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

Embedding information flows within ecological networks

Natural communities form networks of species linked by interactions. Understanding the structure and dynamics of these ecological networks is pivotal to predicting species extinction risks, community stability and ecosystem functioning under global change. Traditionally, ecological network research has focused on interactions involving the flow of matter and energy, such as feeding or pollination. In nature, however, species also interact by intentionally or unintentionally exchanging information signals and cues that influence their behaviour and movement. Here we argue that this exchange of information between species constitutes an information network of nature-a crucial but largely neglected aspect of community organization. We propose to integrate information with matter flow interactions in multilayer networks. This integration reveals a novel classification of information links based on how the senders and receivers of information are embedded in food web motifs. We show that synthesizing information and matter flow interactions in multilayer networks can lead to shorter pathways connecting species and a denser aggregation of species in fewer modules. Ultimately, this tighter interconnectedness of species increases the risk of perturbation spread in natural communities, which undermines their stability. Understanding the information network of nature is thus crucial for predicting community dynamics in the era of global change.

Biological Polymers: Evolution, Function, and Significance

A holistic description of biopolymers and their evolutionary origins will contribute to our understanding of biochemistry, biology, the origins of life, and signatures of life outside our planet. While biopolymer sequences evolve through known Darwinian processes, the origins of the backbones of polypeptides, polynucleotides, and polyglycans are less certain. We frame this topic through two questions: (i) Do the characteristics of biopolymer backbones indicate evolutionary origins? (ii) Are there reasonable mechanistic models of such pre-Darwinian evolutionary processes? To address these questions, we have established criteria to distinguish chemical species produced by evolutionary mechanisms from those formed by nonevolutionary physical, chemical, or geological processes. We compile and evaluate properties shared by all biopolymer backbones rather than isolating a single type. Polypeptide, polynucleotide, and polyglycan backbones are kinetically trapped and thermodynamically unstable in aqueous media. Each biopolymer forms a variety of elaborate assemblies with diverse functions, a phenomenon we call polyfunction. Each backbone changes structure and function upon subtle chemical changes such as the reduction of ribose or a change in the linkage site or stereochemistry of polymerized glucose, a phenomenon we call function-switching. Biopolymers display homo- and heterocomplementarity, enabling atomic-level control of structure and function. Biopolymer backbones access recalcitrant states, where assembly modulates kinetics and thermodynamics of hydrolysis. Biopolymers are emergent; the properties of biological building blocks change significantly upon polymerization. In cells, biopolymers compose mutualistic networks; a cell is an Amazon Jungle of molecules. We conclude that biopolymer backbones exhibit hallmarks of evolution. Neither chemical, physical, nor geological processes can produce molecules consistent with observations. We are faced with the paradox that Darwinian evolution relies on evolved backbones but cannot alter biopolymer backbones. This Darwinian constraint is underlined by the observation that across the tree of life, ribosomes are everywhere and always have been composed of RNA and protein. Our data suggest that chemical species on the Hadean Earth underwent non-Darwinian coevolution driven in part by hydrolytic stress, ultimately leading to biopolymer backbones. We argue that highly evolved biopolymer backbones facilitated a seamless transition from chemical to Darwinian evolution. This model challenges convention, where backbones are products of direct prebiotic synthesis. In conventional models, biopolymer backbones retain vestiges of prebiotic chemistry. Our findings, however, align with models where chemical species underwent iterative and recursive sculpting, selection, and exaptation. This model supports Orgel's "gloomy" prediction that modern biochemistry has discarded vestiges of prebiotic chemistry. But there is hope. We believe an understanding of biopolymer origins will progress during the challenging and exciting integration of chemical sciences and evolutionary theory. These efforts can provide new perspectives on pre-Darwinian mechanisms and can deepen our understanding of evolution and of chemical sciences. Our working definition of chemical evolution is continuous chemical change with exploration of new chemical spaces and avoidance of equilibrium. In alignment with our model, we observe chemical evolution in complex mixtures undergoing wet-dry cycling, which does appear to undergo continuous chemical change and exploration of new chemical spaces while avoiding equilibrium.

Interaction Outcomes in Mutualism-Antagonism Continua: Context Dependency and Instantaneous Effects of the Interactions

AbstractIt is increasingly evident that most interactions are not static and move along a continuum ranging from pure mutualism (i.e., in which each species in the interaction has a net benefit in the long term) to pure antagonism (i.e., in which each species in the interaction has a net damage in the long term). Despite numerous experimental and theoretical works on this concept, predicting interaction outcomes within an ecological community continues to pose a significant challenge. This article aims to tackle this challenge by presenting a theoretical methodology for predicting the interaction outcomes within the common mutualism-antagonism modeling framework. Specifically, my main finding is to describe the influence of the population abundance of the species, the interaction effects, and the ecological context on the interaction outcomes and to quantify their relative contribution. I found that the interaction outcomes depend on the number of interacting species. In particular, when the number of interacting species increases, the trend is to skip situations where all species benefit from the interactions.

Dispersal promotes stability and persistence of exploited yeast mutualisms

Multispecies mutualistic interactions are ubiquitous and essential in nature, yet they face several threats, many of which have been exacerbated in the Anthropocene era. Understanding the factors that drive the stability and persistence of mutualism has become increasingly important in light of global change. Although dispersal is widely recognized as a crucial spatially explicit process in maintaining biodiversity and community structure, knowledge about how the dispersal of mutualists contributes to the persistence of mutualistic systems remains limited. In this study, we used a synthetic mutualism formed by genetically modified budding yeast to investigate the effect of dispersal on the persistence and stability of mutualisms under exploitation. We found that dispersal increased the persistence of exploited mutualisms by 80% compared to the isolated systems. Furthermore, our results showed that dispersal increased local diversity, decreased beta diversity among local communities, and stabilized community structure at the regional scale. Our results indicate that dispersal can allow mutualisms to persist in meta-communities by reintroducing species that are locally competitively excluded by exploiters. With limited dispersal, e.g. due to increased fragmentation of meta-communities, mutualisms might be more prone to breakdown. Taken together, our results highlight the critical role of dispersal in facilitating the persistence of mutualism.

On the structure of species-function participation in multilayer ecological networks

Understanding how biotic interactions shape ecosystems and impact their functioning, resilience and biodiversity has been a sustained research priority in ecology. Yet, traditional assessments of ecological complexity typically focus on species-species interactions that mediate a particular function (e.g., pollination), overlooking both the synergistic effect that multiple functions might develop as well as the resulting species-function participation patterns that emerge in ecosystems that harbor multiple ecological functions. Here we propose a mathematical framework that integrates various types of biotic interactions observed between different species. Its application to recently collected data of an islet ecosystem-reporting 1537 interactions between 691 plants, animals and fungi across six different functions (pollination, herbivory, seed dispersal, decomposition, nutrient uptake, and fungal pathogenicity)-unveils a non-random, nested structure in the way plant species participate across different functions. The framework further allows us to identify a ranking of species and functions, where woody shrubs and fungal decomposition emerge as keystone actors whose removal have a larger-than-random effect on secondary extinctions. The dual insight-from species and functional perspectives-offered by the framework opens the door to a richer quantification of ecosystem complexity and to better calibrate the influence of multifunctionality on ecosystem functioning and biodiversity.

Neural mechanisms of mutualistic fish cleaning behaviour: a study in the wild

One crucial interaction for the health of fish communities in coral reefs is performed by cleaner fish by removing ectoparasites from the body of other fish, so-called clients. Studying the underlying mechanisms of this behaviour is essential to understanding how species react to social stimuli and defining the drivers of mutualistic social behaviour. Here, we pinpoint the neural molecular mechanisms in the cleaning behaviour of Labroides dimidiatus in the wild through an in situ interaction experiment at a coral reef in New Caledonia. Five cleaners and clients (Abudefduf saxatilis) were placed into underwater aquaria to interact, while five were not presented with a client. The brain transcriptomes revealed 233 differentially expressed genes in cleaners that were interacting with a client. Among these genes, grin2d, npy, slc6a3 and immediate early genes (IEGs; fosb and fosl1) were related to learning and memory, glutamate and dopamine pathways, which confirm molecular pathways observed in laboratory studies. However, a new potential mechanism was found with npy (neuropeptide Y) as a driver of feeding behaviour. These results show the role of neurotransmitters and IEGs in mutualistic social behaviour, unveiling the mechanism behind the feeding stimulus that leads the cleaner fish to establish mutualistic interactions in coral reefs.

Assessing impacts of bycatch policies and fishers' heterogeneous information on food webs and fishery sustainability

Ecosystem-based fisheries management (EBFM) has emerged as a promising framework for understanding and managing the long-term interactions between fisheries and the larger marine ecosystems in which they are nested. However, successful implementation of EBFM has been elusive because we still lack a comprehensive understanding of the network of interacting species in marine ecosystems (the food web) and the dynamic relationship between the food web and the humans who harvest those ecosystems. Here, we advance such understanding by developing a network framework that integrates the complexity of food webs with the economic dynamics of different management policies. Specifically, we generate hundreds of different food web models with 20-30 species, each harvested by five different fishers extracting the biomass of a target and a bycatch species, subject to two different management scenarios and exhibiting different information in terms of avoiding bycatch when harvesting the target species. We assess the different ecological and economic consequences of these policy alternatives as species extinctions and profit from sustaining the fishery. We present the results of different policies relative to a benchmark open access scenario where there are no management policies in place. The framework of our network model would allow policymakers to evaluate different management approaches without compromising on the ecological complexities of a fishery.This article is part of the theme issue 'Connected interactions: enriching food web research by spatial and social interactions'.

Connected interactions: enriching food web research by spatial and social interactions

This theme issue features 18 papers exploring ecological interactions, encompassing metabolic, social, and spatial connections alongside traditional trophic networks. This integration enriches food web research, offering insights into ecological dynamics. By examining links across organisms, populations, and ecosystems, a hierarchical approach emerges, connecting horizontal effects within organizational levels vertically across biological organization levels. The inclusion of interactions involving humans is a key focus, highlighting the need for their integration into ecology given the complex interactions between human activities and ecological systems in the Anthropocene. The comprehensive exploration in this theme issue sheds light on the interconnectedness of ecological systems and the importance of considering diverse interactions in understanding ecosystem dynamics. This article is part of the theme issue 'Connected interactions: enriching food web research by spatial and social interactions'.

Towards mechanistic integration of the causes and consequences of biodiversity

The global biodiversity crisis has stimulated decades of research on three themes: species coexistence, biodiversity-ecosystem functioning relationships (BEF), and biodiversity-ecosystem functional stability relationships (BEFS). However, studies on these themes are largely independent, creating barriers to an integrative understanding of the causes and consequences of biodiversity. Here we review recent progress towards mechanistic integration of coexistence, BEF, and BEFS. Mechanisms underlying the three themes can be linked in various ways, potentially creating either positive or negative relationships between them. That said, we generally expect positive associations between coexistence and BEF, and between BEF and BEFS. Our synthesis represents an initial step towards integrating causes and consequences of biodiversity; future developments should include more mechanistic approaches and broader ecological contexts.

Reciprocal facilitation between ants and small mammals in tidal marshes

The role of facilitation in shaping natural communities has primarily been studied in the context of plant assemblages, while its relevance for mobile animals remains less understood. Our study investigates whether reciprocal interspecific facilitation may exist between fire ants (Solenopsis richteri) and cavies (Cavia aperea), two mobile animals, in the SW Atlantic coast brackish marshes. Field samples showed a spatial association between ant mounds and cavies, and that ants prefer to use cavy runways for movement within the marsh. Through experiments involving transplanting the dominant plant, cordgrass (Spartina densiflora), and manipulating cavy presence in areas with and without ant mounds, we observed that cavies forage extensively (and defecate more) near ant mounds. The ants actively remove cavy droppings in their mound vicinity. These ant activities and interactions with cavy droppings led to reduced moisture and organic content while increasing nitrate and phosphate levels in marsh sediment. Consequently, this enhanced plant growth, indirectly facilitating the cavies, which preferred consuming vegetation near ant mounds. These cascading indirect effects persisted over time; even four months after cavies left the marshes, transplanted plants near ant mounds remained larger and exhibited more leaf senescence when exposed to cavy herbivory. Therefore, the networks of positive interactions appear to generate simultaneous selection among species (populations), promoting coexistence within the community. Although complex, these reciprocal facilitative effects among mobile animals may be more common than currently believed and should be further studied to gain a better understanding of the underlying mechanisms driving species coexistence in natural communities.

When cheating turns into a stabilizing mechanism of plant-pollinator communities

Mutualistic interactions, such as plant-mycorrhizal or plant-pollinator interactions, are widespread in ecological communities and frequently exploited by cheaters, species that profit from interactions without providing benefits in return. Cheating usually negatively affects the fitness of the individuals that are cheated on, but the effects of cheating at the community level remains poorly understood. Here, we describe 2 different kinds of cheating in mutualistic networks and use a generalized Lotka-Volterra model to show that they have very different consequences for the persistence of the community. Conservative cheating, where a species cheats on its mutualistic partners to escape the cost of mutualistic interactions, negatively affects community persistence. In contrast, innovative cheating occurs with species with whom legitimate interactions are not possible, because of a physiological or morphological barrier. Innovative cheating can enhance community persistence under some conditions: when cheaters have few mutualistic partners, cheat at low or intermediate frequency and the cost associated with mutualism is not too high. Under these conditions, the negative effects of cheating on partner persistence are overcompensated at the community level by the positive feedback loops that arise in diverse mutualistic communities. Using an empirical dataset of plant-bird interactions (hummingbirds and flowerpiercers), we found that observed cheating patterns are highly consistent with theoretical cheating patterns found to increase community persistence. This result suggests that the cheating patterns observed in nature could contribute to promote species coexistence in mutualistic communities, instead of necessarily destabilizing them.

Towards a general modeling framework of resource competition in cognitive development

The current paper presents an integrated formal model of typical and atypical development based on the mechanisms of mutualism and resource competition. The mutualistic network model is extended with the dynamics of competition for limited resources, such as time and environmental factors. The proposed model generates patterns that resemble established phenomena in cognitive development: the positive manifold, developmental phases, developmental delays and lack of early indicators in atypical development, developmental regression, and "quasi-autism" caused by extreme environmental deprivation. The presented modeling framework fits a general movement towards formal theory construction in psychology. The model is easy to replicate and develop further, and we offer several avenues for future work.

Transformation of Biofilm to Carbon Sinks after Prolonged Droughts Linked with Algal Biodiversity Change

Global climate change significantly increased the duration of droughts in intermittent rivers, impacting benthic microbial-mediated biogeochemical processes. However, the impact of prolonged droughts on the carbon contribution of intermittent rivers remains poorly understood. In this study, we investigated the potential effects of varying drought gradients (ranging from 20 to 130 days) on benthic biofilms community structure (algae, bacteria, and fungi) and their carbon metabolism functions (ecosystem metabolism and carbon dioxide (CO2) emission fluxes) using mesocosm experiments. Our findings indicate that longer drought durations lead to reduced alpha diversity and community heterogeneity, tighter interdomain networks, and an increased role of stochastic processes in community assembly, with a discernible threshold at around 60 days. Concurrently, the biofilm transforms into a carbon sink following a drought period of 60 days, as evidenced by the transformation of CO2 emission fluxes from 633.25 ± 194.69 to -349.61 ± 277.79 mg m-2 h-1. Additionally, the partial least-squares path model revealed that the resilience of algal communities and network stability may drive biofilm's transformation into a carbon sink, primarily through the heightened resilience of autotrophic metabolism. This study underscores the significance of the carbon contribution from intermittent rivers, as the shift in carbon metabolism functions with increasing droughts could lead to skewed estimations of current riverine carbon fluxes.

Herbivore-induced pollinator limitation increases community stability of mutualism-antagonism continuum

Plants connect both pollinators and herbivores, and motivate the exploration of community structure in ecological networks merging antagonistic and mutualistic interactions. Evidence has shown that the two opposite plant-animal interactions are not independent from each other, in particular, herbivores can affect plant-pollinator pairwise interactions. Here, we explored effects of herbivore-induced pollinator limitation on community stability (including temporal stability and composition stability) of the mutualism-antagonism continuum. Our model demonstrated that pollinator limitation can boost up both temporal stability (i.e., the proportion of stable communities) and composition stability (i.e., species persistence), while the positive effects also depend on the strength of antagonistic and mutualistic interactions. Specifically, a community with higher temporal stability has a higher composition stability. Meanwhile, the correlations between network architecture and composition stability are also affected by pollinator limitation. Therefore, our results highlight that pollinator limitation can enhance community stability and may alter network architecture-composition stability relationship, and further advance the interplay between multiple types of species interactions within ecological networks.

Mutualistic interactions shape global spatial congruence and climatic niche evolution in Neotropical mimetic butterflies

Understanding the mechanisms underlying species distributions and coexistence is both a priority and a challenge for biodiversity hotspots such as the Neotropics. Here, we highlight that Müllerian mimicry, where defended prey species display similar warning signals, is key to the maintenance of biodiversity in the c. 400 species of the Neotropical butterfly tribe Ithomiini (Nymphalidae: Danainae). We show that mimicry drives large-scale spatial association among phenotypically similar species, providing new empirical evidence for the validity of Müller's model at a macroecological scale. Additionally, we show that mimetic interactions drive the evolutionary convergence of species climatic niche, thereby strengthening the co-occurrence of co-mimetic species. This study provides new insights into the importance of mutualistic interactions in shaping both niche evolution and species assemblages at large spatial scales. Critically, in the context of climate change, our results highlight the vulnerability to extinction cascades of such adaptively assembled communities tied by positive interactions.

Eukaryotes contribute more than bacteria to the recovery of freshwater ecosystem functions under different drought durations

Global climate change mostly impacts river ecosystems by affecting microbial biodiversity and ecological functions. Considering the high functional redundancy of microorganisms, the unknown relationship between biodiversity and ecosystem functions obstructs river ecological research, especially under the influence of increasing weather extremes, such as in intermittent rivers and ephemeral streams (IRES). Herein, dry-wet alternation experiments were conducted in artificial stream channels for 25 and 90 days of drought, both followed by 20 days of rewetting. The dynamic recovery of microbial biodiversity and ecosystem functions (represented by ecosystem metabolism and denitrification rate) were determined to analyse biodiversity-ecosystem-function (BEF) relationships after different drought durations. There was a significant difference between bacterial and eukaryotic biodiversity recovery after drought. Eukaryotic biodiversity was more sensitive to drought duration than bacterial, and the eukaryotic network was more stable under dry-wet alternations. Based on the establishment of partial least squares path models, we found that eukaryotic biodiversity has a stronger effect on ecosystem functions than bacteria after long-term drought. Indeed, this work represents a significant step forward for further research on the ecosystem functions of IRES, especially emphasizing the importance of eukaryotic biodiversity in the BEF relationship.

Interpreting random forest analysis of ecological models to move from prediction to explanation

As modeling tools and approaches become more advanced, ecological models are becoming more complex. Traditional sensitivity analyses can struggle to identify the nonlinearities and interactions emergent from such complexity, especially across broad swaths of parameter space. This limits understanding of the ecological mechanisms underlying model behavior. Machine learning approaches are a potential answer to this issue, given their predictive ability when applied to complex large datasets. While perceptions that machine learning is a "black box" linger, we seek to illuminate its interpretive potential in ecological modeling. To do so, we detail our process of applying random forests to complex model dynamics to produce both high predictive accuracy and elucidate the ecological mechanisms driving our predictions. Specifically, we employ an empirically rooted ontogenetically stage-structured consumer-resource simulation model. Using simulation parameters as feature inputs and simulation output as dependent variables in our random forests, we extended feature analyses into a simple graphical analysis from which we reduced model behavior to three core ecological mechanisms. These ecological mechanisms reveal the complex interactions between internal plant demography and trophic allocation driving community dynamics while preserving the predictive accuracy achieved by our random forests.

A bioenergetic framework for aboveground terrestrial food webs

Bioenergetic approaches have been greatly influential for understanding community functioning and stability and predicting effects of environmental changes on biodiversity. These approaches use allometric relationships to establish species' trophic interactions and consumption rates and have been successfully applied to aquatic ecosystems. Terrestrial ecosystems, where body mass is less predictive of plant-consumer interactions, present inherent challenges that these models have yet to meet. Here, we discuss the processes governing terrestrial plant-consumer interactions and develop a bioenergetic framework integrating those processes. Our framework integrates bioenergetics specific to terrestrial plants and their consumers within a food web approach while also considering mutualistic interactions. Such a framework is poised to advance our understanding of terrestrial food webs and to predict their responses to environmental changes.

Soil legacy effects of plants and drought on aboveground insects in native and range-expanding plant communities

Soils contain biotic and abiotic legacies of previous conditions that may influence plant community biomass and associated aboveground biodiversity. However, little is known about the relative strengths and interactions of the various belowground legacies on aboveground plant-insect interactions. We used an outdoor mesocosm experiment to investigate the belowground legacy effects of range-expanding versus native plants, extreme drought and their interactions on plants, aphids and pollinators. We show that plant biomass was influenced more strongly by the previous plant community than by the previous summer drought. Plant communities consisted of four congeneric pairs of natives and range expanders, and their responses were not unanimous. Legacy effects affected the abundance of aphids more strongly than pollinators. We conclude that legacies can be contained as soil 'memories' that influence aboveground plant community interactions in the next growing season. These soil-borne 'memories' can be altered by climate warming-induced plant range shifts and extreme drought.

Bacterial species metabolic interaction network for deciphering the lignocellulolytic system in fungal cultivating termite gut microbiota

Fungus-cultivating termite Odontotermes badius developed a mutualistic association with Termitomyces fungi for the plant material decomposition and providing a food source for the host survival. The mutualistic relationship sifted the microbiome composition of the termite gut and Termitomyces fungal comb. Symbiotic bacterial communities in the O. badius gut and fungal comb have been studied extensively to identify abundant bacteria and their lignocellulose degradation capabilities. Despite several metagenomic studies, the species-wide metabolic interaction pattern of bacterial communities in termite gut and fungal comb remains unclear. The bacterial species metabolic interaction network (BSMIN) has been constructed with 230 bacteria identified from the O. badius gut and fungal comb microbiota. The network portrayed the metabolic map of the entire microbiota and highlighted several inter-species biochemical interactions like cross-feeding, metabolic interdependency, and competition. Further, the reconstruction and analysis of the bacterial influence network (BIN) quantified the positive and negative pairwise influences in the termite gut and fungal comb microbial communities. Several key macromolecule degraders and fermentative microbial entities have been identified by analyzing the BIN. The mechanistic interplay between these influential microbial groups and the crucial glycoside hydrolases (GH) enzymes produced by the macromolecule degraders execute the community-wide functionality of lignocellulose degradation and subsequent fermentation. The metabolic interaction pattern between the nine influential microbial species has been determined by considering them growing in a synthetic microbial community. Competition (30%), parasitism (47%), and mutualism (17%) were predicted to be the major mode of metabolic interaction in this synthetic microbial community. Further, the antagonistic metabolic effect was found to be very high in the metabolic-deprived condition, which may disrupt the community functionality. Thus, metabolic interactions of the crucial bacterial species and their GH enzyme cocktail identified from the O. badius gut and fungal comb microbiota may provide essential knowledge for developing a synthetic microcosm with efficient lignocellulolytic machinery.

What Are the Best Pollinator Candidates for Camelia oleifera: Do Not Forget Hoverflies and Flies

Camellia oleifera Abel. is an important woody oil plant, and its pollination success is essential for oil production. We conducted this study to select the best pollinator candidates for C. oleifera using principal component analysis and multi-attribute decision-making. Field observations of the flower-visiting characteristics of candidate pollinators were conducted at three sites. The insect species that visited flowers did not considerably differ between regions or time periods. However, the proportion of each species recorded did vary. We recorded eleven main candidates from two orders and six families at the three sites. The pollen amount carried by Apis mellifera was significantly higher than that of other insects. However, the visit frequency and body length of Apis mellifera were smaller than those of Vespa velutina. Statistical analysis showed that A. mellifera is the best candidate pollinator; Eristaliscerealis is a good candidate pollinator; Phytomia zonata, A. cerana, and V. velutina were ordinary candidate pollinators; and four fly species, Episyrphus balteatus, and Eristalinus arvorum were classified as inefficient candidate pollinators. Our study shows that flies and hoverflies play an important role in the pollination system. Given the global decline in bee populations, the role of flies should also be considered in C. oleifera seed production.

Eco-evolutionary feedbacks among pollinators, herbivores, and their plant resources

Eco-evolutionary feedbacks among multiple species occur when one species affects another species' evolution via its effects on the abundance and traits of a shared partner species. What happens if those two species enact opposing effects on their shared partner's population growth? Furthermore, what if those two kinds of interactions involve separate traits? For example, many plants produce distinct suites of traits that attract pollinators (mutualists) and deter herbivores (antagonists). Here, we develop a model to explore how pollinators and herbivores may influence each other's interactions with a shared plant species via evolutionary effects on the plant's nectar and toxin traits. The model results predict that herbivores indirectly select for the evolution of increased nectar production by suppressing plant population growth. The model also predicts that pollinators indirectly select for the evolution of increased toxin production by plants and increased counterdefenses by herbivores via their positive effects on plant population growth. Unless toxins directly affect pollinator foraging, plants always evolve increases in attraction and defense traits when they interact with both kinds of foragers. This work highlights the value of incorporating ecological dynamics to understand the entangled evolution of mutualisms and antagonisms in natural communities.

Ecological theory of mutualism: Robust patterns of stability and thresholds in two-species population models

Mutualisms are ubiquitous in nature, provide important ecosystem services, and involve many species of interest for conservation. Theoretical progress on the population dynamics of mutualistic interactions, however, comparatively lagged behind that of trophic and competitive interactions, leading to the impression that ecologists still lack a generalized framework to investigate the population dynamics of mutualisms. Yet, over the last 90 years, abundant theoretical work has accumulated, ranging from abstract to detailed. Here, we review and synthesize historical models of two-species mutualisms. We find that population dynamics of mutualisms are qualitatively robust across derivations, including levels of detail, types of benefit, and inspiring systems. Specifically, mutualisms tend to exhibit stable coexistence at high density and destabilizing thresholds at low density. These dynamics emerge when benefits of mutualism saturate, whether due to intrinsic or extrinsic density dependence in intraspecific processes, interspecific processes, or both. We distinguish between thresholds resulting from Allee effects, low partner density, and high partner density, and their mathematical and conceptual causes. Our synthesis suggests that there exists a robust population dynamic theory of mutualism that can make general predictions.

The Evolution of Resource Provisioning in Pollination Mutualisms

AbstractResource dynamics influence the contemporary ecology of consumer-resource mutualisms. Suites of resource traits, such as floral nectar components, also evolve in response to different selective pressures, changing the ecological dynamics of the interacting species at the evolutionary equilibrium. Here we explore the evolution of resource-provisioning traits in a biotically pollinated plant that produces nectar as a resource for beneficial consumers. We develop a mathematical model describing natural selection on two quantitative nectar traits: maximum nectar production rate and maximum nectar reservoir volume. We use this model to examine how nectar production dynamics evolve under different ecological conditions that impose varying cost-benefit regimes on resource provisioning. The model results predict that natural selection favors higher nectar production when ecological factors limit the plant or pollinator's abundance (e.g., a lower productivity environment or a higher pollinator conversion efficiency). We also find that nectar traits evolve as a suite in which higher costs of producing one trait select for a compensatory increase in investment in the other trait. This empirically explicit approach to studying the evolution of consumer-resource mutualisms illustrates how natural selection acting via direct and indirect pathways of species interactions generates patterns of resource provisioning seen in natural systems.

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.

Alteration of coastal productivity and artisanal fisheries interact to affect a marine food web

Top-down and bottom-up forces determine ecosystem function and dynamics. Fisheries as a top-down force can shorten and destabilize food webs, while effects driven by climate change can alter the bottom-up forces of primary productivity. We assessed the response of a highly-resolved intertidal food web to these two global change drivers, using network analysis and bioenergetic modelling. We quantified the relative importance of artisanal fisheries as another predator species, and evaluated the independent and combined effects of fisheries and changes in plankton productivity on food web dynamics. The food web was robust to the loss of all harvested species but sensitive to the decline in plankton productivity. Interestingly, fisheries dampened the negative impacts of decreasing plankton productivity on non-harvested species by reducing the predation pressure of harvested consumers on non-harvested resources, and reducing the interspecific competition between harvested and non-harvested basal species. In contrast, the decline in plankton productivity increased the sensitivity of harvested species to fishing by reducing the total productivity of the food web. Our results show that strategies for new scenarios caused by climate change are needed to protect marine ecosystems and the wellbeing of local communities dependent on their resources.

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.

Species richness and redundancy promote persistence of exploited mutualisms in yeast

Mutualisms, or reciprocally beneficial interspecific interactions, constitute the foundation of many ecological communities and agricultural systems. Mutualisms come in different forms, from pairwise interactions to extremely diverse communities, and they are continually challenged with exploitation by nonmutualistic community members (exploiters). Thus, understanding how mutualisms persist remains an essential question in ecology. Theory suggests that high species richness and functional redundancy could promote mutualism persistence in complex mutualistic communities. Using a yeast system (Saccharomyces cerevisiae), we experimentally show that communities with the greatest mutualist richness and functional redundancy are nearly two times more likely to survive exploitation than are simple communities. Persistence increased because diverse communities were better able to mitigate the negative effects of competition with exploiters. Thus, large mutualistic networks may be inherently buffered from exploitation.