Modern models of trophic meta-communities

Interspecific dispersal constraints suppress pattern formation in metacommunities

Decisions to disperse from a habitat stand out among organismal behaviours as pivotal drivers of ecosystem dynamics across scales. Encounters with other species are an important component of adaptive decision-making in dispersal, resulting in widespread behaviours like tracking resources or avoiding consumers in space. Despite this, metacommunity models often treat dispersal as a function of intraspecific density alone. We show, focusing initially on three-species network motifs, that interspecific dispersal rules generally drive a transition in metacommunities from homogeneous steady states to self-organized heterogeneous spatial patterns. However, when ecologically realistic constraints reflecting adaptive behaviours are imposed-prey tracking and predator avoidance-a pronounced homogenizing effect emerges where spatial pattern formation is suppressed. We demonstrate this effect for each motif by computing master stability functions that separate the contributions of local and spatial interactions to pattern formation. We extend this result to species-rich food webs using a random matrix approach, where we find that eventually, webs become large enough to override the homogenizing effect of adaptive dispersal behaviours, leading once again to predominately pattern-forming dynamics. Our results emphasize the critical role of interspecific dispersal rules in shaping spatial patterns across landscapes, highlighting the need to incorporate adaptive behavioural constraints in efforts to link local species interactions and metacommunity structure. This article is part of the theme issue 'Diversity-dependence of dispersal: interspecific interactions determine spatial dynamics'.

Dispersal evolution and eco-evolutionary dynamics in antagonistic species interactions

Dispersal evolution modifies diverse spatial processes, such as range expansions or biological invasions of single species, but we are currently lacking a realistic vision for metacommunities. Focusing on antagonistic species interactions, we review existing theory of dispersal evolution between natural enemies, and explain how this might be relevant for classic themes in host-parasite evolutionary ecology, namely virulence evolution or local adaptation. Specifically, we highlight the importance of considering the simultaneous (co)evolution of dispersal and interaction traits. Linking such multi-trait evolution with reciprocal demographic and epidemiological feedbacks might change basic predictions about coevolutionary processes and spatial dynamics of interacting species. Future challenges concern the integration of system-specific disease ecology or spatial modifiers, such as spatial network structure or environmental heterogeneity.

Evolutionary Game Dynamics with Environmental Feedback in a Network with Two Communities

Recent developments of eco-evolutionary models have shown that evolving feedbacks between behavioral strategies and the environment of game interactions, leading to changes in the underlying payoff matrix, can impact the underlying population dynamics in various manners. We propose and analyze an eco-evolutionary game dynamics model on a network with two communities such that players interact with other players in the same community and those in the opposite community at different rates. In our model, we consider two-person matrix games with pairwise interactions occurring on individual edges and assume that the environmental state depends on edges rather than on nodes or being globally shared in the population. We analytically determine the equilibria and their stability under a symmetric population structure assumption, and we also numerically study the replicator dynamics of the general model. The model shows rich dynamical behavior, such as multiple transcritical bifurcations, multistability, and anti-synchronous oscillations. Our work offers insights into understanding how the presence of community structure impacts the eco-evolutionary dynamics within and between niches.

Assessing mutualistic metacommunity capacity by integrating spatial and interaction networks

We develop a spatially realistic model of mutualistic metacommunities that exploits the joint structure of spatial and interaction networks. Assuming that all species have the same colonisation and extinction parameters, this model exhibits a sharp transition between stable non-null equilibrium states and a global extinction state. This behaviour allows defining a threshold on colonisation/extinction parameters for the long-term metacommunity persistence. This threshold, the 'metacommunity capacity', extends the metapopulation capacity concept and can be calculated from the spatial and interaction networks without needing to simulate the whole dynamics. In several applications we illustrate how the joint structure of the spatial and the interaction networks affects metacommunity capacity. It results that a weakly modular spatial network and a power-law degree distribution of the interaction network provide the most favourable configuration for the long-term persistence of a mutualistic metacommunity. Our model that encodes several explicit ecological assumptions should pave the way for a larger exploration of spatially realistic metacommunity models involving multiple interaction types.

Both local stability and dispersal contribute to metacommunity sensitivity to asynchronous habitat availability

The stability of isolated communities depends on the complexity of their foodwebs. However, it remains unclear how local stability interacts with dispersal in multitrophic metacommunities to shape biodiversity patterns. This lack of understanding is deeper in the more realistic frame of landscapes that exhibit non-trivial and time-varying structures. Therefore, in this study, we aim to evaluate the influence of local stabilizing factors versus dispersal in determining the sensitivity of metacommunity biodiversity to increasing asynchrony of site availability. Additionally, we assess the role of foodweb complexity and landscape structure as modulating factors. To accomplish our goals we developed a model based on random matrices for local communities, which are linked by stochastic dispersal over explicit dynamic landscapes. We ran numerical simulations and computed the effect sizes of foodweb temperature, self-limitation, dispersal ability, and all pairwise combinations, on the sensitivity of biodiversity to landscape asynchrony. In our experiments we explored gradients of species richness, foodweb connectance, number of sites, and landscape modularity. Our results showed that asynchrony among site availability periods reduced α -diversity and increased β -diversity. Asynchrony increased γ -diversity at high dispersal rates. Both local and regional stabilizing factors determined the sensitivity of metacommunities to landscape asynchrony. Local factors were more influential in landscapes with fewer sites and lower modularity, as well as in metacommunities composed of complex foodwebs. This research offers insights into the dynamics of metacommunities in dynamic landscapes, providing valuable knowledge about the interplay between local and regional factors in shaping ecological stability and species persistence.

The role of the spatial topology in trophic metacommunities: Species with reduced mobility and total population size

A central question in ecology is understanding the influence of the spatial topology on the dynamics of a metacommunity. This is not an easy task, as most fragmented ecosystems have trophic interactions involving many species and patches. Recent attempts to solve this challenge have introduced certain simplifying assumptions or focused on a limited set of examples. These simplifications make the models mathematically tractable but keep away from real-world problems. In this paper, we provide a novel methodology to describe the influence of the spatial topology on the total population size of the species when the dispersal rates are small. The main conclusion is that the influence of the spatial topology is the result of the influence of each path in isolation. Here, a path refers to a pairwise connection between two patches. Our framework can be readily used with any metacommunity, and therefore represents a unification of biological insights. We also discuss several applications regarding the construction of ecological corridors.

Self-segregation in heterogeneous metapopulation landscapes

Complex interactions are at the root of the population dynamics of many natural systems, particularly for being responsible for the allocation of species and individuals across apposite niches of the ecological landscapes. On the other side, the randomness that unavoidably characterises complex systems has increasingly challenged the niche paradigm providing alternative neutral theoretical models. We introduce a network-inspired metapopulation individual-based model (IBM), hereby named self-segregation, where the density of individuals in the hosting patches (local habitats) drives the individuals spatial assembling while still constrained by nodes' saturation. In particular, we prove that the core-periphery structure of the networked landscape triggers the spontaneous emergence of vacant habitat patches, which segregate the population in multistable patterns of isolated (sub)communities separated by empty patches. Furthermore, a quantisation effect in the number of vacant patches is observed once the total system mass varies continuously, emphasising thus a striking feature of the robustness of population stationary distributions. Notably, our model reproduces the patch vacancy found in the fragmented habitat of the Glanville fritillary butterfly Melitaea cinxia, an endemic species of the Åland islands. We argue that such spontaneous breaking of the natural habitat supports the concept of the highly contentious (Grinnellian) niche vacancy and also suggests a new mechanism for the endogeneous habitat fragmentation and consequently the peripatric speciation.

Predator dispersal influences predator distribution but not prey diversity in pitcher plant microbial metacommunities

The spatial distribution of predators can affect both the distribution and diversity of their prey. Therefore, differences in predator dispersal ability that affect their spatial distribution, could also affect prey communities. Here, we use the microbial communities within pitcher plant leaves as a model system to test the relationship between predator (protozoa) dispersal ability and distribution, and its consequences for prey (bacteria) diversity and composition. We hypothesized that limited predator dispersal results in clustered distributions and heterogeneous patches for prey species, whereas wide predator dispersal and distribution could homogenize prey metacommunities. We analyzed the distribution of two prominent bacterivore protozoans from a 2-year survey of an intact field of Sarracenia purpurea pitcher plants, and found a clustered distribution of Tetrahymena and homogeneous distribution of Poterioochromonas. We manipulated the sources of protozoan colonists and recorded protozoan recruitment and bacterial diversity in target leaves in a field experiment. We found the large ciliate, Tetrahymena, was dispersal limited and occupied few leaves, whereas the small flagellate Poterioochromonas was widely dispersed. However, the bacterial communities these protozoans feed on was unaffected by clustering of Tetrahymena, but likely influenced by Poterioochromonas and other bacterivores dispersing in the field. We propose that bacterial communities in this system are structured by a combination of well dispersed bacterivores, bacterial dispersal, and bottom-up mechanisms. Clustered predators could become strong drivers of prey communities if they were specialists or keystone predators, or if they exerted a dominant influence on other predators in top-down controlled systems. Linking dispersal ability within trophic levels and its consequences for trophic dynamics can lead to a more robust perspective on trophic metacommunities.

Estimation of functional diversity and species traits from ecological monitoring data

The rampant loss of biodiversity is starting to be recognized as a global crisis rivaling the climate emergency. To address this crisis, scientists need robust methods to measure the diversity in a system. Importantly, these methods should not only count species but capture the variety of different functions that the species in a system can perform. In this paper, we propose a machine learning method by which existing data from ecosystem monitoring can be reanalyzed to reveal changes of functional biodiversity over time.

The twin crises of climate change and biodiversity loss define a strong need for functional diversity monitoring. While the availability of high-quality ecological monitoring data is increasing, the quantification of functional diversity so far requires the identification of species traits, for which data are harder to obtain. However, the traits that are relevant for the ecological function of a species also shape its performance in the environment and hence, should be reflected indirectly in its spatiotemporal distribution. Thus, it may be possible to reconstruct these traits from a sufficiently extensive monitoring dataset. Here, we use diffusion maps, a deterministic and de facto parameter-free analysis method, to reconstruct a proxy representation of the species’ traits directly from monitoring data and use it to estimate functional diversity. We demonstrate this approach with both simulated data and real-world phytoplankton monitoring data from the Baltic Sea. We anticipate that wider application of this approach to existing data could greatly advance the analysis of changes in functional biodiversity.

Effects of habitat destruction on coevolving metacommunities

Habitat destruction is a growing threat to biodiversity and ecosystem services. The ecological consequences of habitat loss and fragmentation involve reductions in species abundance and even the extinction of species and their interactions. However, we do not yet understand how habitat loss alters the coevolutionary trajectories of the remaining species or how coevolution, in turn, affects their response to habitat loss. To investigate this, we develop a spatially explicit model which couples metacommunity and coevolutionary dynamics. We show that, by changing the size, composition and structure of local networks, habitat destruction increases the diversity of coevolutionary trajectories of mutualists across the landscape. Conversely, in antagonistic communities, some species increase while others reduce their spatial trait heterogeneity. Furthermore, we show that while coevolution dampens the negative effects of habitat destruction in mutualistic networks, its effects on the persistence of antagonistic communities tend to be smaller and less predictable.

Sharp thresholds limit the benefit of defector avoidance in cooperation on networks

Consider a cooperation game on a spatial network of habitat patches, where players can relocate between patches if they judge the local conditions to be unfavorable. In time, the relocation events may lead to a homogeneous state where all patches harbor the same relative densities of cooperators and defectors, or they may lead to self-organized patterns, where some patches become safe havens that maintain an elevated cooperator density. Here we analyze the transition between these states mathematically. We show that safe havens form once a certain threshold in connectivity is crossed. This threshold can be analytically linked to the structure of the patch network and specifically to certain network motifs. Surprisingly, a forgiving defector avoidance strategy may be most favorable for cooperators. Our results demonstrate that the analysis of cooperation games in ecological metacommunity models is mathematically tractable and has the potential to link topics such as macroecological patterns, behavioral evolution, and network topology.

Synchrony and Stability in Trophic Metacommunities: When Top Predators Navigate in a Heterogeneous World

Ecosystem stability strongly depends on spatial aspects since localized perturbations spread across an entire region through species dispersal. Assessing the synchrony of the response of connected populations is fundamental to understand stability at different scales because if populations fluctuate asynchronously, the risk of their simultaneous extinction is low, thus reducing the species' regional extinction risk. Here, we consider a metacommunity model consisting of two food chains connected by dispersal and we review the various mechanisms governing the transmission of small perturbations affecting populations in the vicinity of equilibrium. First, we describe how perturbations propagate vertically (i.e., within food chains through trophic interactions) and horizontally (i.e., between food chains through dispersal) in metacommunities. Then, we discuss the mechanisms susceptible to alter synchrony patterns such as density-depend dispersal or spatial heterogeneity. Density-dependent dispersal, which is the influence of prey or predator abundance on dispersal, has a major impact because the species with the highest coefficient of variation of biomass governs the dispersal rate of the dispersing species and determines the synchrony of its populations, thus bypassing the classic vertical transmission of perturbations. Spatial heterogeneity, which is a disparity between patches of the attack rate of predators on prey in our model, alters the vertical transmission of perturbations in each patch, thus making synchrony dependent on which patch is perturbed. Finally, by combining our understanding of the impact of each of these mechanisms on synchrony, we are able to full explain the response of realistic metacommunities such as the model developed by Rooney et al. (2006). By disentangling the main mechanisms governing synchrony, our metacommunity model provides a broad insight into the consequences of spacial aspects on food web stability.

Master stability functions for metacommunities with two types of habitats

Current questions in ecology revolve around instabilities in the dynamics on spatial networks and particularly the effect of node heterogeneity. We extend the master stability function formalism to inhomogeneous biregular networks having two types of spatial nodes. Notably, this class of systems also allows the investigation of certain types of dynamics on higher-order networks. Combined with the generalized modeling approach to study the linear stability of steady states, this is a powerful tool to numerically asses the stability of large ensembles of systems. We analyze the stability of ecological metacommunities with two distinct types of habitats analytically and numerically in order to identify several sets of conditions under which the dynamics can become stabilized by dispersal. Our analytical approach allows general insights into stabilizing and destabilizing effects in metapopulations. Specifically, we identify self-regulation and negative feedback loops between source and sink populations as stabilizing mechanisms and we show that maladaptive dispersal may be stable under certain conditions.

Metapopulations with habitat modification

Across the tree of life, organisms modify their local environment, rendering it more or less hospitable for other species. Despite the ubiquity of these processes, simple models that can be used to develop intuitions about the consequences of widespread habitat modification are lacking. Here, we extend the classic Levins metapopulation model to a setting where each of n species can colonize patches connected by dispersal, and when patches are vacated via local extinction, they retain a "memory" of the previous occupant-modeling habitat modification. While this model can exhibit a wide range of dynamics, we draw several overarching conclusions about the effects of modification and memory. In particular, we find that any number of species may potentially coexist, provided that each is at a disadvantage when colonizing patches vacated by a conspecific. This notion is made precise through a quantitative stability condition, which provides a way to unify and formalize existing conceptual models. We also show that when patch memory facilitates coexistence, it generically induces a positive relationship between diversity and robustness (tolerance of disturbance). Our simple model provides a portable, tractable framework for studying systems where species modify and react to a shared landscape.

A roadmap towards predicting species interaction networks (across space and time)

Networks of species interactions underpin numerous ecosystem processes, but comprehensively sampling these interactions is difficult. Interactions intrinsically vary across space and time, and given the number of species that compose ecological communities, it can be tough to distinguish between a true negative (where two species never interact) from a false negative (where two species have not been observed interacting even though they actually do). Assessing the likelihood of interactions between species is an imperative for several fields of ecology. This means that to predict interactions between species-and to describe the structure, variation, and change of the ecological networks they form-we need to rely on modelling tools. Here, we provide a proof-of-concept, where we show how a simple neural network model makes accurate predictions about species interactions given limited data. We then assess the challenges and opportunities associated with improving interaction predictions, and provide a conceptual roadmap forward towards predictive models of ecological networks that is explicitly spatial and temporal. We conclude with a brief primer on the relevant methods and tools needed to start building these models, which we hope will guide this research programme forward. This article is part of the theme issue 'Infectious disease macroecology: parasite diversity and dynamics across the globe'.

Strange invaders increase disturbance and promote generalists in an evolving food web

The patterns of diet specialization in food webs determine community structure, stability, and function. While specialists are often thought to evolve due to greater efficiency, generalists should have an advantage in systems with high levels of variability. Here we test the generalist-disturbance hypothesis using a dynamic, evolutionary food web model. Species occur along a body size axis with three traits (body size, feeding center, feeding range) that evolve independently and determine interaction strengths. Communities are assembled via ecological and evolutionary processes, where species biomass and persistence are driven by a bioenergetics model. New species are introduced either as mutants similar to parent species in the community or as invaders, with dissimilar traits. We introduced variation into communities by increasing the dissimilarity of invading species across simulations. We found that strange invaders increased the variability of communities which increased both the degree of generalism and the relative persistence of generalist species, indicating that invasion disturbance promotes the evolution of generalist species in food webs.

Body size dependent dispersal influences stability in heterogeneous metacommunities

Body size affects key biological processes across the tree of life, with particular importance for food web dynamics and stability. Traits influencing movement capabilities depend strongly on body size, yet the effects of allometrically-structured dispersal on food web stability are less well understood than other demographic processes. Here we study the stability properties of spatially-arranged model food webs in which larger bodied species occupy higher trophic positions, while species’ body sizes also determine the rates at which they traverse spatial networks of heterogeneous habitat patches. Our analysis shows an apparent stabilizing effect of positive dispersal rate scaling with body size compared to negative scaling relationships or uniform dispersal. However, as the global coupling strength among patches increases, the benefits of positive body size-dispersal scaling disappear. A permutational analysis shows that breaking allometric dispersal hierarchies while preserving dispersal rate distributions rarely alters qualitative aspects of metacommunity stability. Taken together, these results suggest that the oft-predicted stabilizing effects of large mobile predators may, for some dimensions of ecological stability, be attributed to increased patch coupling per se, and not necessarily coupling by top trophic levels in particular.

Metapopulation capacity determines food chain length in fragmented landscapes

Understanding the persistence of populations in fragmented landscapes is critical for predicting the consequences of habitat destruction, yet analytical tools are largely lacking. Metapopulation capacity provides one such tool, because it summarizes the influences of habitat area and distribution on population persistence in a single metric. However, surprisingly few efforts have extended this theory to multispecies communities. Our analyses demonstrate the power of metapopulation capacity theory in predicting the persistence of prey–predator pairs and food chains in heterogeneous, fragmented landscapes. Such analytic insights serve as a benchmark to predict the consequences of habitat changes. Our findings thus have broad implications for both ecological research and conservation practices.

Metapopulation capacity provides an analytic tool to quantify the impact of landscape configuration on metapopulation persistence, which has proven powerful in biological conservation. Yet surprisingly few efforts have been made to apply this approach to multispecies systems. Here, we extend metapopulation capacity theory to predict the persistence of trophically interacting species. Our results demonstrate that metapopulation capacity could be used to predict the persistence of trophic systems such as prey–predator pairs and food chains in fragmented landscapes. In particular, we derive explicit predictions for food chain length as a function of metapopulation capacity, top-down control, and population dynamical parameters. Under certain assumptions, we show that the fraction of empty patches for the basal species provides a useful indicator to predict the length of food chains that a fragmented landscape can support and confirm this prediction for a host–parasitoid interaction. We further show that the impact of habitat changes on biodiversity can be predicted from changes in metapopulation capacity or approximately by changes in the fraction of empty patches. Our study provides an important step toward a spatially explicit theory of trophic metacommunities and a useful tool for predicting their responses to habitat changes.

Top predator introduction changes the effects of spatial isolation on freshwater community structure

Current conceptual metacommunity models predict that the consequences of local selective pressures on community structure increase with spatial isolation when species favored by local conditions also have higher dispersal rates. This appears to be the case of freshwater insects in the presence of fish. The introduction of predatory fish can produce trophic cascades in freshwater habitats because fish tend to prey upon intermediate predatory taxa, such as predatory insects, indirectly benefiting herbivores and detritivores. Similarly, spatial isolation can limit dispersal and colonization rates of predatory insects more strongly than of herbivores and detritivores, thus generating similar cascading effects. Here we tested the hypothesis that the effect of introduced predatory fish on insect community structure increases with spatial isolation by conducting a field experiment in artificial ponds that manipulated the presence/absence of fish (the redbreast tilapia) at three different distances from a source wetland. Our results showed that fish have direct negative effects on the abundance of predatory insects but probably have variable net effects on the abundance of herbivores and detritivores because the direct negative effects of predation by fish may offset indirect positive ones. Spatial isolation also resulted in indirect positive effects on the abundance of herbivores and detritivores but this effect was stronger in the absence rather than in the presence of fish so that insect communities diverged more strongly between fish and fishless ponds at higher spatial isolation. We argue that an important additional mechanism, ignored in our initial hypothesis, was that as spatial isolation increases fish predation pressure upon herbivores and detritivores increases due to the relative scarcity of predatory insects, thus dampening the positive effect that spatial isolation confers to lower trophic levels. Our results highlight the importance of considering interspecific variation in dispersal and multiple trophic levels to better understand the processes generating community and metacommunity patterns.

Predator avoidance and foraging for food shape synchrony and response to perturbations in trophic metacommunities

The response of species to perturbations strongly depends on spatial aspects in populations connected by dispersal. Asynchronous fluctuations in biomass among populations lower the risk of simultaneous local extinctions and thus reduce the regional extinction risk. However, dispersal is often seen as passive diffusion that balances species abundance between distant patches, whereas ecological constraints, such as predator avoidance or foraging for food, trigger the movement of individuals. Here, we propose a model in which dispersal rates depend on the abundance of the species interacting with the dispersing species (e.g., prey or predators) to determine how density-dependent dispersal shapes spatial synchrony in trophic metacommunities in response to stochastic perturbations. Thus, unlike those with passive dispersal, this model with density-dependent dispersal bypasses the classic vertical transmission of perturbations due to trophic interactions and deeply alters synchrony patterns. We show that the species with the highest coefficient of variation of biomass governs the dispersal rate of the dispersing species and determines the synchrony of its populations. In addition, we show that this mechanism can be modulated by the relative impact of each species on the growth rate of the dispersing species. Species affected by several constraints disperse to mitigate the strongest constraints (e.g., predation), which does not necessarily experience the highest variations due to perturbations. Our approach can disentangle the joint effects of several factors implied in dispersal and provides a more accurate description of dispersal and its consequences on metacommunity dynamics.

Integrative research perspectives on marine conservation

Whereas the conservation and management of biodiversity has become a key issue in environmental sciences and policy in general, the conservation of marine biodiversity faces additional challenges such as the challenges of accessing field sites (e.g. polar, deep sea), knowledge gaps regarding biodiversity trends, high mobility of many organisms in fluid environments, and ecosystem-specific obstacles to stakeholder engagement and governance. This issue comprises contributions from a diverse international group of scientists in a benchmarking volume for a common research agenda on marine conservation. We begin by addressing information gaps on marine biodiversity trends through novel approaches and technologies, then linking such information to ecosystem functioning through a focus on traits. We then leverage the knowledge of these relationships to inform theory aiming at predicting the future composition and functioning of marine communities. Finally, we elucidate the linkages between marine ecosystems and human societies by examining economic, management and governance approaches that contribute to effective marine conservation in practice. This article is part of the theme issue 'Integrative research perspectives on marine conservation'.