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