How exactly plant communities will respond to global change drivers (GCDs) remains uncertain. A recent study has shown that community composition is shifting in response to GCDs – the composition of control plots is increasingly different from treated plots over time, although richness is not systematically affected. We hypothesize that studying community changes based on rank abundance curves will link abstract multivariate patterns of change to tangible insights such as changes in richness, evenness, reordering (changes in rank), and turnover (gain and/or losses of species). Here, we explore these five aspects of community change in response to GCDs utilizing CoRRE, a database of 107 resource manipulation experiments. Additionally, we test for generalities between patterns of multivariate change and changes in rank abundance curves. Our dataset of herbaceous experiments includes a range of GCDs, such as nutrient additions, altered precipitation, increased temperature and several land use changes. We compare control and treatment responses overtime to infer how communities are changing in response to GCDs.
Results/Conclusions
Here we demonstrate how rank abundance curves can be used to understand patterns of multivariate change. Essentially, when there is a shift the centroid mean (i.e., significant PERMANOVA), there is a corresponding larger change in richness, evenness, ranks and/or turnover, compared with when there is no difference in centroid means. Second, we found that 83% of communities undergo some aspect of community change in response to GCD, however how the community changed (i.e., which aspect of rank abundance curve changed) varied strongly. Third, we found that the type of GCD (e.g., N addition vs. drought) did not affect which aspect of the rank abundance curve that changed. And lastly, we found some ecosystem properties affected patterns of change. Evenness changed more at wetter sites and sites with a larger regional species pool. Species gains were more common at sites with a higher regional species pool, and species losses were more common at high productivity sites. Overall, we conclude that studying changes in rank abundance curves can translate complex and often abstract community changes into tangible, accessible ideas, providing key insights into community changes over time.