Foraging adaptation and the relationship between food-web complexity and stability

Strange invaders increase disturbance and promote generalists in an evolving food web

The patterns of diet specialization in food webs determine community structure, stability, and function. While specialists are often thought to evolve due to greater efficiency, generalists should have an advantage in systems with high levels of variability. Here we test the generalist-disturbance hypothesis using a dynamic, evolutionary food web model. Species occur along a body size axis with three traits (body size, feeding center, feeding range) that evolve independently and determine interaction strengths. Communities are assembled via ecological and evolutionary processes, where species biomass and persistence are driven by a bioenergetics model. New species are introduced either as mutants similar to parent species in the community or as invaders, with dissimilar traits. We introduced variation into communities by increasing the dissimilarity of invading species across simulations. We found that strange invaders increased the variability of communities which increased both the degree of generalism and the relative persistence of generalist species, indicating that invasion disturbance promotes the evolution of generalist species in food webs.

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.

Trade-offs Among Resilience, Robustness, Stability, and Performance and How We Might Study Them

Biological systems are likely to be constrained by trade-offs among robustness, resilience, and performance. A better understanding of these trade-offs is important for basic biology, as well as applications where biological systems can be designed for different goals. We focus on redundancy and plasticity as mechanisms governing some types of trade-offs, but mention others as well. Whether trade-offs are due to resource constraints or "design" constraints (i.e., structure of nodes and links within a network) will also affect the types of trade-offs that are important. Identifying common themes across scales of biological organization will require that researchers use similar approaches to quantifying robustness, resilience, and performance, using units that can be compared across systems.

Predator avoidance and foraging for food shape synchrony and response to perturbations in trophic metacommunities

The response of species to perturbations strongly depends on spatial aspects in populations connected by dispersal. Asynchronous fluctuations in biomass among populations lower the risk of simultaneous local extinctions and thus reduce the regional extinction risk. However, dispersal is often seen as passive diffusion that balances species abundance between distant patches, whereas ecological constraints, such as predator avoidance or foraging for food, trigger the movement of individuals. Here, we propose a model in which dispersal rates depend on the abundance of the species interacting with the dispersing species (e.g., prey or predators) to determine how density-dependent dispersal shapes spatial synchrony in trophic metacommunities in response to stochastic perturbations. Thus, unlike those with passive dispersal, this model with density-dependent dispersal bypasses the classic vertical transmission of perturbations due to trophic interactions and deeply alters synchrony patterns. We show that the species with the highest coefficient of variation of biomass governs the dispersal rate of the dispersing species and determines the synchrony of its populations. In addition, we show that this mechanism can be modulated by the relative impact of each species on the growth rate of the dispersing species. Species affected by several constraints disperse to mitigate the strongest constraints (e.g., predation), which does not necessarily experience the highest variations due to perturbations. Our approach can disentangle the joint effects of several factors implied in dispersal and provides a more accurate description of dispersal and its consequences on metacommunity dynamics.

Avoiding artifacts when varying the number of species in ecological models

Ecological theory recognizes the importance of the variety of species for maintaining the functioning of ecosystems and their derived services. We assert that when studying the effects of shifts in biodiversity levels using mathematical models, their dynamics must be sensitive to the variety of species traits but not to raw species numbers, a property that we call order-invariance. We present a testing procedure for verifying order-invariance of ecological network models -with or without trait adaptation- expressed as ODEs. Furthermore, we applied our test to several influential models used for evaluating biodiversity effects on ecosystem functioning. In most of the surveyed studies the equations failed our test. This raises doubts about the validity of previous results and calls for revisiting the theory derived from these studies. Our results foster the creation of artifact-free models, a necessary step towards building a more robust theory of biodiversity-driven ecosystem functioning.

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.

Heatwave-induced synchrony within forage fish portfolio disrupts energy flow to top pelagic predators

During the Pacific marine heatwave of 2014-2016, abundance and quality of several key forage fish species in the Gulf of Alaska were simultaneously reduced throughout the system. Capelin (Mallotus catervarius), sand lance (Ammodytes personatus), and herring (Clupea pallasii) populations were at historically low levels, and within this community abrupt declines in portfolio effects identify trophic instability at the onset of the heatwave. Although compensatory changes in age structure, size, growth or energy content of forage fish were observed to varying degrees among all these forage fish, none were able to fully mitigate adverse impacts of the heatwave, which likely included both top-down and bottom-up forcing. Notably, changes to the demographic structure of forage fish suggested size-selective removals typical of top-down regulation. At the same time, changes in zooplankton communities may have driven bottom-up regulation as copepod community structure shifted toward smaller, warm water species, and euphausiid biomass was reduced owing to the loss of cold-water species. Mediated by these impacts on the forage fish community, an unprecedented disruption of the normal pelagic food web was signaled by higher trophic level disruptions during 2015-2016, when seabirds, marine mammals, and groundfish experienced shifts in distribution, mass mortalities, and reproductive failures. Unlike decadal-scale variability underlying ecosystem regime shifts, the heatwave appeared to temporarily overwhelm the ability of the forage fish community to buffer against changes imposed by warm water anomalies, thereby eliminating any ecological advantages that may have accrued from having a suite of coexisting forage species with differing life-history compensations.

Evaluating the impacts of El Niño events on a marine bay ecosystem based on selected ecological network indicators

El Niño events have great impacts on marine ecosystems worldwide, ranging from low trophic plankton production to fishery resources. Understanding how ecosystems respond to El Niño is the key to the success of ecosystem-based fisheries management (EBFM). However, few studies have focussed on the ecosystems respond to this natural perturbation in China seas, and the selection of effective ecological network analyses (ENA) indicators to evaluate the ecosystem response under El Niño conditions needs to be assessed. In this study, we constructed Ecopath models for Haizhou Bay in ENSO-neutral (2013) and El Niño (2015) years. Comprehensive analyses were conducted to evaluate ENA indicators in terms of sensitivity to the ecosystem variations, robustness to the model parameters uncertainties, and statistical check. Results showed that there were obvious variations in the species composition and biomass in the Haizhou Bay ecosystem under the El Niño event. Four optimal ENA indicators were selected, including total system throughput, total primary production, total system non-cycled throughflow, and ascendency. The indicators further showed a shrunken ecosystem size, increased energetic efficiency, and less organised ecosystem under the El Niño event. These findings enhance our understanding of ecosystem dynamics and underscore the need for precautionary management under El Niño conditions. Moreover, this work can be helpful in guiding the further selection of ENA indicators for evaluating and managing marine ecosystems during El Niño events elsewhere and thusly contribute to the implementation of EBFM.

Rapid evolution promotes fluctuation-dependent species coexistence

Recent studies have demonstrated that rapid contemporary evolution can play a significant role in regulating population dynamics on ecological timescales. Here we identify a previously unrecognised mode by which rapid evolution can promote species coexistence via temporal fluctuations and a trade-off between competitive ability and the speed of adaptive evolution. We show that this interaction between rapid evolution and temporal fluctuations not only increases the range of coexistence conditions under a gleaner-opportunist trade-off (i.e. low minimum resource requirement [R^* ] vs. high maximum growth rate) but also yields stable coexistence in the absence of a classical gleaner-opportunist trade-off. Given the propensity for both oscillatory dynamics and different rates of adaptation between species (including rapid evolution and phenotypic plasticity) in the real world, we argue that this expansion of fluctuation-dependent coexistence theory provides an important overlooked solution to the so-called 'paradox of the plankton'.

Niche Theory for Mutualism: A Graphical Approach to Plant-Pollinator Network Dynamics

AbstractContemporary niche theory is a useful framework for understanding how organisms interact with each other and with their shared environment. Its graphical representation, popularized by Tilman's resource ratio hypothesis, facilitates analysis of the equilibrium structure of complex dynamical models, including species coexistence. This theory has been applied primarily to resource competition since its early beginnings. Here, we integrate mutualism into niche theory by expanding Tilman's graphical representation to the analysis of consumer-resource dynamics of plant-pollinator networks. We graphically explain the qualitative phenomena previously found by numerical simulations, including the effects on community dynamics of nestedness, adaptive foraging, and pollinator invasions. Our graphical approach promotes the unification of niche and network theories and deepens the synthesis of different types of interactions within a consumer-resource framework.

Diversity of biological rhythm and food web stability

How ecosystem biodiversity is maintained remains a persistent question in the field of ecology. Here, I present a new coexistence theory, i.e. diversity of biological rhythm. Circadian, circalunar and circannual rhythms, which control short- and long-term activities, are identified as universal phenomena in organisms. Analysis of a theoretical food web with diel, monthly and annual cycles in foraging activity for each organism shows that diverse biological cycles play key roles in maintaining complex communities. Each biological rhythm does not have a strong stabilizing effect independently but enhances community persistence when combined with other rhythms. Biological rhythms also mitigate inherent destabilization tendencies caused by food web complexity. Temporal weak interactions due to hybridity of multiple activity cycles play a key role toward coexistence. Polyrhythmic changes in biological activities in response to the Earth's rotation may be a key factor in maintaining biological communities.

Stability of generalized ecological-network models

The stability of ecological networks of varying topologies and predator-prey relationships is explored by applying the concept of generalized modeling. The effects of omnivory, complexity, enrichment, number of top predators, and predatory response are discussed. The degree of omnivory plays a large role in governing web stability at steady state. Complexity as measured from connectance and network size is not a perfect indicator of stability; large, highly connected webs can be just as stable as smaller, less connected ones. Learning behavior as expressed in Holling's type III predatory response is stabilizing for food webs and provides exceptions to the paradox of enrichment for some topologies.

Intraspecific variation and energy channel coupling within a Chilean kelp forest

The widespread importance of variable types of primary production, or energy channels, to consumer communities has become increasingly apparent. However, the mechanisms underlying this "multichannel" feeding remain poorly understood, especially for aquatic ecosystems that pose unique logistical constraints given the diversity of potential energy channels. Here, we use bulk tissue isotopic analysis along with carbon isotope (δ13 C) analysis of individual amino acids to characterize the relative contribution of pelagic and benthic energy sources to a kelp forest consumer community in northern Chile. We measured bulk tissue δ13 C and δ15 N for >120 samples; of these we analyzed δ13 C values of six essential amino acids (EAA) from nine primary producer groups (n = 41) and 11 representative nearshore consumer taxa (n = 56). Using EAA δ13 C data, we employed linear discriminant analysis (LDA) to assess how distinct EAA δ13 C values were between local pelagic (phytoplankton/particulate organic matter), and benthic (kelps, red algae, and green algae) endmembers. With this model, we were able to correctly classify nearly 90% of producer samples to their original groupings, a significant improvement on traditional bulk isotopic analysis. With this EAA isotopic library, we then generated probability distributions for the most important sources of production for each individual consumer and species using a bootstrap-resampling LDA approach. We found evidence for multichannel feeding within the community at the species level. Invertebrates tended to focus on either pelagic or benthic energy, deriving 13-67% of their EAA from pelagic sources. In contrast, mobile (fish) taxa at higher trophic levels used more equal proportions of each channel, ranging from 19% to 47% pelagically derived energy. Within a taxon, multichannel feeding was a result of specialization among individuals in energy channel usage, with 37 of 56 individual consumers estimated to derive >80% of their EAA from a single channel. Our study reveals how a cutting-edge isotopic technique can characterize the dynamics of energy flow in coastal food webs, a topic that has historically been difficult to address. More broadly, our work provides a mechanism as to how multichannel feeding may occur in nearshore communities, and we suggest this pattern be investigated in additional ecosystems.

Stability of ecosystems enhanced by species-interaction constraints

Ecosystem stability is a central question both in theoretical and applied biology. Dynamical systems theory can be used to analyze how growth rates, carrying capacities, and patterns of species interactions affect the stability of an ecosystem. The response to increasing complexity has been extensively studied and the general conclusion is that there is a limit. While there is a complexity limit to stability at which global destabilisation occurs, the collapse rarely happens suddenly if a system is fully viable (no species is extinct). In fact, when complexity is successively increased, we find that the generic response is to go through multiple single-species extinctions before a global collapse. In this paper we demonstrate this finding via both numerical simulations and elaborations of theoretical predictions. We explore more biological interaction patterns, and, perhaps most importantly, we show that constrained interaction structures-a constant row sum in the interaction matrix-prevent extinctions from occurring. This makes an ecosystem more robust in terms of allowed complexity, but it also means singles-species extinctions do not precede or signal collapse-a drastically different behavior compared to the generic and commonly assumed case. We further argue that this constrained interaction structure-limiting the total interactions for each species-is biologically plausible.

The Structure of Ecological Networks Across Levels of Organization

Interactions connect the units of ecological systems, forming networks. Individual-based networks characterize variation in niches among individuals within populations. These individual-based networks merge with each other, forming species-based networks and food webs that describe the architecture of ecological communities. Networks at broader spatiotemporal scales portray the structure of ecological interactions across landscapes and over macroevolutionary time. Here, I review the patterns observed in ecological networks across multiple levels of biological organization. A fundamental challenge is to understand the amount of interdependence as we move from individual-based networks to species-based networks and beyond. Despite the uneven distribution of studies, regularities in network structure emerge across scales due to the fundamental architectural patterns shared by complex networks and the interplay between traits and numerical effects. I illustrate the integration of these organizational scales by exploring the consequences of the emergence of highly connected species for network structures across scales.

Intraspecific Adaptation Load: A Mechanism for Species Coexistence

Evolutionary ecological theory suggests that selection arising from interactions with conspecifics, such as sexual and kin selection, may result in evolution of intraspecific conflicts and evolutionary 'tragedy of the commons'. Here, we propose that such an evolution of conspecific conflicts may affect population dynamics in a way that enhances species coexistence. Empirical evidence and theoretical models suggest that more abundant species is more susceptible to invasion of 'selfish' individuals that increase their own reproductive success at the expense of population growth (intraspecific adaptation load). The density-dependent intraspecific adaptation load gives rise to a self-regulation mechanism at the population level, and stabilizes species coexistence at the community level by negative frequency-dependence.

The emergence of new trophic levels in eco-evolutionary models with naturally-bounded traits

Ecosystems and food webs are structured into trophic levels of who eats whom. Species that occupy higher trophic levels have less available energy and higher energetic costs than species at lower trophic levels. So why do higher trophic levels exist? What processes generate new trophic levels? We consider a heuristic eco-evolutionary model based on simple Lotka-Volterra equations, where the evolution of traits is described by a generalisation of Lande's equation. The transition from competition to predation in this simplest of models is a successful, safe strategy for a population, and suggests a propensity to develop new trophic levels may be an inherent property of ecosystems. Numerical simulations with a more complex eco-evolutionary model of interacting plant and herbivore populations display the emergence of a new trophic level as an alternative to continued competition. These simulations reveal that new trophic levels may arise naturally from ecosystems because a robust strategy for a population in the presence of a strong competitor that could dominate or potentially extinguish them, is to predate upon the competitor. The same properties that make the competitor strong make it an ideal prey, suggesting the rubric that it is better to eat a strong competitor than to continue competing.

Co-adaptation enhances the resilience of mutualistic networks

Mutualistic networks, which describe the ecological interactions between multiple types of species such as plants and pollinators, play a paramount role in the generation of Earth's biodiversity. The resilience of a mutualistic network denotes its ability to retain basic functionality when errors and failures threaten the persistence of the community. Under the disturbances of mass extinctions and human-induced disasters, it is crucial to understand how mutualistic networks respond to changes, which enables the system to increase resilience and tolerate further damages. Despite recent advances in the modelling of the structure-based adaptation, we lack mathematical and computational models to describe and capture the co-adaptation between the structure and dynamics of mutualistic networks. In this paper, we incorporate dynamic features into the adaptation of structure and propose a co-adaptation model that drastically enhances the resilience of non-adaptive and structure-based adaptation models. Surprisingly, the reason for the enhancement is that the co-adaptation mechanism simultaneously increases the heterogeneity of the mutualistic network significantly without changing its connectance. Owing to the broad applications of mutualistic networks, our findings offer new ways to design mechanisms that enhance the resilience of many other systems, such as smart infrastructures and social-economical systems.

Adaptive social networks promote the wisdom of crowds

Social networks continuously change as new ties are created and existing ones fade. It is widely acknowledged that our social embedding has a substantial impact on what information we receive and how we form beliefs and make decisions. However, most empirical studies on the role of social networks in collective intelligence have overlooked the dynamic nature of social networks and its role in fostering adaptive collective intelligence. Therefore, little is known about how groups of individuals dynamically modify their local connections and, accordingly, the topology of the network of interactions to respond to changing environmental conditions. In this paper, we address this question through a series of behavioral experiments and supporting simulations. Our results reveal that, in the presence of plasticity and feedback, social networks can adapt to biased and changing information environments and produce collective estimates that are more accurate than their best-performing member. To explain these results, we explore two mechanisms: 1) a global-adaptation mechanism where the structural connectivity of the network itself changes such that it amplifies the estimates of high-performing members within the group (i.e., the network "edges" encode the computation); and 2) a local-adaptation mechanism where accurate individuals are more resistant to social influence (i.e., adjustments to the attributes of the "node" in the network); therefore, their initial belief is disproportionately weighted in the collective estimate. Our findings substantiate the role of social-network plasticity and feedback as key adaptive mechanisms for refining individual and collective judgments.

Predicting collapse of complex ecological systems: quantifying the stability-complexity continuum

Dynamical shifts between the extremes of stability and collapse are hallmarks of ecological systems. These shifts are limited by and change with biodiversity, complexity, and the topology and hierarchy of interactions. Most ecological research has focused on identifying conditions for a system to shift from stability to any degree of instability-species abundances do not return to exact same values after perturbation. Real ecosystems likely have a continuum of shifting between stability and collapse that depends on the specifics of how the interactions are structured, as well as the type and degree of disturbance due to environmental change. Here we map boundaries for the extremes of strict stability and collapse. In between these boundaries, we find an intermediate regime that consists of single-species extinctions, which we call the extinction continuum. We also develop a metric that locates the position of the system within the extinction continuum-thus quantifying proximity to stability or collapse-in terms of ecologically measurable quantities such as growth rates and interaction strengths. Furthermore, we provide analytical and numerical techniques for estimating our new metric. We show that our metric does an excellent job of capturing the system's behaviour in comparison with other existing methods-such as May's stability criteria or critical slowdown. Our metric should thus enable deeper insights about how to classify real systems in terms of their overall dynamics and their limits of stability and collapse.

Diversity and coexistence are influenced by time-dependent species interactions in a predator-prey system

Although numerous studies show that communities are jointly influenced by predation and competitive interactions, few have resolved how temporal variability in these interactions influences community assembly and stability. Here, we addressed this challenge in experimental microbial microcosms by employing empirical dynamic modelling tools to: (1) detect causal interactions between prey species in the absence and presence of a predator; (2) quantify the time-varying strength of these interactions and (3) explore stability in the resulting communities. Our findings show that predators boost the number of causal interactions among community members, and lead to reduced dynamic stability, but higher coexistence among prey species. These results correspond to time-varying changes in species interactions, including emergence of morphological characteristics that appeared to reduce predation, and indirectly facilitate growth of predator-susceptible species. Jointly, our findings suggest that careful consideration of both context and time may be necessary to predict and explain outcomes in multi-trophic systems.

Integrating the underlying structure of stochasticity into community ecology

Stochasticity is a core component of ecology, as it underlies key processes that structure and create variability in nature. Despite its fundamental importance in ecological systems, the concept is often treated as synonymous with unpredictability in community ecology, and studies tend to focus on single forms of stochasticity rather than taking a more holistic view. This has led to multiple narratives for how stochasticity mediates community dynamics. Here, we present a framework that describes how different forms of stochasticity (notably demographic and environmental stochasticity) combine to provide underlying and predictable structure in diverse communities. This framework builds on the deep ecological understanding of stochastic processes acting at individual and population levels and in modules of a few interacting species. We support our framework with a mathematical model that we use to synthesize key literature, demonstrating that stochasticity is more than simple uncertainty. Rather, stochasticity has profound and predictable effects on community dynamics that are critical for understanding how diversity is maintained. We propose next steps that ecologists might use to explore the role of stochasticity for structuring communities in theoretical and empirical systems, and thereby enhance our understanding of community dynamics.

Natural selection contributes to food web stability

How biodiversity is maintained in ecosystems is a central issue in ecology. According to the evolutionary theory, heritable variations between individuals are important for the generation of species diversity, linking both intra and interspecific variations. The present food web model shows that intraspecific variations via natural selection also play crucial roles in maintaining the stability of large communities with diverse species. In particular, our computations indicate that larger communities need more intraspecific variation to be maintained and are powerfully stabilized when multiple traits are variable. Consequently, these variations are likely to be maintained in larger communities. Hence, intra and interspecific diversities may support each other during evolution.

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.

Structural trade-offs can predict rewiring in shrinking social networks

There is growing evidence that organisms can respond to declining population sizes by adapting their interactions with others. Regulating connections with others could underpin resilience of biological networks spanning from social groups to ecological communities. However, our ability to predict the dynamics of shrinking social networks remains limited. Network regulation involves several trade-offs. Removing nodes (and therefore their connections) from networks reduces the number of connections among remaining nodes. Responding by forming new connections then impacts other network properties. A simple way to minimize the impact of up-regulating network connections is to form new connections or to strengthen connections, between nodes that share a lost connection with a recently removed node. I propose a simple 'second-degree rewiring' rule as a biologically plausible regulatory mechanism in shrinking social networks. I argue that two individuals that have lost a connection with a common removed individual will both be more likely, or more willing, to form a new, or strengthen an existing, connection among themselves. I then show that such second-degree rewiring has less impact on important structural properties of the network than forming random new connections. For example, in a network with phenotypic assortment, second-degree nodes are more likely to be similar than any random pair of nodes, and connecting these will better maintain assortativity. This simple rule can therefore maintain network properties without individuals having any knowledge of the global structure of the network or the relative properties of the nodes within it. In this paper, I outline an algorithm for second-degree rewiring. I demonstrate how second-degree rewiring can have less impact than adding new, or increasing the strength of, random connections on both the individual and whole network properties. That is, relative to randomly adding or strengthening connections, second-degree rewiring has less impact on mean degree, assortativity, clustering and network density. I then demonstrate empirically, using social networks of great tits (Parus major), that individuals that previously shared connections to a removed conspecific were more likely to form a new connection or to strengthen their connection, relative to other individuals in the same population. This study highlights how developing a better mechanistic understanding of the structural properties of networks, and the consequences of adding new connections, can provide useful insights into how organisms are likely to regulate their interactions in shrinking populations.

Plant coexistence mediated by adaptive foraging preferences of exploiters or mutualists

Coexistence of plants depends on their competition for common resources and indirect interactions mediated by shared exploiters or mutualists. These interactions are driven either by changes in animal abundance (density-mediated interactions, e.g., apparent competition), or by changes in animal preferences for plants (behaviorally-mediated interactions). This article studies effects of behaviorally-mediated interactions on two plant population dynamics and animal preference dynamics when animal densities are fixed. Animals can be either adaptive exploiters or adaptive mutualists (e.g., herbivores or pollinators) that maximize their fitness. Analysis of the model shows that adaptive animal preferences for plants can lead to multiple outcomes of plant coexistence with different levels of specialization or generalism for the mediator animal species. In particular, exploiter generalism promotes plant coexistence even when inter-specific competition is too strong to make plant coexistence possible without exploiters, and mutualist specialization promotes plant coexistence at alternative stable states when plant inter-specific competition is weak. Introducing a new concept of generalized isoclines allows us to fully analyze the model with respect to the strength of competitive interactions between plants (weak or strong), and the type of interaction between plants and animals (exploitation or mutualism).

Communities at the extreme: Aquatic food webs in desert landscapes

Studying food webs across contrasting abiotic conditions is an important tool in understanding how environmental variability impacts community structure and ecosystem dynamics. The study of extreme environments provides insight into community-wide level responses to environmental pressures with relevance to the future management of aquatic ecosystems. In the western Lake Eyre Basin of arid Australia, there are two characteristic and contrasting aquatic habitats: springs and rivers. Permanent isolated Great Artesian Basin springs represent hydrologically persistent environments in an arid desert landscape. In contrast, hydrologically variable river waterholes are ephemeral in space and time. We comprehensively sampled aquatic assemblages in contrasting ecosystem types to assess patterns in community composition and to quantify food web attributes with stable isotopes. Springs and rivers were found to have markedly different invertebrate communities, with rivers dominated by more dispersive species and springs associated with species that show high local endemism. Qualitative assessment of basal resources shows autochthonous carbon appears to be a key basal resource in both types of habitat, although the particular sources differed between habitats. Food-web variables such as trophic length, trophic breadth, and community isotopic niche size were relatively similar in the two habitat types. The basis for the similarity in food-web structure despite differences in community composition appears to be broader isotopic niches for predatory invertebrates and fish in springs as compared with rivers. In contrast to published theory, our findings suggest that the food webs of the hydrologically variable river sites may show less dietary generalization and more compact food-web modules than in springs.

Adaptive migration promotes food web persistence

Interactions between diverse species that coexist in nature are of utmost interest in the field of ecology. Recent theoretical studies have shown that spatiality plays a key role in maintaining complex systems with multiple differing species. In these models, however, organisms move among habitats randomly, implying that some organisms migrate from areas of higher fitness to areas of lower fitness in a maladaptive way. Herein, a meta-community model of a food web shows that adaptive movements by organisms can play key roles in maintaining large ecological communities. Without adaptive dispersal, species are not likely to persist across habitats, particularly when systems have few habitats where local food webs are strongly coupled by high migration rates. However, adaptive dispersers can improve such low persistence greatly. By abandoning unfavourable habitats for favourable habitats, dispersers prevent regional extinction at the price of local extinction and increase their total numbers further. Hence, the inherent stabilising effect of spatiality may be larger than that expected from theoretical random movement models.

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.

Trophic Patterns of Bighead Carp and Silver Carp Follow the Seasonality of Resource Availability

The influence of seasonality of the aquatic environment on food web has been notoriously understudied in empirical ecology. In this study, we focus on seasonal changes in one key attribute of a food web, the trophic level. We determine whether seasonal variations of fish trophic levels could be indicated by the change in food resources. Silver carp (Hypophthalmichthys molitrix) and bighead carp (H. nobilis) were used to explore the responses of trophic levels of the filter-feeding fish to seasonal variations of food resources. Combined stable isotopic analysis and dietary analysis revealed that filter-feeding fish tended to have a higher trophic level in spring (May) and autumn (September and October). This may result from the abundant density of food resources (zooplankton and phytoplankton) and fish flexible foraging strategy, as we predicted that the trophic level follows the seasonality of food availability. Pearson’ correlation analysis and a structural equation model showed that seasonal variation of total phosphorus and water temperature could indirectly affect trophic levels of silver carp and bighead carp by mediating the abundance of phytoplankton and zooplankton directly and indirectly along the food chain. According to these findings, the seasonal variation of food resources could be an important indicator of the temporal dynamics of the food web trophic pattern in freshwater ecosystems.

Interaction modifications lead to greater robustness than pairwise non-trophic effects in food webs

Considerable emphasis has been placed recently on the importance of incorporating non-trophic effects into our understanding of ecological networks. Interaction modifications are well-established as generating strong non-trophic impacts by modulating the strength of interspecific interactions. For simplicity and comparison with direct interactions within a network context, the consequences of interaction modifications have often been described as direct pairwise interactions. The consequences of this assumption have not been examined in non-equilibrium settings where unexpected consequences of interaction modifications are most likely. To test the distinct dynamic nature of these "higher-order" effects, we directly compare, using dynamic simulations, the robustness to extinctions under perturbation of systems where interaction modifications are either explicitly modelled or represented by corresponding equivalent pairwise non-trophic interactions. Full, multi-species representations of interaction modifications resulted in a greater robustness to extinctions compared to equivalent pairwise effects. Explanations for this increased stability despite apparent greater dynamic complexity can be found in additional routes for dynamic feedbacks. Furthermore, interaction modifications changed the relative vulnerability of species to extinction from those trophically connected close to the perturbed species towards those receiving a large number of modifications. Future empirical and theoretical research into non-trophic effects should distinguish interaction modifications from direct pairwise effects in order to maximize information about the system dynamics. Interaction modifications have the potential to shift expectations of species vulnerability based exclusively on trophic networks.

Experimental loss of generalist plants reveals alterations in plant-pollinator interactions and a constrained flexibility of foraging

Species extinctions undermine ecosystem functioning, with the loss of a small subset of functionally important species having a disproportionate impact. However, little is known about the effects of species loss on plant-pollinator interactions. We addressed this issue in a field experiment by removing the plant species with the highest visitation frequency, then measuring the impact of plant removal on flower visitation, pollinator effectiveness and insect foraging in several sites. Our results show that total visitation decreased exponentially after removing 1-4 most visited plants, suggesting that these plants could benefit co-occurring ones by maintaining high flower visitor abundances. Although we found large variation among plant species, the redistribution of the pollinator guild affected mostly the other plants with high visitor richness. Also, the plant traits mediated the effect of removal on flower visitation; while visitation of plants which had smaller inflorescences and more sugar per flower increased after removal, flower visitors did not switch between flower shapes and visitation decreased mostly in plants visited by many morpho-species of flower visitors. Together, these results suggest that the potential adaptive foraging was constrained by flower traits. Moreover, pollinator effectiveness fluctuated but was not directly linked to changes of flower visitation. In conclusion, it seems that the loss of generalist plants alters plant-pollinator interactions by decreasing pollinator abundance with implications for pollination and insect foraging. Therefore, generalist plants have high conservation value because they sustain the complex pattern of plant-pollinator interactions.

Mutualistic interactions reshuffle the effects of climate change on plants across the tree of life

Climatically induced local species extinctions may trigger coextinction cascades, thus driving many more species to extinction than originally predicted by species distribution models. Using seven pollination networks across Europe that include the phylogeny and life history traits of plants, we show a substantial variability across networks in climatically predicted plant extinction-and particularly the subsequent coextinction-rates, with much higher values in Mediterranean than Eurosiberian networks. While geographic location best predicts the probability of a plant species to be driven to extinction by climate change, subsequent coextinctions are best predicted by the local network of interactions. These coextinctions not only increase the total number of plant species being driven to extinction but also add a bias in the way the major taxonomic and functional groups are pruned.