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The use of trait-based approaches to understand ecological communities has increased in the past two decades because of their promise to preserve more information about community structure than taxonomic methods and their potential to connect community responses to subsequent effects of ecosystem functioning. Though trait-based approaches are a powerful tool for describing ecological communities, many important properties of commonly-used trait metrics remain unexamined. Previous work in studies that simulate communities and trait distributions show consistent sensitivity of functional richness and evenness measures to the number of traits used to calculate them, but these relationships have yet to be studied in actual plant communities with a realistic distribution of trait values, ecologically meaningful covariation of traits, and a realistic number of traits available for analysis. Therefore, we propose to test how the number of traits used and the correlation between traits used in the calculation of functional diversity indices impacts the magnitude of eight functional diversity metrics in real plant communities. We will use trait data from three grassland plant communities in the US to assess the generality of our findings across ecosystems and experiments. We will determine how eight functional diversity metrics (functional richness, functional evenness, functional divergence, functional dispersion, kernel density estimation (KDE) richness, KDE evenness, KDE dispersion, Rao’s Q) differ based on the number of traits used in the metric calculation and on the correlation of traits when holding the number of traits constant. Without a firm understanding of how a scientist’s choices impact these metric, it will be difficult to compare results among studies with different metric parametrization and thus, limit robust conclusions about functional composition of communities across systems. 

Whether the terrestrial biosphere will continue to act as a net carbon (C) sink in the face of multiple global changes is questionable. A key uncertainty is whether increases in plant C fixation under elevated carbon dioxide (CO₂) will translate into decades-long C storage and whether this depends on other concurrently changing factors. We investigated how manipulations of CO₂, soil nitrogen (N) supply, and plant species richness influenced total ecosystem (plant + soil to 60 cm) C storage over 19 y in a free-air CO₂enrichment grassland experiment (BioCON) in Minnesota. On average, after 19 y of treatments, increasing species richness from 1 to 4, 9, or 16 enhanced total ecosystem C storage by 22 to 32%, whereas N addition of 4 g N m⁻²⋅ y⁻¹and elevated CO₂of +180 ppm had only modest effects (increasing C stores by less than 5%). While all treatments increased net primary productivity, only increasing species richness enhanced net primary productivity sufficiently to more than offset enhanced C losses and substantially increase ecosystem C pools. Effects of the three global change treatments were generally additive, and we did not observe any interactions between CO₂and N. Overall, our results call into question whether elevated CO₂will increase the soil C sink in grassland ecosystems, helping to slow climate change, and suggest that losses of biodiversity may influence C storage as much as or more than increasing CO₂or high rates of N deposition in perennial grassland systems.