Do the predicted suitability scores from species distribution models correlate with species performance on-ground?

Species distribution models are a very popular statistical tool for inferring potential distribution range of species across space and time and are thought to be a good predictor for habitat suitability. Some studies have suggested that if these models are reliable, predicted habitat suitability (PHS) should relate to species traits visualization, growth potential, body size, abundance. We validated this hypothesis by estimating association between the PHS and species abundance for 17 avian species endemic to the Western Ghats - Sri Lanka biodiversity hotspot. Additionally, we compared the PHS of sites where species were detected in both seasons (wet and dry) against sites where they were detected in the dry season alone. As a proxy for abundance, we estimated single-season occupancy estimates (ψ) using detection/non-detection data from multiple visits to the survey sites. We report significant and positive PHS-ψ correlation, though the strength of this association varied across species and models. Half of the species showed higher suitability scores for the sites where they were detected year round. The results presented here suggest that the predictive models can be used as a proxy for habitat quality, in addition to inferring the potential distribution.

Methods
The present work utilises the Kerala Bird Atlas dataset available at (https://zenodo.org/record/4920550). Species of interest were selected, presence and absence files were created and five different SDM algorithms were run in the R platform. Input files for occupancy analysis in PRESENCE software were generated. Correlation between the predicted habitat suitability and species occupancy estimates (a proxy for abundance) was estimated.