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Understanding stability across ecological hierarchies is critical for landscape management in a changing world. Recent studies showed that synchrony among lower‐level components is key to scaling temporal stability across two hierarchical levels, whether spatial or organizational. But an extended framework that integrates both spatial scale and organizational level simultaneously is required to clarify the sources of ecosystem stability at large scales. However, such an extension is far from trivial when taking into account the spatial heterogeneities in real‐world ecosystems. In this paper, we develop a partitioning framework that bridges variability and synchrony measures across spatial scales and organizational levels in heterogeneous metacommunities. In this framework, metacommunity variability is expressed as the product of local‐scale population variability and two synchrony indices that capture the temporal coherence across species and space, respectively. We develop an R function ‘var.partition’ and apply it to five types of desert plant communities to illustrate our framework and test how diversity shapes synchrony and variability at different hierarchical levels. As the observation scale increased from local populations to metacommunities, the temporal variability of plant productivity was reduced mainly by factors that decreased species synchrony. Species synchrony decreased from local to regional scales, and spatial synchrony decreased from species to community levels. Local and regional species diversity were key factors that reduced species synchrony at the two scales. Moreover, beta diversity contributed to decreasing spatial synchrony among communities. We conclude that our new framework offers a valuable toolbox for future empirical studies to disentangle the mechanisms and pathways by which ecological factors influence stability at large scales.

Rapid, extensive, and ongoing environmental change increasingly demands that humans intervene in ecosystems to maintain or restore ecosystem services and biodiversity. At the same time, the basic principles and tenets of restoration ecology and conservation biology are being debated and reshaped. Escalating global change is resulting in widespread no-analogue environments and novel ecosystems that render traditional goals unachievable. Policymakers and the general public, however, have embraced restoration without an understanding of its limitations, which has led to perverse policy outcomes. Therefore, a new ecology, free of pre- and misconceptions and directed toward meaningful interventions, is needed. Interventions include altering the biotic and abiotic structures and processes within ecosystems and changing social and policy settings. Interventions can be aimed at leverage points, both within ecosystems and in the broader social system—particularly, feedback loops that either maintain a particular state or precipitate a rapid change from one state to another.

Biodiversity has widely been documented to enhance local community stability but whether such stabilizing effects of biodiversity extend to broader scales remains elusive. Here, we investigated the relationships between biodiversity and community stability in natural plant communities from quadrat (1 m 2 ) to plot (400 m 2 ) and regional (5−214 km 2 ) scales and across broad climatic conditions, using an extensive plant community dataset from the National Ecological Observatory Network. We found that plant diversity provided consistent stabilizing effects on total community abundance across three nested spatial scales and climatic gradients. The strength of the stabilizing effects of biodiversity increased modestly with spatial scale and decreased as precipitation seasonality increased. Our findings illustrate the generality of diversity–stability theory across scales and climatic gradients, which provides a robust framework for understanding ecosystem responses to biodiversity and climate changes. Analysing >6,000 plant species from plots across the US National Ecological Observatory Network (NEON), the authors show that plant diversity consistently stabilizes community abundance across spatial scales and broad ecoclimatic domains, with the strength of the stabilizing effect increasing with scale.

• Demographic studies measure drivers of plant fecundity including seed production and survival, but few address both abiotic and biotic drivers of germination such as variation in climate among sites, population density, maternal plants, seed type and fungal pathogen abundance. • We examined germination and microbial communities of seeds of Danthonia californica, which are either chasmogamous (external, wind-pollinated) or cleistogamous (internal, self-fertilized) and Festuca roemeri, which are solely chasmogamous. Seed populations were sourced across environmental gradients. We tested germination and used high-throughput sequencing to characterize seed fungal community structure. • For F. roemeri, maternal plants significantly influenced germination as did climate and pathogens; germination increased from wetter, cooler sites. For D. californica, the main drivers of germination were maternal plant, seed type and pathogens; on average, more chasmogamous seeds germinated. Fungal communities depended largely on seed type, with fewer fungi associated with cleistogamous seeds, but the communities also depended on site factors such as vapor pressure deficit, plant density and whether the seeds had germinated. • Putative pathogens that were negatively correlated with germination were more abundant for both D. californica and F. roemeri chasmogamous seeds than D. californica cleistogamous seeds. In D. californica, cleistogamous and chasmogamous seeds contain vastly different fungal communities.

Understanding how biotic mechanisms confer stability in variable environments is a fundamental quest in ecology, and one that is becoming increasingly urgent with global change. Several mechanisms, notably a portfolio effect associated with species richness, compensatory dynamics generated by negative species covariance and selection for stable dominant species populations can increase the stability of the overall community. While the importance of these mechanisms is debated, few studies have contrasted their importance in an environmental context. We analyzed nine long-term data sets of grassland species composition to investigate how two key environmental factors, precipitation amount and variability, may directly influence community stability and how they may indirectly influence stability via biotic mechanisms. We found that the importance of stability mechanisms varied along the environmental gradient: strong negative species covariance occurred in sites characterized by high precipitation variability, whereas portfolio effects increased in sites with high mean annual precipitation. Instead of questioning whether compensatory dynamics are important in nature, our findings suggest that debate should widen to include several stability mechanisms and how these mechanisms vary in importance across environmental gradients.

Climate gradients shape spatial variation in the richness and composition of plant communities. Given future predicted changes in climate means and variability, and likely regional variation in the magnitudes of these changes, it is important to determine how temporal variation in climate influences temporal variation in plant community structure. Here, we evaluated how species richness, turnover, and composition of grassland plant communities responded to interannual variation in precipitation by synthesizing long-term data from grasslands across the United States. We found that mean annual precipitation (MAP) was a positive predictor of species richness across sites, but a positive temporal relationship between annual precipitation and richness was only evident within two sites with low MAP. We also found higher average rates of species turnover in dry sites that in turn had a high proportion of annual species, although interannual rates of species turnover were surprisingly high across all locations. Annual species were less abundant than perennial species at nearly all sites, and our analysis showed that the probability of a species being lost or gained from one year to the next increased with decreasing species abundance. Bray-Curtis dissimilarity from one year to the next, a measure of species composition change that is influenced mainly by abundant species, was insensitive to precipitation at all sites. These results suggest that the richness and turnover patterns we observed were driven primarily by rare species, which comprise the majority of the local species pools at these grassland sites. These findings are consistent with the idea that short-lived and less abundant species are more sensitive to interannual climate variability than longer-lived and more abundant species. We conclude that, among grassland ecosystems, xeric grasslands are likely to exhibit the greatest responsiveness of community composition (richness and turnover) to predicted future increases in interannual precipitation variability. Over the long term, species composition may shift to reflect spatial patterns of mean precipitation; however, perennial-dominated systems will be buffered against rising interannual variation, while systems that have a large number of rare, annual species will show the greatest temporal variability in species composition in response to rising interannual variability in precipitation.

Univariate and multivariate methods are commonly used to explore the spatial and temporal dynamics of ecological communities, but each has limitations, including oversimplification or ion of communities. Rank abundance curves (RACs) potentially integrate these existing methodologies by detailing species‐level community changes. Here, we had three goals: first, to simplify analysis of community dynamics by developing a coordinated set of R functions, and second, to demystify the relationships among univariate, multivariate, and RACs measures, and examine how each is influenced by the community parameters as well as data collection methods. We developed new functions for studying temporal changes and spatial differences in RACs in an update to the R package library(“codyn”), alongside other new functions to calculate univariate and multivariate measures of community dynamics. We also developed a new approach to studying changes in the shape of RAC curves. The R package update presented here increases the accessibility of univariate and multivariate measures of community change over time and difference over space. Next, we use simulated and real data to assess the RAC and multivariate measures that are output from our new functions, studying (1) if they are influenced by species richness and evenness, temporal turnover, and spatial variability and (2) how the measures are related to each other. Lastly, we explore the use of the measures with an example from a long‐term nutrient addition experiment. We find that the RAC and multivariate measures are not sensitive to species richness and evenness and that all the measures detail unique aspects of temporal change or spatial differences. We also find that species reordering is the strongest correlate of a multivariate measure of compositional change and explains most community change observed in long‐term nutrient addition experiment. Overall, we show that species reordering is potentially an understudied determinant of community changes over time or differences between treatments. The functions developed here should enhance the use of RACs to further explore the dynamics of ecological communities.

Understanding why some species are common and others are rare is a central question in ecology, and is critical for developing conservation strategies under global change. Rare species are typically considered to be more prone to extinction—but the fact they are rare can impede a general understanding of rarity vs. abundance. Here we develop and empirically test a framework to predict species abundances and stability using mechanisms governing population dynamics. Our results demonstrate that coexisting species with similar abundances can be shaped by different mechanisms (specifically, higher growth rates when rare vs. weaker negative density-dependence). Further, these dynamics influence population stability: species with higher intrinsic growth rates but stronger negative density-dependence were more stable and less sensitive to climate variability, regardless of abundance. This suggests that underlying mechanisms governing population dynamics, in addition to population size, may be critical indicators of population stability in an increasingly variable world. Protection of rare species requires advanced understanding of the reasons for their rarity. Here, Hallett et al. show that potential growth rate and density dependence together predict rarity vs. abundance, and that the stability of species of similar sizes depends on the relative strength of these two mechanisms.

Understanding the factors governing ecological stability in variable environments is a central focus of ecology. Functional diversity can stabilize ecosystem function over time if one group of species compensates for an environmentally driven decline in another. Although intuitively appealing, evidence for this pattern is mixed. We hypothesized that diverse functional responses to rainfall will increase the stability of vegetation cover and biomass across rainfall conditions, but that this effect depends on land-use legacies that maintain functional diversity. We experimentally manipulated grazing in a California grassland to create land-use legacies of low and moderate grazing, across which we implemented rainout shelters and irrigation to create dry and wet conditions over 3 years. We found that the stability of the vegetation cover was greatly elevated and the stability of the biomass was slightly elevated across rainfall conditions in areas with histories of moderate grazing. Initial functional diversity—both in the seed bank and aboveground—was also greater in areas that had been moderately grazed. Rainfall conditions in conjunction with this grazing legacy led to different functional diversity patterns over time. Wet conditions led to rapid declines in functional diversity and a convergence on resource-acquisitive traits. In contrast, consecutively dry conditions maintained but did not increase functional diversity over time. As a result, grazing practices and environmental conditions that decrease functional diversity may be associated with lasting effects on the response of ecosystem functions to drought. Our results demonstrate that theorized relationships between diversity and stability are applicable and important in the context of working grazed landscapes.

Understanding the mechanisms governing ecological stability—why a property such as primary productivity is stable in some communities and variable in others—has long been a focus of ecology. Compensatory dynamics, in which anti‐synchronous fluctuations between populations buffer against fluctuations at the community level, are a key theoretical mechanism of stability. Classically, compensatory dynamics have been quantified using a variance ratio approach that compares the ratio between community variance and aggregate population variance, such that a lower ratio indicates compensation and a higher ratio indicates synchrony among species fluctuations. However, population dynamics may be influenced by different drivers that operate on different timescales, and evidence from aquatic systems indicates that communities can be compensatory on some timescales and synchronous on others. The variance ratio and related metrics cannot reflect this timescale specificity, yet have remained popular, especially in terrestrial systems. Here, we develop a timescale‐specific variance ratio approach that formally decomposes the classical variance ratio according to the timescales of distinct contributions. The approach is implemented in a new R package, called tsvr, that accompanies this paper. We apply our approach to a long‐term, multisite grassland community dataset. Our approach demonstrates that the degree of compensation vs. synchrony in community dynamics can vary by timescale. Across sites, population variability was typically greater over longer compared to shorter timescales. At some sites, minimal timescale specificity in compensatory dynamics translated this pattern of population variability into a similar pattern of greater community variability on longer compared to shorter timescales. But at other sites, differentially stronger compensatory dynamics at longer compared to shorter timescales produced lower‐than‐expected community variability on longer timescales. Within every site, there were plots that exhibited shifts in the strength of compensation between timescales. Our results highlight that compensatory vs. synchronous dynamics are intrinsically timescale‐dependent concepts, and our timescale‐specific variance ratio provides a metric to quantify timescale specificity and relate it back to the classic variance ratio.