Standardized indices to estimate sensitivity to drought across ecosystems

Question Climate change scenarios predict alterations in interannual variability of precipitation and increases of extreme droughts. Drought effects will reflect ecosystems' sensitivity (i.e. the magnitude of the response relative to the change in amount of precipitation), with different consequences for plant communities and ecosystem functioning. However, sensitivity estimations across ecosystems and among years are contingent upon the metric applied. Here, we asked how different sensitivity indices reflect the responses to drought in contrasting ecosystems. Methods We proposed a novel index to estimate sensitivity in drought experiments, which consider the change in the response variable in relation to the reduction in precipitation, standardized by the mean precipitation use efficiency of the site, making it suitable to compare among contrasting ecosystems. We compared the information gained from the new index with two indices commonly used in experimentally induced droughts, through simulated scenarios. Besides, we applied the indices to data from previous field drought experiments to evaluate relative and absolute sensitivity to drought in worldwide grassland ecosystems along a wide precipitation gradient. Results We found that both relative and absolute approaches yielded important information to determine drought sensitivity in different simulated scenarios and under interannual precipitation variability. When the indices were applied to real situations, relative sensitivity to drought showed a significant increase as mean annual precipitation decreases whereas absolute sensitivity did not change significantly with precipitation. Conclusions Our findings highlighted that absolute and relative indices to estimate drought sensitivity, rather than being redundant, may complement each other to inform how ecosystems respond to drought and to provide a more holistic assessment of vulnerable systems toward increasing interannual precipitation variability. This complementary approach enhances our understanding of ecosystem response under different conditions of precipitation variability and of the mechanisms that determine ecosystem changes during extreme droughts.