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.     

Degree distribution in plant–animal mutualistic networks: forbidden links or random interactions?

Recent studies show that ecological interaction networks depart from the "scale-free" topologies observed in many other real world networks. Such a departure has been hypothesized to result from non-matching biological attributes of species, such as phenology or morphology, that prevent the occurrence of certain interactions ("forbidden links"). Here I compare the topology of 17 plant–animal mutualistic networks with that predicted by a simple null model that assumes that a species' degree (number of interspecific interactions) is a function of its frequency of interaction. The topology predicted by this null model is strikingly close to that observed in the real networks. Thus, this null model provides a simple alternative interpretation of patterns observed in ecological interaction networks that does not require the existence of non-matching species traits.     

Seeing through the static: the temporal dimension of plant–animal mutualistic interactions

Most studies of plant–animal mutualistic networks have come from a temporally static perspective. This approach has revealed general patterns in network structure, but limits our ability to understand the ecological and evolutionary processes that shape these networks and to predict the consequences of natural and human‐driven disturbance on species interactions. We review the growing literature on temporal dynamics of plant–animal mutualistic networks including pollination, seed dispersal and ant defence mutualisms. We then discuss potential mechanisms underlying such variation in interactions, ranging from behavioural and physiological processes at the finest temporal scales to ecological and evolutionary processes at the broadest. We find that at the finest temporal scales (days, weeks, months) mutualistic interactions are highly dynamic, with considerable variation in network structure. At intermediate scales (years, decades), networks still exhibit high levels of temporal variation, but such variation appears to influence network properties only weakly. At the broadest temporal scales (many decades, centuries and beyond), continued shifts in interactions appear to reshape network structure, leading to dramatic community changes, including loss of species and function. Our review highlights the importance of considering the temporal dimension for understanding the ecology and evolution of complex webs of mutualistic interactions.     

Does asymmetric specialization differ between mutualistic and trophic networks?

Recently, plant–pollinator networks have been found to be highly structured in a nested pattern in which specialists interact with generalist species. This structure is often assumed to be particular to mutualistic interactions in opposition to the compartmentalized pattern expected for antagonistic networks. We investigated the presence of asymmetric specialization in a data set assembled from the literature of 20 highly resolved plant–insect herbivore networks and compared them with 24 plant–pollinator networks. Our results indicate that these two types of networks differ, but not in the way it is generally assumed. Asymmetric specialization is present in plant–herbivore networks even if it appears less frequently than in plant–pollinator networks. Indeed, mean and median percentages of species showing asymmetric specialisation in herbivory webs are 33% and 14% respectively, compared to 57% and 60% in pollination webs. Furthermore, the amount of asymmetry is linked with species diversity and not to connectance in plant-pollinator networks whereas the opposite pattern is found in plant–herbivore networks. Our results offer promising perspectives for understanding both the mechanisms that structure ecological communities and their impact on community dynamics depending on the type of interaction.     

Biology,Methodology or Chance? The Degree Distributions of Bipartite Ecological Networks

The distribution of the number of links per species, or degree distribution, is widely used as a summary of the topology of complex networks. Degree distributions have been studied in a range of ecological networks, including both mutualistic bipartite networks of plants and pollinators or seed dispersers and antagonistic bipartite networks of plants and their consumers. The shape of a degree distribution, for example whether it follows an exponential or power-law form, is typically taken to be indicative of the processes structuring the network. The skewed degree distributions of bipartite mutualistic and antagonistic networks are usually assumed to show that ecological or co-evolutionary processes constrain the relative numbers of specialists and generalists in the network. I show that a simple null model based on the principle of maximum entropy cannot be rejected as a model for the degree distributions in most of the 115 bipartite ecological networks tested here. The model requires knowledge of the number of nodes and links in the network, but needs no other ecological information. The model cannot be rejected for 159 (69%) of the 230 degree distributions of the 115 networks tested. It performed equally well on the plant and animal degree distributions, and cannot be rejected for 81 (70%) of the 115 plant distributions and 78 (68%) of the animal distributions. There are consistent differences between the degree distributions of mutualistic and antagonistic networks, suggesting that different processes are constraining these two classes of networks. Fit to the MaxEnt null model is consistently poor among the largest mutualistic networks. Potential ecological and methodological explanations for deviations from the model suggest that spatial and temporal heterogeneity are important drivers of the structure of these large networks.     

Plant species with the trait of continuous flowering do not hold core roles in a Neotropical lowland plant‐pollinating insect network

Plant–animal interaction science repeatedly finds that plant species differ by orders of magnitude in the number of interactions they support. The identification of plant species that play key structural roles in plant–animal networks is a global conservation priority; however, in hyperdiverse systems such as tropical forests, empirical datasets are scarce. Plant species with longer reproductive seasons are posited to support more interactions compared to plant species with shorter reproductive seasons but this hypothesis has not been evaluated for plant species with the longest reproductive season possible at the individual plant level, the continuous reproductive phenology. Resource predictability is also associated with promoting specialization, and therefore, continuous reproduction may instead favor specialist interactions. Here, we use quantitative pollinating insect–plant networks constructed from countryside habitat of the Tropical Wet forest Life Zone and modularity analysis to test whether plant species that share the trait of continuous flowering hold core roles in mutualistic networks. With a few exceptions, most plant species sampled within our network were assigned to the role of peripheral. All but one network had significantly high modularity scores and each continuous flowering plant species was in a different module. Our work reveals that the continuous flowering plant species differed in some networks in their topological role, and that more evidence was found for the phenology to support specialized subsets of interactions. Our findings suggest that the conservation of Neotropical pollinating insect communities may require planting species from each module rather than identifying and conserving network hubs.     

Invariant properties in coevolutionary networks of plant–animal interactions

Plant–animal mutualistic networks are interaction webs consisting of two sets of entities, plant and animal species, whose evolutionary dynamics are deeply influenced by the outcomes of the interactions, yielding a diverse array of coevolutionary processes. These networks are two‐mode networks sharing many common properties with others such as food webs, social, and abiotic networks. Here we describe generalized patterns in the topology of 29 plant–pollinator and 24 plant–frugivore networks in natural communities. Scale‐free properties have been described for a number of biological, social, and abiotic networks; in contrast, most of the plant–animal mutualistic networks (65.6%) show species connectivity distributions (number of links per species) with a power‐law regime but decaying as a marked cut‐off, i.e. truncated power‐law or broad‐scale networks and few (22.2%) show scale‐invariance. We hypothesize that plant–animal mutualistic networks follow a build‐up process similar to complex abiotic nets, based on the preferential attachment of species. However, constraints in the addition of links such as morphological mismatching or phenological uncoupling between mutualistic partners, restrict the number of interactions established, causing deviations from scale‐invariance. This reveals generalized topological patterns characteristic of self‐organized complex systems. Relative to scale‐invariant networks, such constraints may confer higher robustness to the loss of keystone species that are the backbone of these webs.     

Congruence between visitation and pollen-transport networks in a California plant–pollinator community

Most recent studies describing pollination networks are based on observed flower visits, and few have explicitly tested if the floral visitors actually carry pollen. Since floral visitors can vary in their ability to remove and transfer pollen, it is important to show that visitation patterns reflect effective pollination. Given the difficulty of measuring per-visit pollen deposition at the community scale, a first step is to examine the amount of conspecific pollen carried by insect visitors. Here I compared the plant–animal visitation network with the pollen-transport network, estimated from insect pollen loads, for a montane meadow community from southern California, USA. Visitation and pollen-transport networks were positively associated with each other in both 2001 and 2002. However, the exclusion of visitors that do not carry any conspecific pollen reveals that pollen-transport networks are more specialized from the plants' perspective and that species are involved in fewer mutualistic interactions compared with estimates derived from visitation frequencies. Although conspecific pollen loads were smaller in 2002, bees tended to carry the largest conspecific loads in both years and were responsible for transporting the most pollen. These results suggest that, although visitation networks are suitable first-order approximations of pollination networks, information on which visitors carry conspecific pollen, and in what amounts, is crucial for distinguishing between antagonistic and mutualistic interactions.     

Habitat loss and the disassembly of mutalistic networks

Recent studies have described the architecture of plant–animal mutualistic networks, but little is known on how such networks disassemble as a consequence of global change. This is a relevant question because 1) species interactions seem to be very susceptible to habitat loss, and 2) the loss of a critical fraction of interactions can abruptly change the topology of the entire network with potential consequences for its functioning. Here we develop a spatially explicit metacommunity model based on the structure of 30 real mutualistic networks. We find that there is a critical value of habitat destruction beyond which interactions are lost very fast. Second, there is a homogeneous distribution of the number of interactions per patch when the habitat is pristine, while this becomes very skewed at the brink of extinction. This increase in skewness is discussed in the context of potential indicators of network collapse.     

Structure of a plant–flower-visitor network in the high-altitude sub-alpine desert of Tenerife, Canary Islands

Confined within a volcanic caldera at 2000 m a.s.l., the sub-alpine desert of Tenerife, Canary Islands, harbors a distinct biota. At this altitude the climate is harsh and the growing season short. Hence, plant and animal communities, constituting the sub-alpine plant–flower-visitor network, are clearly delimited, both spatially and temporally. We investigated species composition and interaction structure of this system. A total of 11 plant species (91% endemics) and 37 flower-visiting animal species (62% endemics) formed 108 interactions. Numbers of interactions among species varied ten-fold within both plant and animal communities. Generalization level of a species was positively correlated with its local abundance. Two separate network analyses revealed a significantly nested structure. In relation to a plant–flower-visitor system, nestedness implies that specialized species (animals or plants) interact with a subset of the species pool visiting (animals) or being visited (plants) by more generalized species. Therefore, specialized, locally rare plants tend to be visited by generalized, locally abundant animals, and specialized, locally rare animals tend to utilize generalized, locally abundant food plants. Such patterns could have implications for conservation of the sub-alpine network, and stress the importance of preserving not only rare species, but also the more abundant ones, which may be key food resources or pollinators in the plant–flower-visitor network.     

Incorporating seed fate into plant–frugivore networks increases interaction diversity across plant regeneration stages

Plant–animal mutualistic interactions, such as pollination and seed dispersal, affect ecosystem functioning by driving plant population dynamics. However, little is known of how the diversity of interactions in these mutualistic networks determines plant regeneration dynamics. To fill this gap, interaction networks should not only account for the number of seeds dispersed by animals, but also for seed fate after dispersal. Here, we compare plant–animal networks at both the seed dispersal and seedling recruitment stage to evaluate how interaction diversity, represented by different network metrics, changes throughout the process of plant regeneration. We focused on a system with six species of frugivorous birds and three species of fleshy‐fruited trees in the temperate secondary forest of the Cantabrian Range (northern Iberian Peninsula). We considered two plant cohorts corresponding to two fruiting years showing strong differences in fruit and frugivore abundance. Seed dispersal interactions were estimated from a spatially‐explicit, field‐validated model predicting tree and bird species‐specific seed deposition in different microhabitats. These interactions were further transformed into interactions at the seedling recruitment stage by accounting for plant‐ and microhabitat‐specific seed fates estimated from field sampling. We found that network interaction diversity varied across plant regeneration stages and cohorts, both in terms of the evenness and the number of paired interactions. Tree–bird interactions were more evenly distributed across species pairs at the recruitment stage than at the seed deposition stage, although some interactions disappeared in the seed‐to‐seedling transition for one plant cohort. The variations in interaction diversity were explained by between‐plant differences in post‐dispersal seed fate and in inter‐annual fruit production, rather than by differences between frugivores in seed deposition patterns. These results highlight the need for integrating plant traits and disperser quality to predict the functional outcome of plant–animal mutualistic networks.     

Diversity in a complex ecological network with two interaction types

Most studies on ecological networks consider only a single interaction type (e.g. competitive, predatory or mutualistic), and try to developrules for system stability based exclusively on properties of this interaction type. However, the stability of ecological networks may be more dependent on the way different interaction types are combined in real communities. To address this issue, we start by compiling an ecological network in the Doñana Biological Reserve, southern Spain, with 390 species and 798 mu-tualistic and antagonistic interactions. We characterize network structure by looking at how mutualistic and antagonistic interactions are combined across all plant species. Both the ratio of mutualistic to antagonistic interactions per plant, and the number of basic modules with an antagonistic and a mutualistic interaction are very heterogeneous across plant species, with a few plant species showing very high values for these parameters. To assess the implications of these network patterns on species diversity, we study analytically and by simulation a model of this ecological network. We find that the observed correlation between strong interaction strengths and high mutualistic to antagonistic ratios in a few plant species significantly increases community diversity. Thus, to predict the persistence of biodiversity we need to understand how interaction strength and the architecture of ecological networks with different interaction types are combined.     

Plant–mycorrhizal fungus co‐occurrence network lacks substantial structure

The interactions between plants and arbuscular mycorrhizal fungi (AMF) maintain a crucial link between macroscopic organisms and the soil microbial world. These interactions are of extreme importance for the diversity of plant communities and ecosystem functioning. Despite this importance, only recently has the structure of plant–AMF interaction networks been studied. These recent studies, which used genetic data, suggest that these networks are highly structured, very similar to plant–animal mutualistic networks. However, the assembly process of plant–AMF communities is still largely unknown, and an important feature of plant–AMF interactions has not been incorporated: they occur at an extremely localized scale. Studying plant–AMF networks in a spatial context seems therefore a crucial step. This paper studies a plant–AMF spatial co‐occurrence network using novel methodology based on information theory and a unique set of spatially explicit species‐level data. We apply three null models of which only one accounts for spatial effects. We find that the data show substantial departures from null expectations for the two non‐spatial null models. However, for the null model considering spatial effects, there are few significant co‐occurrences compared with the other two null models. Thus, plant–AMF spatial co‐occurrences seem to be mostly explained by stochasticity, with a small role for other factors related to plant–AMF specialization. Furthermore, we find that the network is not significantly nested or modular. We conclude that this plant–AMF spatial co‐occurrence network lacks substantial structure and, therefore, plants and AMF species do not track each other over space. Thus, random encounters seem more important in the first step of the assembly of plant–AMF communities. Synthesis The symbiotic interaction between plants and arbuscular mycorrhizal fungi (AMF) is crucial for ecosystem functioning. However, the factors affecting the assembly of plant‐AMF communities are poorly understood. An important factor of the assembly of plant‐AMF communities has been overlooked: plant‐AMF interactions occur at a localized spatial scale. Our study investigated the importance of space in the structure of plant‐AMF communities. We studied a plant‐AMF spatial co‐occurrence network using a unique set of spatially explicit data and applied three null models. We found that plant‐AMF spatial co‐occurrences seem to be mostly explained by stochasticity. In particular, our study shows that this plant‐AMF spatial co‐occurrence network lacks substantial structure and, therefore, plants and AMF species do not track each other over space. Thus, random encounters seem to drive the assembly of plant‐AMF communities.     

Do extrafloral nectar resources, species abundances, and body sizes contribute to the structure of ant–plant mutualistic networks?

Recent research has shown that many mutualistic communities display non-random structures. While our understanding of the structural properties of mutualistic communities continues to improve, we know little of the biological variables resulting in them. Mutualistic communities include those formed between ants and extrafloral (EF) nectar-bearing plants. In this study, we examined the contributions of plant and ant abundance, plant and ant size, and plant EF nectar resources to the network structures of nestedness and interaction frequency of ant–plant networks across five sites within one geographic locality in the Sonoran Desert. Interactions between ant and plant species were largely symmetric. That is, ant and plant species exerted nearly equivalent quantitative interaction effects on one another, as measured by their frequency of interaction. The mutualistic ant–plant networks also showed nested patterns of structure, in which there was a central core of generalist ant and plant species interacting with one another and few specialist–specialist interactions. Abundance and plant size and ant body size were the best predictors of symmetric interactions between plants and ants, as well as nestedness. Despite interactions in these communities being ultimately mediated by EF nectar resources, the number of EF nectaries had a relatively weak ability to explain variation in symmetric interactions and nestedness. These results suggest that different mechanisms may contribute to structure of bipartite networks. Moreover, our results for ant–plant mutualistic networks support the general importance of species abundances for the structure of species interactions within biological communities.     

Plant–pollinator networks: adding the pollinator's perspective

Pollination network studies are based on pollinator surveys conducted on focal plants. This plant-centred approach provides insufficient information on flower visitation habits of rare pollinator species, which are the majority in pollinator communities. As a result, pollination networks contain very high proportions of pollinator species linked to a single plant species (extreme specialists), a pattern that contrasts with the widely accepted view that plant–pollinator interactions are mostly generalized. In this study of a Mediterranean scrubland community in NE Spain we supplement data from an intensive field survey with the analysis of pollen loads carried by pollinators. We observed 4265 contacts corresponding to 19 plant and 122 pollinator species. The addition of pollen data unveiled a very significant number of interactions, resulting in important network structural changes. Connectance increased 1.43-fold, mean plant connectivity went from 18.5 to 26.4, and mean pollinator connectivity from 2.9 to 4.1. Extreme specialist pollinator species decreased 0.6-fold, suggesting that ecological specialization is often overestimated in plant–pollinator networks. We expected a greater connectivity increase in rare species, and consequently a decrease in the level of asymmetric specialization. However, new links preferentially attached to already highly connected nodes and, as a result, both nestedness and centralization increased. The addition of pollen data revealed the existence of four clearly defined modules that were not apparent when only field survey data were used. Three of these modules had a strong phenological component. In comparison to other pollination webs, our network had a high proportion of connector links and species. That is, although significant, the four modules were far from isolated.     

Analysis and assembling of network structure in mutualistic systems

It has been observed that mutualistic bipartite networks have a nested structure of interactions. In addition, the degree distributions associated with the two guilds involved in such networks (e.g., plants and pollinators or plants and seed dispersers) approximately follow a truncated power law (TPL). We show that nestedness and TPL distributions are intimately linked, and that any biological reasons for such truncation are superimposed to finite size effects. We further explore the internal organization of bipartite networks by developing a self-organizing network model (SNM) that reproduces empirical observations of pollination systems of widely different sizes. Since the only inputs to the SNM are numbers of plant and animal species, and their interactions (i.e., no data on local abundance of the interacting species are needed), we suggest that the well-known association between species frequency of interaction and species degree is a consequence rather than a cause, of the observed network structure.     

Accumulation of local pathogens: a new hypothesis to explain exotic plant invasions

Recent studies have concluded that release from native soil pathogens may explain invasion of exotic plant species. However, release from soil enemies does not explain all plant invasions. The invasion of Ammophila arenaria (marram grass or European beach grass) in California provides an illustrative example for which the enemy release hypothesis has been refuted. To explore the possible role of plant–soil community interactions in this invasion, we developed a mathematical model. First, we analyzed the role of plant–soil community interactions in the succession of A. arenaria in its native range (north-western Europe). Then, we used our model to explore for California how alternative plant–soil community interactions may generate the same effect as if A. arenaria were released from soil enemies. This analysis was carried out by construction of a 'recovery plane' that discriminates between plant competition and plant–soil community interactions. Our model shows that in California, the accumulation of local pathogens by A. arenaria could result in exclusion of native plant species. Moreover, this mechanism could trigger the rate and spatial pattern of invasive spread generally observed in nature. We propose that our 'accumulation of local pathogens' hypothesis could serve as an alternative explanation for the enemy release hypothesis to be considered in further experimental studies on invasive plant species.     

Top‐down network analysis characterizes hidden termite–termite interactions

The analysis of ecological networks is generally bottom‐up, where networks are established by observing interactions between individuals. Emergent network properties have been indicated to reflect the dominant mode of interactions in communities that might be mutualistic (e.g., pollination) or antagonistic (e.g., host–parasitoid communities). Many ecological communities, however, comprise species interactions that are difficult to observe directly. Here, we propose that a comparison of the emergent properties from detail‐rich reference communities with known modes of interaction can inform our understanding of detail‐sparse focal communities. With this top‐down approach, we consider patterns of coexistence between termite species that live as guests in mounds built by other host termite species as a case in point. Termite societies are extremely sensitive to perturbations, which precludes determining the nature of their interactions through direct observations. We perform a literature review to construct two networks representing termite mound cohabitation in a Brazilian savanna and in the tropical forest of Cameroon. We contrast the properties of these cohabitation networks with a total of 197 geographically diverse mutualistic plant–pollinator and antagonistic host–parasitoid networks. We analyze network properties for the networks, perform a principal components analysis (PCA), and compute the Mahalanobis distance of the termite networks to the cloud of mutualistic and antagonistic networks to assess the extent to which the termite networks overlap with the properties of the reference networks. Both termite networks overlap more closely with the mutualistic plant–pollinator communities than the antagonistic host–parasitoid communities, although the Brazilian community overlap with mutualistic communities is stronger. The analysis raises the hypothesis that termite–termite cohabitation networks may be overall mutualistic. More broadly, this work provides support for the argument that cryptic communities may be analyzed via comparison to well‐characterized communities.     

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.     

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.