The sixth mass coextinction: are most endangered species parasites and mutualists?

The effects of species declines and extinction on biotic interactions remain poorly understood. The loss of a species is expected to result in the loss of other species that depend on it (coextinction), leading to cascading effects across trophic levels. Such effects are likely to be most severe in mutualistic and parasitic interactions. Indeed, models suggest that coextinction may be the most common form of biodiversity loss. Paradoxically, few historical or contemporary coextinction events have actually been recorded. We review the current knowledge of coextinction by: (i) considering plausible explanations for the discrepancy between predicted and observed coextinction rates; (ii) exploring the potential consequences of coextinctions; (iii) discussing the interactions and synergies between coextinction and other drivers of species loss, particularly climate change; and (iv) suggesting the way forward for understanding the phenomenon of coextinction, which may well be the most insidious threat to global biodiversity.     

Predicting the effect of competition on secondary plant extinctions in plant–pollinator networks

What are the limitations of models that predict the behavior of an ecological community based on a single type of species interaction? Using plant–pollinator network models as an example, we contrast the predicted vulnerability of a community to secondary extinctions under the assumption of purely mutualistic interactions versus mutualistic and competitive interactions. We find that competition among plant species increases the risk of secondary extinctions and extinction cascades. Simulations over a number of different network structures indicate that this effect is stronger in larger networks, more strongly connected networks and networks with higher plant:pollinator ratios. We conclude that efforts to model plant–pollinator communities will systematically over‐estimate community robustness to species loss if plant competition is ignored. However, because the effect of plant competition depends on network architecture, and because characterization of plant competition is work intensive, we suggest that efforts to account for plant competition in plant–pollinator network models should be focused on large, strongly connected networks with high plant:pollinator ratios.     

Pattern of functional extinctions in ecological networks with a variety of interaction types

There is a strong trend of declining populations in many species of both animals and plants. Dwindling numbers of species can eventually lead to their functional extinction. Functional, or ecological, extinction occurs when a species becomes too rare to fulfill its ecological, interactive role in the ecosystem, leading to true (numerical) extinction of other depending species. Recent theoretical work on food webs suggests that the frequency of functional extinction might be surprisingly high. However, little is known about the risk of functional species extinctions in networks with other types of interactions than trophic ones. Here, we explore the frequency of functional extinctions in model ecological networks having different proportions of antagonistic and mutualistic links. Furthermore, we investigate the topological relationship between functionally and numerically extinct species. We find that (1) the frequency of functional extinctions is higher in networks containing a mixture of antagonistic and mutualistic interactions than in networks with only one type of interaction, (2) increased mortality rate of species having both mutualistic and antagonistic links is more likely to lead to extinction of another species than to extinction of the species itself compared to species having only mutualistic or antagonistic links, and (3) trophic distance (shortest path) between functionally and numerically extinct species is, on average, longer than one, indicating the importance of indirect effects. These results generalize the findings of an earlier study on food webs, demonstrating the potential importance of functional extinction in a variety of ecological network types.     

Global stability of obligate mutualism in community modules with facultative mutualists

Mutualism is a fundamental building block of ecological communities and an important driver of biotic evolution. Classic theory suggests that a pairwise two‐species obligate mutualism is fragile, with a large perturbation potentially driving both mutualist populations into extinction. In nature, however, there are many cases of pairwise obligate mutualism. Such pairwise obligate mutualisms are occasionally associated with additional interactions with facultative mutualists. Here, we use a mathematical model to show that when a two‐species obligate mutualism has a single additional link to a third facultative mutualist, the obligate mutualism can become permanently persistent. In the model, a facultative mutualist interacts with one of two inter‐dependent obligate mutualists, and the facultative mutualist enhances the persistence not only of its directly interacting obligate mutualist, but also that of the other obligate mutualist indirectly, enabling the permanent coexistence of the three mutualist species. The effect of the facultative mutualist is strong; it can allow a three‐species permanent coexistence even when two obligate mutualists by themselves are not sustainable (i.e. not locally stable). These results suggest that facultative mutualists can play a pivotal role for the persistence of obligate mutualisms, and contribute to a better understanding on the mechanisms maintaining more complex mutualistic networks of multiple species.     

The effects of space and diversity of interaction types on the stability of complex ecological networks

The relationship between structure and stability in ecological networks and the effect of spatial dynamics on natural communities have both been major foci of ecological research for decades. Network research has traditionally focused on a single interaction type at a time (e.g. food webs, mutualistic networks). Networks comprising different types of interactions have recently started to be empirically characterized. Patterns observed in these networks and their implications for stability demand for further theoretical investigations. Here, we employed a spatially explicit model to disentangle the effects of mutualism/antagonism ratios in food web dynamics and stability. We found that increasing levels of plant-animal mutualistic interactions generally resulted in more stable communities. More importantly, increasing the proportion of mutualistic vs. antagonistic interactions at the base of the food web affects different aspects of ecological stability in different directions, although never negatively. Stability is either not influenced by increasing mutualism—for the cases of population stability and species’ spatial distributions—or is positively influenced by it—for spatial aggregation of species. Additionally, we observe that the relative increase of mutualistic relationships decreases the strength of biotic interactions in general within the ecological network. Our work highlights the importance of considering several dimensions of stability simultaneously to understand the dynamics of communities comprising multiple interaction types.     

An interaction switch predicts the nested architecture of mutualistic networks

Nested architecture is distinctive in plant-animal mutualistic networks. However, to date an integrative and quantitative explanation has been lacking. It is evident that species often switch their interactive partners in real-world mutualistic networks such as pollination and seed-dispersal networks. By incorporating an interaction switch into a novel multi-population model, we show that the nested architecture rapidly emerges from an initially random network. The model allowing interaction switches between partner species produced predictions which fit remarkably well with observations from 81 empirical networks. Thus, the nested architecture in mutualistic networks could be an intrinsic physical structure of dynamic networks and the interaction switch is likely a key ecological process that results in nestedness of real-world networks. Identifying the biological processes responsible for network structures is thus crucial for understanding the architecture of ecological networks.     

Predicting abundances of plants and pollinators using a simple compartmental mutualistic model

Key gaps to be filled in population and community ecology are predicting the strength of species interactions and linking pattern with process to understand species coexistence and their relative abundances. In the case of mutualistic webs, like plant–pollinator networks, advances in understanding species abundances are currently limited, mainly owing to the lack of methodological tools to deal with the intrinsic complexity of mutualisms. Here, we propose an aggregation method leading to a simple compartmental mutualistic population model that captures both qualitatively and quantitatively the size-segregated populations observed in a Mediterranean community of nectar-producing plant species and nectar-searching animal species. We analyse the issue of optimal aggregation level and its connection with the trade-off between realism and overparametrization. We show that aggregation of both plants and pollinators into five size classes or compartments leads to a robust model with only two tunable parameters. Moreover, if, in each compartment, (i) the interaction coefficients fulfil the condition of weak mutualism and (ii) the mutualism is facultative for at least one party of the compartment, then the interactions between different compartments are sufficient to guarantee global stability of the equilibrium population.     

The assembly and disassembly of ecological networks

Global change has created a severe biodiversity crisis. Species are driven extinct at an increasing rate, and this has the potential to cause further coextinction cascades. The rate and shape of these coextinction cascades depend very much on the structure of the networks of interactions across species. Understanding network structure and how it relates to network disassembly, therefore, is a priority for system-level conservation biology. This process of network collapse may indeed be related to the process of network build-up, although very little is known about both processes and even less about their relationship. Here we review recent work that provides some preliminary answers to these questions. First, we focus on network assembly by emphasizing temporal processes at the species level, as well as the structural building blocks of complex ecological networks. Second, we focus on network disassembly as a consequence of species extinctions or habitat loss. We conclude by emphasizing some general rules of thumb that can help in building a comprehensive framework to understand the responses of ecological networks to global change.     

Comparing species interaction networks along environmental gradients

Knowledge of species composition and their interactions, in the form of interaction networks, is required to understand processes shaping their distribution over time and space. As such, comparing ecological networks along environmental gradients represents a promising new research avenue to understand the organization of life. Variation in the position and intensity of links within networks along environmental gradients may be driven by turnover in species composition, by variation in species abundances and by abiotic influences on species interactions. While investigating changes in species composition has a long tradition, so far only a limited number of studies have examined changes in species interactions between networks, often with differing approaches. Here, we review studies investigating variation in network structures along environmental gradients, highlighting how methodological decisions about standardization can influence their conclusions. Due to their complexity, variation among ecological networks is frequently studied using properties that summarize the distribution or topology of interactions such as number of links, connectance, or modularity. These properties can either be compared directly or using a procedure of standardization. While measures of network structure can be directly related to changes along environmental gradients, standardization is frequently used to facilitate interpretation of variation in network properties by controlling for some co‐variables, or via null models. Null models allow comparing the deviation of empirical networks from random expectations and are expected to provide a more mechanistic understanding of the factors shaping ecological networks when they are coupled with functional traits. As an illustration, we compare approaches to quantify the role of trait matching in driving the structure of plant–hummingbird mutualistic networks, i.e. a direct comparison, standardized by null models and hypothesis‐based metaweb. Overall, our analysis warns against a comparison of studies that rely on distinct forms of standardization, as they are likely to highlight different signals. Fostering a better understanding of the analytical tools available and the signal they detect will help produce deeper insights into how and why ecological networks vary along environmental gradients.     

On the structure and stability of mutualistic systems: Analysis of predator-prey and competition models as modified by the action of a slow-growing mutualist

Two basic models of mutualism are presented in which interactions among three species lead to mutualism between two of them. The models represent 2-species predator-prey or competition systems in which a third species acts as a mutualist with either the predator, the prey, or one of the competitors. The models include the assumptions that there is a cost of associating with the mutualist and that the mutualist population grows much more slowly than the other two populations. Special cases of these two models correspond to six qualitatively different types of mutualistic benefit, all of which are known to occur in nature: deterring predation, increasing prey availability, feeding on (or competing with) a predator, increasing competitive interactions, decreasing competitive interactions, and feeding on (or competing with) a competitor. These models and their special cases are subjected to a local stability analysis. The results show that mutualism based upon deterring predation, competing with a predator, or decreasing competitive interactions enhances local stability, while mutualism based upon increasing prey availability or increasing competitive interactions reduces local stability. These results clearly reject the idea that mutualism is an inherently unstable process, and reinforces the idea that each different kind of mutualism will have to be considered separately. Compared to 2-species models of mutualism, the 3-species models provide a more realistic representation of the structure of many mutualistic systems, the mechanisms by which one species benefits another, and the regulation of the interaction.     

Impacts of consumer–resource interaction transitions on persistence and long‐term interaction outcomes of random ecological networks

Despite the prevalence of context‐dependent interaction transitions in ecological systems, their impacts on persistence and interaction diversity have scarcely been explored in complex ecological networks. By using multispecies bi‐directional and unidirectional consumer–resource models, representing a continuum of interaction transitions (sign change of interaction outcomes), we investigated the effects of structural interaction transitions on persistence (the fraction of remaining species) and long‐term interaction outcomes in random ecological networks. We found that high interaction strength of exploiting resources generally decreased persistence, and high strength of providing resources increased persistence when the strength of exploiting resources was low in more complex networks; also, the networks with high persistence had a high proportion of mutualistic interactions relative to antagonistic interactions present initially and over the long term. The shifting of interaction strengths shaped the long‐term interaction compositions. Meanwhile, population dynamics, especially species extinction, affected the difference between initial and long‐term interactions. Based on classical consumer–resource theory, these results establish a transitional continuum of interaction outcomes in ecological networks and imply a theoretical association among interaction transition, community persistence and interaction diversity.     

Evolutionary double suicide in symbiotic systems

Mutualism is thought to face a threat of coextinction cascade because the loss of a member species could lead to the extinction of the other member. Despite this common emphasis on the perils of such knock-on effect, hitherto, the evolutionary causes leading to extinction have been less emphasised. Here, we examine how extinction could be triggered in mutualism and whether an evolutionary response to partner loss could prevent collateral extinctions, by theoretically examining the coevolution of the host exploitation by symbionts and host dependence on symbiosis. Our model reveals that mutualism is more vulnerable to co-extinction through adaptive evolution (evolutionary double suicide) than parasitism. Additionally, it shows that the risk of evolutionary double suicide rarely promotes the backward evolution to an autonomous (non-symbiotic) state. Our results provide a new perspective on the evolutionary fragility of mutualism and the rarity of observed evolutionary transitions from mutualism to parasitism.     

Succinctly assessing the topological importance of species in flower–pollinator networks

The topological importance of species within networks is an important way of bringing a species-level consideration to the study of whole ecological networks. There are many different indices of topological importance, including centrality indices, but it is likely that a small number are sufficient to explain variation in topological importance. We used 14 indices to describe topological importance of plants and pollinators in 12 quantitative mutualistic (plant–pollinator) networks. The 14 indices varied in their consideration of interaction strength (weighted versus unweighted indices) and indirect interactions (from the local measure of degree to meso-scale indices). We use principal components approximation to assess how well every combination of 1–14 indices approximated to the results of principal components analysis (PCA). We found that one or two indices were sufficient to explain up to 90% of the variation in topological importance in both plants and pollinators. The choice of index was crucial because there was considerable variation between the best and the worst approximating subsets of indices. The best single indices were unweighted degree and unweighted topological importance (Jordán's TI index) with two steps (a measurement of apparent competition). The best pairs of indices consisted of a measure of a TI index and one of closeness centrality (weighted or unweighted) or d′ (a standardised species-level measure of partner diversity). Although we have found indices that efficiently explain variation in topological importance, we recommend further research to discover the real-world relevance of different aspects of topological importance to species in ecological networks.     

Dual lattice model of the evolution of facultative symbiosis with continuous Prisoner's Dilemma game

Mutualism is ubiquitous in nature and is thought to have played a key role in the history of life. However, how mutualism could evolve despite being prone to unilateral exploitation is a puzzling question in evolutionary ecology. Some theoretical studies have shown that spatial structure of habitat can facilitate the emergence and maintenance of mutualism. However, they are based on the simple assumption that the trait in question is discrete: each individual is either a mutualist or a non-mutualist. In this article I develop a simple simulation model of coevolution of facultative symbiosis using a one-shot continuous Prisoner's Dilemma game to investigate the evolutionary dynamics of mutualism between two species. In this model I assume continuous traits for both species from -1 (fully deceptive) to 1 (fully cooperative). The habitat has a dual-lattice structure, each layer is inhabited by one species. Interspecific interaction is restricted between two corresponding sites of the two layers. Without limitation on the magnitude of a single mutation, I find that mutualism can arise and persist when the intrinsic reproduction rate is low (but is above a threshold) and the benefit/cost ratio of the cooperative strategy is large, which is consistent with Yamamura et al. [2004. Evolution of mutualism through spatial effects. J. Theor. Biol. 226, 421-428]. In these cases, extreme antagonism often evolves starting from a neutral population that seems nearly stable, but once mutualism arises, the cooperative individuals quickly increase and both the populations eventually become mutualistic on average, although they are polymorphic. However, when the effect of a single mutation was limited to be small, extreme antagonism is much likely to dominate unless the intrinsic reproduction rate is low. When only one species is allowed to evolve, mutualism arises when the initial strategy of the other species is cooperative. Otherwise, excessive deception evolves in the former, and the latter often becomes driven to extinction.     

Spatial structure of ant–plant mutualistic networks

The structure of mutualistic networks provides insights into ecological and coevolutionary dynamics of interacting species. However, the spatial effect has only recently been incorporated as a factor structuring mutualistic networks. In this study, we evaluated how the topological structure and species turnover of ant–plant mutualistic networks vary over a spatial gradient. We showed that although the ant and plant composition of networks changed over space, the central core of generalist species and the structure of networks remained unaltered on a geographic distance of up to 5099 m in the southern Brazilian Amazon. This finding indicates that independently of variation in local and landscape environmental factors, the nonrandom pattern organization of these interacting assemblages do not change. Finally, we suggest that a stable core can increase the potential for coevolutionary convergence of traits among species from both sides of the interaction within the community. These findings contribute to our understanding of the maintenance of biodiversity and coevolutionary processes.     

Coevolution in temporally variable environments

Many potentially mutualistic interactions are conditional, with selection that varies between mutualism and antagonism over space and time. We develop a genetic model of temporally variable coevolution that incorporates stochastic fluctuations between mutualism and antagonism. We use this model to determine conditions necessary for the coevolution of matching traits between a host and a conditional mutualist. Using an analytical approximation, we show that matching traits will coevolve when the geometric mean interaction is mutualistic. When this condition does not hold, polymorphism and trait mismatching are maintained, and coevolutionary cycles may result. Numerical simulations verify this prediction and suggest that it remains robust in the presence of temporal autocorrelation. These results are compared with those from spatial models with unrestricted movement. The comparisons demonstrate that gene flow is unnecessary for generating empirical patterns predicted by the geographic mosaic theory of coevolution.     

Partitioning the effects of deterministic and stochastic processes on species extinction risk

Species populations are subjected to deterministic and stochastic processes, both of which contribute to their risk of extinction. However, current understanding of the relative contributions of these processes to species extinction risk is far from complete. Here, we address this knowledge gap by analyzing a suite of models representing species populations with negative intrinsic growth rates, to partition extinction risk according to deterministic processes and two broad classes of stochastic processes – demographic and environmental variance. Demographic variance refers to random variations in population abundance arising from random sampling of events given a particular set of intrinsic demographic rates, whereas environmental variance refers to random abundance variations arising from random changes in intrinsic demographic rates over time. When the intrinsic growth rate was not close to zero, we found that deterministic growth was the main driver of mean time to extinction, even when population size was small. This contradicts the intuition that demographic variance is always an important determinant of extinction risk for small populations. In contrast, when the intrinsic growth rate was close to zero, stochastic processes exerted substantial negative effects on the mean time to extinction. Demographic variance had a greater effect than environmental variance at low abundances, with the reverse occurring at higher abundances. In addition, we found that the combined effects of demographic and environmental variance were often substantially lower than the sum of their effects in isolation from each other. This sub-additivity indicates redundancy in the way the two stochastic processes increase extinction risk, and probably arises because both processes ultimately increase extinction risk by boosting variation in abundance over time.     

Persistence of mutualisms with bidirectional interactions in a two-species system

In Lotka–Volterra equations (LVEs) of mutualisms, population densities of mutualists will increase infinitely if the mutualisms between them are strong, which is called the divergence problem. In order to avoid the problem, a mutualism system of two species is analyzed in this work. The model is derived from reactions on lattice and has a form similar to that of LVEs. Population densities of species will not increase infinitely because of spatial limitation on the lattice. Stability analysis of the model demonstrates basic mechanisms by which the mutualisms lead to coexistence/extinction of the species. When in coexistence, intermediate mutualistic effect is shown to lead to the maximal density in certain parameter ranges, while a strong or weak mutualistic effect is not so good. Furthermore, the stability analysis exhibits that extremely strong/weak mutualisms will result in extinction of one/both species.