Robustness of mutualistic networks under phenological change and habitat destruction

Climate change can alter species phenologies and therefore disrupt species interactions. Habitat destruction can damage biodiversity and population viability. However, we still know very little about the potential effects of these two factors on the diversity and structure of interaction networks when both act simultaneously. Here we developed a mutualistic metacommunity model to explore the effects of habitat destruction and phenological changes on the diversity and structure of plant–pollinator networks. Using an empirical data set of plant and pollinator interactions and their duration in days, we simulated increasing levels of habitat destruction, under projected scenarios of phenological shifts as well for historically recorded changes in phenologies. On one hand, we found that habitat destruction causes catastrophic collapse in global diversity, as well as inducing alternative states. On the other hand, phenological shifts tend to make interactions weaker, increasing local extinction rates. Together, habitat destruction and phenological changes act synergistically, making metacommunities even more vulnerable to global collapse. Metacommunities are also more vulnerable to collapses under scenarios of historical change, in which phenologies are shortened, not just shifted. Furthermore, connectance and nestedness tends to decrease gradually with habitat destruction before the global collapse. Small phenological shifts can raise connectance slightly, due novel interactions appearing in a few generalist species, but larger shifts always reduce connectance. We conclude that the robustness of mutualistic metacommunities against habitat destruction can be greatly impaired by the weakening of positive interactions that results from the loss of phenological overlap.     

Interaction intimacy affects structure and coevolutionary dynamics in mutualistic networks

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

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.     

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.     

The assembly and disassembly of ecological networks

Global change has created a severe biodiversity crisis. Species are driven extinct at an increasing rate, and this has the potential to cause further coextinction cascades. The rate and shape of these coextinction cascades depend very much on the structure of the networks of interactions across species. Understanding network structure and how it relates to network disassembly, therefore, is a priority for system-level conservation biology. This process of network collapse may indeed be related to the process of network build-up, although very little is known about both processes and even less about their relationship. Here we review recent work that provides some preliminary answers to these questions. First, we focus on network assembly by emphasizing temporal processes at the species level, as well as the structural building blocks of complex ecological networks. Second, we focus on network disassembly as a consequence of species extinctions or habitat loss. We conclude by emphasizing some general rules of thumb that can help in building a comprehensive framework to understand the responses of ecological networks to global change.     

The disentangled bank: how loss of habitat fragments and disassembles ecological networks

Habitat transformation is one of the leading causes of changes in biodiversity and the breakdown of ecosystem function and services. The impacts of habitat transformation on biodiversity are complex and can be difficult to test and demonstrate. Network approaches to biodiversity science have provided a powerful set of tools and models that are beginning to present new insight into the structural and functional effects of habitat transformation on complex ecological systems. We propose a framework for studying the ways in which habitat loss and fragmentation jointly affect biodiversity by altering both habitat and ecological interaction networks. That is, the explicit study of "networks of networks" is required to understand the impacts of habitat change on biodiversity. We conduct a broad review of network methods and results, with the aim of revealing the common approaches used by landscape ecology and community ecology. We find that while a lot is known about the consequences of habitat transformation for habitat network topology and for the structure and function of simple antagonistic and mutualistic interaction networks, few studies have evaluated the consequences for large interaction networks with complex and spatially explicit architectures. Moreover, almost no studies have been focused on the continuous feedback between the spatial structure and dynamics of the habitat network and the structure and dynamics of the interaction networks inhabiting the habitat network. We conclude that theory and experiments that tackle the ecology of networks of networks are needed to provide a deeper understanding of biodiversity change in fragmented landscapes.     

The future of plant-pollinator diversity: understanding interaction networks across time, space, and global change

Structural analysis of plant-pollinator networks has revealed remarkably high species and interaction diversity and highlighted the species important for pollination services. Although techniques to analyze plant-pollinator networks began to emerge a decade ago, the characterization of spatiotemporal variation of interactions is still in its infancy. Understanding the ecological and evolutionary causes and consequences of spatial and temporal variation in plant-pollinator interactions is important for both basic and applied questions in community structure and function, the evolution of floral traits, and the development of optimal conservation strategies. Here we review observational, theoretical, and experimental studies of temporal and spatial variation in plant-pollinator interaction networks to establish a foundation for future studies to incorporate perspectives in spatiotemporal variation. Such perspectives are crucial given the rapid environmental changes associated with habitat loss, climate change, and biological invasions, which we discuss in this context. The inherent plasticity of plant-pollinator interactions and network structure suggests that many species should be able to persist by responding to environmental changes quickly, even though the identity of their mutualistic partners may change.     

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.     

Defaunation leads to interaction deficits,not interaction compensation,in an island seed dispersal network

Following defaunation, the loss of interactions with mutualists such as pollinators or seed dispersers may be compensated through increased interactions with remaining mutualists, ameliorating the negative cascading impacts on biodiversity. Alternatively, remaining mutualists may respond to altered competition by reducing the breadth or intensity of their interactions, exacerbating negative impacts on biodiversity. Despite the importance of these responses for our understanding of the dynamics of mutualistic networks and their response to global change, the mechanism and magnitude of interaction compensation within real mutualistic networks remains largely unknown. We examined differences in mutualistic interactions between frugivores and fruiting plants in two island ecosystems possessing an intact or disrupted seed dispersal network. We determined how changes in the abundance and behavior of remaining seed dispersers either increased mutualistic interactions (contributing to “interaction compensation”) or decreased interactions (causing an “interaction deficit”) in the disrupted network. We found a “rich‐get‐richer” response in the disrupted network, where remaining frugivores favored the plant species with highest interaction frequency, a dynamic that worsened the interaction deficit among plant species with low interaction frequency. Only one of five plant species experienced compensation and the other four had significant interaction deficits, with interaction frequencies 56–95% lower in the disrupted network. These results do not provide support for the strong compensating mechanisms assumed in theoretical network models, suggesting that existing network models underestimate the prevalence of cascading mutualism disruption after defaunation. This work supports a mutualist biodiversity‐ecosystem functioning relationship, highlighting the importance of mutualist diversity for sustaining diverse and resilient ecosystems.     

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.     

Interactive effects of elevation,species richness and extreme climatic events on plant–pollinator networks

Plant–pollinator interactions are essential for the functioning of terrestrial ecosystems, but are increasingly affected by global change. The risks to such mutualistic interactions from increasing temperature and more frequent extreme climatic events such as drought or advanced snow melt are assumed to depend on network specialization, species richness, local climate and associated parameters such as the amplitude of extreme events. Even though elevational gradients provide valuable model systems for climate change and are accompanied by changes in species richness, responses of plant–pollinator networks to climatic extreme events under different environmental and biotic conditions are currently unknown. Here, we show that elevational climatic gradients, species richness and experimentally simulated extreme events interactively change the structure of mutualistic networks in alpine grasslands. We found that the degree of specialization in plant–pollinator networks (H2′) decreased with elevation. Nonetheless, network specialization increased after advanced snow melt at high elevations, whereas changes in network specialization after drought were most pronounced at sites with low species richness. Thus, changes in network specialization after extreme climatic events depended on climatic context and were buffered by high species richness. In our experiment, only generalized plant–pollinator networks changed in their degree of specialization after climatic extreme events. This indicates that contrary to our assumptions, network generalization may not always foster stability of mutualistic interaction networks.     

Structure–stability relationships in networks combining mutualistic and antagonistic interactions

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

Resilient networks of ant-plant mutualists in amazonian forest fragments

Background

The organization of networks of interacting species, such as plants and animals engaged in mutualisms, strongly influences the ecology and evolution of partner communities. Habitat fragmentation is a globally pervasive form of spatial heterogeneity that could profoundly impact the structure of mutualist networks. This is particularly true for biodiversity-rich tropical ecosystems, where the majority of plant species depend on mutualisms with animals and it is thought that changes in the structure of mutualist networks could lead to cascades of extinctions.

Methodology/Principal Findings

We evaluated effects of fragmentation on mutualistic networks by calculating metrics of network structure for ant-plant networks in continuous Amazonian forests with those in forest fragments. We hypothesized that networks in fragments would have fewer species and higher connectance, but equal nestedness and resilience compared to forest networks. Only one of the nine metrics we compared differed between continuous forest and forest fragments, indicating that networks were resistant to the biotic and abiotic changes that accompany fragmentation. This is partially the result of the loss of only specialist species with one connection that were lost in forest fragments.

Conclusions/Significance

We found that the networks of ant-plant mutualists in twenty-five year old fragments are similar to those in continuous forest, suggesting these interactions are resistant to the detrimental changes associated with habitat fragmentation, at least in landscapes that are a mosaic of fragments, regenerating forests, and pastures. However, ant-plant mutualistic networks may have several properties that may promote their persistence in fragmented landscapes. Proactive identification of key mutualist partners may be necessary to focus conservation efforts on the interactions that insure the integrity of network structure and the ecosystems services networks provide.     

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.     

Global warming and the disruption of plant-pollinator interactions

Anthropogenic climate change is widely expected to drive species extinct by hampering individual survival and reproduction, by reducing the amount and accessibility of suitable habitat, or by eliminating other organisms that are essential to the species in question. Less well appreciated is the likelihood that climate change will directly disrupt or eliminate mutually beneficial (mutualistic) ecological interactions between species even before extinctions occur. We explored the potential disruption of a ubiquitous mutualistic interaction of terrestrial habitats, that between plants and their animal pollinators, via climate change. We used a highly resolved empirical network of interactions between 1420 pollinator and 429 plant species to simulate consequences of the phenological shifts that can be expected with a doubling of atmospheric CO₂. Depending on model assumptions, phenological shifts reduced the floral resources available to 17–50% of all pollinator species, causing as much as half of the ancestral activity period of the animals to fall at times when no food plants were available. Reduced overlap between plants and pollinators also decreased diet breadth of the pollinators. The predicted result of these disruptions is the extinction of pollinators, plants and their crucial interactions.     

The interconnected rhizosphere: High network complexity dominates rhizosphere assemblages

While interactions between roots and microorganisms have been intensively studied, we know little about interactions among root‐associated microbes. We used random matrix theory‐based network analysis of 16S rRNA genes to identify bacterial networks associated with wild oat (Avena fatua) over two seasons in greenhouse microcosms. Rhizosphere networks were substantially more complex than those in surrounding soils, indicating the rhizosphere has a greater potential for interactions and niche‐sharing. Network complexity increased as plants grew, even as diversity decreased, highlighting that community organisation is not captured by univariate diversity. Covariations were predominantly positive (> 80%), suggesting that extensive mutualistic interactions may occur among rhizosphere bacteria; we identified quorum‐based signalling as one potential strategy. Putative keystone taxa often had low relative abundances, suggesting low‐abundance taxa may significantly contribute to rhizosphere function. Network complexity, a previously undescribed property of the rhizosphere microbiome, appears to be a defining characteristic of this habitat.     

Population dynamics in migratory networks

Migratory animals are comprised of a complex series of interconnected breeding and nonbreeding populations. Because individuals in any given population can arrive from a variety of sites the previous season, predicting how different populations will respond to environmental change can be challenging. In this study, we develop a population model composed of a network of breeding and wintering sites to show how habitat loss affects patterns of connectivity and species abundance. When the costs of migration are evenly distributed, habitat loss at a single site can increase the degree of connectivity (mixing) within the entire network, which then acts to buffer global populations from declines. However, the degree to which populations are buffered depends on where habitat loss occurs within the network: a site that has the potential to receive individuals from multiple populations in the opposite season will lead to smaller declines than a site that is more isolated. In other cases when there are equal costs of migration to two or more sites in the opposite season, habitat loss can result in some populations becoming segregated (disconnected) from the rest of the network. The geographic structure of the network can have a significant influence on relative population sizes of sites in the same season and can also affect the overall degree of mixing in the network, even when sites are of equal intrinsic quality. When a migratory network is widely spaced and migration costs are high, an equivalent habitat loss will lead to a larger decline in global population size than will occur in a network where the overall costs of migration are low. Our model provides an important foundation to test predictions related to habitat loss in real-world migratory networks and demonstrates that migratory networks will likely produce different dynamics from traditional metapopulations. Our results provide strong evidence that estimating population connectivity is a prerequisite for successfully predicting changes in migratory populations.     

The architecture of weighted mutualistic networks

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

Defining invasiveness and invasibility in ecological networks

The success of a biological invasion is context dependent, and yet two key concepts—the invasiveness of species and the invasibility of recipient ecosystems—are often defined and considered separately. We propose a framework that can elucidate the complex relationship between invasibility and invasiveness. It is based on trait-mediated interactions between species and depicts the response of an ecological network to the intrusion of an alien species, drawing on the concept of community saturation. Here, invasiveness of an introduced species with a particular trait is measured by its per capita population growth rate when the initial propagule pressure of the introduced species is very low. The invasibility of the recipient habitat or ecosystem is dependent on the structure of the resident ecological network and is defined as the total width of an opportunity niche in the trait space susceptible to invasion. Invasibility is thus a measure of network instability. We also correlate invasibility with the asymptotic stability of resident ecological network, measured by the leading eigenvalue of the interaction matrix that depicts trait-based interaction intensity multiplied by encounter rate (a pairwise product of propagule pressure of all members in a community). We further examine the relationship between invasibility and network architecture, including network connectance, nestedness and modularity. We exemplify this framework with a trait-based assembly model under perturbations in ways to emulate fluctuating resources and random trait composition in ecological networks. The maximum invasiveness of a potential invader (greatest intrinsic population growth rate) was found to be positively correlated with invasibility of the recipient ecological network. Additionally, ecosystems with high network modularity and high ecological stability tend to exhibit high invasibility. Where quantitative data are lacking we propose using a qualitative interaction matrix of the ecological network perceived by a potential invader so that the structural network stability and invasibility can be estimated from the literature or from expert opinion. This approach links network structure, invasiveness and invasibility in the context of trait-mediated interactions, such as the invasion of insects into mutualistic and antagonistic networks.