Warming and top-down control of stage-structured prey: Linking theory to patterns in natural systems

Warming has broad and often nonlinear impacts on organismal physiology and traits, allowing it to impact species interactions like predation through a variety of pathways that may be difficult to predict. Predictions are commonly based on short-term experiments and models, and these studies often yield conflicting results depending on the environmental context, spatiotemporal scale, and the predator and prey species considered. Thus, the accuracy of predicted changes in interaction strength, and their importance to the broader ecosystems they take place in, remain unclear. Here, we attempted to link one such set of predictions generated using theory, modeling, and controlled experiments to patterns in the natural abundance of prey across a broad thermal gradient. To do so, we first predicted how warming would impact a stage-structured predator-prey interaction in riverine rock pools between Pantala spp. dragonfly nymph predators and Aedes atropalpus mosquito larval prey. We then described temperature variation across a set of hundreds of riverine rock pools (n = 775) and leveraged this natural gradient to look for evidence for or against our model's predictions. Our model's predictions suggested that warming should weaken predator control of mosquito larval prey by accelerating their development and shrinking the window of time during which aquatic dragonfly nymphs could consume them. This was consistent with data collected in rock pool ecosystems, where the negative effects of dragonfly nymph predators on mosquito larval abundance were weaker in warmer pools. Our findings provide additional evidence to substantiate our model-derived predictions while emphasizing the importance of assessing similar predictions using natural gradients of temperature whenever possible.

Prey selection along a predators' body size gradient evidences the role of different trait-based mechanisms in food web organization

An increase in prey richness, prey size and predator trophic position with predator body size has been consistently reported as prime features of food web organization. These trends have been explained by non-exclusive mechanisms. First, the increase in energy demand with body size determines that larger predators must reduce prey selectivity for achieving the required number of resources, being consumption relationships independent of prey traits. Second, when consumption is restricted by gape limitation, small predators are constrained to select among small prey. However, this selection weakens over large predators, which progressively consume more and larger prey. Finally, the optimal foraging mechanism predicts that larger predators optimize their diet by selecting only large prey with high energy reward. Each one of these mechanisms can individually explain the increase in prey richness, prey size and predator trophic position with predator body size but their relative importance or the direct evidence for their combined role was seldom considered. Here we use the community assembly by trait selection (CATS) theory for evaluating the support for each one of these mechanisms based on the prey selection patterns that they predict. We analyzed how prey body size and trophic guild determine prey selection by predators of increasing body size in a killifish guild from a temporary pond system. Results support the combination of the three mechanisms to explain the structural trends in our food web, although their strength is contingent on prey trophic group. Overall, high energy prey are preferred by larger predators, and small predators select small prey of all trophic status. However, large predators prefer large primary producers and avoid large carnivorous prey, probably because of the inherent risk of consuming other carnivorous. Our study provides a mechanistic understanding of how predator traits determine the selection of prey traits affecting food web assembly.

Simultaneously estimating food web connectance and structure with uncertainty

Food web models explain and predict the trophic interactions in a food web, and they can infer missing interactions among the organisms. The allometric diet breadth model (ADBM) is a food web model based on the foraging theory. In the ADBM, the foraging parameters are allometrically scaled to body sizes of predators and prey. In Petchey et al. (Proceedings of the National Academy of Sciences, 2008; 105: 4191), the parameterization of the ADBM had two limitations: (a) the model parameters were point estimates and (b) food web connectance was not estimated.

The novelty of our current approach is: (a) We consider multiple predictions from the ADBM by parameterizing it with approximate Bayesian computation, to estimate parameter distributions and not point estimates. (b) Connectance emerges from the parameterization, by measuring model fit using the true skill statistic, which takes into account prediction of both the presences and absences of links.

We fit the ADBM using approximate Bayesian computation to 12 observed food webs from a wide variety of ecosystems. Estimated connectance was consistently greater than previously found. In some of the food webs, considerable variation in estimated parameter distributions occurred and resulted in considerable variation (i.e., uncertainty) in predicted food web structure.

These results lend weight to the possibility that the observed food web data is missing some trophic links that do actually occur. It also seems likely that the ADBM likely predicts some links that do not exist. The latter could be addressed by accounting in the ADBM for additional traits other than body size. Further work could also address the significance of uncertainty in parameter estimates for predicted food web responses to environmental change.

The global ocean size spectrum from bacteria to whales

It has long been hypothesized that aquatic biomass is evenly distributed among logarithmic body mass size classes. Although this community structure has been observed regionally, mostly among plankton groups, its generality has never been formally tested across all marine life over the global ocean, nor have the impacts of humans on it been globally assessed. Here, we bring together data at the global scale to test the hypothesis from bacteria to whales. We find that biomass within most order of magnitude size classes is indeed remarkably constant, near 1 gigatonne (Gt) wet weight (10¹⁵ g), but bacteria and large marine mammals are markedly above and below this value, respectively. Furthermore, human impacts appear to have significantly truncated the upper one-third of the spectrum. This dramatic alteration to what is possibly life’s largest-scale regularity underscores the global extent of human activities.

Dynamic population stage structure due to juvenile-adult asymmetry stabilizes complex ecological communities

Natural ecological communities are diverse, complex, and often surprisingly stable, but the mechanisms underlying their stability remain a theoretical enigma. Interactions such as competition and predation presumably structure communities, yet theory predicts that complex communities are stable only when species growth rates are mostly limited by intraspecific self-regulation rather than by interactions with resources, competitors, and predators. Current theory, however, considers only the network topology of population-level interactions between species and ignores within-population differences, such as between juvenile and adult individuals. Here, using model simulations and analysis, I show that including commonly observed differences in vulnerability to predation and foraging efficiency between juvenile and adult individuals results in up to 10 times larger, more complex communities than observed in simulations without population stage structure. These diverse communities are stable or fluctuate with limited amplitude, although in the model only a single basal species is self-regulated, and the population-level interaction network is highly connected. Analysis of the species interaction matrix predicts the simulated communities to be unstable but for the interaction with the population-structure subsystem, which completely cancels out these instabilities through dynamic changes in population stage structure. Common differences between juveniles and adults and fluctuations in their relative abundance may hence have a decisive influence on the stability of complex natural communities and their vulnerability when environmental conditions change. To explain community persistence, it may not be sufficient to consider only the network of interactions between the constituting species.

The multiple meanings of omnivory influence empirical, modular theory and whole food web stability relationships

The persistence of whole communities hinges on the presence of select interactions which act to stabilize communities making the identification of these keystone interactions critical. One potential candidate is omnivory, yet theoretical research on omnivory thus far has been dominated by a modular theory approach whereby an omnivore and consumer compete for a shared resource. Empirical research, however, has highlighted the presence of a broader suite of omnivory modules. Here, we integrate empirical data analysis and mathematical models to explore the influence of both omnivory module (including classic, multi-resource, higher level, mutual predation and cannibalism) and omnivore-resource interaction type on food web stability. We use six classic empirical food webs to examine the prevalence of the different types of omnivory, a multi-species consumer-resource model to determine the stability of these different kinds of omnivory within a module context, and finally extend these models to a 50 species, whole food web model to examine the influence of omnivory on whole food web persistence. Our results challenge the concept that omnivory is broadly stabilizing. In particular, we demonstrate that the impact of omnivory depends on the type of omnivory being examined with multi-resource omnivory having the largest correlation with whole food web persistence. Moreover, our results highlight that we need to exercise caution when scaling modular theory to whole food web theory. Cannibalism, for example, was the most persistent and stable omnivory module in the modular theory analysis, but only demonstrated a weak correlation with whole food web persistence. Lastly, our results demonstrate that the frequency of omnivory modules are more important for whole food web persistence than the frequency of omnivore-resource interactions. Together, these results demonstrate that the role of omnivory often depends both on the type of omnivory being examined and the food web within which it is nested. In whole food web models, omnivory acts less as a keystone interaction, rather, specific types of omnivory, particularly multi-resource omnivory, act as keystone modules. Future work integrating module and whole food web theory is critical for resolving the role of key interactions in food webs.

Does evolution design robust food webs?

Theoretical works that use a dynamical approach to study the ability of ecological communities to resist perturbations are largely based on randomly generated ecosystem structures. By contrast, we ask here whether the evolutionary history of food webs matters for their robustness. Using a community evolution model, we first generate trophic networks by varying the level of energy supply (richness) of the environment in which species adapt and diversify. After placing our simulation outputs in perspective with present-day food webs empirical data, we highlight the complex, structuring role of this environmental condition during the evolutionary setting up of trophic networks. We then assess the robustness of food webs by studying their short-term ecological responses to swift changes in their customary environmental richness. We reveal that the past conditions have a crucial effect on the robustness of current food webs. Moreover, directly focusing on connectance of evolved food webs, it turns out that the most connected ones appear to be the least robust to sharp depletion in the environmental energy supply. Finally, we appraise the 'adaptation' of food webs themselves: generally poor, except in relation to a diversity of flux property.

Persistent contaminants as potential constraints on the recovery of urban river food webs from gross pollution

Urban areas contribute substantially to xenobiotic contaminant loads in rivers, but their effects have been investigated more for individual organisms and sensitive taxa, rather than through the emergent properties of communities. Here, we use replicated, catchment-scale sampling of benthic invertebrates and novel multivariate techniques to assess whether urban wastewater contaminants affected the structure and function of river food webs. We postulated that the continued occurrence of selected contaminants in river systems might explain the incomplete recovery of urban rivers from legacy gross pollution. Benthic invertebrate communities were sampled monthly over a year (2016-2017) at 18 sites across 3 river systems in South Wales (United Kingdom). Contaminant sources were characterised using remote sensing, water quality data from routine monitoring and measured concentrations of selected persistent xenobiotic pollutants (polychlorinated biphenyls and polybrominated diphenyl ethers). Urban wastewater discharges had relatively limited effects on river water quality, with small increases in nitrate, phosphate, temperature, conductivity and total dissolved solids in urban systems. Concentrations of polychlorinated biphenyls and polybrominated diphenyl ethers in invertebrates, however, were significantly higher under greater urban land cover and wastewater discharge. Food webs at the most highly contaminated urban sites were characterised by: (i) reduced taxonomic and functional diversity; (ii) simplified food web structure with reduced network connectance; and (iii) reductions in the abundance of prey important for apex predators such as the Eurasian dipper (Cinclus cinclus). Although correlative and partially confounded by other effects, these data provide support for the hypothesis that impairment to food webs resulting from urban pollutants might explain population, community and ecosystem-level effects in urban river systems, and hence incomplete recovery from past pollution.

A potential role for rare species in ecosystem dynamics

The ecological importance of common species for many ecosystem processes and functions is unquestionably due to their high abundance. Yet, the importance of rare species is much less understood. Here we take a theoretical approach, exposing dynamical models of ecological networks to small perturbations, to explore the dynamical importance of rare and common species. We find that both species types contribute to the recovery of communities following generic perturbations (i.e. perturbations affecting all species). Yet, when perturbations are selective (i.e. affects only one species), perturbations to rare species have the most pronounced effect on community stability. We show that this is due to the strong indirect effects induced by perturbations to rare species. Because indirect effects typically set in at longer timescales, our results indicate that the importance of rare species may be easily overlooked and thus underrated. Hence, our study provides a potential ecological motive for the management and protection of rare species.

Eco-evolutionary dynamics in a disturbed world: implications for the maintenance of ecological networks

Past management of exploited species and of conservation issues has often ignored the evolutionary dynamics of species. During the 70s and 80s, evolution was mostly considered a slow process that may be safely ignored for most management issues. However, in recent years, examples of fast evolution have accumulated, suggesting that time scales of evolutionary dynamics (variations in genotype frequencies) and of ecological dynamics (variations in species densities) are often largely comparable, so that complex feedbacks commonly exist between the ecological and the evolutionary context ("eco-evolutionary dynamics"). While a first approach is of course to consider the evolution of a given species, in ecological communities, species are interlinked by interaction networks. In the present article, I discuss how species (co)evolution in such a network context may alter our understanding and predictions for species coexistence, given the disturbed world we live in. I review some concepts and examples suggesting that evolution may enhance the robustness of ecological networks and then show that, in many situations, the reverse may also happen, as evolutionary dynamics can harm diversity maintenance in various ways. I particularly focus on how evolution modifies indirect effects in ecological networks, then move to coevolution and discuss how the outcome of coevolution for species coexistence depends on the type of interaction (mutualistic or antagonistic) that is considered. I also review examples of phenotypes that are known to be important for ecological networks and shown to vary rapidly given global changes. Given all these components, evolution produces indirect eco-evolutionary effects within networks that will ultimately influence the optimal management of the current biodiversity crisis.

Size-dependent functional response of Xenopus laevis feeding on mosquito larvae

Predators can play an important role in regulating prey abundance and diversity, determining food web structure and function, and contributing to important ecosystem services, including the regulation of agricultural pests and disease vectors. Thus, the ability to predict predator impact on prey is an important goal in ecology. Often, predators of the same species are assumed to be functionally equivalent, despite considerable individual variation in predator traits known to be important for shaping predator–prey interactions, like body size. This assumption may greatly oversimplify our understanding of within-species functional diversity and undermine our ability to predict predator effects on prey. Here, we examine the degree to which predator–prey interactions are functionally homogenous across a natural range of predator body sizes. Specifically, we quantify the size-dependence of the functional response of African clawed frogs (Xenopus laevis) preying on mosquito larvae (Culex pipiens). Three size classes of predators, small (15–30 mm snout-vent length), medium (50–60 mm) and large (105–120 mm), were presented with five densities of prey to determine functional response type and to estimate search efficiency and handling time parameters generated from the models. The results of mesocosm experiments showed that type of functional response of X. laevis changed with size: small predators exhibited a Type II response, while medium and large predators exhibited Type III responses. Functional response data showed an inversely proportional relationship between predator attack rate and predator size. Small and medium predators had highest and lowest handling time, respectively. The change in functional response with the size of predator suggests that predators with overlapping cohorts may have a dynamic impact on prey populations. Therefore, predicting the functional response of a single size-matched predator in an experiment may misrepresent the predator’s potential impact on a prey population.

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.

Multiscale mixing patterns in networks

Assortative mixing in networks is the tendency for nodes with the same attributes, or metadata, to link to each other. It is a property often found in social networks, manifesting as a higher tendency of links occurring between people of the same age, race, or political belief. Quantifying the level of assortativity or disassortativity (the preference of linking to nodes with different attributes) can shed light on the organization of complex networks. It is common practice to measure the level of assortativity according to the assortativity coefficient, or modularity in the case of categorical metadata. This global value is the average level of assortativity across the network and may not be a representative statistic when mixing patterns are heterogeneous. For example, a social network spanning the globe may exhibit local differences in mixing patterns as a consequence of differences in cultural norms. Here, we introduce an approach to localize this global measure so that we can describe the assortativity, across multiple scales, at the node level. Consequently, we are able to capture and qualitatively evaluate the distribution of mixing patterns in the network. We find that, for many real-world networks, the distribution of assortativity is skewed, overdispersed, and multimodal. Our method provides a clearer lens through which we can more closely examine mixing patterns in networks.

Go big or … don't? A field-based diet evaluation of freshwater piscivore and prey fish size relationships

Body size governs predator-prey interactions, which in turn structure populations, communities, and food webs. Understanding predator-prey size relationships is valuable from a theoretical perspective, in basic research, and for management applications. However, predator-prey size data are limited and costly to acquire. We quantified predator-prey total length and mass relationships for several freshwater piscivorous taxa: crappie (Pomoxis spp.), largemouth bass (Micropterus salmoides), muskellunge (Esox masquinongy), northern pike (Esox lucius), rock bass (Ambloplites rupestris), smallmouth bass (Micropterus dolomieu), and walleye (Sander vitreus). The range of prey total lengths increased with predator total length. The median and maximum ingested prey total length varied with predator taxon and length, but generally ranged from 10–20% and 32–46% of predator total length, respectively. Predators tended to consume larger fusiform prey than laterally compressed prey. With the exception of large muskellunge, predators most commonly consumed prey between 16 and 73 mm. A sensitivity analysis indicated estimates can be very accurate at sample sizes greater than 1,000 diet items and fairly accurate at sample sizes greater than 100. However, sample sizes less than 50 should be evaluated with caution. Furthermore, median log₁₀ predator-prey body mass ratios ranged from 1.9–2.5, nearly 50% lower than values previously reported for freshwater fishes. Managers, researchers, and modelers could use our findings as a tool for numerous predator-prey evaluations from stocking size optimization to individual-based bioenergetics analyses identifying prey size structure. To this end, we have developed a web-based user interface to maximize the utility of our models that can be found at www.LakeEcologyLab.org/pred_prey.

Structure and inference in annotated networks

For many networks of scientific interest we know both the connections of the network and information about the network nodes, such as the age or gender of individuals in a social network. Here we demonstrate how this 'metadata' can be used to improve our understanding of network structure. We focus in particular on the problem of community detection in networks and develop a mathematically principled approach that combines a network and its metadata to detect communities more accurately than can be done with either alone. Crucially, the method does not assume that the metadata are correlated with the communities we are trying to find. Instead, the method learns whether a correlation exists and correctly uses or ignores the metadata depending on whether they contain useful information. We demonstrate our method on synthetic networks with known structure and on real-world networks, large and small, drawn from social, biological and technological domains.

Network structure beyond food webs: mapping non-trophic and trophic interactions on Chilean rocky shores

How multiple types of non-trophic interactions map onto trophic networks in real communities remains largely unknown. We present the first effort, to our knowledge, describing a comprehensive ecological network that includes all known trophic and diverse non-trophic links among >100 coexisting species for the marine rocky intertidal community of the central Chilean coast. Our results suggest that non-trophic interactions exhibit highly nonrandom structures both alone and with respect to food web structure. The occurrence of different types of interactions, relative to all possible links, was well predicted by trophic structure and simple traits of the source and target species. In this community, competition for space and positive interactions related to habitat/refuge provisioning by sessile and/or basal species were by far the most abundant non-trophic interactions. If these patterns are orroborated in other ecosystems, they may suggest potentially important dynamic constraints on the combined architecture of trophic and non-trophic interactions. The nonrandom patterning of non-trophic interactions suggests a path forward for developing a more comprehensive ecological network theory to predict the functioning and resilience of ecological communities.

Predicting the stability of large structured food webs

The stability of ecological systems has been a long-standing focus of ecology. Recently, tools from random matrix theory have identified the main drivers of stability in ecological communities whose network structure is random. However, empirical food webs differ greatly from random graphs. For example, their degree distribution is broader, they contain few trophic cycles, and they are almost interval. Here we derive an approximation for the stability of food webs whose structure is generated by the cascade model, in which 'larger' species consume 'smaller' ones. We predict the stability of these food webs with great accuracy, and our approximation also works well for food webs whose structure is determined empirically or by the niche model. We find that intervality and broad degree distributions tend to stabilize food webs, and that average interaction strength has little influence on stability, compared with the effect of variance and correlation.

Latitudinal gradients in climatic-niche evolution accelerate trait evolution at high latitudes

Despite the importance of divergent selection to the speed of evolution, it remains poorly understood if divergent selection is more prevalent in the tropics (where species richness is highest), or at high latitudes (where paleoclimate change has been most intense). We tested whether the rate of climatic-niche evolution - one proxy for divergent selection - varies with latitude for 111 pairs of bird species. Using Brownian motion and Ornsetin-Ulhenbeck models, we show that evolutionary rates along two important axes of the climatic-niche - temperature and seasonality - have been faster at higher latitudes. We then tested whether divergence of the climatic-niche was associated with evolution in traits important in ecological differentiation (body mass) and reproductive isolation (song), and found that climatic divergence is associated with faster rates in both measures. These results highlight the importance of climate-mediated divergent selection pressures in driving evolutionary divergence and reproductive isolation at high latitudes.

FORUM: Ecological networks: the missing links in biomonitoring science

Monitoring anthropogenic impacts is essential for managing and conserving ecosystems, yet current biomonitoring approaches lack the tools required to deal with the effects of stressors on species and their interactions in complex natural systems.

Ecological networks (trophic or mutualistic) can offer new insights into ecosystem degradation, adding value to current taxonomically constrained schemes. We highlight some examples to show how new network approaches can be used to interpret ecological responses.

Synthesis and applications. Augmenting routine biomonitoring data with interaction data derived from the literature, complemented with ground‐truthed data from direct observations where feasible, allows us to begin to characterise large numbers of ecological networks across environmental gradients. This process can be accelerated by adopting emerging technologies and novel analytical approaches, enabling biomonitoring to move beyond simple pass/fail schemes and to address the many ecological responses that can only be understood from a network‐based perspective.

Augmenting routine biomonitoring data with interaction data derived from the literature, complemented with ground‐truthed data from direct observations where feasible, allows us to begin to characterise large numbers of ecological networks across environmental gradients. This process can be accelerated by adopting emerging technologies and novel analytical approaches, enabling biomonitoring to move beyond simple pass/fail schemes and to address the many ecological responses that can only be understood from a network‐based perspective.

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.

Grazing and detritivory in 20 stream food webs across a broad pH gradient

Acidity is a major driving variable in the ecology of fresh waters, and we sought to quantify macroecological patterns in stream food webs across a wide pH gradient. We postulated that a few generalist herbivore-detritivores would dominate the invertebrate assemblage at low pH, with more specialists grazers at high pH. We also expected a switch towards algae in the diet of all primary consumers as the pH increased. For 20 stream food webs across the British Isles, spanning pH 5.0–8.4 (the acid sites being at least partially culturally acidified), we characterised basal resources and primary consumers, using both gut contents analysis and stable isotopes to study resource use by the latter. We found considerable species turnover across the pH gradient, with generalist herbivore-detritivores dominating the primary consumer assemblage at low pH and maintaining grazing. These were joined or replaced at higher pH by a suite of specialist grazers, while many taxa that persisted across the pH gradient broadened the range of algae consumed as acidity declined and increased their ingestion of biofilm, whose nutritional quality was higher than that of coarse detritus. There was thus an increased overall reliance on algae at higher pH, both by generalist herbivore-detritivores and due to the presence of specialist grazers, although detritus was important even in non-acidic streams. Both the ability of acid-tolerant, herbivore-detritivores to exploit both autochthonous and allochthonous food and the low nutritional value of basal resources might render chemically recovering systems resistant to invasion by the specialist grazers and help explain the sluggish ecological recovery of fresh waters whose water chemistry has ameliorated.

Who eats whom in a pool? A comparative study of prey selectivity by predatory aquatic insects

Predatory aquatic insects are a diverse group comprising top predators in small fishless water bodies. Knowledge of their diet composition is fragmentary, which hinders the understanding of mechanisms maintaining their high local diversity and of their impacts on local food web structure and dynamics. We conducted multiple-choice predation experiments using nine common species of predatory aquatic insects, including adult and larval Coleoptera, adult Heteroptera and larval Odonata, and complemented them with literature survey of similar experiments. All predators in our experiments fed selectively on the seven prey species offered, and vulnerability to predation varied strongly between the prey. The predators most often preferred dipteran larvae; previous studies further reported preferences for cladocerans. Diet overlaps between all predator pairs and predator overlaps between all prey pairs were non-zero. Modularity analysis separated all primarily nectonic predator and prey species from two groups of large and small benthic predators and their prey. These results, together with limited evidence from the literature, suggest a highly interconnected food web with several modules, in which similarly sized predators from the same microhabitat are likely to compete strongly for resources in the field (observed Pianka’s diet overlap indices >0.85). Our experiments further imply that ontogenetic diet shifts are common in predatory aquatic insects, although we observed higher diet overlaps than previously reported. Hence, individuals may or may not shift between food web modules during ontogeny.