Hierarchical Bayesian Species Distribution Models

User-friendly and fast set of functions for estimating parameters of hierarchical Bayesian species distribution models (Latimer et al. 2006 ). Such models allow 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.


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hSDM is an R package for estimating parameters of hierarchical Bayesian species distribution models. Such models allow 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.

Installation

# Install release version from CRAN
install.packages("hSDM")
 
# Install development version from GitHub
devtools::install_github("ghislainv/hSDM")

Vignettes and manual

In the wild

Related publications

Diez J. M. and Pulliam H. R. 2007. Hierarchical analysis of species distributions and abundance across environmental gradients. Ecology. 88(12): 3144-3152.

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.

Latimer, A. M.; Wu, S. S.; Gelfand, A. E. & Silander, J. A. 2006. Building statistical models to analyze species distributions. Ecological Applications. 16(1): 33-50.

MacKenzie, D. I.; Nichols, J. D.; Lachman, G. B.; Droege, S.; Andrew Royle, J. and Langtimm, C. A. 2002. Estimating site occupancy rates when detection probabilities are less than one. Ecology. 83: 2248-2255.

Royle, J. A. 2004. N-mixture models for estimating population size from spatially replicated counts. Biometrics. 60: 108-115.

News

Reference manual

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install.packages("hSDM")

1.4.1 by Ghislain Vieilledent, 14 days ago


https://ecology.ghislainv.fr/hSDM, https://github.com/ghislainv/hSDM


Report a bug at https://github.com/ghislainv/hSDM/issues


Browse source code at https://github.com/cran/hSDM


Authors: Ghislain Vieilledent [aut, cre] , Matthieu Autier [ctb] , Alan E. Gelfand [ctb] , Jérôme Guélat [ctb] , Marc Kéry [ctb] , Andrew M. Latimer [ctb] , Cory Merow [ctb] , Frédéric Mortier [ctb] , John A. Silander Jr. [ctb] , Adam M. Wilson [ctb] , Shanshan Wu [ctb] , CIRAD [cph, fnd]


Documentation:   PDF Manual  


GPL-3 | file LICENSE license


Imports coda

Suggests knitr, raster, sp, rmarkdown, bookdown


See at CRAN