Using spatiotemporal species distribution models to identify temporally evolving hotspots of species co‐occurrence

• Published in: Ecological applications 2015, Vol.25 (8), p.2198-2209
• Main Authors: Ward, Eric J, Jason E. Jannot, Yong-Woo Lee, Kotaro Ono, Andrew O. Shelton, James T. Thorson
• Format: Article
• Language: English
• Subjects: anthropogenic activities; biogeography; bycatch; case studies; coasts; data collection; Endangered Species Act of 1973; fishing boats; nontarget organisms; population growth; population size; risk; shrimp; statistical models; surface water temperature; Thaleichthys pacificus
• ISSN: 1051-0761; 1939-5582

Identifying spatiotemporal hotspots is important for understanding basic ecological processes, but is particularly important for species at risk. A number of terrestrial and aquatic species are indirectly affected by anthropogenic impacts, simply because they tend to be associated with species that are targeted for removals. Using newly developed statistical models that allow for the inclusion of time‐varying spatial effects, we examine how the co‐occurrence of a targeted and nontargeted species can be modeled as a function of environmental covariates (temperature, depth) and interannual variability. The nontarget species in our case study (eulachon) is listed under the U.S. Endangered Species Act, and is encountered by fisheries off the U.S. West Coast that target pink shrimp. Results from our spatiotemporal model indicated that eulachon bycatch risk decreases with depth and has a convex relationship with sea surface temperature. Additionally, we found that over the 2007–2012 period, there was support for an increase in eulachon density from both a fishery data set (+40%) and a fishery‐independent data set (+55%). Eulachon bycatch has increased in recent years, but the agreement between these two data sets implies that increases in bycatch are not due to an increase in incidental targeting of eulachon by fishing vessels, but because of an increasing population size of eulachon. Based on our results, the application of spatiotemporal models to species that are of conservation concern appears promising in identifying the spatial distribution of environmental and anthropogenic risks to the population.