estimate_PotNatVeg_biomass: Adjust mean monthly biomass values of grass and shrub...

In DrylandEcology/rSOILWAT2: An Ecohydrological Ecosystem-Scale Water Balance Simulation Model

Adjust mean monthly biomass values of grass and shrub functional groups by climate relationships

Description

Adjust mean monthly biomass values of grass and shrub functional groups by climate relationships

Usage

estimate_PotNatVeg_biomass(
  target_temp,
  target_MAP_mm,
  ref_temp,
  tr_VegBiom = rSOILWAT2::sw2_tr_VegBiom,
  do_adjust_phenology = FALSE,
  do_adjust_biomass = FALSE,
  fgrass_c3c4ann = c(1, 0, 0)
)

Arguments

target_temp	A numeric vector of length 12. Mean monthly temperature values in degree Celsius of a target site / condition for which x is to be adjusted.
target_MAP_mm	A numeric value. Mean annual precipitation in millimeter of the location.
ref_temp	A numeric vector of length 12. Reference mean monthly temperature values in degree Celsius under which x was determined / is valid.
tr_VegBiom	A data.frame with 12 rows (one for each month) and columns X.Biomass, X.Amount.Live, X.Perc.Live, and X.Litter where X are for the functional groups shrubs, X = Sh; C3-grasses, X = C3; C4-grasses, X = C4; and annuals, X = Annual containing default input values. Function default values are from Bradford et al. 2014, see sw2_tr_VegBiom.
do_adjust_phenology	A logical value. If TRUE then monthly phenology is adjusted by temperature.
do_adjust_biomass	A logical value. If TRUE then monthly biomass is adjusted by precipitation.
fgrass_c3c4ann	A numeric vector of length 3. Relative contribution ⁠[0-1]⁠ of the C3-grasses, C4-grasses, and annuals functional groups. The sum of fgrass_c3c4ann is 1.

Value

A list with two elements grass, shrub. Each element is a matrix with 12 rows (one for each month) and columns Biomass, Amount.Live, Perc.Live, and Litter.

Default inputs

• Shrubs are based on location ‘IM_USC00107648_Reynolds’ which resulted in a vegetation composition of 70 % shrubs and 30 % C3-grasses. Default monthly biomass values were estimated for MAP = 450 mm yr-1.

• Grasses are based on location ‘GP_SGSLTER’ (shortgrass steppe) which resulted in 12 % shrubs, 22 % C3-grasses, and 66 % C4-grasses. Default biomass values were estimated for MAP = 340 mm yr-1.

• Mean monthly reference temperature are the median values across 898 big sagebrush sites (see https://github.com/DrylandEcology/rSFSTEP2/issues/195)

Details

If do_adjust_biomass, then the internal function adjBiom_by_ppt() is used to adjust biomass by annual precipitation amount. If do_adjust_phenology, then the exported function adj_phenology_by_temp() is used to adjust the seasonal pattern of biomass (phenology) by monthly temperature.

References

Bradford, J.B., Schlaepfer, D.R., Lauenroth, W.K. & Burke, I.C. (2014). Shifts in plant functional types have time-dependent and regionally variable impacts on dryland ecosystem water balance. J Ecol, 102, 1408-1418.

Examples

clim <- calc_SiteClimate(weatherList = rSOILWAT2::weatherData)

veg_cover <- rSOILWAT2::estimate_PotNatVeg_composition(
  MAP_mm = 10 * clim[["MAP_cm"]],
  MAT_C = clim[["MAT_C"]],
  mean_monthly_ppt_mm = 10 * clim[["meanMonthlyPPTcm"]],
  mean_monthly_Temp_C = clim[["meanMonthlyTempC"]],
  dailyC4vars = clim[["dailyC4vars"]]
)

rSOILWAT2::estimate_PotNatVeg_biomass(
  target_temp = clim[["meanMonthlyTempC"]],
  target_MAP_mm = 10 * clim[["MAP_cm"]],
  do_adjust_phenology = TRUE,
  do_adjust_biomass = TRUE,
  fgrass_c3c4ann = veg_cover[["Grasses"]]
)

DrylandEcology/rSOILWAT2 documentation built on Jan. 12, 2024, 9:06 p.m.