Softwares

hSDM R package

Adansonia grandidieri

hSDM is an R package for hierarchical Bayesian species distribution models. It includes functions to fit mixture models (site-occupancy, N-mixture, ZIB and ZIP models) accounting for imperfect detection, excess of zeros in the observations and spatial autocorrelation (through an intrinsic CAR process). The functions uses an adaptive Metropolis within Gibbs algorithm written in C code. This makes parameter inference faster than with softwares commonly used to fit such models (such as JAGS, WinBUGS or OpenBUGS) and allows analyzing very large data-sets (typically with more than tens of thousands grid cells).

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. manuscript in 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. manuscript in pdf

Royle, J. A. 2004. N-Mixture Models for Estimating Population Size from Spatially Replicated Counts. Biometrics. 60: 108-115. manuscript in pdf

hSDM website: http://hSDM.sf.net.

Contribution to MCMCpack

MCMCpack

MCMCpack (Markov chain Monte Carlo Package) is an R package which contains functions to perform Bayesian inference using posterior simulation for a number of statistical models. Most simulation is done in compiled C++ written with the Scythe Statistical Library Version 1.0.2. Authors: Andrew D. Martin, Kevin M. Quinn, and Jong Hee Park.

Since version 1.1-1 (July 2011), MCMCpack includes additional functions for generalized linear mixed models (glmm): MCMChregress() for Gaussian models, MCMChlogit() for Bernoulli models (logit link function) and MCMChpoisson() for Poisson models (log link function). Author: Ghislain Vieilledent.

Martin A. D., Quinn K. M. and Jong Hee Park 2011. MCMCpack: Markov Chain Monte Carlo in R. Journal of Statistical Software. 42(9): 1-21. manuscript in pdf

Pemstein D., Quinn K. M. and Martin A. D. 2011. The Scythe Statistical Library: An Open Source C++ Library for Statistical Computation. Journal of Statistical Software. 42(12):1-26. manuscript in pdf

Last version of MCMCpack is available on the Comprehensive R Archive Network at http://cran.r-project.org/package=MCMCpack.

phcfM R package

deforestation

phcfM is an R package for modelling anthropogenic deforestation. It was initially developed to obtain REDD+ baseline scenarios of deforestation for the programme holistique de conservation des forêts à Madagascar (from which the package was named after). It includes two main functions:

  1. demography(), to model the population growth with time in a hierarchical Bayesian framework using population census data and Gaussian linear mixed models.
  2. deforestation(), to model the deforestation process in a hierarchical Bayesian framework using land-cover change data and Binomial logistic regression models with variable time-intervals between land-cover observations.

Code and manual

The last stable version of the phcfM R package is officially available for several operating systems (Unix, Windows and Mac OSX) on the Comprehensive R Archive Network (CRAN).

Example

A GRASS location (phcfM_SM) and two mapsets with geographical data layers (PERMANENT and study_area_4) are available to illustrate the use of the phcfM R package. Associated to the GRASS location, a directory (./scripts) includes the data and the R/GRASS scripts used for the demographic and deforestation models.

Vieilledent G., C. Grinand and R. Vaudry. 2013. Forecasting deforestation and carbon emissions in tropical developing countries facing demographic expansion: a case study in Madagascar. Ecology and Evolution. 3:1702-1716. [doi:10.1002/ece3.550]. manuscript in pdf / Supplementary materials supplements

phcfM website: http://phcfM.sf.net.

twoe (2e) software:

twoe

twoe (2e) is a software which aims first, at estimating the demographic parameters of tropical tree species from permanent forest plot data (through an R package) and second, at simulating forest dynamics (through a Capsis module). Authors: Ghislain Vieilledent, François de Coligny.

Laurans M., B. Hérault, G. Vieilledent and G. Vincent. 2014. Vertical stratification reduces competition for light in dense tropical forests. Forest Ecology and Management. 329: 79-88. [doi:10.1016/j.foreco.2014.05.059]. manuscript in pdf / Supplementary materials supplements

Last versions of the R package and of the Capsis module are available on the twoe website: http://twoe.sf.net.