Can fieldwork driven by predictive species distribution models yield new rare or relevant geographic records? A case study with Neotropical snakes

Abstract

Understanding species distribution patterns has been a major quest in biodiversity research. Due to their secretive habits and rarity, snakes have been historically underrepresented in assessments of geographic distribution range. In this work, we employ a pipeline for predictive model-based species sampling, using Neotropical snakes as a model organism. We employ species distribution models based on verified point records for five candidate snake species of probable occurrence to Rio Grande do Sul state, Brazil: Apostolepis dimidiata (Jan 1862), Erythrolamprus aesculapii (Linnaeus 1758), Helicops leopardinus (Schlegel 1837), Lygophis meridionalis (Schenkel 1901), and Micrurus corallinus (Merrem 1820). Based on the resulting models, we conducted fieldwork on areas with higher overlap of suitable ranges and probability of new records. Our study yields a new state record of A. dimidiata to Rio Grande do Sul and highlights the usefulness of species distribution models in eliciting priority areas for faunal assessments.