The contribution of intra- and interspecific tolerance variability to biodiversity changes along toxicity gradients

Linking ecotoxicological effects on biodiversity and ecosystem functions to impairment of ecosystem services is a challenge: an illustration with the case of plant protection products

There is growing interest in using the ecosystem services framework for environmental risk assessments of chemicals, including plant protection products (PPPs). Although this topic is increasingly discussed in the recent scientific literature, there is still a substantial gap between most ecotoxicological studies and a solid evaluation of potential ecotoxicological consequences on ecosystem services. This was recently highlighted by a collective scientific assessment (CSA) performed by 46 scientific experts who analyzed the international science on the impacts of PPPs on biodiversity, ecosystem functions, and ecosystem services. Here, we first point out the main obstacles to better linking knowledge on the ecotoxicological effects of PPPs on biodiversity and ecological processes with ecosystem functions and services. Then, we go on to propose and discuss possible pathways for related improvements. We describe the main processes governing the relationships between biodiversity, ecological processes, and ecosystem functions in response to effects of PPP, and we define categories of ecosystem functions that could be directly linked with the ecological processes used as functional endpoints in investigations on the ecotoxicology of PPPs. We then explore perceptions on the possible links between these categories of ecosystem functions and ecosystem services among a sub-panel of the scientific experts from various fields of environmental science. We find that these direct and indirect linkages still need clarification. This paper, which reflects the difficulties faced by the multidisciplinary group of researchers involved in the CSA, suggests that the current gap between most ecotoxicological studies and a solid potential evaluation of ecotoxicological consequences on ecosystem services could be partially addressed if concepts and definitions related to ecological processes, ecosystem functions, and ecosystem services were more widely accepted and shared within the ecotoxicology community. Narrowing this gap would help harmonize and extend the science that informs decision-making and policy-making, and ultimately help to better address the trade-off between social benefits and environmental losses caused by the use of PPPs.

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.

Metal Mixture Toxicity of Ni, Cu, and Zn in Freshwater Algal Communities and the Correlation of Single-Species Sensitivities Among Single Metals: A Comparative Analysis

The effects assessment of metals is mainly based on data of single metals on single species, thereby not accounting for effects of metal mixtures or effects of species interactions. Both of these effects were tested in combination, thereby hypothesizing that the sensitivity of a community to synergistic mixture toxicity depends on the correlation of single-species sensitivities among the single metals. Single-metal and metal-mixture effects were tested in full concentration-response experiments (fixed ray of 1:1:3 and 5:1:13 mass ratio Ni:Cu:Zn) on eight single freshwater algal species and 14 algal communities of four species each. The mean correlation of single-species median effect concentrations among the single metals (Ni-Cu, Cu-Zn, and Zn-Ni) for all species in a community (r ̅ ) ranged from -0.4 to 0.9 among the communities; most of these (12/14) were positive. Functional endpoints (total biomass) were overall less sensitive than structural endpoints (Bray-Curtis similarity index) for communities with positively correlated single-species sensitivities among the single metals (r ̅ > 0.33 ), suggesting that such correlations indicate functional redundancy under metal-mixture stress. Antagonistic metal-mixture interactions were predominantly found in single species, whereas metal-mixture interactions were antagonistic and surprisingly synergistic for the communities, irrespective of the reference mixture model used (concentration addition or independent action). The mixture interactions close to the carrying capacity (day 7) of communities gradually shifted from antagonism to more noninteractions with increasing correlation of single-species sensitivities among the single metals. Overall, this suggests that functional redundancy under mixed-metal stress comes at the cost of reduced biodiversity and that synergisms can emerge at the community level without any synergisms on the single-species level. Environ Toxicol Chem 2023;42:2666-2683. © 2023 SETAC.

Three perspectives on the prediction of chemical effects in ecosystems

The increasing production, use and emission of synthetic chemicals into the environment represents a major driver of global change. The large number of synthetic chemicals, limited knowledge on exposure patterns and effects in organisms and their interaction with other global change drivers hamper the prediction of effects in ecosystems. However, recent advances in biomolecular and computational methods are promising to improve our capacity for prediction. We delineate three idealised perspectives for the prediction of chemical effects: the suborganismal, organismal and ecological perspective, which are currently largely separated. Each of the outlined perspectives includes essential and complementary theories and tools for prediction but captures only part of the phenomenon of chemical effects. Links between the perspectives may foster predictive modelling of chemical effects in ecosystems and extrapolation between species. A major challenge for the linkage is the lack of data sets simultaneously covering different levels of biological organisation (here referred to as biological levels) as well as varying temporal and spatial scales. Synthesising the three perspectives, some central aspects and associated types of data seem particularly necessary to improve prediction. First, suborganism- and organism-level responses to chemicals need to be recorded and tested for relationships with chemical groups and organism traits. Second, metrics that are measurable at many biological levels, such as energy, need to be scrutinised for their potential to integrate across levels. Third, experimental data on the simultaneous response over multiple biological levels and spatiotemporal scales are required. These could be collected in nested and interconnected micro- and mesocosm experiments. Lastly, prioritisation of processes involved in the prediction framework needs to find a balance between simplification and capturing the essential complexity of a system. For example, in some cases, eco-evolutionary dynamics and interactions may need stronger consideration. Prediction needs to move from a static to a real-world eco-evolutionary view.

Mean Species Abundance as a Measure of Ecotoxicological Risk

Chemical pollution of surface waters is considered an important driver for recent declines in biodiversity. Species sensitivity distributions (SSDs) are commonly used to evaluate the ecological risks of chemical exposure, accounting for variation in interspecies sensitivity. However, SSDs do not reflect the effects of chemical exposure on species abundance, considered an important endpoint in biological conservation. Although complex population modeling approaches lack practical applicability when it comes to the routine practice of lower tier chemical risk assessment, in the present study we show how information from widely available laboratory toxicity tests can be used to derive the change in mean species abundance (MSA) as a function of chemical exposure. These exposure-response MSA relationships combine insights into intraspecies exposure-response relationships and population growth theory. We showcase the practical applicability of our method for cadmium, copper, and zinc, and include a quantification of the associated statistical uncertainty. For all 3 metals, we found that concentrations hazardous for 5% of the species (HC₅ s) based on MSA relationships are systematically higher than SSD-based HC₅ values. Our proposed framework can be useful to derive abundance-based ecological protective criteria for chemical exposure, and creates the opportunity to assess abundance impacts of chemical exposure in the context of various other anthropogenic stressors. Environ Toxicol Chem 2020;39:2304-2313. © 2020 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

Establishing causal links between aquatic biodiversity and ecosystem functioning: Status and research needs

Understanding how changes in biodiversity affects ecosystem functioning is imperative in allowing Ecosystem-Based Management (EBM), especially when addressing global change and environmental degradation. Research into the link between biodiversity and ecosystem functioning (BEF) has indeed increased considerably over the past decades. BEF research has focussed on terrestrial ecosystems and aquatic ecosystems have received considerably less attention. Due to differences in phylogenetic diversity, ecological processes and reported BEF relationships, however, it may at least be questionable whether BEF relationships are exchangeable between these ecosystems (i.e. terrestrial and aquatic). The aim of the present paper was therefore to pinpoint key areas and bottlenecks in establishing BEF relationships for aquatic ecosystems (freshwater, transitional, and marine). To this end, the available literature with special emphasis on the last 10 years was assessed to evaluate: i) reported mechanisms and shapes of aquatic BEF relationships; ii) to what extent BEF relations are interchangeable or ecosystem-specific; and iii) contemporary gaps and needs in aquatic BEF research. Based on our analysis, it may be concluded that despite considerable progress in BEF research over the past decades, several bottlenecks still need to be tackled, namely incorporating the multitude of functions supported by ecosystems, functional distinctiveness of rare species, multitrophic interactions and spatial-temporal scales, before BEF relationships can be used in ecosystem-based management.

Light limitation increases multidimensional trait evenness in phytoplankton populations

Individual-level variation arising from responses to environmental gradients influences population and community dynamics. How such responses empirically relate to the mechanisms that govern species coexistence is, however, poorly understood. Previous results from l ake phytoplankton communities suggested that the evenness of organismal traits in multiple dimensions increases with resource limitation, possibly due to resource partitioning at the individual level. Here we experimentally tested the emergence of this pattern by growing two phytoplankton species (Pseudokirchneriella subcapitata and Microcystis aeruginosa) under a gradient of light intensity, in monoculture and jointly. Under low light (resource) conditions, the populations diversified into a wide range of phenotypes, which were evenly distributed in multidimensional trait space (defined by four pigment-related trait dimensions), consistent with the observed field pattern. Our interpretation is that under conditions of light limitation, individual phytoplankton cells alter photosynthetic traits to reduce overlap in light acquisition, acquiring unexploited resources and thereby likely maximising individual success. Our results provide prime experimental evidence that resource limitation increases the evenness of conspecific and heterospecific microbial phenotypes along trait axes, advancing our understanding of trait-based coexistence.

Using field data to quantify chemical impacts on wildlife population viability

Environmental pollution is an important driver of biodiversity loss. Yet, to date, the effects of chemical exposure on wildlife populations have been quantified for only a few species, mainly due to a lack of appropriate laboratory data to quantify chemical impacts on vital rates. In this study, we developed a method to quantify the effects of toxicant exposure on wildlife population persistence based on field monitoring data. We established field-based vital-rate-response functions for toxicants, using quantile regression to correct for the influences of confounding factors on the vital rates observed, and combined the response curves with population viability modelling. We then applied the method to quantify the impact of DDE on three bird species: the White-tailed Eagle, Bald Eagle, and Osprey. Population viability was expressed via five population extinction vulnerability metrics: population growth rate (r₁ ), critical patch size (CPS), minimum viable population size (MVP), probability of population extirpation (PE), and median time to population extirpation (MTE). We found that past DDE exposure concentrations increased population extirpation vulnerabilities of all three bird species. For example, at DDE concentrations of 25 mg/kg wet mass of egg (the maximum historic exposure concentration reported in literature for the Osprey), r₁ became small (White-tailed Eagle and Osprey) or close to zero (Bald Eagle), the CPS increased up to almost the size of Connecticut (White-tailed Eagle and Osprey) or West Virginia (Bald Eagle), the MVP increased up to approximately 90 (White-tailed Eagle and Osprey) or 180 breeding pairs (Bald Eagle), the PE increased up to almost certain extirpation (Bald Eagle) or only slightly elevated levels (White-tailed Eagle and Osprey) and the MTE became within decades (Bald Eagle) or remained longer than a millennium (White-tailed Eagle and Osprey). Our study provides a method to derive species-specific field-based response curves of toxicant exposure, which can be used to assess population extinction vulnerabilities and obtain critical levels of toxicant exposure based on maximum permissible effect levels. This may help conservation managers to better design appropriate habitat restoration and population recovery measures, such as reducing toxicant levels, increasing the area of suitable habitat or reintroducing individuals.

Individual-level trait diversity predicts phytoplankton community properties better than species richness or evenness

Understanding how microbial diversity influences ecosystem properties is of paramount importance. Cellular traits-which determine responses to the abiotic and biotic environment-may help us rigorously link them. However, our capacity to measure traits in natural communities has thus far been limited. Here we compared the predictive power of trait richness (trait space coverage), evenness (regularity in trait distribution) and divergence (prevalence of extreme phenotypes) derived from individual-based measurements with two species-level metrics (taxonomic richness and evenness) when modelling the productivity of natural phytoplankton communities. Using phytoplankton data obtained from 28 lakes sampled at different spatial and temporal scales, we found that the diversity in individual-level morphophysiological traits strongly improved our ability to predict community resource-use and biomass yield. Trait evenness-the regularity in distribution of individual cells/colonies within the trait space-was the strongest predictor, exhibiting a robust negative relationship across scales. Our study suggests that quantifying individual microbial phenotypes in trait space may help us understand how to link physiology to ecosystem-scale processes. Elucidating the mechanisms scaling individual-level trait variation to microbial community dynamics could there improve our ability to forecast changes in ecosystem properties across environmental gradients.

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.

Water-borne pharmaceuticals reduce phenotypic diversity and response capacity of natural phytoplankton communities

Chemical micropollutants occur worldwide in the environment at low concentrations and in complex mixtures, and how they affect the ecology of natural systems is still uncertain. Dynamics of natural communities are driven by the interaction between individual organisms and their growth environment, which is mediated by the organisms’ expressed phenotypic traits. We tested whether exposure to a mixture of 12 pharmaceuticals and personal care products (PPCP) influences phenotypic trait diversity in lake phytoplankton communities and their ability to regulate biomass production to fit environmental changes (response capacity). We exposed natural phytoplankton assemblages to three mixture levels in permeable microcosms maintained at three depths in a eutrophic lake for one week, during which the environmental conditions were fluctuating. We studied individual-level traits, phenotypic diversity and community biomass. PPCP reduced individual-level trait variance and overall community phenotypic diversity, but maintained higher standing phytoplankton biomass compared to untreated controls. Estimated effect sizes of PPCP on traits and community properties were very large (partial Eta-squared > 0.15). The PPCP mixture antagonistically interacted with the natural environmental gradient in habitats offered by different depths and, at concentrations comparable to those in waste-water effluents, prevented communities from converging to the same phenotypic structure and total biomass of unexposed controls. We show that micropollutants can alter individual-level trait diversity of lake phytoplankton communities and therefore their capacity to respond to natural environmental gradients, potentially affecting aquatic ecosystem processes.

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.

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.

Relative contribution of persistent organic pollutants to marine phytoplankton biomass dynamics in the North Sea and the Kattegat

In this paper, we use concentrations of persistent organic pollutants (POPs) and of chlorophyll a to infer POP-induced effects on marine primary production in the Kattegat and the North Sea between the 1990s and the 2000s. To do so, we modelled phytoplankton dynamics using four classical drivers (light and nutrient availability, temperature and zooplankton grazing) and tested whether extending this model with a POP-induced phytoplankton growth limitation term improved model fit to observed chlorophyll a concentrations. Including monitored concentrations of PCBs and pesticides did not lead to a better model fit, suggesting that POP-induced growth limitation of marine phytoplankton in the North Sea and the Kattegat is small compared to the limitations caused by the classical drivers. In an attempt to more fully represent the multitude of POPs in the marine environment, the monitored concentrations were multiplied with a factor 10 and 100. Under these two configurations, region-specific contributions of POPs in the phytoplankton growth limitation were found. The inferred contribution of POPs to phytoplankton growth limitation was ca. 1% in Belgian marine waters, but in the Kattegat POPs explained ca. 10% of the phytoplankton growth limitation. These results suggest that there are regional differences in the contribution of POPs to the phytoplankton growth limitation.

Prescriptive Evolution to Conserve and Manage Biodiversity

We are witnessing a global, but unplanned, evolutionary experiment with the biodiversity of the planet. Anthropogenic disturbances such as habitat degradation and climate change result in evolutionary mismatch between the environments to which species are adapted and those in which they now exist. The impacts of unmanaged evolution are pervasive, but approaches to address them have received little attention. We review the evolutionary challenges of managing populations in the Anthropocene and introduce the concept of prescriptive evolution, which considers how evolutionary processes may be leveraged to proactively promote wise management. We advocate the planned management of evolutionary processes and explore the advantages of evolutionary interventions to preserve and sustain biodiversity. We show how an evolutionary perspective to conserving biodiversity is fundamental to effective management. Finally, we advocate building frameworks for decision-making, monitoring, and implementation at the boundary between management and evolutionary science to enhance conservation outcomes.