Tue, Aug 16, 2022: 2:10 PM-2:30 PM
520F
Background/Question/MethodsThe diversity-stability relationship (DSR) is a classic theme in ecology, which has motivated a long-standing interest among theoretical and experimental scientists. Several decades of research efforts contribute to resolving the early debate on DSR by clarifying that stability is a multidimensional concept and DSR can be either positive or negative depending on which measure of stability is used. Among the various dimensions of stability, the most commonly used measure is the temporal stability of community or ecosystem functions (measured by the inverse of temporal variability of total biomass or productivity). Theoretical and experimental studies have showed consistently that species diversity can increase temporal stability, suggesting that biodiversity loss is likely to impair the stability of ecosystem functions. In spite of these advances, previous studies have mostly focused on local communities, at a spatial scale that is much smaller than that of ecological conservation and management. Therefore, there is an urgent need to extend DSR theory to larger scales. To fill this gap, we developed new theoretical frameworks and used several datasets to study DSR across spatial scales.
Results/ConclusionsWe developed two theoretical frameworks to characterize temporal stability across scales. In the first framework, we defined consistent measures of stability at local (alpha) and regional (gamma) scales, and defined a metric of spatial asynchrony (beta stability) that serves as a scaling factor from alpha to gamma scales. Based on metacommunity models, we showed that alpha and beta diversity can promote alpha and beta stability, respectively, through local and insurance effects. In the second framework, we proposed the concept of stability-area relationship (StAR) to capture the spatial scaling of stability. We then analyzed DSRs in both experimental and natural communities, using a global dataset of grassland biodiversity experiments and the observational data of plant communities from the National Ecological Observatory Network. The results supported our predictions on the positive DSRs across scales. They also showed that the spatial scaling of stability (StAR) was largely driven by that of species diversity (i.e. species-area relationships). Moreover, by collaborating with the Nutrient Network, we found that eutrophication could weaken the positive relationships between diversity and stability at different scales. Taken together, our theoretical and empirical work demonstrated the destabilizing effects of biodiversity loss across scales and their potential interactions with global change drivers.
Results/ConclusionsWe developed two theoretical frameworks to characterize temporal stability across scales. In the first framework, we defined consistent measures of stability at local (alpha) and regional (gamma) scales, and defined a metric of spatial asynchrony (beta stability) that serves as a scaling factor from alpha to gamma scales. Based on metacommunity models, we showed that alpha and beta diversity can promote alpha and beta stability, respectively, through local and insurance effects. In the second framework, we proposed the concept of stability-area relationship (StAR) to capture the spatial scaling of stability. We then analyzed DSRs in both experimental and natural communities, using a global dataset of grassland biodiversity experiments and the observational data of plant communities from the National Ecological Observatory Network. The results supported our predictions on the positive DSRs across scales. They also showed that the spatial scaling of stability (StAR) was largely driven by that of species diversity (i.e. species-area relationships). Moreover, by collaborating with the Nutrient Network, we found that eutrophication could weaken the positive relationships between diversity and stability at different scales. Taken together, our theoretical and empirical work demonstrated the destabilizing effects of biodiversity loss across scales and their potential interactions with global change drivers.