Among-individual variation in the swimming behaviour of the amphipod Gammarus pulex under dark and light conditions.

In recent years, considerable computational advancements have been made allowing automated analysis of behavioural endpoints using video cameras. However, the results of such analyses are often confounded by a large variation among individuals, making it problematic to derive endpoints that allow distinguishing treatment effects in behavioural studies. In this study, we quantitatively analysed the effects of light conditions on the swimming behaviour of the freshwater amphipod Gammarus pulex by high-throughput tracking, and attempted to unravel among individual variation using size and sex. For this, we developed the R-package Kinematics, allowing for the rapid and reproducible analysis of the swimming behaviour (speed, acceleration, thigmotaxis, curvature and startle response) of G. pulex, as well as any other organism. Our results show a considerable amount of variation among individuals (standard deviation ranging between 5 and 115 % of the average swimming behaviour). The factors size and sex and the interaction between the two only explained a minor part of this found variation. Additionally, our study is the first to quantify the startle response in G. pulex after the light is switched on, and study the variability of this response between individuals. To analyse this startle response, we established two metrics: 1) startle response magnitude (the drop in swimming velocity directly after the light switches on), and 2) startle response duration (the time it takes to recover from the drop in swimming velocity to average swimming speed). Almost 80 % of the individuals showed a clear startle response and, therefore, these metrics demonstrate a great potential for usage in behavioural studies. The findings of this study are important for the development of appropriate experimental set-ups for behavioural experiments with G. pulex.

Effects of the antidepressant fluoxetine on the swimming behaviour of the amphipod Gammarus pulex: Comparison of short-term and long-term toxicity in the laboratory and the semi-field.

Fluoxetine is one of the worlds most prescribed antidepressant, and frequently detected in surface waters. Once present in the aquatic environment, fluoxetine has been shown to disrupt the swimming behaviour of fish and invertebrates. However, swimming behaviour is also known to be highly variable according to experimental conditions, potentially concealing relevant effects. Therefore, the aims of this study were two-fold: i) investigate the swimming and feeding behaviour of Gammarus pulex after exposure to the antidepressant fluoxetine (0.2, 2, 20, and 200 µg/L), and ii) assess to what degree the experimental test duration (short-term and long-term) and test location (laboratory and semi-field conditions) affect gammarid's swimming behaviour. We used automated video tracking and analysis to asses a range of swimming behaviours of G. pulex, including swimming speed, startle responses after light transition, acceleration, curvature and thigmotaxis. We found larger effects on the swimming behaviour of G. pulex due to experimental conditions than due to tested antidepressant concentrations. Gammarids swam faster, more straight and showed a stronger startle response during light transition when kept under semi-field conditions compared to the laboratory. Effects found for different test durations were opposite in the laboratory and semi-field. In the laboratory gammarids swam slower and spent more time at the inner zone of the arena after 2 days compared to 21 days while for the semi-field the reverse was observed. Fluoxetine had only minor impacts on the swimming behaviour of G. pulex, but experimental conditions influenced behavioural outcomes in response to fluoxetine exposure. Overall, our results highlight the importance of standardizing and optimizing experimental protocols that assess behaviour to achieve reproducible results in ecotoxicology.

(Eco)toxicological tests for assessing impacts of chemical stress to aquatic ecosystems: Facts, challenges, and future.

Monitoring of chemicals in the aquatic environment by chemical analysis alone cannot completely assess and predict the effects of chemicals on aquatic species and ecosystems. This is primarily because of the increasing number of (unknown) chemical stressors and mixture effects present in the environment. In addition, the ability of ecological indices to identify underlying stressors causing negative ecological effects is limited. Therefore, additional complementary methods are needed that can address the biological effects in a direct manner and provide a link to chemical exposure, i.e. (eco)toxicological tests. (Eco)toxicological tests are defined as test systems that expose biological components (cells, individuals, populations, communities) to (environmental mixtures of) chemicals to register biological effects. These tests measure responses at the sub-organismal (biomarkers and in vitro bioassays), whole-organismal, population, or community level. We performed a literature search to obtain a state-of-the-art overview of ecotoxicological tests available for assessing impacts of chemicals to aquatic biota and to reveal datagaps. In total, we included 509 biomarkers, 207 in vitro bioassays, 422 tests measuring biological effects at the whole-organismal level, and 78 tests at the population- community- and ecosystem-level. Tests at the whole-organismal level and biomarkers were most abundant for invertebrates and fish, whilst in vitro bioassays are mostly based on mammalian cell lines. Tests at the community- and ecosystem-level were almost missing for organisms other than microorganisms and algae. In addition, we provide an overview of the various extrapolation challenges faced in using data from these tests and suggest some forward looking perspectives. Although extrapolating the measured responses to relevant protection goals remains challenging, the combination of ecotoxicological experiments and models is key for a more comprehensive assessment of the effects of chemical stressors to aquatic ecosystems.

Cross-species extrapolation of chemical sensitivity.

Ecosystems are usually populated by many species. Each of these species carries the potential to show a different sensitivity towards all of the numerous chemical compounds that can be present in their environment. Since experimentally testing all possible species-chemical combinations is impossible, the ecological risk assessment of chemicals largely depends on cross-species extrapolation approaches. This review overviews currently existing cross-species extrapolation methodologies, and discusses i) how species sensitivity could be described, ii) which predictors might be useful for explaining differences in species sensitivity, and iii) which statistical considerations are important. We argue that risk assessment can benefit most from modelling approaches when sensitivity is described based on ecologically relevant and robust effects. Additionally, specific attention should be paid to heterogeneity of the training data (e.g. exposure duration, pH, temperature), since this strongly influences the reliability of the resulting models. Regarding which predictors are useful for explaining differences in species sensitivity, we review interspecies-correlation, relatedness-based, traits-based, and genomic-based extrapolation methods, describing the amount of mechanistic information the predictors contain, the amount of input data the models require, and the extent to which the different methods provide protection for ecological entities. We develop a conceptual framework, incorporating the strengths of each of the methods described. Finally, the discussion of statistical considerations reveals that regardless of the method used, statistically significant models can be found, although the usefulness, applicability, and understanding of these models varies considerably. We therefore recommend publication of scientific code along with scientific studies to simultaneously clarify modelling choices and enable elaboration on existing work. In general, this review specifies the data requirements of different cross-species extrapolation methods, aiming to make regulators and publishers more aware that access to raw- and meta-data needs to be improved to make future cross-species extrapolation efforts successful, enabling their integration into the regulatory environment.

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.

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.