Plant-animal Mutualistic Networks Research Articles

Loss of functional diversity rather than species diversity of pollinators decreases community‐wide trait matching and pollination function

Abstract Loss of animal species and functional diversity can degrade ecosystem functions and services in plant–animal mutualistic networks, but their relative effects have rarely been previously examined in natural communities. Contrary to previously published theoretical results, under natural conditions, changes in pollinator functional niches caused by species and functional diversity losses are dynamic and often unpredictable. The lack of studies on natural networks limits our ability to predict future effects of decreasing pollinator diversity on wild and cultivated plants. We quantitatively evaluated the relative effects of pollinator species and functional diversity loss on plant–pollinator trait matching and pollination success across 40 spatiotemporally variable coastal networks. We found that low pollinator functional diversity (low abundance of long‐tongued pollinators) reduced community‐level plant functional specialization and trait matching between flowers and pollinators by reducing functional floral‐niche partitioning among pollinators. In contrast, pollinator species diversity did not influence community‐level trait matching. Furthermore, decreasing community‐level trait matching had a negative effect on community‐level plant pollination success, regardless of flower morphology. The present study demonstrated that pollinator functional diversity loss, rather than species diversity loss, was the main factor contributing to pollination functional loss in the plant–pollinator networks studied. We also demonstrated the importance of assessing functional aspects of plant–pollinator networks to evaluate community‐level pollination functional loss under global pollinator decline. Read the free Plain Language Summary for this article on the Journal blog.

Fungal communities in feces of the frugivorous bat Ectophylla alba and its highly specialized Ficus colubrinae diet

BackgroundBats are important long-distance dispersers of many tropical plants, yet, by consuming fruits, they may disperse not only the plant’s seeds, but also the mycobiota within those fruits. We characterized the culture-dependent and independent fungal communities in fruits of Ficus colubrinae and feces of Ectophylla alba to determine if passage through the digestive tract of bats affected the total mycobiota.ResultsUsing presence/absence and normalized abundance data from fruits and feces, we demonstrate that the fungal communities were significantly different, even though there was an overlap of ca. 38% of Amplicon Sequence Variants (ASVs). We show that some of the fungi from fruits were also present and grew from fecal samples. Fecal fungal communities were dominated by Agaricomycetes, followed by Dothideomycetes, Sordariomycetes, Eurotiomycetes, and Malasseziomycetes, while fruit samples were dominated by Dothideomycetes, followed by Sordariomycetes, Agaricomycetes, Eurotiomycetes, and Laboulbeniomycetes. Linear discriminant analyses (LDA) show that, for bat feces, the indicator taxa include Basidiomycota (i.e., Agaricomycetes: Polyporales and Agaricales), and the ascomycetous class Eurotiomycetes (i.e., Eurotiales, Aspergillaceae). For fruits, indicator taxa are in the Ascomycota (i.e., Dothideomycetes: Botryosphaeriales; Laboulbeniomycetes: Pyxidiophorales; and Sordariomycetes: Glomerellales). In our study, the differences in fungal species composition between the two communities (fruits vs. feces) reflected on the changes in the functional diversity. For example, the core community in bat feces is constituted by saprobes and animal commensals, while that of fruits is composed mostly of phytopathogens and arthropod-associated fungi.ConclusionsOur study provides the groundwork to continue disentangling the direct and indirect symbiotic relationships in an ecological network that has not received enough attention: fungi-plants-bats. Findings also suggest that the role of frugivores in plant-animal mutualistic networks may extend beyond seed dispersal: they may also promote the dispersal of potentially beneficial microbial symbionts while, for example, hindering those that can cause plant disease.

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.

Mutualistic networks: moving closer to a predictive theory.

Plant-animal mutualistic networks sustain terrestrial biodiversity and human food security. Global environmental changes threaten these networks, underscoring the urgency for developing a predictive theory on how networks respond to perturbations. Here, I synthesise theoretical advances towards predicting network structure, dynamics, interaction strengths and responses to perturbations. I find that mathematical models incorporating biological mechanisms of mutualistic interactions provide better predictions of network dynamics. Those mechanisms include trait matching, adaptive foraging, and the dynamic consumption and production of both resources and services provided by mutualisms. Models incorporating species traits better predict the potential structure of networks (fundamental niche), while theory based on the dynamics of species abundances, rewards, foraging preferences and reproductive services can predict the extremely dynamic realised structures of networks, and may successfully predict network responses to perturbations. From a theoretician's standpoint, model development must more realistically represent empirical data on interaction strengths, population dynamics and how these vary with perturbations from global change. From an empiricist's standpoint, theory needs to make specific predictions that can be tested by observation or experiments. Developing models using short-term empirical data allows models to make longer term predictions of community dynamics. As more longer term data become available, rigorous tests of model predictions will improve.

Network resilience of mutualistic ecosystems and environmental changes: an empirical study.

It is theorized that a mutualistic ecosystem's resilience against perturbations (e.g. species extinction) is determined by a single macroscopic parameter (network resilience), calculable from the network. Given that such perturbations occur owing to environmental changes (e.g. climate change and human impact), it has been predicted that mutualistic ecosystems that exist despite extensive environmental changes exhibit higher network resilience; however, such a prediction has not been confirmed using real-world data. Thus, in this study, the effects of climate change velocity and human activities on mutualistic network resilience were investigated. A global dataset of plant–animal mutualistic networks was used, and spatial analysis was performed to examine the effects. Moreover, the potential confounding effects of network size, current climate and altitude were statistically controlled. It was demonstrated that mutualistic network resilience was globally influenced by warming velocity and human impact, in addition to current climate. Specifically, pollination network resilience increased in response to human impact, and seed-dispersal network resilience increased with warming velocity. The effect of environmental changes on network resilience for plants was remarkable. The results confirmed the prediction obtained based on the theory and imply that real-world mutualistic networks have a structure that increases ecosystem resilience against environmental changes. These findings will enhance the understanding of ecosystem resilience.

Interaction frequency, network position, and the temporal persistence of interactions in a plant-pollinator network.

Ecological interactions are highly dynamic in time and space. Previous studies of plant-animal mutualistic networks have shown that the occurrence of interactions varies substantially across years. We analyzed interannual variation of a quantitative mutualistic network, in which links are weighted by interaction frequency. The network was sampled over six consecutive years, representing one of the longest time series for a community-wide mutualistic network. We estimated the interannual similarity in interactions and assessed the determinants of their persistence. The occurrence of interactions varied greatly among years, with most interactions seen in only one year (64%) and few (20%) in more than two years. This variation was associated with the frequency and position of interactions relative to the network core, so that the network consisted of a persistent core of frequent interactions and many peripheral, infrequent interactions. Null model analyses suggest that species abundances play a substantial role in generating these patterns. Our study represents an important step in the study of ecological networks, furthering our mechanistic understanding of the ecological processes driving the temporal persistence of interactions.

Geographical variation in the heterogeneity of mutualistic networks.

Plant–animal mutualistic networks are characterized by highly heterogeneous degree distributions. The majority of species interact with few partner species, while a small number are highly connected to form network hubs that are proposed to play an important role in community stability. It has not been investigated, however, if or how the degree distributions vary among types of mutualisms or communities, or between plants and animals in the same network. Here, we evaluate the degree distributions of pollination and seed-dispersal networks, which are two major types of mutualistic networks that have often been discussed in parallel, using an index based on Pielou's evenness. Among 56 pollination networks we found strong negative correlation of the heterogeneity between plants and animals, and geographical shifts of network hubs from plants in temperate regions to animals in the tropics. For 28 seed-dispersal networks, by contrast, the correlation was positive, and there is no comparable geographical pattern. These results may be explained by evolution towards specialization in the presence of context-dependent costs that occur if plants share the animal species as interaction partner. How the identity of network hubs affects the stability and resilience of the community is an important question for future studies.

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.

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.SynthesisThe 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.

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.

Interaction intimacy of pathogens and herbivores with their host plants influences the topological structure of ecological networks in different ways.

• Over the past two decades an interest in the role that plant-animal mutualistic networks play in the organization and dynamic of biodiversity has steadily risen. Despite the ecological, evolutionary, and economic importance of plant-herbivore and plant-pathogen antagonistic relationships, however, few studies have examined these interactions in an ecological network framework.• We describe for the first time the topological structure of multitrophic networks involving congeneric tropical plant species of the genus Heliconia (Heliconiaceae, Zingiberales) and their herbivores and pathogens in the state of Pernambuco, Brazil. We based our study on the available literature describing the organisms (e.g., insects, mites, fungi, and bacteria) that attack 24 different species, hybrids, and cultivated varieties of Heliconia.• In general, pathogen- and herbivore-Heliconia networks differed in their topological structure (more modular vs. more nested, respectively): pathogen-Heliconia networks were more specialized and compartmentalized than herbivore-Heliconia networks. High modularity was likely due to the high intimacy that pathogens have with their host plants as compared with the more generalized feeding modes and behavior of herbivores. Some clusters clearly reflected the clustering of closely related cultivated varieties of Heliconia sharing the same pathogens.• From a commercial standpoint, different varieties of the same Heliconia species may be more susceptible to being attacked by the same species of pathogens. In summary, our study highlights the importance of interaction intimacy in structuring trophic relationships between plants and pathogens in the tropics.

Does the role that frugivorous bird species play in seed dispersal networks influence the speed of evolutionary divergence?

Extensive work on plant–animal mutualistic networks has shown that species in such networks vary in their number of connections with other species, from highly connected species (‘super-generalists’) to those connected only to a few other species (‘specialists’). How these species with different degrees of network specialization differ in their speciation rate remains largely unexplored. Here we hypothesize that having many interaction partners lowers the amount of leverage of any one partner, and slows coevolution. We then explored the speciation rate in frugivorous birds in a dataset of published seed dispersal networks, using a recent phylogeny that has a date for the divergence time of all bird species from their most closely related sister taxa. We found that generalist species’ divergence time was longer than specialist species’. While there may be other correlated traits to specialization that could contribute to this result, specialists and generalists did not vary in the size of their global distributions, and thus specialists are not simply rarer, if the size of the distribution reflects the species’ abundance. We discuss whether similar tests can be applied to other kinds of plant–animal interactions, and what level of taxonomy is appropriate to investigate to answer these sorts of questions.

Correlated loss of ecosystem services in coupled mutualistic networks.

Networks of species interactions promote biodiversity and provide important ecosystem services. These networks have traditionally been studied in isolation, but species are commonly involved in multiple, diverse types of interaction. Therefore, whether different types of species interaction networks coupled through shared species show idiosyncratic or correlated responses to habitat degradation is unresolved. Here we study the collective response of coupled mutualistic networks of plants and their pollinators and seed dispersers to the degradation of Europe's last relict of old-growth lowland forest (Białowieża, Poland). We show that logging of old-growth forests has correlated effects on the number of partners and interactions of plants in both mutualisms, and that these effects are mediated by shifts in plant densities on logged sites. These results suggest bottom-up-controlled effects of habitat degradation on plant-animal mutualistic networks, and predict that the conversion of primary old-growth forests to secondary habitats may cause a parallel loss of multiple animal-mediated ecosystem services.

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.

The strength of plant–pollinator interactions

Recent studies of plant-animal mutualistic networks have assumed that interaction frequency between mutualists predicts species impacts (population-level effects), and that field estimates of interaction strength (per-interaction effects) are unnecessary. Although existing evidence supports this assumption for the effect of animals on plants, no studies have evaluated it for the reciprocal effect of plants on animals. We evaluate this assumption using data on the reproductive effects of pollinators on plants and the reciprocal reproductive effects of plants on pollinators. The magnitude of species impacts of plants on pollinators, the reciprocal impacts of pollinators on plants, and their asymmetry were well predicted by interaction frequency. However, interaction strength was a key determinant of the sign of species impacts. These results underscore the importance of quantifying interaction strength in studies of mutualistic networks. We also show that the distributions of interaction strengths and species impacts are highly skewed, with few strong and many weak interactions. This skewed distribution matches the pattern observed in food webs, suggesting that the community-wide organization of species interactions is fundamentally similar between mutualistic and antagonistic interactions. Our results have profound ecological implications, given the key role of interaction strength for community stability.

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.

Nestedness versus modularity in ecological networks: two sides of the same coin?

1. Understanding the structure of ecological networks is a crucial task for interpreting community and ecosystem responses to global change. 2. Despite the recent interest in this subject, almost all studies have focused exclusively on one specific network property. The question remains as to what extent different network properties are related and how understanding this relationship can advance our comprehension of the mechanisms behind these patterns. 3. Here, we analysed the relationship between nestedness and modularity, two frequently studied network properties, for a large data set of 95 ecological communities including both plant-animal mutualistic and host-parasite networks. 4. We found that the correlation between nestedness and modularity for a population of random matrices generated from the real communities decreases significantly in magnitude and sign with increasing connectance independent of the network type. At low connectivities, networks that are highly nested also tend to be highly modular; the reverse happens at high connectivities. 5. The above result is qualitatively robust when different null models are used to infer network structure, but, at a finer scale, quantitative differences exist. We observed an important interaction between the network structure pattern and the null model used to detect it. 6. A better understanding of the relationship between nestedness and modularity is important given their potential implications on the dynamics and stability of ecological communities.

Nested structure acquired through simple evolutionary process

Nested structure, which is non-random, controls cooperation dynamics and biodiversity in plant–animal mutualistic networks. This structural pattern has been explained in a static (non-growth) network models. However, evolutionary processes might also influence the formation of such a structural pattern. We thereby propose an evolving network model for plant–animal interactions and show that non-random patterns such as nested structure and heterogeneous connectivity are both qualitatively and quantitatively predicted through simple evolutionary processes. This finding implies that network models can be simplified by considering evolutionary processes, and also that another explanation exists for the emergence of non-random patterns and might provide more comprehensible insights into the formation of plant–animal mutualistic networks from the evolutionary perspective.

Global architecture of metabolite distributions across species and its formation mechanisms

Living organisms produce metabolites of many types via metabolic reactions. Especially, flavonoids, a type of secondary metabolite, of plant species are interesting examples. Since plant species are believed to have specific flavonoids that were formed response to diverse environments, elucidation of the design principles of metabolite distributions across plant species is important for understanding metabolite diversity and plant evolution. In our previous study, we found heterogeneous connectivity in metabolite distribution, and proposed a simple model to explain the possible origin of heterogeneous connectivity. In this paper, we determine additional structural properties of metabolite distribution among families that are analogous analogy with plant–animal mutualistic networks: nested structure and modular structure. An earlier model representative of these structural properties in bipartite relationships was established on the basis of the traits of elements and external factors. However, we found that the architecture of metabolite distribution could be explained by simple evolutionary processes without trait-based mechanisms by comparing our model and the earlier model. Our model provided a better qualitative and quantitative prediction of nested and modular structures in addition to heterogeneous connectivity. This finding implies an alternative possible origin of these structural properties, and suggests the mechanisms underlying establishment metabolite distributions across plant species are simpler than expected.

Evaluating multiple determinants of the structure of plant–animal mutualistic networks

The structure of mutualistic networks is likely to result from the simultaneous influence of neutrality and the constraints imposed by complementarity in species phenotypes, phenologies, spatial distributions, phylogenetic relationships, and sampling artifacts. We develop a conceptual and methodological framework to evaluate the relative contributions of these potential determinants. Applying this approach to the analysis of a plant-pollinator network, we show that information on relative abundance and phenology suffices to predict several aggregate network properties (connectance, nestedness, interaction evenness, and interaction asymmetry). However, such information falls short of predicting the detailed network structure (the frequency of pairwise interactions), leaving a large amount of variation unexplained. Taken together, our results suggest that both relative species abundance and complementarity in spatiotemporal distribution contribute substantially to generate observed network patters, but that this information is by no means sufficient to predict the occurrence and frequency of pairwise interactions. Future studies could use our methodological framework to evaluate the generality of our findings in a representative sample of study systems with contrasting ecological conditions.