Increasing community size and connectance can increase stability in competitive communities

Interconnection between density-regulation and stability in competitive ecological network

In natural ecosystems, species can be characterized by the nonlinear density-dependent self-regulation of their growth profile. Species of many taxa show a substantial density-dependent reduction for low population size. Nevertheless, many show the opposite trend; density regulation is minimal for small populations and increases significantly when the population size is near the carrying capacity. The theta-logistic growth equation can portray the intraspecific density regulation in the growth profile, theta being the density regulation parameter. In this study, we examine the role of these different growth profiles on the stability of a competitive ecological community with the help of a mathematical model of competitive species interactions. This manuscript deals with the random matrix theory to understand the stability of the classical theta-logistic models of competitive interactions. Our results suggest that having more species with strong density dependence, which self-regulate at low densities, leads to more stable communities. With this, stability also depends on the complexity of the ecological network. Species network connectance (link density) shows a consistent trend of increasing stability, whereas community size (species richness) shows a context-dependent effect. We also interpret our results from the aspect of two different life history strategies: r and K-selection. Our results show that the stability of a competitive network increases with the fraction of r-selected species in the community. Our result is robust, irrespective of different network architectures.

Dual species interaction and ecological community stability

How diverse species coexist in nature remains a challenging issue that is not yet resolved in ecology. The traditional approach to tackling this problem uses an ecological community network comprising various biological interaction links between species, such as predator-prey, mutualism, and competition. However, in nature, the interaction between any species pair is not limited to a singular interaction; instead, various interactions occur mostly in two ways, such as competition/facilitation in plants, mutualism/antagonism in consumer-resource mutualisms, and reciprocal predation. Here, using an ecological community model, I show that such so-called dual interactions play a key role in stabilizing ecological communities. Theory predicts that dual interactions can stabilize ecological communities through the balance of positive and negative effects, which behave as if the interactions disappear. Communities with dual interactions are inherently more stable than a classical random community with multiple types of singular interactions, suggesting that dual interactions are more widespread than expected in nature and help to maintain ecological communities.

Maximal ecological diversity exceeds evolutionary diversity in model ecosystems

Understanding community saturation is fundamental to ecological theory. While investigations of the diversity of evolutionary stable states (ESSs) are widespread, the diversity of communities that have yet to reach an evolutionary endpoint is poorly understood. We use Lotka-Volterra dynamics and trait-based competition to compare the diversity of randomly assembled communities to the diversity of the ESS. We show that, with a large enough founding diversity (whether assembled at once or through sequential invasions), the number of long-time surviving species exceeds that of the ESS. However, the excessive founding diversity required to assemble a saturated community increases rapidly with the dimension of phenotype space. Additionally, traits present in communities resulting from random assembly are more clustered in phenotype space compared to random, although still markedly less ordered than the ESS. By combining theories of random assembly and ESSs we bring a new viewpoint to both the saturation and random assembly literature.

Book Review: On ecological networks and biological invasions

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Biodiversity as insurance: from concept to measurement and application

Biological insurance theory predicts that, in a variable environment, aggregate ecosystem properties will vary less in more diverse communities because declines in the performance or abundance of some species or phenotypes will be offset, at least partly, by smoother declines or increases in others. During the past two decades, ecology has accumulated strong evidence for the stabilising effect of biodiversity on ecosystem functioning. As biological insurance is reaching the stage of a mature theory, it is critical to revisit and clarify its conceptual foundations to guide future developments, applications and measurements. In this review, we first clarify the connections between the insurance and portfolio concepts that have been used in ecology and the economic concepts that inspired them. Doing so points to gaps and mismatches between ecology and economics that could be filled profitably by new theoretical developments and new management applications. Second, we discuss some fundamental issues in biological insurance theory that have remained unnoticed so far and that emerge from some of its recent applications. In particular, we draw a clear distinction between the two effects embedded in biological insurance theory, i.e. the effects of biodiversity on the mean and variability of ecosystem properties. This distinction allows explicit consideration of trade-offs between the mean and stability of ecosystem processes and services. We also review applications of biological insurance theory in ecosystem management. Finally, we provide a synthetic conceptual framework that unifies the various approaches across disciplines, and we suggest new ways in which biological insurance theory could be extended to address new issues in ecology and ecosystem management. Exciting future challenges include linking the effects of biodiversity on ecosystem functioning and stability, incorporating multiple functions and feedbacks, developing new approaches to partition biodiversity effects across scales, extending biological insurance theory to complex interaction networks, and developing new applications to biodiversity and ecosystem management.

Connectance and nestedness as stabilizing factors in response to pulse disturbances in adaptive antagonistic networks

Understanding how network architectures are related to community robustness is essential to investigating the effects of disturbances on biological systems. Regarding the perturbations that are observed in disturbance regimes, frequency and intensity are two main descriptors, specifically for those events with short duration. Here, I used the architecture of 45 real-world weighted bipartite networks to assess whether network size, connectance, and nestedness are related to the effects of pulse disturbances in antagonistic communities. Networks were simulated under five scenarios with different combinations of frequency and intensity of perturbations. The dynamics of resource-consumer interactions followed the adaptive interaction switching behavior, which is the key topological process underlying most of the architectures of antagonistic webs. As opposed to most studies considering the effects of disturbances as species extinctions explicitly, the effects of disturbances here were modeled as changes in the abundance of consumers following immediate reductions in the abundance of resources. Simulations revealed that community robustness to pulse disturbances increased with both connectance and nestedness overall, with no effect of network size. Community networks with highly connected and nested topologies were more robust to disturbances, particularly under high frequency and intensity perturbations. By considering disturbances that are not directly related to species' extinctions, this study provides valuable insights that connectance and nestedness have an important stabilizing role in ecological networks.

Species co-occurrence analysis predicts management outcomes for multiple threats

Mitigating the impacts of global anthropogenic change on species is conservation's greatest challenge. Forecasting the effects of actions to mitigate threats is hampered by incomplete information on species' responses. We develop an approach to predict community restructuring under threat management, which combines models of responses to threats with network analyses of species co-occurrence. We discover that contributions by species to network co-occurrence predict their recovery under reduction of multiple threats. Highly connected species are likely to benefit more from threat management than poorly connected species. Importantly, we show that information from a few species on co-occurrence and expected responses to alternative threat management actions can be used to train a response model for an entire community. We use a unique management dataset for a threatened bird community to validate our predictions and, in doing so, demonstrate positive feedbacks in occurrence and co-occurrence resulting from shared threat management responses during ecosystem recovery.

Predicting ecosystem stability from community composition and biodiversity

As biodiversity is declining at an unprecedented rate, an important current scientific challenge is to understand and predict the consequences of biodiversity loss. Here, we develop a theory that predicts the temporal variability of community biomass from the properties of individual component species in monoculture. Our theory shows that biodiversity stabilises ecosystems through three main mechanisms: (1) asynchrony in species' responses to environmental fluctuations, (2) reduced demographic stochasticity due to overyielding in species mixtures and (3) reduced observation error (including spatial and sampling variability). Parameterised with empirical data from four long-term grassland biodiversity experiments, our prediction explained 22-75% of the observed variability, and captured much of the effect of species richness. Richness stabilised communities mainly by increasing community biomass and reducing the strength of demographic stochasticity. Our approach calls for a re-evaluation of the mechanisms explaining the effects of biodiversity on ecosystem stability.