Coastal nurseries are critical for the early stages of many elasmobranchs, and understanding spatial ecology during these periods is essential for effective population management. Here, we investigated the environmental drivers shaping shark presence and spatial distribution in an open coastal nursery used by young-of-the-year Sphyrna lewini along the southern Pacific Coast of Mexico. Using acoustic telemetry data collected over three consecutive seasons, we combined Random Forest models with an interpretable machine learning framework, including permutation-based variable importance, accumulated local effects, and a Rashomon set approach. Shark presence was primarily driven by seasonal patterns and lunar illumination, whereas spatial distribution within the nursery area was structured by tide level, shark length, accumulated precipitation, and sea surface temperature. Tide level emerged as the most influential and stable predictor of spatial preference, while size-dependent responses revealed ontogenetic spatial segregation among zones. These results demonstrate that open-coast nurseries can operate through dynamic environmental processes rather than static habitat features, with river-influenced areas playing a key role for smaller individuals. By integrating telemetry data with interpretable machine learning methods, this study provides a mechanistic understanding of nursery habitat use and offers a transferable framework for assessing spatial ecology and conservation priorities in threatened coastal shark populations.
Rosende‐Pereiro et al. (Sat,) studied this question.