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

Published online by Cambridge University Press:  12 June 2019

Cody J Schank*
Affiliation:
Department of Geography and the Environment, The University of Texas at Austin, Austin, TX 78712, USA Global Wildlife Conservation, Austin, TX, USA
Michael V Cove
Affiliation:
Department of Applied Ecology, North Carolina State University, Raleigh, NC 27695, USA
Marcella J Kelly
Affiliation:
Department of Fish and Wildlife Conservation, Virginia Tech, Blacksburg, VA 24061, USA
Clayton K Nielsen
Affiliation:
Department of Forestry and Cooperative Wildlife Research Laboratory, Southern Illinois University, Carbondale, IL 62901-6504, USA
Georgina O’Farrill
Affiliation:
Department of Ecology and Evolutionary Biology, University of Toronto, 25 Harbord Street, Toronto, Ontario, M5S 3G5, Canada
Ninon Meyer
Affiliation:
El Colegio de la Frontera Sur, Departamento de Conservacion de la Biodiversidad, Lerma, Campeche, Mexico Fundación Yaguara-Panama, Ciudad del Saber, Panama
Christopher A Jordan
Affiliation:
Global Wildlife Conservation, Austin, TX, USA Panthera, New York, NY, USA Department of Fisheries and Wildlife, Michigan State University, East Lansing, MI, USA
Jose F González-Maya
Affiliation:
Proyecto de Conservación de Aguas y Tierras, ProCAT Colombia/Internacional, Bogotá, Colombia
Diego J Lizcano
Affiliation:
Departamento Central de Investigación, Universidad Laica Eloy Alfaro de Manabí, Manta, Ecuador The Nature Conservancy, Bogotá, Colombia
Ricardo Moreno
Affiliation:
Fundación Yaguara-Panama, Ciudad del Saber, Panama Smithsonian Tropical Research Institute, Balboa, Panama
Michael Dobbins
Affiliation:
Department of Geography, University of Florida, Gainesville, FL, USA
Victor Montalvo
Affiliation:
Instituto Internacional en Conservación y Manejo de Vida Silvestre, Universidad Nacional, Heredia 3000-1350, Costa Rica
Juan Carlos Cruz Díaz
Affiliation:
Instituto Internacional en Conservación y Manejo de Vida Silvestre, Universidad Nacional, Heredia 3000-1350, Costa Rica Department of Environmental Conservation, University of Massachusetts Amherst, MA, 01003, USA
Gilberto Pozo Montuy
Affiliation:
Conservación de la Biodiversidad del Usumacinta A.C., Emiliano Zapata, Tabasco, C.P. 86990, Mexico
J Antonio de la Torre
Affiliation:
Instituto de Ecología, UNAM, Laboratorio de Ecología y Conservación de Vertebrados Terrestres, Ap. Postal 70-275, C.P. 04510 Ciudad Universitaria, Mexico Bioconciencia A.C., Ciudad de México, Mexico
Esteban Brenes-Mora
Affiliation:
Nai Conservation, San José, Costa Rica Escuela de Biología, Universidad de Costa Rica, Ciudad Universitaria, San José 2060, CostaRica
Margot A Wood
Affiliation:
Conservation International, Arlington, VA, USA
Jessica Gilbert
Affiliation:
Department of Wildlife and Fisheries Sciences, Texas A&M University, College Station, TX, USA
Walter Jetz
Affiliation:
Department of Ecology and Evolutionary Biology, Yale University, New Haven, CT, USA Department of Life Sciences, Imperial College London, Silwood Park Campus, Ascot, Berkshire, UK
Jennifer A Miller
Affiliation:
Department of Geography and the Environment, The University of Texas at Austin, Austin, TX 78712, USA
*
Author for correspondence: Cody J Schank, Email: [email protected]

Summary

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.

Type
Research Paper
Copyright
© Foundation for Environmental Conservation 2019 

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