Optimization of spatial scale, but not functional shape, affects the performance of habitat suitability models: a case study of tigers (Panthera tigris) in Thailand

Species habitat suitability models rarely incorporate multiple spatial scales or functional shapes of a species’ response to covariates. Optimizing for these factors may produce more robust, reliable, and informative models, which can be beneficial the conservation rare endangered species, such as tigers (Panthera tigris). We provide first formal assessment relative impacts scale-optimization shape-optimization on model performance predictions. explored how optimization influences conclusions regarding selection mapped probability occurrence. collated environmental variables expected affect tiger occurrence, calculating focal statistics landscape metrics at ranging from 250 m 16 km. then constructed set presence–absence generalized linear including: (1) single-scale optimized (SSO); (2) multi-scale (MSO); (3) shape-optimized (SSSO) (4) multi-scale- (MSSO). compared resulting prediction maps top performing models. The SSO (16 km), SSSO MSO, MSSO performed equally well (AUC > 0.9). However, differed substantially in suitability, leading different ecological understanding potentially divergent recommendations. Habitat was highly scale-dependent strongest relationships with were broadest analysed. Modelling approach had substantial influence variable importance among Our results suggest that scale resource is crucial modelling selection. this analysis, did not improve performance.