10.5061/DRYAD.PQ624
Rota, Christopher T.
West Virginia University
University of Missouri
Ferreira, Marco A. R.
Virginia Tech
Kays, Roland W.
North Carolina State University
North Carolina Museum of Natural Sciences
Forrester, Tavis D.
Smithsonian Conservation Biology Institute
Kalies, Elizabeth L.
University of Missouri
McShea, William J.
Smithsonian Conservation Biology Institute
Parsons, Arielle W.
North Carolina Museum of Natural Sciences
Millspaugh, Joshua J.
University of Missouri
Data from: A multispecies occupancy model for two or more interacting species
Dryad
dataset
2017
eMammal
multinomial logit
multivariate Bernoulli
Urocyon cinereoargenteus
Canis latrans
multinomial probit
interspecfic interactions
Holocene
2017-05-04T00:00:00Z
2017-05-04T00:00:00Z
en
https://doi.org/10.1111/2041-210x.12587
212442 bytes
1
CC0 1.0 Universal (CC0 1.0) Public Domain Dedication
Species occurrence is influenced by environmental conditions and the
presence of other species. Current approaches for multispecies occupancy
modelling are practically limited to two interacting species and often
require the assumption of asymmetric interactions. We propose a
multispecies occupancy model that can accommodate two or more interacting
species. We generalize the single-species occupancy model to two or more
interacting species by assuming the latent occupancy state is a
multivariate Bernoulli random variable. We propose modelling the
probability of each potential latent occupancy state with both a
multinomial logit and a multinomial probit model and present details of a
Gibbs sampler for the latter. As an example, we model co-occurrence
probabilities of bobcat (Lynx rufus), coyote (Canis latrans), grey fox
(Urocyon cinereoargenteus) and red fox (Vulpes vulpes) as a function of
human disturbance variables throughout 6 Mid-Atlantic states in the
eastern United States. We found evidence for pairwise interactions among
most species, and the probability of some pairs of species occupying the
same site varied along environmental gradients; for example, occupancy
probabilities of coyote and grey fox were independent at sites with little
human disturbance, but these two species were more likely to occur
together at sites with high human disturbance. Ecological communities are
composed of multiple interacting species. Our proposed method improves our
ability to draw inference from such communities by permitting modelling of
detection/non-detection data from an arbitrary number of species, without
assuming asymmetric interactions. Additionally, our proposed method
permits modelling the probability two or more species occur together as a
function of environmental variables. These advancements represent an
important improvement in our ability to draw community-level inference
from multiple interacting species that are subject to imperfect detection.
Data and code for fitting multi-species occupancy model.Camera trap
detection / non-detection data for bobcats, coyotes, gray foxes, and red
foxes from 6 mid-Atlantic states and the District of Columbia, USA;
associated site-level covariates; and R and Stan code for fitting a
multi-species occupancy model. See ReadMe for detailed file
descriptions.Data.zip
North Carolina
District of Columbia
West Virginia
Tennessee
Maryland
Virginia
South Carolina