macroBiome (version 0.4.0)

cliForestSteppeGrid: Forest-Steppe Models

Description

Calculates the values of bioclimatic indices used in forest-steppe models with different theoretical backgrounds, and estimates the presence/absence of 'forest-steppe' ecotone, for a given region and year/epoch, by using the monthly time series of climate variables, and the elevation data.

Usage

cliForestSteppeGrid(
  rs.temp,
  rs.prec,
  rs.bsdf = NULL,
  rl.elv = NULL,
  sc.year = 2000,
  aprchTEMP = c("hip", "tsi", "const"),
  aprchBSDF = c("hip", "const"),
  dvTEMP = rep(0.7, 12),
  verbose = FALSE,
  filename = "",
  ...
)

Value

Depending on the settings, a SpatRaster object with two or more layers where the presence/absence data are stored in layers labelled 'fsp_hlz', 'fsp_fai' and 'fsp_svm', while the additional layers contain the values of bioclimatic indices used. If verbose = FALSE, the return object is a two- or three-layer SpatRaster object with presence/absence data, depending on the available data.

Arguments

rs.temp

multi-layer Raster*/SpatRaster object with one-year time series of monthly mean air temperature (in °C)

rs.prec

multi-layer Raster*/SpatRaster object with one-year time series of monthly precipitation sum (in mm)

rs.bsdf

multi-layer Raster*/SpatRaster object with one-year time series of monthly mean relative sunshine duration (dimensionless)

rl.elv

single-layer Raster*/SpatRaster object with the elevation values (in meters above sea level)

sc.year

'numeric' scalar with the value of the year (using astronomical year numbering)

aprchTEMP

'character' vector of length 1 that indicates the scheme used to generate daily values of the daily mean air temperature for a specific year. Valid values are as follows:
(a) 'hip' - this scheme applies the mean-preserving 'harmonic' interpolation method of Epstein (1991) to the values of monthly mean air temperature in order to generate daily values;
(b) 'tsi' - this scheme uses an iterative interpolation technique (Lüdeke et al. 1994) to time series of the monthly mean air temperature, in order to generate a synthetic time series of the selected meteorological variable at a temporal resolution that is higher than the daily scale; finally, this synthetic time series is upscaled to a daily resolution;
(c) 'const' - this scheme is assumed that values of the daily mean air temperature are constant within each month.

aprchBSDF

'character' vector of length 1 that indicates the scheme used to generate daily values of the daily fractional sunshine duration for a specific year. Valid values are as follows:
(a) 'hip' - this scheme applies the mean-preserving 'harmonic' interpolation method of Epstein (1991) to the values of monthly mean relative sunshine duration in order to generate daily values;
(b) 'const' - this scheme is assumed that values of the daily relative sunshine duration are constant within each month.

dvTEMP

'numeric' vector of length 12 with monthly values of the damping variable for the air temperature data.

verbose

'logical' scalar that indicates whether or not values of the bioclimatic indices used should be added to the output.

filename

output filename

...

additional arguments passed on to writeRaster

Details

See cliForestSteppePoints.

References

Epstein ES (1991) On Obtaining Daily Climatological Values from Monthly Means. J Clim 4(3):365–368. tools:::Rd_expr_doi("10.1175/1520-0442(1991)004<0365:oodcvf>2.0.CO;2")

Lüdeke MKB, Badeck FW, Otto RD, Häger C, Dönges S, Kindermann J, Würth G, Lang T, Jäkel U, Klaudius A, Ramge P, Habermehl S, Kohlmaier GH (1994) The Frankfurt Biosphere Model: A global process-oriented model of seasonal and long-term CO2 exchange between terrestrial ecosystems and the atmosphere. I. Model description and illustrative results for cold deciduous and boreal forests. Clim Res 4(2):143-166. tools:::Rd_expr_doi("10.3354/cr004143")

Examples

# Loading mandatory data for the Example 'Climate Normal Grid'
data(inp_exClnrGrid)

# Predict the 'forest-steppe' ecotone (using the related bioclimatic indices),
# with default settings, for Csongrad-Csanad County (for the normal period 1981-2010)
with(inp_exClnrGrid, {
year <- trunc(mean(seq(1981, 2010)))
rs.fsp1 <- cliForestSteppeGrid(temp, prec, verbose = TRUE)
rs.fsp1
})

# \donttest{
# Predict the 'forest-steppe' ecotone (using the related bioclimatic indices),
# with default settings, for Csongrad-Csanad County (for the normal period 1981-2010)
with(inp_exClnrGrid, {
year <- trunc(mean(seq(1981, 2010)))
rs.fsp2 <- cliForestSteppeGrid(temp, prec, bsdf, elv, sc.year = year, verbose = TRUE)
rs.fsp2
})
# }