Physiology-based prognostic modeling of the influence of changes in precipitation on a keystone dryland plant species.

Fluctuations in mean annual precipitation (MAP) will strongly influence the ecology of dryland ecosystems in the future, yet, because individual precipitation events drive growth and resource availability for many dryland organisms, changes in intra-annual precipitation may disproportionately influence future dryland processes. This work examines the hypothesis that intra-annual precipitation changes will drive dryland productivity to a greater extent than changes to MAP. To test this hypothesis, we created a physiology-based model to predict the effects of precipitation change on a widespread biocrust moss that regulates soil structure, water retention, and nutrient cycling in drylands. First, we used the model to examine moss productivity over the next 100 years driven by alterations in MAP by ± 10, 20 and 30%, and changes in intra-annual precipitation (event size and frequency). Productivity increased as a function of MAP, but differed among simulations where intra-annual precipitation was manipulated under constant MAP. Supporting our hypothesis, this demonstrates that, even if MAP does not change, changes in the features of individual precipitation events can strongly influence long-term performance. Second, we used the model to examine 100-year productivity based on projected dryland precipitation from published global and regional models. These simulations predicted 25-63% reductions in productivity and increased moss mortality rates, declines that will likely alter water and nutrient cycling in dryland ecosystems. Intra-annual precipitation in model-based simulations was a stronger predictor of productivity compared to MAP, further supporting our hypothesis, and illustrating that intra-annual precipitation patterns may dominate dryland responses to altered precipitation in a future climate.