Frameworks on Patterns of Grasslands’ Sensitivity to Forecast Extreme Drought

Abstract

Climate models have predicted the future occurrence of extreme drought (ED). The management, conservation, or restoration of grasslands following ED requires a robust prior knowledge of the patterns and mechanisms of sensitivity—declining rate of ecosystem functions due to ED. Yet, the global-scale pattern of grasslands’ sensitivity to any ED event remains unresolved. Here, frameworks were built to predict the sensitivity patterns of above-ground net primary productivity (ANPP) spanning the global precipitation gradient under ED. The frameworks particularly present three sensitivity patterns that could manipulate (weaken, strengthen, or erode) the orthodox positive precipitation–productivity relationship which exists under non-drought (ambient) condition. First, the slope of the relationship could become steeper via higher sensitivity at xeric sites than mesic and hydric ones. Second, if the sensitivity emerges highest in hydric, followed by mesic, then xeric, a weakened slope, flat line, or negative slope would emerge. Lastly, if the sensitivity emerges unexpectedly similar across the precipitation gradient, the slope of the relationship would remain similar to that of the ambient condition. Overall, the frameworks provide background knowledge on possible differences or similarities in responses of grasslands to forecast ED, and could stimulate increase in conduct of experiments to unravel the impacts of ED on grasslands. More importantly, the frameworks indicate the need for reconciliation of conflicting hypotheses of grasslands’ sensitivity to ED through global-scale experiments.