Community Modeling

USGS Patuxent Wildlife Research Center (link)


Amielle DeWan
Defenders of Wildlife

Bob Dorazio
USGS Florida Integrated Science Center

Jim Hines
USGS Patuxent Wildlife Research Center

Marc K
Swiss Ornithological Institute

Viviana Ruiz-Gutiérrez
Cornell University Laboratory of Ornithology

John Sauer
USGS Patuxent Wildlife Research Center

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A Hierarchical Approach to Multi-species Inference

Elise Zipkin                                             J. Andrew Royle

USGS Patuxent Wildlife Research Center          USGS Patuxent Wildlife Research Center                                   

The hierarchical community model is a multi-species approach to obtain community information, such as species or assemblage richness, by estimating individual species occurrence probabilities. The fundamental idea behind the community approach is that collective information on all observed species can inform probabilities of detection and occurrence for both observed and unobserved species, even those that are rare or elusive. This results in an improved composite analysis of the community and increased precision in species specific estimates of occurrence. The hierarchical model can be specified to incorporate habitat and sampling effects that influence occurrence and detection. Thus the community approach can provide the best possible estimates of species richness and other metrics of interest across a heterogeneous landscape, while accounting for variation in occurrence and detection among species.

The purpose of this website is to illustrate the methodology behind community hierarchical models by providing the necessary software code to implement the basic model as well as more complicated models, including those with covariates and multiple years of data. We also include references to papers with relevant examples.