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BIOCLIM rasters

Source: R/bioclims_GRaster.r, R/bioclims_SpatRaster.r
bioclims.Rd

The BIOCLIM set of bioclimatic variables were created for modeling species' geographic distributions (Booth et al. 2014). This function can create the "standard" 19 set of variables, plus several more from an "extended" set.

"Classic" set of BIOCLIM variables (Booth et al. 2014): The units reported below assume that input rasters are in mm (precipitation) and deg C (temperature), and that each raster represents a month (but other time units are allowed, with corresponding changes to the temporal units assumed below).

  • BIO1: Mean annual temperature, calculated using monthly means (deg C)

  • BIO2: Mean diurnal range across months (average of monthly difference between maximum and minimum temperature) (deg C)

  • BIO3: Isothermality (100 * BIO02 / BIO07; unit-less)

  • BIO4: Temperature seasonality (standard deviation across months of average monthly temperature * 100; deg C)

  • BIO5: Maximum temperature of the warmest month (based on maximum temperature; deg C)

  • BIO6: Minimum temperature of the coldest month (based on minimum temperature; deg C)

  • BIO7: Range of annual temperature (BIO05 - BIO06; deg C)

  • BIO8: Temperature of the wettest quarter (based on mean temperature; deg C)

  • BIO9: Temperature of the driest quarter (based on mean temperature; deg C)

  • BIO10: Temperature of the warmest quarter (based on mean temperature; deg C)

  • BIO11: Temperature of the coldest quarter (based on mean temperature; deg C)

  • BIO12: Total annual precipitation (mm)

  • BIO13: Precipitation of the wettest month (mm)

  • BIO14: Precipitation of the driest month (mm)

  • BIO15: Precipitation seasonality (100 * coefficient of variation; unit-less)

  • BIO16: Precipitation of the wettest quarter (mm)

  • BIO17: Precipitation of the driest quarter (mm)

  • BIO18: Precipitation of the warmest quarter (based on mean temperature; mm)

  • BIO19: Precipitation of the coldest quarter (based on mean temperature; mm)

"Extended" set of BIOCLIM variables (starts at 41 to avoid conflicts with Kriticos et al. 2014):

  • BIO41: Temperature of the quarter following the coldest quarter (based on mean temperature; deg C)

  • BIO42: Temperature of the quarter following the warmest quarter (based on mean temperature; deg C)

  • BIO43: Precipitation of the quarter following the coldest quarter (based on mean temperature; mm)

  • BIO44: Precipitation of the quarter following the warmest quarter (based on mean temperature; mm)

  • BIO45: Temperature of the quarter following the driest quarter (based on mean temperature; deg C)

  • BIO46: Temperature of the quarter following the wettest quarter (based on mean temperature; deg C)

  • BIO47: Precipitation of the quarter following the driest quarter (based on mean temperature; mm)

  • BIO48: Precipitation of the quarter following the wettest quarter (based on mean temperature; mm)

  • BIO49: Hottest month (based on maximum temperature)

  • BIO50: Coldest month (based on minimum temperature)

  • BIO51: Wettest month

  • BIO52: Driest month

  • BIO53: First month of the warmest quarter (based on mean temperature)

  • BIO54: First month of the coldest quarter (based on mean temperature)

  • BIO55: First month of the wettest quarter

  • BIO56: First month of the driest quarter

  • BIO57: The greatest decrease in temperature from one month to the next (deg C; always >= 0)

  • BIO58: The greatest increase in temperature from one month to the next (deg C; always >= 0)

  • BIO59: The greatest decrease in precipitation from one month to the next (mm; always >= 0)

  • BIO60: The greatest increase in precipitation from one month to the next (mm; always >= 0)

By default, "quarter" refers to any consecutive run of three months, not a financial quarter. A quarter can thus include November-December-January, or December-January-February, for example. However, the length of a quarter can be changed using the argument quarter.

The variables are defined assuming that the input rasters represent monthly values (12 rasters for min/max temperature and precipitation), but you can also use sets of 52 rasters, representing one per week, in which case "quarter" would be a successive run of 3 weeks. You could also attempt 365 rasters, in which case a "quarter" would be a run of 3 successive days.

BIOCLIMs 41 through 44 are added here to capture the "shoulder" seasons (spring and autumn) important in temperature regions. BIOCLIMs 45 through 48 are also included for consistency.

BIOCLIMs 49 through 60 are not bioclimatic variables per se, but useful for assessing the properties of the variables that are defined based on the "-est" month or quarter.

Usage

# S4 method for class 'GRaster'
bioclims(
  ppt,
  tmin,
  tmax,
  tmean = NULL,
  bios = NULL,
  sample = TRUE,
  quarter = 3,
  pptDelta = 1,
  verbose = TRUE
)

# S4 method for class 'SpatRaster'
bioclims(
  ppt,
  tmin,
  tmax,
  tmean = NULL,
  bios = NULL,
  sample = TRUE,
  quarter = 3,
  pptDelta = 1,
  verbose = TRUE
)

Arguments

ppt

A multi-layered GRaster or SpatRaster, representing monthly/weekly/daily precipitation.

tmin, tmax

A multi-layered GRaster or SpatRaster, representing monthly/weekly/daily minimum and maximum temperature.

tmean

Either NULL (default), or a multi-layered GRaster or SpatRaster, representing monthly/weekly/daily average temperature. If NULL, tmean will be calculated internally from tmin and tmax. Providing these rasters thus saves time if you already have them on hand.

bios

Any of:

  • Numeric values: Calculate these BIOCLIM variables. For example, bios = c(1, 12) calculates BIOCLIMs 1 and 12.

  • NULL (default): Calculate BIOCLIMs 1 through 19

  • "*": Calculate all BIOCLIMs this function can calculate.

  • "+": Calculate BIOCLIMs 41 onward.

  • Any combination of the above except NULL (e.g., c(1, 12, "+")).

sample

Logical: If TRUE (default), BIO4 and 15 are calculated with the sample standard deviation. If FALSE, then the population standard deviation is used.

quarter

Numeric: Length of a "quarter". BIOCLIM variables are typically calculated using monthly-averaged rasters (e.g., precipitation and temperature of January, February, etc.), in which case a "quarter" is 3 months (so the default for quarter is 3). However, this function can accommodate any set of rasters representing a time series (e.g., 365 for daily rasters), in which case the user can decide what constitutes a "quarter" for calculation of the any BIOCLIMs that use "quarters" in their definitions.

pptDelta

Numeric: Value to add to precipitation for calculation of BIO15 (coefficient of variation of precipitation, times 100). Adding a small value avoids division by 0. The default is 1.

verbose

Logical: If TRUE (default), display progress.

Value

A GRaster with one or more layers.

References

Booth, T.H., Nix, H.A., Busby, J.R., and Hutchinson, M.F. 2014. BIOCLIM: The first species distribution modeling package, its early applications and relevance to most current MaxEnt studies. Diversity and Distributions 20:1-9 doi:10.1111/ddi.12144 .

Kriticos, D.J., Jarošik, V., and Otam N. 2014. Extending the suite of BIOCLIM variables: A proposed registry system and case study using principal components analysis. Methods in Ecology and Evolution 5:956-960 doi:10.1111/2041-210X.12244 .

Examples

if (grassStarted()) {

# Setup
library(terra)

# Load rasters with precipitation and min/max temperature
madPpt <- fastData("madPpt")
madTmin <- fastData("madTmin")
madTmax <- fastData("madTmax")

### Classic and extended BIOCLIMs from SpatRasters
bcSR <- bioclims(madPpt, madTmin, madTmax, bios = "*")
bcSR

### BIOCLIMs from GRasters
ppt <- fast(madPpt)
tmin <- fast(madTmin)
tmax <- fast(madTmax)

# For small rasters, takes longer to run compared to SpatRaster version:
bc <- bioclims(ppt, tmin, tmax, bios = c(1, 5, 12))
bc
plot(bc)

}