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Eutrophication usually impacts grassland biodiversity, community composition, and biomass production, but its impact on the stability of these community aspects is unclear. One challenge is that stability has many facets that can be tightly correlated (low dimensionality) or highly disparate (high dimensionality). Using standardized experiments in 55 grassland sites from a globally distributed experiment (NutNet), we quantify the effects of nutrient addition on five facets of stability (temporal invariability, resistance during dry and wet growing seasons, recovery after dry and wet growing seasons), measured on three community aspects (aboveground biomass, community composition, and species richness). Nutrient addition reduces the temporal invariability and resistance of species richness and community composition during dry and wet growing seasons, but does not affect those of biomass. Different stability measures are largely uncorrelated under both ambient and eutrophic conditions, indicating consistently high dimensionality. Harnessing the dimensionality of ecological stability provides insights for predicting grassland responses to global environmental change.

 

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 Plant productivity varies due to environmental heterogeneity, and theory suggests that plant diversity can reduce this variation. While there is strong evidence of diversity effects on temporal variability of productivity, whether this mechanism extends to variability across space remains elusive. Here we determine the relationship between plant diversity and spatial variability of productivity in 83 grasslands, and quantify the effect of experimentally increased spatial heterogeneity in environmental conditions on this relationship. We found that communities with higher plant species richness (alpha and gamma diversity) have lower spatial variability of productivity as reduced abundance of some species can be compensated for by increased abundance of other species. In contrast, high species dissimilarity among local communities (beta diversity) is positively associated with spatial variability of productivity, suggesting that changes in species composition can scale up to affect productivity. Experimentally increased spatial environmental heterogeneity weakens the effect of plant alpha and gamma diversity, and reveals that beta diversity can simultaneously decrease and increase spatial variability of productivity. Our findings unveil the generality of the diversity-stability theory across space, and suggest that reduced local diversity and biotic homogenization can affect the spatial reliability of key ecosystem functions. 

All multicellular organisms host a diverse microbiome composed of microbial pathogens, mutualists, and commensals, and changes in microbiome diversity or composition can alter host fitness and function. Nonetheless, we lack a general understanding of the drivers of microbiome diversity, in part because it is regulated by concurrent processes spanning scales from global to local. Global-scale environmental gradients can determine variation in microbiome diversity among sites, however an individual host’s microbiome also may reflect its local micro-environment. We fill this knowledge gap by experimentally manipulating two potential mediators of plant microbiome diversity (soil nutrient supply and herbivore density) at 23 grassland sites spanning global-scale gradients in soil nutrients, climate, and plant biomass. Here we show that leaf-scale microbiome diversity in unmanipulated plots depended on the total microbiome diversity at each site, which was highest at sites with high soil nutrients and plant biomass. We also found that experimentally adding soil nutrients and excluding herbivores produced concordant results across sites, increasing microbiome diversity by increasing plant biomass, which created a shaded microclimate. This demonstration of consistent responses of microbiome diversity across a wide range of host species and environmental conditions suggests the possibility of a general, predictive understanding of microbiome diversity.

 

Grassland ecosystems cover around 37% of the ice-free land surface on Earth and have critical socioeconomic importance globally. As in many terrestrial ecosystems, biological dinitrogen (N 2 ) fixation represents an essential natural source of nitrogen (N). The ability to fix atmospheric N 2 is limited to diazotrophs, a diverse guild of bacteria and archaea. To elucidate the abiotic (climatic, edaphic), biotic (vegetation), and spatial factors that govern diazotrophic community composition in global grassland soils, amplicon sequencing of the dinitrogenase reductase gene— nifH —was performed on samples from a replicated standardized nutrient [N, phosphorus (P)] addition experiment in 23 grassland sites spanning four continents. Sites harbored distinct and diverse diazotrophic communities, with most of reads assigned to diazotrophic taxa within the Alphaproteobacteria (e.g., Rhizobiales ), Cyanobacteria (e.g., Nostocales ), and Deltaproteobacteria (e.g., Desulforomonadales ) groups. Likely because of the wide range of climatic and edaphic conditions and spatial distance among sampling sites, only a few of the taxa were present at all sites. The best model describing the variation among soil diazotrophic communities at the OTU level combined climate seasonality (temperature in the wettest quarter and precipitation in the warmest quarter) with edaphic (C:N ratio, soil texture) and vegetation factors (various perennial plant covers). Additionally, spatial variables (geographic distance) correlated with diazotrophic community variation, suggesting an interplay of environmental variables and spatial distance. The diazotrophic communities appeared to be resilient to elevated nutrient levels, as 2–4 years of chronic N and P additions had little effect on the community composition. However, it remains to be seen, whether changes in the community composition occur after exposure to long-term, chronic fertilization regimes. 

The value of large‐scale collaborations for solving complex problems is widely recognized, but many barriers hinder meaningful authorship for all on the resulting multi‐author publications. Because many professional benefits arise from authorship, much of the literature on this topic has focused on cheating, conflict and effort documentation. However, approaches specifically recognizing and creatively overcoming barriers to meaningful authorship have received little attention.

We have developed an inclusive authorship approach arising from 15 years of experience coordinating the publication of over 100 papers arising from a long‐term, international collaboration of hundreds of scientists.

This method of sharing a paper initially as a storyboard with clear expectations, assignments and deadlines fosters communication and creates unambiguous opportunities for all authors to contribute intellectually. By documenting contributions through this multi‐step process, this approach ensures meaningful engagement by each author listed on a publication.

The perception that co‐authors on large authorship publications have not meaningfully contributed underlies widespread institutional bias against multi‐authored papers, disincentivizing large collaborations despite their widely recognized value for advancing knowledge. Our approach identifies and overcomes key barriers to meaningful contributions, protecting the value of authorship even on massively multi‐authored publications.