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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 with simulated communities and trait distributions shows sensitivity of functional diversity measures to the number and correlation 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. To address this gap, we used data from six grassland plant communities in Minnesota and New Mexico, USA to test how the number of traits and the correlation between traits used in the calculation of eight functional diversity indices impact the magnitude of functional diversity metrics in real plant communities. We found that most metrics were sensitive to the number of traits used to calculate them, but functional dispersion (FDis), kernel density estimation dispersion (KDE dispersion), and Rao’s quadratic entropy (Rao’s Q) maintained consistent rankings of communities across the range of trait numbers. Despite sensitivity of metrics to trait correlation, there was no consistent pattern between communities as to how metrics were affected by the correlation of traits used to calculate them. We recommend that future use of evenness metrics include sensitivity analyses to ensure results are robust to the number of traits used to calculate them. In addition, we recommend use of FDis, KDE dispersion, and Rao’s Q when ecologically applicable due to their ability to produce consistent rankings among communities across a range of the numbers of traits used to calculate them. 

Abstract In our changing world, understanding plant community responses to global change drivers is critical for predicting future ecosystem composition and function. Plant functional traits promise to be a key predictive tool for many ecosystems, including grasslands; however, their use requires both complete plant community and functional trait data. Yet, representation of these data in global databases is sparse, particularly beyond a handful of most used traits and common species. Here we present the CoRRE Trait Data, spanning 17 traits (9 categorical, 8 continuous) anticipated to predict species’ responses to global change for 4,079 vascular plant species across 173 plant families present in 390 grassland experiments from around the world. The dataset contains complete categorical trait records for all 4,079 plant species obtained from a comprehensive literature search, as well as nearly complete coverage (99.97%) of imputed continuous trait values for a subset of 2,927 plant species. These data will shed light on mechanisms underlying population, community, and ecosystem responses to global change in grasslands worldwide. 

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. 

Abstract Causal effects of biodiversity on ecosystem functions can be estimated using experimental or observational designs — designs that pose a tradeoff between drawing credible causal inferences from correlations and drawing generalizable inferences. Here, we develop a design that reduces this tradeoff and revisits the question of how plant species diversity affects productivity. Our design leverages longitudinal data from 43 grasslands in 11 countries and approaches borrowed from fields outside of ecology to draw causal inferences from observational data. Contrary to many prior studies, we estimate that increases in plot-level species richness caused productivity to decline: a 10% increase in richness decreased productivity by 2.4%, 95% CI [−4.1, −0.74]. This contradiction stems from two sources. First, prior observational studies incompletely control for confounding factors. Second, most experiments plant fewer rare and non-native species than exist in nature. Although increases in native, dominant species increased productivity, increases in rare and non-native species decreased productivity, making the average effect negative in our study. By reducing the tradeoff between experimental and observational designs, our study demonstrates how observational studies can complement prior ecological experiments and inform future ones. 

Abstract In most plant communities, the net effect of nitrogen enrichment is an increase in plant productivity. However, nitrogen enrichment also has been shown to decrease species richness and to acidify soils, each of which may diminish the long‐term impact of nutrient enrichment on productivity. Here we use a long‐term (20 year) grassland plant diversity by nitrogen enrichment experiment in Minnesota, United States (a subexperiment within the BioCON experiment) to quantify the net impacts of nitrogen enrichment on productivity, including its potential indirect effects on productivity via changes in species richness and soil pH over an experimental diversity gradient. Overall, we found that nitrogen enrichment led to an immediate positive increment in productivity, but that this effect became nonsignificant over later years of the experiment, with the difference in productivity between fertilized and unfertilized plots decreasing in proportion to nitrogen addition‐dependent declines in soil pH and losses of plant diversity. The net effect of nitrogen enrichment on productivity could have been 14.5% more on average over 20 years in monocultures if not for nitrogen‐induced decreases in pH and about 28.5% more on average over 20 years in 16 species communities if not for nitrogen‐induced species richness losses. Together, these results suggest that the positive effects of nutrient enrichment on biomass production can diminish in their magnitude over time, especially because of soil acidification in low diversity communities and especially because of plant diversity loss in initially high diversity communities. 

Climate change is increasing the frequency and severity of short-term (~1 y) drought events—the most common duration of drought—globally. Yet the impact of this intensification of drought on ecosystem functioning remains poorly resolved. This is due in part to the widely disparate approaches ecologists have employed to study drought, variation in the severity and duration of drought studied, and differences among ecosystems in vegetation, edaphic and climatic attributes that can mediate drought impacts. To overcome these problems and better identify the factors that modulate drought responses, we used a coordinated distributed experiment to quantify the impact of short-term drought on grassland and shrubland ecosystems. With a standardized approach, we imposed ~a single year of drought at 100 sites on six continents. Here we show that loss of a foundational ecosystem function—aboveground net primary production (ANPP)—was 60% greater at sites that experienced statistically extreme drought (1-in-100-y event) vs. those sites where drought was nominal (historically more common) in magnitude (35% vs. 21%, respectively). This reduction in a key carbon cycle process with a single year of extreme drought greatly exceeds previously reported losses for grasslands and shrublands. Our global experiment also revealed high variability in drought response but that relative reductions in ANPP were greater in drier ecosystems and those with fewer plant species. Overall, our results demonstrate with unprecedented rigor that the global impacts of projected increases in drought severity have been significantly underestimated and that drier and less diverse sites are likely to be most vulnerable to extreme drought. 

Abstract Scientists have known for over a century that resource addition can lead to species loss from plant communities. Recent studies have also shown that resource addition can substantially restructure communities by altering their functional and taxonomic composition—even when species richness remains unchanged. Understanding which aspects of community structure are impacted by different resources and over which timescales will provide insight for management decisions and may also elucidate which measures can act as early warning indicators for subsequent changes in the community. Here, we take advantage of a long‐term factorial experiment to understand how grassland plant communities respond to a decade of nitrogen fertilization (14 g N·m⁻²·yr⁻¹) and irrigation (25 mm water/week during the growing season). After 10 yr, fertilization and irrigation decreased species richness by 22% and 9%, while functional richness decreased by 31% and 41%. Abundance‐weighted functional distance between treatments and controls increased by 55% and 24%, respectively. We expected that abundance‐weighted measures would shift before presence–absence‐based measures, but found limited evidence for this. Instead, our results suggest that species gains, which can occur quickly because they require the addition of only one individual, may serve as early indicators for subsequent community restructuring in the opposite direction. Overall, both chronic nitrogen fertilization and irrigation tended to have gradual and increasing impacts on community structure, but the magnitude of these effects varied greatly depending on the aspect of community structure investigated. Further study will be needed to determine the extent to which our results can be generalized to other resources or sites in order to develop management strategies to maintain both taxonomic and functional trait diversity in the face of chronic resource changes.