The phylogenetic component of food web structure and intervality

Despite the exceptional complexity formed by species and their interactions in ecological networks, such as food webs, regularities in the network structures are repeatedly demonstrated. The interactions are determined by the characteristics of a species. The characteristics are in turn determined by the species’ phylogenetic relationships, but also by factors not related to evolutionary history. Here, we test whether species’ phylogenetic relationships provides a significant proxy for food web intervality. We thereafter quantify the degree to which different species traits remain valuable predictors of food web structure after the baseline effect of species’ relatedness has been removed. We find that the phylogenetic relationships provide a significant background from which to estimate food web intervality and thereby structure. However, we also find that there is an important, non-negligible part of some traits, e.g., body size, in food webs that is not accounted for by the phylogenetic relationships. Additionally, both these relationships differ depending if a predator or a prey perspective is adopted. Clearly, species’ evolutionary history as well as traits not determined by phylogenetic relationships shapes predator-prey interactions in food webs, and the underlying evolutionary processes take place on slightly different time scales depending on the direction of predator-prey adaptations.     

Matching consumer feeding behaviours and resource traits: a fourth‐corner problem in food‐web theory

For decades, food web theory has proposed phenomenological models for the underlying structure of ecological networks. Generally, these models rely on latent niche variables that match the feeding behaviour of consumers with their resource traits. In this paper, we used a comprehensive database to evaluate different hypotheses on the best dependency structure of trait‐matching patterns between consumers and resource traits. We found that consumer feeding behaviours had complex interactions with resource traits; however, few dimensions (i.e. latent variables) could reproduce the trait‐matching patterns. We discuss our findings in the light of three food web models designed to reproduce the multidimensionality of food web data; additionally, we discuss how using species traits clarify food webs beyond species pairwise interactions and enable studies to infer ecological generality at larger scales, despite potential taxonomic differences, variations in ecological conditions and differences in species abundance between communities.     

Exploring the evolutionary signature of food webs' backbones using functional traits

Increasing evidence suggests that an appropriate model for food webs, the network of feeding links in a community of species, should take into account the inherent variability of ecological interactions. Harnessing this variability, we will show that it is useful to interpret empirically observed food webs as realisations of a family of stochastic processes, namely random dot‐product graph models. These models provide an ideal extension of food‐web models beyond the limitations of current deterministic or partially probabilistic models. As an additional bene?t, our RDPG framework enables us to identify the pairwise distance structure given by species' functional food‐web traits: this allows for the natural emergence of ecologically meaningful species groups. Lastly, our results suggest the notion that the evolutionary signature in food webs is already detectable in their stochastic backbones, while the contribution of their ?ne wiring is arguable. Synthesis Food webs are influenced by many stochastic processes and are constantly evolving. Here, we treat observed food webs as realisations of random dot‐product graph models (RDPG), extending food‐web modelling beyond the limitations of current deterministic or partially probabilistic models. Our RDPG framework enables us to identify the pairwise‐distance structure given by species' functional food‐web traits, which in turn allows for the natural emergence of ecologically meaningful species groups. It also provides a way to measure the phylogenetic signal present in food webs, which we find is strongest in webs' low‐dimensional backbones.     

Predicting trophic relations in ecological networks: A test of the Allometric Diet Breadth Model

Few food web theory hypotheses/predictions can be readily tested using likelihoods of reproducing the data. Simple probabilistic models for food web structure, however, are an exception as their likelihoods were recently derived. Here I test the performance of a more complex model for food web structure that is grounded in the allometric scaling of interactions with body size and the theory of optimal foraging (Allometric Diet Breadth Model—ADBM). This deterministic model has been evaluated by measuring the fraction of trophic relations it correctly predicts. I contrasted this value with that produced by simpler models based on body sizes and found that the quantitative information on allometric scaling and optimal foraging does not significantly increase model fit. Also, I present a method to compute the p-value for the fraction of trophic interactions correctly predicted by the ADBM, or any other model, with respect to three probabilistic models. I find that the ADBM predicts significantly more links than random graphs, but other models can outperform it. Although optimal foraging and allometric scaling may improve our understanding of food webs, the ADBM needs to be modified or replaced to find support in the data.     

Phylogeny versus body size as determinants of food web structure

Food webs are the complex networks of trophic interactions that stoke the metabolic fires of life. To understand what structures these interactions in natural communities, ecologists have developed simple models to capture their main architectural features. However, apparently realistic food webs can be generated by models invoking either predator-prey body-size hierarchies or evolutionary constraints as structuring mechanisms. As a result, this approach has not conclusively revealed which factors are the most important. Here we cut to the heart of this debate by directly comparing the influence of phylogeny and body size on food web architecture. Using data from 13 food webs compiled by direct observation, we confirm the importance of both factors. Nevertheless, phylogeny dominates in most networks. Moreover, path analysis reveals that the size-independent direct effect of phylogeny on trophic structure typically outweighs the indirect effect that could be captured by considering body size alone. Furthermore, the phylogenetic signal is asymmetric: closely related species overlap in their set of consumers far more than in their set of resources. This is at odds with several food web models, which take only the view-point of consumers when assigning interactions. The echo of evolutionary history clearly resonates through current food webs, with implications for our theoretical models and conservation priorities.     

Species traits as drivers of food web structure

The use of functional traits to describe community structure is a promising approach to reveal generalities across organisms and ecosystems. Plant ecologists have demonstrated the importance of traits in explaining community structure, competitive interactions as well as ecosystem functioning. The application of trait‐based methods to more complex communities such as food webs is however more challenging owing to the diversity of animal characteristics and of interactions. The objective of this study was to determine how functional structure is related to food web structure. We consider that food web structure is the result of 1) the match between consumer and resource traits, which determine the occurence of a trophic interaction between them, and 2) the distribution of functional traits in the community. We implemented a statistical approach to assess whether or not 35 466 pairwise interactions between soil organisms are constrained by trait‐matching and then used a Procrustes analysis to investigate correlations between functional indices and network properties across 48 sites. We found that the occurrence of trophic interactions is well predicted by matching the traits of the resource with those of the consumer. Taxonomy and body mass of both species were the most important traits for the determination of an interaction. As a consequence, functional evenness and the variance of certain traits in the community were correlated to trophic complementarity between species, while trait identity, more than diversity, was related to network topology. The analysis was however limited by trait data availability, and a coarse resolution of certain taxonomic groups in our dataset. These limitations explain the importance of taxonomy, as well as the complexity of the statistical model needed. Our results outline the important implications of trait composition on ecological networks, opening promising avenues of research into the relationship between functional diversity and ecosystem functioning in multi‐trophic systems.     

The role of fish life histories in allometrically scaled food‐web dynamics

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The dynamics of multispecies, multi-life-stage models of aquatic food webs

We investigated the dynamics of models of aquatic food webs using stability analysis methods previously applied to other types of food web models. Our models expanded traditional Lotka-Volterra models of predator-prey interactions in several ways. We added life history structure to these models in order to investigate its effects. Life history omnivory is different life history stages of a species feeding in trophically different positions in a food web. Such a species might appear omnivorous, integrating across all stages, but the individual stage might not be. Other important additions to the basic models included stock-recruitment relationships between adults and young and food-dependent maturation rates for early life history stages. Complex models of multispecies interactions were built from basic ones by adding new features sequentially. Our analysis revealed five major features of our multispecies, multi-life-stage models. Omnivory reduces stability, as it does in food web models without life history structure. However, life history omnivory reduces stability much less than single life stage omnivory does. Stock recruitment relationships affect the likelihood of finding stable models. If the maturation rate of young varies with their food supply, the chance of finding stable models decreases. Finally, predation loops of the type A eats B, B eats A, or A eats B, B eats C, C eats A greatly reduce model stability. We present both biological and mathematical explanations for these findings. We also discuss their implications for management of marine resources.     

Do Food Web Models Reproduce the Structure of Mutualistic Networks?

Background

Simple models inspired by processes shaping consumer-resource interactions have helped to establish the primary processes underlying the organization of food webs, networks of trophic interactions among species. Because other ecological interactions such as mutualisms between plants and their pollinators and seed dispersers are inherently based in consumer-resource relationships we hypothesize that processes shaping food webs should organize mutualistic relationships as well.

Methodology/Principal Findings

We used a likelihood-based model selection approach to compare the performance of food web models and that of a model designed for mutualisms, in reproducing the structure of networks depicting mutualistic relationships. Our results show that these food web models are able to reproduce the structure of most of the mutualistic networks and even the simplest among the food web models, the cascade model, often reproduce overall structural properties of real mutualistic networks.

Conclusions/Significance

Based on our results we hypothesize that processes leading to feeding hierarchy, which is a characteristic shared by all food web models, might be a fundamental aspect in the assembly of mutualisms. These findings suggest that similar underlying ecological processes might be important in organizing different types of interactions.     

Complexity and structural properties of food webs in the Barents Sea

A food web topology describes the diversity of species and their trophic interactions, i.e. who eats whom, and structural analysis of food web topologies can provide insight into ecosystem structure and function. It appears simple, at first sight, to list all species and their trophic interactions. However, the very large number of species at low trophic levels and the impossibility to monitor all trophic interactions in the ocean makes it impossible to construct complete food web topologies. In practice, food web topologies are simplified by aggregating species into groups termed trophospecies. It is not clear though, how much simplified versions of food webs retain the structural properties of more detailed networks. Using the most comprehensive Barents Sea food web to date, we investigate the performance of methods to construct simplified food webs using three approaches: taxonomic, structural and regular clustering. We then evaluate how topological properties vary with the level of network simplification. Results show that alteration of food web structural properties due to aggregation are highly sensitive to the methodology used for grouping species and trophic links. In the specific case of the Barents Sea, we show that it is possible to preserve key structural properties of the original complex food web in simplified versions when using taxonomic or structural clustering combined with intermediate 25% linkage for trophic aggregation.     

Towards a mechanistic understanding of temperature and enrichment effects on species interaction strength,omnivory and food‐web structure

Revealing the links between species functional traits, interaction strength and food‐web structure is of paramount importance for understanding and predicting the relationships between food‐web diversity and stability in a rapidly changing world. However, little is known about the interactive effects of environmental perturbations on individual species, trophic interactions and ecosystem functioning. Here, we combined modelling and laboratory experiments to investigate the effects of warming and enrichment on a terrestrial tritrophic system. We found that the food‐web structure is highly variable and switches between exploitative competition and omnivory depending on the effects of temperature and enrichment on foraging behaviour and species interaction strength. Our model contributes to identifying the mechanisms that explain how environmental effects cascade through the food web and influence its topology. We conclude that considering environmental factors and flexible food‐web structure is crucial to improve our ability to predict the impacts of global changes on ecosystem diversity and stability.     

Phylogenetic Patterns of Extinction Risk in the Eastern Arc Ecosystems,an African Biodiversity Hotspot

There is an urgent need to reduce drastically the rate at which biodiversity is declining worldwide. Phylogenetic methods are increasingly being recognised as providing a useful framework for predicting future losses, and guiding efforts for pre-emptive conservation actions. In this study, we used a reconstructed phylogenetic tree of angiosperm species of the Eastern Arc Mountains – an important African biodiversity hotspot – and described the distribution of extinction risk across taxonomic ranks and phylogeny. We provide evidence for both taxonomic and phylogenetic selectivity in extinction risk. However, we found that selectivity varies with IUCN extinction risk category. Vulnerable species are more closely related than expected by chance, whereas endangered and critically endangered species are not significantly clustered on the phylogeny. We suggest that the general observation for taxonomic and phylogenetic selectivity (i.e. phylogenetic signal, the tendency of closely related species to share similar traits) in extinction risks is therefore largely driven by vulnerable species, and not necessarily the most highly threatened. We also used information on altitudinal distribution and climate to generate a predictive model of at-risk species richness, and found that greater threatened species richness is found at higher altitude, allowing for more informed conservation decision making. Our results indicate that evolutionary history can help predict plant susceptibility to extinction threats in the hyper-diverse but woefully-understudied Eastern Arc Mountains, and illustrate the contribution of phylogenetic approaches in conserving African floristic biodiversity where detailed ecological and evolutionary data are often lacking.     

Predicting food‐web structure with metacommunity models

Synthesis Metacommunity theory aims to elucidate the relative influence of local and regional‐scale processes in generating diversity patterns across the landscape. Metacommunity research has focused largely on assemblages of competing organisms within a single trophic level. Here, we test the ability of metacommunity models to predict the network structure of the aquatic food web found in the leaves of the northern pitcher plant Sarracenia purpurea. The species‐sorting and patch‐dynamics models most accurately reproduced nine food web properties, suggesting that local‐scale interactions play an important role in structuring Sarracenia food webs. Our approach can be applied to any well‐resolved food web for which data are available from multiple locations. The metacommunity framework explores the relative influence of local and regional‐scale processes in generating diversity patterns across the landscape. Metacommunity models and empirical studies have focused mostly on assemblages of competing organisms within a single trophic level. Studies of multi‐trophic metacommunities are predominantly restricted to simplified trophic motifs and rarely consider entire food webs. We tested the ability of the patch‐dynamics, species‐sorting, mass‐effects, and neutral metacommunity models, as well as three hybrid models, to reproduce empirical patterns of food web structure and composition in the complex aquatic food web found in the northern pitcher plant Sarracenia purpurea. We used empirical data to determine regional species pools and estimate dispersal probabilities, simulated local food‐web dynamics, dispersed species from regional pools into local food webs at rates based on the assumptions of each metacommunity model, and tested their relative fits to empirical data on food‐web structure. The species‐sorting and patch‐dynamics models most accurately reproduced nine food web properties, suggesting that local‐scale interactions were important in structuring Sarracenia food webs. However, differences in dispersal abilities were also important in models that accurately reproduced empirical food web properties. Although the models were tested using pitcher‐plant food webs, the approach we have developed can be applied to any well‐resolved food web for which data are available from multiple locations.     

Invasions cause biodiversity loss and community simplification in vertebrate food webs

Global change is increasing the occurrence of perturbation events on natural communities, with biological invasions posing a major threat to ecosystem integrity and functioning worldwide. Most studies addressing biological invasions have focused on individual species or taxonomic groups to understand both, the factors determining invasion success and their effects on native species. A more holistic approach that considers multispecies communities and species’ interactions can contribute to a better understanding of invasion effects on complex communities. Here we address biological invasions on species‐rich food webs. We performed in silico experiments on empirical vertebrate food webs by introducing virtual species characterised by different ecological roles and belonging to different trophic groups. We varied a number of invasive species traits, including their diet breadth, the number of predators attacking them, and the bioenergetic thresholds below which invader and native species become extinct. We found that simpler food webs were more vulnerable to invasions, and that relatively less connected mammals were the most successful invaders. Invasions altered food web structure by decreasing species richness and the number of links per species, with most extinctions affecting poorly connected birds. Our food web approach allows identifying the combinations of trophic factors that facilitate or prevent biological invasions, and it provides testable predictions on the effects of invasions on the structure and dynamics of multitrophic communities.     

The role of body mass in diet contiguity and food-web structure

1. The idea that species occupy distinct niches is a fundamental concept in ecology. Classically, the niche was described as an n-dimensional hypervolume where each dimension represents a biotic or abiotic characteristic. More recently, it has been hypothesised that a single dimension may be sufficient to explain the system-level organization of trophic interactions observed between species in a community. 2. Here, we test the hypothesis that species body mass is that single dimension. Specifically, we determine how the intervality of food webs ordered by body size compares to that of randomly ordered food webs. We also extend this analysis beyond the community level to the effect of body mass in explaining the diets of individual species. 3. We conclude that body mass significantly explains the ordering of species and the contiguity of diets in empirical communities. 4. At the species-specific level, we find that the degree to which body mass is a significant explanatory variable depends strongly on the phylogenetic history, suggesting that other evolutionarily conserved traits partly account for species' roles in the food web. 5. Our investigation of the role of body mass in food webs thus helps us to better understand the important features of community food-web structure and the evolutionary forces that have led us to the communities we observe.     

Predicting rates of interspecific interaction from phylogenetic trees

Integrating phylogenetic information can potentially improve our ability to explain species' traits, patterns of community assembly, the network structure of communities, and ecosystem function. In this study, we use mathematical models to explore the ecological and evolutionary factors that modulate the explanatory power of phylogenetic information for communities of species that interact within a single trophic level. We find that phylogenetic relationships among species can influence trait evolution and rates of interaction among species, but only under particular models of species interaction. For example, when interactions within communities are mediated by a mechanism of phenotype matching, phylogenetic trees make specific predictions about trait evolution and rates of interaction. In contrast, if interactions within a community depend on a mechanism of phenotype differences, phylogenetic information has little, if any, predictive power for trait evolution and interaction rate. Together, these results make clear and testable predictions for when and how evolutionary history is expected to influence contemporary rates of species interaction.     

Differences in evolutionary history translate into differences in invasion success of alien mammals in South Africa

Attempts to investigate the drivers of invasion success are generally limited to the biological and evolutionary traits distinguishing native from introduced species. Although alien species introduced to the same recipient environment differ in their invasion intensity – for example, some are “strong invaders”; others are “weak invaders” – the factors underlying the variation in invasion success within alien communities are little explored. In this study, we ask what drives the variation in invasion success of alien mammals in South Africa. First, we tested for taxonomic and phylogenetic signal in invasion intensity. Second, we reconstructed predictive models of the variation in invasion intensity among alien mammals using the generalized linear mixed‐effects models. We found that the family Bovidae and the order Artiodactyla contained more “strong invaders” than expected by chance, and that such taxonomic signal did not translate into phylogenetic selectivity. In addition, our study indicates that latitude, gestation length, social group size, and human population density are only marginal determinant of the variation in invasion success. However, we found that evolutionary distinctiveness – a parameter characterising the uniqueness of each alien species – is the most important predictive variable. Our results indicate that the invasive behavior of alien mammals may have been “fingerprinted” in their evolutionary past, and that evolutionary history might capture beyond ecological, biological and life‐history traits usually prioritized in predictive modeling of invasion success. These findings have applicability to the management of alien mammals in South Africa.     

Predicting plant responses to mycorrhizae: integrating evolutionary history and plant traits

We assessed whether (1) arbuscular mycorrhizal colonization of roots (RC) and/or plant responses to arbuscular mycorrhizae (MR) vary with plant phylogeny and (2) MR and RC can be more accurately predicted with a phylogenetic predictor relative to a null model and models with plant trait and taxonomic predictors. In a previous study, MR and RC of 95 grassland species were measured. We constructed a phylogeny for these species and found it explained variation in MR and RC. Next, we used multiple regressions to identify the models that most accurately predicted plant MR. Models including either phylogenetic or phenotypic and taxonomic information similarly improved our ability to predict MR relative to a null model. Our study illustrates the complex evolutionary associations among species and constraints of using phylogenetic information, relative to plant traits, to predict how a plant species will interact with AMF.     

Interspecific plant functional variation prevails over intraspecific variation in driving spider beta diversity

1. Non-trophic interactions between plants and animals can affect community structure and species trait composition. However, it is unclear how changes in intra- and interspecific morphological traits of plant species affect non-trophic interactions at a metacommunity scale. Additionally, whether plant evolutionary history determines taxonomic and functional diversity of plant-dwelling predators is an open question. 2. To address these gaps, this study used a published dataset with spiders dwelling exclusively on bromeliads to investigate if: (i) intra- and interspecific variability in host plant morphological traits affects spider taxonomic and functional diversity; and (ii) bromeliad trait evolution determines present-day patterns of spider trait diversity. 3. Spider and bromeliad traits were measured, and a new statistical framework was used to quantify the response of spider beta diversity to intra- and interspecific variation in bromeliad traits. In addition, bromeliad traits were decomposed across its phylogenetic tree to check whether the current variation in morphological traits of bromeliads is a result of either ancestral or recent diversification. 4. Bromeliad intraspecific variation did not affect spiders, but leaf length variation between bromeliad species had a positive effect on spider functional beta diversity. Interestingly, the most ancestral split between two subfamilies explained most of the variation in bromeliad species, which suggests that spider functional diversity could represent an outcome of bromeliad evolutionary history. 5. Overall, the results of this study suggest that interactions between plants and organisms that do not feed directly on their tissues could be shaped by plant evolutionary history, which in turn suggests that non-trophic interactions can be maintained over time.