ensemble.PET.seasons: Raster calculations of beginnings and lengths of growing...

Description Usage Arguments Details Value Author(s) References See Also Examples

Description

The main function of ensemble.PET.seasons calculates the number of growing seasons and their starts and lengths from the dry period criterion of 2 * P < PET (http://www.fao.org/nr/climpag/cropfor/lgp_en.asp). Functions ensemble.PREC.season and ensemble.TMEAN.season calculate the total precipitation and average temperature for provided starts and lengths of a growing season. Together with data on optimal and absolute precipitation and temperature limits for a selected crop (as available from FAO's ECOCROP database), these layers enable the calculation of crop suitability using methods detailed in Chapman et al. (2020).

Usage

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ensemble.PET.seasons(PREC.stack=NULL, PET.stack=NULL, 
    index=c("seasons", "start1", "length1", "start2", "length2", "start3", "length3"),
    filename=NULL, overwrite=TRUE,
    CATCH.OFF=FALSE, ...)

ensemble.prec.season(PREC.stack=NULL, 
    start.layer=NULL, length.layer=NULL,
    filename=NULL, overwrite=TRUE,
    CATCH.OFF=FALSE, ...)

ensemble.tmean.season(TMEAN.stack=NULL, 
    start.layer=NULL, length.layer=NULL,
    filename=NULL, overwrite=TRUE,
    CATCH.OFF=FALSE, ...)

ensemble.season.suitability(season.raster=NULL, 
    thresholds=NULL,
    filename=NULL, overwrite=TRUE,
    CATCH.OFF=FALSE, ...)
    

Arguments

PREC.stack

stack object (stack) with monthly precipitation values.

PET.stack

stack object (stack) with monthly potential evapotranspiration values.

TMEAN.stack

stack object (stack) with monthly average temperature values.

index

selection of type of output - see details.

start.layer

raster layer with index of the month of the start of the growing season.

length.layer

raster layer with index of the length of the growing season.

season.raster

raster layer with seasonal precipitation or mean temperature.

thresholds

optimal and absolute thresholds of crop suitability, defined similarly as by ECOCROP.

filename

Name for writing the resulting raster layer (as in writeRaster).

overwrite

Replace a previous version of the same file.

CATCH.OFF

Disable calls to function tryCatch.

...

Additional arguments for writeRaster.

Details

Function ensemble.PET.seasons calculates the number, starts and lengths of growing seasons after first internally determining dry periods from the criterion of 2 * P < PET. The function was developed with data sets with monthly precipitatin and PET values, but probably can also work with data sets of other temporal resolution. Where there are multiple gaps between dry seasons, different growing periods are identified.

The definition of dry periods is less strict than the definition of P < PET used in ensemble.PET.season, following the methodologies for this function.

Argument index determines the contents of the output rasters: - seasons selects the number of growing periods to be returned; - start1 selects the index of the start of the first or only growing period to be returned; - length1 selects the index of the end of the first or only growing period to be returned; - start2 selects the index of the start of the second growing period to be returned; - length2 selects the index of the end of the second growing period to be returned; - start3 selects the index of the start of the third growing period to be returned; and - length3 selects the index of the end of the third growing period to be returned.

The methodology of calculating crop suitability is directly based on Chapman et al. (2020), following their equations 2 (temperature suitability, based on the mean temperature of the growing season) and 3 (precipitation suitability, based on the total precipitation of the growing season). The methods of Chapman et al. (2020) are based on Ramirez-Villegas et al. (2013), including the calculation of crop suitability as the product of temperature suitability and crop suitability (their respective equations 1 and 3).

Crop thresholds are available from the FAO ECOCROP database, which are also available via function getCrop.

Note that calculations can take a while for larger data sets.

Value

The function returns and writes raster layers.

Author(s)

Roeland Kindt (World Agroforestry Centre)

References

Ramirez-Villegas J, Jarvis A and Laderach P. 2013. Empirical approaches for assessing impacts of climate change on agriculture: The EcoCrop model and a case study with grain sorghum. Agricultural and Forest Meteorology doi: 10.1016/j.agrformet.2011.09.005

Chapman et al. 2020. Impact of climate change on crop suitability in sub-Saharan Africa in parameterized and convection-permitting regional climate models. Environmental Research Letters https://iopscience.iop.org/article/10.1088/1748-9326/ab9daf

See Also

ensemble.PET.season

Examples

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## Not run: 

## Not run: 

library(raster)
P.stack <- stack(monthly.prec.files)
PE.stack <- stack(monthly.PET.files)

# Calculate average monthly values similarly as in 
TMIN.stack <- stack(monthly.tmin.files)
TMAX.stack <- stack(monthly.tmax.files)
T.stack <- stack(0.5*(TMIN.stack + TMAX.stack))

# step 1: determine number of seasons, start and length of season 1

seasons.raster <- ensemble.PET.seasons(PREC.stack=P.stack, PET.stack=PE.stack, 
    index="seasons", filename="seasons.tif", CATCH.OFF=TRUE)

start1.raster <- ensemble.PET.seasons(PREC.stack=P.stack, PET.stack=PE.stack, 
    index="start1", filename="start1.tif", CATCH.OFF=TRUE)

length1.raster <- ensemble.PET.seasons(PREC.stack=P.stack, PET.stack=PE.stack, 
    index="length1", filename="length1.tif", CATCH.OFF=TRUE)

start2.raster <- ensemble.PET.seasons(PREC.stack=P.stack, PET.stack=PE.stack, 
    index="start2", filename="start2.tif", CATCH.OFF=TRUE)

length2.raster <- ensemble.PET.seasons(PREC.stack=P.stack, PET.stack=PE.stack, 
    index="length2", filename="length2.tif", CATCH.OFF=TRUE)

# step 2: calculate total precipitation in first rainy season,
# then use this value to calculate precipitation suitability

prec.season <- ensemble.prec.season(PREC.stack=P.stack, 
    start.layer=start1.raster, length.layer=length1.raster, 
    filename="precSeason.tif", CATCH.OFF=FALSE)  

dismo::getCrop("Sorghum (med. altitude)")

prec.suit <- ensemble.season.suitability(season.raster=prec.season, 
    thresholds=c(300, 500, 1000, 3000), 
    filename="precSuitability.tif", CATCH.OFF=FALSE)  

# step 3: calculate average temperature in first rainy steason,
# then use this value to calculate temperature suitability

tmean.season <- ensemble.tmean.season(TMEAN.stack=T.stack, 
    start.layer=start1.raster, length.layer=length1.raster, 
    filename="tmeanSeason.tif", CATCH.OFF=FALSE) 

temp.suit <- ensemble.season.suitability(season.raster=tmean.season, 
    thresholds=c(10, 24, 35, 40), 
    filename="tempSuitability.tif", CATCH.OFF=FALSE) 
    
# step 4: seasonal crop suitability is product of precipitation suitability
# and temperature suitability
    
sorghum.suit <- prec.suit * temp.suit
plot(sorghum.suit)


## End(Not run)

BiodiversityR documentation built on April 20, 2021, 5:07 p.m.