The speed of change in climate and land cover is associated with the speed of biodiversity changes in avian assemblages of the United States

PLOS One | https://doi.org/10.1371/journal.pone.0330153 August 29, 2025 10 / 20 models for total assemblage dissimilarity in the Eastern Temperate Forest, Great Plains, and North American Deserts, and of models for species replacement and species loss, was lower (Table 3). The results of the sensitivity analysis showed that the amount of variance in the four biodiversity metrics studied that was explained by the environmental predictors varied with the geographical scale of the analysis (Table 3). For instance, while the variance explained of total assemblage dissimilarity for the Northwestern Forested Mountains was 27% when the scale of the predictors was tabulated for 25 km sampling areas, the variance explained was 38% for 12.5 km and 47% for 50 km sampling areas. Relative importance of climate and LULC as drivers of rate of change of biodiversity The relative importance of climate change and LULC change varied by biodiversity metric and was ecoregion-dependent (Fig 4). As a general trend, LULC variables were more important predictors for all biodiversity metrics for the Northern Forest (Fig 4A-4D), for species replacement and loss in Great Plains and North American Deserts (Fig 4B and 4C), and for species richness in the Northwestern Forested Mountains (Fig 4D). Both climatic and LULC variables were equally important in predicting the total dissimilarity and species replacement in the Northwestern Forested mountains (Fig 4A and 4B). Climatic variables were the most important predictors for the species replacement, loss and richness of the Eastern

Temperate Forests (Fig 4B-4D). Discussion Our analyses spanned an extensive geographic region and a relatively long time period (30 years), revealing four main general results: 1. High elevation and high latitude ecoregions showed stronger relationships between biodiversity metrics and environ- mental factors where fast change in the environment was associated with fast biotic responses. Table 2. GAMMs relating the rate of change of species richness with the rate of change of the environment in five ecoregions of the US at a resolution of 25 km (1990–2019). Ecoregion PPT (mm) Tmax (oC) Tmin (oC) Barren land Crop/ Pasture Forest Grassland/ Shrubland Urban Wetland Elevation (m) R2 Northern Forest (N = 61) – (-) – (-) – (-) NA – (-) 0.1* (*) – (-) 0.1* (*) – (-) – (-) 0.17 Northwestern Forested Mountains (N = 56) – (***) – (-) −0.09** (**) – (-) −0.07* (*) – (*) 0.05^ (*) NA – (***) NA 0.03 Great Plains (N = 95) No term was significant 0 North Ameri- can Deserts (N = 50) No term was significant 0 Eastern Temperate Forest (N = 309) – (-) 0.06** (**) – (-) NA – (-) – (-) – (-) NA – (-) – (-) 0.02 We show the linear model coefficients of variables with a significant effect and the significance of smooth terms between parenthesis for all variables. We also present the proportion of the variability the model explains (Adjusted R2) and the number of BBS routes included in the analyses (N). Significant P-values are represented as follow: ***P < 0.001, **P < 0.01, *P < 0.05. Marginally significant P-values are represented as ^P < 0.065. Non-significant

effects are denoted with a single dash (-) and predictor variables not included in the model are denoted with NA. https://doi.org/10.1371/journal.pone.0330153.t002