Details
Date: Mar 12, 2025
Location: San Francisco, CA - USA
Abstract
Predicting species’ responses to environmental change is a critical challenge in ecology. Traditional species distribution models (SDMs) often rely on correlative relationships with strong equilibrium assumptions and limited skill at forecasting distributions under novel conditions. Dynamic range models (DRMs) offer a more mechanistic approach by explicitly incorporating the demographic processes (recruitment, death, movement) that drive range dynamics. However, the complexity of DRMs has hindered their widespread adoption. We introduce drmr, an open-source R package that substantially lowers the barrier to entry for DRM applications. drmr provides a user-friendly framework for building, fitting, visualizing, evaluating, and projecting age-structured DRMs, leveraging the power of Stan for efficient Bayesian inference. Users can readily relate environmental drivers to demographic processes based on observations for a species across space and time. Models can be tailored to specific ecological systems, and competing hypotheses can be tested for range shift mechanisms. By explicitly modeling demographic processes and their environmental drivers, drmr provides a powerful and accessible tool for ecologists to understand and predict changes in species distributions, thereby contributing to improved conservation planning and management in the face of global change.