Abstract
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.
| Original language | English |
|---|---|
| Pages (from-to) | 1164-1173 |
| Number of pages | 10 |
| Journal | Methods in Ecology and Evolution |
| Volume | 7 |
| Issue number | 10 |
| DOIs | |
| State | Published - Oct 1 2016 |
Funding
We thank our 376 volunteers for their hard work collecting camera trap data for this study. For their field assistance and volunteer coordination, we thank the staff of the NPS, USFWS, USFS, TNC, NC, SC, VA, MD and TN State Parks, NCWRC, TNDF, VDGIF, WVWA, the WNF and RPRCR. We thank N. Fuentes, S. Higdon, T. Perkins, L. Gatens, R. Owens, R. Gayle, C. Backman, K. Clark, J. Grimes and J. Simkins for their help reviewing photographs. This work was conducted with funding from the National Science Foundation grant #1232442 and #1319293, the VWR Foundation, the US Forest Service, the North Carolina Museum of Natural Sciences and the Smithsonian Institution. We thank M. Baker for conversations about study design, training and managing volunteers in WV, VA and MD, and for reviewing, cleaning and managing data from the project. We thank R. Dorazio, R. O’Hara and an anonymous reviewer for helpful comments on early versions of this manuscript. Data, R and Stan code are deposited in the Dryad repository http://dx.doi.org/10.5061/dryad.pq624.
| Funders | Funder number |
|---|---|
| 1319293, 1232442 | |
| Smithsonian Institution | |
| U.S. Forest Service-Retired | |
| North Carolina State Museum of Natural Sciences | |
Keywords
- community
- competition
- eMammal
- interspecific interactions
- multinomial logit
- multinomial probit
- multivariate Bernoulli
- occupancy modelling
- predation