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There is increasing interest in measuring ecological stability to understand how communities and ecosystems respond to broad‐scale global changes. One of the most common approaches is to quantify the variation through time in community or ecosystem aggregate attributes (e.g. total biomass), referred to as aggregate variability. It is now widely recognized that aggregate variability represents only one aspect of communities and ecosystems, and compositional variability, the changes in the relative frequency of species in an assemblage, is equally important. Recent contributions have also begun to explore ecological stability at regional spatial scales, where interconnected local communities form metacommunities, a key concept in managing complex landscapes. However, the conceptual frameworks and measures of ecological stability in space have only focused on aggregate variability, leaving a conceptual gap. Here, we address this gap with a novel framework for quantifying the aggregate and compositional variability of communities and ecosystems through space and time. We demonstrate that the compositional variability of a metacommunity depends on the degree of spatial synchrony in compositional trajectories among local communities. We then provide a conceptual framework in which compositional variability of 1) the metacommunity through time and 2) among local communities combine into four archetype scenarios: spatial stasis (low/low), spatial synchrony (high/low), spatial asynchrony (high/high) and spatial compensation (low/high). We illustrate this framework based on numerical examples and a case study of a macroalgal metacommunity in which low spatial synchrony reduced variability in aggregate biomass at the metacommunity scale, while masking high spatial synchrony in compositional trajectories among local communities. Finally, we discuss the role of dispersal, environmental heterogeneity, species interactions and suggest future avenues. We believe this framework will be helpful for considering both aspects of variability simultaneously, which is important to better understand ecological stability in natural and complex landscapes in response to environmental changes. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Because natural ecosystems are complex, it is difficult to predict how their variability scales across space and levels of organization. The species‐insurance hypothesis predicts that asynchronous dynamics among species should reduce variability when biomass is aggregated either from local species populations to local multispecies communities, or from metapopulations to metacommunities. Similarly, the spatial‐insurance hypothesis predicts that asynchronous spatial dynamics among either local populations or local communities should stabilize metapopulation biomass and metacommunity biomass, respectively. In combination, both species and spatial insurance reduce variation in metacommunity biomass over time, yet these insurances are rarely considered together in natural systems. We partitioned the extent that species insurance and spatial insurance reduced the annual variation in macroalgal biomass in a southern California kelp forest. We quantified variability and synchrony at two levels of organization (population and community) and two spatial scales (local plots and region) and quantified the strength of species and spatial insurance by comparing observed variability and synchrony in aggregate biomass to null models of independent species or spatial dynamics based on cyclic‐shift permutation. Spatial insurance was weak, presumably because large‐scale oceanographic processes in the study region led to high spatial synchrony at both population‐ and community‐level biomass. Species insurance was stronger due to asynchronous dynamics among the metapopulations of a few common species. In particular, a regional decline in the dominant understory kelp species Pterygophora californica was compensated for by the rise of three subdominant species. These compensatory dynamics were associated with positive values of the Pacific Decadal Oscillation, indicating that differential species tolerances to warmer temperature and nutrient‐poor conditions may underlie species insurance in this system. Our results illustrate how species insurance can stabilize aggregate community properties in natural ecosystems where environmental conditions vary over broad spatial scales. [ABSTRACT FROM AUTHOR]