COS 54-2 - How to measure response diversity

Background/Question/Methods

Though convenient to measure, species-based diversity metrics are, at best, proxies for the inter- and intraspecific trait differences that mechanistically underlie the insurance effect of biodiversity—that diversity enhances and stabilises aggregate ecosystem properties. In theory, variation in functional (e.g., biomass) responses to environmental change can buffer and maintain ecosystem functioning. This variation, termed response diversity, is therefore a potentially critical determinant of ecological stability. However, response diversity has yet to be widely quantified, possibly due to difficulties in its measurement, and when it has been measured, approaches have varied. Here, we propose a methodological framework for quantifying response diversity from experimental or observational data, which can be practically applied in lab and field settings across a range of taxa. Our approach, which is based on environment-dependent functional responses to any biotic or abiotic environment, is conceptually simple and robust to any form of environmental response, including nonlinear responses. As opposed to previous studies focusing primarily on ‘low level’ functional traits such as nitrogen content, or specific leaf area, we suggest considering response diversity a ‘high level’ trait of, for instance, per capita growth rates. We then apply this method to data from two case studies on aquatic microbes.

Results/Conclusions

Here we reanalyse data from a previous study measuring response diversity, and reveal nonlinearities and environment-dependencies where there previously were none. Response diversity peaked at median temperatures (~22-24 C), but high temperatures resulted in constant growth rate among species (i.e., lower response diversity). We also found that peak response diversity was driven mainly by a single ciliate species (Colpidium striatum), highlighting the disproportionate contribution of this species to response diversity, and hence perhaps to stability. In a second case study, we show that microbial communities isolated from pond duckweeds exhibit response diversity of growth rates. This response diversity scales with nutrient additions, where high Nitrogen concentrations produce the highest response diversity, and a more varied response diversity through time as natural community turnover and succession takes place. In turn, we found that response diversity was positively related to ecological stability (that is, dampened community biomass fluctuations), providing evidence for a positive diversity-stability relationship driven mechanistically by response diversity. By capturing even subtle inter- or intraspecific differences in environmental responses, and environment-dependencies in response diversity, we hope this framework will motivate tests of the diversity-stability relationship from a new perspective, in turn, facilitating a more mechanistic understanding of ecological stability.