Stable diverse food webs become more common when interactions are more biologically constrained.

Ecologists have long sought to understand how diversity and structure mediate the stability of whole ecosystems. For high-diversity food webs, the interactions between species are typically represented using matrices with randomly chosen interaction strengths. Unfortunately, this procedure tends to produce ecological systems with no underlying equilibrium solution, and so ecological inferences from this approach may be biased by nonbiological outcomes. Using recent computationally efficient methodological advances from metabolic networks, we employ for the first time an inverse approach to diversity-stability research. We compare classical random interaction matrices of realistic food web topology (hereafter the classical model) to feasible, biologically constrained, webs produced using the inverse approach. We show that an energetically constrained feasible model yields a far higher proportion of stable high-diversity webs than the classical random matrix approach. When we examine the energetically constrained interaction strength distributions of these matrix models, we find that although these diverse webs have consistent negative self-regulation, they do not require strong self-regulation to persist. These energetically constrained diverse webs instead show an increasing preponderance of weak interactions that are known to increase local stability. Further examination shows that some of these weak interactions naturally appear to arise in the model food webs from a constraint-generated realistic generalist-specialist trade-off, whereby generalist predators have weaker interactions than more specialized species. Additionally, the inverse technique we present here has enormous promise for understanding the role of the biological structure behind stable high-diversity webs and for linking empirical data to the theory.

When can higher-order interactions produce stable coexistence?

Most ecological models are based on the assumption that species interact in pairs. Diverse communities, however, can have higher-order interactions, in which two or more species jointly impact the growth of a third species. A pitfall of the common pairwise approach is that it misses the higher-order interactions potentially responsible for maintaining natural diversity. Here, we explore the stability properties of systems where higher-order interactions guarantee that a specified set of abundances is a feasible equilibrium of the dynamics. Even these higher-order interactions which lead to equilibria do not necessarily produce stable coexistence. Instead, these systems are more likely to be stable when the pairwise interactions are weak or facilitative. Correlations between the pairwise and higher-order interactions, however, do permit robust coexistence even in diverse systems. Our work not only reveals the challenges in generating stable coexistence through higher-order interactions but also uncovers interaction patterns that can enable diversity.

Stability of consumer-resource interactions in periodic environments.

Periodic fluctuations in abiotic conditions are ubiquitous across a range of temporal scales and regulate the structure and function of ecosystems through dynamic biotic responses that are adapted to these external forces. Research has suggested that certain environmental signatures may play a crucial role in the maintenance of biodiversity and the stability of food webs, while others argue that coupled oscillators ought to promote chaos. As such, numerous uncertainties remain regarding the intersection of temporal environmental patterns and biological responses, and we lack a general understanding of the implications for food web stability. Alarmingly, global change is altering the nature of both environmental rhythms and biological rates. Here, we develop a general theory for how continuous periodic variation in productivity, across temporal scales, influences the stability of consumer-resource interactions: a fundamental building block of food webs. Our results suggest that consumer-resource dynamics under environmental forcing are highly complex and depend on asymmetries in both the speed of forcing relative to underlying dynamics and in local stability properties. These asymmetries allow for environmentally driven stabilization under fast forcing, relative to underlying dynamics, as well as extremely complex and unstable dynamics at slower periodicities. Our results also suggest that changes in naturally occurring periodicities from climate change may lead to precipitous shifts in dynamics and stability.

Life-history speed, population disappearances and noise-induced ratchet effects.

Nature is replete with variation in the body sizes, reproductive output and generation times of species that produce life-history responses known to vary from small and fast to large and slow. Although researchers recognize that life-history speed likely dictates fundamental processes in consumer-resource interactions like productivity and stability, theoretical work remains incomplete in this critical area. Here, we examine the role of life-history speed on consumer-resource interactions by using a well-used mathematical approach that manipulates the speed of the consumer's growth rate in a consumer-resource interaction. Importantly, this approach holds the isocline geometry intact, allowing us to assess the impacts of altered life-history speed on stability (coefficient of variation, CV) without changing the underlying qualitative dynamics. Although slowing life history can be initially stabilizing, we find that in stochastic settings slowing ultimately drives highly destabilizing population disappearances, especially under reddened noise. Our results suggest that human-driven reddening of noise may decrease species stability because the autocorrelation of red noise enlarges the period and magnitude of perturbations, overwhelming a species' natural compensatory responses via a ratchet-like effect. This ratchet-like effect then pushes species' population dynamics far away from equilibria, which can lead to precipitous local extinction.

Landscape modification and nutrient-driven instability at a distance.

Almost 50 years ago, Michael Rosenzweig pointed out that nutrient addition can destabilise food webs, leading to loss of species and reduced ecosystem function through the paradox of enrichment. Around the same time, David Tilman demonstrated that increased nutrient loading would also be expected to cause competitive exclusion leading to deleterious changes in food web diversity. While both concepts have greatly illuminated general diversity-stability theory, we currently lack a coherent framework to predict how nutrients influence food web stability across a landscape. This is a vitally important gap in our understanding, given mounting evidence of serious ecological disruption arising from anthropogenic displacement of resources and organisms. Here, we combine contemporary theory on food webs and meta-ecosystems to show that nutrient additions are indeed expected to drive loss in stability and function in human-impacted regions. Our models suggest that destabilisation is more likely to be caused by the complete loss of an equilibrium due to edible plant species being competitively excluded. In highly modified landscapes, spatial nutrient transport theory suggests that such instabilities can be amplified over vast distances from the sites of nutrient addition. Consistent with this theoretical synthesis, the empirical frequency of these distant propagating ecosystem imbalances appears to be growing. This synthesis of theory and empirical data suggests that human modification of the Earth is strongly connecting distantly separated ecosystems, causing rapid, expansive and costly nutrient-driven instabilities over vast areas of the planet. Similar to existing food web theory, the corollary to this spatial nutrient theory is that slowing down spatial nutrient pathways can be a potent means of stabilising degraded ecosystems.

Potential oscillators and keystone modules in food webs.

Food web theory suggests that the placement of a weak interaction is critical such that under some conditions even one well-placed weak interaction can stabilise multiple strong interactions. This theory suggests that complex stable webs may be built from pivotal weak interactions such that the removal of even one to a few keystone interactions can have significant cascading impacts on whole system diversity and structure. However, the connection between weak interactions, derived from the theory of modular food web components, and keystone species, derived from empirical results, is not yet well understood. Here, we develop numerical techniques to detect potential oscillators hidden in complex food webs, and show that, both in random and real food webs, keystone consumer-resource interactions often operate to stabilise them. Alarmingly, this result suggests that nature frequently may be dangerously close to precipitous change with even the loss of one or a few weakly interacting species.

On the prevalence and dynamics of inverted trophic pyramids and otherwise top-heavy communities.

Classically, biomass partitioning across trophic levels was thought to add up to a pyramidal distribution. Numerous exceptions have, however, been noted including complete pyramidal inversions. Elevated levels of biomass top-heaviness (i.e. high consumer/resource biomass ratios) have been reported from Arctic tundra communities to Brazilian phytotelmata, and in species assemblages as diverse as those dominated by sharks and ants. We highlight two major pathways for creating top-heaviness, via: (1) endogenous channels that enhance energy transfer across trophic boundaries within a community and (2) exogenous pathways that transfer energy into communities from across spatial and temporal boundaries. Consumer-resource models and allometric trophic network models combined with niche models reveal the nature of core mechanisms for promoting top-heaviness. Outputs from these models suggest that top-heavy communities can be stable, but they also reveal sources of instability. Humans are both increasing and decreasing top-heaviness in nature with ecological consequences. Current and future research on the drivers of top-heaviness can help elucidate fundamental mechanisms that shape the architecture of ecological communities and govern energy flux within and between communities. Questions emerging from the study of top-heaviness also usefully draw attention to the incompleteness and inconsistency by which ecologists often establish definitional boundaries for communities.

Reconciling the omnivory-stability debate.

Despite attempts at reconciliation, the role of omnivory in food web stability remains unclear. Here we develop a novel community matrix approach that is analogous to the bifurcation method of modular food web theory to show that the stability of omnivorous food chains depends critically on interaction strength. We find that there are only six possible ways that omnivorous interaction strengths can influence the stability of linear food chains. The results from these six cases suggest that: (1) strong omnivory is always destabilizing, (2) stabilization by weak to intermediate omnivorous interaction strengths dominates the set of possible stability responses, and, (3) omnivory can be occasionally strictly destabilizing or intermittently destabilizing. We then revisit the classical results of Pimm and Lawton to show that although their parameterization tends to produce a low percentage of stable omnivorous webs, the same parameterization shows strong theoretical support for the weak interaction effect. Finally, we end by arguing that our current empirical knowledge of omnivory resonates with this general theory.

Structural asymmetry and the stability of diverse food webs.

Untangling the influence of human activities on food-web stability and persistence is complex given the large numbers of species and overwhelming number of interactions within ecosystems. Although biodiversity has been associated with stability, the actual structures and processes that confer stability to diverse food webs remain largely unknown. Here we show that real food webs are structured such that top predators act as couplers of distinct energy channels that differ in both productivity and turnover rate. Our theoretical analysis shows that coupled fast and slow channels convey both local and non-local stability to food webs. Alarmingly, the same human actions that have been implicated in the loss of biodiversity also directly erode the very structures and processes that we show to confer stability on food webs.

Strong nutrient-plant interactions enhance the stability of ecosystems.

Modular food web theory shows how weak energetic fluxes resulting from consumptive interactions plays a major role in stabilizing food webs in space and time. Despite the reliance on energetic fluxes, food web theory surprisingly remains poorly understood within an ecosystem context that naturally focuses on material fluxes. At the same time, while ecosystem theory has employed modular nutrient-limited ecosystem models to understand how limiting nutrients alter the structure and dynamics of food webs, ecosystem theory has overlooked the role of key ecosystem interactions and their strengths (e.g., plant-nutrient; R-N) in mediating the stability of nutrient-limited ecosystems. Here, towards integrating food web theory and ecosystem theory, we first briefly review consumer-resource interactions (C-R) highlighting the relationship between the structure of C-R interactions and the stability of food web modules. We then translate this framework to nutrient-based systems, showing that the nutrient-plant interaction behaves as a coherent extension of current modular food web theory; however, in contrast to the rule that weak C-R interactions tend to be stabilizing we show that strong nutrient-plant interactions are potent stabilizers in nutrient-limited ecosystem models.

Management implications of long transients in ecological systems.

The underlying biological processes that govern many ecological systems can create very long periods of transient dynamics. It is often difficult or impossible to distinguish this transient behaviour from similar dynamics that would persist indefinitely. In some cases, a shift from the transient to the long-term, stable dynamics may occur in the absence of any exogenous forces. Recognizing the possibility that the state of an ecosystem may be less stable than it appears is crucial to the long-term success of management strategies in systems with long transient periods. Here we demonstrate the importance of considering the potential of transient system behaviour for management actions across a range of ecosystem organizational scales and natural system types. Developing mechanistic models that capture essential system dynamics will be crucial for promoting system resilience and avoiding system collapses.

Long transients in ecology: Theory and applications.

This paper discusses the recent progress in understanding the properties of transient dynamics in complex ecological systems. Predicting long-term trends as well as sudden changes and regime shifts in ecosystems dynamics is a major issue for ecology as such changes often result in population collapse and extinctions. Analysis of population dynamics has traditionally been focused on their long-term, asymptotic behavior whilst largely disregarding the effect of transients. However, there is a growing understanding that in ecosystems the asymptotic behavior is rarely seen. A big new challenge for theoretical and empirical ecology is to understand the implications of long transients. It is believed that the identification of the corresponding mechanisms along with the knowledge of scaling laws of the transient's lifetime should substantially improve the quality of long-term forecasting and crisis anticipation. Although transient dynamics have received considerable attention in physical literature, research into ecological transients is in its infancy and systematic studies are lacking. This text aims to partially bridge this gap and facilitate further progress in quantitative analysis of long transients in ecology. By revisiting and critically examining a broad variety of mathematical models used in ecological applications as well as empirical facts, we reveal several main mechanisms leading to the emergence of long transients and hence lays the basis for a unifying theory.

Transient phenomena in ecology.

The importance of transient dynamics in ecological systems and in the models that describe them has become increasingly recognized. However, previous work has typically treated each instance of these dynamics separately. We review both empirical examples and model systems, and outline a classification of transient dynamics based on ideas and concepts from dynamical systems theory. This classification provides ways to understand the likelihood of transients for particular systems, and to guide investigations to determine the timing of sudden switches in dynamics and other characteristics of transients. Implications for both management and underlying ecological theories emerge.

Consistent role of weak and strong interactions in high- and low-diversity trophic food webs.

The growing realization of a looming biodiversity crisis has inspired considerable progress in the quest to link biodiversity, structure and ecosystem function. Here we construct a method that bridges low- and high-diversity approaches to food web theory by elucidating the connection between the stability of the basic building block of food webs and the mean stability properties of large random food web networks. Applying this theoretical framework to common food web models reveals two key findings. First, in almost all cases, high-diversity food web models yield a stability relationship between weak and strong interactions that are compatible in every way to simple low-diversity models. And second, the models that generate the recently discovered phenomena of being purely stabilized by increasing interaction strength correspond to the biologically implausible assumption of perfect interaction strength symmetry.

Early warning signals detect critical impacts of experimental warming.

Earth's surface temperatures are projected to increase by ~1-4°C over the next century, threatening the future of global biodiversity and ecosystem stability. While this has fueled major progress in the field of physiological trait responses to warming, it is currently unclear whether routine population monitoring data can be used to predict temperature-induced population collapse. Here, we integrate trait performance theory with that of critical tipping points to test whether early warning signals can be reliably used to anticipate thermally induced extinction events. We find that a model parameterized by experimental growth rates exhibits critical slowing down in the vicinity of an experimentally tested critical threshold, suggesting that dynamical early warning signals may be useful in detecting the potentially precipitous onset of population collapse due to global climate change.