Stability in real food webs: weak links in long loops

Theory of invasion extinction dynamics in minimal food webs

When food webs are exposed to species invasion, secondary extinction cascades may be set off. Although much work has gone into characterizing the structure of food webs, systematic predictions on their evolutionary dynamics are still scarce. Here we present a theoretical framework that predicts extinctions in terms of an alternating sequence of two basic processes: resource depletion by or competitive exclusion between consumers. We first propose a conceptual invasion extinction model (IEM) involving random fitness coefficients. We bolster this IEM by an analytical, recursive procedure for calculating idealized extinction cascades after any species addition and simulate the long-time evolution. Our procedure describes minimal food webs where each species interacts with only a single resource through the generalized Lotka-Volterra equations. For such food webs ex- tinction cascades are determined uniquely and the system always relaxes to a stable steady state. The dynamics and scale invariant species life time resemble the behavior of the IEM, and correctly predict an upper limit for trophic levels as observed in the field.

Stability lies in flowers: Plant diversification mediating shifts in arthropod food webs

Arthropod community composition in agricultural landscapes is dependent on habitat characteristics, such as plant composition, landscape homogeneity and the presence of key resources, which are usually absent in monocultures. Manipulating agroecosystems through the insertion of in-field floral resources is a useful technique to reduce the deleterious effects of habitat simplification. Food web analysis can clarify how the community reacts to the presence of floral resources which favour ecosystem services such as biological control of pest species. Here, we reported quantitative and qualitative alterations in arthropod food web complexity due to the presence of floral resources from the Mexican marigold (Tagetes erecta L.) in a field scale lettuce community network. The presence of marigold flowers in the field successfully increased richness, body size, and the numerical and biomass abundance of natural enemies in the lettuce arthropod community, which affected the number of links, vulnerability, generality, omnivory rate and food chain length in the community, which are key factors for the stability of relationships between species. Our results reinforce the notion that diversification through insertion of floral resources may assist in preventing pest outbreaks in agroecosystems. This community approach to arthropod interactions in agricultural landscapes can be used in the future to predict the effect of different management practices in the food web to contribute with a more sustainable management of arthropod pest species.

Existence and construction of large stable food webs

Ecological diversity is ubiquitous despite the restrictions imposed by competitive exclusion and apparent competition. To explain the observed richness of species in a given habitat, food-web theory has explored nonlinear functional responses, self-interaction, or spatial structure and dispersal-model ingredients that have proven to promote stability and diversity. We return instead here to classical Lotka-Volterra equations, where species-species interaction is characterized by a simple product and spatial restrictions are ignored. We quantify how this idealization imposes constraints on coexistence and diversity for many species. To this end, we introduce the concept of free and controlled species and use this to demonstrate how stable food webs can be constructed by the sequential addition of species. The resulting food webs can reach dozens of species and generally yield nonrandom degree distributions in accordance with the constraints imposed through the assembly process. Our model thus serves as a formal starting point for the study of sustainable interaction patterns between species.

Energy Flux: The Link between Multitrophic Biodiversity and Ecosystem Functioning

Relating biodiversity to ecosystem functioning in natural communities has become a paramount challenge as links between trophic complexity and multiple ecosystem functions become increasingly apparent. Yet, there is still no generalised approach to address such complexity in biodiversity-ecosystem functioning (BEF) studies. Energy flux dynamics in ecological networks provide the theoretical underpinning of multitrophic BEF relationships. Accordingly, we propose the quantification of energy fluxes in food webs as a powerful, universal tool for understanding ecosystem functioning in multitrophic systems spanning different ecological scales. Although the concept of energy flux in food webs is not novel, its application to BEF research remains virtually untapped, providing a framework to foster new discoveries into the determinants of ecosystem functioning in complex systems.

Biodiversity and the Ecology of Emerging Infectious Diseases

The question of how biodiversity influences the emergence of infectious diseases is the subject of ongoing research. A set of nonlinear differential equations is been used to explore the interactions between ecology and epidemiology. The model allows for frequency-dependent transmission of infection within host species, and density-dependent transmission between species, via the environment or a vector. Three examples are discussed. It is shown that removing a pathogen may increase a consumer population, decreasing its resource. It is then shown that the presence of a pathogen could enable a predator and a prey species to coexist. Finally the dilution effect, by which increasing biodiversity reduces the transmission of an infectious disease, is investigated.

Warming alters the energetic structure and function but not resilience of soil food webs

Climate warming is predicted to alter the structure, stability, and functioning of food webs1-5. Yet, despite the importance of soil food webs for energy and nutrient turnover in terrestrial ecosystems, warming effects on these food webs-particularly in combination with other global change drivers-are largely unknown. Here, we present results from two complementary field experiments testing the interactive effects of warming with forest canopy disturbance and drought on energy fluxes in boreal-temperate ecotonal forest soil food webs. The first experiment applied a simultaneous above- and belowground warming treatment (ambient, +1.7°C, +3.4°C) to closed canopy and recently clear-cut forest, simulating common forest disturbance6. The second experiment crossed warming with a summer drought treatment (-40% rainfall) in the clear-cut habitats. We show that warming reduces energy fluxes to microbes, while forest canopy disturbance and drought facilitates warming-induced increases in energy flux to higher trophic levels and exacerbates reductions in energy flux to microbes, respectively. Contrary to expectations, we find no change in whole-network resilience to perturbations, but significant losses of ecosystem functioning. Warming thus interacts with forest disturbance and drought, shaping the energetic structure of soil food webs and threatening the provisioning of multiple ecosystem functions in boreal-temperate ecotonal forests.

Modeling Microbial Communities: A Call for Collaboration between Experimentalists and Theorists

With our growing understanding of the impact of microbial communities, understanding how such communities function has become a priority. The influence of microbial communities is widespread. Human-associated microbiota impacts health, environmental microbes determine ecosystem sustainability, and microbe-driven industrial processes are expanding. This broad range of applications has led to a wide range of approaches to analyze and describe microbial communities. In particular, theoretical work based on mathematical modeling has been a steady source of inspiration for explaining and predicting microbial community processes. Here, we survey some of the modeling approaches used in different contexts. We promote classifying different approaches using a unified platform, and encourage cataloging the findings in a database. We believe that the synergy emerging from a coherent collection facilitates a better understanding of important processes that determine microbial community functions. We emphasize the importance of close collaboration between theoreticians and experimentalists in formulating, classifying, and improving models of microbial communities.

Persistence of a stage-structured food-web

Contrary to a theoretical prediction, natural communities comprise many interacting species, thereby developing complex ecosystems. Earlier theoretical studies assumed that each component species within an ecological network has a simple life history, despite the fact that the interaction partners of many species, such as their predators and resources, change during the developmental stages. This poses an open question on the effect of life history complexity on the dynamics of communities. Here using a food web model, I showed that species with a stage-structured life cycle greatly changes the relationship between community complexity and persistence. Without stage-structured species, an increase in species diversity and interaction links decreases the community persistence, whereas in the presence of stage-structured species, community complexity can increase the community persistence. Therefore, life history complexity may be a key element of biodiversity that is self-maintaining.

Spatial effects in meta-foodwebs

In ecology it is widely recognised that many landscapes comprise a network of discrete patches of habitat. The species that inhabit the patches interact with each other through a foodweb, the network of feeding interactions. The meta-foodweb model proposed by Pillai et al. combines the feeding relationships at each patch with the dispersal of species between patches, such that the whole system is represented by a network of networks. Previous work on meta-foodwebs has focussed on landscape networks that do not have an explicit spatial embedding, but in real landscapes the patches are usually distributed in space. Here we compare the dispersal of a meta-foodweb on Erdős-Rényi networks, that do not have a spatial embedding, and random geometric networks, that do have a spatial embedding. We found that local structure and large network distances in spatially embedded networks, lead to meso-scale patterns of patch occupation by both specialist and omnivorous species. In particular, we found that spatial separations make the coexistence of competing species more likely. Our results highlight the effects of spatial embeddings for meta-foodweb models, and the need for new analytical approaches to them.

Detection of time delays and directional interactions based on time series from complex dynamical systems

Data-based and model-free accurate identification of intrinsic time delays and directional interactions is an extremely challenging problem in complex dynamical systems and their networks reconstruction. A model-free method with new scores is proposed to be generally capable of detecting single, multiple, and distributed time delays. The method is applicable not only to mutually interacting dynamical variables but also to self-interacting variables in a time-delayed feedback loop. Validation of the method is carried out using physical, biological, and ecological models and real data sets. Especially, applying the method to air pollution data and hospital admission records of cardiovascular diseases in Hong Kong reveals the major air pollutants as a cause of the diseases and, more importantly, it uncovers a hidden time delay (about 30-40 days) in the causal influence that previous studies failed to detect. The proposed method is expected to be universally applicable to ascertaining and quantifying subtle interactions (e.g., causation) in complex systems arising from a broad range of disciplines.

Degree heterogeneity and stability of ecological networks

A classic measure of ecological stability describes the tendency of a community to return to equilibrium after small perturbations. While many advances show how the network architecture of these communities severely constrains such tendencies, one of the most fundamental properties of network structure, i.e. degree heterogeneity-the variability of the number of links associated with each species, deserves further study. Here we show that the effects of degree heterogeneity on stability vary with different types of interspecific interactions. Degree heterogeneity consistently destabilizes ecological networks with both competitive and mutualistic interactions, while its effects on networks of predator-prey interactions such as food webs depend on prey contiguity, i.e. the extent to which the species consume an unbroken sequence of prey in community niche space. Increasing degree heterogeneity tends to stabilize food webs except those with the highest prey contiguity. These findings help explain why food webs are highly but not completely interval and, more broadly, deepen our understanding of the stability of complex ecological networks.

Compositional Stability of the Bacterial Community in a Climate-Sensitive Sub-Arctic Peatland

The climate sensitivity of microbe-mediated soil processes such as carbon and nitrogen cycling offers an interesting case for evaluating the corresponding sensitivity of microbial community composition to environmental change. Better understanding of the degree of linkage between functional and compositional stability would contribute to ongoing efforts to build mechanistic models aiming at predicting rates of microbe-mediated processes. We used an amplicon sequencing approach to test if previously observed large effects of experimental soil warming on C and N cycle fluxes (50–100% increases) in a sub-arctic Sphagnum peatland were reflected in changes in the composition of the soil bacterial community. We found that treatments that previously induced changes to fluxes did not associate with changes in the phylogenetic composition of the soil bacterial community. For both DNA- and RNA-based analyses, variation in bacterial communities could be explained by the hierarchy: spatial variation (12–15% of variance explained) > temporal variation (7–11%) > climate treatment (4–9%). We conclude that the bacterial community in this environment is stable under changing conditions, despite the previously observed sensitivity of process rates—evidence that microbe-mediated soil processes can alter without concomitant changes in bacterial communities. We propose that progress in linking soil microbial communities to ecosystem processes can be advanced by further investigating the relative importance of community composition effects versus physico-chemical factors in controlling biogeochemical process rates in different contexts.

How habitat-modifying organisms structure the food web of two coastal ecosystems

The diversity and structure of ecosystems has been found to depend both on trophic interactions in food webs and on other species interactions such as habitat modification and mutualism that form non-trophic interaction networks. However, quantification of the dependencies between these two main interaction networks has remained elusive. In this study, we assessed how habitat-modifying organisms affect basic food web properties by conducting in-depth empirical investigations of two ecosystems: North American temperate fringing marshes and West African tropical seagrass meadows. Results reveal that habitat-modifying species, through non-trophic facilitation rather than their trophic role, enhance species richness across multiple trophic levels, increase the number of interactions per species (link density), but decrease the realized fraction of all possible links within the food web (connectance). Compared to the trophic role of the most highly connected species, we found this non-trophic effects to be more important for species richness and of more or similar importance for link density and connectance. Our findings demonstrate that food webs can be fundamentally shaped by interactions outside the trophic network, yet intrinsic to the species participating in it. Better integration of non-trophic interactions in food web analyses may therefore strongly contribute to their explanatory and predictive capacity.

Beyond connectedness: why pairwise metrics cannot capture community stability

The connectedness of species in a trophic web has long been a key structural characteristic for both theoreticians and empiricists in their understanding of community stability. In the past decades, there has been a shift from focussing on determining the number of interactions to taking into account their relative strengths. The question is: How do the strengths of the interactions determine the stability of a community? Recently, a metric has been proposed which compares the stability of observed communities in terms of the strength of three‐ and two‐link feedback loops (cycles of interaction strengths). However, it has also been suggested that we do not need to go beyond the pairwise structure of interactions to capture stability. Here, we directly compare the performance of the feedback and pairwise metrics. Using observed food‐web structures, we show that the pairwise metric does not work as a comparator of stability and is many orders of magnitude away from the actual stability values. We argue that metrics based on pairwise‐strength information cannot capture the complex organization of strong and weak links in a community, which is essential for system stability.

No complexity-stability relationship in empirical ecosystems

Understanding the mechanisms responsible for stability and persistence of ecosystems is one of the greatest challenges in ecology. Robert May showed that, contrary to intuition, complex randomly built ecosystems are less likely to be stable than simpler ones. Few attempts have been tried to test May's prediction empirically, and we still ignore what is the actual complexity–stability relationship in natural ecosystems. Here we perform a stability analysis of 116 quantitative food webs sampled worldwide. We find that classic descriptors of complexity (species richness, connectance and interaction strength) are not associated with stability in empirical food webs. Further analysis reveals that a correlation between the effects of predators on prey and those of prey on predators, combined with a high frequency of weak interactions, stabilize food web dynamics relative to the random expectation. We conclude that empirical food webs have several non-random properties contributing to the absence of a complexity–stability relationship.

A long-standing ecological hypothesis is that complexity should decrease stability in food webs. Here, Jacquet and colleagues analyse over 100 real-world food webs and show that complexity does not decrease stability, but that a high frequency of weak species interactions stabilizes complex food webs.

Stability and complexity in model meta-ecosystems

The diversity of life and its organization in networks of interacting species has been a long-standing theoretical puzzle for ecologists. Ever since May's provocative paper challenging whether 'large complex systems [are] stable' various hypotheses have been proposed to explain when stability should be the rule, not the exception. Spatial dynamics may be stabilizing and thus explain high community diversity, yet existing theory on spatial stabilization is limited, preventing comparisons of the role of dispersal relative to species interactions. Here we incorporate dispersal of organisms and material into stability-complexity theory. We find that stability criteria from classic theory are relaxed in direct proportion to the number of ecologically distinct patches in the meta-ecosystem. Further, we find the stabilizing effect of dispersal is maximal at intermediate intensity. Our results highlight how biodiversity can be vulnerable to factors, such as landscape fragmentation and habitat loss, that isolate local communities.

Environmental variability uncovers disruptive effects of species' interactions on population dynamics

How species respond to changes in environmental variability has been shown for single species, but the question remains whether these results are transferable to species when incorporated in ecological communities. Here, we address this issue by analysing the same species exposed to a range of environmental variabilities when (i) isolated or (ii) embedded in a food web. We find that all species in food webs exposed to temporally uncorrelated environments (white noise) show the same type of dynamics as isolated species, whereas species in food webs exposed to positively autocorrelated environments (red noise) can respond completely differently compared with isolated species. This is owing to species following their equilibrium densities in a positively autocorrelated environment that in turn enables species-species interactions to come into play. Our results give new insights into species' response to environmental variation. They especially highlight the importance of considering both species' interactions and environmental autocorrelation when studying population dynamics in a fluctuating environment.

Food-web complexity, meta-community complexity and community stability

What allows interacting, diverse species to coexist in nature has been a central question in ecology, ever since the theoretical prediction that a complex community should be inherently unstable. Although the role of spatiality in species coexistence has been recognized, its application to more complex systems has been less explored. Here, using a meta-community model of food web, we show that meta-community complexity, measured by the number of local food webs and their connectedness, elicits a self-regulating, negative-feedback mechanism and thus stabilizes food-web dynamics. Moreover, the presence of meta-community complexity can give rise to a positive food-web complexity-stability effect. Spatiality may play a more important role in stabilizing dynamics of complex, real food webs than expected from ecological theory based on the models of simpler food webs.

Evidence for interspecific interactions in the ectoparasite infracommunity of a wild mammal

Background

Co-infection with multiple parasite species is commonly observed in nature and interspecific interactions are likely to occur in parasite infracommunities. Such interactions may affect the distribution of parasites among hosts but also the response of infracommunities to perturbations. However, the response of infracommunities to perturbations has not been well studied experimentally for ectoparasite communities of small mammal hosts.

Methods

In the current study we used experimental perturbations of the ectoparasite infracommunity of sengis from Africa. We suppressed tick recruitment by applying an acaride and monitored the effects on the ectoparasite community.

Results

Our treatment affected the target as well as two non-target species directly. The experimental removal of the dominant tick (Rhipicephalus spp.) resulted in increases in the abundance of chiggers and lice. However, while these effects were short-lived in chiggers, which are questing from the environment, they were long-lasting for lice which spend their entire life-cycle on the host. In addition, the recruitment rates of some ectoparasite species were high and did not always correspond to total burdens observed.

Conclusion

These findings indicate that infracommunity interactions may contribute to patterns of parasite burdens. The divergent responses of species with differing life-history traits suggest that perturbation responses may be affected by parasite life-history and that the ectoparasite infracommunity of sengis may lack resilience to perturbations. The latter observation contrasts with the high resilience reported previously for endoparasite communities and also suggests that anti-parasite treatments can affect the distribution of non-target species.

Electronic supplementary material

The online version of this article (doi:10.1186/s13071-016-1342-7) contains supplementary material, which is available to authorized users.

Predicting the consequences of species loss using size-structured biodiversity approaches

Understanding the consequences of species loss in complex ecological communities is one of the great challenges in current biodiversity research. For a long time, this topic has been addressed by traditional biodiversity experiments. Most of these approaches treat species as trait-free, taxonomic units characterizing communities only by species number without accounting for species traits. However, extinctions do not occur at random as there is a clear correlation between extinction risk and species traits. In this review, we assume that large species will be most threatened by extinction and use novel allometric and size-spectrum concepts that include body mass as a primary species trait at the levels of populations and individuals, respectively, to re-assess three classic debates on the relationships between biodiversity and (i) food-web structural complexity, (ii) community dynamic stability, and (iii) ecosystem functioning. Contrasting current expectations, size-structured approaches suggest that the loss of large species, that typically exploit most resource species, may lead to future food webs that are less interwoven and more structured by chains of interactions and compartments. The disruption of natural body-mass distributions maintaining food-web stability may trigger avalanches of secondary extinctions and strong trophic cascades with expected knock-on effects on the functionality of the ecosystems. Therefore, we argue that it is crucial to take into account body size as a species trait when analysing the consequences of biodiversity loss for natural ecosystems. Applying size-structured approaches provides an integrative ecological concept that enables a better understanding of each species' unique role across communities and the causes and consequences of biodiversity loss.

Eelgrass (Zostera marina) Food Web Structure in Different Environmental Settings

This study compares the structure of eelgrass (Zostera marina L.) meadows and associated food webs in two eelgrass habitats in Denmark, differing in exposure, connection to the open sea, nutrient enrichment and water transparency. Meadow structure strongly reflected the environmental conditions in each habitat. The eutrophicated, protected site had higher biomass of filamentous algae, lower eelgrass biomass and shoot density, longer and narrower leaves, and higher above to below ground biomass ratio compared to the less nutrient-enriched and more exposed site. The faunal community composition and food web structure also differed markedly between sites with the eutrophicated, enclosed site having higher biomass of consumers and less complex food web. These relationships resulted in a column shaped biomass distribution of the consumers at the eutrophicated site whereas the less nutrient-rich site showed a pyramidal biomass distribution of consumers coupled with a more diverse consumer community. The differences in meadow and food web structure of the two seagrass habitats, suggest how physical setting may shape ecosystem response and resilience to anthropogenic pressure. We encourage larger, replicated studies to further disentangle the effects of different environmental variables on seagrass food web structure.

Linking structure and function in food webs: maximization of different ecological functions generates distinct food web structures

Trophic interactions are central to ecosystem functioning, but the link between food web structure and ecosystem functioning remains obscure. Regularities (i.e. consistent patterns) in food web structure suggest the possibility of regularities in ecosystem functioning, which might be used to relate structure to function. We introduce a novel, genetic algorithm approach to simulate food webs with maximized throughput (a proxy for ecosystem functioning) and compare the structure of these simulated food webs to real empirical food webs using common metrics of food web structure. We repeat this analysis using robustness to secondary extinctions (a proxy for ecosystem resilience) instead of throughput to determine the relative contributions of ecosystem functioning and ecosystem resilience to food web structure. Simulated food webs that maximized robustness were similar to real food webs when connectance (i.e. levels of interaction across the food web) was high, but this result did not extend to food webs with low connectance. Simulated food webs that maximized throughput or a combination of throughput and robustness were not similar to any real food webs. Simulated maximum-throughput food webs differed markedly from maximum-robustness food webs, which suggests that maximizing different ecological functions can generate distinct food web structures. Based on our results, food web structure would appear to have a stronger relationship with ecosystem resilience than with ecosystem throughput. Our genetic algorithm approach is general and is well suited to large, realistically complex food webs. Genetic algorithms can incorporate constraints on structure and can generate outputs that can be compared directly to empirical data. Our method can be used to explore a range of maximization or minimization hypotheses, providing new perspectives on the links between structure and function in ecological systems.

Resilience, reactivity and variability: A mathematical comparison of ecological stability measures

In theoretical studies, the most commonly used measure of ecological stability is resilience: ecosystems asymptotic rate of return to equilibrium after a pulse-perturbation -or shock. A complementary notion of growing popularity is reactivity: the strongest initial response to shocks. On the other hand, empirical stability is often quantified as the inverse of temporal variability, directly estimated on data, and reflecting ecosystems response to persistent and erratic environmental disturbances. It is unclear whether and how this empirical measure is related to resilience and reactivity. Here, we establish a connection by introducing two variability-based stability measures belonging to the theoretical realm of resilience and reactivity. We call them intrinsic, stochastic and deterministic invariability; respectively defined as the inverse of the strongest stationary response to white-noise and to single-frequency perturbations. We prove that they predict ecosystems worst response to broad classes of disturbances, including realistic models of environmental fluctuations. We show that they are intermediate measures between resilience and reactivity and that, although defined with respect to persistent perturbations, they can be related to the whole transient regime following a shock, making them more integrative notions than reactivity and resilience. We argue that invariability measures constitute a stepping stone, and discuss the challenges ahead to further unify theoretical and empirical approaches to stability.

A world without parasites: exploring the hidden ecology of infection

Parasites have historically been considered a scourge, deserving of annihilation. Although parasite eradications rank among humanity's greatest achievements, new research is shedding light on the collateral effects of parasite loss. Here, we explore a "world without parasites": a thought experiment for illuminating the ecological roles that parasites play in ecosystems. While there is robust evidence for the effects of parasites on host individuals (eg affecting host vital rates), this exercise highlights how little we know about the influence of parasites on communities and ecosystems (eg altering energy flow through food webs). We present hypotheses for novel, interesting, and general effects of parasites. These hypotheses are largely untested, and should be considered a springboard for future research. While many uncertainties exist, the available evidence suggests that a world without parasites would be very different from the world we know, with effects extending from host individuals to populations, communities, and even ecosystems.

Analytical formulae for computing dominance from species-abundance distributions

The evenness of an ecological community affects ecosystem structure, functioning and stability, and has implications for biodiversity conservation. In uneven communities, most species are rare while a few dominant species drive ecosystem-level properties. In even communities, dominance is lower, with possibly many species playing key ecological roles. The dominance aspect of evenness can be measured as a decreasing function of the proportion of species required to make up a fixed fraction (e.g., half) of individuals in a community. Here we sought general rules about dominance in ecological communities by linking dominance mathematically to the parameters of common theoretical species-abundance distributions (SADs). We found that if a community's SAD was log-series or lognormal, then dominance was almost inevitably high, with fewer than 40% of species required to account for 90% of all individuals. Dominance for communities with an exponential SAD was lower but still typically high, with fewer than 40% of species required to account for 70% of all individuals. In contrast, communities with a gamma SAD only exhibited high dominance when the average species abundance was below a threshold of approximately 100. Furthermore, we showed that exact values of dominance were highly scale-dependent, exhibiting non-linear trends with changing average species abundance. We also applied our formulae to SADs derived from a mechanistic community model to demonstrate how dominance can increase with environmental variance. Overall, our study provides a rigorous basis for theoretical explorations of the dynamics of dominance in ecological communities, and how this affects ecosystem functioning and stability.

Weak Interactions and Instability Cascades

Food web theory states that a weak interactor which is positioned in the food web such that it tends to deflect, or mute, energy away from a potentially oscillating consumer-resource interaction often enhances community persistence and stability. Here we examine how adding other weak interactions (predation/harvesting) on the stabilizing weak interactor alters the stability of food web using a set of well-established food web models/modules. We show that such “weak on weak” interaction chains drive an indirect dynamic cascade that can rapidly ignite a distant consumer-resource oscillator. Nonetheless, we also show that the “weak on weak” interactions are still more stable than the food web without them, and so weak interactions still generally act to stabilize food webs. Rather, these results are best interpreted to say that the degree of the stabilizing effect of a given important weak interaction can be severely compromised by other weak interactions (including weak harvesting).

Food-web stability signals critical transitions in temperate shallow lakes

A principal aim of ecologists is to identify critical levels of environmental change beyond which ecosystems undergo radical shifts in their functioning. Both food-web theory and alternative stable states theory provide fundamental clues to mechanisms conferring stability to natural systems. Yet, it is unclear how the concept of food-web stability is associated with the resilience of ecosystems susceptible to regime change. Here, we use a combination of food web and ecosystem modelling to show that impending catastrophic shifts in shallow lakes are preceded by a destabilizing reorganization of interaction strengths in the aquatic food web. Analysis of the intricate web of trophic interactions reveals that only few key interactions, involving zooplankton, diatoms and detritus, dictate the deterioration of food-web stability. Our study exposes a tight link between food-web dynamics and the dynamics of the whole ecosystem, implying that trophic organization may serve as an empirical indicator of ecosystem resilience.

How mechanisms underlying food-web stability may influence ecosystem regime shifts is not well understood. Combining food-web and ecosystem modelling, Kuiper et al. show that destabilizing reorganization of a small number of key trophic interactions precede catastrophic changes in shallow lake ecosystems.