Mean species responses predict effects of environmental change on coexistence.

Environmental change research is plagued by the curse of dimensionality: the number of communities at risk and the number of environmental drivers are both large. This raises the pressing question if a general understanding of ecological effects is achievable. Here, we show evidence that this is indeed possible. Using theoretical and simulation-based evidence for bi- and tritrophic communities, we show that environmental change effects on coexistence are proportional to mean species responses and depend on how trophic levels on average interact prior to environmental change. We then benchmark our findings using relevant cases of environmental change, showing that means of temperature optima and of species sensitivities to pollution predict concomitant effects on coexistence. Finally, we demonstrate how to apply our theory to the analysis of field data, finding support for effects of land use change on coexistence in natural invertebrate communities.

Predicting effects of multiple interacting global change drivers across trophic levels.

Global change encompasses many co-occurring anthropogenic drivers, which can act synergistically or antagonistically on ecological systems. Predicting how different global change drivers simultaneously contribute to observed biodiversity change is a key challenge for ecology and conservation. However, we lack the mechanistic understanding of how multiple global change drivers influence the vital rates of multiple interacting species. We propose that reaction norms, the relationships between a driver and vital rates like growth, mortality, and consumption, provide insights to the underlying mechanisms of community responses to multiple drivers. Understanding how multiple drivers interact to affect demographic rates using a reaction-norm perspective can improve our ability to make predictions of interactions at higher levels of organization-that is, community and food web. Building on the framework of consumer-resource interactions and widely studied thermal performance curves, we illustrate how joint driver impacts can be scaled up from the population to the community level. A simple proof-of-concept model demonstrates how reaction norms of vital rates predict the prevalence of driver interactions at the community level. A literature search suggests that our proposed approach is not yet used in multiple driver research. We outline how realistic response surfaces (i.e., multidimensional reaction norms) can be inferred by parametric and nonparametric approaches. Response surfaces have the potential to strengthen our understanding of how multiple drivers affect communities as well as improve our ability to predict when interactive effects emerge, two of the major challenges of ecology today.

Interactive effects of multiple stressors vary with consumer interactions, stressor dynamics and magnitude.

Predicting the impacts of multiple stressors is important for informing ecosystem management but is impeded by a lack of a general framework for predicting whether stressors interact synergistically, additively or antagonistically. Here, we use process-based models to study how interactions generalise across three levels of biological organisation (physiological, population and consumer-resource) for a two-stressor experiment on a seagrass model system. We found that the same underlying processes could result in synergistic, additive or antagonistic interactions, with interaction type depending on initial conditions, experiment duration, stressor dynamics and consumer presence. Our results help explain why meta-analyses of multiple stressor experimental results have struggled to identify predictors of consistently non-additive interactions in the natural environment. Experiments run over extended temporal scales, with treatments across gradients of stressor magnitude, are needed to identify the processes that underpin how stressors interact and provide useful predictions to management.

Biodiversity promotes ecosystem functioning despite environmental change.

Three decades of research have demonstrated that biodiversity can promote the functioning of ecosystems. Yet, it is unclear whether the positive effects of biodiversity on ecosystem functioning will persist under various types of global environmental change drivers. We conducted a meta-analysis of 46 factorial experiments manipulating both species richness and the environment to test how global change drivers (i.e. warming, drought, nutrient addition or CO2 enrichment) modulated the effect of biodiversity on multiple ecosystem functions across three taxonomic groups (microbes, phytoplankton and plants). We found that biodiversity increased ecosystem functioning in both ambient and manipulated environments, but often not to the same degree. In particular, biodiversity effects on ecosystem functioning were larger in stressful environments induced by global change drivers, indicating that high-diversity communities were more resistant to environmental change. Using a subset of studies, we also found that the positive effects of biodiversity were mainly driven by interspecific complementarity and that these effects increased over time in both ambient and manipulated environments. Our findings support biodiversity conservation as a key strategy for sustainable ecosystem management in the face of global environmental change.

Dispersal syndromes in challenging environments: A cross-species experiment.

Dispersal is a central biological process tightly integrated into life-histories, morphology, physiology and behaviour. Such associations, or syndromes, are anticipated to impact the eco-evolutionary dynamics of spatially structured populations, and cascade into ecosystem processes. As for dispersal on its own, these syndromes are likely neither fixed nor random, but conditional on the experienced environment. We experimentally studied how dispersal propensity varies with individuals' phenotype and local environmental harshness using 15 species ranging from protists to vertebrates. We reveal a general phenotypic dispersal syndrome across studied species, with dispersers being larger, more active and having a marked locomotion-oriented morphology and a strengthening of the link between dispersal and some phenotypic traits with environmental harshness. Our proof-of-concept metacommunity model further reveals cascading effects of context-dependent syndromes on the local and regional organisation of functional diversity. Our study opens new avenues to advance our understanding of the functioning of spatially structured populations, communities and ecosystems.

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.

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.

Towards a unified study of multiple stressors: divisions and common goals across research disciplines.

Anthropogenic environmental changes, or 'stressors', increasingly threaten biodiversity and ecosystem functioning worldwide. Multiple-stressor research is a rapidly expanding field of science that seeks to understand and ultimately predict the interactions between stressors. Reviews and meta-analyses of the primary scientific literature have largely been specific to either freshwater, marine or terrestrial ecology, or ecotoxicology. In this cross-disciplinary study, we review the state of knowledge within and among these disciplines to highlight commonality and division in multiple-stressor research. Our review goes beyond a description of previous research by using quantitative bibliometric analysis to identify the division between disciplines and link previously disconnected research communities. Towards a unified research framework, we discuss the shared goal of increased realism through both ecological and temporal complexity, with the overarching aim of improving predictive power. In a rapidly changing world, advancing our understanding of the cumulative ecological impacts of multiple stressors is critical for biodiversity conservation and ecosystem management. Identifying and overcoming the barriers to interdisciplinary knowledge exchange is necessary in rising to this challenge. Division between ecosystem types and disciplines is largely a human creation. Species and stressors cross these borders and so should the scientists who study them.

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.

Horizontal and vertical diversity jointly shape food web stability against small and large perturbations.

The biodiversity of food webs is composed of horizontal (i.e. within trophic levels) and vertical diversity (i.e. the number of trophic levels). Understanding their joint effect on stability is a key challenge. Theory mostly considers their individual effects and focuses on small perturbations near equilibrium in hypothetical food webs. Here, we study the joint effects of horizontal and vertical diversity on the stability of hypothetical (modelled) and empirical food webs. In modelled food webs, horizontal and vertical diversity increased and decreased stability, respectively, with a stronger positive effect of producer diversity on stability at higher consumer diversity. Experiments with an empirical plankton food web, where we manipulated horizontal and vertical diversity and measured stability from species interactions and from resilience against large perturbations, confirmed these predictions. Taken together, our findings highlight the need to conserve horizontal biodiversity at different trophic levels to ensure stability.

Modeling the Sensitivity of Aquatic Macroinvertebrates to Chemicals Using Traits.

In this study, a trait-based macroinvertebrate sensitivity modeling tool is presented that provides two main outcomes: (1) it constructs a macroinvertebrate sensitivity ranking and, subsequently, a predictive trait model for each one of a diverse set of predefined Modes of Action (MOAs) and (2) it reveals data gaps and restrictions, helping with the direction of future research. Besides revealing taxonomic patterns of species sensitivity, we find that there was not one genus, family, or class which was most sensitive to all MOAs and that common test taxa were often not the most sensitive at all. Traits like life cycle duration and feeding mode were identified as important in explaining species sensitivity. For 71% of the species, no or incomplete trait data were available, making the lack of trait data the main obstacle in model construction. Research focus should therefore be on completing trait databases and enhancing them with finer morphological traits, focusing on the toxicodynamics of the chemical (e.g., target site distribution). Further improved sensitivity models can help with the creation of ecological scenarios by predicting the sensitivity of untested species. Through this development, our approach can help reduce animal testing and contribute toward a new predictive ecotoxicology framework.

Biodiversity effects on ecosystem functioning respond unimodally to environmental stress.

Understanding how biodiversity (B) affects ecosystem functioning (EF) is essential for assessing the consequences of ongoing biodiversity changes. An increasing number of studies, however, show that environmental conditions affect the shape of BEF relationships. Here, we first use a game-theoretic community model to reveal that a unimodal response of the BEF slope can be expected along environmental stress gradients, but also how the ecological mechanisms underlying this response may vary depending on how stress affects species interactions. Next, we analysed a global dataset of 44 experiments that crossed biodiversity with environmental conditions. Confirming our main model prediction, the effect of biodiversity on ecosystem functioning tends to be greater at intermediate levels of environmental stress, but varies among studies corresponding to differences in stress-effects on species interactions. Together, these results suggest that increases in stress from ongoing global environmental changes may amplify the consequences of biodiversity changes.

Community- and ecosystem-level effects of multiple environmental change drivers: Beyond null model testing.

Understanding the joint effect of multiple drivers of environmental change is a key scientific challenge. The dominant approach today is to compare observed joint effects with predictions from various types of null models. Drivers are said to combine synergistically (antagonistically) when their observed joint effect is larger (smaller) than that predicted by the null model. Here, I argue that this approach does not promote understanding of effects on important community- and ecosystem-level variables such as biodiversity and ecosystem function. I use ecological theory to show that different mechanisms can lead to the same deviation from a null model's prediction. Inversely, I show that the same mechanism can lead to different deviations from a null model's prediction. These examples illustrate that it is not possible to make strong mechanistic inferences from null models. Next, I present an alternative framework to study such effects. This framework makes a clear distinction between two different kinds of drivers (resource ratio shifts and multiple stressors) and integrates both by incorporating stressor effects into resource uptake theory. I show that this framework can advance understanding because of three reasons. First, it forces formalization of "multiple stressors," using factors that describe the number and kind of stressors, their selectivity and dynamic behaviour, and the initial trait diversity and tolerance among species. Second, it produces testable predictions on how these factors affect biodiversity and ecosystem function, alone and in combination with resource ratio shifts. Third, it can fail in informative ways. That is, its assumptions are clear, so that different kinds of deviations between predictions and observed effects can guide new experiments and theory improvement. I conclude that this framework will more effectively progress understanding of global change effects on communities and ecosystems than does the current practice of null model testing.

Selective and context-dependent effects of chemical stress across trophic levels at the basis of marine food webs.

Human activities increasingly impact the functioning of marine food webs, but anthropogenic stressors are seldom included in ecological study designs. Diet quality, as distinct from just diet quantity, has moreover rarely been highlighted in food web studies in a stress context. We measured the effects of metal and pesticide stress (copper and atrazine) on the contribution of a benthic intertidal diatom community to two processes that are key to the functioning of intertidal systems: biomass (diet quantity) and lipid (diet quality) production. We then examined if stressors affected diatom functioning by selectively targeting the species contributing most to functioning (selective stress effects) or by changing the species' functional contribution (context-dependent effects). Finally, we tested if stress-induced changes in diet quality altered the energy flow to the diatoms' main grazers (harpacticoid copepods). Diatom diet quantity was reduced by metal stress but not by low pesticide levels due to the presence of an atrazine-tolerant, mixotrophic species. Selective effects of the pesticide reduced diatom diet quality by 60% and 75% at low and high pesticide levels respectively, by shifting diatom community structure from dominance by lipid-rich species toward dominance by an atrazine-tolerant, but lipid-poor, species. Context-dependent effects did not affect individual diatom lipid content at low levels of both stressors, but caused diatoms to lose 40% of their lipids at high copper stress. Stress-induced changes in diet quality predicted the energy flow from the diatoms to their copepod consumers, which lost half of their lipids when feeding on diatoms grown under low and high pesticide and high metal stress. Selective pesticide effects were a more important threat for trophic energy transfer than context-dependent effects of both stressors, with shifts in diatom community structure affecting the energy flow to their copepod grazers at stress levels where no changes in diatom lipid content were detected.

Links Between Heathland Fungal Biomass Mineralization, Melanization, and Hydrophobicity.

Comprehending the decomposition process is crucial for our understanding of the mechanisms of carbon (C) sequestration in soils. The decomposition of plant biomass has been extensively studied. It revealed that extrinsic biomass properties that restrict its access to decomposers influence decomposition more than intrinsic ones that are only related to its chemical structure. Fungal biomass has been much less investigated, even though it contributes to a large extent to soil organic matter, and is characterized by specific biochemical properties. In this study, we investigated the extent to which decomposition of heathland fungal biomass was affected by its hydrophobicity (extrinsic property) and melanin content (intrinsic property). We hypothesized that, as for plant biomass, hydrophobicity would have a greater impact on decomposition than melanin content. Mineralization was determined as the mineralization of soil organic carbon (SOC) into CO2 by headspace GC/MS after inoculation by a heathland soil microbial community. Results show that decomposition was not affected by hydrophobicity, but was negatively correlated with melanin content. We argue that it may indicate that either melanin content is both an intrinsic and extrinsic property, or that some soil decomposers evolved the ability to use surfactants to access to hydrophobic biomass. In the latter case, biomass hydrophobicity should not be considered as a crucial extrinsic factor. We also explored the ecology of decomposition, melanin content, and hydrophobicity, among heathland soil fungal guilds. Ascomycete black yeasts had the highest melanin content, and hyaline Basidiomycete yeasts the lowest. Hydrophobicity was an all-or-nothing trait, with most isolates being hydrophobic.

Effects of a herbicide and copper mixture on the quality of marine plankton.

Pesticides and metals are often used in agriculture and are therefore often simultaneously discharged to nearby estuarine and marine areas. The effects of this organic-inorganic chemical mixture on food quality of aquatic organisms are currently unknown. In this study we test if a mixture of copper (inorganic) and the herbicide Primextra® Gold TZ (organic) affects the quality of the diatom Thalassiosira weissflogii and the copepod Acartia tonsa - two key species that fuel the local food-web. We quantified quality (i.e. energy content as food for the next trophic level) in terms of fatty acids, proteins and thiobarbituric acid reacting substances. We found non-additive effects (positive and negative) of the metal-herbicide mixture on the diatom and copepod species. In general, nutritionally important biochemical parameters of Acartia tonsa were most sensitive to the chemical stressors.

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.

The Consequences of Nonrandomness in Species-Sensitivity in Relation to Functional Traits for Ecosystem-Level Effects of Chemicals.

Estimating ecosystem-level effects from single-species bioassays is a major challenge in environmental risk assessment. Most extrapolation procedures are based on the implicit assumption that species sensitivities are random with regard to their functional traits. Here, we explore how nonrandomness in species sensitivities affects how species-level and ecosystem level effects of chemical exposure correspond. The effect of a correlation between the trait value under control conditions and the sensitivity of the trait to chemical stress is studied for two traits (per capita growth rate and monoculture yield) under constant and temporary exposure. Theoretical model predictions are thereby validated against a 3-week microcosm experiment, in which eight marine diatoms systems with different correlations between trait values and sensitivities were temporary (1 week) or constantly (3 weeks) exposed to two concentrations of the herbicide atrazine (100 and 250 µg L-1). Negative correlations increased the reduction in ecosystem functioning (productivity) by atrazine for both traits. However, correlations in the per capita growth rate affected productivity only shortly following changes in environmental conditions, whereas correlations in the monoculture yield affected productivity throughout exposure. Correlations between species sensitivities and functional trait values can thus help to identify when ecosystem-level effects are likely to exceed species-level effects.

Biodiversity increases functional and compositional resistance, but decreases resilience in phytoplankton communities.

There is now ample evidence that biodiversity stabilizes aggregated ecosystem functions, such as primary production, in changing environments. In primary producer systems, this stabilizing effect is found to be driven by higher functional resistance (i.e., reduced changes in functions by environmental changes) rather than through higher functional resilience (i.e., rapid recovery following environmental changes) in more diverse systems. The stability of aggregated ecosystem functions directly depends on changes in species composition and by consequence their functional contributions to ecosystem functions. Still, it remains only theoretically explored how biodiversity can stabilize ecosystem functions by affecting compositional stability. Here, we demonstrate how biodiversity effects on compositional stability drive biodiversity effects on functional stability in diatom communities. In a microcosm experiment, we exposed 39 communities of five different levels of species richness (1, 2, 4, 6, and 8 species) to three concentrations of a chemical stressor (0, 25, and 250 µg/L atrazine) for four weeks, after which all communities were transferred to atrazine-free medium for three more weeks. Biodiversity simultaneously increased, increasing functional and compositional resistance, but decreased functional and compositional resilience. These results confirm the theoretically proposed link between biodiversity effects on functional and compositional stability in primary producer systems, and provide a mechanistic underpinning for observed biodiversity-stability relationships. Finally, we discuss how higher compositional stability can be expected to become increasingly important in stabilizing ecosystem functions under field conditions when multiple environmental stressors fluctuate simultaneously.

Dispersal dynamics in food webs.

Studies of food webs suggest that limited nonrandom dispersal can play an important role in structuring food webs. It is not clear, however, whether density-dependent dispersal fits empirical patterns of food webs better than density-independent dispersal. Here, we study a spatially distributed food web, using a series of population-dispersal models that contrast density-independent and density-dependent dispersal in landscapes where sampled sites are either homogeneously or heterogeneously distributed. These models are fitted to empirical data, allowing us to infer mechanisms that are consistent with the data. Our results show that models with density-dependent dispersal fit the α, ß, and γ tritrophic richness observed in empirical data best. Our results also show that density-dependent dispersal leads to a critical distance threshold beyond which site similarity (i.e., ß tritrophic richness) starts to decrease much faster. Such a threshold can also be detected in the empirical data. In contrast, models with density-independent dispersal do not predict such a threshold. Moreover, preferential dispersal from more centrally located sites to peripheral sites does not provide a better fit to empirical data when compared with symmetric dispersal between sites. Our results suggest that nonrandom dispersal in heterogeneous landscapes is an important driver that shapes local and regional richness (i.e., α and γ tritrophic richness, respectively) as well as the distance-decay relationship (i.e., ß tritrophic richness) in food webs.