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# written by Fabian Stenzel, based on work by Sebastian Ostberg
# 2022-2023 - stenzel@pik-potsdam.de
################# EcoRisk calc functions ###################
#' Wrapper for calculating the ecosystem change metric EcoRisk
#'
#' Function to read in data for ecorisk, and call the calculation function once,
#' if overtime is FALSE, or for each timeslice of length window years, if
#' overtime is TRUE
#'
#' @param path_ref folder of reference run
#' @param path_scen folder of scenario run
#' @param read_saved_data whether to read in previously saved data
#' (default: FALSE)
#' @param save_data file to save read in data to (default NULL)
#' @param save_ecorisk file to save EcoRisk data to (default NULL)
#' @param nitrogen include nitrogen outputs for pools and fluxes into EcoRisk
#' calculation (default FALSE)
#' @param weighting apply "old" (Ostberg-like), "new", or "equal" weighting of
#' vegetation_structure_change weights (default "equal")
#' @param varnames data.frame with names of output files (outname) and time res.
#' (timestep) -- can be specified to account for variable file names
#' (default NULL -- standard names as below)
#' @param time_span_reference vector of years to use as scenario period
#' @param time_span_scenario vector of years to use as scenario period
#' @param dimensions_only_local flag whether to use only local change component
#' for water/carbon/nitrogen fluxes and pools, or use an average of
#' local change, global change and ecosystem balance (default FALSE)
#' @param overtime logical: calculate ecorisk as time-series? (default: FALSE)
#' @param window integer, number of years for window length (default: 30)
#' @param debug write out all nitrogen state variables (default FALSE)
#'
#' @return list data object containing arrays of ecorisk_total,
#' vegetation_structure_change, local_change, global_importance,
#' ecosystem_balance, carbon_stocks, carbon_fluxes, water_fluxes
#' (+ nitrogen_stocks and nitrogen_fluxes)
#'
#' @export
ecorisk_wrapper <- function(path_ref,
path_scen,
read_saved_data = FALSE,
save_data = NULL,
save_ecorisk = NULL,
nitrogen = TRUE,
weighting = "equal",
varnames = NULL,
time_span_reference,
time_span_scenario,
dimensions_only_local = FALSE,
overtime = FALSE,
window = 30,
debug = FALSE) {
if (is.null(varnames)) {
print("variable name list not provided, using standard list, which might
not be applicable for this case ...")
varnames <- data.frame(
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row.names = c("grid","fpc", "fpc_bft", "cftfrac", "firec", "npp", "runoff",
"transp", "vegc", "firef", "rh", "harvestc", "rharvestc",
"pft_harvestc", "pft_rharvestc", "evap", "interc", "discharge",
"soilc", "litc", "swc", "vegn", "soilnh4", "soilno3",
"leaching", "n2o_denit", "n2o_nit", "n2_emis", "bnf",
"n_volatilization", "gpp", "res_storage", "lakevol", "ndepos",
"rd", "prec", "terr_area", "irrig", "nfert_agr", "nmanure_agr",
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"firen", "harvestn", "rivervol", "irrig_stor"),
outname = c("grid.bin.json", "fpc.bin.json", "fpc_bft.bin.json",
"cftfrac.bin.json", "firec.bin.json", "mnpp.bin.json",
"mrunoff.bin.json", "mtransp.bin.json", "vegc.bin.json",
"firef.bin.json", "mrh.bin.json", "harvestc.bin.json",
"rharvestc.bin.json", "pft_harvest.pft.bin.json",
"pft_rharvest.pft.bin.json", "mevap.bin.json",
"minterc.bin.json", "mdischarge.bin.json", "soilc.bin.json",
"litc.bin.json", "mswc.bin.json", "vegn.bin.json",
"soilnh4.bin.json", "soilno3.bin.json", "mleaching.bin.json",
"mn2o_denit.bin.json", "mn2o_nit.bin.json", "mn2_emis.bin.json",
"mbnf.bin.json", "mn_volatilization.bin.json", "mgpp.bin.json",
"res_storage.bin.json", "lakevol.bin.json", "ndepos.bin.json",
"rd.bin.json", "mprec.bin.json", "terr_area.bin.json",
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"mirrig.bin.json", "nfert_agr.bin.json", "nmanure_agr.bin.json",
"firen.bin.json", "harvestn.bin.json", "rivervol.bin.json",
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"irrig_stor.bin.json"),
)
}
nyears <- length(time_span_reference)
nyears_scen <- length(time_span_scenario)
if (nyears < 30 || nyears_scen < 30) {
stop("Warning: timespan in reference or scenario is smaller than 30 years. \
Aborting!")
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}
# translate varnames and folders to files_scenarios/reference lists
files_scenario <- list(
grid = paste0(path_scen, varnames["grid", "outname"]),
fpc = paste0(path_scen, varnames["fpc", "outname"]),
fpc_bft = paste0(path_scen, varnames["fpc_bft", "outname"]),
cftfrac = paste0(path_scen, varnames["cftfrac", "outname"]),
firec = paste0(path_scen, varnames["firec", "outname"]),
npp = paste0(path_scen, varnames["npp", "outname"]),
runoff = paste0(path_scen, varnames["runoff", "outname"]),
transp = paste0(path_scen, varnames["transp", "outname"]),
vegc = paste0(path_scen, varnames["vegc", "outname"]),
firef = paste0(path_scen, varnames["firef", "outname"]),
rh = paste0(path_scen, varnames["rh", "outname"]),
harvestc = paste0(path_scen, varnames["harvestc", "outname"]),
rharvestc = paste0(path_scen, varnames["rharvestc", "outname"]),
pft_harvestc = paste0(path_scen, varnames["pft_harvest", "outname"]),
pft_rharvestc = paste0(path_scen, varnames["pft_rharvest", "outname"]),
evap = paste0(path_scen, varnames["evap", "outname"]),
interc = paste0(path_scen, varnames["interc", "outname"]),
discharge = paste0(path_scen, varnames["discharge", "outname"]),
soilc = paste0(path_scen, varnames["soilc", "outname"]),
litc = paste0(path_scen, varnames["litc", "outname"]),
swc = paste0(path_scen, varnames["swc", "outname"]),
vegn = paste0(path_scen, varnames["vegn", "outname"]),
soilnh4 = paste0(path_scen, varnames["soilnh4", "outname"]),
soilno3 = paste0(path_scen, varnames["soilno3", "outname"]),
leaching = paste0(path_scen, varnames["leaching", "outname"]),
n2o_denit = paste0(path_scen, varnames["n2o_denit", "outname"]),
n2o_nit = paste0(path_scen, varnames["n2o_nit", "outname"]),
n2_emis = paste0(path_scen, varnames["n2_emis", "outname"]),
bnf = paste0(path_scen, varnames["bnf", "outname"]),
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n_volatilization = paste0(path_scen, varnames["n_volatilization", "outname"]),
gpp = paste0(path_scen, varnames["gpp", "outname"]),
res_storage = paste0(path_scen, varnames["res_storage", "outname"]),
lakevol = paste0(path_scen, varnames["lakevol", "outname"]),
ndepos = paste0(path_scen, varnames["ndepos", "outname"]),
rd = paste0(path_scen, varnames["rd", "outname"]),
prec = paste0(path_scen, varnames["prec", "outname"]),
terr_area = paste0(path_scen, varnames["terr_area", "outname"]),
irrig = paste0(path_scen, varnames["irrig", "outname"]),
nfert_agr = paste0(path_scen, varnames["nfert_agr", "outname"]),
nmanure_agr = paste0(path_scen, varnames["nmanure_agr", "outname"]),
ndepos = paste0(path_scen, varnames["ndepos", "outname"]),
firen = paste0(path_scen, varnames["firen", "outname"]),
harvestn = paste0(path_scen, varnames["harvestn", "outname"]),
irrig_stor = paste0(path_scen, varnames["irrig_stor", "outname"]),
rivervol = paste0(path_scen, varnames["rivervol", "outname"])
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)
files_reference <- list(
grid = paste0(path_ref, varnames["grid", "outname"]),
fpc = paste0(path_ref, varnames["fpc", "outname"]),
fpc_bft = paste0(path_ref, varnames["fpc_bft", "outname"]),
cftfrac = paste0(path_ref, varnames["cftfrac", "outname"]),
firec = paste0(path_ref, varnames["firec", "outname"]),
npp = paste0(path_ref, varnames["npp", "outname"]),
runoff = paste0(path_ref, varnames["runoff", "outname"]),
transp = paste0(path_ref, varnames["transp", "outname"]),
vegc = paste0(path_ref, varnames["vegc", "outname"]),
firef = paste0(path_ref, varnames["firef", "outname"]),
rh = paste0(path_ref, varnames["rh", "outname"]),
harvestc = paste0(path_ref, varnames["harvestc", "outname"]),
rharvestc = paste0(path_ref, varnames["rharvestc", "outname"]),
pft_harvestc = paste0(path_ref, varnames["pft_harvest", "outname"]),
pft_rharvestc = paste0(path_ref, varnames["pft_rharvest", "outname"]),
evap = paste0(path_ref, varnames["evap", "outname"]),
interc = paste0(path_ref, varnames["interc", "outname"]),
discharge = paste0(path_ref, varnames["discharge", "outname"]),
soilc = paste0(path_ref, varnames["soilc", "outname"]),
litc = paste0(path_ref, varnames["litc", "outname"]),
swc = paste0(path_ref, varnames["swc", "outname"]),
vegn = paste0(path_ref, varnames["vegn", "outname"]),
soilnh4 = paste0(path_ref, varnames["soilnh4", "outname"]),
soilno3 = paste0(path_ref, varnames["soilno3", "outname"]),
leaching = paste0(path_ref, varnames["leaching", "outname"]),
n2o_denit = paste0(path_ref, varnames["n2o_denit", "outname"]),
n2o_nit = paste0(path_ref, varnames["n2o_nit", "outname"]),
n2_emis = paste0(path_ref, varnames["n2_emis", "outname"]),
bnf = paste0(path_ref, varnames["bnf", "outname"]),
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n_volatilization = paste0(path_ref, varnames["n_volatilization", "outname"]),
gpp = paste0(path_ref, varnames["gpp", "outname"]),
res_storage = paste0(path_ref, varnames["res_storage", "outname"]),
lakevol = paste0(path_ref, varnames["lakevol", "outname"]),
ndepos = paste0(path_ref, varnames["ndepos", "outname"]),
rd = paste0(path_ref, varnames["rd", "outname"]),
prec = paste0(path_ref, varnames["prec", "outname"]),
terr_area = paste0(path_ref, varnames["terr_area", "outname"]),
irrig = paste0(path_ref, varnames["irrig", "outname"]),
nfert_agr = paste0(path_ref, varnames["nfert_agr", "outname"]),
nmanure_agr = paste0(path_ref, varnames["nmanure_agr", "outname"]),
ndepos = paste0(path_ref, varnames["ndepos", "outname"]),
firen = paste0(path_ref, varnames["firen", "outname"]),
harvestn = paste0(path_ref, varnames["harvestn", "outname"]),
irrig_stor = paste0(path_ref, varnames["irrig_stor", "outname"]),
rivervol = paste0(path_ref, varnames["rivervol", "outname"])
if (overtime && (window != nyears)) stop("Overtime is enabled, but window \
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length (", window, ") does not match the reference nyears.")
if (read_saved_data) {
if (!is.null(save_data)) {
print(paste("Loading saved data from:", save_data))
load(file = save_data)
} else {
stop("save_data is not specified as parameter, ",
"nothing to load ... exiting")
}
} else {
# first read in all lpjml output files required for computing EcoRisk
returned_vars <- read_ecorisk_data(
files_reference = files_reference,
files_scenario = files_scenario,
save_file = save_data,
export = FALSE,
nitrogen = nitrogen,
time_span_reference = time_span_reference,
time_span_scenario = time_span_scenario,
debug = debug
)
# extract variables from return list object and give them proper names
state_ref <- returned_vars$state_ref
state_scen <- returned_vars$state_scen
fpc_ref <- returned_vars$fpc_ref
fpc_scen <- returned_vars$fpc_scen
bft_ref <- returned_vars$bft_ref
bft_scen <- returned_vars$bft_scen
cft_ref <- returned_vars$cft_ref
cft_scen <- returned_vars$cft_scen
lat <- returned_vars$lat
lon <- returned_vars$lon
cell_area <- returned_vars$cell_area
rm(returned_vars)
}
ncells <- length(cell_area)
slices <- (nyears_scen - window + 1)
ecorisk <- list(
ecorisk_total = array(0, dim = c(ncells, slices)),
vegetation_structure_change = array(0, dim = c(ncells, slices)),
local_change = array(0, dim = c(ncells, slices)),
global_importance = array(0, dim = c(ncells, slices)),
ecosystem_balance = array(0, dim = c(ncells, slices)),
carbon_stocks = array(0, dim = c(ncells, slices)),
carbon_fluxes = array(0, dim = c(ncells, slices)),
water_stocks = array(0, dim = c(ncells, slices)),
water_fluxes = array(0, dim = c(ncells, slices)),
nitrogen_stocks = array(0, dim = c(ncells, slices)),
nitrogen_fluxes = array(0, dim = c(ncells, slices))
)
for (y in 1:slices) {
print(paste0("Calculating time slice ", y, " of ", slices))
returned <- calc_ecorisk(
fpc_ref = fpc_ref,
fpc_scen = fpc_scen[, , y:(y + window - 1)],
bft_ref = bft_ref,
bft_scen = bft_scen[, , y:(y + window - 1)],
cft_ref = cft_ref,
cft_scen = cft_scen[, , y:(y + window - 1)],
state_ref = state_ref,
state_scen = state_scen[, y:(y + window - 1), ],
weighting = weighting,
lat = lat,
lon = lon,
cell_area = cell_area,
dimensions_only_local = dimensions_only_local,
nitrogen = nitrogen
)
ecorisk$ecorisk_total[, y] <- returned$ecorisk_total
ecorisk$vegetation_structure_change[, y] <- (
returned$vegetation_structure_change
)
ecorisk$local_change[, y] <- returned$local_change
ecorisk$global_importance[, y] <- returned$global_importance
ecorisk$ecosystem_balance[, y] <- returned$ecosystem_balance
ecorisk$carbon_stocks[, y] <- returned$carbon_stocks
ecorisk$carbon_fluxes[, y] <- returned$carbon_fluxes
ecorisk$water_stocks[, y] <- returned$water_stocks
ecorisk$water_fluxes[, y] <- returned$water_fluxes
if (nitrogen) {
ecorisk$nitrogen_stocks[, y] <- returned$nitrogen_stocks
ecorisk$nitrogen_fluxes[, y] <- returned$nitrogen_fluxes
}
}
############## export and save data if requested #############
if (!(is.null(save_ecorisk))) {
print(paste0("Saving EcoRisk data to: ", save_ecorisk))
save(ecorisk, file = save_ecorisk)
}
#
###
return(ecorisk)
}
#' Calculate the ecosystem change metric EcoRisk between 2 sets of states
#'
#' Function to calculate the ecosystem change metric EcoRisk, based on
#' gamma/vegetation_structure_change
#' work from Sykes (1999), Heyder (2011), and Ostberg (2015,2018).
#' This is a reformulated version in R, not producing 100% similar values
#' than the C/bash version from Ostberg et al. 2018, but similar the methodology
#'
#' @param fpc_ref reference run data for fpc
#' @param fpc_scen scenario run data for fpc
#' @param bft_ref reference run data for fpc_bft
#' @param bft_scen scenario run data for fpc_bft
#' @param cft_ref reference run data for cftfrac
#' @param cft_scen scenario run data for cftfrac
#' @param state_ref reference run data for state variables
#' @param state_scen scenario run data for state variables
#' @param weighting apply "old" (Ostberg-like), "new", or "equal" weighting of
#' vegetation_structure_change weights (default "equal")
#' @param lat latitude array
#' @param lon longitude array
#' @param cell_area cellarea array
#' @param dimensions_only_local flag whether to use only local change component
#' for water/carbon/nitrogen fluxes and pools, or use an average of
#' local change, global change and ecosystem balance (default FALSE)
#' @param nitrogen include nitrogen outputs (default: TRUE)
#'
#' @return list data object containing arrays of ecorisk_total,
#' vegetation_structure_change, local_change, global_importance,
#' ecosystem_balance, carbon_stocks, carbon_fluxes, water_fluxes
#' (+ nitrogen_stocks and nitrogen_fluxes)
#'
#' @export
calc_ecorisk <- function(fpc_ref,
fpc_scen,
bft_ref,
bft_scen,
cft_ref,
cft_scen,
state_ref,
state_scen,
weighting = "equal",
lat,
lon,
cell_area,
dimensions_only_local = FALSE,
nitrogen = TRUE) {
di_ref <- dim(fpc_ref)
di_scen <- dim(fpc_scen)
ncells <- di_ref[1]
nyears <- di_ref[3]
if (di_ref[3] != di_scen[3]) {
stop("Dimension year does not match between fpc_scen and fpc_ref.")
}
# calc vegetation_structure_change and variability of
# vegetation_structure_change within
# reference period S(vegetation_structure_change,
# sigma_vegetation_structure_change)
fpc_ref_mean <- apply(fpc_ref, c(1, 2), mean)
bft_ref_mean <- apply(bft_ref, c(1, 2), mean)
cft_ref_mean <- apply(cft_ref, c(1, 2), mean)
sigma_vegetation_structure_change_ref_list <- array(
0, dim = c(ncells, nyears)
)
# calculate for every year of the reference period,
# vegetation_structure_change between that year and the average reference
# period year
# this gives the variability of vegetation_structure_change within the
# reference period
for (y in 1:nyears) {
sigma_vegetation_structure_change_ref_list[, y] <- calc_delta_v( # nolint
fpc_ref = fpc_ref_mean,
fpc_scen = fpc_ref[, , y],
bft_ref = bft_ref_mean,
bft_scen = bft_ref[, , y],
cft_ref = cft_ref_mean,
cft_scen = cft_ref[, , y],
weighting = weighting
)
}
# calculate the std deviation over the reference period for each gridcell
vegetation_structure_changesd <- apply(
sigma_vegetation_structure_change_ref_list,
c(1),
stats::sd
)
# calculate vegetation_structure_change between average reference and average
# scenario period
vegetation_structure_change <- calc_delta_v(
fpc_ref = fpc_ref_mean,
fpc_scen = apply(fpc_scen, c(1, 2), mean),
bft_ref = bft_ref_mean,
bft_scen = apply(bft_scen, c(1, 2), mean),
cft_ref = cft_ref_mean,
cft_scen = apply(cft_scen, c(1, 2), mean),
weighting = weighting
)
#
####
############## calc EcoRisk components ################
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# dimensions in the state vector
# 1 "vegetation_carbon_pool"
# 2 "soil_carbon_pool"
# 3 "carbon_influx"
# 4 "carbon_outflux"
# 5 "soil_water_pool"
# 6 "surface_water_pool"
# 7 "water_influx"
# 8 "water_outflux"
# 9 "other"
# 10 "vegetation_nitrogen_pool"
# 11 "soil_mineral_nitrogen_pool"
# 12 "nitrogen_influx"
# 13 "nitrogen_outflux"
delta <- vegetation_structure_change * s_change_to_var_ratio(
vegetation_structure_change,
vegetation_structure_changesd
) # vegetation_structure_change
nitrogen_dimensions <- c("vegetation_nitrogen_pool","soil_mineral_nitrogen_pool","nitrogen_influx","nitrogen_outflux")
all_dimensions <- dimnames(state_scen)$class
non_nitrogen_dimensions <- setdiff(all_dimensions,nitrogen_dimensions)
if (nitrogen) {
lc <- calc_component(
ref = state_ref,
scen = state_scen,
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gi <- calc_component(
ref = state_ref,
scen = state_scen,
local = FALSE,
cell_area = cell_area
) # global importance
eb <- calc_ecosystem_balance(
ref = state_ref,
scen = state_scen
) # ecosystem balance
}else {
lc <- calc_component(
ref = state_ref[,,non_nitrogen_dimensions],
scen = state_scen[,,non_nitrogen_dimensions],
gi <- calc_component(
ref = state_ref[,,non_nitrogen_dimensions],
scen = state_scen[,,non_nitrogen_dimensions],
local = FALSE,
eb <- calc_ecosystem_balance(
ref = state_ref[,,non_nitrogen_dimensions],
scen = state_scen[,,non_nitrogen_dimensions]
) # ecosystem balance
}
if (dimensions_only_local == TRUE) {
# carbon stocks (local change)
cs <- calc_component(
ref = state_ref[, , c("vegetation_carbon_pool", "soil_carbon_pool")],
scen = state_scen[, , c("vegetation_carbon_pool", "soil_carbon_pool")],
# carbon fluxes (local change)
cf <- calc_component(
ref = state_ref[, , c("carbon_influx", "carbon_outflux")],
scen = state_scen[, , c("carbon_influx", "carbon_outflux")],
cell_area = cell_area)
# water fluxes (local change)
wf <- calc_component(
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ref = state_ref[, , c("water_influx","water_outflux")],
scen = state_scen[, , c("water_influx","water_outflux")],
# water pools (local change)
ws <- calc_component(
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ref = state_ref[, , c("soil_water_pool","surface_water_pool")],
scen = state_scen[, , c("soil_water_pool","surface_water_pool")],
local = TRUE,
cell_area = cell_area
)
# nitrogen stocks (local change)
if (nitrogen) {
ns <- calc_component(
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ref = state_ref[, , c("vegetation_nitrogen_pool","soil_mineral_nitrogen_pool")],
scen = state_scen[, , c("vegetation_nitrogen_pool","soil_mineral_nitrogen_pool")],
)
# nitrogen fluxes (local change)
nf <- calc_component(
ref = state_ref[, , c("nitrogen_influx","nitrogen_outflux")],
scen = state_scen[, , c("nitrogen_influx","nitrogen_outflux")],
local = TRUE,
cell_area = cell_area
)
}
} else {
cf <- (
calc_component(
ref = state_ref[, , c("carbon_influx","carbon_outflux")],
scen = state_scen[, , c("carbon_influx","carbon_outflux")],
local = TRUE,
cell_area = cell_area
) + # carbon fluxes
calc_component(
ref = state_ref[, , c("carbon_influx","carbon_outflux")],
scen = state_scen[, , c("carbon_influx","carbon_outflux")],
local = FALSE,
cell_area = cell_area
) +
ref = state_ref[, , c("carbon_influx","carbon_outflux")],
scen = state_scen[, , c("carbon_influx","carbon_outflux")]
ref = state_ref[, , c("vegetation_carbon_pool","soil_carbon_pool")],
scen = state_scen[, , c("vegetation_carbon_pool","soil_carbon_pool")],
local = TRUE,
cell_area = cell_area
) +
calc_component(
ref = state_ref[, , c("vegetation_carbon_pool","soil_carbon_pool")],
scen = state_scen[, , c("vegetation_carbon_pool","soil_carbon_pool")],
local = FALSE,
cell_area = cell_area
) +
calc_ecosystem_balance(
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ref = state_ref[, , c("vegetation_carbon_pool","soil_carbon_pool")],
scen = state_scen[, , c("vegetation_carbon_pool","soil_carbon_pool")]
)
) / 3
# water fluxes
wf <- (
calc_component(
ref = state_ref[, , c("water_influx","water_outflux")],
scen = state_scen[, , c("water_influx","water_outflux")],
local = TRUE,
cell_area = cell_area
) +
calc_component(
ref = state_ref[, , c("water_influx","water_outflux")],
scen = state_scen[, , c("water_influx","water_outflux")],
local = FALSE,
cell_area = cell_area
) + calc_ecosystem_balance(
ref = state_ref[, , c("water_influx","water_outflux")],
scen = state_scen[, , c("water_influx","water_outflux")]
)
) / 3
# water pools
ws <- (
calc_component(
ref = state_ref[, , c("soil_water_pool","surface_water_pool")],
scen = state_scen[, , c("soil_water_pool","surface_water_pool")],
local = TRUE,
cell_area = cell_area
) +
calc_component(
ref = state_ref[, , c("soil_water_pool","surface_water_pool")],
scen = state_scen[, , c("soil_water_pool","surface_water_pool")],
local = FALSE,
cell_area = cell_area
) +
calc_ecosystem_balance(
ref = state_ref[, , c("soil_water_pool","surface_water_pool")],
scen = state_scen[, , c("soil_water_pool","surface_water_pool")]
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if (nitrogen) {
# nitrogen stocks (local change)
ns <- (
calc_component(
ref = state_ref[, , c("vegetation_nitrogen_pool","soil_mineral_nitrogen_pool")],
scen = state_scen[, , c("vegetation_nitrogen_pool","soil_mineral_nitrogen_pool")],
local = TRUE,
cell_area = cell_area
) +
calc_component(
ref = state_ref[, , c("vegetation_nitrogen_pool","soil_mineral_nitrogen_pool")],
scen = state_scen[, , c("vegetation_nitrogen_pool","soil_mineral_nitrogen_pool")],
local = FALSE, cell_area = cell_area
) +
calc_ecosystem_balance(
ref = state_ref[, , c("vegetation_nitrogen_pool","soil_mineral_nitrogen_pool")],
scen = state_scen[, , c("vegetation_nitrogen_pool","soil_mineral_nitrogen_pool")]
)
) / 3
# nitrogen fluxes (local change)
nf <- (
calc_component(
ref = state_ref[, , c("nitrogen_influx","nitrogen_outflux")],
scen = state_scen[, , c("nitrogen_influx","nitrogen_outflux")],
local = TRUE,
cell_area = cell_area
) +
calc_component(
ref = state_ref[, , c("nitrogen_influx","nitrogen_outflux")],
scen = state_scen[, , c("nitrogen_influx","nitrogen_outflux")],
local = FALSE,
cell_area = cell_area
) +
calc_ecosystem_balance(
ref = state_ref[, , c("nitrogen_influx","nitrogen_outflux")],
scen = state_scen[, , c("nitrogen_influx","nitrogen_outflux")]
)
) / 3
}
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}
# calc total EcoRisk as the average of the 4 components
ecorisk_full <- (delta + lc + gi + eb) / 4 # check for NAs
if (nitrogen) {
ecorisk <- list(
ecorisk_total = ecorisk_full,
vegetation_structure_change = delta,
local_change = lc,
global_importance = gi,
ecosystem_balance = eb,
carbon_stocks = cs,
carbon_fluxes = cf,
water_fluxes = wf,
water_stocks = ws,
nitrogen_stocks = ns,
nitrogen_fluxes = nf
)
} else {
ecorisk <- list(
ecorisk_total = ecorisk_full,
vegetation_structure_change = delta,
local_change = lc,
global_importance = gi,
ecosystem_balance = eb,
carbon_stocks = cs,
carbon_fluxes = cf,
water_fluxes = wf,
water_stocks = ws,
nitrogen_stocks = NA,
nitrogen_fluxes = NA
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)
}
###
return(ecorisk)
}
#' Read in output data from LPJmL to calculate the ecosystem change metric
#' EcoRisk
#'
#' Utility function to read in output data from LPJmL for calculation of EcoRisk
#'
#' @param files_reference folder of reference run
#' @param files_scenario folder of scenario run
#' @param save_file file to save read in data to (default NULL)
#' @param export flag whether to export réad in data to global environment
#' (default FALSE)
#' @param time_span_reference vector of years to use as scenario period
#' @param time_span_scenario vector of years to use as scenario period
#' @param nitrogen include nitrogen outputs for pools and fluxes into EcoRisk
#' calculation (default FALSE)
#' @param debug write out all nitrogen state variables (default FALSE)
#'
#' @return list data object containing arrays of state_ref, mean_state_ref,
#' state_scen, mean_state_scen, fpc_ref, fpc_scen, bft_ref, bft_scen,
#' cft_ref, cft_scen, lat, lon, cell_area
#'
#' @export
read_ecorisk_data <- function(files_reference, # nolint
files_scenario,
save_file = NULL,
export = FALSE,
time_span_reference,
time_span_scenario,
nitrogen,
debug = FALSE) {
file_type <- tools::file_ext(files_reference$grid)
if (file_type %in% c("json", "clm")) {
# read grid
grid <- lpjmlkit::read_io(
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files_reference$grid
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cell_area <- drop(lpjmlkit::read_io(
filename = files_reference$terr_area
)$data) # in m2
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ncells <- length(lat)
nyears <- length(time_span_scenario)
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### read in lpjml output
# for vegetation_structure_change (fpc,fpc_bft,cftfrac)
print("Reading in fpc, fpc_bft, cftfrac")
cft_scen <- aperm(lpjmlkit::read_io(
files_scenario$cftfrac,
subset = list(year = as.character(time_span_scenario))
) %>%
lpjmlkit::transform(to = c("year_month_day")) %>%
lpjmlkit::as_array(aggregate = list(month = sum)), c(1, 3, 2))
bft_scen <- aperm(lpjmlkit::read_io(
files_scenario$fpc_bft,
subset = list(year = as.character(time_span_scenario))
) %>%
lpjmlkit::transform(to = c("year_month_day")) %>%
lpjmlkit::as_array(aggregate = list(month = sum)), c(1, 3, 2))
fpc_scen <- aperm(lpjmlkit::read_io(
files_scenario$fpc,
subset = list(year = as.character(time_span_scenario))
) %>%
lpjmlkit::transform(to = c("year_month_day")) %>%
lpjmlkit::as_array(aggregate = list(month = sum)), c(1, 3, 2))
if (file.exists(files_reference$cftfrac)) {
cft_ref <- aperm(lpjmlkit::read_io(
files_reference$cftfrac,
subset = list(year = as.character(time_span_reference))
) %>%
lpjmlkit::transform(to = c("year_month_day")) %>%
lpjmlkit::as_array(aggregate = list(month = sum)), c(1, 3, 2))
} else {
cft_ref <- cft_scen * 0
}
if (file.exists(files_reference$fpc_bft)) {
bft_ref <- aperm(lpjmlkit::read_io(
files_reference$fpc_bft,
subset = list(year = as.character(time_span_reference))
) %>%
lpjmlkit::transform(to = c("year_month_day")) %>%
lpjmlkit::as_array(aggregate = list(month = sum)), c(1, 3, 2))
} else {
bft_ref <- bft_scen * 0
}
fpc_ref <- aperm(lpjmlkit::read_io(
files_reference$fpc,
subset = list(year = as.character(time_span_reference))
) %>%
lpjmlkit::transform(to = c("year_month_day")) %>%
lpjmlkit::as_array(aggregate = list(month = sum)), c(1, 3, 2))
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#### new input reading ###
metric_files <- system.file(
"extdata",
"metric_files.yml",
package = "biospheremetrics"
) %>%
yaml::read_yaml()
nclasses <- length(metric_files$metric$ecorisk_nitrogen$metric_class)
nstate_dimensions <- 0
for (i in 1:nclasses) nstate_dimensions <- nstate_dimensions +
length(metric_files$metric$ecorisk_nitrogen$metric_class[[i]])
state_ref <- array(0,dim=c(ncells,nyears,nstate_dimensions))
state_scen <- array(0,dim=c(ncells,nyears,nstate_dimensions))
class_names <- 1:nstate_dimensions
index <- 1
# iterate over main classes (carbon pools, water fluxes ...)
for (c in 1:nclasses) {
classe <- metric_files$metric$ecorisk_nitrogen$metric_class[[c]]
nsubclasses <- length(classe)
# iterate over subclasses (vegetation carbon, soil water ...)
for (s in 1:nsubclasses) {
subclass <- classe[s]
class_names[index] <- names(subclass)
vars <- split_sign(unlist(subclass))
for (v in 1:length(vars[,1])) {
path_scen_file <- files_scenario[[vars[v, "variable"]]]
if (file.exists(path_scen_file)) {
header_scen <- lpjmlkit::read_meta(filename = path_scen_file)
print(paste("Reading in", path_scen_file,"with unit",header_scen$unit,
"-> as part of",class_names[index]))
var_scen <- lpjmlkit::read_io(
path_scen_file,
subset = list(year = as.character(time_span_scenario))
) %>%
lpjmlkit::transform(to = c("year_month_day")) %>%
lpjmlkit::as_array(aggregate = list(month = sum, band = sum)) %>%
drop()
} else {
stop(paste("Couldn't read in:",path_scen_file," - stopping!"))
}
path_ref_file <- files_reference[[vars[v, "variable"]]]
if (file.exists(path_ref_file)) {
header_ref <- lpjmlkit::read_meta(path_ref_file)
print(paste("Reading in", path_ref_file,"with unit",header_ref$unit,
"-> as part of",class_names[index]))
var_ref <- lpjmlkit::read_io(
path_ref_file,
subset = list(year = as.character(time_span_reference))
) %>%
lpjmlkit::transform(to = c("year_month_day")) %>%
lpjmlkit::as_array(aggregate = list(month = sum, band = sum)) %>%
drop()
} else {
stop(paste("Couldn't read in:",path_ref_file," - stopping!"))
}
#if (window > 30){
# if (vars[v,"sign"] == "+"){
# state_scen[,,index,] <- state_scen[,,index,] + var_scen
# state_ref[,,index,] <- state_ref[,,index,] + var_ref
# } else { # vars[v,"sign"] == "-"
# state_scen[,,index,] <- state_scen[,,index,] - var_scen
# state_ref[,,index,] <- state_ref[,,index,] - var_ref
# }
#}else{
if (vars[v,"sign"] == "+"){
state_scen[,,index] <- state_scen[,,index] + var_scen
state_ref[,,index] <- state_ref[,,index] + var_ref
} else { # vars[v,"sign"] == "-"
state_scen[,,index] <- state_scen[,,index] - var_scen
state_ref[,,index] <- state_ref[,,index] - var_ref
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}
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}
index <- index + 1
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}
dimnames(state_scen) <- list(cell = 0:(ncells-1), year = as.character(time_span_scenario), class = class_names)
dimnames(state_ref) <- list(cell = 0:(ncells-1), year = as.character(time_span_reference), class = class_names)
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} else if (file_type == "nc") { # to be added
stop(
"nc reading has not been updated to latest functionality. ",
"Please contact Fabian Stenzel"
)
} else {
stop("Unrecognized file type (", file_type, ")")
}
if (!(is.null(save_file))) {
print(paste0("Saving data to: ", save_file))
save(state_ref, state_scen, fpc_ref, fpc_scen,
bft_ref, bft_scen, cft_ref, cft_scen, lat, lon, cell_area,
file = save_file
)
}
return(
list(
state_ref = state_ref,
state_scen = state_scen,
fpc_ref = fpc_ref,
fpc_scen = fpc_scen,
bft_ref = bft_ref,
bft_scen = bft_scen,
cft_ref = cft_ref,
cft_scen = cft_scen,
lat = lat,
lon = lon,
cell_area = cell_area
)
)
}
#' Calculates changes in vegetation structure (vegetation_structure_change)
#'
#' Utility function to calculate changes in vegetation structure
#' (vegetation_structure_change) for calculation of EcoRisk
#'
#' @param fpc_ref reference fpc array (dim: [ncells,npfts+1])
#' @param fpc_scen scenario fpc array (dim: [ncells,npfts+1])
#' @param bft_ref reference bft array (dim: [ncells,nbfts])
#' @param bft_scen scenario bft array (dim: [ncells,nbfts])
#' @param cft_ref reference cft array (dim: [ncells,ncfts])
#' @param cft_scen scenario cft array (dim: [ncells,ncfts])
#' @param weighting apply "old" (Ostberg-like), "new", or "equal" weighting of
#' vegetation_structure_change weights (default "equal")
#'
#' @return vegetation_structure_change array of size ncells with the
#' vegetation_structure_change value [0,1] for each cell
#'
#' @examples
#' \dontrun{
#' vegetation_structure_change <- calc_delta_v(
#' fpc_ref = fpc_ref_mean,
#' fpc_scen = apply(fpc_scen, c(1, 2), mean),
#' bft_ref = bft_ref_mean,
#' bft_scen = apply(bft_scen, c(1, 2), mean),
#' cft_ref = cft_ref_mean,
#' cft_scen = apply(cft_scen, c(1, 2), mean),
#' weighting = "equal"
#' )
#' }
#' @export
calc_delta_v <- function(fpc_ref, # nolint
fpc_scen,
bft_ref,
bft_scen,
cft_ref,
cft_scen,
weighting = "equal") {
di <- dim(fpc_ref)
ncells <- di[1]
npfts <- di[2] - 1
fpc_ref[fpc_ref < 0] <- 0
fpc_scen[fpc_scen < 0] <- 0
bft_ref[bft_ref < 0] <- 0
bft_scen[bft_scen < 0] <- 0
cft_ref[cft_ref < 0] <- 0
cft_scen[cft_scen < 0] <- 0
if (npfts == 9) {
# barren = 1 - crop area - natural vegetation area +
# barren under bioenergy trees
barren_area_ref <- (
1 - rowSums(cft_ref) -
rowSums(fpc_ref[, 2:10]) * fpc_ref[, 1] +
rowSums(cft_ref[, c(16, 32)]) * (1 - rowSums(bft_ref[, c(1:4, 7:10)]))
)
barren_area_ref[barren_area_ref < 0] <- 0
tree_area_ref <- array(0, dim = c(ncells, 11))
# natural tree area fractions scaled by total natural frac
tree_area_ref[, 1:7] <- (
fpc_ref[, 2:8] * fpc_ref[, 1]
)
# fraction of rainfed tropical and temperate BE trees scaled by total
# rainfed bioenergy tree area and relative fpc of bioenergy trees and
# grass under bioenergy trees
tree_area_ref[, 8:9] <- (
cft_ref[, 16] * bft_ref[, 1:2] / rowSums(bft_ref[, c(1, 2, 4)])
)
# fraction of irrigated tropical and temperate BE trees scaled by total
# irrigated bioenergy tree area and relative fpc of bioenergy trees and
# grass under bioenergy trees
tree_area_ref[, 10:11] <- (
cft_ref[, 32] * bft_ref[, 7:8] / rowSums(bft_ref[, c(7, 8, 10)])
)
grass_area_ref <- array(0, dim = c(ncells, 20))
# natural grass
grass_area_ref[, 1:2] <- fpc_ref[, 9:10] * fpc_ref[, 1]
# crops
grass_area_ref[, 3:15] <- cft_ref[, 1:13] + cft_ref[, 17:29]
# managed grass rf
grass_area_ref[, 16] <- cft_ref[, 14]
# managed grass irr
grass_area_ref[, 17] <- cft_ref[, 30]
# bioenergy grass
grass_area_ref[, 18] <- cft_ref[, 15] + cft_ref[, 31]
# fraction of rainfed grass under bioenergy trees
grass_area_ref[, 19] <- (
cft_ref[, 16] * bft_ref[, 4] / rowSums(bft_ref[, c(1, 2, 4)])
)
# fraction of irrigated grass under bioenergy trees
grass_area_ref[, 20] <- (
cft_ref[, 32] * bft_ref[, 10] / rowSums(bft_ref[, c(7, 8, 10)])
)
# barren
barren_area_scen <- (
1 - rowSums(cft_scen) -
rowSums(fpc_scen[, 2:10]) * fpc_scen[, 1] +
rowSums(cft_scen[, c(16, 32)]) * (1 - rowSums(bft_scen[, c(1:4, 7:10)]))
)
barren_area_scen[barren_area_scen < 0] <- 0
tree_area_scen <- array(0, dim = c(ncells, 11))
# natural tree area fractions scaled by total natural frac
tree_area_scen[, 1:7] <- (
fpc_scen[, 2:8] * fpc_scen[, 1]
)
# fraction of rainfed tropical and temperate BE trees scaled by total
# rainfed bioenergy tree area and relative fpc of bioenergy trees and