Ecological pathways connecting riverine drought to community change across space and time

Climate change is intensifying droughts via reduced snowpack and accelerated snowmelt in high mountains globally, altering community structure in snow-dependent rivers. To predict impending ecological change in rivers, we must understand the importance of the abiotic and biotic mechanisms connecting hydrologic change to biodiversity change and whether these mechanisms operate similarly across space and time. Here, we studied abiotic effects of drought and invertebrate communities in a minimally disturbed watershed in California's Sierra Nevada. Our study employed a highly replicated design of 60 nested sites (capturing microhabitat to reach-level variation) and over two decades of change (2002–2023) in a subset of sites, including the driest period on record. We used spatial stream network (SSN) models and autoregressive (AR) models to partition the spatial and temporal variance into covariate-driven versus autocorrelation effects. Structural equation modeling allowed us to identify causal pathways connecting hydrologic change to invertebrate community change. We found that drought-driven variation in temperature, water velocity, and fine sediment all explained variation in abundance in over a third of the species in the community. Notably, the influence of abiotic effects differed across space and time: no taxa had their variance explained by the same abiotic effect in the same direction across space and time, and total spatial variance explained by abiotic effects for each species had no relationship with its temporal counterpart. We also found that community dissimilarity across space was poorly explained by abiotic effects, while temporal dissimilarity was driven by differences in temperature and water velocity causing species turnover. Finally, we tested the scale dependency of our inferences by changing the extent and resolution of our data (resampling from seasonal to interannual; from microhabitat to watershed-level data) and found that pathways of community change varied depending on scale and on whether comparisons were made across space or time. These differences between space and time likely arise from some ecological drivers operating more strongly in one dimension and from spatial and temporal autocorrelation in species abundances masking environmental effects. Our study illustrates that projecting riverine community composition under future hydroclimates requires accounting for mechanism context dependency over space and time.