The probabilistic niche model reveals the niche structure and role of body size in a complex food web

Linking biodiversity, ecosystem function, and Nature's contributions to people: a macroecological energy flux perspective

At macroecological scales, the provision of Nature's contributions to people (NCP) is mostly estimated with biophysical information, ignoring the ecological processes underlying them. This hinders our ability to properly quantify the impact of declining biodiversity and the provision of NCP. Here, we propose a framework that combines local-scale food web energy flux approaches and large-scale biodiversity models to evaluate ecosystem functions and flux-related NCP at extensive spatiotemporal scales. Importantly, this approach has the potential to upscale ecosystem functions, assess the vulnerability of flux-related NCP to the climate crisis, and support the development of multiscale mitigation policies.

How realistic features affect the stability of an Arctic marine food web model

Rapid sea-ice decline and warmer waters are threatening the stability of Arctic ecosystems and potentially forcing their restructuring. Mathematical models that support observational evidence are becoming increasingly important. We develop a food web model for the Southern Beaufort Sea based on species with high ecological significance. Generalized modeling is applied to study the impact of realistic characteristics on food web stability; a powerful method that provides a linear stability analysis for systems with uncertainty in data and underlying physical processes. We find that including predator-specific foraging traits, weighted predator-prey interactions, and habitat constraints increase food-web stability. The absence of a fierce top predator (killer whale, polar bear, etc.) also significantly increases the portion of stable webs. Adding ecosystem background noise in terms of a collective impact of latent, minor ecosystem members shows a peak in stability at an optimum, relatively small background pressure. These results indicate that refining models with more realistic detail to account for the complexity of the ecological system may be key to bridge the gap between empirical observations and model predictions in ecosystem stability.

Changes in vertical and horizontal diversities mediated by the size structure of introduced fish collectively shape food-web stability

Species introductions can alter local food-web structure by changing the vertical or horizontal diversity within communities, largely driven by their body size distributions. Increasing vertical and horizontal diversities is predicted to have opposing effects on stability. However, their interactive effects remain largely overlooked. We investigated the independent and collective effects of vertical and horizontal diversities on food-web stability in alpine lakes stocked with variable body size distributions of introduced fish species. Introduced predators destabilize food-webs by increasing vertical diversity through food chain lengthening. Alternatively, increasing horizontal diversity results in more stable food-web topologies. A non-linear interaction between vertical and horizontal diversities suggests that increasing vertical diversity is most destabilizing when horizontal diversity is low. Our findings suggest that the size structure of introduced predators drives their impacts on stability by modifying the structure of food-webs, and highlights the interactive effects of vertical and horizontal diversities on stability.

Body size of fungus-growing termites infers on the volume and density of their fungal cultivar

The body size of an animal plays a crucial role in determining its trophic level and position within the food web, as well as its interactions with other species. In the symbiosis between Termitomyces and fungus-growing termites, termites rely on nutrition of fungal nodules produced by Termitomyces. To understand whether the size of termites and fungal nodules are related to their partner specificity, we quantified the size of termite farmer caste, and the size and density of nodules in termite nests of four genera of fungus-growing termites, and identified their cultivated Termitomyces fungus species based on internal transcribed spacer regions and partial large subunit ribosomal RNA gene sequences. The results showed that the size and density of fungal nodules were different among Termitomyces clades and revealed a constant trade-off between size and density among clades. The nodule size of each clade has low variation and fits normal distribution, indicating that size is a stabilized trait. Moreover, we found larger termite genera cultivated Termitomyces with larger but less numerous nodules. Based on these results, we concluded that there is a size specificity between Termitomyces and fungus-growing termites, which may lead to diversification of Termitomyces as adaptations to different termite genera.

Predicting ecosystem metaphenome from community metagenome: A grand challenge for environmental biology

Elucidating how an organism's characteristics emerge from its DNA sequence has been one of the great triumphs of biology. This triumph has cumulated in sophisticated computational models that successfully predict how an organism's detailed phenotype emerges from its specific genotype. Inspired by that effort's vision and empowered by its methodologies, a grand challenge is described here that aims to predict the biotic characteristics of an ecosystem, its metaphenome, from nucleic acid sequences of all the species in its community, its metagenome. Meeting this challenge would integrate rapidly advancing abilities of environmental nucleic acids (eDNA and eRNA) to identify organisms, their ecological interactions, and their evolutionary relationships with advances in mechanistic models of complex ecosystems. Addressing the challenge would help integrate ecology and evolutionary biology into a more unified and successfully predictive science that can better help describe and manage ecosystems and the services they provide to humanity.

Combining Geographic Distribution and Trait Information to Infer Predator–Prey Species-Level Interaction Properties

Biotic interactions are a key component of the proper functioning of ecosystems. However, information on biotic interactions is spatially and taxonomically biased and limited to several groups. The most efficient strategy to fill these gaps is to combine spatial information (species ranges) with different sources of information (functional and field data) to infer potential interactions. This approach is possible due to the fact that there is a correspondence between the traits of two trophic levels (e.g., predator and prey sizes are correlated). Therefore, our objective was to evaluate the performance of the joint use of spatial, functional and field data to infer properties of the predator–prey interaction for five neotropical cats. To do this, we used presence–absence matrices to obtain lists of potential prey species per grid-cell for each predator range. These lists were filtered according to different criteria (models), and for each model, an interaction property was estimated and compared with field observations. Our results show that the use of functional information and co-occurrence allows us to generate values similar to those observed in the field. We also observed that there were differences in model performance related to the intrinsic characteristics of the predator (body size) and the interaction property being evaluated.

A size-constrained feeding-niche model distinguishes predation patterns between aquatic and terrestrial food webs

Understanding the formation of feeding links provides insights into processes underlying food webs. Generally, predators feed on prey within a certain body-size range, but a systematic quantification of such feeding niches is lacking. We developed a size-constrained feeding-niche (SCFN) model and parameterized it with information on both realized and non-realized feeding links in 72 aquatic and 65 terrestrial food webs. Our analyses revealed profound differences in feeding niches between aquatic and terrestrial predators and variation along a temperature gradient. Specifically, the predator-prey body-size ratio and the range in prey sizes increase with the size of aquatic predators, whereas they are nearly constant across gradients in terrestrial predator size. Overall, our SCFN model well reproduces the feeding relationships and predation architecture across 137 natural food webs (including 3878 species and 136,839 realized links). Our results illuminate the organisation of natural food webs and enables novel trait-based and environment-explicit modelling approaches.

Combining food web theory and population dynamics to assess the impact of invasive species

The impacts of invasive species on resident communities are driven by a tangle of ecological interactions difficult to quantify empirically. Combining a niche model with a population dynamic model, both allometrically parametrized, may represent a consistent framework to investigate invasive species impacts on resident communities in a food web context when empirical data are scarce. We used this framework to assess the ecological consequences of an invasive apex predator (Silurus glanis) in peri-Alpine lake food webs. Both increases and decreases of resident species abundances were highlighted and differed when accounting for different S. glanis body sizes. Complementarily, the prominence of indirect effects, such as trophic cascades, suggested that common approaches may only capture a restricted fraction of invasion consequences through direct predation or competition. By leveraging widely available biodiversity data, our approach may provide relevant insights for a comprehensive assessment and management of invasive species impacts on aquatic ecosystems.

Inferring Size-Based Functional Responses From the Physical Properties of the Medium

First derivations of the functional response were mechanistic, but subsequent uses of these functions tended to be phenomenological. Further understanding of the mechanisms underpinning predator-prey relationships might lead to novel insights into functional response in natural systems. Because recent consideration of the physical properties of the environment has improved our understanding of predator-prey interactions, we advocate the use of physics-based approaches for the derivation of the functional response from first principles. These physical factors affect the functional response by constraining the ability of both predators and prey to move according to their size. A physics-based derivation of the functional response should thus consider the movement of organisms in relation to their physical environment. One recent article presents a model along these criteria. As an initial validation of our claim, we use a slightly modified version of this model to derive the classical parameters of the functional response (i.e., attack rate and handling time) of aquatic organisms, as affected by body size, buoyancy, water density and viscosity. We compared the predictions to relevant data. Our model provided good fit for most parameters, but failed to predict handling time. Remarkably, this is the only parameter whose derivation did not rely on physical principles. Parameters in the model were not estimated from observational data. Hence, systematic discrepancies between predictions and real data point immediately to errors in the model. An added benefit to functional response derivation from physical principles is thus to provide easy ways to validate or falsify hypotheses about predator-prey relationships.

Inferring species interactions from ecological survey data: A mechanistic approach to predict quantitative food webs of seed feeding by carabid beetles

Ecological networks are valuable for ecosystem analysis but their use is often limited by a lack of data because many types of ecological interaction, for example, predation, are short-lived and difficult to observe or detect. While there are different methods for inferring the presence of interactions, they have rarely been used to predict the interaction strengths that are required to construct weighted, or quantitative, ecological networks.Here, we develop a trait-based approach suitable for inferring weighted networks, that is, with varying interaction strengths. We developed the method for seed-feeding carabid ground beetles (Coleoptera: Carabidae) although the principles can be applied to other species and types of interaction.Using existing literature data from experimental seed-feeding trials, we predicted a per-individual interaction cost index based on carabid and seed size. This was scaled up to the population level to create inferred weighted networks using the abundance of carabids and seeds from empirical samples and energetic intake rates of carabids from the literature. From these weighted networks, we also derived a novel measure of expected predation pressure per seed type per network.This method was applied to existing ecological survey data from 255 arable fields with carabid data from pitfall traps and plant seeds from seed rain traps. Analysis of these inferred networks led to testable hypotheses about how network structure and predation pressure varied among fields.Inferred networks are valuable because (a) they provide null models for the structuring of food webs to test against empirical species interaction data, for example, DNA analysis of carabid gut regurgitates and (b) they allow weighted networks to be constructed whenever we can estimate interactions between species and have ecological census data available. This permits ecological network analysis even at times and in places when interactions were not directly assessed.

Probing the Ecology and Climate of the Eocene Southern Ocean With Sand Tiger Sharks Striatolamia macrota

Many explanations for Eocene climate change focus on the Southern Ocean-where tectonics influenced oceanic gateways, ocean circulation reduced heat transport, and greenhouse gas declines prompted glaciation. To date, few studies focus on marine vertebrates at high latitudes to discern paleoecological and paleoenvironmental impacts of this climate transition. The Tertiary Eocene La Meseta (TELM) Formation has a rich fossil assemblage to characterize these impacts; Striatolamia macrota, an extinct (†) sand tiger shark, is abundant throughout the La Meseta Formation. Body size is often tracked to characterize and integrate across multiple ecological dimensions. †S. macrota body size distributions indicate limited changes during TELMs 2-5 based on anterior tooth crown height (n = 450, mean = 19.6 ± 6.4 mm). Similarly, environmental conditions remained stable through this period based on δ18OPO4 values from tooth enameloid (n = 42; 21.5 ± 1.6‰), which corresponds to a mean temperature of 22.0 ± 4.0°C. Our preliminary ε Nd (n = 4) results indicate an early Drake Passage opening with Pacific inputs during TELM 2-3 (45-43 Ma) based on single unit variation with an overall radiogenic trend. Two possible hypotheses to explain these observations are (1) †S. macrota modified its migration behavior to ameliorate environmental changes related to the Drake Passage opening, or (2) the local climate change was small and gateway opening had little impact. While we cannot rule out an ecological explanation, a comparison with climate model results suggests that increased CO2 produces warm conditions that also parsimoniously explain the observations.

Key Node Ranking in Complex Networks: A Novel Entropy and Mutual Information-Based Approach

Numerous problems in many fields can be solved effectively through the approach of modeling by complex network analysis. Finding key nodes is one of the most important and challenging problems in network analysis. In previous studies, methods have been proposed to identify key nodes. However, they rely mainly on a limited field of local information, lack large-scale access to global information, and are also usually NP-hard. In this paper, a novel entropy and mutual information-based centrality approach (EMI) is proposed, which attempts to capture a far wider range and a greater abundance of information for assessing how vital a node is. We have developed countermeasures to assess the influence of nodes: EMI is no longer confined to neighbor nodes, and both topological and digital network characteristics are taken into account. We employ mutual information to fix a flaw that exists in many methods. Experiments on real-world connected networks demonstrate the outstanding performance of the proposed approach in both correctness and efficiency as compared with previous approaches.

Predation risk influences food-web structure by constraining species diet choice

The foraging behaviour of species determines their diet and, therefore, also emergent food-web structure. Optimal foraging theory (OFT) has previously been applied to understand the emergence of food-web structure through a consumer-centric consideration of diet choice. However, the resource-centric viewpoint, where species adjust their behaviour to reduce the risk of predation, has not been considered. We develop a mechanistic model that merges metabolic theory with OFT to incorporate the effect of predation risk on diet choice to assemble food webs. This 'predation-risk-compromise' (PR) model better captures the nestedness and modularity of empirical food webs relative to the classical optimal foraging model. Specifically, compared with optimal foraging alone, risk-mitigated foraging leads to more-nested but less-modular webs by broadening the diet of consumers at intermediate trophic levels. Thus, predation risk significantly affects food-web structure by constraining species' ability to forage optimally, and needs to be considered in future work.

A physical model for efficient ranking in networks

We present a physically inspired model and an efficient algorithm to infer hierarchical rankings of nodes in directed networks. It assigns real-valued ranks to nodes rather than simply ordinal ranks, and it formalizes the assumption that interactions are more likely to occur between individuals with similar ranks. It provides a natural statistical significance test for the inferred hierarchy, and it can be used to perform inference tasks such as predicting the existence or direction of edges. The ranking is obtained by solving a linear system of equations, which is sparse if the network is; thus, the resulting algorithm is extremely efficient and scalable. We illustrate these findings by analyzing real and synthetic data, including data sets from animal behavior, faculty hiring, social support networks, and sports tournaments. We show that our method often outperforms a variety of others, in both speed and accuracy, in recovering the underlying ranks and predicting edge directions.

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.

Modelling food-web mediated effects of hydrological variability and environmental flows

Environmental flows are designed to enhance aquatic ecosystems through a variety of mechanisms; however, to date most attention has been paid to the effects on habitat quality and life-history triggers, especially for fish and vegetation. The effects of environmental flows on food webs have so far received little attention, despite food-web thinking being fundamental to understanding of river ecosystems. Understanding environmental flows in a food-web context can help scientists and policy-makers better understand and manage outcomes of flow alteration and restoration. In this paper, we consider mechanisms by which flow variability can influence and alter food webs, and place these within a conceptual and numerical modelling framework. We also review the strengths and weaknesses of various approaches to modelling the effects of hydrological management on food webs. Although classic bioenergetic models such as Ecopath with Ecosim capture many of the key features required, other approaches, such as biogeochemical ecosystem modelling, end-to-end modelling, population dynamic models, individual-based models, graph theory models, and stock assessment models are also relevant. In many cases, a combination of approaches will be useful. We identify current challenges and new directions in modelling food-web responses to hydrological variability and environmental flow management. These include better integration of food-web and hydraulic models, taking physiologically-based approaches to food quality effects, and better representation of variations in space and time that may create ecosystem control points.

Species traits and interaction rules shape a species-rich seed-dispersal interaction network

Species phenotypic traits affect the interaction patterns and the organization of seed-dispersal interaction networks. Understanding the relationship between species characteristics and network structure help us understand the assembly of natural communities and how communities function. Here, we examine how species traits may affect the rules leading to patterns of interaction among plants and fruit-eating vertebrates. We study a species-rich seed-dispersal system using a model selection approach to examine whether the rules underlying network structure are driven by constraints in fruit resource exploitation, by preferential consumption of fruits by the frugivores, or by a combination of both. We performed analyses for the whole system and for bird and mammal assemblages separately, and identified the animal and plant characteristics shaping interaction rules. The structure of the analyzed interaction network was better explained by constraints in resource exploitation in the case of birds and by preferential consumption of fruits with specific traits for mammals. These contrasting results when looking at bird-plant and mammal-plant interactions suggest that the same type of interaction is organized by different processes depending on the assemblage we focus on. Size-related restrictions of the interacting species (both for mammals and birds) were the most important factors driving the interaction rules. Our results suggest that the structure of seed-dispersal interaction networks can be explained using species traits and interaction rules related to simple ecological mechanisms.

Invasive rodents have multiple indirect effects on seabird island invertebrate food web structure

Burrowing seabirds that nest on islands transfer nutrients from the sea, disturb the soil through burrowing, damage tree foliage when landing, and thereby modify the surface litter. However, seabirds are in decline worldwide, as are their community- and ecosystem-level impacts, primarily due to invasive predatory mammals. The direct and indirect effects of seabird decline on communities and ecosystems are inherently complex. Here we employed network analysis, as a means of simplifying ecological complexity, to better understand the effects seabird loss may have on island invertebrate communities. Using data on leaf litter communities, we constructed invertebrate food webs for each of 18 offshore oceanic islands in northeastern New Zealand, nine of which have high seabird densities and nine of were invaded by rats. Ten network topological metrics (including entropy, generality, and vulnerability) were compared between rat-invaded and uninvaded (seabird-dominant) islands. We found that, on rat-invaded islands, the invertebrate food webs were smaller and less complex than on their seabird-dominated counterparts, which may be due to the suppression of seabird-derived nutrients and consequent effects on trophic cascades. This decreased complexity of food webs due to the presence of rats is indicative of lower ecosystem resistance via lower trophic redundancy. Our results show that rat effects on island ecosystems are manifested throughout entire food webs, and demonstrate how network analysis may be useful to assess ecosystem recovery status as these invaded islands are restored.

Extensions of Island Biogeography Theory predict the scaling of functional trait composition with habitat area and isolation

The Theory of Island Biogeography (TIB) predicts how area and isolation influence species richness equilibrium on insular habitats. However, the TIB remains silent about functional trait composition and provides no information on the scaling of functional diversity with area, an observation that is now documented in many systems. To fill this gap, we develop a probabilistic approach to predict the distribution of a trait as a function of habitat area and isolation, extending the TIB beyond the traditional species-area relationship. We compare model predictions to the body-size distribution of piscivorous and herbivorous fishes found on tropical reefs worldwide. We find that small and isolated reefs have a higher proportion of large-sized species than large and connected reefs. We also find that knowledge of species body-size and trophic position improves the predictions of fish occupancy on tropical reefs, supporting both the allometric and trophic theory of island biogeography. The integration of functional ecology to island biogeography is broadly applicable to any functional traits and provides a general probabilistic approach to study the scaling of trait distribution with habitat area and isolation.

Pleistocene megafaunal interaction networks became more vulnerable after human arrival

The end of the Pleistocene was marked by the extinction of almost all large land mammals worldwide except in Africa. Although the debate on Pleistocene extinctions has focused on the roles of climate change and humans, the impact of perturbations depends on properties of ecological communities, such as species composition and the organization of ecological interactions. Here, we combined palaeoecological and ecological data, food-web models and community stability analysis to investigate if differences between Pleistocene and modern mammalian assemblages help us understand why the megafauna died out in the Americas while persisting in Africa. We show Pleistocene and modern assemblages share similar network topology, but differences in richness and body size distributions made Pleistocene communities significantly more vulnerable to the effects of human arrival. The structural changes promoted by humans in Pleistocene networks would have increased the likelihood of unstable dynamics, which may favour extinction cascades in communities facing extrinsic perturbations. Our findings suggest that the basic aspects of the organization of ecological communities may have played an important role in major extinction events in the past. Knowledge of community-level properties and their consequences to dynamics may be critical to understand past and future extinctions.

The meaning of functional trait composition of food webs for ecosystem functioning

There is a growing interest in using trait-based approaches to characterize the functional structure of animal communities. Quantitative methods have been derived mostly for plant ecology, but it is now common to characterize the functional composition of various systems such as soils, coral reefs, pelagic food webs or terrestrial vertebrate communities. With the ever-increasing availability of distribution and trait data, a quantitative method to represent the different roles of animals in a community promise to find generalities that will facilitate cross-system comparisons. There is, however, currently no theory relating the functional composition of food webs to their dynamics and properties. The intuitive interpretation that more functional diversity leads to higher resource exploitation and better ecosystem functioning was brought from plant ecology and does not apply readily to food webs. Here we appraise whether there are interpretable metrics to describe the functional composition of food webs that could foster a better understanding of their structure and functioning. We first distinguish the various roles that traits have on food web topology, resource extraction (bottom-up effects), trophic regulation (top-down effects), and the ability to keep energy and materials within the community. We then discuss positive effects of functional trait diversity on food webs, such as niche construction and bottom-up effects. We follow with a discussion on the negative effects of functional diversity, such as enhanced competition (both exploitation and apparent) and top-down control. Our review reveals that most of our current understanding of the impact of functional trait diversity on food web properties and functioning comes from an over-simplistic representation of network structure with well-defined levels. We, therefore, conclude with propositions for new research avenues for both theoreticians and empiricists.

Predicting the consequences of species loss using size-structured biodiversity approaches

Understanding the consequences of species loss in complex ecological communities is one of the great challenges in current biodiversity research. For a long time, this topic has been addressed by traditional biodiversity experiments. Most of these approaches treat species as trait-free, taxonomic units characterizing communities only by species number without accounting for species traits. However, extinctions do not occur at random as there is a clear correlation between extinction risk and species traits. In this review, we assume that large species will be most threatened by extinction and use novel allometric and size-spectrum concepts that include body mass as a primary species trait at the levels of populations and individuals, respectively, to re-assess three classic debates on the relationships between biodiversity and (i) food-web structural complexity, (ii) community dynamic stability, and (iii) ecosystem functioning. Contrasting current expectations, size-structured approaches suggest that the loss of large species, that typically exploit most resource species, may lead to future food webs that are less interwoven and more structured by chains of interactions and compartments. The disruption of natural body-mass distributions maintaining food-web stability may trigger avalanches of secondary extinctions and strong trophic cascades with expected knock-on effects on the functionality of the ecosystems. Therefore, we argue that it is crucial to take into account body size as a species trait when analysing the consequences of biodiversity loss for natural ecosystems. Applying size-structured approaches provides an integrative ecological concept that enables a better understanding of each species' unique role across communities and the causes and consequences of biodiversity loss.

Indirect Energy Flows in Niche Model Food Webs: Effects of Size and Connectance

Indirect interactions between species have long been of interest to ecologists. One such interaction type takes place when energy or materials flow via one or more intermediate species between two species with a direct predator-prey relationship. Previous work has shown that, although each such flow is small, their great number makes them important in ecosystems. A new network analysis method, dynamic environ approximation, was used to quantify the fraction of energy flowing from prey to predator over paths of length greater than 1 (flow indirectness or FI) in a commonly studied food web model. Web structure was created using the niche model and dynamics followed the Yodzis-Innes model. The effect of food web size (10 to 40 species) and connectance (0.1 to 0.48) on FI was examined. For each of 250 model realizations run for each pair of size and connectance values, the FI of every predator-prey interaction in the model was computed and then averaged over the whole network. A classification and regression tree (CART) analysis was then used to find the best predictors of FI. The mean FI of the model food webs is 0.092, with a standard deviation of 0.0279. It tends to increase with system size but peaks at intermediate connectance levels. Of 27 potential predictor variables, only five (mean path length, dominant eigenvalue of the adjacency matrix, connectance, mean trophic level and fraction of species belonging to intermediate trophic levels) were selected by the CART algorithm as best accounting for variation in the data; mean path length and the dominant eigenvalue of the adjacency matrix were dominant.

From mice to elephants: overturning the 'one size fits all' paradigm in marine plankton food chains

It is widely believed that consumer control is a weak regulator of marine phytoplankton communities. It remains unclear, however, why this should be the case when marine consumers routinely regulate their prey at higher trophic levels. One possibility is that the weak consumer control of phytoplankton communities results from the inability of field researchers to effectively account for consumer-prey trophic relationships operating at the scale of the plankton. We explored this issue by reviewing studies of trophic control in marine plankton. Experimental studies indicate that size is a critical determinant of feeding relationships among plankton. In sharp contrast, of the 51 field studies reviewed, 78% did not distinguish among the sizes or species of phytoplankton and their consumers, but instead assumed a general bulk phytoplankton-zooplankton trophic connection. Such an approach neglects the possibility that several trophic connections may separate the smallest phytoplankton (0.2 μm) from the larger zooplankton (~ 1000 μm), a remarkable size differential exceeding that between a mouse (~10 cm) and an elephant (~2500 cm). The size-based approach we propose integrates theory, experiments and field observations and has the potential to greatly enhance our understanding of the causes and consequences of recently documented restructuring of plankton communities.

Modelling size structured food webs using a modified niche model with two predator traits

The structure of food webs is frequently described using phenomenological stochastic models. A prominent example, the niche model, was found to produce artificial food webs resembling real food webs according to a range of summary statistics. However, the size structure of food webs generated by the niche model and real food webs has not yet been rigorously compared. To fill this void, I use a body mass based version of the niche model and compare prey-predator body mass allometry and predator-prey body mass ratios predicted by the model to empirical data. The results show that the model predicts weaker size structure than observed in many real food webs. I introduce a modified version of the niche model which allows to control the strength of size-dependence of predator-prey links. In this model, optimal prey body mass depends allometrically on predator body mass and on a second trait, such as foraging mode. These empirically motivated extensions of the model allow to represent size structure of real food webs realistically and can be used to generate artificial food webs varying in several aspects of size structure in a controlled way. Hence, by explicitly including the role of species traits, this model provides new opportunities for simulating the consequences of size structure for food web dynamics and stability.

The role of a water bug, Sigara striata, in freshwater food webs

Freshwater food webs are dominated by aquatic invertebrates whose trophic relationships are often poorly known. Here, I used laboratory experiments to study the role of a water bug, Sigara striata, as a potential predator and prey in food webs of stagnant waters. Multiple-choice predation experiment revealed that Sigara, which had been considered mostly herbivorous, also consumed larvae of Chironomus midges. Because they often occur in high densities and are among the most ubiquitous aquatic insects, Sigara water bugs may be important predators in fresh waters. A second experiment tested the role of Sigara as a potential prey for 13 common invertebrate predators. Mortality of Sigara inflicted by different predators varied widely, especially depending on body mass, foraging mode (ambush/searching) and feeding mode (chewing/suctorial) of the predators. Sigara was highly vulnerable to ambush predators, while searching predators caused on average 8.1 times lower mortality of Sigara. Additionally, suctorial predators consumed on average 6.6 times more Sigara individuals than chewing predators, which supports previous results hinting on potentially different predation pressures of these two types of predators on prey populations. The importance of these two foraging-related traits demonstrates the need to move from body mass based to multiple trait based descriptions of food web structure. Overall, the results suggests that detailed experimental studies of common but insufficiently known species can significantly enhance our understanding of food web structure.

Emergent global patterns of ecosystem structure and function from a mechanistic general ecosystem model

This paper presents the first mathematical model that attempts to represent the biology and behavior of all individual organisms globally, taking us a step closer to holistic ecological and conservation science founded on mechanistic predictions.

Anthropogenic activities are causing widespread degradation of ecosystems worldwide, threatening the ecosystem services upon which all human life depends. Improved understanding of this degradation is urgently needed to improve avoidance and mitigation measures. One tool to assist these efforts is predictive models of ecosystem structure and function that are mechanistic: based on fundamental ecological principles. Here we present the first mechanistic General Ecosystem Model (GEM) of ecosystem structure and function that is both global and applies in all terrestrial and marine environments. Functional forms and parameter values were derived from the theoretical and empirical literature where possible. Simulations of the fate of all organisms with body masses between 10 µg and 150,000 kg (a range of 14 orders of magnitude) across the globe led to emergent properties at individual (e.g., growth rate), community (e.g., biomass turnover rates), ecosystem (e.g., trophic pyramids), and macroecological scales (e.g., global patterns of trophic structure) that are in general agreement with current data and theory. These properties emerged from our encoding of the biology of, and interactions among, individual organisms without any direct constraints on the properties themselves. Our results indicate that ecologists have gathered sufficient information to begin to build realistic, global, and mechanistic models of ecosystems, capable of predicting a diverse range of ecosystem properties and their response to human pressures.

Ecosystems across the world are being rapidly degraded. This threatens their provision of natural goods and services, upon which all life depends. To be able to reduce—and one day reverse—this damage, we need to be able to predict the effects of human actions on ecosystems. Here, we present the first example of a General Ecosystem Model (GEM)—called the Madingley Model—a novel class of computational model that can be applied to any ecosystem, marine or terrestrial, and can be simulated at any spatial scale from local up to global. It covers almost all organisms in ecosystems, from the smallest to the largest, encoding the underlying biology and behaviour of individual organisms to capture the interactions between them and with the environment, to model the fate of each individual organism, and to make predictions about ecosystem structure and function. Predictions made by the Madingley Model broadly resemble what we observe in real-world ecosystems across scales from individuals through to communities, ecosystems, and the world as a whole. Our results show that ecologists can now begin modelling all nonhuman life on earth, and we suggest that this type of approach may hold promise for predicting the ecological implications of different future trajectories of human activity on our shared planet.

Empirical evaluation of neutral interactions in host-parasite networks

While niche-based processes have been invoked extensively to explain the structure of interaction networks, recent studies propose that neutrality could also be of great importance. Under the neutral hypothesis, network structure would simply emerge from random encounters between individuals and thus would be directly linked to species abundance. We investigated the impact of species abundance distributions on qualitative and quantitative metrics of 113 host-parasite networks. We analyzed the concordance between neutral expectations and empirical observations at interaction, species, and network levels. We found that species abundance accurately predicts network metrics at all levels. Despite host-parasite systems being constrained by physiology and immunology, our results suggest that neutrality could also explain, at least partially, their structure. We hypothesize that trait matching would determine potential interactions between species, while abundance would determine their realization.

From projected species distribution to food-web structure under climate change

Climate change is inducing deep modifications in species geographic ranges worldwide. However, the consequences of such changes on community structure are still poorly understood, particularly the impacts on food-web properties. Here, we propose a new framework, coupling species distribution and trophic models, to predict climate change impacts on food-web structure across the Mediterranean Sea. Sea surface temperature was used to determine the fish climate niches and their future distributions. Body size was used to infer trophic interactions between fish species. Our projections reveal that 54 fish species of 256 endemic and native species included in our analysis would disappear by 2080-2099 from the Mediterranean continental shelf. The number of feeding links between fish species would decrease on 73.4% of the continental shelf. However, the connectance of the overall fish web would increase on average, from 0.26 to 0.29, mainly due to a differential loss rate of feeding links and species richness. This result masks a systematic decrease in predator generality, estimated here as the number of prey species, from 30.0 to 25.4. Therefore, our study highlights large-scale impacts of climate change on marine food-web structure with potential deep consequences on ecosystem functioning. However, these impacts will likely be highly heterogeneous in space, challenging our current understanding of climate change impact on local marine ecosystems.

Body mass evolution and diversification within horses (family Equidae)

Horses (family Equidae) are a classic example of adaptive radiation, exhibiting a nearly 60-fold increase in maximum body mass and a peak taxonomic diversity of nearly 100 species across four continents. Such patterns are commonly attributed to niche competition, in which increased taxonomic diversity drives increased size disparity. However, neutral processes, such as macroevolutionary 'diffusion', can produce similar increases in disparity without increased diversity. Using a comprehensive database of Equidae species size estimates and a common mathematical framework, we measure the contributions of diversity-driven and diffusion-driven mechanisms for increased disparity during the Equidae radiation. We find that more than 90% of changes in size disparity are attributable to diffusion alone. These results clarify the role of species competition in body size evolution, indicate that morphological disparity and species diversity may be only weakly coupled in general, and demonstrate that large species may evolve from neutral macroevolutionary diffusion processes alone.