents from Hoyos-Sebá et al. (2024).

Usage

reportManureFuel(gdx, file = NULL)

Arguments

gdx

GDX file
file

a file name the output should be written to using write.magpie

Value

MAgPIE object with manure fuel at ISO level in PJ.

Author(s)

Kristine Karstens

Examples

## Not run: 
  x <- reportManureFuel(gdx)

## End(Not run)

reportNetForestChange

Description

reports net and gross forest area change

Usage

reportNetForestChange(gdx, level = "regglo")

Arguments

gdx

GDX file
level

An aggregation level for the spatial dimension. Can be any level available via superAggregateX.

Value

NetForestChange as magclass object (Mha per year)

Net forest change variables

Name Unit Meta
Resources|NetForestChange Mha/yr Annual net change in total forest area

Gross forest loss variables

Name Unit Meta
Resources|GrossForestLoss Mha/yr Annual gross deforested area
Resources|GrossForestLoss|+|Primary Mha/yr Annual gross loss of primary forest area
Resources|GrossForestLoss|+|Secondary Mha/yr Annual gross loss of secondary forest area
Resources|GrossForestLoss|+|Planted Mha/yr Annual gross loss of planted forest area
Resources|GrossForestLoss|Planted|Plantation|+|Timber Mha/yr Annual gross loss of timber plantation area
Resources|GrossForestLoss|Planted|Plantation|+|CO2-price AR Mha/yr Annual gross loss of CO2-price afforestation/reforestation plantation area
Resources|GrossForestLoss|Planted|Natural|+|CO2-price AR Mha/yr Annual gross loss of CO2-price afforestation/reforestation natural forest area
Resources|GrossForestLoss|Planted|Natural|+|NPI_NDC AR Mha/yr Annual gross loss of NPI/NDC afforestation/reforestation area

Gross forest gain variables

Name Unit Meta
Resources|GrossForestGain Mha/yr Annual gross expansion of forest area
Resources|GrossForestGain|+|Primary Mha/yr Annual gross expansion of primary forest area
Resources|GrossForestGain|+|Secondary Mha/yr Annual gross expansion of secondary forest area
Resources|GrossForestGain|+|Planted Mha/yr Annual gross expansion of planted forest area
Resources|GrossForestGain|Planted|Plantation|+|Timber Mha/yr Annual gross expansion of timber plantation area
Resources|GrossForestGain|Planted|Plantation|+|CO2-price AR Mha/yr Annual gross expansion of carbon plantation area through reforestation and/or afforestation with monoculture and/or non-native species
Resources|GrossForestGain|Planted|Natural|+|CO2-price AR Mha/yr Annual gross reforestation and/or afforestation area for carbon sequestration with native tree species
Resources|GrossForestGain|Planted|Natural|+|NPI_NDC AR Mha/yr Annual gross expansion of NPI/NDC afforestation/reforestation area

Author(s)

Florian Humpenoeder

Examples

## Not run: 
x <- reportNetForestChange(gdx)

## End(Not run)

reportNitrogenBudgetCropland

Description

Reports the Nitrogen Budgets of Croplands for future MAgPIE projections

Usage

reportNitrogenBudgetCropland(gdx, include_emissions = FALSE, level = "regglo")

Arguments

gdx

GDX file
include_emissions

TRUE also divides the N surplus into different emissions
level

aggregation level of returned data ("regglo" by default); use "grid" for 0.5 degree grid level

Nitrogen inputs variables

Name Unit Meta
Resources|Nitrogen|Cropland Budget|Inputs Mt Nr/yr Total nitrogen inputs to cropland
Resources|Nitrogen|Cropland Budget|Inputs|+|Fertilizer Mt Nr/yr Synthetic fertilizer nitrogen applied to cropland
Resources|Nitrogen|Cropland Budget|Inputs|+|Manure Mt Nr/yr Manure nitrogen applied to cropland
Resources|Nitrogen|Cropland Budget|Inputs|+|BNF Mt Nr/yr Biological nitrogen fixation on cropland
Resources|Nitrogen|Cropland Budget|Inputs|+|Atmospheric deposition Mt Nr/yr Atmospheric nitrogen deposition on cropland
Resources|Nitrogen|Cropland Budget|Inputs|+|Seeds Mt Nr/yr Nitrogen from seeds

Nitrogen withdrawals variables

Name Unit Meta
Resources|Nitrogen|Cropland Budget|Withdrawals Mt Nr/yr Total nitrogen withdrawals from cropland
Resources|Nitrogen|Cropland Budget|Withdrawals|+|Harvest Mt Nr/yr Nitrogen removed in harvested crops
Resources|Nitrogen|Cropland Budget|Withdrawals|+|Above-ground residues Mt Nr/yr Nitrogen in above-ground crop residues
Resources|Nitrogen|Cropland Budget|Withdrawals|+|Below-ground residues Mt Nr/yr Nitrogen in below-ground crop residues

Nitrogen balance variables

Name Unit Meta
Resources|Nitrogen|Cropland Budget|Balance Mt Nr/yr Total nitrogen balance on cropland
Resources|Nitrogen|Cropland Budget|Balance|+|Surplus Mt Nr/yr Nitrogen surplus on cropland (inputs minus withdrawals)
Resources|Nitrogen|Cropland Budget|Balance|+|Soil organic matter Mt Nr/yr Net nitrogen flow into soil organic matter (negative = release)
Resources|Nitrogen|Cropland Budget|Balance|+|Balance flow Mt Nr/yr Nitrogen balance flow (calibration term)

Author(s)

Benjamin Leon Bodirsky

See Also

NitrogenBudget

Examples

## Not run: 
x <- reportNitrogenBudgetCropland(gdx)

## End(Not run)

reportNitrogenBudgetNonagland

Description

Reports the Nitrogen Budgets of non-agricultural lands for future MAgPIE projections

Usage

reportNitrogenBudgetNonagland(gdx, level = "reg")

Arguments

gdx

GDX file
level

aggregation level of returned data ("reg" by default); use "grid" for grid level

Non-agricultural nitrogen budget variables

Name Unit Meta
Resources|Nitrogen|Non-Agricultural Land Budget|Balance Mt Nr/yr Nitrogen surplus on non-agricultural land
Resources|Nitrogen|Non-Agricultural Land Budget|Inputs Mt Nr/yr Total nitrogen inputs to non-agricultural land
Resources|Nitrogen|Non-Agricultural Land Budget|Inputs|+|Fixation Mt Nr/yr Biological N fixation on non-ag land
Resources|Nitrogen|Non-Agricultural Land Budget|Inputs|+|Deposition Mt Nr/yr Atmospheric N deposition on non-ag land

Author(s)

Benjamin Leon Bodirsky

See Also

NitrogenBudget

Examples

## Not run: 
    x <- reportNitrogenBudgetNonagland(gdx)
  
## End(Not run)

reportNitrogenBudgetCropland

Description

Reports the Nitrogen Budgets of Croplands for future MAgPIE projections

Usage

reportNitrogenBudgetPasture(gdx, include_emissions = FALSE, level = "regglo")

Arguments

gdx

GDX file
include_emissions

TRUE also divides the N surplus into different emissions
level

aggregation level of returned data ("regglo" by default); use "grid" for grid level

Nitrogen pasture budget variables

Name Unit Meta
Resources|Nitrogen|Pasture Budget|Inputs Mt Nr/yr Total nitrogen inputs to pastures
Resources|Nitrogen|Pasture Budget|Inputs|+|Manure Mt Nr/yr Manure nitrogen deposited on pastures
Resources|Nitrogen|Pasture Budget|Inputs|+|Atmospheric deposition Mt Nr/yr Atmospheric nitrogen deposition on pastures
Resources|Nitrogen|Pasture Budget|Withdrawals Mt Nr/yr Total nitrogen withdrawals from pastures
Resources|Nitrogen|Pasture Budget|Balance Mt Nr/yr Nitrogen balance on pastures
Resources|Nitrogen|Pasture Budget|Balance|+|Surplus Mt Nr/yr Nitrogen surplus on pastures

Author(s)

Benjamin Leon Bodirsky

See Also

NitrogenBudget

Examples

## Not run: 
    x <- reportNitrogenBudgetCropland(gdx)
  
## End(Not run)

reportNitrogenEfficiencies

Description

Reports different nitrogen use efficiency indicators

Usage

reportNitrogenEfficiencies(gdx, level = "regglo")

Arguments

gdx

GDX file
level

aggregation level of returned data ("regglo" by default)

Nitrogen efficiency variables

Name Unit Meta
Resources|Nitrogen|Cropland Budget|Nitrogen Use Efficiency complete Mt Nr/Mt Nr Complete nitrogen use efficiency on cropland
Resources|Nitrogen|Cropland Budget|Nitrogen Use Efficiency basic Mt Nr/Mt Nr Basic nitrogen use efficiency (harvest/inputs)
Resources|Nitrogen|Cropland Budget|Soil Nitrogen Uptake Efficiency Mt Nr/Mt Nr Soil nitrogen uptake efficiency
Resources|Nitrogen|Pasture Budget|Nitrogen Use Efficiency complete Mt Nr/Mt Nr Complete nitrogen use efficiency on pastures

Author(s)

Benjamin Leon Bodirsky

See Also

reportNitrogenEfficiencies

Examples

## Not run: 
x <- reportNitrogenEfficiencies(gdx)

## End(Not run)

reportNitrogenPollution

Description

Reports total Nitrogen Pollution as the sum of surplus from cropland, pasture, awms, consumption and non-agricutlural land

Usage

reportNitrogenPollution(gdx, level = "regglo")

Arguments

gdx

GDX file
level

aggregation level of returned data ("regglo" by default)

Nitrogen pollution variables

Name Unit Meta
Resources|Nitrogen|Pollution|Surplus Mt Nr/yr Total nitrogen pollution surplus from all sources
Resources|Nitrogen|Pollution|Surplus|+|Cropland Mt Nr/yr Nitrogen surplus from cropland
Resources|Nitrogen|Pollution|Surplus|+|Pasture Mt Nr/yr Nitrogen surplus from pasture
Resources|Nitrogen|Pollution|Surplus|+|Animal waste management Mt Nr/yr Nitrogen losses from animal waste management systems
Resources|Nitrogen|Pollution|Surplus|+|Non-agricultural land Mt Nr/yr Nitrogen surplus from non-agricultural land
Resources|Nitrogen|Pollution|Surplus|+|End-of-life losses Mt Nr/yr Nitrogen losses from food consumption and waste

Nitrogen aggregate variables

Name Unit Meta
Resources|Nitrogen|Nutrient surplus from agricultural land Mt Nr/yr Nitrogen surplus from cropland and pasture
Resources|Nitrogen|Nutrient surplus from agricultural land and manure management Mt Nr/yr Nitrogen surplus from cropland, pasture, and AWMS
Resources|Nitrogen|Nutrient surplus from all land and manure management Mt Nr/yr Nitrogen surplus from all land and manure management

Author(s)

Benjamin Leon Bodirsky, Michael Crawford

See Also

NitrogenBudget

Examples

## Not run: 
x <- reportNitrogenPollution(gdx)

## End(Not run)

reportOutputPerWorker

Description

reports output per worker in crop+livestock production from MAgPIE results

Usage

reportOutputPerWorker(gdx, level = "regglo")

Arguments

gdx

GDX file
level

aggregation level of returned data ("regglo" by default)

Value

output per worker as MAgPIE object

Output per worker variables

Name Unit Meta
Labor|Productivity|Monetary output per worker US$2017/worker Monetary output per agricultural worker

Author(s)

Debbora Leip

Examples

## Not run: 
    x <- reportOutputPerWorker(gdx)
  
## End(Not run)

reportPastSoilCarbon

Description

reports pasture soil carbon

Usage

reportPastSoilCarbon(gdx)

Arguments

gdx

GDX file

Value

Soil carbon values as magpie objetc

Pasture soil carbon variables

Name Unit Meta
Resources|Soil Carbon Target|Pasture|Continuous grazing|Density tC per ha Target soil carbon density for pastures
Resources|Soil Carbon Target Change|Pasture|Continuous grazing|Density tC per ha Change in target soil carbon density

Author(s)

Marcos Alves

Examples

## Not run: 
x <- reportPastSoilCarbon(gdx)

## End(Not run)

reportPBbiosphere

Description

reports biosphere planetary boundary: Share of intact land relative to total land area (unitless) Share of intact land covered by areas within Global Safety Net (unitless) Share of land area that satisfies landscape target (unitless)

Usage

reportPBbiosphere(gdx, level = "regglo", intactnessRule = "carbon:0.95")

Arguments

gdx

GDX file
level

level of aggregation (regglo: regions and global)
intactnessRule

rule for intact land can be based on percentage of potential carbon density reached or on age classes for secondary forests, planted forest and other natural land. The argument is split into two components: rule: carbon or ageclass threshold: share of carbon density reached to be classified as intact or threshold in years can be set via this argument Example: "carbon:0.95" or "ageclass:70"

Value

MAgPIE object

Biosphere planetary boundary variables

Name Unit Meta
Planetary Boundary|Biosphere|Share of intact land relative to total land area unitless Fraction of intact land (primary forest, mature secondary forest, other natural land)
Planetary Boundary|Biosphere|Share of intact land covered by areas within Global Safety Net unitless Share of intact land in priority conservation areas
Planetary Boundary|Biosphere|Share of land area that satisfies landscape target unitless Share of land where cropland does not exceed 80% of available cropland

Author(s)

Patrick von Jeetze, Felicitas Beier

Examples

## Not run: 
x <- reportPBbiosphere(gdx)

## End(Not run)

reportPBland

Description

reports land planetary boundary: forest area

Usage

reportPBland(gdx, level = "regglo", foresttype = "all")

Arguments

gdx

GDX file
level

level of aggregation (regglo: regions and global)
foresttype

managed forest types that are included in the calculation of the forest area (all: all managed forests, noTimber: timber plantations are not counted)

Value

MAgPIE object

Land planetary boundary variables

Name Unit Meta
Planetary Boundary|Land|Forest cover Mha Total forest area (natural and managed forests)

Author(s)

Felicitas Beier, Patrick von Jeetze

Examples

## Not run: 
    x <- reportPBland(gdx)
  
## End(Not run)

reportPBnitrogen

Description

reports nitrogen planetary boundary

Usage

reportPBnitrogen(gdx, level = "regglo")

Arguments

gdx

GDX file
level

level of aggregation (regglo: regions and global)

Value

MAgPIE object

Nitrogen planetary boundary variables

Name Unit Meta
Planetary Boundary|Nitrogen|Agricultural Nitrogen surplus Mt N/yr Total nitrogen surplus from cropland and pasture

Author(s)

Felicitas Beier, Mike Crawford

Examples

## Not run: 
    x <- reportPBnitrogen(gdx)
  
## End(Not run)

reportPBwater

Description

reports water planetary boundaries

Usage

reportPBwater(gdx, level = "regglo")

Arguments

gdx

GDX file
level

level of aggregation (regglo: regions and global)

Value

MAgPIE object

Water planetary boundary variables

Name Unit Meta
Planetary Boundary|Freshwater|Water consumption km3/yr Total blue water consumption (agricultural and non-agricultural)

Author(s)

Felicitas Beier, Jens Heinke

Examples

## Not run: 
    x <- reportPBwater(gdx)
  
## End(Not run)

reportPeatland

Description

reports peatland area

Usage

reportPeatland(gdx, level = "regglo")

Arguments

gdx

GDX file
level

An aggregation level for the spatial dimension. Can be any level available via superAggregateX.

Value

peatland area as magclass object (million ha)

Peatland variables

Name Unit Meta
Resources|Peatland million ha Area of peatlands
Resources|Peatland|+|Intact million ha Area of intact peatlands
Resources|Peatland|+|Degraded million ha Area of drained peatlands
Resources|Peatland|+|Rewetted million ha Area of rewetted peatlands

Author(s)

Florian Humpenoeder

Examples

## Not run: 
    x <- reportPeatland(gdx)
  
## End(Not run)

reportPlantationEstablishment

Description

reports MAgPIE harvested area for timber.

Usage

reportPlantationEstablishment(gdx, level = "regglo")

Arguments

gdx

GDX file
level

aggregation level of returned data ("regglo" by default)

Value

Area harvested for timber production

Plantation establishment variables

Name Unit Meta
Resources|Timber operations|Area Newly Established|Forestry Mha per yr Annual area of new timber plantations established

Author(s)

Abhijeet Mishra

Examples

## Not run: 
    x <- reportPlantationEstablishment(gdx)
  
## End(Not run)

reportPopulation

Description

reports Population

Usage

reportPopulation(gdx, level = "regglo")

Arguments

gdx

GDX file
level

spatial aggregation: "reg", "glo", "regglo", "iso"

Value

population as MAgPIE object

Population variables

Name Unit Meta
Population million people Total population

Author(s)

Florian Humpenoeder

Examples

## Not run: 
    x <- reportPopulation(gdx)
  
## End(Not run)

reportPriceAgriculture

Description

reports food commodity prices

Usage

reportPriceAgriculture(gdx, level = "regglo")

Arguments

gdx

GDX file
level

aggregation level of returned data ("regglo" by default)

Value

agricultural commodity prices as MAgPIE object (USD)

Agricultural price variables

Name Unit Meta
Prices|Agriculture|Crops US$2017/tDM Prices for crop products
Prices|Agriculture|Livestock products US$2017/tDM Prices for livestock products

Author(s)

Mishko Stevanovic

Examples

## Not run: 
    x <- reportPriceAgriculture(gdx)
  
## End(Not run)

reportPriceBioenergy

Description

reports bioenergy prices

Usage

reportPriceBioenergy(gdx, level = "regglo")

Arguments

gdx

GDX file
level

aggregation level of returned data ("regglo" by default)

Value

bioenergy price as MAgPIE object Unit: see names

Bioenergy price variables

Name Unit Meta
Prices|Bioenergy US$2017/GJ Bioenergy price

Author(s)

Florian Humpenoeder

Examples

## Not run: 
    x <- reportPriceBioenergy(gdx)
  
## End(Not run)

reportHunger

Description

Calculates the share of people living in hunger.

Usage

reportPriceElasticities(gdx, level = "regglo")

Arguments

gdx

GDX file
level

An aggregation level for the spatial dimension. Can be any level available via superAggregateX.

Value

magpie object with hunger (mio people) or hunger share

Price elasticity variables

Name Unit Meta
Food Supply|PriceElasticities|Total Calories %/% Price elasticity of total calorie demand
Food Supply|PriceElasticities|Staples %/% Price elasticity of staple food demand
Food Supply|PriceElasticities|Livestock Products %/% Price elasticity of livestock product demand
Food Supply|PriceElasticities|Vegetables, Fruits and Nuts %/% Price elasticity of fruits and vegetables demand

Author(s)

Benjamin Leon Bodirsky

Examples

## Not run: 
    x <- reportHunger(gdx)
  
## End(Not run)

reportPriceFoodIndex

Description

reports food price index

Usage

reportPriceFoodIndex(gdx, baseyear = "y2020", level = "regglo")

Arguments

gdx

GDX file
baseyear

baseyear of the price index
level

aggregation level of returned data ("regglo" by default)

Value

Food price index as MAgPIE object Unit: see names

Food price index variables

Name Unit Meta
Prices|Index|Agriculture|Food products 1 Food price index relative to baseyear
Prices|Index|Agriculture|Food products|Plant-based 1 Plant-based food price index
Prices|Index|Agriculture|Food products|Plant-based|Maize 1 Maize price index
Prices|Index|Agriculture|Food products|Plant-based|Rice 1 Rice price index
Prices|Index|Agriculture|Food products|Plant-based|Soybean 1 Soybean price index
Prices|Index|Agriculture|Food products|Plant-based|Temperate cereals 1 Wheat/temperate cereals price index
Prices|Index|Agriculture|Food products|Livestock 1 Livestock food price index

Author(s)

Florian Humpenoeder, Felicitas Beier

Examples

## Not run: 
    x <- reportPriceFoodIndex(gdx)
  
## End(Not run)

reportPriceGHG

Description

reports GHG emission prices

Usage

reportPriceGHG(gdx, level = "regglo")

Arguments

gdx

GDX file
level

An aggregation level for the spatial dimension. Can be any level available via superAggregateX.

Value

GHG emission prices as MAgPIE object

GHG price variables

Name Unit Meta
Prices|GHG Emission|CO2 US$2017/tCO2 Carbon dioxide emission price
Prices|GHG Emission|N2O US$2017/tN2O Nitrous oxide emission price
Prices|GHG Emission|CH4 US$2017/tCH4 Methane emission price

Author(s)

Florian Humpenoeder, Amsalu W. Yalew

Examples

## Not run: 
    x <- reportPriceGHG(gdx)
  
## End(Not run)

reportPriceLand

Description

reports land prices (land rent)

Usage

reportPriceLand(gdx, level = "regglo")

Arguments

gdx

GDX file
level

aggregation level of returned data ("regglo" by default)

Value

land prices as MAgPIE object Unit: see names

Land price variables

Name Unit Meta
Prices|Land|Cropland US$2017/ha Land rent (shadow price of cropland constraint)

Author(s)

Florian Humpenoeder

Examples

## Not run: 
    x <- reportPriceLand(gdx)
  
## End(Not run)

reportPriceShock

Description

Reports the change in consumption and expenditure due to higher or lower food prices

Usage

reportPriceShock(gdx, level = "regglo")

Arguments

gdx

GDX file
level

An aggregation level for the spatial dimension. Can be any level available via superAggregateX.

Value

magpie object

Price shock variables

Name Unit Meta
Food Supply|Calorie Supply|Price Induced Change|Absolute|Total Calories kcal/cap/day Absolute total
Food Supply|Calorie Supply|Price Induced Change|Absolute|Livestock Calories kcal/cap/day Livestock
Food Supply|Calorie Supply|Price Induced Change|Relative|Total Calories kcal/kcal Relative total
Household Expenditure|Food|Price Induced Change|Absolute|Food Expenditure USD/cap Absolute expense
Household Expenditure|Food|Price Induced Change|Relative|Food Expenditure USD/USD Relative expense

Author(s)

Benjamin Leon Bodirsky

Examples

## Not run: 
    x <- reportPriceShock(gdx)
  
## End(Not run)

reportPriceWater

Description

reports water prices

Usage

reportPriceWater(gdx, level = "regglo")

Arguments

gdx

GDX file
level

aggregation level of returned data ("regglo" by default)

Value

water usage as MAgPIE object Unit: see names

Water price variables

Name Unit Meta
Prices|Water|Agriculture Index 2005=100 Agricultural water price index

Author(s)

Florian Humpenoeder

Examples

## Not run: 
x <- reportPriceWater(gdx)

## End(Not run)

reportPriceWoodyBiomass

Description

reports woody biomass prices (land rent)

Usage

reportPriceWoodyBiomass(gdx, level = "regglo")

Arguments

gdx

GDX file
level

aggregation level of returned data ("regglo" by default)

Value

land prices as MAgPIE object Unit: see names

Woody biomass price variables

Name Unit Meta
Prices|Wood US$2017/tDM Wood price
Prices|Woodfuel US$2017/tDM Woodfuel price

Author(s)

Abhijeet Mishra

Examples

## Not run: 
    x <- reportPriceWoodyBiomass(gdx)
  
## End(Not run)

reportProcessing

Description

reportes processing input and output quantities primary-to-process or primary-to-secondary

Usage

reportProcessing(
  gdx,
  detail = TRUE,
  indicator = "primary_to_process",
  level = "regglo"
)

Arguments

gdx

GDX file
detail

if detail=FALSE, the subcategories of groups are not reported (e.g. "soybean" within "oilcrops")
indicator

"primary_to_process" for process or "secondary_from_primary" for secondary product output
level

aggregation level of returned data ("regglo" by default)

Value

processing demand as MAgPIE object (Mt DM)

Processing demand variables

Name Unit Meta
Demand|Processing|++|Crops Mt DM/yr Primary crop products processed into secondary products
Demand|Processing|++|Livestock products Mt DM/yr Primary livestock products processed into secondary products
Processing|Raw material|Processed into Secondary products Mt DM/yr Total raw materials processed into secondary products

Author(s)

David Chen, Benjamin Leon Bodirsky

Examples

## Not run: 
x <- reportProcessing(gdx = gdx, detail = TRUE, indicator = "primary_to_process")

## End(Not run)

reportProcessingResiduesForestry

Description

Reports processing residues from timber production available for energy use.

Processing residues are sawmill byproducts (sawdust, bark, slabs, offcuts) generated during conversion of industrial roundwood to finished products. They are NOT currently tracked as a variable in MAgPIE's GAMS code and represent additional biomass supply for REMIND's bioenergy sector.

Note: Logging residues (branches, tops) tracked in v73_prod_residues are NOT included here because they already feed into MAgPIE's woodfuel supply equation (q73_prod_woodfuel) and would be double-counted if reported separately for REMIND.

Usage

reportProcessingResiduesForestry(gdx, level = "regglo")

Arguments

gdx

GDX file
level

Level of regional aggregation ("regglo" by default)

Details

Full mass balance of timber harvest

When 1 hectare of forest is harvested, the total biomass removed is:

  • Stem biomass = im_growing_stock (tDM/ha)

  • Logging residues (branches, tops) = 15% of stem, tracked in v73_prod_residues

  • Total removed = stem x 1.15

The model splits stem production between industrial roundwood (vm_prod("wood")) and woodfuel (vm_prod("woodfuel")). Only the industrial roundwood fraction enters processing facilities and generates processing residues. Woodfuel is burned directly. Logging residues already feed into MAgPIE's woodfuel supply (NOT reported here). 

1 hectare harvested -> total biomass = stem x 1.15
|
+-- Stem (100% = vm_prod, split between "wood" and "woodfuel" by the model)
|   If allocated to industrial roundwood (vm_prod("wood")) -> processing facilities:
|   |
|   +-- Sawnwood pathway (~57% of IR):
|   |   +-- 50% finished sawnwood
|   |   +-- 43% processing residues (sawdust, slabs, bark, offcuts) -> THIS FUNCTION
|   |   +--  7% losses
|   |
|   +-- Pulpwood pathway (~35% of IR):
|   |   +-- 95-100% utilized (black liquor burned internally at pulp mill)
|   |   +-- 0-5% solid residues available externally
|   |
|   +-- Other industrial roundwood (~8% of IR):
|       +-- Assumed similar to sawnwood (43% residue rate)
|
+-- Logging residues (15% of stem = branches, tops)
    -> Already in MAgPIE woodfuel via v73_prod_residues (NOT reported here)

Processing residue rate

The rate is derived from FAO product composition of industrial roundwood (from f73_prod_specific_timber, stable at these shares across 1965-2015) and product-specific recovery rates:

Product Share of IR Recovery Residue rate Source
Sawnwood (sawlogs + veneer) ~57% 50% 43% FAO/UNECE; Mantau 2012 UNECE DP-51
Pulpwood ~35% 95-100% 0-5% Black liquor burned internally
Other industrial roundwood ~8% ~50% 43% Assumed same as sawnwood

Production-weighted rate: 0.57 x 0.43 + 0.35 x 0.025 + 0.08 x 0.43 = 0.29 Rounded to 0.30 (stable at 30-35% across 1965-2015 FAO data).

Why only industrial roundwood, not woodfuel

Processing residues are computed from industrial roundwood supply (ov_supply("wood")) only. Woodfuel (ov_supply("woodfuel")) is excluded because it is burned directly for energy — it does not pass through sawmills or pulp mills and therefore generates no processing residues.

Why all processing residues go to energy

In reality, some processing residues are used for pulp or particleboard. However, MAgPIE models all wood products as aggregate "industrial roundwood" (kforestry = wood). The downstream split into sawnwood, pulp, and panels is not modeled — there is no competing use for processing residues within MAgPIE. Therefore, all processing residues are assumed available for energy use.

Construction wood

calcConstructionWoodDemand in mrcommons applies a factor 2 to construction wood demand, reflecting a 50% sawmill recovery rate (Churkina et al. 2020). This means half of the harvested roundwood for construction becomes processing waste. These residues are clean, uniform offcuts with high energy recovery potential. Reported separately from general processing residues.

What this function does NOT include

  • Logging residues (branches, tops): already in MAgPIE woodfuel (v73_prod_residues)

  • Post-consumer waste wood (demolition, furniture): excluded for consistency with carbonLTS, which tracks CO2 from HWP decay using IPCC first-order decay (half-lives: sawnwood 30yr, construction 60yr, pulpwood 2yr). Adding end-of-life energy recovery would require splitting HWP outflow into burned vs decayed fractions — assumptions not currently in the model. The CO2 from HWP decay is already reported; the energy from burning waste wood is not tracked to avoid parallel lifetime assumptions.

  • Black liquor: burned internally at pulp mills, not available for external energy

References

  • FAO/UNECE conversion factors for sawnwood recovery rates

  • Mantau, U. (2012). Wood flows in Europe (EU27). UNECE/FAO Discussion Paper 51 (DP-51).

  • Oswalt et al. (2019). Forest Resources of the United States. USDA.

  • Churkina et al. (2020). Buildings as a global carbon sink. Nature Sustainability.

Value

MAgPIE object with processing residues in PJ/yr

Variables

Name Unit Meta
Residues for energy|Forestry|+|Processing residues from construction wood PJ/yr Sawmill waste from construction wood (50% of demand)
Residues for energy|Forestry|+|Processing residues from other roundwood PJ/yr 30% of non-construction roundwood
Residues for energy|+|Forestry PJ/yr Total forestry processing residues for energy

Author(s)

Florian Humpenoeder

Examples

## Not run: 
  x <- reportProcessingResiduesForestry(gdx)

## End(Not run)

reportProcessingWoodResidues

Description

Reports the potential of wood processing residues (sawmill byproducts) from a MAgPIE GDX file at ISO country level and converts to energy (PJ). Processing residues are computed from industrial roundwood demand using a 30

Usage

reportProcessingWoodResidues(gdx, file = NULL)

Arguments

gdx

GDX file
file

a file name the output should be written to using write.magpie

Value

MAgPIE object with potential wood processing residues at ISO level in PJ.

Author(s)

Kristine Karstens

Examples

## Not run: 
  x <- reportProcessingWoodResidues(gdx)

## End(Not run)

reportProducerPriceIndex

Description

reports producer price index

Usage

reportProducerPriceIndex(gdx, prod_groups = FALSE, level = "regglo")

Arguments

gdx

GDX file
prod_groups

whether to return only product groups
level

aggregation level of returned data ("regglo" by default)

Value

Producer price index as MAgPIE object Unit: see names

Producer price index variables

Name Unit Meta
Prices|Index2020|Agriculture|Producer|Primary food products Index 2020=100 Producer price index for primary food products
Prices|Index2020|Agriculture|Producer|Crops Index 2020=100 Producer price index for crops
Prices|Index2020|Agriculture|Producer|Livestock products Index 2020=100 Producer price index for livestock products
Prices|Index2020|Agriculture|Producer|Bioenergy Index 2020=100 Producer price index for bioenergy crops
Prices|Index2020|Agriculture|Producer|All agricultural products Index 2020=100 Producer price index for all agricultural products

Author(s)

Isabelle Weindl, David M CHen

Examples

## Not run: 
    x <- reportProducerPriceIndex(gdx)
  
## End(Not run)

reportProduction

Description

reports production

Usage

reportProduction(gdx, detail = FALSE, agmip = FALSE, level = "regglo")

Arguments

gdx

GDX file
detail

if detail=FALSE, the subcategories of groups are not reported (e.g. "soybean" within "oilcrops")
agmip

if agmip = TRUE, additional sector aggregates required for AgMIP are reported (e.g. "AGR")
level

aggregation level of returned data ("regglo" by default)

Value

production as MAgPIE object. Unit: see names

Production variables

Name Unit Meta
Production Mt DM/yr Total agricultural production
Production|+|Crops Mt DM/yr Production of crops
Production|+|Livestock products Mt DM/yr Production of livestock products (excluding fish)
Production|+|Secondary products Mt DM/yr Production of secondary products (processed agricultural goods)
Production|+|Pasture Mt DM/yr Production of pasture biomass
Production|+|Bioenergy crops Mt DM/yr Production of second-generation bioenergy crops (short rotation grasses, short rotation trees)

Author(s)

Benjamin Leon Bodirsky, Isabelle Weindl

Examples

## Not run: 
    x <- reportProduction(gdx)
  
## End(Not run)

reportProductionBioenergy

Description

reports 2nd gen bioenergy production

Usage

reportProductionBioenergy(gdx, detail = FALSE, level = "regglo")

Arguments

gdx

GDX file
detail

if detail=FALSE, the subcategories of groups are not reported (e.g. "soybean" within "oilcrops")
level

An aggregation level for the spatial dimension. Can be any level available via superAggregateX.

Value

production as MAgPIE object. Unit: see names

Bioenergy production variables

Name Unit Meta
Production|Bioenergy|2nd generation EJ/yr Second generation bioenergy production (grassy and woody crops)
Production|Bioenergy|2nd generation|++|Grassy bioenergy crops EJ/yr Production from short rotation grasses
Production|Bioenergy|2nd generation|++|Woody bioenergy crops EJ/yr Production from short rotation trees
Production|Bioenergy|2nd generation|Cumulative EJ Cumulative second generation bioenergy production

Author(s)

Florian Humpenoeder

Examples

## Not run: 
    x <- reportProductionBioenergy(gdx)
  
## End(Not run)

reportProductionGrowth

Description

reports production growth rate

Usage

reportProductionGrowth(gdx, detail = FALSE)

Arguments

gdx

GDX file
detail

if true, provides results for all commodities, otherwhise aggregates some groups

Value

Production growth rates (index)

Production growth variables

Name Unit Meta
Production|Production Growth Rate Index Production volume index relative to base year
Production|Production Growth Rate|+|Crop products Index Crop production growth index
Production|Production Growth Rate|+|Livestock products Index Livestock production growth index

Author(s)

Xiaoxi Wang

Examples

## Not run: 
    x <- reportProductionGrowth(gdx="fulldata.gdx",detail=TRUE)
  
## End(Not run)

reportProductionNr

Description

reports production in Nr analogous to reportProduction

Usage

reportProductionNr(gdx, detail = FALSE)

Arguments

gdx

GDX file
detail

if detail = FALSE, the subcategories of groups are not reported (e.g. "soybean" within "oilcrops")

Value

production as MAgPIE object. Unit: see names

Nitrogen production variables

Name Unit Meta
Production Nr Mt Nr/yr Total nitrogen in agricultural production
Production Nr|+|Crop products Mt Nr/yr Nitrogen in crop production
Production Nr|+|Livestock products Mt Nr/yr Nitrogen in livestock production

Author(s)

Benjamin Leon Bodirsky

Examples

## Not run: 
    x <- reportProductionNr(gdx)
  
## End(Not run)

reportProtein

Description

reports per-capita protein food supply (including household waste)

Usage

reportProtein(gdx, detail = FALSE, level = "regglo")

Arguments

gdx

GDX file
detail

if detail=F, the subcategories of groups are not reported (e.g. "soybean" within "oilcrops")
level

An aggregation level for the spatial dimension. Can be any level available via superAggregateX.

Value

per-capita protein as MAgPIE object (protein/cap/day)

Protein supply variables

Name Unit Meta
Nutrition|Protein Supply protein/capita/day Total per-capita protein supply (including household waste)
Nutrition|Protein Supply|+|Crops protein/capita/day Protein supply from crops
Nutrition|Protein Supply|+|Livestock products protein/capita/day Protein supply from livestock products
Nutrition|Protein Supply|+|Secondary products protein/capita/day Protein supply from secondary/processed products

Author(s)

Benjamin Leon Bodirsky, Kristine Karstens, Abhijeet Mishra, Florian Humpenoeder

Examples

## Not run: 
    x <- reportKcal(gdx)
  
## End(Not run)

reportRelativeHourlyLaborCosts

Description

reports labor costs per ag. worker in relation to GDP pc from MAgPIE results

Usage

reportRelativeHourlyLaborCosts(gdx, level = "regglo")

Arguments

gdx

GDX file
level

aggregation level of returned data ("regglo" by default)

Value

labor costs per ag. worker in relation to GDP pc as MAgPIE object

Relative hourly labor cost variables

Name Unit Meta
Labor|Wages|Labor costs per worker relative to GDP pc % Agricultural labor costs relative to GDP per capita

Author(s)

Debbora Leip

Examples

## Not run: 
    x <- reportRelativeHourlyLaborCosts(gdx)
  
## End(Not run)

reportSOM

Description

Report soil organic carbon stock size for future MAgPIE projections

Usage

reportResidues(gdx)

Arguments

gdx

GDX file

Residue variables

Name Unit Meta
Resources|Carbon|Cropland|Residues Mt C/yr Total carbon in crop residues
Resources|Carbon|Cropland|Residues|+|Cereals Mt C/yr Carbon in cereal residues
Resources|Carbon|Cropland|Residues|+|Oilcrops Mt C/yr Carbon in oilcrop residues

Author(s)

Kristine Karstens

Examples

## Not run: 
    x <- reportSOM(gdx)
  
## End(Not run)

reportRotationLength

Description

reports Forest rotation length.

Usage

reportRotationLength(gdx, level = "regglo")

Arguments

gdx

GDX file
level

aggregation level of returned data ("regglo" by default)

Value

Forest rotation length

Rotation length variables

Name Unit Meta
Rotation lengths|Forestry years Optimal rotation length for timber plantations

Author(s)

Abhijeet Mishra

Examples

## Not run: 
    x <- reportRotationLength(gdx)
  
## End(Not run)

reportRuralDemandShares

Description

reports rural demand and production shares based on local consumption

Usage

reportRuralDemandShares(gdx, type = "tradOnly", level = "regglo")

Arguments

gdx

GDX file
type

Type of ratio that should be calculated

  • all: How much rural & trad demand as a share of all demand is satisfied locally

  • tradOnly: How much rural & trad demand as a share of rural & trad demand is satisfied locally

  • potential: How much total gridded demand is potentially satisfied by gridded production

level

spatial aggregation: "reg", "glo", "regglo"

Value

share of food demand at disaggregated level coming from local production as MAgPIE object

Rural demand share variables

Name Unit Meta
Share of Rural Demand Satisfied by Rural Production|Primary Crop and Livestock Products 0 - 1 Share of rural demand met by local production
Share of Total Demand Satisfied by Rural Production|Primary Crop and Livestock Products 0 - 1 Share of total demand met by rural production
Share of Total Demand Potentially Satisfied by Local Production 0 - 1 Potential local production share

Author(s)

David M Chen

Examples

## Not run: 
x <- reportruralDemandShares(gdx)

## End(Not run)

reportSDG1

Description

reports all SDG indicators relevant for SDG1 - Poverty

Usage

reportSDG1(gdx, level = "regglo")

Arguments

gdx

GDX file
level

An aggregation level for the spatial dimension. Can be any level available via superAggregateX.

Value

MAgPIE object

SDG1 Poverty variables

Name Unit Meta
SDG|SDG01|Per-capita income US$2017 PPP/cap/yr GDP per capita (after shock)

Author(s)

Benjamin Bodirsky

Examples

## Not run: 
    x <- reportSDG3(gdx)
  
## End(Not run)

reportSDG12

Description

reports all SDG indicators relevant for SD12 - Sustainable Production and Consumption

Usage

reportSDG12(gdx, level = "regglo")

Arguments

gdx

GDX file
level

An aggregation level for the spatial dimension. Can be any level available via superAggregateX.

Value

MAgPIE object

SDG12 Sustainable consumption variables

Name Unit Meta
SDG|SDG12|Material footprint tDM/capita/yr Per-capita crop demand (material footprint proxy)
SDG|SDG12|Food waste kcal/cap/day Per-capita daily food waste (caloric availability minus intake)
SDG|SDG12|Food waste total Mt DM/yr Total food waste in dry matter
SDG|SDG12|Food loss Mt DM/yr Food losses in supply chain (pre-consumer waste)

Author(s)

Benjamin Bodirsky

Examples

## Not run: 
    x <- reportSDG12(gdx)
  
## End(Not run)

reportSDG15

Description

reports all SDG indicators relevant for SD15 - Life on Land

Usage

reportSDG15(gdx, level = "regglo")

Arguments

gdx

GDX file
level

An aggregation level for the spatial dimension. Can be any level available via superAggregateX.

Value

MAgPIE object

SDG15 Life on land variables

Name Unit Meta
SDG|SDG15|Forest share share of total land Share of land covered by forest (primary, secondary, forestry)
SDG|SDG15|Primary forest share share of total land Share of land covered by primary forest
SDG|SDG15|Afforestation million ha Area of afforestation (NDC and additional)
SDG|SDG15|Other natural land share share of total land Share of land covered by other natural land
SDG|SDG15|Terrestrial biodiversity index Biodiversity Intactness Index (BII)
SDG|SDG15|Non-agricultural land share share of total land Share of land not used for agriculture
SDG|SDG15|Biological nitrogen fixation on cropland Mt N/yr Total biological nitrogen fixation on cropland
SDG|SDG15|Industrial and intentional biological fixation of N Mt N/yr Sum of fertilizer and crop nitrogen fixation

Author(s)

Benjamin Bodirsky, Isabelle Weindl

Examples

## Not run: 
    x <- reportSDG15(gdx)
  
## End(Not run)

reportSDG2

Description

reports all SDG indicators relevant for SD2 - Hunger

Usage

reportSDG2(gdx, level = "regglo")

Arguments

gdx

GDX file
level

An aggregation level for the spatial dimension. Can be any level available via superAggregateX.

Value

MAgPIE object

SDG2 Hunger variables

Name Unit Meta
SDG|SDG02|Prevalence of underweight million Population with underweight BMI
SDG|SDG02|Prevalence of underweight|Children million Children under 5 with underweight BMI
SDG|SDG02|Food availability kcal/cap/day Daily per-capita caloric availability
SDG|SDG02|Food expenditure share income Share of income spent on food (value added)
SDG|SDG02|Agricultural primary product expenditure share income Share of income spent on agricultural primary products
SDG|SDG02|Agricultural commodity price index wrt 2020 1 Food price index relative to 2020 baseline
SDG|SDG02|Prevalence of obesity|Children million Children under 5 with obesity
SDG|SDG02|Investment in AgR&D million US$2017/yr Investment in agricultural research and development

Author(s)

Benjamin Bodirsky

Examples

## Not run: 
    x <- reportSDG2(gdx)
  
## End(Not run)

reportSDG3

Description

reports all SDG indicators relevant for SDG3 - Health

Usage

reportSDG3(gdx, level = "regglo")

Arguments

gdx

GDX file
level

An aggregation level for the spatial dimension. Can be any level available via superAggregateX.

Value

MAgPIE object

SDG3 Health variables

Name Unit Meta
SDG|SDG03|Prevalence of overweight million Population with overweight BMI
SDG|SDG03|Prevalence of obesity million Population with obesity
SDG|SDG03|Prevalence of overweight|Children million Children under 5 with overweight BMI
SDG|SDG03|Prevalence of obesity|Children million Children under 5 with obesity
SDG|SDG03|Consumption of alcohol kcal/cap/day Daily per-capita caloric intake from alcohol

Author(s)

Benjamin Bodirsky

Examples

## Not run: 
    x <- reportSDG3(gdx)
  
## End(Not run)

reportSDG6

Description

reports all SDG indicators relevant for SDG6 - Access to Water

Usage

reportSDG6(gdx, level = "regglo")

Arguments

gdx

GDX file
level

An aggregation level for the spatial dimension. Can be any level available via superAggregateX.

Value

MAgPIE object

SDG6 Water variables

Name Unit Meta
SDG|SDG06|Fertilizer use Mt N/yr Nitrogen fertilizer application on cropland
SDG|SDG06|Nitrogen surplus on cropland Mt N/yr Nitrogen surplus from cropland budget
SDG|SDG06|Agricultural water use km3/yr Agricultural water withdrawal during growing period

Author(s)

Felicitas Beier, Isabelle Weindl

Examples

## Not run: 
    x <- reportSDG6(gdx)
  
## End(Not run)

reportSDG9

Description

reports all SDG indicators relevant for SD9 - Industrial innovation and infrastructure

Usage

reportSDG9(gdx, level = "regglo")

Arguments

gdx

GDX file
level

An aggregation level for the spatial dimension. Can be any level available via superAggregateX.

Value

MAgPIE object

Author(s)

Felicitas Beier

Examples

## Not run: 
    x <- reportSDG9(gdx)
  
## End(Not run)

reportSOM

Description

Report soil organic carbon stock size for future MAgPIE projections

Usage

reportSOM(gdx, baseyear = 1995, level = "regglo")

Arguments

gdx

GDX file
baseyear

baseyear for calculating carbon stock change
level

aggregation level of returned data ("regglo" by default)

Actual soil carbon stock variables

Name Unit Meta
Resources|Soil Carbon|Actual|Stock|SOC in top 30 cm Mt C Total soil organic carbon stock in top 30 cm
Resources|Soil Carbon|Actual|Stock|SOC in top 30 cm|+|Cropland Soils Mt C SOC stock in cropland soils
Resources|Soil Carbon|Actual|Stock|SOC in top 30 cm|+|Noncropland Soils Mt C SOC stock in non-cropland soils

Soil carbon stock change variables

Name Unit Meta
Resources|Soil Carbon|Actual|Stock Change|SOC in top 30 cm Mt C wrt baseyear Change in total SOC stock relative to base year
Resources|Soil Carbon|Actual|Stock Change|SOC in top 30 cm|+|Cropland Soils Mt C wrt baseyear Change in cropland SOC stock relative to base year
Resources|Soil Carbon|Actual|Stock Change|SOC in top 30 cm|+|Noncropland Soils Mt C wrt baseyear Change in non-cropland SOC stock relative to base year

Actual soil carbon density variables

Name Unit Meta
Resources|Soil Carbon|Actual|Density|SOC in top 30 cm tC/ha Average SOC density in top 30 cm
Resources|Soil Carbon|Actual|Density|SOC in top 30 cm|Cropland Soils tC/ha SOC density in cropland soils
Resources|Soil Carbon|Actual|Density|SOC in top 30 cm|Noncropland Soils tC/ha SOC density in non-cropland soils

Target soil carbon stock variables

Name Unit Meta
Resources|Soil Carbon|Target|Stock|SOC in top 30 cm Mt C Target total SOC stock at steady state
Resources|Soil Carbon|Target|Stock|SOC in top 30 cm|+|Cropland Soils Mt C Target SOC stock in cropland soils
Resources|Soil Carbon|Target|Stock|SOC in top 30 cm|+|Noncropland Soils Mt C Target SOC stock in non-cropland soils

Target soil carbon density variables

Name Unit Meta
Resources|Soil Carbon|Target|Density|SOC in top 30 cm tC/ha Target average SOC density at steady state
Resources|Soil Carbon|Target|Density|SOC in top 30 cm|Cropland Soils tC/ha Target SOC density in cropland soils
Resources|Soil Carbon|Target|Density|SOC in top 30 cm|Noncropland Soils tC/ha Target SOC density in non-cropland soils

Actual carbon share variables

Name Unit Meta
Resources|Soil Carbon|Actual|Carbon Share|SOC in top 30 cm tC/tC SOC relative to natural state
Resources|Soil Carbon|Actual|Carbon Share|SOC in top 30 cm|Cropland Soils tC/tC Cropland SOC relative to natural state
Resources|Soil Carbon|Actual|Carbon Share|SOC in top 30 cm|Noncropland Soils tC/tC Non-cropland SOC relative to natural state

Target carbon share variables

Name Unit Meta
Resources|Soil Carbon|Target|Carbon Share|SOC in top 30 cm tC/tC Target SOC share at steady state
Resources|Soil Carbon|Target|Carbon Share|SOC in top 30 cm|Cropland Soils tC/tC Target cropland SOC share at steady state
Resources|Soil Carbon|Target|Carbon Share|SOC in top 30 cm|Noncropland Soils tC/tC Target non-cropland SOC share at steady state

Author(s)

Kristine Karstens

Examples

## Not run: 
    x <- reportSOM(gdx)
  
## End(Not run)

reportSOM2

Description

Report soil organic carbon stock size for future MAgPIE projections (new som realization)

Usage

reportSOM2(gdx, baseyear = 1995)

Arguments

gdx

GDX file
baseyear

baseyear for calculating carbon stock change

Actual soil carbon stock variables

Name Unit Meta
Resources|Soil Carbon|Actual|Stock|SOC in top 30 cm Mt C Actual soil organic carbon stock
Resources|Soil Carbon|Actual|Stock|SOC in top 30 cm|+|Cropland Soils Mt C SOC in cropland soils
Resources|Soil Carbon|Actual|Stock|SOC in top 30 cm|+|Noncropland Soils Mt C SOC in non-cropland soils

Target soil carbon stock variables

Name Unit Meta
Resources|Soil Carbon|Target|Stock|SOC in top 30 cm Mt C Target SOC stock at steady state
Resources|Soil Carbon|Target|Stock|SOC in top 30 cm|+|Cropland Soils Mt C Target SOC stock in cropland soils
Resources|Soil Carbon|Target|Stock|SOC in top 30 cm|+|Noncropland Soils Mt C Target SOC stock in non-cropland soils

Soil carbon stock change variables

Name Unit Meta
Resources|Soil Carbon|Actual|Stock Change|SOC in top 30 cm Mt C wrt baseyear Change in total SOC stock relative to base year
Resources|Soil Carbon|Actual|Stock Change|SOC in top 30 cm|+|Cropland Soils Mt C wrt baseyear Change in cropland SOC stock relative to base year
Resources|Soil Carbon|Actual|Stock Change|SOC in top 30 cm|+|Noncropland Soils Mt C wrt baseyear Change in non-cropland SOC stock relative to base year

Soil carbon debt variables

Name Unit Meta
Resources|Soil Carbon|Actual|Debt|SOC in top 30 cm Mt C SOC debt relative to natural state
Resources|Soil Carbon|Actual|Debt|SOC in top 30 cm|+|Cropland Soils Mt C Cropland SOC debt relative to natural state
Resources|Soil Carbon|Actual|Debt|SOC in top 30 cm|+|Noncropland Soils Mt C Non-cropland SOC debt relative to natural state

Actual soil carbon density variables

Name Unit Meta
Resources|Soil Carbon|Actual|Density|SOC in top 30 cm tC/ha SOC density
Resources|Soil Carbon|Actual|Density|SOC in top 30 cm|+|Cropland Soils tC/ha SOC density in cropland soils
Resources|Soil Carbon|Actual|Density|SOC in top 30 cm|+|Noncropland Soils tC/ha SOC density in non-cropland soils

Target soil carbon density variables

Name Unit Meta
Resources|Soil Carbon|Target|Density|SOC in top 30 cm tC/ha Target SOC density at steady state
Resources|Soil Carbon|Target|Density|SOC in top 30 cm|+|Cropland Soils tC/ha Target SOC density in cropland soils
Resources|Soil Carbon|Target|Density|SOC in top 30 cm|+|Noncropland Soils tC/ha Target SOC density in non-cropland soils

Actual carbon share variables

Name Unit Meta
Resources|Soil Carbon|Actual|Carbon Share|SOC in top 30 cm tC/tC SOC relative to natural state
Resources|Soil Carbon|Actual|Carbon Share|SOC in top 30 cm|+|Cropland Soils tC/tC Cropland SOC relative to natural state
Resources|Soil Carbon|Actual|Carbon Share|SOC in top 30 cm|+|Noncropland Soils tC/tC Non-cropland SOC relative to natural state

Target carbon share variables

Name Unit Meta
Resources|Soil Carbon|Target|Carbon Share|SOC in top 30 cm tC/tC Target SOC share at steady state
Resources|Soil Carbon|Target|Carbon Share|SOC in top 30 cm|+|Cropland Soils tC/tC Target cropland SOC share at steady state
Resources|Soil Carbon|Target|Carbon Share|SOC in top 30 cm|+|Noncropland Soils tC/tC Target non-cropland SOC share at steady state

Author(s)

Kristine Karstens

Examples

## Not run: 
    x <- reportSOM2(gdx)
  
## End(Not run)

reportTau

Description

reports Tau

Usage

reportTau(gdx, level = "regglo")

Arguments

gdx

GDX file
level

An aggregation level for the spatial dimension. Can be any level available via superAggregateX.

Value

tau values as MAgPIE object (Index)

Tau variables

Name Unit Meta
Productivity|Landuse Intensity Indicator Tau Index Agricultural land-use intensity indicator for crops

Author(s)

Florian Humpenoeder, Patrick v. Jeetze

Examples

## Not run: 
x <- reportTau(gdx)

## End(Not run)

reportTc

Description

reports Tc

Usage

reportTc(gdx, level = "regglo")

Arguments

gdx

GDX file
level

Aggregation level of the returned Tc report

Value

tc values as MAgPIE object (%/yr)

Technological change variables

Name Unit Meta
Productivity|Yield-increasing technological change crops %/yr Annual rate of yield-increasing technological change for crops

Author(s)

Florian Humpenoeder

Examples

## Not run: 
    x <- reportTc(gdx)
  
## End(Not run)

reportTimber

Description

reports MAgPIE demand for timber.

Usage

reportTimber(gdx, level = "regglo")

Arguments

gdx

GDX file
level

aggregation level of returned data ("regglo" by default)

Value

Timber demand

Timber demand variables

Name Unit Meta
Timber|Volumetric|Demand|+|Roundwood Mm3/yr Total roundwood demand
Timber|Volumetric|Demand|Roundwood|+|Industrial roundwood Mm3/yr Demand for industrial roundwood
Timber|Volumetric|Demand|Roundwood|+|Wood fuel Mm3/yr Demand for wood fuel
Timber|Volumetric|Demand|Roundwood|+|Timber for construction Mm3/yr Demand for timber used in construction

Timber production variables

Name Unit Meta
Timber|Volumetric|Production|+|Roundwood Mm3/yr Total roundwood production
Timber|Volumetric|Production|Roundwood|+|Industrial roundwood Mm3/yr Production of industrial roundwood
Timber|Volumetric|Production|Roundwood|+|Wood fuel Mm3/yr Production of wood fuel
Timber|Volumetric|Production|Roundwood|+|Timber for construction Mm3/yr Production of timber for construction

Timber trade variables

Name Unit Meta
Timber|Volumetric|Net-Trade|+|Roundwood Mm3/yr Net export of roundwood
Timber|Volumetric|Net-Trade|Roundwood|+|Industrial roundwood Mm3/yr Net export of industrial roundwood
Timber|Volumetric|Net-Trade|Roundwood|+|Wood fuel Mm3/yr Net export of wood fuel
Timber|Volumetric|Net-Trade|Roundwood|+|Timber for construction Mm3/yr Net export of timber for construction
Timber|Volumetric|Exports|+|Roundwood Mm3/yr Gross exports of roundwood
Timber|Volumetric|Exports|Roundwood|+|Industrial roundwood Mm3/yr Gross exports of industrial roundwood
Timber|Volumetric|Exports|Roundwood|+|Wood fuel Mm3/yr Gross exports of wood fuel
Timber|Volumetric|Exports|Roundwood|+|Timber for construction Mm3/yr Gross exports of timber for construction
Timber|Volumetric|Imports|+|Roundwood Mm3/yr Gross imports of roundwood
Timber|Volumetric|Imports|Roundwood|+|Industrial roundwood Mm3/yr Gross imports of industrial roundwood
Timber|Volumetric|Imports|Roundwood|+|Wood fuel Mm3/yr Gross imports of wood fuel
Timber|Volumetric|Imports|Roundwood|+|Timber for construction Mm3/yr Gross imports of timber for construction

Author(s)

Abhijeet Mishra

Examples

## Not run: 
    x <- reportTimber(gdx)
  
## End(Not run)

reportTimberDemand

Description

reports MAgPIE demand for timber in tDM (complementing reportTimber which reports in Mm3).

Usage

reportTimberDemand(gdx)

Arguments

gdx

GDX file

Value

Timber demand

Timber demand variables

Name Unit Meta
Timber demand|Roundwood mio tDM Total roundwood demand
Timber demand|Industrial roundwood mio tDM Industrial wood demand
Timber demand|Wood fuel mio tDM Wood fuel demand

Author(s)

Abhijeet Mishra

Examples

## Not run: 
    x <- reportTimberDemand(gdx)
  
## End(Not run)

reportTotalHoursWorked

Description

reports total hours worked in crop+livestock production (and maccs) from MAgPIE results

Usage

reportTotalHoursWorked(gdx, level = "regglo")

Arguments

gdx

GDX file
level

spatial aggregation: "reg", "glo", "regglo"

Value

total hours worked as MAgPIE object

Total hours worked variables

Name Unit Meta
Labor|Total Hours Worked mio h Total hours worked in crop and livestock production

Author(s)

Debbora Leip

Examples

## Not run: 
    x <- reportTotalHoursWorked(gdx)
  
## End(Not run)

reportTrade

Description

reports trade

Usage

reportTrade(gdx, detail = FALSE, level = "regglo")

Arguments

gdx

GDX file
detail

if true, provides estimates for all commodities, otherwise aggregates some groups
level

The aggregation level of the trade reporting

Value

Net-Exports and self sufficiency (exports/domestic supply) as MAgPIE object. Unit: see names

Net trade variables

Name Unit Meta
Trade|Net-Trade|+|Crops Mt DM/yr Net export of crops (positive = net exporter)
Trade|Net-Trade|+|Livestock products Mt DM/yr Net export of livestock products (excluding fish)
Trade|Net-Trade|+|Secondary products Mt DM/yr Net export of secondary products
Trade|Net-Trade|+|Bioenergy crops Mt DM/yr Net export of bioenergy crops

Gross trade variables

Name Unit Meta
Trade|Exports|+|Crops Mt DM/yr Gross exports of crops
Trade|Exports|+|Livestock products Mt DM/yr Gross exports of livestock products
Trade|Imports|+|Crops Mt DM/yr Gross imports of crops
Trade|Imports|+|Livestock products Mt DM/yr Gross imports of livestock products

Self-sufficiency variables

Name Unit Meta
Trade|Self-sufficiency|+|Crops 1 Self-sufficiency ratio for crops (production/domestic supply)
Trade|Self-sufficiency|+|Livestock products 1 Self-sufficiency ratio for livestock products

Author(s)

Benjamin Leon Bodirsky, Mishko Stevanovic

Examples

## Not run: 
    x <- reportTrade(gdx="fulldata.gdx",detail=TRUE)
  
## End(Not run)

reportTradeGrowth

Description

reports trade growth rate

Usage

reportTradeGrowth(gdx, detail = FALSE)

Arguments

gdx

GDX file
detail

if true, provides results for all commodities, otherwhise aggregates some groups

Value

Trade growth rates (index)

Trade growth variables

Name Unit Meta
Trade|Trade Growth Rate Index Trade volume index relative to base year
Trade|Trade Growth Rate|+|Crop products Index Crop trade growth index
Trade|Trade Growth Rate|+|Livestock products Index Livestock trade growth index

Author(s)

Xiaoxi Wang

Examples

## Not run: 
    x <- reportTradeGrowth(gdx="fulldata.gdx",detail=TRUE)
  
## End(Not run)

reportValueMaterialDemand

Description

reports value of material demand

Usage

reportValueMaterialDemand(gdx, level = "regglo")

Arguments

gdx

GDX file
level

aggregation level of returned data ("regglo" by default)

Value

magpie object

Material demand value variables

Name Unit Meta
Value|Bioeconomy Demand million US$2017/yr Total value of bioeconomy material demand
Value|Bioeconomy Demand|+|Crops million US$2017/yr Value of crop products for material demand
Value|Bioeconomy Demand|+|Residues million US$2017/yr Value of residues for material demand

Author(s)

David Chen

Examples

## Not run: 
x <- reportValueMaterialDemand(gdx)

## End(Not run)

reportValueTrade

Description

reports trade value

Usage

reportValueTrade(gdx, detail = FALSE, level = "regglo")

Arguments

gdx

GDX file
detail

if true, provides estimates for all commodities, otherwhise aggregates some groups
level

aggregation level of returned data ("regglo" by default)

Value

trade value as MAgPIE object Unit: see names

Trade value variables

Name Unit Meta
Trade Value|Net-Exports million US$2017/yr Net trade value (exports minus imports)
Trade Value|Exports million US$2017/yr Gross export value
Trade Value|Imports million US$2017/yr Gross import value

Author(s)

Florian Humpenoeder

Examples

## Not run: 
    x <- reportValueTrade(gdx)
  
## End(Not run)

reportVegfruitShare

Description

reports the share of livestock products (including fish) in total calorie food supply

Usage

reportVegfruitShare(gdx, level = "regglo")

Arguments

gdx

GDX file
level

An aggregation level for the spatial dimension. Can be any level available via superAggregateX.

Value

per-capita calories as MAgPIE object (kcal/cap/day)

Vegfruit share variables

Name Unit Meta
Nutrition|Dietary Composition|Vegetables Fruits Nuts Share kcal/kcal Share of vegetables, fruits, and nuts in total calorie supply

Author(s)

Benjamin Leon Bodirsky

Examples

## Not run: 
    x <- reportLivestockShare(gdx)
  
## End(Not run)

reportWageDevelopment

Description

reports indicator on wage development: hourly labor costs in each time step relative to hourly labor costs in 2000

Usage

reportWageDevelopment(gdx, baseYear = 2000, level = "regglo")

Arguments

gdx

GDX file
baseYear

year relative to which the wage development should be calculated
level

spatial aggregation: "reg", "glo", "regglo"

Value

indicator on wage development as MAgPIE object

Wage development variables

Name Unit Meta
Labor|Wages|Hourly labor costs relative to 2000 index Hourly labor cost development relative to base year

Author(s)

Debbora Leip

Examples

## Not run: 
x <- reportWageDevelopment(gdx)

## End(Not run)

reportWaterAvailability

Description

reports water availability

Usage

reportWaterAvailability(gdx, level = "regglo")

Arguments

gdx

GDX file
level

aggregation level of returned data ("regglo" by default)

Value

water availability as MAgPIE object Unit: see names

Water availability variables

Name Unit Meta
Resources|Water|Availability|Agriculture km3/yr Water available for agricultural use

Author(s)

Felicitas Beier

Examples

## Not run: 
    x <- reportWaterAvailability(gdx)
  
## End(Not run)

reportWaterIndicators

Description

reports a set of water indicators

Usage

reportWaterIndicators(gdx, level = "regglo")

Arguments

gdx

GDX file
level

aggregation level of returned data ("regglo" by default)

Value

MAgPIE object

Water indicator variables

Name Unit Meta
Water|Environmental flow violation volume km3/yr Volume of environmental flow violations
Water|Environmental flow violation share of total water withdrawals share EFV share of human water withdrawals
Water|Environmental flow violation share of water availability share EFV share of water availability
Water|Irrigated Area suffering under Environmental Flow Violation Mha Area in clusters with EFV
Water|Share of total Irrigated Area suffering from Environmental Flow Violations share Share of irrigated area in EFV clusters
Water|Withdrawal to Availability ratio fraction Water stress indicator

Author(s)

Felicitas Beier

Examples

## Not run: 
x <- reportWaterIndicators(gdx)

## End(Not run)

reportWaterUsage

Description

reports water usage for agricultural sector, crops and livestock and non-agricultural sector

Usage

reportWaterUsage(gdx, detail = TRUE, level = "regglo")

Arguments

gdx

GDX file
detail

logical. Setting to FALSE reports for agricultural sector, TRUE reports for combined, crops and livestock separately
level

aggregation level of returned data ("regglo" by default)

Value

water usage as MAgPIE object Unit: see names

Agricultural water withdrawal variables

Name Unit Meta
Resources|Water|Withdrawal|Agriculture km3/yr Total agricultural water withdrawal
Resources|Water|Withdrawal|Agriculture|Crops km3/yr Water withdrawal for crop irrigation
Resources|Water|Withdrawal|Agriculture|Crops|+|Crops km3/yr Water withdrawal for food and feed crops
Resources|Water|Withdrawal|Agriculture|Crops|+|Bioenergy crops km3/yr Water withdrawal for bioenergy crops
Resources|Water|Withdrawal|Agriculture|Livestock|+|Livestock products km3/yr Water withdrawal for livestock

Agricultural water consumption variables

Name Unit Meta
Resources|Water|Consumption|Agriculture km3/yr Total agricultural water consumption
Resources|Water|Consumption|Agriculture|Crops km3/yr Water consumption for crop irrigation
Resources|Water|Consumption|Agriculture|Livestock km3/yr Water consumption for livestock

Non-agricultural water variables

Name Unit Meta
Resources|Water|Withdrawal|Non-agriculture km3/yr Total non-agricultural water withdrawal
Resources|Water|Withdrawal|Non-agriculture|+|domestic km3/yr Water withdrawal for domestic use
Resources|Water|Withdrawal|Non-agriculture|+|manufacturing km3/yr Water withdrawal for manufacturing sector
Resources|Water|Withdrawal|Non-agriculture|+|electricity km3/yr Water withdrawal for electricity generation
Resources|Water|Consumption|Non-agriculture km3/yr Total non-agricultural water consumption

Author(s)

Florian Humpenoeder, Vartika Singh, Miodrag Stevanovic, Felicitas Beier

Examples

## Not run: 
x <- reportWaterUsage(gdx)

## End(Not run)

reportWoodFuel

Description

Reports wood fuel demand from a MAgPIE GDX file at ISO country level and converts from volumetric units (Mm³) to energy (PJ).

Usage

reportWoodFuel(gdx, file = NULL)

Arguments

gdx

GDX file
file

a file name the output should be written to using write.magpie

Value

MAgPIE object with wood fuel demand at ISO level in PJ. Dimension 1: ISO country, Dimension 2: year, Dimension 3: "woodfuel"

Author(s)

Kristine Karstens

Examples

## Not run: 
  x <- reportWoodFuel(gdx)

## End(Not run)

reportWorkingAgePopulation

Description

reports working age population

Usage

reportWorkingAgePopulation(gdx, level = "regglo")

Arguments

gdx

GDX file
level

spatial aggregation: "reg", "glo", "regglo", "iso"

Value

working age population as MAgPIE object

Working age population variables

Name Unit Meta
Working age population million people Population aged 15-64 years

Author(s)

Debbora Leip

Examples

## Not run: 
    x <- reportWorkingAgePopulation(gdx)
  
## End(Not run)

reportYields

Description

reports yields

Usage

reportYields(gdx, detail = FALSE, physical = TRUE, level = "regglo")

Arguments

gdx

GDX file
detail

if detail=FALSE, the subcategories of groups are not reported (e.g. "soybean" within "oilcrops")
physical

if true (default) physical area (croparea) used for yield calculation; if false harvested area used for yield calculation
level

aggregation level of returned data ("regglo" by default)

Value

yield as MAgPIE object (Mt DM/ha)

Yield variables

Name Unit Meta
Productivity|Yield t DM/ha Crop yields calculated as production divided by physical cropland area
Productivity|Yield|+|Crops t DM/ha Yield of all crops
Productivity|Yield|Crops|+|Cereals t DM/ha Yield of cereals (maize, rice, temperate cereals and tropical cereals)
Productivity|Yield|Crops|+|Oil crops t DM/ha Yield of oil crops (cotton seed, groundnuts, oilpalms, other oil crops, soybean, sunflower)
Productivity|Yield|Crops|+|Sugar crops t DM/ha Yield of sugar crops (sugar beet, sugar cane)
Productivity|Yield|Crops|+|Other crops t DM/ha Yield of other crops (fruits, vegetables, nuts, potatoes, pulses, tropical roots)
Productivity|Yield|+|Pasture t DM/ha Yield of pasture biomass
Productivity|Yield|++|Irrigated t DM/ha Yield on irrigated cropland
Productivity|Yield|++|Rainfed t DM/ha Yield on rainfed cropland

Yield by harvested area variables

Name Unit Meta
Productivity|Yield by harvested area t DM/ha Crop yields calculated as production divided by harvested cropland area
Productivity|Yield by harvested area|+|Crops t DM/ha Yield by harvested area of all crops
Productivity|Yield by harvested area|Crops|+|Cereals t DM/ha Yield by harvested area of cereals

Author(s)

Florian Humpenoeder, Xiaoxi Wang, Kristine Karstens, Abhijeet Mishra, Felicitas Beier

Examples

## Not run: 
x <- reportYields(gdx)

## End(Not run)

reportYieldsCropCalib

Description

reports potential yields after calibration

Usage

reportYieldsCropCalib(gdx, detail = FALSE, level = "regglo")

Arguments

gdx

GDX file
detail

if detail=FALSE, the subcategories of groups are not reported (e.g. "soybean" within "oilcrops")
level

aggregation level of returned data ("regglo" by default)

Value

yield as MAgPIE object (Mt DM/ha)

Calibrated yield variables

Name Unit Meta
Productivity|Yield (after calibration) t DM/ha Potential crop yields after calibration
Productivity|Yield (after calibration)|+|Cereals t DM/ha Calibrated cereal yields
Productivity|Yield (including tau) t DM/ha Potential yields including tau factor

Author(s)

Edna J. Molina Bacca

Examples

## Not run: 
x <- reportYieldsCropCalib(gdx)

## End(Not run)

reportYieldsCropRaw

Description

reports potential yields before calibration

Usage

reportYieldsCropRaw(gdx, detail = FALSE, level = "regglo")

Arguments

gdx

GDX file
detail

if detail=FALSE, the subcategories of groups are not reported (e.g. "soybean" within "oilcrops")
level

aggregation level of returned data ("regglo" by default)

Value

yield as MAgPIE object (Mt DM/ha)

Raw yield variables

Name Unit Meta
Productivity|Yield (before calibration) t DM/ha Potential crop yields before calibration
Productivity|Yield (before calibration)|+|Cereals t DM/ha Uncalibrated cereal yields

Author(s)

Edna J. Molina Bacca

Examples

## Not run: 
x <- reportYieldsCropRaw(gdx)

## End(Not run)

reportYieldShifter

Description

Reports the Crop model input yield shifter

Usage

reportYieldShifter(
  gdx,
  file = NULL,
  level = "reg",
  baseyear = "y2000",
  relative = TRUE
)

Arguments

gdx

GDX file
file

a file name the output should be written to using write.magpie
level

Level of regional aggregation; "reg" (regional), "glo" (global), "regglo" (regional and global) or any other aggregation level defined in superAggregate
baseyear

baseyear for the yield shifter. Also fixes land patterns for aggregation to baseyear.
relative

relative or absolute changes to baseyear

Value

crop yield as MAgPIE object (unit depends on attributes)

Yield shifter variables

Name Unit Meta
Productivity|Climate Change Yield Shifter Index baseyear=1 Climate-induced yield changes relative to base year
Productivity|Climate Change Yield Shifter|Cereals|Rainfed Index baseyear=1 Yield shifter for rainfed cereals
Productivity|Climate Change Yield Shifter|Cereals|Irrigated Index baseyear=1 Yield shifter for irrigated cereals

Author(s)

Benjamin Leon Bodirsky

See Also

reportYieldShifter

Examples

## Not run: 
    x <- reportYieldShifter(gdx)
  
## End(Not run)

ResidueBiomass

Description

reads Crop Residue Biomass out of a MAgPIE gdx file

Usage

ResidueBiomass(
  gdx,
  level = "reg",
  products = "kcr",
  product_aggr = FALSE,
  attributes = "dm",
  water_aggr = TRUE,
  plantpart = "both"
)

Arguments

gdx

GDX file
level

Level of regional aggregation; "reg" (regional), "glo" (global), "regglo" (regional and global) or any other aggregation level defined in gdxAggregate
products

Selection of products (either by naming products, e.g. "tece", or naming a set,e.g."kcr")
product_aggr

aggregate over products or not. Usually boolean, but here also the value "kres" is allowed, which provides kcr aggregated to kres
attributes

dry matter: Mt ("dm"), gross energy: PJ ("ge"), reactive nitrogen: Mt ("nr"), phosphor: Mt ("p"), potash: Mt ("k"), wet matter: Mt ("wm"). Can also be a vector.
water_aggr

aggregate irrigated and non-irriagted production or not (boolean).
plantpart

both ag or bg

Value

production as MAgPIE object (unit depends on attributes)

Author(s)

Benjamin Leon Bodirsky

See Also

reportProduction, demand

Examples

## Not run: 
x <- production(gdx)

## End(Not run)

Residues

Description

reads various crop residue (carbon) outputs out of a MAgPIE gdx file

Usage

Residues(
  gdx,
  level = "regglo",
  products = "kres",
  waterAggr = TRUE,
  output = "all"
)

Arguments

gdx

GDX file
level

Level of regional aggregation; "reg" (regional), "glo" (global), "regglo" (regional and global)
products

Selection of products (either "kcr" or "kres")
waterAggr

Aggregate irrigated and non-irriagted production or not (boolean).
output

Switch between different outputs: "biomass", "fieldBalance", "resDemand", all

Value

production as MAgPIE object (unit depends on attributes)

Author(s)

Kristine Karstens, Michael Crawford

See Also

ResidueBiomass

Examples

## Not run: 
    x <- Residues(gdx)
  
## End(Not run)

ResidueUsage

Description

reads Crop Residue Usage out of a MAgPIE gdx file

Usage

ResidueUsage(
  gdx,
  level = "reg",
  products = "kcr",
  product_aggr = FALSE,
  attributes = "dm",
  water_aggr = TRUE
)

Arguments

gdx

GDX file
level

Level of regional aggregation; "reg" (regional), "glo" (global), "regglo" (regional and global) or any other aggregation level defined in gdxAggregate
products

Selection of products (either by naming products, e.g. "tece", or naming a set,e.g."kcr")
product_aggr

aggregate over products or not. Usually boolean, but here also the value "kres" is allowed, which provides kcr aggregated to kres
attributes

dry matter: Mt ("dm"), gross energy: PJ ("ge"), reactive nitrogen: Mt ("nr"), phosphor: Mt ("p"), potash: Mt ("k"), wet matter: Mt ("wm"). Can also be a vector.
water_aggr

aggregate irrigated and non-irriagted production or not (boolean).

Value

production as MAgPIE object (unit depends on attributes)

Author(s)

Kristine Karstens, Michael Crawford

See Also

ResidueBiomass

Examples

## Not run: 
x <- ResidueUsage(gdx)

## End(Not run)

RotationLength

Description

reads rotation length out of a MAgPIE gdx file

Usage

RotationLength(gdx, file = NULL, level = "regglo")

Arguments

gdx

GDX file
file

a file name the output should be written to using write.magpie
level

Level of regional aggregation; "cell", "reg" (regional), "glo" (global), "regglo" (regional and global) or any secdforest aggregation level defined in superAggregate

Details

Forest rotation length

Value

Forest rotation length

Author(s)

Abhijeet Mishra

Examples

## Not run: 
    x <- RotationLength(gdx)
  
## End(Not run)

ruralDemandShares

Description

reports rural demand shares based on local consumption

Usage

ruralDemandShares(
  gdx,
  type = "tradOnly",
  level = "reg",
  product_aggr = TRUE,
  file = NULL
)

Arguments

gdx

GDX file
type

Type of ratio that should be calculated

  • all: How much rural & trad demand as a share of all demand is satisfied locally

  • tradOnly: How much rural & trad demand as a share of rural & trad demand is satisfied locally

  • potential: How much total gridded demand is potentially satisfied by gridded production

level

spatial aggregation to report employment ("reg", "glo" or "regglo")
product_aggr

sum over products if TRUE
file

a file name the output should be written to using write.magpie

Value

share of food consumed locally

Author(s)

David M Chen

Examples

## Not run: 
x <- localDemandShares(gdx)

## End(Not run)

Seed

Description

Calculates MAgPIE demand for Seed out of a gdx file

Usage

Seed(gdx, level = "reg", attributes = "dm")

Arguments

gdx

GDX file
level

Level of regional aggregation ("reg", "glo", "regglo")
attributes

dry matter: Mt ("dm"), gross energy: PJ ("ge"), reactive nitrogen: Mt ("nr"), phosphor: Mt ("p"), potash: Mt ("k"), wet matter: Mt ("wm"). Can also be a vector.

Details

Demand definitions are equivalent to FAO CBS categories

Value

demand as MAgPIE object (Unit depends on attributes)

Author(s)

Benjamin Leon Bodirsky

Examples

## Not run: 
    x <- demand(level="regglo", products="kcr")
  
## End(Not run)

SOM

Description

Calculates soil organic carbon stock size based on a MAgPIE gdx file

Usage

SOM(
  gdx,
  file = NULL,
  type = "stock",
  reference = "actual",
  level = "reg",
  noncrop_aggr = TRUE
)

Arguments

gdx

GDX file
file

a file name the output should be written to using write.magpie
type

"stock" (default) for absoulte values, "density" for per hectar values
reference

default is "actual" (cshare in actual carbon stocks). Other option is "target" (cshare in target carbon stocks).
level

Level of regional aggregation; "reg" (regional), "glo" (global), "regglo" (regional and global) or any other aggregation level defined in superAggregate
noncrop_aggr

aggregate non cropland types to 'noncropland' (if FALSE all land types of pools59 will be reported)

Value

A MAgPIE object containing som values

Author(s)

Kristine Karstens

Examples

## Not run: 
x <- SOM(gdx)

## End(Not run)

SOM2

Description

Calculates soil organic carbon stock size based on a MAgPIE gdx file (for threepool realization)

Usage

SOM2(gdx, type = "stock", level = "regglo", noncropAggr = TRUE)

Arguments

gdx

GDX file
type

"stock" (default) for absoulte values, "density" for per hectar values
level

Level of regional aggregation; "reg" (regional), "glo" (global), "regglo" (regional and global)
noncropAggr

aggregate non cropland types to 'noncropland' (if FALSE all land types of pools59 will be reported)

Value

A MAgPIE object containing som values

Author(s)

Kristine Karstens

Examples

## Not run: 
  x <- SOM2(gdx)

## End(Not run)

submitCalibration

Description

Submits Calibration Factors of current run to calibration archive. Currently covers calibration factors for yields and land conversion costs. This is useful to make runs more comparable to each other. The function can be also used as part of a script running a collection of runs.

Usage

submitCalibration(
  name,
  file = c("modules/14_yields/input/f14_yld_calib.csv",
    "modules/39_landconversion/input/f39_calib.cs3"),
  archive = "/p/projects/landuse/data/input/calibration"
)

Arguments

name

name under which the calibration should be stored. Should be as self-explaining as possible. The total file name has the format calibration_<name>_<date>.tgz.
file

path to a f14_yld_calib.csv and f39_calib.cs3 (older version f39_calib.csv) file (in this order). Alternatively a fulldata.gdx file containing the calibration factors can be used. Supported file types are "csv", "cs3" and "gdx".
archive

path to the archive the calibration factors should be stored

Value

file name of the stored calibration factors (useful for scripts in which you might want to re-use a calibration setting at a later stage again)

Author(s)

Jan Philipp Dietrich, Florian Humpenoeder, Patrick v. Jeetze

Examples

## Not run: 
fname <- submitCalibration("TestCalibration", file = "fulldata.gdx")

## End(Not run)

superAggregateX

Description

drop-in replacement for superAggregate based on toolAggregate

Usage

superAggregateX(
  data,
  aggr_type,
  level = "reg",
  weight = NULL,
  crop_aggr = FALSE
)

Arguments

data

A MAgPIE object
aggr_type

Aggregation Type. Can be any function for one or two objects (data and weight) of the same size. Currently pre-supported functions: "sum","mean","weighted_mean".
level

Either a level or the name of a mapping file. Allowed level types are global "glo", regional "reg" and "regglo". The mapping file can only map from regions to other regions.
weight

Currently only used for weighted_mean
crop_aggr

determines whether output should be crop-specific (FALSE) or aggregated over all crops (TRUE). The method used for aggregation is set by aggr_type

Value

returns a MAgPIE object.

Author(s)

Jan Philipp Dietrich

See Also

Other Spatial: addGeometry(), clusterOutputToTerraVector(), gdxAggregate(), mappingToLongFormat()

surplusChange

Description

calculates aggregate change in economic surplus in mio.US$ based on a MAgPIE gdx files from two different scenarios.

Usage

surplusChange(gdx1, gdx2, file = NULL, level = "reg", type = "consumer")

Arguments

gdx1

GDX file from benchmark scenario
gdx2

GDX file from the analyzed scenario
file

a file name the output should be written to using write.magpie
level

Level of regional aggregation; "reg" (regional), "glo" (global), "regglo" (regional and global) or any other aggregation level defined in superAggregate
type

Economic surplus type: "consumer" (default), "producer" or "welfare"

Value

A MAgPIE object containing aggregate changes in producer surplus, consumer surplus and aggregate economic welfare between an analyzed scenario and a benchmark scenario, in million $US.

Author(s)

Miodrag Stevanovic

Examples

## Not run: 
    x <- surplusChange(gdx1, gdx2)
  
## End(Not run)

tau

Description

Calculates Landuse intensity indicator tau based on a MAgPIE gdx file

Usage

tau(
  gdx,
  file = NULL,
  level = "reg",
  start_value = FALSE,
  digits = 4,
  prev_year = "y1985",
  type = "crop"
)

Arguments

gdx

GDX file
file

a file name the output should be written to using write.magpie
level

Level of regional aggregation; "reg" (regional), "glo" (global), "regglo" (regional and global) or any other aggregation level defined in superAggregateX
start_value

If TRUE, the initial values are added under the year prev_year
digits

The result will be rounded to this number of digits
prev_year

Year to store the initialization tau information in
type

currently only "crop"

Value

A MAgPIE object containing tau values (index)

Author(s)

Jan Philipp Dietrich, Patrick v. Jeetze

Examples

## Not run: 
x <- tau(gdx)

## End(Not run)

taxRevenueRotations

Description

calculates taxes of crop rotations as difference between the selected scenario and the baseline scenario that shall capture the internalized incentives for crop rotations.

Usage

taxRevenueRotations(
  gdx,
  file = NULL,
  level = "regglo",
  penalty = "onlyTaxRevenue"
)

Arguments

gdx

GDX file
file

a file name the output should be written to using write.magpie
level

aggregation level, reg, glo or regglo
penalty

"OnlyTaxRevenue" provides the tax Revenues from a rotation tax/subsidy. "OnlyInternalizedServices" provides the penalty by foregone Ecosystem Services, the part of the externality which is internalized by the farmer independent of the tax. "FullPenalty" provides the sum of both, which is what the model sees.

Author(s)

Benjamin Leon Bodirsky

Examples

## Not run: 
x <- wageRent(gdx)

## End(Not run)

tc

Description

Calculates TC rates based on a MAgPIE gdx file

Usage

tc(
  gdx,
  file = NULL,
  level = "reg",
  annual = TRUE,
  avrg = FALSE,
  baseyear = 1995,
  type = "crop"
)

Arguments

gdx

GDX file
file

a file name the output should be written to using write.magpie
level

Level of regional aggregation; "reg" (regional), "glo" (global), "regglo" (regional and global) or any other aggregation level defined in superAggregate
annual

If TRUE, annual values are reported. If FALSE, the values for the whole timestep are reported. If FALSE, avrg has no effect
avrg

If FALSE the annual tc rates of the current period are returned, otherwise the average annual tc rate for the period tbase to tn is returned. tbase defaults to the first timestep (see baseyear)
baseyear

Determines the base year timestep for annual tc calculation. Average tc rates for later timesteps are calculated with respect to baseyear. No tc rates for timesteps before baseyear are returned)
type

currently only 'crop'

Value

A MAgPIE object containing tc rates. Annual ones if annual=TRUE, for the whole timestep if annual=FALSE.

Author(s)

Jan Philipp Dietrich

Examples

## Not run: 
x <- tc(gdx)

## End(Not run)

Timber

Description

reads timber demand out of a MAgPIE gdx file

Usage

Timber(gdx, file = NULL, level = "regglo")

Arguments

gdx

GDX file
file

a file name the output should be written to using write.magpie
level

Level of regional aggregation; "cell", "reg" (regional), "regglo" (regional and global), custom region aggregation or any secdforest aggregation level defined in superAggregateX

Details

Forest demandfor timber production

Value

Forest demandfor timber production

Author(s)

Abhijeet Mishra

Examples

## Not run: 
    x <- Timber(gdx)
  
## End(Not run)

TimberDemand

Description

reads timber demand out of a MAgPIE gdx file

Usage

TimberDemand(gdx, file = NULL, level = "regglo")

Arguments

gdx

GDX file
file

a file name the output should be written to using write.magpie
level

Level of regional aggregation; "cell", "reg" (regional), "glo" (global), "regglo" (regional and global) or any secdforest aggregation level defined in superAggregate

Details

Forest demandfor timber production

Value

Forest demandfor timber production

Author(s)

Abhijeet Mishra

Examples

## Not run: 
    x <- TimberDemand(gdx)
  
## End(Not run)

TimberProductionVolumetric

Description

reads timber production out of a MAgPIE gdx file

Usage

TimberProductionVolumetric(
  gdx,
  file = NULL,
  level = "regglo",
  sumProduct = FALSE,
  sumSource = TRUE
)

Arguments

gdx

GDX file
file

a file name the output should be written to using write.magpie
level

Level of regional aggregation; "cell", "reg" (regional), "glo" (global), "regglo" (regional and global) or any secdforest aggregation level defined in superAggregate
sumProduct

sum over wood and woodfuel (TRUE/FALSE)
sumSource

sum over timber sources: timber plantations, primary forest, secondary forest and non-forest land (woodfuel only) (TRUE/FALSE)

Details

Annual timber production from timber plantations, primary forest, secondary forest and non-forest land (woodfuel only). Converted from mio. ton DM per year to mio. m3 per year using volumetric conversion factors.

Value

Timber production in mio. m3 per year

Author(s)

Abhijeet Mishra, Florian Humpenoeder

Examples

## Not run: 
x <- TimberProductionVolumetric(gdx)

## End(Not run)

timePeriods

Description

Calculates MAgPIE time period lengths between each two timesteps

Usage

timePeriods(gdx)

Arguments

gdx

GDX file

Value

magpie time periods as MAgPIE object as a number of years

Author(s)

Mishko Stevanovic

Examples

## Not run: 
    x <- timePeriods(gdx=gdx)
  
## End(Not run)

totalHoursWorked

Description

returns total hours worked per year in crop+livestock production from MAgPIE results

Usage

totalHoursWorked(gdx, level = "reg", file = NULL)

Arguments

gdx

GDX file
level

spatial aggregation to report employment ("reg", "glo", or "regglo")
file

a file name the output should be written to using write.magpie

Value

total hours worked in agriculture per year

Author(s)

Debbora Leip

Examples

## Not run: 
x <- totalHoursWorked(gdx)

## End(Not run)

trade

Description

Calculates MAgPIE trade or self-sufficiencies out of a gdx file

Usage

trade(
  gdx,
  file = NULL,
  level = "reg",
  products = "k_trade",
  productAggr = FALSE,
  attributes = "dm",
  weight = FALSE,
  relative = FALSE,
  type = "net-exports"
)

Arguments

gdx

GDX file
file

a file name the output should be written to using write.magpie
level

Level of regional aggregation ("reg", "glo", "regglo", or name of custom mapping)
products

Selection of products (either by naming products, e.g. "tece", or naming a set,e.g."kcr")
productAggr

aggregate over products or not (boolean)
attributes

dry matter: Mt ("dm"), gross energy: PJ ("ge"), reactive nitrogen: Mt ("nr"), phosphor: Mt ("p"), potash: Mt ("k"), wet matter: Mt ("wm"). Can also be a vector.
weight

in case relative=T also the weighting for the self sufficiencies is provided as it is an intensive parameter
relative

if relative=TRUE, self sufficiencies are reported, so the amount of production divided by domestic demand
type

exports-imports ("net-exports"), gross imports ("imports") or gross exports ("exports"), in the bilateral case we report a few others given balanceflow: ; only valid if relative=FALSE

Details

Trade definitions are equivalent to FAO CBS categories

Value

trade (production-demand) as MAgPIE object; unit depends on attributes

Author(s)

Benjamin Leon Bodirsky, Florian Humpenoeder, Mishko Stevanovic

Examples

## Not run: 
    x <- trade(gdx="fulldata.gdx", level="regglo", products="kcr")
  
## End(Not run)

tradedPrimariesBilateral

Description

Converts trade flows into primary product equivalents by tracing secondary and livestock products back to their primary inputs. Supports both net trade flows and bilateral trade matrices. Trade flows are decomposed into three pathways: (1) direct primary trade, (2) primaries embodied in secondary products, and (3) primaries needed as feed for livestock.

Usage

tradedPrimariesBilateral(
  gdx,
  file = NULL,
  bilateral = TRUE,
  convFactor = "exporter",
  kastner = TRUE,
  level = "reg",
  disaggLivestock = FALSE
)

Arguments

gdx

GDX file
file

a file name the output should be written to using write.magpie
bilateral

Logical. If TRUE, uses bilateral trade matrix (ov21_trade) if available. If FALSE, uses net trade flows. Default is TRUE.
convFactor

Character. When using bilateral trade, determines whether processing shares and feed baskets are taken from "exporter" or "importer" region. Default is "exporter" (footprint allocation to producing region).
kastner

Logical. If TRUE and bilateral=TRUE, applies Kastner et al. 2011 adjustment to bilateral trade matrix. Default is TRUE.
level

Regional aggregation level ("reg", "glo", "regglo", or custom). Default is "reg".
disaggLivestock

Logical. If TRUE, the feed pathway retains the livestock product dimension so that feed crop demands can be traced back to specific animal products. Output dim 3 will be kli_product.kve_product for the feed pathway instead of the aggregated feed.kve_product. The prim and secd pathways are unchanged (pathway.kve_product). Default is FALSE.

Details

When convFactor="exporter", the exporting region's processing pathways and feed baskets are used, which is appropriate for production-based footprint accounting. When convFactor="importer", the importing region's factors are used, which maintains backward compatibility with the original tradedPrimaries function.

For bilateral trade, the output includes full origin-destination detail. For net trade, the output is aggregated by region.

When disaggLivestock=TRUE, callers can assign embodied resources either to the feed crop (collapse dim 3.1, i.e. the livestock dimension) or to the animal product (collapse dim 3.2, i.e. the crop dimension).

Value

MAgPIE object with primary product trade equivalents in dry matter (tDM). For bilateral trade: dimensions are (exporter.importer, year, pathway.product) For net trade: dimensions are (region, year, pathway.product) When disaggLivestock=TRUE: feed items have dimensions kli_product.kve_product instead of feed.kve_product; prim/secd items are unchanged.

Author(s)

David M Chen, Kristine Karstens

Examples

## Not run: 
  # Bilateral trade with exporter's factors (production-based accounting)
  x <- tradedPrimariesBilateral(gdx, bilateral = TRUE, convFactor = "exporter")
  
  # Bilateral trade with importer's factors (consumption-based accounting)
  x <- tradedPrimariesBilateral(gdx, bilateral = TRUE, convFactor = "importer")
  
  # Net trade (backward compatible with tradedPrimaries)
  x <- tradedPrimariesBilateral(gdx, bilateral = FALSE)

## End(Not run)

tradeKastner

Description

Implements Kastner et al. 2011 (DOI: 10.1016/j.ecolecon.2011.01.012) on the MAgPIE bilateral trade matrix. Adjusts the trade matrix based on a assumption of proportionality such that intermediate trade partners (importing to re-export) are removed from the matrix.

Usage

tradeKastner(gdx, trade, level = "reg", products = "kall", attributes = "dm")

Arguments

gdx

GDX file to read from (for production data)
trade

Bilateral trade data (ov21_trade or other)
level

Level of regional aggregation ("reg", "glo", "regglo", or custom mapping)
products

Selection of products (e.g. "kall", "kcr", "kli")
attributes

dry matter: Mt ("dm"), gross energy: PJ ("ge"), reactive nitrogen: Mt ("nr"), phosphor: Mt ("p"), potash: Mt ("k"), wet matter: Mt ("wm")

Value

MAgPIE object with bilateral trade adjusted using Kastner method. Dimensions: (importer_exporter, year, product) Values represent apparent consumption of bilateral trade (production + imports - exports)

Author(s)

David M Chen

tradeValue

Description

Calculates the value of traded goods based on a gdx file

Usage

tradeValue(
  gdx,
  file = NULL,
  level = "reg",
  products = "k_trade",
  product_aggr = FALSE,
  type = "net-exports",
  glo_weight = "export",
  relative = FALSE
)

Arguments

gdx

GDX file
file

a file name the output should be written to using write.magpie
level

Level of regional aggregation ("reg", "glo", "regglo")
products

Selection of products (either by naming products, e.g. "tece", or naming a set,e.g."kcr")
product_aggr

aggregate over products or not (boolean)
type

exports-imports ("net-exports"), gross imports ("imports") or gross exports ("exports"); only valid if relative=FALSE
glo_weight

Decides the calculation of global prices. Weighting schemes are applied for estimation of global producer price. If "export" prices are calculated as average of regional exporters' prices, weighted by the export volumes. If "production" (default), prices are calculated as average of regional prices weighted by regional production. Alternatively, if "free_trade", the global prices are directly taken from the shadow prices of the global trade constraint, and no averaging is performed. Alternatively, if "constant_prices_initial" constant 1995 global prices for each commodity are used as weight.
relative

if relative=TRUE, self sufficiencies are reported (the amount of production divided by domestic demand)

Value

A MAgPIE object containing the value of trade flows in Million of US dollars

Author(s)

Misko Stevanovic, Florian Humpenoeder, Edna J. Molina Bacca

Examples

## Not run: 
x <- tradeValue(gdx)

## End(Not run)

tryList

Description

Internal support function to run a list of reportings in a tryReport environment.

Usage

tryList(..., gdx, level = "regglo")

Arguments

...

report function to be run
gdx

gdx file to report from
level

spatial level (either "regglo" for region+global or "iso" for ISO countries)

Value

A list of magpie objects (successful reports) or NULL (failed reports)

Author(s)

Jan Philipp Dietrich

See Also

tryReport, reportResult

Other Infrastructure: expectVariablesPresent(), metadata_comments(), out(), tryReport()

tryReport

Description

Internal support function to run a reporting in a try environment and properly report problems if something goes wrong without stopping the further processing in case of an error.

Usage

tryReport(report, gdx, level = "regglo", env = parent.frame())

Arguments

report

report function to be run
gdx

gdx file to report from
level

spatial level (either "regglo" for region+global, "iso" for country-level, or the file of a mapping file).
env

environment to evaluate the report in

Value

A named list with information on the outcome of the report (success, error, validationError, warning)

Author(s)

Jan Philipp Dietrich

See Also

reportResult

Other Infrastructure: expectVariablesPresent(), metadata_comments(), out(), tryList()

validation

Description

Create Validation pdf from MAgPIE output and corresponding validation.mif

Usage

validation(
  gdx,
  hist,
  file = "validation.pdf",
  runinfo = NULL,
  clusterinfo = NULL,
  debug = FALSE,
  reportfile = NULL,
  scenario = NULL,
  getReport = NULL,
  ...
)

Arguments

gdx

GDX file
hist

Validation data. All formats allowed which can be converted to quitte (including characters containing the path to a mif file)
file

a file name the output pdf
runinfo

(optional) Rdata object with run information
clusterinfo

(optional) RDS file or vector containing mapping information on 0.5degree between regions and cluster
debug

Switch to activate or deactivate debug mode
reportfile

file name to which a backup of the magpie reporting should be written (file ending should be ".mif"). No report written if set to NULL or if report is already provided via getReport!
scenario

scenario name used inside reportfile. Not used if reportfile is NULL.
getReport

the return value of the getReport function. Can be provided if available to reduce overall runtime.
...

additional arguments supplied to the validationpdf function

Author(s)

Jan Philipp Dietrich

Examples

## Not run: 
    validation("fulldata.gdx","validation.mif",filter="Yield")
  
## End(Not run)

ValueMaterialDemand

Description

calculates agricultural costs without taxes and incentives (i.e. GHG taxes and BII incentives)

Usage

ValueMaterialDemand(gdx, file = NULL, level = "regglo")

Arguments

gdx

GDX file
file

a file name the output should be written to using write.magpie
level

aggregation level, reg, glo or regglo

Author(s)

David M Chen

Examples

## Not run: 
x <- ValueMaterialDemand(gdx)

## End(Not run)

VegfruitShare

Description

Calculates the share of fruits, vegetables and nuts in total food supply from the food demand model

Usage

VegfruitShare(
  gdx,
  file = NULL,
  level = "reg",
  after_shock = TRUE,
  calibrated = TRUE,
  attributes = "kcal"
)

Arguments

gdx

GDX file
file

a file name the output should be written to using write.magpie
level

Level of regional aggregation; "iso" ISO country codes, "reg" (regional), "glo" (global)
after_shock

FALSE is using the exogenous real income and the prices before a shock, TRUE is using the endogeenous real income that takes into account food price change on real income
calibrated

if FALSE, the true regression outputs are used, if TRUE the values calibrated to the start years are used
attributes

unit: kilocalories per day ("kcal"), g protein per day ("protein"). Mt reactive nitrogen ("nr").

Value

magpie object with the livestock share in a region or country. Unit is dimensionsless, but value depends on chosen attribute

Author(s)

Benjamin Bodirsky

Examples

## Not run: 
    x <- VegfruitShare(gdx)
  
## End(Not run)

wageDevelopment

Description

calculates indicator to describe wage development based on agricultural wages in MAgPIE (hourly labor costs relative to a base year)

Usage

wageDevelopment(gdx, baseYear = 2000, file = NULL, level = "regglo")

Arguments

gdx

GDX file
baseYear

year relative to which the wage development should be calculated
file

a file name the output should be written to using write.magpie
level

Level of regional aggregation ("iso", "reg", "glo", "regglo")

Value

MAgPIE object containing indicator on wage development

Author(s)

Debbora Leip

Examples

## Not run: 
x <- wageDevelopment(gdx)

## End(Not run)

wageRent

Description

calculates wage rent for exogenous wage scenarios

Usage

wageRent(gdx, file = NULL, level = "regglo")

Arguments

gdx

GDX file
file

a file name the output should be written to using write.magpie
level

aggregation level, reg, glo or regglo

Author(s)

Debbora Leip

Examples

## Not run: 
x <- wageRent(gdx)

## End(Not run)

water_AAI

Description

reads area actually irrigated from a MAgPIE gdx file

Usage

water_AAI(gdx, file = NULL, level = "reg")

Arguments

gdx

GDX file
file

a file name the output should be written to using write.magpie. See write.magpie for supported file types
level

spatial level of aggregation: "cell" (cellular), "reg" (regional), "glo" (global), "regglo" (regional and global) or any other aggregation level defined in gdxAggregate

Value

A MAgPIE object containing the area actually irrigated (Mha)

Author(s)

Stephen Wirth, Anne Biewald, Felicitas Beier

Examples

## Not run: 
x <- water_AEI(gdx)

## End(Not run)

water_AEI

Description

reads area equipped for irrigation from a MAgPIE gdx file

Usage

water_AEI(gdx, file = NULL, level = "reg")

Arguments

gdx

GDX file
file

a file name the output should be written to using write.magpie
level

spatial level of aggregation: "cell" (cellular), "reg" (regional), "glo" (global), "regglo" (regional and global) or any other aggregation level defined in superAggregate

Value

A MAgPIE object containing the area equipped for irrigation (Mha)

Author(s)

Markus Bonsch

Examples

## Not run: 
    x <- water_AEI(gdx)
  
## End(Not run)

water_avail

Description

reads available water from a MAgPIE gdx file

Usage

water_avail(
  gdx,
  file = NULL,
  level = "reg",
  sources = NULL,
  sum = TRUE,
  digits = 4
)

Arguments

gdx

GDX file
file

a file name the output should be written to using write.magpie
level

spatial level of aggregation: "cell" (cellular), "reg" (regional), "glo" (global), "regglo" (regional and global) or any other aggregation level defined in superAggregate
sources

Vector of water sources that shall be obtained. NULL for all sources
sum

Sum the contribution of different sources (TRUE) or display them individually (FALSE)
digits

integer. For rounding of the return values

Value

A MAgPIE object containing the available water (km^3)

Author(s)

Markus Bonsch, Felicitas Beier

Examples

## Not run: 
x <- water_avail(gdx)

## End(Not run)

water_efficiency

Description

reads Irrigation efficiency from a MAgPIE gdx file

Usage

water_efficiency(gdx, file = NULL, level = "reg")

Arguments

gdx

GDX file
file

a file name the output should be written to using write.magpie
level

spatial level of aggregation: "cell" (cellular), "reg" (regional), "glo" (global), "regglo" (regional and global) or any other aggregation level defined in superAggregate

Value

A MAgPIE object containing the irrigation efficiency on the requested aggregation level

Author(s)

Markus Bonsch

Examples

## Not run: 
    x <- water_efficiency(gdx)
  
## End(Not run)

water_price

Description

reads water prices from a MAgPIE gdx file

Usage

water_price(
  gdx,
  file = NULL,
  level = "reg",
  weight = "value",
  index = FALSE,
  index_baseyear = 2005,
  digits = 4
)

Arguments

gdx

GDX file
file

a file name the output should be written to using write.magpie
level

spatial level of aggregation: "cell" (cellular), "reg" (regional), "glo" (global), "regglo" (regional and global) or any other aggregation level defined in superAggregate
weight

For determining weights to use for generating water prices at levels beyond 'cellular'. Takes "value" and "quantity". "value" sums regional weights by value of water per cluster, "quantity" sums regional weight by qty of water per cluster
index

FALSE (default) or TRUE
index_baseyear

baseyear to use for index calculation (only used if index=TRUE)
digits

integer. For rounding of the return values

Value

A MAgPIE object containing the water shadow prices (US Dollar/cubic metre).

Author(s)

Markus Bonsch, Vartika Singh, Miodrag Stevanovic

Examples

## Not run: 
    x <- water_price(gdx)
  
## End(Not run)

water_usage

Description

reads area usage from a MAgPIE gdx file

Usage

water_usage(
  gdx,
  file = NULL,
  level = "reg",
  users = NULL,
  sum = FALSE,
  seasonality = "total",
  abstractiontype = "withdrawal",
  digits = 4
)

Arguments

gdx

GDX file
file

a file name the output should be written to using write.magpie
level

spatial level of aggregation: "grid" (grid-cell) "cell" (cellular), "reg" (regional), "glo" (global), "regglo" (regional and global) or any other aggregation level defined in gdxAggregate
users

NULL or "sectors" or "kcr" or "kli". If NULL, all sectors including crop-wise water use and livestock will be obtained. If sectors, will only report for high-level sectors - agriculture, industry, electricity, domestic, ecosystem. Sum is applicable only in the case of sectors
sum

determines whether output should be sector specific (FALSE) or aggregated over all sectors (TRUE)
seasonality

water usage time of the year. options: "grper" (growing period) or "total" (entire year). Note: currently only implemented for non-agricultural water usage.
abstractiontype

water usage abstraction type: "withdrawal" or "consumption"
digits

integer. For rounding of the return values

Value

A MAgPIE object containing the water usage (km^3/yr)

Author(s)

Markus Bonsch, Vartika Singh, Felicitas Beier

Examples

## Not run: 
x <- water_usage(gdx)

## End(Not run)

waterEFR

Description

reads environmental flow requirements (as they enter MAgPIE) from a MAgPIE gdx file

Usage

waterEFR(gdx, file = NULL, level = "cell", digits = 4)

Arguments

gdx

GDX file
file

a file name the output should be written to using write.magpie
level

spatial level of aggregation: "cell" (cellular), "reg" (regional), "glo" (global), "regglo" (regional and global)
digits

integer. For rounding of the return values

Value

A MAgPIE object containing environmental flow requirements (km^3)

Author(s)

Felicitas Beier

Examples

## Not run: 
x <- waterEFR(gdx)

## End(Not run)

waterEFVarea

Description

calculates area that falls into cluster experiencing environmental flow violations from MAgPIE outputs

Usage

waterEFVarea(gdx, file = NULL, level = "reg", digits = 4)

Arguments

gdx

GDX file
file

a file name the output should be written to using write.magpie
level

spatial level of aggregation: "cell" (cellular), "reg" (regional), "glo" (global), "regglo" (regional and global), or "grid" (for disaggregated output using cropland as weight)
digits

integer. For rounding of the return values

Value

A MAgPIE object containing the area under environmental flow violations (Mha)

Author(s)

Felicitas Beier

Examples

## Not run: 
x <- waterEFVarea(gdx)

## End(Not run)

waterEFViolation

Description

calculates environmental flow violation volume from MAgPIE outputs

Usage

waterEFViolation(gdx, file = NULL, level = "reg", digits = 4)

Arguments

gdx

GDX file
file

a file name the output should be written to using write.magpie
level

spatial level of aggregation: "cell" (cellular), "reg" (regional), "glo" (global), "regglo" (regional and global), or "grid" (for disaggregated output using cropland as weight)
digits

integer. For rounding of the return values

Value

A MAgPIE object containing the volume of environmental flow violations (km^3)

Author(s)

Felicitas Beier

Examples

## Not run: 
x <- waterEFViolation(gdx)

## End(Not run)

waterEFVratio

Description

calculates ratio of environmental flow violation volume (EFV) to water environmental flow requirements (EFR) in MAgPIE.

Usage

waterEFVratio(gdx, file = NULL, level = "cell")

Arguments

gdx

GDX file
file

a file name the output should be written to using write.magpie
level

spatial level of aggregation: "cell" (cellular), "reg" (regional), "glo" (global), "regglo" (regional and global) or "grid" (grid cell)

Value

MAgPIE object

Author(s)

Felicitas Beier

Examples

## Not run: 
    x <- waterEFVratio(gdx)
  
## End(Not run)

waterStress

Description

calculates which areas are affected by water stress from water availability and water demand in MAgPIE. Water stress is calculated based on the proportion of water withdrawals to water availability. Thresholds based on World Resources Institute definition (https://www.wri.org/data/water-stress-country): Low stress: <10 Low-to-medium stress: 10-20 Medium to high stress: 20-40 High stress: 40-80 Extremely high stress: >80

Usage

waterStress(gdx, stressRatio = 0.4, file = NULL, level = "cell")

Arguments

gdx

GDX file
stressRatio

threshold defining level of water stress (e.g. 0.2 for medium water stress, 0.4 for high water stress)
file

a file name the output should be written to using write.magpie
level

spatial level of aggregation: "cell" (cellular), "reg" (regional), "glo" (global), "regglo" (regional and global)

Value

MAgPIE object indicating whether location is water stressed (1) or not (0)

Author(s)

Felicitas Beier

Examples

## Not run: 
x <- waterStress(gdx)

## End(Not run)

waterStressedPopulation

Description

People living in water stressed region

Usage

waterStressedPopulation(gdx, file = NULL, level = "cell", absolute = TRUE)

Arguments

gdx

GDX file
file

a file name the output should be written to using write.magpie
level

spatial level of aggregation: "cell" (cellular), "reg" (regional), "glo" (global), "regglo" (regional and global) or "grid" (grid cell)
absolute

TRUE: reports people living in water stressed region in million, FALSE: returns share of population

Value

MAgPIE object

Author(s)

Felicitas Beier

Examples

## Not run: 
    x <- waterStressRatio(gdx)
  
## End(Not run)

waterStressRatio

Description

calculates water stress ratio from water availability and water demand in MAgPIE. Water stress ratio is the ratio of water withdrawals (in the growing period) to water availability (in the growing period)

Usage

waterStressRatio(gdx, file = NULL, level = "cell")

Arguments

gdx

GDX file
file

a file name the output should be written to using write.magpie
level

spatial level of aggregation: "cell" (cellular), "reg" (regional), "glo" (global), "regglo" (regional and global) or "grid" (grid cell)

Value

MAgPIE object

Author(s)

Felicitas Beier

Examples

## Not run: 
    x <- waterStressRatio(gdx)
  
## End(Not run)

woodHarvestArea

Description

Reads wood harvest area separated by source (primforest, secdforest, forestry, other) and age classes from a gdx. The data is on cluster level and the unit is Mha per year.

Usage

woodHarvestArea(gdx)

Arguments

gdx

A fulldata.gdx of a magpie run, usually with endogenous forestry enabled

Value

A magpie object with the following dimensions: region, id, year, source, ageClass

Author(s)

Pascal Sauer

woodProduction

Description

Reads roundwood and fuelwood production/harvest data separated by source (primforest, secdforest, forestry, other) from a gdx. The data is on cluster level and the unit is Petagram (= mio. t) dry matter per year (Pg DM yr-1).

Usage

woodProduction(gdx)

Arguments

gdx

A fulldata.gdx of a magpie run, usually with endogenous forestry enabled

Value

A magpie object with the following dimensions: region, id, year, source, woodType

Author(s)

Pascal Sauer

yields

Description

Calculates crop yields based on a MAgPIE gdx file

Usage

yields(
  gdx,
  file = NULL,
  level = "reg",
  products = "kcr",
  product_aggr = FALSE,
  attributes = "dm",
  water_aggr = TRUE
)

Arguments

gdx

GDX file
file

a file name the output should be written to using write.magpie
level

Level of regional aggregation; "reg" (regional), "glo" (global), "regglo" (regional and global) or any other aggregation level defined in superAggregateX
products

Selection of products (either by naming products, e.g. "tece", or naming a set,e.g."kcr"), also including "pasture"
product_aggr

aggregate over products or not (boolean)
attributes

dry matter: Mt/ha ("dm"), gross energy: PJ/ha ("ge"), reactive nitrogen: Mt/ha ("nr"), phosphor: Mt/ha ("p"), potash: Mt/ha ("k"), wet matter: Mt/ha ("wm"). Can also be a vector.
water_aggr

aggregate irrigated and non-irriagted production or not (boolean).

Value

crop yield as MAgPIE object (unit depends on attributes)

Author(s)

Florian Humpenoeder

See Also

reportYields

Examples

## Not run: 
    x <- yields(gdx)
  
## End(Not run)

YieldsCropCalib

Description

Reads potential yields after calibration

Usage

YieldsCropCalib(gdx, file = NULL, level = "cell", tau = FALSE)

Arguments

gdx

GDX file
file

a file name the output should be written to using write.magpie
level

Level of regional aggregation
tau

if TRUE add effect of TAU to the yield

Value

A MAgPIE object containing values of potential yields after the calibration routines

Author(s)

Edna Molina Bacca

Examples

## Not run: 
x <- YieldsCropCalib(gdx)

## End(Not run)

YieldsCropRaw

Description

Reads potential yields after calibration

Usage

YieldsCropRaw(gdx, file = NULL, level = "cell")

Arguments

gdx

GDX file
file

a file name the output should be written to using write.magpie
level

Level of regional aggregation

Value

A MAgPIE object containing values of potential yields after the calibration routines

Author(s)

Edna Molina Bacca

Examples

## Not run: 
x <- YieldsCropRaw(gdx)

## End(Not run)