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bioRxiv · 10.64898/2026.09.11.750976

Climate Warming Patterns Predict Potential Residency Shifts

Abstract

Introduction and Aim: Future climate instability creates obstacles for organisms across taxa, especially in areas that experience higher stochasticity. Wetland wading bird populations are a prime example of this scenario, as the hydrologic cycles that drive population success in these habitats depend heavily on the predictability of wet and dry periods. When fluctuations in wet and dry periods shift excessively, populations may be forced to relocate or shift migration routes. Our goal is to predict if worsening environmental conditions could drive increases in facultative migration and subsequent residency shifts Location: State of Florida, USA. Methods: We developed an individual-based movement model motivated by wading birds in southern Florida to determine if this concept of climate-driven range or residency shift is likely to occur in the future. To further interpret the outputs of this individual-based model, we compared habitat suitability for the American wood stork across Southeast of the United States between 2010 and 2025, 2055 and 2085. Results: Our IBM model predicted that a northward residency shift is predicted to occur given the environmental scenario of harsher fluctuation via climate instability in the Everglades. Moreover, our findings suggest that wood storks with partial and/or facultative migration may be more likely to adapt to these fluctuations. Our suitability maps showed spatially heterogeneous responses, with notable increases in northern Georgia, and the Carolinas, and consistent declines in northern Florida, indicating a gradual northward shift in suitable breeding habitat. Main Conclusions: Conserving networks of suitable wetlands across broader spatial scales, may be critical for facilitating movement and persistence under hydrologic instability. Mechanistic models such as the one presented in this study can help anticipate these shifts and inform proactive conservation planning. This model can also be adapted to fit similar wetland systems, or other landscapes with various population and movement phenotypes present.

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BibTeXRIS

Hessler, G. R., Ma, S., Gilbert, N., DeAngelis, D., Zhai, L., Zhang, B.. 2026-09-15. Climate Warming Patterns Predict Potential Residency Shifts. https://doi.org/10.64898/2026.09.11.750976

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