Abstract
Abstract Context Species habitat suitability models rarely incorporate multiple spatial scales or functional shapes of a species’ response to covariates. Optimizing models for these factors may produce more robust, reliable, and informative habitat suitability models, which can be beneficial for the conservation of rare and endangered species, such as tigers (Panthera tigris). Objectives We provide the first formal assessment of the relative impacts of scale-optimization and shape-optimization on model performance and habitat suitability predictions. We explored how optimization influences conclusions regarding habitat selection and mapped probability of occurrence. Methods We collated environmental variables expected to affect tiger occurrence, calculating focal statistics and landscape metrics at spatial scales ranging from 250 m to 16 km. We then constructed a set of presence–absence generalized linear models including: (1) single-scale optimized models (SSO); (2) a multi-scale optimized model (MSO); (3) single-scale shape-optimized models (SSSO) and (4) a multi-scale- and shape-optimized model (MSSO). We compared performance and resulting prediction maps for top performing models. Results The SSO (16 km), SSSO (16 km), MSO, and MSSO models performed equally well (AUC > 0.9). However, these differed substantially in prediction and mapped habitat suitability, leading to different ecological understanding and potentially divergent conservation recommendations. Habitat selection was highly scale-dependent and the strongest relationships with environmental variables were at the broadest scales analysed. Modelling approach had a substantial influence in variable importance among top models. Conclusions Our results suggest that optimization of the scale of resource selection is crucial in modelling tiger habitat selection. However, in this analysis, shape-optimization did not improve model performance.
Highlights
Much of modern ecological analysis is underpinned by ecological niche theory (Hutchinson 1957)
Our results suggest that optimization of the scale of resource selection is crucial in modelling tiger habitat selection
The Dong Phayayen–Khao Yai Forest Complex (DPKY) covers 6155 km2 in eastern Thailand (Fig. 1). It consists of five protected areas—Khao Yai National Park (KYNP), Thap Lan National Park (TLNP), Pang Sida National Park (PSNP), Ta Phraya National Park (TPNP), and Dong Yai Wildlife Sanctuary (DYWS)
Summary
Much of modern ecological analysis is underpinned by ecological niche theory (Hutchinson 1957). The proliferation of modern analytical tools (Elith et al 2006; Blonder 2018) and increased computational power to quantify these fundamental and realized niches has advanced the field of landscape ecology and enabled more powerful habitat selection modelling (Hegel et al 2010). Such assessments, even for wellstudied species, are rarely straightforward (Mayor et al 2009). Related assumptions pertaining to these relationships have largely been untested
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