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Middle Rio Grande riparian plant cover sensitivity to variability in groundwater depth collected by the Bosque Ecosystem Monitoring Program

Determining the ecological consequences of interactions between slow changes in long-term climate means and amplified variability in climate is an important research frontier in plant ecology. We combined the recent approach of climate sensitivity functions with a revised hydrological ‘bucket model’ to improve predictions on how plant species will respond to future changes in both the mean and variance of groundwater resources. We leveraged spatiotemporal variation in a long-term dataset of riparian vegetation cover to build the first groundwater sensitivity functions (GSFs) for common plant species of dryland riparian corridors. Our results demonstrate the value of this approach to identifying which plant species will thrive (or fail) in an increasingly variable climate layered on top of declining groundwater stores. Riparian plant species differed in sensitivity to both the mean and variance in groundwater levels. Rio Grande cottonwood (Populus deltoides ssp. wislizenii) cover was predicted to decline with greater interannual groundwater variance, while coyote willow (Salix exigua) and other native wetland species were predicted to benefit from greater year-to-year variance. No non-native species were sensitive to groundwater variance, but patterns for Russian olive (Elaeagnus angustifolia) predict declines under deeper mean groundwater tables. Warm air temperatures modulated groundwater sensitivity for cottonwood, which was more sensitive to variability in groundwater in years/sites with warmer maximum temperatures than in cool sites/periods. Cottonwood cover declined most with greater intra-annual coefficients of variation (CV) in groundwater, but was not significantly correlated with inter-annual CV, perhaps due to the relatively short time series (16 y) relative to cottonwood lifespan. In contrast, non-native tamarisk (Tamarix chinensis) cover increased with both intra- and inter-annual CV in groundwater. Altogether, our results predict that changes in groundw