| cliHoldridgePoints {macroBiome} | R Documentation |
Vegetation Classifier Using the HLZ System
Description
Calculates the values of bioclimatic indices used in the Holdridge life zone (HLZ) system (Holdridge 1947, 1967), and designates the HLZ type using these values, by using the monthly time series of temperature and precipitation.
Usage
cliHoldridgePoints(temp, prec, verbose = FALSE)
Arguments
temp |
'numeric' R object with one-year time series of monthly mean air temperature (in °C) |
prec |
'numeric' R object with one-year time series of monthly precipitation sum (in mm) |
verbose |
'logical' scalar that indicates whether or not values of the bioclimatic indices used should be added to the output. |
Details
To classify vegetation, the HLZ system developed by Holdridge (1947, 1967) uses the values of the following 3 bioclimatic indices:
abt: Mean Annual Biotemperature (Eq 1 in Szelepcsényi et al. (2014); in °C)tap: Total Annual Precipitation (in mm)per: Potential Evapotranspiration Ratio (Eq 4 in Szelepcsényi et al. (2014); dimensionless)
For details about calculating bioclimatic indices, see the function
cliBioCliIdxPoints.
The HLZ system classifies the vegetation type based on the distance from the ideal (theoretical) point in the
3-dimensional space of bioclimatic indices. Numerous variants of the HLZ system are known (e.g.,
Henderson-Sellers 1994; Yates et al. 2000). Here, one of its most widely used versions ('version with no
altitudinal belts') is implemented, in accordance with works of Szelepcsényi et al. (2014, 2018). In this
version, a total of 39 HLZ types are distinguished (see vegClsNumCodes).
Value
Depending on the setting, a data frame with one or more columns where the HLZ types are stored in the last
(character) column, while the additional columns contain the values of bioclimatic indices used. The
abbreviations of HLZ types can be found in the data frame vegClsNumCodes. If
verbose = FALSE, the return object is a one-column data frame with the HLZ types.
Note
As with any function with a point mode, a set of basic input data is defined here. In this case, they are as
follows: 'temp' (one-year time series of monthly mean air temperature), and 'prec' (one-year
time series of monthly precipitation sum). The objects 'temp' and 'pre' must be either vectors
of length 12 or 12-column matrices. The first dimensions of these matrices have to be the same length. The
function automatically converts vectors into single-row matrices during the error handling, and then uses
these matrices. The first dimensions of these matrices determines the number of rows in the result matrix.
References
Henderson-Sellers A (1994) Global terrestrial vegetation ‘prediction’: the use and abuse of climate and application models. Prog Phys Geogr 18(2):209–246. doi:10.1177/030913339401800203
Holdridge LR (1947) Determination of World Plant Formations From Simple Climatic Data. Science 105(2727):367–368. doi:10.1126/science.105.2727.367
Holdridge LR (1967) Life zone ecology. Tropical Science Center, San Jose, Costa Rica
Szelepcsényi Z, Breuer H, Sümegi P (2014) The climate of Carpathian Region in the 20th century based on the original and modified Holdridge life zone system. Cent Eur J Geosci 6(3):293–307. doi:10.2478/s13533-012-0189-5
Szelepcsényi Z, Breuer H, Kis A, Pongrácz R, Sümegi P (2018) Assessment of projected climate change in the Carpathian Region using the Holdridge life zone system. Theor Appl Climatol 131(1–2):593–610. doi:10.1007/s00704-016-1987-3
Yates DN, Kittel TGF, Cannon RF (2000) Comparing the Correlative Holdridge Model to Mechanistic Biogeographical Models for Assessing Vegetation Distribution Response to Climatic Change. Clim Chang 44(1–2):59–87. doi:10.1023/A:1005495908758
Examples
# Loading mandatory data for the Example 'Points'
data(inp_exPoints)
data(vegClsNumCodes)
# Designate the HLZ type (using the related bioclimatic indices),
# at a grid cell near Szeged, Hungary (46.3N, 20.2E) (for the normal period 1981-2010)
with(inp_exPoints, {
HLZ <- cliHoldridgePoints(colMeans(temp), colMeans(prec), verbose = TRUE)
numCode <- which(sapply(vegClsNumCodes$Code.HLZ, identical, HLZ[, "vegCls"]))
cbind(HLZ[,-c(4)], vegClsNumCodes[numCode, c("Name.HLZ", "Code.HLZ")])
})