A Sensitivity Analysis of the Application of Integrated Species Distribution Models to Mobile Species: A Case Study with the Endangered Baird's Tapir

Species distribution models (SDMs) are statistical tools used to develop continuous predictions of species occurrence. 'Integrated SDMs' (ISDMs) are an elaboration of this approach with potential advantages that allow for the dual use of opportunistically collected presence-only data and site-occupancy data from planned surveys. These models also account for survey bias and imperfect detection through the use of a hierarchical modelling framework that separately estimates the species-environment response and detection process. This is particularly helpful for conservation applications and predictions for rare species, where data are often limited and prediction errors may have significant management consequences. Despite this potential importance, ISDMs remain largely untested under a variety of scenarios. We performed an exploration of key modelling decisions and assumptions on an ISDM using the endangered Baird's tapir (Tapirus bairdii) as a test species. We found that site area had the strongest effect on the magnitude of population estimates and underlying intensity surface and was driven by estimates of model intercepts. Selecting a site area that accounted for the individual movements of the species within an average home range led to population estimates that coincided with expert estimates. ISDMs that do not account for the individual movements of species will likely lead to less accurate estimates of species intensity (number of individuals per unit area) and thus overall population estimates. This bias could be severe and highly detrimental to conservation actions if uninformed ISDMs are used to estimate global populations of threatened and data-deficient species, particularly those that lack natural history and movement information. However, the ISDM was consistently the most accurate model compared to other approaches, which demonstrates the importance of this new modelling framework and the ability to combine opportunistic data with systematic survey data. Thus, we recommend researchers use ISDMs with conservative movement information when estimating population sizes of rare and data-deficient species. ISDMs could be improved by using a similar parameterization to spatial capture-recapture models that explicitly incorporate animal movement as a model parameter, which would further remove the need for spatial subsampling prior to implementation. © 2019 Foundation for Environmental Conservation.

Department of Geography and the Environment, University of Texas at Austin, Austin, TX 78712, United States, Global Wildlife Conservation, Austin, TX, United States

Department of Applied Ecology, North Carolina State University, Raleigh, NC 27695, United States

Kelly, M.J., Department of Fish and Wildlife Conservation, Virginia Tech, Blacksburg, VA 24061, United States

Department of Ecology and Evolutionary Biology, University of Toronto, 25 Harbord Street, Toronto, ON M5S 3G5, Canada

El Colegio de la Frontera sur, Departamento de Conservacion de la Biodiversidad, Lerma, Campeche, Mexico, Fundación Yaguara-Panama, Ciudad del Saber, Panama

Global Wildlife Conservation, Austin, TX, United States, Panthera, New York, NY, United States, Department of Fisheries and Wildlife, Michigan State University, East Lansing, MI, United States

Proyecto de Conservación de Aguas y Tierras, ProCAT Colombia/Internacional, Bogotá, Colombia

Instituto Internacional en Conservación y Manejo de Vida Silvestre, Universidad Nacional, Heredia, 3000-1350, Costa Rica

Instituto Internacional en Conservación y Manejo de Vida Silvestre, Universidad Nacional, Heredia, 3000-1350, Costa Rica

Instituto Internacional en Conservación y Manejo de Vida Silvestre