Proximal microclimate: Moving beyond spatiotemporal resolution improves ecological predictions

作者：David H. Klinges, J. Alex Baecher, Jonas J. Lembrechts, Ilya M. D. Maclean, Jonathan Lenoir, Caroline Greiser, Michael B. Ashcroft, Luke J. Evans, Michael Kearney, Juha Aalto, Isabel C. Barrio, Pieter De Frenne, Joannès Guillemot, Kristoffer Hylander, Tommaso Jucker, Martin Kopecký, Miska Luoto, Martin Macek, Ivan Nijs, Josef Urban, Liesbeth van den Brink, Pieter Vangansbeke, Jonathan von Oppen, Jan Wild, Julia Boike, Rafaella Canessa, Marcelo D. Nosetto, Alexey V. Rubtsov, Jhonatan Sallo‐Bravo, Brett R. Scheffers · 发表于：Global Ecology and Biogeography · 年份：2024 · DOI：10.1111/geb.13884 · 被引用次数：42 · 研究领域：Species Distribution and Climate Change、Land Use and Ecosystem Services、Remote Sensing in Agriculture

Abstract Aim The scale of environmental data is often defined by their extent (spatial area, temporal duration) and resolution (grain size, temporal interval). Although describing climate data scale via these terms is appropriate for most meteorological applications, for ecology and biogeography, climate data of the same spatiotemporal resolution and extent may differ in their relevance to an organism. Here, we propose that climate proximity, or how well climate data represent the actual conditions that an organism is exposed to, is more important for ecological realism than the spatiotemporal resolution of the climate data. Location Temperature comparison in nine countries across four continents; ecological case studies in Alberta (Canada), Sabah (Malaysia) and North Carolina/Tennessee (USA). Time Period 1960–2018. Major Taxa Studied Case studies with flies, mosquitoes and salamanders, but concepts relevant to all life on earth. Methods We compare the accuracy of two macroclimate data sources (ERA5 and WorldClim) and a novel microclimate model ( microclimf ) in predicting soil temperatures. We then use ERA5, WorldClim and microclimf to drive ecological models in three case studies: temporal (fly phenology), spatial (mosquito thermal suitability) and spatiotemporal (salamander range shifts) ecological responses. Results For predicting soil temperatures, microclimf had 24.9% and 16.4% lower absolute bias than ERA5 and WorldClim respectively. Across the case studies, we find th...