Modelling snow cover duration improves predictions of functional and taxonomic diversity for alpine plant communities

摘要: Background and Aims Quantifying relationships between snow cover duration plant community properties remains an important challenge in alpine ecology. This study develops a method to estimate spatial variation energy availability the context of topographically complex, high-elevation watershed, which was used test explanatory power environmental gradients both with without relation taxonomic functional diversity. Methods Snow French Alps mapped at 15-m resolution using Landsat imagery for five recent years, generalized additive model (GAM) fitted each year linking time topography. Predicted maps were combined air temperature solar radiation data daily resolution, summed averaged across years. Equivalent growing season also estimated accounting duration. Relationships tested diversity metrics measured 100 plots, including species richness, community-weighted mean traits, hyperspectral estimates canopy chlorophyll content. Key Results Accounting variables consistently led improved predictive power as well as more ecologically meaningful characterizations diversity. Model parameters differed significantly when cover. Filtering compared average gain R2 0·26 reversed slope direction intuitive several metrics. Conclusions The results show that environments high-resolution on are pivotal capturing heterogeneity use climate consideration can lead erroneous predictions further indicate studies seeking predict response communities change need consider shifts nival regimes.