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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 FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. Isolating the relationships between biodiversity and ecosystem functioning in natural ecosystems is challenging. Here, the authors apply a causal inference approach to observational data from grasslands and find a negative effect of biodiversity on productivity driven by non-native and rare species. [ABSTRACT FROM AUTHOR]

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. Isolating the relationships between biodiversity and ecosystem functioning in natural ecosystems is challenging. Here, the authors apply a causal inference approach to observational data from grasslands and find a negative effect of biodiversity on productivity driven by non-native and rare species. [ABSTRACT FROM AUTHOR]

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 FROM AUTHOR]

The effects of altered nutrient supplies and herbivore density on species diversity vary with spatial scale, because coexistence mechanisms are scale dependent. This scale dependence may alter the shape of the species–area relationship (SAR), which can be described by changes in species richness (S) as a power function of the sample area (A): S = cAz, where c and z are constants. We analysed the effects of experimental manipulations of nutrient supply and herbivore density on species richness across a range of scales (0.01–75 m2) at 30 grasslands in 10 countries. We found that nutrient addition reduced the number of species that could co‐occur locally, indicated by the SAR intercepts (log c), but did not affect the SAR slopes (z). As a result, proportional species loss due to nutrient enrichment was largely unchanged across sampling scales, whereas total species loss increased over threefold across our range of sampling scales. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

BACKGROUND: Vocational recovery is a concept that has grown out of the mental health recovery model and has been operationalized as a threshold for work capacity for persons working with serious mental illness (SMI). In this article, is it conceptualized as a process towards gainful employment and overall mental health recovery. OBJECTIVE: This article describes the early phases of the vocational recovery process of individuals with serious mental illness participating in a supported employment program and the factors that make up this process. This study describes the vocational recovery process and the mental health related recovery gains attained through employment. METHODS:Aconstructivist grounded theory approachwas employed in this study. The primary author conducted participant observations and conducted semi-structured interviews with 10 individuals at a supported employment program to develop a theory about a vocational process that is grounded in data. RESULTS: A phase like process emerged from the data, which moved individuals from prevocational to early vocational recovery to active vocational recovery process. Participants experienced both mental health and vocational recovery challenges and benefits as they moved through the supported employment program and substantial support from providers, family members, program director and peers emerged as a driving force to move individuals through the recovery process. CONCLUSION: Participants in this study rapidly placed into a supported employment program were able to move through their psychosocial barriers to employment and move towards an active vocational recovery process. The phase like progression suggests that appropriate interventions can be formulated that best meets the individual's vocational and mental health needs depending on where individuals are in their overall vocational recovery process. Follow up research is necessary. [ABSTRACT FROM AUTHOR]

Recent studies have revealed many potential benefits of increasing plant diversity in natural ecosystems, as well as in agroecosystems and production forests. Plant diversity potentially provides a partial to complete substitute for many costly agricultural inputs, such as fertilizers, pesticides, imported pollinators and irrigation. Diversification strategies include enhancing crop genetic diversity, mixed plantings, rotating crops, agroforestry and diversifying landscapes surrounding croplands., Here we briefly review studies considering how increasing plant diversity influences the production of crops, forage, and wood, yield stability, and several regulating and supporting agroecosystem services. We also discuss challenges and recommendations for diversifying agroecosystems., There is consistently strong evidence that strategically increasing plant diversity increases crop and forage yield, wood production, yield stability, pollinators, weed suppression and pest suppression, whereas effects of diversification on soil nutrients and carbon remain poorly understood., Synthesis. The benefits of diversifying agroecosystems are expected to be greatest where the aims are to sustainably intensify production while reducing conventional inputs or to optimize both yields and ecosystem services. Over the next few decades, as monoculture yields continue to decelerate or decline for many crops, and as demand for ecosystem services continues to rise, diversification could become an essential tool for sustaining production and ecosystem services in croplands, rangelands and production forests. [ABSTRACT FROM AUTHOR]

Tens of thousands of species are threatened with extinction as a result of human activities. Here we explore how the extinction risks of terrestrial mammals and birds might change in the next 50 years. Future population growth and economic development are forecasted to impose unprecedented levels of extinction risk on many more species worldwide, especially the large mammals of tropical Africa, Asia and South America. Yet these threats are not inevitable. Proactive international efforts to increase crop yields, minimize land clearing and habitat fragmentation, and protect natural lands could increase food security in developing nations and preserve much of Earth's remaining biodiversity. [ABSTRACT FROM AUTHOR]

The correct version states "[ I P i SB I i i sb ( I R i ") - I P i SB I i i sb ( I R i ')]" in place of "[(R") - (R')]", " I P i SB I i i sb ( I R i ')" in place of " I P i ( I R i ')", and " I E i [ I P i SB I i i sb ( I R i ") - I P i SB I i i sb ( I R i ')]" in place of "[(R") - P(R')]". These sentences incorrectly read "The causal effect of a change in richness from I R i ' to I R i " on productivity I P i in plot I i i is defined as [( I R i ") - ( I R i ')], where I P i SB I i i sb ( I R i ") is the potential productivity outcome when I R i = I R i " and I P i ( I R i ') is the potential productivity outcome when I R i = I R i ' ( I R i ' /= I R i ")." and "The average causal effect of a change in biodiversity from I R i ' to I R i " across all plots is [( I R i ") - I P i ( I R i ')], where I E i [-] is the expectation operator.". [Extracted from the article]

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. [ABSTRACT FROM AUTHOR]