A Bayesian method for assessing multiscalespecies-habitat relationships

Landscape Ecology
By: , and 

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Abstract

Context

Scientists face several theoretical and methodological challenges in appropriately describing fundamental wildlife-habitat relationships in models. The spatial scales of habitat relationships are often unknown, and are expected to follow a multi-scale hierarchy. Typical frequentist or information theoretic approaches often suffer under collinearity in multi-scale studies, fail to converge when models are complex or represent an intractable computational burden when candidate model sets are large.

Objectives

Our objective was to implement an automated, Bayesian method for inference on the spatial scales of habitat variables that best predict animal abundance.

Methods

We introduce Bayesian latent indicator scale selection (BLISS), a Bayesian method to select spatial scales of predictors using latent scale indicator variables that are estimated with reversible-jump Markov chain Monte Carlo sampling. BLISS does not suffer from collinearity, and substantially reduces computation time of studies. We present a simulation study to validate our method and apply our method to a case-study of land cover predictors for ring-necked pheasant (Phasianus colchicus) abundance in Nebraska, USA.

Results

Our method returns accurate descriptions of the explanatory power of multiple spatial scales, and unbiased and precise parameter estimates under commonly encountered data limitations including spatial scale autocorrelation, effect size, and sample size. BLISS outperforms commonly used model selection methods including stepwise and AIC, and reduces runtime by 90%.

Conclusions

Given the pervasiveness of scale-dependency in ecology, and the implications of mismatches between the scales of analyses and ecological processes, identifying the spatial scales over which species are integrating habitat information is an important step in understanding species-habitat relationships. BLISS is a widely applicable method for identifying important spatial scales, propagating scale uncertainty, and testing hypotheses of scaling relationships.

Additional publication details

Publication type Article
Publication Subtype Journal Article
Title A Bayesian method for assessing multiscalespecies-habitat relationships
Series title Landscape Ecology
DOI 10.1007/s10980-017-0575-y
Volume 32
Issue 12
Year Published 2017
Language English
Publisher Springer
Contributing office(s) Coop Res Unit Seattle
Description 17 p.
First page 2365
Last page 2381
Country United States
State Nebraska