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.     

Detecting phylogenetic signal in mutualistic interaction networks using a Markov process model

Ecological interaction networks, such as those describing the mutualistic interactions between plants and their pollinators or between plants and their frugivores, exhibit non‐random structural properties that cannot be explained by simple models of network formation. One factor affecting the formation and eventual structure of such a network is its evolutionary history. We argue that this, in many cases, is closely linked to the evolutionary histories of the species involved in the interactions. Indeed, empirical studies of interaction networks along with the phylogenies of the interacting species have demonstrated significant associations between phylogeny and network structure. To date, however, no generative model explaining the way in which the evolution of individual species affects the evolution of interaction networks has been proposed. We present a model describing the evolution of pairwise interactions as a branching Markov process, drawing on phylogenetic models of molecular evolution. Using knowledge of the phylogenies of the interacting species, our model yielded a significantly better fit to 21% of a set of plant–pollinator and plant–frugivore mutualistic networks. This highlights the importance, in a substantial minority of cases, of inheritance of interaction patterns without excluding the potential role of ecological novelties in forming the current network architecture. We suggest that our model can be used as a null model for controlling evolutionary signals when evaluating the role of other factors in shaping the emergence of ecological networks.     

Evolution and coevolution in mutualistic networks

A major current challenge in evolutionary biology is to understand how networks of interacting species shape the coevolutionary process. We combined a model for trait evolution with data for twenty plant-animal assemblages to explore coevolution in mutualistic networks. The results revealed three fundamental aspects of coevolution in species-rich mutualisms. First, coevolution shapes species traits throughout mutualistic networks by speeding up the overall rate of evolution. Second, coevolution results in higher trait complementarity in interacting partners and trait convergence in species in the same trophic level. Third, convergence is higher in the presence of super-generalists, which are species that interact with multiple groups of species. We predict that worldwide shifts in the occurrence of super-generalists will alter how coevolution shapes webs of interacting species. Introduced species such as honeybees will favour trait convergence in invaded communities, whereas the loss of large frugivores will lead to increased trait dissimilarity in tropical ecosystems.     

Asymmetries in specialization in ant-plant mutualistic networks

Mutualistic networks involving plants and their pollinators or frugivores have been shown recently to exhibit a particular asymmetrical organization of interactions among species called nestedness: a core of reciprocal generalists accompanied by specialist species that interact almost exclusively with generalists. This structure contrasts with compartmentalized assemblage structures that have been verified in antagonistic food webs. Here we evaluated whether nestedness is a property of another type of mutualism-the interactions between ants and extrafloral nectary-bearing plants--and whether species richness may lead to differences in degree of nestedness among biological communities. We investigated network structure in four communities in Mexico. Nested patterns in ant-plant networks were very similar to those previously reported for pollination and frugivore systems, indicating that this form of asymmetry in specialization is a common feature of mutualisms between free-living species, but not always present in species-poor systems. Other ecological factors also appeared to contribute to the nested asymmetry in specialization, because some assemblages showed more extreme asymmetry than others even when species richness was held constant. Our results support a promising approach for the development of multispecies coevolutionary theory, leading to the idea that specialization may coevolve in different but simple ways in antagonistic and mutualistic assemblages.     

Missing and forbidden links in mutualistic networks

Ecological networks are complexes of interacting species, but not all potential links among species are realized. Unobserved links are either missing or forbidden. Missing links exist, but require more sampling or alternative ways of detection to be verified. Forbidden links remain unobservable, irrespective of sampling effort. They are caused by linkage constraints. We studied one Arctic pollination network and two Mediterranean seed-dispersal networks. In the first, for example, we recorded flower-visit links for one full season, arranged data in an interaction matrix and got a connectance C of 15 per cent. Interaction accumulation curves documented our sampling of interactions through observation of visits to be robust. Then, we included data on pollen from the body surface of flower visitors as an additional link ‘currency’. This resulted in 98 new links, missing from the visitation data. Thus, the combined visit–pollen matrix got an increased C of 20 per cent. For the three networks, C ranged from 20 to 52 per cent, and thus the percentage of unobserved links (100 − C) was 48 to 80 per cent; these were assumed forbidden because of linkage constraints and not missing because of under-sampling. Phenological uncoupling (i.e. non-overlapping phenophases between interacting mutualists) is one kind of constraint, and it explained 22 to 28 per cent of all possible, but unobserved links. Increasing phenophase overlap between species increased link probability, but extensive overlaps were required to achieve a high probability. Other kinds of constraint, such as size mismatch and accessibility limitations, are briefly addressed.     

Peptides mediating interaction networks: new leads at last

A growing number of protein interactions are found to be mediated by a large globular region in one protein binding to a comparatively short, peptide stretch in another. Regions that bind a common protein often show a similar sequence pattern or linear motif that mediates the binding. The past year has seen reports of new techniques that can uncover these motifs directly from interaction data. These studies have suggested that the fraction of interactions mediated by these regions is greater than previously anticipated. Concurrently, other work has demonstrated that it is possible to target these interactions using small molecules. Together these developments hold great promise for future efforts to target chemically precise details of complex systems.     

Coevolution can stabilize a mutualistic interaction

Interspecific mutualisms are ubiquitous in nature, despite their ecological and evolutionary instability. Recent studies have developed coevolutionary theory of mutualisms, which coupled population and evolutionary dynamics, to resolve the longstanding puzzle. However, earlier studies assumed a time-scale separation between these dynamics, leaving an unanswered question of how a relaxation in the time-scale separation affects the coevolutionary dynamics of mutualism. Here I relax the strong assumption to theoretically show that ecological and evolutionary dynamics occurring in a similar time scale can stabilize an otherwise unstable mutualism. I show that the coevolutionary dynamics can cause a stable limit cycle or stable equilibrium in the population sizes, even if the population sizes increase unbounded in the absence of evolutionary adaptation. In contrast, coevolution can also cause stable limit cycle even if the population dynamics is stable in the absence of evolutionary adaptation. Furthermore, the model predicts that the population dynamics is likely to converge to equilibrium when the evolutionary speed of two species is similar and fast or highly dissimilar. The results suggest that the ease of the evolutionary ‘arms race’ is of crucial importance to maintain mutualism.     

Varieties of mutualistic interaction in population models

A Lotka-Volterra model of mutalism indicates eight possible cases, of which two lead to survival of both populations, two indicate inevitable extinction, and four are indeterminate, the result depending on the initial population sizes. Conventional neighborhood stability analysis is a poor indicator of the biological result expected. Modification of the Lotka-Volterra model to give non-linear isoclines is necessary to obtain a minimum of biological realism; this modified model is illustrated with an analysis of a legume-Rhizobium mutualism.     

The architecture of weighted mutualistic networks

Several ecosystem services directly depend on mutualistic interactions. In species rich communities, these interactions can be studied using network theory. Current knowledge of mutualistic networks is based mainly on binary links; however, little is known about the role played by the weights of the interactions between species. What new information can be extracted by analyzing weighted mutualistic networks? In performing an exhaustive analysis of the topological properties of 29 weighted mutualistic networks, our results show that the generalist species, defined as those with a larger number of interactions in a network, also have the strongest interactions. Though most interactions of generalists are with specialists, the strongest interactions occur between generalists. As a result and by defining binary and weighted clustering coefficients for bipartite networks, we demonstrate that generalists form strongly‐interconnected groups of species. The existence of these strong clusters reinforces the idea that generalist species govern the coevolution of the whole community.     

Fitness consequences of centrality in mutualistic individual-based networks

The relationships among the members of a population can be visualized using individual networks, where each individual is a node connected to each other by means of links describing the interactions. The centrality of a given node captures its importance within the network. We hypothesize that in mutualistic networks, the centrality of a node should benefit its fitness. We test this idea studying eight individual-based networks originated from the interaction between Erysimum mediohispanicum and its flower visitors. In these networks, each plant was considered a node and was connected to conspecifics sharing flower visitors. Centrality indicates how well connected is a given E. mediohispanicum individual with the rest of the co-occurring conspecifics because of sharing flower visitors. The centrality was estimated by three network metrics: betweenness, closeness and degree. The complex relationship between centrality, phenotype and fitness was explored by structural equation modelling. We found that the centrality of a plant was related to its fitness, with plants occupying central positions having higher fitness than those occupying peripheral positions. The structural equation models (SEMs) indicated that the centrality effect on fitness was not merely an effect of the abundance of visits and the species richness of visitors. Centrality has an effect even when simultaneously accounting for these predictors. The SEMs also indicated that the centrality effect on fitness was because of the specific phenotype of each plant, with attractive plants occupying central positions in networks, in relation to the distribution of conspecific phenotypes. This finding suggests that centrality, owing to its dependence on social interactions, may be an appropriate surrogate for the interacting phenotype of individuals.     

Social structure of primate interaction networks facilitates the emergence of cooperation

Animal cooperation has puzzled biologists for a long time as its existence seems to contravene the basic notion of evolutionary biology that natural selection favours ‘selfish’ genes that promote only their own well-being. Evolutionary game theory has shown that cooperators can prosper in populations of selfish individuals if they occur in clusters, interacting more frequently with each other than with the selfish. Here we show that social networks of primates possess the necessary social structure to promote the emergence of cooperation. By simulating evolutionary dynamics of cooperative behaviour on interaction networks of 70 primate groups, we found that for most groups network reciprocity augmented the fixation probability for cooperation. The variation in the strength of this effect can be partly explained by the groups’ community modularity—a network measure for the groups’ heterogeneity. Thus, given selective update and partner choice mechanisms, network reciprocity has the potential to explain socially learned forms of cooperation in primate societies.     

Host switch leads to emergence of Plasmodium vivax malaria in humans

The geographical origin of Plasmodium vivax, the most widespread human malaria parasite, is controversial. Although genetic closeness to Asian primate malarias has been confirmed by phylogenetic analyses, genetic similarities between P. vivax and Plasmodium simium, a New World primate malaria, suggest that humans may have acquired P. vivax from New World monkeys or vice versa. Additionally, the near fixation of the Duffy-negative blood type (FY x B(null)/FY x B(null)) in West and Central Africa, consistent with directional selection, and the association of Duffy negativity with complete resistance to vivax malaria suggest a prolonged period of host-parasite coevolution in Africa. Here we use Bayesian and likelihood methods in conjunction with cophylogeny mapping to reconstruct the genetic and coevolutionary history of P. vivax from the complete mitochondrial genome of 176 isolates as well as several closely related Plasmodium species. Taken together, a haplotype network, parasite migration patterns, demographic history, and cophylogeny mapping support an Asian origin via a host switch from macaque monkeys.     

Trait-mediated diversification in nematode predator-prey systems

Nematodes are presumably the most numerous Metazoans in terrestrial habitats. They are represented at all trophic levels and are known to respond to nutrient limitation, prey availability, and microbial resources. Predatory nematodes reside at the highest trophic level, and as such their feeding habits could have a major impact on soil food web functioning. Here, we investigate the effects of gender and developmental stage on the nematode body sizes in coarse and loamy soils. Besides Neodiplogasteridae, our predators are much larger than other soil-dwelling nematodes from their early developmental stage onwards. From juvenile to adult, the predatory Aporcelaimellus (Kruskal-Wallis P < 0.001), Dorylaimoides, and Tripyla (both P < 0.01) show great length increases during their developmental growth, in contrast to their possible prey (almost all P < 0.001). Less than 4% of the prey exceeds the length of the predatory adults, but more than 30% of the prey exceeds the length of the predatory juveniles. Potential body size ratios and some physical problems experienced by small fluid feeders attacking large prey are discussed in an attempt to summarize different prey-searching mechanisms and aggregative predatory responses in the soil system.     

Build-up mechanisms determining the topology of mutualistic networks

The frequency distribution of the number of interactions per species (i.e., degree distribution) within plant-animal mutualistic assemblages often decays as a power-law with an exponential truncation. Such a truncation suggests that there are ecological factors limiting the frequency of supergeneralist species. However, it is not clear whether these patterns can emerge from intrinsic features of the interacting assemblages, such as differences between plant and animal species richness (richness ratio). Here, we show that high richness ratios often characterize plant-animal mutualisms. Then, we demonstrate that exponential truncations are expected in bipartite networks generated by a simple model that incorporates build-up mechanisms that lead to a high richness ratio. Our results provide a simple interpretation for the truncations commonly observed in the degree distributions of mutualistic networks that complements previous ones based on biological effects.     

Specialization, constraints, and conflicting interests in mutualistic networks

The topology of ecological interaction webs holds important information for theories of coevolution, biodiversity, and ecosystem stability . However, most previous network analyses solely counted the number of links and ignored variation in link strength. Because of this crude resolution, results vary with scale and sampling intensity, thus hampering a comparison of network patterns at different levels . We applied a recently developed quantitative and scale-independent analysis based on information theory to 51 mutualistic plant-animal networks, with interaction frequency as measure of link strength. Most networks were highly structured, deviating significantly from random associations. The degree of specialization was independent of network size. Pollination webs were significantly more specialized than seed-dispersal webs, and obligate symbiotic ant-plant mutualisms were more specialized than nectar-mediated facultative ones. Across networks, the average specialization of animal and plants was correlated, but is constrained by the ratio of plant to animal species involved. In pollination webs, rarely visited plants were on average more specialized than frequently attended ones, whereas specialization of pollinators was positively correlated with their interaction frequency. We conclude that quantitative specialization in ecological communities mirrors evolutionary trade-offs and constraints of web architecture. This approach can be easily expanded to other types of biological interactions.     

The role of disorder in interaction networks: a structural analysis

Recent studies have emphasized the value of including structural information into the topological analysis of protein networks. Here, we utilized structural information to investigate the role of intrinsic disorder in these networks. Hub proteins tend to be more disordered than other proteins (i.e. the proteome average); however, we find this only true for those with one or two binding interfaces (‘single’‐interface hubs). In contrast, the distribution of disordered residues in multi‐interface hubs is indistinguishable from the overall proteome. Surprisingly, we find that the binding interfaces in single‐interface hubs are highly structured, as is the case for multi‐interface hubs. However, the binding partners of single‐interface hubs tend to have a higher level of disorder than the proteome average, suggesting that their binding promiscuity is related to the disorder of their binding partners. In turn, the higher level of disorder of single‐interface hubs can be partly explained by their tendency to bind to each other in a cascade. A good illustration of this trend can be found in signaling pathways and, more specifically, in kinase cascades. Finally, our findings have implications for the current controversy related to party and date‐hubs.     

Interaction intimacy affects structure and coevolutionary dynamics in mutualistic networks

The structure of mutualistic networks provides clues to processes shaping biodiversity [1-10]. Among them, interaction intimacy, the degree of biological association between partners, leads to differences in specialization patterns [4, 11] and might affect network organization [12]. Here, we investigated potential consequences of interaction intimacy for the structure and coevolution of mutualistic networks. From observed processes of selection on mutualistic interactions, it is expected that symbiotic interactions (high-interaction intimacy) will form species-poor networks characterized by compartmentalization [12, 13], whereas nonsymbiotic interactions (low intimacy) will lead to species-rich, nested networks in which there is a core of generalists and specialists often interact with generalists [3, 5, 7, 12, 14]. We demonstrated an association between interaction intimacy and structure in 19 ant-plant mutualistic networks. Through numerical simulations, we found that network structure of different forms of mutualism affects evolutionary change in distinct ways. Change in one species affects primarily one mutualistic partner in symbiotic interactions but might affect multiple partners in nonsymbiotic interactions. We hypothesize that coevolution in symbiotic interactions is characterized by frequent reciprocal changes between few partners, but coevolution in nonsymbiotic networks might show rare bursts of changes in which many species respond to evolutionary changes in a single species.