Abstract

Understanding the intricate relationships between climate and vegetation remains a fundamental challenge in contemporary ecology. The ability to anticipate the specific climatic factors affecting different tree species and understand how they respond is crucial for mitigating the impacts of climate change on forested ecosystems. Additionally, quantitatively assessing habitat loss resulting from anthropogenic activities is essential for informed conservation efforts. Our objective is to evaluate the potential distribution of pitch pine (Pinus rigida) in North America and assess the associated habitat loss. To achieve this, we employ a stepwise multidimensional climate envelope modeling approach, comparing two data-intensive models—the Variable Interaction Model (VIM) and the Variable Non-Interaction Model (VNM). These models discern the influence of diverse combinations of climatic characteristics on the distribution of the species. Both VNM and VIM employ Shapley values for factor ranking during construction. VNM assumes independent effects, resulting in a hyperrectangle-shaped climate envelope, while VIM considers interactions, yielding a complex, data-driven multidimensional envelope. Data integration involves mining the US Forest Inventories and climatic data, encompassing 19 parameters. The results unequivocally highlight the superior predictive accuracy of VIM compared to the Variable Non-Interaction Model, VNM. The modeling approach developed in this study has the potential to enhance species distribution models for various tree species in the context of evolving climatic conditions.

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