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Identifying the factors that destabilize communities is critical for predicting and mitigating the ecological impacts of environmental change. Although theory has shown that local ecosystem size and regional dispersal can determine biodiversity, less is known about the direct and indirect effects of these factors on community stability. Here we show that multitrophic community instability of invertebrates and fishes in coastal ponds is negatively related to local pond size and positively related to distance to the ocean, a proxy for dispersal limitation. Importantly, the effects of pond size and distance on instability were direct rather than indirectly mediated by species richness. This suggests that the diversity-stability relationship is an epiphenomenon whose resolution is neither necessary nor sufficient to understand the stability of these multitrophic communities. Instead, well-established and easily measured local and regional factors historically linked to species richness can be used to predict multitrophic community stability in a variable world., (© 2020 by the Ecological Society of America.)

Understanding how biodiversity influences ecosystem functioning is one of the central goals of modern ecology. The early and often acrimonious debates about the relationship between biodiversity and ecosystem functioning were largely resolved following the advent of a statistical partitioning scheme that decomposed the net effect of biodiversity on ecosystem functioning into a "selection" effect and a "complementarity" effect. Here we show that both the biodiversity effect and its statistical decomposition into selection and complementarity are fundamentally flawed because these methods use a naïve null expectation based on neutrality, likely leading to an overestimate of the net biodiversity effect, and because they fail to account for the nonlinear abundance-ecosystem-functioning relationships widely observed in nature. Furthermore, under nonlinearity no such statistical scheme can be devised to partition the biodiversity effect. We also present an alternative approach that provides a more reasonable starting point for estimating biodiversity effects. Overall, our results suggest that all studies conducted since the early 1990s are likely to have overestimated the positive effects of biodiversity on ecosystem functioning., (© 2019 by the Ecological Society of America.)

Although it is well established that the microbial communities inhabiting corals perform key functions that promote the health and persistence of their hosts, little is known about their spatial structure and temporal stability. We examined the natural variability of microbial communities associated with six Caribbean coral species from three genera at four reef sites over one year. We identified differences in microbial community composition between coral genera and species that persisted across space and time, suggesting that local host identity likely plays a dominant role in structuring the microbiome. However, we found that microbial community dissimilarity increased with geographical distance, which indicates that regional processes such as dispersal limitation and spatiotemporal environmental heterogeneity also influence microbial community composition. In addition, network analysis revealed that the strength of host identity varied across coral host genera, with species from the genus Acropora having the most influence over their microbial community. Overall, our results demonstrate that despite high levels of microbial diversity, coral species are characterized by signature microbiomes that are stable in both space and time.

The persistence of mutualisms in host-microbial - or holobiont - systems is difficult to explain because microbial mutualists, who bear the costs of providing benefits to their host, are always prone to being competitively displaced by non-mutualist 'cheater' species. This disruptive effect of competition is expected to be particularly strong when the benefits provided by the mutualists entail costs such as reduced competitive ability. Using a metacommunity model, we show that competition between multiple cheaters within the host's microbiome, when combined with the spatial structure of host-microbial interactions, can have a constructive rather than a disruptive effect by allowing the emergence and maintenance of mutualistic microorganisms within the host. These results indicate that many of the microorganisms inhabiting a host's microbiome, including those that would otherwise be considered opportunistic or even potential pathogens, play a cryptic yet critical role in promoting the health and persistence of the holobiont across spatial scales., (© 2014 John Wiley & Sons Ltd/CNRS.)

Although positive species interactions are ubiquitous in nature, theory has generally focused on the role of negative interactions to explain patterns of species diversity. Here, we incorporate recruitment facilitation, a positive interaction prevalent in marine and terrestrial systems, into a metacommunity framework to assess how the interplay between colonisation, competition and facilitation mediates coexistence. We show that when subordinate species facilitate the recruitment of dominant species, multi-species metacommunities can persist stably even if the colonisation rate of the dominant species is greater than that of the subordinate species. In addition, recruitment facilitation can buffer population growth from changes in colonisation rates, and thus explain the paradoxical mismatch between patterns of abundance and recruitment in marine systems. Overall, our results demonstrate that recruitment facilitation can have profound effects on the assembly, dissolution and regulation of metacommunities by mediating the relative influence of local and regional processes on population abundance and species diversity., (2011 Blackwell Publishing Ltd/CNRS.)

Clark et al. (2019) sought to extend the Loreau–Hector partitioning scheme by showing how to estimate selection and complementarity effects from an incomplete sample of species. We demonstrate that their approach suffers from serious conceptual and mathematical errors. Instead of finding unbiased estimators for a finite population, they inserted ad hoc correction factors into unbiased parameter estimators for an infinite population without any mathematical justification in order to force the sample estimators of an infinite population to converge to the true finite population parameter values as sample size n approached population size N. In doing so, they confused the unbiasedness of a sample estimator with its equivalence to the true population parameter value when n=N.Additionally, we show that their estimators of complementarity, selection and the net biodiversity effect are incorrect. We then derive the correct unbiased estimators but caution that, contrary to what Clark et al. claim, these quantities will not approximate the corresponding population parameters without significant repeated random sampling, something that would likely be unfeasible in most if not all biodiversity experiments.Clark et al. also state that their method can be used to compare distinct experiments characterized by different species and diversity levels, or extrapolate from biodiversity experiments to natural systems. This is incorrect because relative yields are not a property of individual species like monoculture yields but an emergent and specific feature of an experimental community. As such, two experimental communities, even when overlapping significantly in species, are incommensurable for the purpose of predicting relative yields. In other words, different experimental communities are not equivalent to different samples taken from the same statistical population.Finally, Clark et al. incorrectly claim that both the original Loreau–Hector partitioning scheme and their extension work for any baseline despite the fact that recent research has shown that a nonlinear relationship between monoculture density and ecosystem functioning will likely inflate the net biodiversity effect in plant systems, and will always lead to spurious measurements of complementarity and selection. [ABSTRACT FROM AUTHOR]