Intraspecific demographic and trait responses to environmental change drivers are linked in two species of ciliate

BACKGROUND

Over the past decade, theory and observations have suggested intraspecific variation, trait-based differences within species, as a buffer against biodiversity loss from multiple environmental changes. This buffering effect can only occur when different populations of the same species respond differently to environmental change. More specifically, variation of demographic responses fosters buffering of demography, while variation of trait responses fosters buffering of functioning. Understanding how both responses are related is important for predicting biodiversity loss and its consequences. In this study, we aimed to empirically assess whether population-level trait responses to multiple environmental change drivers are related to the demographic response to these drivers. To this end, we measured demographic and trait responses in microcosm experiments with two species of ciliated protists. For three clonal strains of each species, we measured responses to two environmental change drivers (climate change and pollution) and their combination. We also examined if relationships between demographic and trait responses existed across treatments and strains.

RESULTS

We found different demographic responses across strains of the same species but hardly any interactive effects between the two environmental change drivers. Also, trait responses (summarized in a survival strategy index) varied among strains within a species, again with no driver interactions. Demographic and trait responses were related across all strains of both species tested in this study: Increasing intrinsic growth and self-limitation were associated with a shift in survival strategy from sit-and-wait towards flee.

CONCLUSIONS

Our results support the existence of a link between a population's demographic and trait responses to environmental change drivers in two species of ciliate. Future work could dive deeper into the specifics of phenotypical trait values, and changes therein, related to specific life strategies in different species of ciliate and other zooplankton grazers.

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.

Relationships of temperature and biodiversity with stability of natural aquatic food webs

Temperature and biodiversity changes occur in concert, but their joint effects on ecological stability of natural food webs are unknown. Here, we assess these relationships in 19 planktonic food webs. We estimate stability as structural stability (using the volume contraction rate) and temporal stability (using the temporal variation of species abundances). Warmer temperatures were associated with lower structural and temporal stability, while biodiversity had no consistent effects on either stability property. While species richness was associated with lower structural stability and higher temporal stability, Simpson diversity was associated with higher temporal stability. The responses of structural stability were linked to disproportionate contributions from two trophic groups (predators and consumers), while the responses of temporal stability were linked both to synchrony of all species within the food web and distinctive contributions from three trophic groups (predators, consumers, and producers). Our results suggest that, in natural ecosystems, warmer temperatures can erode ecosystem stability, while biodiversity changes may not have consistent effects.

Density declines, richness increases, and composition shifts in stream macroinvertebrates

Documenting trends of stream macroinvertebrate biodiversity is challenging because biomonitoring often has limited spatial, temporal, and taxonomic scopes. We analyzed biodiversity and composition of assemblages of >500 genera, spanning 27 years, and 6131 stream sites across forested, grassland, urban, and agricultural land uses throughout the United States. In this dataset, macroinvertebrate density declined by 11% and richness increased by 12.2%, and insect density and richness declined by 23.3 and 6.8%, respectively, over 27 years. In addition, differences in richness and composition between urban and agricultural versus forested and grassland streams have increased over time. Urban and agricultural streams lost the few disturbance-sensitive taxa they once had and gained disturbance-tolerant taxa. These results suggest that current efforts to protect and restore streams are not sufficient to mitigate anthropogenic effects.

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.

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.

Spatial and Ecological Scaling of Stability in Spatial Community Networks

There are many scales at which to quantify stability in spatial and ecological networks. Local-scale analyses focus on specific nodes of the spatial network, while regional-scale analyses consider the whole network. Similarly, species- and community-level analyses either account for single species or for the whole community. Furthermore, stability itself can be defined in multiple ways, including resistance (the inverse of the relative displacement caused by a perturbation), initial resilience (the rate of return after a perturbation), and invariability (the inverse of the relative amplitude of the population fluctuations). Here, we analyze the scale-dependence of these stability properties. More specifically, we ask how spatial scale (local vs. regional) and ecological scale (species vs. community) influence these stability properties. We find that regional initial resilience is the weighted arithmetic mean of the local initial resiliences. The regional resistance is the harmonic mean of local resistances, which makes regional resistance particularly vulnerable to nodes with low stability, unlike regional initial resilience. Analogous results hold for the relationship between community- and species-level initial resilience and resistance. Both resistance and initial resilience are “scale-free” properties: regional and community values are simply the biomass-weighted means of the local and species values, respectively. Thus, one can easily estimate both stability metrics of whole networks from partial sampling. In contrast, invariability generally is greater at the regional and community-level than at the local and species-level, respectively. Hence, estimating the invariability of spatial or ecological networks from measurements at the local or species level is more complicated, requiring an unbiased estimate of the network (i.e., region or community) size. In conclusion, we find that scaling of stability depends on the metric considered, and we present a reliable framework to estimate these metrics.

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.

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.

Community composition modifies direct and indirect effects of pesticides in freshwater food webs

For environmental risk assessment, the effects of pesticides on aquatic ecosystems are often assessed based on single species tests, disregarding the potential influence of community composition. We, therefore, studied the influence of changing the horizontal (the number of species within trophic levels) and vertical composition (number of trophic levels) on the ecological effects of the herbicide linuron and the insecticide chlorpyrifos, targeting producers and herbivores, respectively. We tested how adding, to a single primary producer, 4 selected competing producer species, 0-1-4 selected herbivore species, and one selected predator species resulting in 1, 2 and 3 trophic levels, changes the effects of the two pesticides. Linuron decreased producer biovolume less (17%) when the 4 producers were added, because insensitive producers compensated for the loss of sensitive producers. However, linuron decreased producer biovolume 42% and 32% more as we increased the number of herbivore species from 0 to 4 and as we increased trophic levels from 1 to 3, respectively. The indirect negative effect of linuron on herbivore biovolume was 11% and 15% lower when more producer and herbivores were added, respectively. Adding a predator increased this indirect negative effect by 22%. Chlorpyrifos decreased herbivore biovolume about 10% less when adding multiple herbivore or producer species. However, adding a predator magnified the direct negative impact on herbivores (13%). Increasing the number of producer, herbivore species and adding trophic levels increased the indirect positive impact on producer biovolume (between 10% and 35%). Our study shows that changing horizontal composition can both increase and decrease the effects of the selected pesticides, while changing vertical composition by adding number of trophic levels always increased these effects. Therefore, single species sensitivity will not always represent a worst case estimate of ecological effects. Protecting the most sensitive species may not ensure protection of ecosystems.

Potential impact of chemical stress on freshwater invertebrates: A sensitivity assessment on continental and national scale based on distribution patterns, biological traits, and relatedness

Current chemical risk assessment approaches rely on a standard suite of test species to assess toxicity to environmental species. Assessment factors are used to extrapolate from single species to communities and ecosystem effects. This approach is pragmatic, but lacks resolution in biological and environmental parameters. Novel modelling approaches can help improve the biological resolution of assessments by using mechanistic information to identify priority species and priority regions that are potentially most impacted by chemical stressors. In this study we developed predictive sensitivity models by combining species-specific information on acute chemical sensitivity (LC50 and EC50), traits, and taxonomic relatedness. These models were applied at two spatial scales to reveal spatial differences in the sensitivity of species assemblages towards two chemical modes of action (MOA): narcosis and acetylcholinesterase (AChE) inhibition. We found that on a relative scale, 46% and 33% of European species were ranked as more sensitive towards narcosis and AChE inhibition, respectively. These more sensitive species were distributed with higher occurrences in the south and north-eastern regions, reflecting known continental patterns of endemic macroinvertebrate biodiversity. We found contradicting sensitivity patterns depending on the MOA for UK scenarios, with more species displaying relative sensitivity to narcotic MOA in north and north-western regions, and more species with relative sensitivity to AChE inhibition MOA in south and south-western regions. Overall, we identified hotspots of species sensitive to chemical stressors at two spatial scales, and discuss data gaps and crucial technological advances required for the successful application of the proposed methodology to invertebrate scenarios, which remain underrepresented in global conservation priorities.

The topology and drivers of ant-symbiont networks across Europe

Intimate associations between different species drive community composition across ecosystems. Understanding the ecological and evolutionary drivers of these symbiotic associations is challenging because their structure eventually determines stability and resilience of the entire species network. Here, we compiled a detailed database on naturally occurring ant-symbiont networks in Europe to identify factors that affect symbiont network topology. These networks host an unrivalled diversity of macrosymbiotic associations, spanning the entire mutualism-antagonism continuum, including: (i) myrmecophiles - commensalistic and parasitic arthropods; (ii) trophobionts - mutualistic aphids, scale insects, planthoppers and caterpillars; (iii) social parasites - parasitic ant species; (iv) parasitic helminths; and (v) parasitic fungi. We dissected network topology to investigate what determines host specificity, symbiont species richness, and the capacity of different symbiont types to switch hosts. We found 722 macrosymbionts (multicellular symbionts) associated with European ants. Symbiont type explained host specificity and the average relatedness of the host species. Social parasites were associated with few hosts that were phylogenetically highly related, whereas the other symbiont types interacted with a larger number of hosts across a wider taxonomic distribution. The hosts of trophobionts were the least phylogenetically related across all symbiont types. Colony size, host range and habitat type predicted total symbiont richness: ant hosts with larger colony size, a larger distribution range or with a wider habitat range contained more symbiont species. However, we found that different sets of host factors affected diversity in the different types of symbionts. Ecological factors, such as colony size, host range and niche width predominantly determined myrmecophile species richness, whereas host phylogeny was the most important predictor of mutualistic trophobiont, social parasite and parasitic helminth species richness. Lastly, we found that hosts with a common biogeographic history support a more similar community of symbionts. Phylogenetically related hosts also shared more trophobionts, social parasites and helminths, but not myrmecophiles. Taken together, these results suggest that ecological and evolutionary processes structure host specificity and symbiont richness in large-scale ant-symbiont networks, but these drivers may shift in importance depending on the type of symbiosis. Our findings highlight the potential of well-characterized bipartite networks composed of different types of symbioses to identify candidate processes driving community composition.

Biodiversity mediates the effects of stressors but not nutrients on litter decomposition

Understanding the consequences of ongoing biodiversity changes for ecosystems is a pressing challenge. Controlled biodiversity-ecosystem function experiments with random biodiversity loss scenarios have demonstrated that more diverse communities usually provide higher levels of ecosystem functioning. However, it is not clear if these results predict the ecosystem consequences of environmental changes that cause non-random alterations in biodiversity and community composition. We synthesized 69 independent studies reporting 660 observations of the impacts of two pervasive drivers of global change (chemical stressors and nutrient enrichment) on animal and microbial decomposer diversity and litter decomposition. Using meta-analysis and structural equation modeling, we show that declines in decomposer diversity and abundance explain reduced litter decomposition in response to stressors but not to nutrients. While chemical stressors generally reduced biodiversity and ecosystem functioning, detrimental effects of nutrients occurred only at high levels of nutrient inputs. Thus, more intense environmental change does not always result in stronger responses, illustrating the complexity of ecosystem consequences of biodiversity change. Overall, these findings provide strong evidence that the consequences of observed biodiversity change for ecosystems depend on the kind of environmental change, and are especially significant when human activities decrease biodiversity.

Quantifying the primary biotic resource use by fisheries: A global assessment

In this paper, the specific primary production required (SPPR expressed as kg-NPP/kg-fish in wet weight) of more than 1700 marine species were calculated directly from 96 published food web models using the newly developed SPPR calculation framework. The relationship between SPPR and other ecological factors were then statistically analyzed. Among- and within-species variability of SPPR were found to be both explained by trophic level (TL), suggesting similar mechanisms underpinning both sources of variability. Among species, we found that harvesting species at higher mean trophic levels (MTL) increases the mean SPPR by a factor of 19 per 1 unit increase in MTL. Based on our empirical relationship, the mean SPPR of more than 9000 marine species were predicted and subsequently used to assess the primary production required (PPR) to support fisheries in five major fishing countries in Europe. The results indicated that conventional approach to estimating PPR, which neglects food web ecology, can underestimate PPR by up to a factor of 5. Within species, we found that harvesting populations occupying a higher TL leads to a higher SPPR. For example, the SPPR of Atlantic cod in the Celtic Sea (TL = 4.75) was 5 times higher than in the Gilbert Bay (TL = 3.3). Our results, which are based on large amounts of field data, highlight the importance of properly accounting for ecological factors during the impact assessment of fisheries.

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.

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.

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.

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.

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.

The combined and interactive effects of zinc, temperature, and phosphorus on the structure and functioning of a freshwater community

Ecotoxicological studies mainly consist of single-species experiments evaluating the effects of a single stressor. However, under natural conditions aquatic communities are exposed to a mixture of stressors. The present study aimed to identify how the toxicity of zinc (Zn) is affected by increased temperature and increased phosphorus (P) supply and how these interactions vary among species, functional groups, and community structure and function. Aquatic microcosms were subjected to 3 Zn concentrations (background, no Zn added, and 75 and 300 μg Zn/L), 2 temperatures (16-19 and 21-24 °C), and 2 different P additions (low, 0.02, and high, 0.4 mg P L^-1  wk^-1 ) for 5 wk using a full factorial design. During the study, consistent interactions between Zn and temperature were only rarely found at the species level (4%), but were frequently found at the functional group level (36%), for community structure (100%) and for community function (100%; such as dissolved organic carbon concentrations and total chlorophyll). The majority of the Zn × temperature interactions were observed at 300 μg Zn/L and generally indicated a smaller effect of Zn at higher temperature. Furthermore, no clear indication was found that high P addition by itself significantly affected the overall effects of Zn on the community at any level of organization. Interestingly, though, 90% of all the Zn × temperature interactions observed at the species, group, and community composition level were found under high P addition. Collectively, the results of our study with the model chemical Zn suggest that temperature and phosphorus loading to freshwater systems should be accounted for in risk assessment, because these factors may modify the effects of chemicals on the structure and functioning of aquatic communities, especially at higher levels of biological organization. Environ Toxicol Chem 2018;37:2413-2427. © 2018 SETAC.

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.

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.

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.

The combined effects of biotic and abiotic stress on species richness and connectance

Food web structure and species richness are both subject to biotic (e.g. predation pressure and resource limitation) and abiotic stress (e.g. environmental change). We investigated the combined effects of both types of stress on richness and connectance, and on their relationship, in a predator-prey system. To this end, we developed a mathematical two trophic level food-web model to investigate the effects of biotic and abiotic stress on food web connectance and species richness. We found negative effects of top-down and bottom-up control on prey and predator richness, respectively. Effects of top-down and bottom-up control were stronger when initial connectance was high and low, respectively. Bottom-up control could either aggravate or buffer negative effects of top-down control. Abiotic stress affecting predator richness had positive indirect effects on prey richness, but only when initial connectance was low. However, no indirect effects on predator richness were observed following direct effects on prey richness. Top-down and bottom-up control selected for weakly connected prey and highly connected predators, thereby decreasing and increasing connectance, respectively. Our simulations suggest a broad range of negative and positive richness-connectance relationships, thereby revisiting the often found negative relationship between richness and connectance in food webs. Our results suggest that (1) initial food-web connectance strongly influences the effects of biotic stress on richness and the occurrence of indirect effects on richness; and (2) the shape of the richness-connectance relationship depends on the type of biotic stress.

Toward refined environmental scenarios for ecological risk assessment of down-the-drain chemicals in freshwater environments

Current regulatory practice for chemical risk assessment suffers from the lack of realism in conventional frameworks. Despite significant advances in exposure and ecological effect modeling, the implementation of novel approaches as high-tier options for prospective regulatory risk assessment remains limited, particularly among general chemicals such as down-the-drain ingredients. While reviewing the current state of the art in environmental exposure and ecological effect modeling, we propose a scenario-based framework that enables a better integration of exposure and effect assessments in a tiered approach. Global- to catchment-scale spatially explicit exposure models can be used to identify areas of higher exposure and to generate ecologically relevant exposure information for input into effect models. Numerous examples of mechanistic ecological effect models demonstrate that it is technically feasible to extrapolate from individual-level effects to effects at higher levels of biological organization and from laboratory to environmental conditions. However, the data required to parameterize effect models that can embrace the complexity of ecosystems are large and require a targeted approach. Experimental efforts should, therefore, focus on vulnerable species and/or traits and ecological conditions of relevance. We outline key research needs to address the challenges that currently hinder the practical application of advanced model-based approaches to risk assessment of down-the-drain chemicals. Integr Environ Assess Manag 2017;13:233-248. © 2016 SETAC.

European environmental scenarios of chemical bioavailability in freshwater systems

In exposure prediction for environmental risk assessment, the transition to more dynamic and realistic modelling approaches and scenarios has been recently identified as a major challenge, since it would allow a more accurate prediction of bioavailable concentrations and their variations in space and time. In this work, an improved version of the multimedia model ChimERA fate, including a phytoplankton compartment and equations to calculate phytoplankton, detritus and dissolved organic matter variations in time, was developed. The model was parameterized to simulate five dynamic scenarios for shallow meso-eutrophic water bodies based on a latitudinal gradient (in Europe); such scenarios include seasonal profiles of water temperature, phytoplankton biomass, detritus, and dissolved organic matter. Model runs were performed for each scenario for 8 hydrophobic chemicals (PCB congeners), with the aim of investigating the influence of scenario characteristics and compound properties on bioavailable concentrations. The key processes were adsorption/uptake by phytoplankton and deposition to sediment of detritus-bound chemicals. The northern scenarios ("Scandinavia" and "UK") showed the highest bioavailable concentrations, with annual maximum/minimum concentration up to 25; in contrast, for example, maximum concentrations in the "Mediterranean" scenario were lower by a factor of 2 to 9 with respect to the northern ones (depending on chemical hydrophobicity), due to the generally higher biomass and carbon levels, and showed only limited seasonal variability (up to a factor of 4). These results highlight the importance of including biomass and organic carbon dynamics in both modelling approaches and scenarios for the evaluation of exposure concentrations in aquatic environments.

Time-varying effects of aromatic oil constituents on the survival of aquatic species: Deviations between model estimates and observations

There is a need to study the time course of toxic chemical effects on organisms because there might be a time lag between the onset of chemical exposure and the corresponding adverse effects. For aquatic organisms, crude oil and oil constituents originating from either natural seeps or human activities can be relevant case studies. In the present study the authors tested a generic toxicokinetic model to quantify the time-varying effects of various oil constituents on the survival of aquatic organisms. The model is based on key parameters applicable to an array of species and compounds with baseline toxicity reflected by a generic, internal toxicity threshold or critical body burden (CBB). They compared model estimates with experimental data on the effects of 8 aromatic oil constituents on the survival of aquatic species including crustaceans and fish. The average model uncertainty, expressed as the root mean square error, was 0.25 (minimum-maximum, 0.04-0.67) on a scale between 0 and 1. The estimated survival was generally lower than the measured survival right after the onset of oil constituent exposure. In contrast, the model underestimated the maximum mortality for crustaceans and fish observed in the laboratory. Thus, the model based on the CBB concept failed to adequately predict the lethal effects of the oil constituents on crustaceans and fish. Possible explanations for the deviations between model estimates and observations may include incorrect assumptions regarding a constant lethal body burden, the absence of biotransformation products, and the steady state of aromatic hydrocarbon concentrations in organisms. Clearly, a more complex model approach than the generic model used in the present study is needed to predict toxicity dynamics of narcotic chemicals. Environ Toxicol Chem 2017;36:128-136. © 2016 SETAC.

Reintroducing Environmental Change Drivers in Biodiversity-Ecosystem Functioning Research

For the past 20 years, research on biodiversity and ecosystem functioning (B-EF) has only implicitly considered the underlying role of environmental change. We illustrate that explicitly reintroducing environmental change drivers in B-EF research is needed to predict the functioning of ecosystems facing changes in biodiversity. Next we show how this reintroduction improves experimental control over community composition and structure, which helps to provide mechanistic insight on how multiple aspects of biodiversity relate to function and how biodiversity and function relate in food webs. We also highlight challenges for the proposed reintroduction and suggest analyses and experiments to better understand how random biodiversity changes, as studied by classic approaches in B-EF research, contribute to the shifts in function that follow environmental change.

Crude oil affecting the biomass of the marine copepod Calanus finmarchicus: Comparing a simple and complex population model

In the current study differences were evaluated between a complex 3D multistage population model (SINMOD) and a simpler consumer-resource population model for estimating the effects of crude oil on the marine copepod Calanus finmarchicus. The SINTEF OSCAR model was used to simulate hypothetical oil spills in the Lofoten area in 1995, 1997, and 2001. Both population models simulated a negligible effect of crude oil on the Calanus' biomass when assuming low species sensitivity. The simple model estimated a larger effect on the biomass (up to a 100% decline) compared to the complex model (maximum decline of 60-80%) at high species sensitivity to crude oil. These differences may be related to the inclusion of copepod advection in the complex model. Our study showed that if little data is available to parameterize a model, or if computational resources are scarce, the simple model could be used for risk screening. Nevertheless, the possibility of including a dilution factor for time-varying biomass should be examined to improve the estimations of the simple model. The complex model should be used for a more in depth risk analysis, as it includes physical processes such as the drift of organisms and differentiation between developmental stages.

Realistic environmental mixtures of hydrophobic compounds do not alter growth of a marine diatom

In this paper we determine whether a realistic mixture of hydrophobic chemicals affects the growth dynamics of a marine diatom and how this effect compares to the effect of temperature, light regime and nutrient conditions. To do so, we examine the specific growth rate of Phaeodactylum tricornutum in a 72 h algal growth inhibition test using a full factorial design with three nutrient regimes, two test temperatures, three light intensities and three chemical exposures. Passive samplers were used to achieve exposure to realistic mixtures of organic chemicals close to ambient concentrations. Nutrient regime, temperature and time interval (24, 48 and 72 h) explained 85% of the observed variability in the experimental data. The variability explained by chemical exposure was about 1%. Overall, ambient concentrations of hydrophobic compounds present in Belgian coastal waters, and for which the passive samplers have affinity, are too low to affect the intrinsic growth rate of P. tricornutum.

Population-level effects and recovery of aquatic invertebrates after multiple applications of an insecticide

Standard risk assessment of plant protection products (PPP) combines "worst-case" exposure scenarios with effect thresholds using assessment (safety) factors to account for uncertainties. If needed, risks can be addressed applying more realistic conditions at higher tiers, which refine exposure and/or effect assessments using additional data. However, it is not possible to investigate the wide range of potential scenarios experimentally. In contrast, ecotoxicological mechanistic effect models do allow for addressing a multitude of scenarios. Furthermore, they may aid the interpretation of experiments such as mesocosm studies, allowing extrapolation to conditions not covered in experiments. Here, we explore how to use mechanistic effect models in the aquatic risk assessment of a model insecticide (Modelmethrin), applied several times per season but rapidly dissipating between applications. The case study focuses on potential effects on aquatic arthropods, the most sensitive group for this substance. The models provide information on the impact of a number of short exposure pulses on sensitive and/or vulnerable populations and, when impacted, assess recovery. The species to model were selected based on their sensitivity in laboratory and field (mesocosm) studies. The general unified threshold model for survival (GUTS) model, which describes the toxicokinetics and toxicodynamics of chemicals in individuals, was linked to 3 individual-based models (IBM), translating individual survival of sensitive organisms into population-level effects. The impact of pulsed insecticide exposures on populations were modeled using the spatially explicit IBM metapopulation model for assessing spatial and temporal effects of pesticides (MASTEP) for Gammarus pulex, the Chaoborus IBM for populations of Chaoborus crystallinus, and the "IdamP" model for populations of Daphnia magna. The different models were able to predict the potential effects of Modelmethrin applications to key arthropod species inhabiting different aquatic ecosystems; the most sensitive species were significantly impacted unless respective mitigation measures were implemented (buffer zones resulting in reduced exposure). As expected the impact was stronger in shallow ditches as compared to deeper pond scenarios. Furthermore, as expected, recovery depended on factors such as temperature (affecting population growth rate and number of generations) and the occurence of nonimpacted aquatic ecosystems (their frequency and connectivity). These model predictions were largely in line with field observations and/or the results of a mesocosm study, providing additional evidence on the suitability and reliability of the models for risk assessment purposes. Because of their flexibility, models may predict the likelihood of unacceptable effects-based on previously defined protection goals-for a range of insecticide exposure scenarios and freshwater habitats.

Re-evaluating Primary Biotic Resource Use for Marine Biomass Production: A New Calculation Framework

The environmental impacts of biomass harvesting can be quantified through the amount of net primary production required to produce one unit of harvested biomass (SPPR-specific primary production required). This paper presents a new calculation framework that explicitly takes into account full food web complexity and shows that the resulting SPPR for toothed whales in the Icelandic marine ecosystem is 2.8 times higher than the existing approach based on food web simplification. In addition, we show that our new framework can be coupled to food web modeling to examine how uncertainty on ecological data and processes can be accounted for while estimating SPPR. This approach reveals that an increase in the degree of heterotrophy by flagellates from 0% to 100% results in a two-fold increase in SPPR estimates in the Barents Sea. It also shows that the estimated SPPR is between 3.9 (herring) and 5.0 (capelin) times higher than that estimated when adopting food chain theory. SPPR resulting from our new approach is only valid for the given time period for which the food web is modeled and cannot be used to infer changes in SPPR when the food web is altered by changes in human exploitation or environmental changes.

Importance of environmental and biomass dynamics in predicting chemical exposure in ecological risk assessment

In ecological risk assessment, exposure is generally modelled assuming static conditions, herewith neglecting the potential role of emission, environmental and biomass dynamics in affecting bioavailable concentrations. In order to investigate the influence of such dynamics on predicted bioavailable concentrations, the spatially-resolved dynamic model "ChimERA fate" was developed, incorporating macrophyte and particulate/dissolved organic carbon (POC/DOC) dynamics into a water-sediment system. An evaluation against three case studies revealed a satisfying model performance. Illustrative simulations then highlighted the potential spatio-temporal variability of bioavailable concentrations after a pulsed emission of four chemicals in a system composed of a pond connected to its inflow and outflow streams. Changes in macrophyte biomass and POC/DOC levels caused exposure variations which were up to a factor of 4.5 in time and even more significant (several orders of magnitude) in space, especially for highly hydrophobic chemicals. ChimERA fate thus revealed to be a useful tool to investigate such variations and to identify those environmental and ecological conditions in which risk is expected to be highest.