Trophic tug-of-war: Coexistence mechanisms within and across trophic levels.

Ecological communities encompass rich diversity across multiple trophic levels. While modern coexistence theory has been widely applied to understand community assembly, its traditional formalism only allows assembly within a single trophic level. Here, using an expanded definition of niche and fitness differences applicable to multitrophic communities, we study how diversity within and across trophic levels affects species coexistence. If each trophic level is analysed separately, both lower- and higher trophic levels are governed by the same coexistence mechanisms. In contrast, if the multitrophic community is analysed as a whole, different trophic levels are governed by different coexistence mechanisms: coexistence at lower trophic levels is predominantly limited by fitness differences, whereas coexistence at higher trophic levels is predominantly limited by niche differences. This dichotomy in coexistence mechanisms is supported by theoretical derivations, simulations of phenomenological and trait-based models, and a case study of a primeval forest ecosystem. Our work provides a general and testable prediction of coexistence mechanism operating in multitrophic communities.

Higher-order species interactions cause time-dependent niche and fitness differences: Experimental evidence in plant-feeding arthropods.

Species interact in different ways, including competition, facilitation and predation. These interactions can be non-linear or higher order and may depend on time or species densities. Although these higher-order interactions are virtually ubiquitous, they remain poorly understood, as they are challenging both theoretically and empirically. We propose to adapt niche and fitness differences from modern coexistence theory and apply them to species interactions over time. As such, they may not merely inform about coexistence, but provide a deeper understanding of how species interactions change. Here, we investigated how the exploitation of a biotic resource (plant) by phytophagous arthropods affects their interactions. We performed monoculture and competition experiments to fit a generalized additive mixed model to the empirical data, which allowed us to calculate niche and fitness differences. We found that species switch between different types of interactions over time, including intra- and interspecific facilitation, and strong and weak competition.

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.

Building modern coexistence theory from the ground up: The role of community assembly.

Modern coexistence theory (MCT) is one of the leading methods to understand species coexistence. It uses invasion growth rates-the average, per-capita growth rate of a rare species-to identify when and why species coexist. Despite significant advances in dissecting coexistence mechanisms when coexistence occurs, MCT relies on a 'mutual invasibility' condition designed for two-species communities but poorly defined for species-rich communities. Here, we review well-known issues with this component of MCT and propose a solution based on recent mathematical advances. We propose a clear framework for expanding MCT to species-rich communities and for understanding invasion resistance as well as coexistence, especially for communities that could not be analysed with MCT so far. Using two data-driven community models from the literature, we illustrate the utility of our framework and highlight the opportunities for bridging the fields of community assembly and species coexistence.

Mechanistic Models of Trophic Interactions: Opportunities for Species Richness and Challenges for Modern Coexistence Theory.

AbstractMany potential mechanisms promote species coexistence, but we know little about their relative importance. To compare multiple mechanisms, we modeled a two-trophic planktonic food web based on mechanistic species interactions and empirically measured species traits. We simulated thousands of possible communities under realistic and altered interaction strengths to assess the relative importance of three potential drivers of phytoplankton and zooplankton species richness: resource-mediated coexistence mechanisms, predator-prey interactions, and trait trade-offs. Next, we computed niche and fitness differences of competing zooplankton to obtain a deeper understanding of how these mechanisms determine species richness. We found that predator-prey interactions were the most important driver of phytoplankton and zooplankton species richness and that large zooplankton fitness differences were associated with low species richness, but zooplankton niche differences were not associated with species richness. However, for many communities we could not apply modern coexistence theory to compute niche and fitness differences of zooplankton because of conceptual issues with the invasion growth rates arising from trophic interactions. We therefore need to expand modern coexistence theory to fully investigate multitrophic-level communities.

Chemical Mixtures and Multiple Stressors: Same but Different?

Ecosystems are strongly influenced by multiple anthropogenic stressors, including a wide range of chemicals and their mixtures. Studies on the effects of multiple stressors have largely focussed on nonchemical stressors, whereas studies on chemical mixtures have largely ignored other stressors. However, both research areas face similar challenges and require similar tools and methods to predict the joint effects of chemicals or nonchemical stressors, and frameworks to integrate multiple chemical and nonchemical stressors are missing. We provide an overview of the research paradigms, tools, and methods commonly used in multiple stressor and chemical mixture research and discuss potential domains of cross-fertilization and joint challenges. First, we compare the general paradigms of ecotoxicology and (applied) ecology to explain the historical divide. Subsequently, we compare methods and approaches for the identification of interactions, stressor characterization, and designing experiments. We suggest that both multiple stressor and chemical mixture research are too focused on interactions and would benefit from integration regarding null model selection. Stressor characterization is typically more costly for chemical mixtures. While for chemical mixtures comprehensive classification systems at suborganismal level have been developed, recent classification systems for multiple stressors account for environmental context. Both research areas suffer from rather simplified experimental designs that focus on only a limited number of stressors, chemicals, and treatments. We discuss concepts that can guide more realistic designs capturing spatiotemporal stressor dynamics. We suggest that process-based and data-driven models are particularly promising to tackle the challenge of prediction of effects of chemical mixtures and nonchemical stressors on (meta-)communities and (meta-)food webs. We propose a framework to integrate the assessment of effects for multiple stressors and chemical mixtures. Environ Toxicol Chem 2023;42:1915-1936. © 2023 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

Stressor richness intensifies productivity loss but mitigates biodiversity loss.

Ecosystems are subject to a multitude of anthropogenic environmental changes. Experimental research in the field of multiple stressors has typically involved varying the number of stressors, here termed stressor richness, but without controlling for total stressor intensity. Mistaking stressor intensity effects for stressor richness effects can misinform management decisions when there is a trade-off between mitigating these two factors. We incorporate multiple stressors into three community models and show that, at a fixed total stressor intensity, increasing stressor richness aggravates joint stressor effects on ecosystem functioning, but reduces effects on species persistence and composition. In addition, stressor richness weakens the positive selection and negative complementarity effects on ecosystem function. We identify the among-species variation of stressor effects on traits as a key determinant of the resulting community-level stressor effects. Taken together, our results unravel the mechanisms linking multiple environmental changes to biodiversity and ecosystem function.

Species richness increases fitness differences, but does not affect niche differences.

A key question in ecology is what limits species richness. Modern coexistence theory presents the persistence of species as a balance between niche differences and fitness differences that favour and hamper coexistence, respectively. With most applications focusing on species pairs, however, we know little about if and how this balance changes with species richness. Here, we apply recently developed definitions of niche and fitness differences, based on invasion analysis, to multispecies communities. We present the first mathematical proof that, for invariant average interaction strengths, the average fitness difference among species increases with richness, while the average niche difference stays constant. Extensive simulations with more complex models and analyses of empirical data confirmed these mathematical results. Combined, our work suggests that, as species accumulate in ecosystems, ever-increasing fitness differences will at some point exceed constant niche differences, limiting species richness. Our results contribute to a better understanding of coexistence multispecies communities.

Reinterpreting the relationship between number of species and number of links connects community structure and stability.

For 50 years, ecologists have examined how the number of interactions (links) scales with the number of species in ecological networks. Here, we show that the way the number of links varies when species are sequentially removed from a community is fully defined by a single parameter identifiable from empirical data. We mathematically demonstrate that this parameter is network-specific and connects local stability and robustness, establishing a formal connection between community structure and two prime stability concepts. Importantly, this connection highlights a local stability-robustness trade-off, which is stronger in mutualistic than in trophic networks. Analysis of 435 empirical networks confirmed these results. We finally show how our network-specific approach relates to the classical across-network approach found in literature. Taken together, our results elucidate one of the intricate relationships between network structure and stability in community networks.

Intuitive and broadly applicable definitions of niche and fitness differences.

Explaining nature's biodiversity is a key challenge for science. To persist, populations must be able to grow faster when rare, a feature called negative frequency dependence and quantified as 'niche differences' ( N ) in modern coexistence theory. Here, we first show that available definitions of N differ in how N link to species interactions, are difficult to interpret and often apply to specific community types only. We then present a new definition of N that is intuitive and applicable to a broader set of (modelled and empirical) communities than is currently the case, filling a main gap in the literature. Given N , we also redefine fitness differences ( F ) and illustrate how N and F determine coexistence. Finally, we demonstrate how to apply our definitions to theoretical models and experimental data, and provide ideas on how they can facilitate comparison and synthesis in community ecology.

Food Web Uncertainties Influence Predictions of Climate Change Effects on Soil Carbon Sequestration in Heathlands.

Carbon cycling models consider soil carbon sequestration a key process for climate change mitigation. However, these models mostly focus on abiotic soil processes and, despite its recognized critical mechanistic role, do not explicitly include interacting soil organisms. Here, we use a literature study to show that even a relatively simple soil community (heathland soils) contains large uncertainties in temporal and spatial food web structure. Next, we used a Lotka-Volterra-based food web model to demonstrate that, due to these uncertainties, climate change can either increase or decrease soil carbon sequestration to varying extents. Both the strength and direction of changes strongly depend on (1) the main consumer's (enchytraeid worms) feeding preferences and (2) whether decomposers (fungi) or enchytraeid worms are more sensitive to stress. Hence, even for a soil community with a few dominant functional groups and a simulation model with a few parameters, filling these knowledge gaps is a critical first step towards the explicit integration of soil food web dynamics into carbon cycling models in order to better assess the role soils play in climate change mitigation.

Shifts of community composition and population density substantially affect ecosystem function despite invariant richness.

There has been considerable focus on the impacts of environmental change on ecosystem function arising from changes in species richness. However, environmental change may affect ecosystem function without affecting richness, most notably by affecting population densities and community composition. Using a theoretical model, we find that, despite invariant richness, (1) small environmental effects may already lead to a collapse of function; (2) competitive strength may be a less important determinant of ecosystem function change than the selectivity of the environmental change driver and (3) effects on ecosystem function increase when effects on composition are larger. We also present a complementary statistical analysis of 13 data sets of phytoplankton and periphyton communities exposed to chemical stressors and show that effects on primary production under invariant richness ranged from -75% to +10%. We conclude that environmental protection goals relying on measures of richness could underestimate ecological impacts of environmental change.