Data-driven selection of climate variables for ecological applications

Rapport Preprint Data-driven selection of climate variables for ecological applications eng 2026 2026-07-29 author Allaman Héloïse 0009-0007-9761-3944 429871 Serv com physique appliquée (FIGCO) author Miele Chiara 929898 author Goyette Stéphane 0000-0001-5199-5974 647994 Serv com physique appliquée (FIGCO) author Kasparian Jérôme 0000-0003-2398-3882 662563 Serv com physique appliquée (FIGCO) 19 10.2139/ssrn.7202493 https://www.ssrn.com/abstract=7202493 <p>Climate change is impacting ecological systems. The predicted impacts, however, are highly sensitive to the choice of bioclimatic variables. As a result, an essential step in using climate projections is to identify those variables properly aligned with the study&apos;s objectives. Here, we propose a fundamental method for variable selection. We seek to identify variables that capture biophysical properties of a system of interest. This is done by identifying variables where the range of values occupied is relatively narrow compared to the full range of values over the considered domain. The absolute difference between the two distributions is a measure of its ecological relevance. This enables us to select an optimal subset of variables for the system. We assess this approach by applying it to the climatic niches of 287 European tree species. More specifically, we construct climatic niches based on variables selected with our method and compare them with niches derived from two alternatives: a simple variable set based only on temperature and precipitation, and ab unrestricted set including a large number of climatic variables. The choice of variable sets has a strong influence on the inferred climatic niches, with simple or unrestricted sets producing systematically broader and less informative niches. In contrast, the proposed selection framework yields more consistent and ecologically meaningful representations of species–climate relationships. Furthermore, optimal variable sets for individual species are close to the one optimised for the 287 considered tree species.</p> Variable Selection Covariate selection Climatic niche Species Distribution Modelling Europe Trees Climate Change Dewey 500.2 Dewey 333.7-333.9 35 Groupe de physique appliquée 135 18 Institut des sciences de l'environnement 0DB false 803 Groupe Kasparian 938 ISE Pôle Sciences 941 ISE Pôle Informatique environnementale 943 ISE Climat 63a19f50-d874-488d-a4f5-684a962d31b3 Preprint Public paper_param_selection.pdf 8925641 application/pdf cb1d7df8a7619cb2668cf86575b691d88d93ed4a84a469b9d789b3f90ef18617 openAccess Faculté des sciences / Section de physique / Groupe de physique appliquée Centres et instituts / Institut des sciences de l'environnement

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