On the prevalence and dynamics of inverted trophic pyramids and otherwise top-heavy communities.

Classically, biomass partitioning across trophic levels was thought to add up to a pyramidal distribution. Numerous exceptions have, however, been noted including complete pyramidal inversions. Elevated levels of biomass top-heaviness (i.e. high consumer/resource biomass ratios) have been reported from Arctic tundra communities to Brazilian phytotelmata, and in species assemblages as diverse as those dominated by sharks and ants. We highlight two major pathways for creating top-heaviness, via: (1) endogenous channels that enhance energy transfer across trophic boundaries within a community and (2) exogenous pathways that transfer energy into communities from across spatial and temporal boundaries. Consumer-resource models and allometric trophic network models combined with niche models reveal the nature of core mechanisms for promoting top-heaviness. Outputs from these models suggest that top-heavy communities can be stable, but they also reveal sources of instability. Humans are both increasing and decreasing top-heaviness in nature with ecological consequences. Current and future research on the drivers of top-heaviness can help elucidate fundamental mechanisms that shape the architecture of ecological communities and govern energy flux within and between communities. Questions emerging from the study of top-heaviness also usefully draw attention to the incompleteness and inconsistency by which ecologists often establish definitional boundaries for communities.

Approaching a state shift in Earth's biosphere.

Localized ecological systems are known to shift abruptly and irreversibly from one state to another when they are forced across critical thresholds. Here we review evidence that the global ecosystem as a whole can react in the same way and is approaching a planetary-scale critical transition as a result of human influence. The plausibility of a planetary-scale 'tipping point' highlights the need to improve biological forecasting by detecting early warning signs of critical transitions on global as well as local scales, and by detecting feedbacks that promote such transitions. It is also necessary to address root causes of how humans are forcing biological changes.

Niche partitioning due to adaptive foraging reverses effects of nestedness and connectance on pollination network stability.

Much research debates whether properties of ecological networks such as nestedness and connectance stabilise biological communities while ignoring key behavioural aspects of organisms within these networks. Here, we computationally assess how adaptive foraging (AF) behaviour interacts with network architecture to determine the stability of plant-pollinator networks. We find that AF reverses negative effects of nestedness and positive effects of connectance on the stability of the networks by partitioning the niches among species within guilds. This behaviour enables generalist pollinators to preferentially forage on the most specialised of their plant partners which increases the pollination services to specialist plants and cedes the resources of generalist plants to specialist pollinators. We corroborate these behavioural preferences with intensive field observations of bee foraging. Our results show that incorporating key organismal behaviours with well-known biological mechanisms such as consumer-resource interactions into the analysis of ecological networks may greatly improve our understanding of complex ecosystems.

Parasites affect food web structure primarily through increased diversity and complexity.

Comparative research on food web structure has revealed generalities in trophic organization, produced simple models, and allowed assessment of robustness to species loss. These studies have mostly focused on free-living species. Recent research has suggested that inclusion of parasites alters structure. We assess whether such changes in network structure result from unique roles and traits of parasites or from changes to diversity and complexity. We analyzed seven highly resolved food webs that include metazoan parasite data. Our analyses show that adding parasites usually increases link density and connectance (simple measures of complexity), particularly when including concomitant links (links from predators to parasites of their prey). However, we clarify prior claims that parasites "dominate" food web links. Although parasites can be involved in a majority of links, in most cases classic predation links outnumber classic parasitism links. Regarding network structure, observed changes in degree distributions, 14 commonly studied metrics, and link probabilities are consistent with scale-dependent changes in structure associated with changes in diversity and complexity. Parasite and free-living species thus have similar effects on these aspects of structure. However, two changes point to unique roles of parasites. First, adding parasites and concomitant links strongly alters the frequency of most motifs of interactions among three taxa, reflecting parasites' roles as resources for predators of their hosts, driven by trophic intimacy with their hosts. Second, compared to free-living consumers, many parasites' feeding niches appear broader and less contiguous, which may reflect complex life cycles and small body sizes. This study provides new insights about generic versus unique impacts of parasites on food web structure, extends the generality of food web theory, gives a more rigorous framework for assessing the impact of any species on trophic organization, identifies limitations of current food web models, and provides direction for future structural and dynamical models.

Effects of trophic similarity on community composition.

Understanding how ecological processes determine patterns among species coexisting within ecosystems is central to ecology. Here, we explore relationships between species' local coexistence and their trophic niches in terms of their feeding relationships both as consumers and as resources. We build on recent concepts and methods from community phylogenetics to develop a framework for analysing mechanisms responsible for community composition using trophic similarity among species and null models of community assembly. We apply this framework to 50 food webs found in 50 Adirondack lakes and find that species composition in these communities appears to be driven by both bottom-up effects by which the presence of prey species selects for predators of those prey, and top-down effects by which prey more tolerant of predation out-compete less tolerant prey of the same predators. This approach to community food webs is broadly applicable and shows how species interaction networks can inform an increasingly large array of theory central to community ecology.

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.

Mechanistic theory and modelling of complex food-web dynamics in Lake Constance.

Mechanistic understanding of consumer-resource dynamics is critical to predicting the effects of global change on ecosystem structure, function and services. Such understanding is severely limited by mechanistic models' inability to reproduce the dynamics of multiple populations interacting in the field. We surpass this limitation here by extending general consumer-resource network theory to the complex dynamics of a specific ecosystem comprised by the seasonal biomass and production patterns in a pelagic food web of a large, well-studied lake. We parameterised our allometric trophic network model of 24 guilds and 107 feeding relationships using the lake's food web structure, initial spring biomasses and body-masses. Adding activity respiration, the detrital loop, minimal abiotic forcing, prey resistance and several empirically observed rates substantially increased the model's fit to the observed seasonal dynamics and the size-abundance distribution. This process illuminates a promising approach towards improving food-web theory and dynamic models of specific habitats.

More than a meal integrating non-feeding interactions into food webs.

Organisms eating each other are only one of many types of well documented and important interactions among species. Other such types include habitat modification, predator interference and facilitation. However, ecological network research has been typically limited to either pure food webs or to networks of only a few (<3) interaction types. The great diversity of non-trophic interactions observed in nature has been poorly addressed by ecologists and largely excluded from network theory. Herein, we propose a conceptual framework that organises this diversity into three main functional classes defined by how they modify specific parameters in a dynamic food web model. This approach provides a path forward for incorporating non-trophic interactions in traditional food web models and offers a new perspective on tackling ecological complexity that should stimulate both theoretical and empirical approaches to understanding the patterns and dynamics of diverse species interactions in nature.

Simple prediction of interaction strengths in complex food webs.

Darwin's classic image of an "entangled bank" of interdependencies among species has long suggested that it is difficult to predict how the loss of one species affects the abundance of others. We show that for dynamical models of realistically structured ecological networks in which pair-wise consumer-resource interactions allometrically scale to the (3/4) power--as suggested by metabolic theory--the effect of losing one species on another can be predicted well by simple functions of variables easily observed in nature. By systematically removing individual species from 600 networks ranging from 10-30 species, we analyzed how the strength of 254,032 possible pair-wise species interactions depended on 90 stochastically varied species, link, and network attributes. We found that the interaction strength between a pair of species is predicted well by simple functions of the two species' biomasses and the body mass of the species removed. On average, prediction accuracy increases with network size, suggesting that greater web complexity simplifies predicting interaction strengths. Applied to field data, our model successfully predicts interactions dominated by trophic effects and illuminates the sign and magnitude of important nontrophic interactions.

Compilation and network analyses of cambrian food webs.

A rich body of empirically grounded theory has developed about food webs--the networks of feeding relationships among species within habitats. However, detailed food-web data and analyses are lacking for ancient ecosystems, largely because of the low resolution of taxa coupled with uncertain and incomplete information about feeding interactions. These impediments appear insurmountable for most fossil assemblages; however, a few assemblages with excellent soft-body preservation across trophic levels are candidates for food-web data compilation and topological analysis. Here we present plausible, detailed food webs for the Chengjiang and Burgess Shale assemblages from the Cambrian Period. Analyses of degree distributions and other structural network properties, including sensitivity analyses of the effects of uncertainty associated with Cambrian diet designations, suggest that these early Paleozoic communities share remarkably similar topology with modern food webs. Observed regularities reflect a systematic dependence of structure on the numbers of taxa and links in a web. Most aspects of Cambrian food-web structure are well-characterized by a simple "niche model," which was developed for modern food webs and takes into account this scale dependence. However, a few aspects of topology differ between the ancient and recent webs: longer path lengths between species and more species in feeding loops in the earlier Chengjiang web, and higher variability in the number of links per species for both Cambrian webs. Our results are relatively insensitive to the exclusion of low-certainty or random links. The many similarities between Cambrian and recent food webs point toward surprisingly strong and enduring constraints on the organization of complex feeding interactions among metazoan species. The few differences could reflect a transition to more strongly integrated and constrained trophic organization within ecosystems following the rapid diversification of species, body plans, and trophic roles during the Cambrian radiation. More research is needed to explore the generality of food-web structure through deep time and across habitats, especially to investigate potential mechanisms that could give rise to similar structure, as well as any differences.

Unified spatial scaling of species and their trophic interactions.

Two largely independent bodies of scaling theory address the quantitative relationships between habitat area, species diversity and trophic interactions. Spatial theory within macroecology addresses how species richness scales with area in landscapes, while typically ignoring interspecific interactions. Complexity theory within community ecology addresses how trophic links scale with species richness in food webs, while typically ignoring spatial considerations. Recent studies suggest unifying these theories by demonstrating how spatial patterns influence food-web structure and vice versa. Here, we follow this suggestion by developing and empirically testing a more unified scaling theory. On the basis of power-law species-area relationships, we develop link-area and non-power-law link-species models that accurately predict how trophic links scale with area and species richness of microcosms, lakes and streams from community to metacommunity levels. In contrast to previous models that assume that species richness alone determines the number of trophic links, these models include the species' spatial distribution, and hence extend the domain of complexity theory to metacommunity scales. This generality and predictive success shows how complexity theory and spatial theory can be unified into a much more general theory addressing new domains of ecology.

Mutualism increases diversity, stability, and function of multiplex networks that integrate pollinators into food webs.

Ecosystems are composed of complex networks of many species interacting in different ways. While ecologists have long studied food webs of feeding interactions, recent studies increasingly focus on mutualistic networks including plants that exchange food for reproductive services provided by animals such as pollinators. Here, we synthesize both types of consumer-resource interactions to better understand the controversial effects of mutualism on ecosystems at the species, guild, and whole-community levels. We find that consumer-resource mechanisms underlying plant-pollinator mutualisms can increase persistence, productivity, abundance, and temporal stability of both mutualists and non-mutualists in food webs. These effects strongly increase with floral reward productivity and are qualitatively robust to variation in the prevalence of mutualism and pollinators feeding upon resources in addition to rewards. This work advances the ability of mechanistic network theory to synthesize different types of interactions and illustrates how mutualism can enhance the diversity, stability, and function of complex ecosystems.

Simulated evolution assembles more realistic food webs with more functionally similar species than invasion.

While natural communities are assembled by both ecological and evolutionary processes, ecological assembly processes have been studied much more and are rarely compared with evolutionary assembly processes. We address these disparities here by comparing community food webs assembled by simulating introductions of species from regional pools of species and from speciation events. Compared to introductions of trophically dissimilar species assumed to be more typical of invasions, introducing species trophically similar to native species assumed to be more typical of sympatric or parapatric speciation events caused fewer extinctions and assembled more empirically realistic networks by introducing more persistent species with higher trophic generality, vulnerability, and enduring similarity to native species. Such events also increased niche overlap and the persistence of both native and introduced species. Contrary to much competition theory, these findings suggest that evolutionary and other processes that more tightly pack ecological niches contribute more to ecosystem structure and function than previously thought.

Predator traits determine food-web architecture across ecosystems.

Predator-prey interactions in natural ecosystems generate complex food webs that have a simple universal body-size architecture where predators are systematically larger than their prey. Food-web theory shows that the highest predator-prey body-mass ratios found in natural food webs may be especially important because they create weak interactions with slow dynamics that stabilize communities against perturbations and maintain ecosystem functioning. Identifying these vital interactions in real communities typically requires arduous identification of interactions in complex food webs. Here, we overcome this obstacle by developing predator-trait models to predict average body-mass ratios based on a database comprising 290 food webs from freshwater, marine and terrestrial ecosystems across all continents. We analysed how species traits constrain body-size architecture by changing the slope of the predator-prey body-mass scaling. Across ecosystems, we found high body-mass ratios for predator groups with specific trait combinations including (1) small vertebrates and (2) large swimming or flying predators. Including the metabolic and movement types of predators increased the accuracy of predicting which species are engaged in high body-mass ratio interactions. We demonstrate that species traits explain striking patterns in the body-size architecture of natural food webs that underpin the stability and functioning of ecosystems, paving the way for community-level management of the most complex natural ecosystems.

Parasites in food webs: the ultimate missing links.

Parasitism is the most common consumer strategy among organisms, yet only recently has there been a call for the inclusion of infectious disease agents in food webs. The value of this effort hinges on whether parasites affect food-web properties. Increasing evidence suggests that parasites have the potential to uniquely alter food-web topology in terms of chain length, connectance and robustness. In addition, parasites might affect food-web stability, interaction strength and energy flow. Food-web structure also affects infectious disease dynamics because parasites depend on the ecological networks in which they live. Empirically, incorporating parasites into food webs is straightforward. We may start with existing food webs and add parasites as nodes, or we may try to build food webs around systems for which we already have a good understanding of infectious processes. In the future, perhaps researchers will add parasites while they construct food webs. Less clear is how food-web theory can accommodate parasites. This is a deep and central problem in theoretical biology and applied mathematics. For instance, is representing parasites with complex life cycles as a single node equivalent to representing other species with ontogenetic niche shifts as a single node? Can parasitism fit into fundamental frameworks such as the niche model? Can we integrate infectious disease models into the emerging field of dynamic food-web modelling? Future progress will benefit from interdisciplinary collaborations between ecologists and infectious disease biologists.

Success and its limits among structural models of complex food webs.

1. Following the development of the relatively successful niche model, several other simple structural food web models have been proposed. These models predict the detailed structure of complex food webs given only two input parameters, the numbers of species and the number of feeding links among them. 2. The models claim different degrees of success but have not been compared consistently with each other or with the empirical data. We compared the performance of five structural models rigorously against 10 empirical food webs from a variety of aquatic and terrestrial habitats containing 25-92 species and 68-997 links. 3. All models include near-hierarchical ordering of species' consumption and have identical distributions of the number of prey of each consumer species, but differ in the extent to which species' diets are required to be contiguous and the rules used to assign feeding links. 4. The models perform similarly on a range of food-web properties, including the fraction of top, intermediate and basal species, the standard deviations of generality and connectivity and the fraction of herbivores and omnivores. 5. For other properties, including the standard deviation of vulnerability, the fraction of cannibals and species in loops, mean trophic level, path length, clustering coefficient, maximum similarity and diet discontinuity, there are significant differences in the performance of the different models. 6. While the empirical data do not support the niche model's assumption of diet contiguity, models which relax this assumption all have worse overall performance than the niche model. All the models under-estimate severely the fraction of species that are herbivores and exhibit other important failures that need to be addressed in future research.

Species traits and network structure predict the success and impacts of pollinator invasions.

Species invasions constitute a major and poorly understood threat to plant-pollinator systems. General theory predicting which factors drive species invasion success and subsequent effects on native ecosystems is particularly lacking. We address this problem using a consumer-resource model of adaptive behavior and population dynamics to evaluate the invasion success of alien pollinators into plant-pollinator networks and their impact on native species. We introduce pollinator species with different foraging traits into network models with different levels of species richness, connectance, and nestedness. Among 31 factors tested, including network and alien properties, we find that aliens with high foraging efficiency are the most successful invaders. Networks exhibiting high alien-native diet overlap, fraction of alien-visited plant species, most-generalist plant connectivity, and number of specialist pollinator species are the most impacted by invaders. Our results mimic several disparate observations conducted in the field and potentially elucidate the mechanisms responsible for their variability.

Response of complex food webs to realistic extinction sequences.

Although an ecosystem's response to biodiversity loss depends on the order in which species are lost, the extinction sequences generally used to explore such responses in food webs have been ecologically unrealistic. We investigate how several extinction orders affect the minimum number of secondary extinctions expected within pelagic food webs from 34 temperate freshwater lakes. An ecologically plausible extinction order is derived from the geographically nested pattern of species composition among the lakes and is corroborated by species' pH tolerances. Simulations suggest that lake communities are remarkably robust to this realistic extinction order and highly sensitive to the reverse sequence of species loss. This sensitivity is not well explained by the known sensitivity of networks to the loss of highly connected species but appears to be better explained by our observation that trophic specialists preferentially consume widely distributed species at low risk of extinction. Our results highlight an important aspect of community organization that may help to maintain biodiversity amidst changing environments.

Degree heterogeneity and stability of ecological networks.

A classic measure of ecological stability describes the tendency of a community to return to equilibrium after small perturbations. While many advances show how the network architecture of these communities severely constrains such tendencies, one of the most fundamental properties of network structure, i.e. degree heterogeneity-the variability of the number of links associated with each species, deserves further study. Here we show that the effects of degree heterogeneity on stability vary with different types of interspecific interactions. Degree heterogeneity consistently destabilizes ecological networks with both competitive and mutualistic interactions, while its effects on networks of predator-prey interactions such as food webs depend on prey contiguity, i.e. the extent to which the species consume an unbroken sequence of prey in community niche space. Increasing degree heterogeneity tends to stabilize food webs except those with the highest prey contiguity. These findings help explain why food webs are highly but not completely interval and, more broadly, deepen our understanding of the stability of complex ecological networks.

Allometric scaling enhances stability in complex food webs.

Classic local stability theory predicts that complex ecological networks are unstable and are unlikely to persist despite empiricists' abundant documentation of such complexity in nature. This contradiction has puzzled biologists for decades. While some have explored how stability may be achieved in small modules of a few interacting species, rigorous demonstrations of how large complex and ecologically realistic networks dynamically persist remain scarce and inadequately understood. Here, we help fill this void by combining structural models of complex food webs with nonlinear bioenergetic models of population dynamics parameterized by biological rates that are allometrically scaled to populations' average body masses. Increasing predator-prey body mass ratios increase population persistence up to a saturation level that is reached by invertebrate and ectotherm vertebrate predators when being 10 or 100 times larger than their prey respectively. These values are corroborated by empirical predator-prey body mass ratios from a global data base. Moreover, negative effects of diversity (i.e. species richness) on stability (i.e. population persistence) become neutral or positive relationships at these empirical ratios. These results demonstrate that the predator-prey body mass ratios found in nature may be key to enabling persistence of populations in complex food webs and stabilizing the diversity of natural ecosystems.