Resolution in species distribution models shapes spatial patterns of plant multifaceted diversity

نویسندگان

چکیده

Species distribution models (SDMs) are statistical tools that relate species observations to environmental conditions retrieve ecological niches and predict species' potential geographic distributions. The quality robustness of SDMs clearly depend on good modelling practices including ascertaining the relevance predictors for studied choosing an appropriate spatial resolution (or ‘grain size'). While past studies showed improved model performance with increasing sessile organisms, there is still no consensus regarding how inappropriate can impede understanding mapping multiple facets diversity. Here, we modelled 1180 plant across European Alps two sets (climate soil) at resolutions ranging from 100-m 40-km. We assessed predictors' importance each resolution, calculated taxonomic (TD), relative phylogenetic (rPD) functional diversity (rFD) accordingly, compared resulting diversities space. In accordance previous studies, found predictive generally decrease decreasing predictor resolution. Overall, multifaceted was be strongly affected by particularly rPD, as exhibited weak average linear relationships between 1-km (0.13 ≤ R2 0.57). Our results demonstrate necessity using highly resolved explain distributions, especially in mountain environments. Using coarser might cause mispredicted, important consequences biodiversity management conservation.

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ژورنال

عنوان ژورنال: Ecography

سال: 2022

ISSN: ['0906-7590', '1600-0587']

DOI: https://doi.org/10.1111/ecog.05973