hSDM R package
hSDM is an R package for estimating parameters of hierarchical Bayesian species distribution models. Such models allows interpreting the observations (occurrence and abundance of a species) as a result of several hierarchical processes including ecological processes (habitat suitability, spatial dependence and anthropogenic disturbance) and observation processes (species detectability). Hierarchical species distribution models are essential for accurately characterizing the environmental response of species, predicting their probability of occurrence, and assessing uncertainty in the model results.
The last stable version of the
hSDM R package
is officially available for several operating systems (Unix, Windows and Mac OSX) on the Comprehensive R Archive Network (CRAN).
Manual and vignette
Package manual and vignette
are available here:
The source code and development version are available on GitHub and can be cloned with the following command:
git clone https://github.com/ghislainv/hSDM.git
Tutorials on internet
- Tutorial on using opportunistic species occurrence data for occupancy modelling by Adam M. Wilson on GitHub.
- Tutorial on modelling spatial autocorrelation by Jérôme Guélat on Amazonaws.
Methodological related publications
Gelfand A. E., Silander J. A., Wu S. S., Latimer A., Lewis P. O., Rebelo A. G. and Holder M. 2006. Explaining species distribution patterns through hierarchical modeling. Bayesian Analysis. 1(1): 41-92. pdf
Latimer A. M., Wu S. S., Gelfand A. E. and Silander J. A. 2006. Building statistical models to analyze species distributions. Ecological Applications. 16(1): 33-50. pdf
MacKenzie D. I., Nichols J. D., Lachman G. B., Droege S., Royle J. A. and Langtimm C. A. 2002. Estimating site occupancy rates when detection probabilities are less than one. Ecology. 83: 2248-2255. pdf
Royle, J. A. 2004. N-Mixture Models for Estimating Population Size from Spatially Replicated Counts. Biometrics. 60: 108-115. pdf
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