Historical climate‐change influences modularity and nestedness of pollination networks

The structure of species interaction networks is important for species coexistence, community stability and exposure of species to extinctions. Two widespread structures in ecological networks are modularity, i.e. weakly connected subgroups of species that are internally highly interlinked, and nestedness, i.e. specialist species that interact with a subset of those species with which generalist species also interact. Modularity and nestedness are often interpreted as evolutionary ecological structures that may have relevance for community persistence and resilience against perturbations, such as climate‐change. Therefore, historical climatic fluctuations could influence modularity and nestedness, but this possibility remains untested. This lack of research is in sharp contrast to the considerable efforts to disentangle the role of historical climate‐change and contemporary climate on species distributions, richness and community composition patterns. Here, we use a global database of pollination networks to show that historical climate‐change is at least as important as contemporary climate in shaping modularity and nestedness of pollination networks. Specifically, on the mainland we found a relatively strong negative association between Quaternary climate‐change and modularity, whereas nestedness was most prominent in areas having experienced high Quaternary climate‐change. On islands, Quaternary climate‐change had weak effects on modularity and no effects on nestedness. Hence, for both modularity and nestedness, historical climate‐change has left imprints on the network structure of mainland communities, but had comparably little effect on island communities. Our findings highlight a need to integrate historical climate fluctuations into eco‐evolutionary hypotheses of network structures, such as modularity and nestedness, and then test these against empirical data. We propose that historical climate‐change may have left imprints in the structural organisation of species interactions in an array of systems important for maintaining biological diversity.     

Abundance and generalisation in mutualistic networks: solving the chicken‐and‐egg dilemma

A frequent observation in plant–animal mutualistic networks is that abundant species tend to be more generalised, interacting with a broader range of interaction partners than rare species. Uncovering the causal relationship between abundance and generalisation has been hindered by a chicken‐and‐egg dilemma: is generalisation a by‐product of being abundant, or does high abundance result from generalisation? Here, we analyse a database of plant–pollinator and plant–seed disperser networks, and provide strong evidence that the causal link between abundance and generalisation is uni‐directional. Specifically, species appear to be generalists because they are more abundant, but the converse, that is that species become more abundant because they are generalists, is not supported by our analysis. Furthermore, null model analyses suggest that abundant species interact with many other species simply because they are more likely to encounter potential interaction partners.     

Abundance and nestedness in interaction networks

Nestedness is a useful metric that characterizes the generalist–specialist balance in ecological communities. Although several nestedness indices have been proposed, few have explored how species abundance per se affects their performance and the ability to detect true interaction networks. We here develop a mathematical framework that takes into account abundance in estimates of nestedness. We use an analytical approach to relate abundance and nestedness. In our null model the probability of interaction among species is determined solely as function of their abundances. Assuming a power-law abundance model we analytically find the nestedness index and its coefficient of variability. We find that the sloping abundance distribution of our null model generates more nested structures. On the other hand steeper abundances lead to higher coefficients of variability. Both results suggest that nestedness analysis should be evaluated and explanations sought carefully.     

Finding NEMO: nestedness engendered by mutualistic organization in anemonefish and their hosts

The interaction structure of mutualistic relationships, in terms of relative specialization of the partners, is important to understanding their ecology and evolution. Analyses of the mutualistic interaction between anemonefish and their host sea anemones show that the relationship is highly nested in structure, generalist species interacting with one another and specialist species interacting mainly with generalists. This supports the hypothesis that the configuration of mutualistic interactions will tend towards nestedness. In this case, the structure of the interaction is at a much larger scale than previously hypothesized, across more than 180 degrees of longitude and some 60 degrees of latitude, probably owing to the pelagic dispersal capabilities of these species in a marine environment. Additionally, we found weak support for the hypothesis that geographically widespread species should be more generalized in their interactions than species with small ranges. This study extends understanding of the structure of mutualistic relationships into previously unexplored taxonomic and physical realms, and suggests how nestedness analysis can be applied to the conservation of obligate species interactions.     

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.     

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.     

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.     

Structure–stability relationships in networks combining mutualistic and antagonistic interactions

The relationship between the structure of ecological networks and community stability has been studied for decades. Recent developments highlighted that this relationship depended on whether interactions were antagonistic or mutualistic. Different structures promoting stability in different types of ecological networks, i.e. mutualistic or antagonistic, have been pointed out. However, these findings come from studies considering mutualistic and antagonistic interactions separately whereas we know that species are part of both types of networks simultaneously. Understanding the relationship between network structure and community stability, when mutualistic and antagonistic interactions are merged in a single network, thus appears as the next challenge to improve our understanding of the dynamics of natural communities. Using a theoretical approach, we test whether the structural characteristics known to promote stability in networks made of a single interaction type still hold for network merging mutualistic and antagonistic interactions. We show that the effects of diversity and connectance remain unchanged. But the effects of nestedness and modularity are strongly weakened in networks combining mutualistic and antagonistic interactions. By challenging the stabilizing mechanisms proposed for networks with a single interaction type, our study calls for new measures of structure for networks that integrate the diversity of interaction.     

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.     

Digest: Process‐based phylogenetic models provide unique insights into the evolution of mutualistic networks*

Figs and their pollinating fig wasps are a classic example of long‐term obligate associations between different species. Satler et al. use a process‐based model adopted from molecular evolution to identify the major processes that affect cophylogenetic matching between figs and fig wasps. They find that host‐switching is one of the most important evolutionary processes contributing to current cophylogenetic patterns, illustrating the value of probabilistic approaches to studying the evolutionary history of mutualisms.     

Trait-mediated interaction leads to structural emergence in mutualistic networks

As asymmetric structures of mutualistic networks can potentially contribute to system resilience, elucidating drivers behind the emergence of particular network architectures remains a major endeavour in ecology. Here, using an eco-evolutionary model for bipartite mutualistic networks with trait-mediated interactions, we explore how particular levels of connectance, nestedness and modularity are affected by three network assembly forces: resource accessibility, tolerance to trait difference between mutualistic pairs and competition intensity. We found that a moderate accessibility to intra-trophic resources and cross-trophic mutualistic support can result in a highly nested web, while low tolerance to trait difference between interacting pairs leads to a high level of modularity. Network-level trait complementarity leads to low connectance and high modularity, while network-level specialization can result in nested structures. Consequently, we argue that the interplay of ecological and evolutionary processes through trait-mediated interactions can explain these widely observed architectures in mutualistic networks.     

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.     

Habitat loss and the structure of plant-animal mutualistic networks

Recent papers have described the structure of plant–animal mutualistic networks. However, no study has yet explored the dynamical implications of network structure for the persistence of such mutualistic communities. Here, we develop a patch-model of a whole plant–animal community and explore its persistence. To assess the role of network structure, we build three versions of the model. In the first version, we use the exact network of interactions of two real mutualistic communities. In the other versions, we randomize the observed network of interactions using two different null models. We show that the community response to habitat loss is affected by network structure. Real communities start to decay sooner than random communities, but persist for higher destruction levels. There is a destruction threshold at which the community collapses. Our model is the first attempt to describe the dynamics of whole mutualistic metacommunities interacting in realistic ways.     

A comprehensive framework for the study of species co‐occurrences,nestedness and turnover

Binary presence–absence matrices (rows = species, columns = sites) are often used to quantify patterns of species co‐occurrence, and to infer possible biotic interactions from these patterns. Previous classifications of co‐occurrence patterns as nested, segregated, or modular have led to contradictory results and conclusions. These analyses usually do not incorporate the functional traits of the species or the environmental characteristics of the sites, even though the outcomes of species interactions often depend on trait expression and site quality. Here we address this shortcoming by developing a method that incorporates realized functional and environmental niches, and relates them to species co‐occurrence patterns. These niches are defined from n‐dimensional ellipsoids, and calculated from the n eigenvectors and eigenvalues of the variance–covariance matrix of measured environmental or trait variables. Average niche overlap among species and the spatial distribution of niches define a triangle plot with vertices of species segregation (low niche overlap), nestedness (high niche overlap), and modular co‐occurrence (clusters of overlapping niches). Applying this framework to temperate understorey plant communities in southwest Poland, we found a consistent modular structure of species occurrences, a pattern not detected by conventional presence–absence analysis. These results suggest that, in our case study, habitat filtering is the most important process structuring understorey plant communities. Furthermore, they demonstrate how incorporating trait and environmental data into co‐occurrence analysis improves pattern detection and provides a stronger theoretical framework for understanding community structure.