Novel Concepts for Novel Entities: Updating Ecotoxicology for a Sustainable Anthropocene

Factors of global change affecting plants act at different levels of the ecological hierarchy

Plants and ecosystems worldwide are exposed to a wide range of chemical, physical, and biological factors of global change, many of which act concurrently. As bringing order to the array of factors is required in order to generate an enhanced understanding of simultaneous impacts, classification schemes have been developed. One such classification scheme is dedicated to capturing the different targets of global change factors along the ecological hierarchy. We build on this pioneering work, and refine the conceptual framework in several ways, focusing on plants and terrestrial systems: (i) we more strictly define the target level of the hierarchy, such that every factor typically has just one target level, and not many; (ii) we include effects above the level of the community, that is, there are effects also at the ecosystem scale that cannot be reduced to any level below this; (iii) we introduce the level of the landscape to capture certain land use change effects while abandoning the level below the individual. We discuss how effects can propagate along the levels of the ecological hierarchy, upwards and downwards, presenting opportunities for explaining non-additivity of effects of multiple factors. We hope that this updated conceptual framework will help inform the next generation of plant-focused global change experiments, specifically aimed at non-additivity of effects at the confluence of many factors.

Biotransformation and oxidative stress responses in fish (Astyanax aeneus) inhabiting a Caribbean estuary contaminated with pesticide residues from agricultural runoff

The estuarine ecosystem of Madre de Dios Lagoon (MDL), in the Caribbean Coast of Costa Rica, is exposed to contamination with pesticide residues coming from the upstream agricultural areas. Biomarkers can provide a better indication of the fitness of biota in real mixture exposure scenarios than traditional lethal dose toxicity measurements. Here, we measured biomarkers of biotransformation, oxidative stress, and neurotoxicity on Astyanax aeneus, an abundant fish species in MDL. Glutathione S-transferase activity (GST), catalase activity (CAT), lipid peroxidation (LPO), and cholinesterase activity (ChE) were measured in fish collected during seven sampling campaigns, carried out between 2016 and 2018. Pesticide residues were analyzed in surface water samples collected every time fish were sampled. Residues of 25 pesticides, including fungicides, insecticides, and herbicides, were detected. The biomarkers measured in A. aeneus varied along the sampling moments, with biotransformation and oxidative stress signals showing a coupled response throughout the assessment. Furthermore, significant correlations were established between three biomarkers (GST, LPO, and CAT) and individual pesticides, as well as between GST and LPO with groups of pesticides with shared biocide action. Among pesticides, insecticide residues had a major influence on the responses observed in fish. This work demonstrates the chronic exposure to pesticide residues in MDL and how such exposure is related to physiological responses in fish that can affect their health and potentially, the trophic networks. This early warning information should be considered to improve the protection of estuarine ecosystems in the tropics.

Pollution impacts on water bugs (Nepomorpha, Gerromorpha): state of the art and their biomonitoring potential

As water pollution poses an increasing risk worldwide, it is timely to assess the achievements of the aquatic macroinvertebrate ecotoxicology to provide a sound basis for the discipline's future and support the development of biomonitoring. Aquatic and semi-aquatic bugs (Hemiptera: Nepomorpha, Gerromorpha) are ubiquitous in almost all water types, sometimes in high densities, and play a significant role in organic material turnover and energy flow. Nevertheless, they are ignored in the water pollution biomonitoring schemes. Here, based on 300 papers, we review and evaluate the effects of chemical pesticides, microorganism-derived pesticides, insecticides of plant origin, heavy metals, eutrophication, salinisation and light pollution which are summarised for the first time. Our review encompasses the results of 100 laboratory and 39 semi-field/field experiments with 47 pesticides and 70 active ingredients. Pyrethroids were found to be more toxic than organochlorine, organophosphate and neonicotinoid insecticides to water bugs, like other macroinvertebrate groups. Additionally, in 10 out of 17 cases, the recommended field concentration of the pesticide was higher than the LC50 values, indicating potential hazards to water bugs. The recommended field concentrations of pesticides used in mosquito larvae control were found non-toxic to water bugs. As very few replicated studies are available, other findings on the effects of pesticides cannot be generalised. The microorganism-derived pesticide Bti appears to be safe when used at the recommended field concentration. Data indicates that plant-derived pesticides are safe with a high degree of certainty. We have identified three research areas where water bugs could be better involved in water biomonitoring. First, some Halobates spp. are excellent, and Gerris spp. are promising sentinels for Cd contamination. Second, Micronecta and, to a certain extent, Corixidae species composition is connected to and the indicator of eutrophication. Third, the species composition of the Corixidae is related to salinisation, and a preliminary method to quantify the relationship is already available. Our review highlights the potential of water bugs in water pollution monitoring.

Can a mixture of agrochemicals (glyphosate, chlorpyrifos and chlorothalonil) mask the perception of an individual chemical? A hidden trap underlying ecological risk

As aquatic environments associated with conventional agriculture are exposed to various pesticides, it is important to identify any possible interactions that modify their effects when in a mixture. We applied avoidance tests with Danio rerio, exposing juveniles to three relevant current use pesticides: chlorpyrifos (CPF), chlorothalonil (CTL) and glyphosate (Gly), individually and in binary mixtures (CPF-Gly and CTL-Gly). Our goal was to identify the potential of contaminants to trigger the avoidance response in fish and detect any changes to that response resulting from binary mixtures. Avoidance was assessed for three hours using an open gradient system with six levels of increasing concentrations. Fish avoided environmentally relevant concentrations of the three compounds. The avoidance of CPF [AC50 = 7.95 (3.3-36.3) µg/L] and CTL [AC50 = 3.41 (1.2-41.6) µg/L] was evident during the entire period of observation. In the case of Gly, the response changed throughout the experiment: initially (until 100 min) the fish tolerated higher concentrations of the herbicide [AC50 = 52.2 (12.1-2700) µg/L] while during the later period (after 100 min) a clearer avoidance [1.5 (0.8-4.2) µg/L] was observed. The avoidance recorded using CPF and CTL alone was attenuated by the presence of Gly. Applying an additive concentration model, Gly initially acted synergistically with the other two compounds, although this interaction was not observed during the later period. Avoidance gives us an idea of how the distribution of populations may be altered by contamination, our results suggest that in some mixtures this response may be inhibited, at least temporarily, thus masking the ecological risk of the exposure.

Transient exposure to sublethal concentrations of a pesticide mixture (chlorpyrifos-difenoconazole) caused different responses in fish species from different trophic levels of the same community

The assessment of early effects caused in biota by sublethal exposure to pesticide mixtures should enhance the realism in the ecological risk assessment for agricultural landscapes. This study aimed to evaluate sub-individual responses in fish, which can be linked with outcomes at higher levels of biological organization and affect their trophic relationships. A multilevel biomarker approach was applied to assess the effects of a 48 h exposure of two freshwater mesoamerican fish species (Parachromis dovii and Poecilia gillii) to a mixture of sublethal concentrations of chlorpyrifos (5 μg/L) and difenoconazole (325 μg/L). Transcriptomic induction of cyp1A and the activities of 7-ethoxy-resorufin-O-distillase (EROD) and glutathione S-transferase (GST) were measured as biotransformation-related biomarkers; cholinesterase activity (ChE) was assessed as a neurotoxicity biomarker; resting metabolic rate (RMR) was measured as a physiological biomarker; and the movement of fish in a dark-light environment as a behavior biomarker. The exposure to the mixture had evident effects on P. gillii, with significant induction of cyp1A transcription, increased EROD activity, ChE inhibition in muscle, and increased permanence in the light side of the dark-light environment. Meanwhile, P. dovii only showed significant induction of cyp1A, without evidence of neurotoxicity or changes in behavior. This study demonstrates that the severity of the effects caused by the exposure to a mixture of pesticides can differ among species from the same trophic chain. The potential impairment of predator-prey relationships is a relevant effect that pesticide pollution can cause and it should be considered for the risk assessment of such contaminants.

Image learning to accurately identify complex mixture components

The study of complex mixtures is very important for exploring the evolution of natural phenomena, but the complexity of the mixtures greatly increases the difficulty of material information extraction. Image perception-based machine-learning techniques have the ability to cope with this problem in a data-driven way. Herein, we report a 2D-spectral imaging method to collect matter information from mixture components, and the obtained feature images can be easily provided to deep convolutional neural networks (CNNs) for establishing a spectral network. The results demonstrated that a single CNN trained end-to-end from the proposed images can directly accomplish synchronous measurement of multi-component samples using only raw pixels as inputs. Our strategy has some innate advantages, such as fast data acquisition, low cost, and simple chemical treatment, suggesting that it can be extensively applied in many fields, including environmental science, biology, medicine, and chemistry.

On the difficulties of being rigorous in environmental geochemistry studies: some recommendations for designing an impactful paper

There have been numerous environmental geochemistry studies using chemical, geological, ecological, and toxicological methods but each of these fields requires more subject specialist rigour than has generally been applied so far. Field-specific terminology has been misused and the resulting interpretations rendered inaccurate. In this paper, we propose a series of suggestions, based on our experience as teachers, researchers, reviewers, and editorial board members, to help authors to avoid pitfalls. Many scientific inaccuracies continue to be unchecked and are repeatedly republished by the scientific community. These recommendations should help our colleagues and editorial board members, as well as reviewers, to avoid the numerous inaccuracies and misconceptions currently in circulation and establish a trend towards greater rigour in scientific writing.