Mutualistic Communities Research Articles

Rethinking the logistic approach for population dynamics of mutualistic interactions

Mutualistic communities have an internal structure that makes them resilient to external perturbations. Late research has focused on their stability and the topology of the relations between the different organisms to explain the reasons of the system robustness. Much less attention has been invested in analyzing the systems dynamics. The main population models in use are modifications of the r−K formulation of logistic equation with additional terms to account for the benefits produced by the interspecific interactions. These models have shortcomings as the so-called r−K formulation diverges under some conditions. In this work, we introduce a model for population dynamics under mutualism that preserves the original logistic formulation. It is mathematically simpler than the widely used type II models, although it shows similar complexity in terms of fixed points and stability of the dynamics. We perform an analytical stability analysis and numerical simulations to study the model behavior in general interaction scenarios including tests of the resilience of its dynamics under external perturbations. Despite its simplicity, our results indicate that the model dynamics shows an important richness that can be used to gain further insights in the dynamics of mutualistic communities.

Ecology. Why are plant-pollinator networks nested?

Mutualistic communities maximize their structural stability [Also see Research Article by Rohr et al. ]

Restoration of plant–pollinator interaction networks via species translocation

The recent decline in pollinator biodiversity, notably in the case of wild bee populations, puts both wild and agricultural ecosystems at risk of ecological community collapse. This has triggered calls for further study of these mutualistic communities in order to more effectively inform restoration of disturbed plant–pollinator communities. Here, we use a dynamic network model to test a variety of translocation strategies for restoring a community after it experiences the loss of some of its species. We consider the reintroduction of extirpated species, both immediately after the original loss and after the community has reequilibrated, as well as the introduction of other native species that were originally absent from the community. We find that reintroducing multiple highly interacting generalist species best restores species richness for lightly disturbed communities. However, for communities that experience significant losses in biodiversity, introducing generalist species that are not originally present in the community may most effectively restore species richness, although in these cases the resultant community often shares few species with the original community. We also demonstrate that the translocation of a single species has a minimal impact on both species richness and the frequency of community collapse. These results have important implications for restoration practices in the face of varying degrees of community perturbations, the refinement of which is crucial for community management.

The sudden collapse of pollinator communities

Declines in pollinator populations may harm biodiversity and agricultural productivity. Little attention has, however, been paid to the systemic response of mutualistic communities to global environmental change. Using a modelling approach and merging network theory with theory on critical transitions, we show that the scale and nature of critical transitions is likely to be influenced by the architecture of mutualistic networks. Specifically, we show that pollinator populations may collapse suddenly once drivers of pollinator decline reach a critical point. A high connectance and/or nestedness of the mutualistic network increases the capacity of pollinator populations to persist under harsh conditions. However, once a tipping point is reached, pollinator populations collapse simultaneously. Recovering from this single community-wide collapse requires a relatively large improvement of conditions. These findings may have large implications for our view on the sustainability of pollinator communities and the services they provide.

Effects of Antibiotic Use on the Microbiota of the Gut and Associated Alterations of Immunity and Metabolism

The excessively widespread use of antibiotics has created many threats. A well-known problem is the increasing bacterial resistance to antibiotics, which has clearly become a worldwide challenge to the effective control of infections by many pathogens. But, beyond affecting the pathogenic agents for which it is intended, antibiotic treatment also affects the mutualistic communities of microbes that inhabit the human body. As they inhibit susceptible organisms and select for resistant ones, antibiotics can have strong immediate effects on the composition of these communities, such as the proliferation of resistant opportunists that can cause accute disease. Furthermore, antibiotic-induced microbiota alterations are also likely to have more insidious effects on long-term health. In the case of the gut microbiota, this community interacts with many crucial aspects of human biology, including the regulation of immune and metabolic homeostasis, in the gut and beyond. It follows that antibiotic treatments bear the risk of altering these basic equilibria. Here, we review the growing literature on the effects of antibiotic use on gut microbiota composition and function, and their consequences for immunity, metabolism, and health.

Habitat loss alters the architecture of plant–pollinator interaction networks

Habitat loss can have a negative effect on the number, abundance, and composition of species in plant-pollinator communities. Although we have a general understanding of the negative consequences of habitat loss for biodiversity, much less is known about the resulting effects on the pattern of interactions in mutualistic networks. Ecological networks formed by mutualistic interactions often exhibit a highly nested architecture with low modularity, especially in comparison with antagonistic networks. These patterns of interaction are thought to confer stability on mutualistic communities. With the growing threat of environmental change, it is important to expand our understanding of the factors that affect biodiversity and the stability of the communities that provide critical ecosystem functions and services. We studied the effects of habitat loss on plant--pollinator network architecture and found that regional habitat loss contributes directly to species loss and indirectly to the reorganization of interspecific interactions in a local community. Networks became more highly connected and more modular with habitat loss. Species richness and abundance were the primary drivers of variation in network architecture, though species compositi n affected modularity. Theory suggests that an increase in modularity with habitat loss will threaten community stability, which may contribute to an extinction debt in communities already affected by habitat loss.

Network Dynamics Contribute to Structure: Nestedness in Mutualistic Networks

Both ecological and evolutionary timescales are of importance when considering an ecological system; population dynamics affect the evolution of species traits, and vice versa. Recently, these two timescales have been used to explain structural patterns in host-parasite networks, where the evolution of the manner in which species balance the use of their resources in interactions with each other was examined.One of these patterns was nestedness, in which the set of parasite species within a particular host forms a subset of those within a more species-rich host. Patterns of both nestedness and anti-nestedness have been observed significantly more often than expected due to chance in host-parasite networks. In contrast, mutualistic networks tend to display a significant degree of nestedness, but are rarely anti-nested. Within networks with different interaction types, therefore, there appears to be a feature promoting non-random structural patterns, such as nestedness and anti-nestedness, depending on the interaction types involved.Here, we invoke the co-evolution of species trait-values when allocating resources to interactions to explain the structural pattern of nestedness in a mutualistic community. We look at a bipartite, multi-species system, in which the strength of an interaction between two species is determined by the resources that each species invests in that relationship. We then analyze the evolution of these interactions using adaptive dynamics.We found that the evolution of these interactions, reflecting the trade-off of resources, could be used to accurately predict that nestedness occurs significantly more often than expect due to chance alone in a mutualistic network. This complements previous results applying the same concept to an antagonistic network. We conclude that population dynamics and resource trade-offs could be important promoters of structural patterns in ecological networks of different types.

James et al. reply

Replying to S. Saavedra & D. B. Stouffer , 10.1038/nature12380 (2013) Saavedra and Stouffer1 claim that the results of James et al.2 are a consequence of the method used to randomize interaction matrices. We recognize the importance of examining alternative randomization schemes and have repeated our analysis using their methods. However, we find no evidence that ‘reconfirms the importance of nestedness in mutualistic communities’1.

Abundant equals nested

How ecological network structures are influenced by species coexistence, community stability and perturbations is a topic of debate. It seems that one overlooked correlate of nested structures is species abundances. See Letter p.449 Cooperation among species tends to result in mutualistic networks with a nested structure. Although nestedness may increase biodiversity and persistence, theoretical work suggests that nested networks tend to be less stable than unstructured ones. This paper shows analytically that nested networks result from a mechanism that maximizes species abundances in mutualistic communities and that the abundance of the nested species is directly linked to the resilience of the community. This work offers a model for the study of how ecological factors and evolutionary history shape ecological networks.

Emergence of structural and dynamical properties of ecological mutualistic networks

Mutualistic networks are formed when the interactions between two classes of species are mutually beneficial. They are important examples of cooperation shaped by evolution. Mutualism between animals and plants has a key role in the organization of ecological communities. Such networks in ecology have generally evolved a nested architecture independent of species composition and latitude; specialist species, with only few mutualistic links, tend to interact with a proper subset of the many mutualistic partners of any of the generalist species. Despite sustained efforts to explain observed network structure on the basis of community-level stability or persistence, such correlative studies have reached minimal consensus. Here we show that nested interaction networks could emerge as a consequence of an optimization principle aimed at maximizing the species abundance in mutualistic communities. Using analytical and numerical approaches, we show that because of the mutualistic interactions, an increase in abundance of a given species results in a corresponding increase in the total number of individuals in the community, and also an increase in the nestedness of the interaction matrix. Indeed, the species abundances and the nestedness of the interaction matrix are correlated by a factor that depends on the strength of the mutualistic interactions. Nestedness and the observed spontaneous emergence of generalist and specialist species occur for several dynamical implementations of the variational principle under stationary conditions. Optimized networks, although remaining stable, tend to be less resilient than their counterparts with randomly assigned interactions. In particular, we show analytically that the abundance of the rarest species is linked directly to the resilience of the community. Our work provides a unifying framework for studying the emergent structural and dynamical properties of ecological mutualistic networks.

Phylogenetic relationships among host plants explain differences in fungal species richness and community composition in ectomycorrhizal symbiosis

Geographic and taxonomic host ranges determine the distribution of biotrophic organisms. Host phylogenetic distance strongly affects the community composition of pathogens and parasites, but little is known about the host phylogeny effect on communities of mutualists, such as plant-pollinator and plant-mycorrhizal fungi systems. By incorporating phylogenetic eigenvectors into univariate and multivariate models, we aimed to determine the relative contribution of host phylogeny and environmental variables to mycorrhizal traits and community composition of ectomycorrhizal (EcM) fungi in Salicaceae at the local scale. Host phylogeny explained 75% of the variation in fungal species richness and 20% of the variation in community composition. We also re-analyzed a system involving eight hosts from Japan, in which host phylogeny explained 26% and 9% of the variation in fungal richness and community composition, respectively. [Correction added after online publication 21 May 2013: in the preceding sentence the values 9% and 26% have been transposed.] Phylogenetic eigenvectors that differentially account for clades and terminal taxa across the phylogeny revealed stronger host effects than did the treatment of host species as categorical or dummy variables in multiregression models, and in comparison with methods such as Mantel test and its analogs. Our results indicate the usefulness of the eigenvector method for the quantification of the host phylogeny effect, which represents an integrated complex function of taxonomic sampling effect and phylogenetic distance per se.

Global versus local extinction in a network model of plant–pollinator communities

The loss of a species from an ecological community can trigger a cascade of additional extinctions; the complex interactions that comprise ecological communities make the dynamics and impacts of such a cascade challenging to predict. Previous studies have typically considered global extinctions, where a species cannot re-enter a community once it is lost. However, in some cases a species only becomes locally extinct, and may be able to reinvade from surrounding communities. Here, we use a dynamic, Boolean network model of plant–pollinator community assembly to analyze the differences between global and local extinction events in mutualistic communities. As expected, we find that compared to global extinctions, communities respond to local extinctions with lower biodiversity loss, and less variation in topological network properties. We demonstrate that in the face of global extinctions, larger communities suffer greater biodiversity loss than smaller communities when similar proportions of species are lost. Conversely, smaller communities suffer greater loss in the face of local extinctions. We show that targeting species with the most interacting partners causes more biodiversity loss than random extinctions in the case of global, but not local, extinctions. These results extend our understanding of how mutualistic communities respond to species loss, with implications for community management and conservation efforts.

Strategy Diversity Stabilizes Mutualism through Investment Cycles, Phase Polymorphism, and Spatial Bubbles

There is continuing interest in understanding factors that facilitate the evolution and stability of cooperation within and between species. Such interactions will often involve plasticity in investment behavior, in response to the interacting partner's investments. Our aim here is to investigate the evolution and stability of reciprocal investment behavior in interspecific interactions, a key phenomenon strongly supported by experimental observations. In particular, we present a comprehensive analysis of a continuous reciprocal investment game between mutualists, both in well-mixed and spatially structured populations, and we demonstrate a series of novel mechanisms for maintaining interspecific mutualism. We demonstrate that mutualistic partners invariably follow investment cycles, during which mutualism first increases, before both partners eventually reduce their investments to zero, so that these cycles always conclude with full defection. We show that the key mechanism for stabilizing mutualism is phase polymorphism along the investment cycle. Although mutualistic partners perpetually change their strategies, the community-level distribution of investment levels becomes stationary. In spatially structured populations, the maintenance of polymorphism is further facilitated by dynamic mosaic structures, in which mutualistic partners form expanding and collapsing spatial bubbles or clusters. Additionally, we reveal strategy-diversity thresholds, both for well-mixed and spatially structured mutualistic communities, and discuss factors for meeting these thresholds, and thus maintaining mutualism. Our results demonstrate that interspecific mutualism, when considered as plastic investment behavior, can be unstable, and, in agreement with empirical observations, may involve a polymorphism of investment levels, varying both in space and in time. Identifying the mechanisms maintaining such polymorphism, and hence mutualism in natural communities, provides a significant step towards understanding the coevolution and population dynamics of mutualistic interactions.

Analysis of stomach bacterial communities in Australian feral horses

We investigated the community structure of bacteria that populate the stomach of the Brumby, a breed of feral horses from the Australian outback. Using a 16S rRNA gene clone library, we identified 155 clones that were assigned to 26 OTUs based on a 99.0 % sequence identity cutoff. Two OTUs represented 73.5 % of clones, while 18 OTUs were each assigned only a single clone. Four major bacterial types were identified in the Brumby stomach: Lactobacillaceae, Streptococcaceae, Veillonellaceae and Pasteurellaceae. The first three groups, which represented 98.1 % of the Brumby stomach library clones, belonged to the bacterial phylum Firmicutes. We found that 49.7 % of clones were related to bacterial species previously identified in the equine hindgut, and that 44.5 % of clones were related to symbiotic bacterial species identified in the mouth or throat of either horses or other mammals. Our results indicated that the composition of mutualistic bacterial communities of feral horses was consistent with other studies on domestic horses. In addition to bacterial sequences, we also identified four plastid 16S rRNA gene sequences, which may help in further characterizing the type of vegetation consumed by Brumby horses in their natural environment.

COEVOLUTION AND THE ARCHITECTURE OF MUTUALISTIC NETWORKS

Although coevolution is widely recognized as an important evolutionary process for pairs of reciprocally specialized species, its importance within species-rich communities of generalized species has been questioned. Here we develop and analyze mathematical models of mutualistic communities, such as those between plants and pollinators or plants and seed-dispersers to evaluate the importance of coevolutionary selection within complex communities. Our analyses reveal that coevolutionary selection can drive significant changes in trait distributions with important consequences for the network structure of mutualistic communities. One such consequence is greater connectance caused by an almost invariable increase in the rate of mutualistic interaction within the community. Another important consequence is altered patterns of nestedness. Specifically, interactions mediated by a mechanism of phenotype matching tend to be antinested when coevolutionary selection is weak and even more strongly antinested as increasing coevolutionary selection favors the emergence of reciprocal specialization. In contrast, interactions mediated by a mechanism of phenotype differences tend to be nested when coevolutionary selection is weak, but less nested as increasing coevolutionary selection favors greater levels of generalization in both plants and animals. Taken together, our results show that coevolutionary selection can be an important force within mutualistic communities, driving changes in trait distributions, interaction rates, and even network structure.

Interspecific interactions affect species and community responses to climate shifts

The response of individual species to climate change may alter the composition and dynamics of communities. Here, we show that the impacts of environmental change on communities can depend on the nature of the interspecific interactions: mutualistic communities typically respond differently than commensalistic or parasitic communities. We model and analyse the geographic range shifting of metapopulations of two interacting species – a host and an obligate species. Different types of interspecific interactions are implemented by modifying local extinction rates according to the presence/absence of the other species. We distinguish and compare three fundamentally different community types: mutualism, commensalism and parasitism. We find that community dynamics during geographic range shifting critically depends on the type of interspecific interactions. Parasitic interactions exacerbate the negative effect of environmental change whereas mutualistic interactions only partly compensate it. Commensalistic interactions exhibit an intermediate response. Based on these model outcomes, we predict that parasitic species interactions may be more vulnerable to geographic range shifting than commensalistic or mutualistic ones. However, we observe that when climate stabilises following a period of change, the rate of community recovery is largely independent of the type of interspecific interactions. These results emphasize that communities respond delicately to environmental change, and that local interspecific interactions can affect range shifting communities at large spatial scales.

Disentangling nestedness from models of ecological complexity

Complex networks of interactions are ubiquitous and are particularly important in ecological communities, in which large numbers of species exhibit negative (for example, competition or predation) and positive (for example, mutualism) interactions with one another. Nestedness in mutualistic ecological networks is the tendency for ecological specialists to interact with a subset of species that also interact with more generalist species. Recent mathematical and computational analysis has suggested that such nestedness increases species richness. By examining previous results and applying computational approaches to 59 empirical data sets representing mutualistic plant–pollinator networks, we show that this statement is incorrect. A simpler metric—the number of mutualistic partners a species has—is a much better predictor of individual species survival and hence, community persistence. Nestedness is, at best, a secondary covariate rather than a causative factor for biodiversity in mutualistic communities. Analysis of complex networks should be accompanied by analysis of simpler, underpinning mechanisms that drive multiple higher-order network properties.

Characterization of the Fungal Microbiota (Mycobiome) in Healthy and Dandruff-Afflicted Human Scalps

The human scalp harbors a vast community of microbial mutualists, the composition of which is difficult to elucidate as many of the microorganisms are not culturable using current culture techniques. Dandruff, a common scalp disorder, is known as a causative factor of a mild seborrheic dermatitis as well as pityriasis versicolor, seborrheic dermatitis, and atopic dermatitis. Lipophilic yeast Malassezia is widely accepted to play a role in dandruff, but relatively few comprehensive studies have been reported. In order to investigate fungal biota and genetic resources of dandruff, we amplified the 26S rRNA gene from samples of healthy scalps and dandruff-afflicted scalps. The sequences were analyzed by a high throughput method using a GS-FLX 454 pyrosequencer. Of the 74,811 total sequence reads, Basidiomycota (Filobasidium spp.) was the most common phylum associated with dandruff. In contrast, Ascomycota (Acremonium spp.) was common in the healthy scalps. Our results elucidate the distribution of fungal communities associated with dandruff and provide new avenues for the potential prevention and treatment of dandruff.

Impact of maximum sustainable yield on mutualistic communities

We analyze effects of reaching the maximum sustainable yield (MSY) in a system of n cooperating logistic populations under proportional harvesting strategy. In case a selective harvesting effort adjusted to each species is implemented, the optimum effort is smaller than half the biotic potential of each species. This results in the total maximum sustainable yield (TMSY1) which does not affect the persistence of the system. In case the system is harvested with a common harvesting effort which is approximately the same for all cooperating species, like in a trawler fishing, the optimum harvesting effort leads to the TMSY2, where TMSY1≥TMSY2. In addition, species with lower biotic potential and carrying capacity may be driven to extinction, especially if these species weakly cooperate with the rest of the system. Hence, a call for implementation of TMSY2 may be equivalent to a call for extermination of some species, and it runs against the Convention on Biological Diversity (CBD, 1992). Since the documents advocating MSY, starting with the Johannesburg Implementation plan (IP, 2002) and including the EU Green Paper (EU, 2009), use TMSY2, the call for MSY must be urgently retracted and replaced with a call for adaptive management that respects CBD.

Phenology drives mutualistic network structure and diversity

Several network properties have been identified as determinants of the stability and complexity of mutualistic networks. However, it is unclear which mechanisms give rise to these network properties. Phenology seems important, because it shapes the topology of mutualistic networks, but its effects on the dynamics of mutualistic networks have scarcely been studied. Here, we study these effects with a general dynamical model of mutualistic and competitive interactions where the interaction strength depends on the temporal overlap between species resulting from their phenologies. We find a negative complexity-stability relationship, where phenologies maximising mutualistic interactions and minimising intraguild competitive interactions generate speciose, nested and poorly connected networks with moderate asymmetry and low resilience. Moreover, lengthening the season increases diversity and resilience. This highlights the fragility of real mutualistic communities with short seasons (e.g. Arctic environments) to drastic environmental changes.