ecospat.migclim: Implementing Dispersal Into Species Distribution Models

Description

Enables the implementation of species-specific dispersal constraints into projections of species distribution models under environmental change and/or landscape fragmentation scenarios.

Usage

ecospat.migclim ()

Arguments

Details

The MigClim model is a cellular automaton originally designed to implement dispersal constraints into projections of species distributions under environmental change and landscape fragmentation scenarios.

References

Engler, R., W. Hordijk and A. Guisan. 2012. The MIGCLIM R package -- seamless integration of dispersal constraints into projections of species distribution models. Ecography, 35, 872-878.

Engler, R. and A. Guisan. 2009. MIGCLIM: predicting plant distribution and dispersal in a changing climate. Diversity and Distributions, 15, 590-601.

Engler, R., C.F. Randin, P. Vittoz, T. Czaka, M. Beniston, N.E. Zimmermann and A. Guisan. 2009. Predicting future distributions of mountain plants under climate change: does dispersal capacity matter? Ecography, 32, 34-45.

Examples

Run this code

## Not run: 
# ecospat.migclim()
# ### Some example data files can be downloaded from the following web page:
# ### http://www.unil.ch/ecospat/page89413.html
# ###
# ### Run the example as follows (set the current working directory to the
# ### folder where the example data files are located):
# ###
# data(MigClim.testData)
# ### Run MigClim with a data frame type input.
# n <- MigClim.migrate (iniDist=MigClim.testData[,1:3],
# hsMap=MigClim.testData[,4:8], rcThreshold=500,
# envChgSteps=5, dispSteps=5, dispKernel=c(1.0,0.4,0.16,0.06,0.03),
# barrier=MigClim.testData[,9], barrierType="strong",
# iniMatAge=1, propaguleProd=c(0.01,0.08,0.5,0.92),
# lddFreq=0.1, lddMinDist=6, lddMaxDist=15,
# simulName="MigClimTest", replicateNb=1, overWrite=TRUE,
# testMode=FALSE, fullOutput=FALSE, keepTempFiles=FALSE)## End(Not run)

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