Two constructed wetlands within a Mediterranean natural park immersed in an agrolandscape reduce most heavy metal water concentrations and dampen the majority of pesticide presence

Effects of the fungicide azoxystrobin in two habitats representative of mediterranean coastal wetlands: A mesocosm experiment

This paper investigates the effects of the fungicide azoxystrobin, a compound widely used in rice farming, on aquatic communities representative of two habitats characteristic of Mediterranean wetland ecosystems: water springs and eutrophic lake waters. The long-term effects of azoxystrobin were evaluated on several structural (phytoplankton, zooplankton, macroinvertebrate populations and communities) and functional (microbial decomposition, macrophyte and periphyton growth) parameters making use of freshwater mesocosms. Azoxystrobin was applied in two pulses of 2, 20, 200 µg/L separated by 14 d using the commercial product ORTIVA (23 % azoxystrobin w/w). The results show that these two habitats responded differently to the fungicide application due to their distinct physico-chemical, functional, and structural characteristics. Although overall sensitivity was found to be similar between the two (lowest NOEC < 2 µg/L), the taxa and processes that were affected differed substantially. In general, the most sensitive species to the fungicide were found in the water spring mesocosms, with some species of phytoplankton (Nitzschia sp.) or macrocrustaceans (Echinogammarus sp. and Dugastella valentina) being significantly affected at 2 µg/L. In the eutrophic lake mesocosms, effects were found on phytoplankton taxa (Desmodesmus sp. and Coelastrum sp.), on numerous zooplankton taxa, on chironomids and on the beetle Colymbetes fuscus, although at higher concentrations. The hemipteran Micronecta scholtzi was affected in both treatments. In addition, functional parameters such as organic matter decomposition or macrophyte growth were also affected at relatively low concentrations (NOEC 2 µg/L). Structural Equation Modelling was used to shed light on the indirect effects caused by azoxystrobin on the ecosystem. These results show that azoxystrobin is likely to pose structural and functional effects on Mediterranean wetland ecosystems at environmentally relevant concentrations. Moreover, it highlights the need to consider habitat-specific features when conducting ecotoxicological research at the population and community levels.

Multi-omics and gut microbiome: Unveiling the pathogenic mechanisms of early-life pesticide exposure

The extensive application of pesticides in agricultural production has raised significant concerns about its impact on human health. Different pesticides, including fungicides, insecticides, and herbicides, cause environmental pollution and health problems for non-target organisms. Infants and young children are so vulnerable to the harmful effects of pesticide exposure that early-life exposure to pesticides deserves focused attention. Recent research lays emphasis on understanding the mechanism between negative health impacts and early-life exposure to various pesticides. Studies have explored the impacts of exposure to these pesticides on model organisms (zebrafish, rats, and mice), as well as the mechanism of negative health effects, based on advanced methodologies like gut microbiota and multi-omics. These methodologies help comprehend the pathogenic mechanisms associated with early-life pesticide exposure. In addition to presenting health problems stemming from early-life exposure to pesticides and their pathogenic mechanisms, this review proposes expectations for future research. These proposals include focusing on identifying biomarkers that indicate early-life pesticide exposure, investigating transgenerational effects, and seeking effective treatments for diseases arising from such exposure. This review emphasizes how to understand the pathogenic mechanisms of early-life pesticide exposure through gut microbiota and multi-omics, as well as the adverse health effects of such exposure.

Pharmaceutical and pesticide mixtures in a Mediterranean coastal wetland: comparison of sampling methods, ecological risks, and removal by a constructed wetland

Pharmaceuticals and pesticides can be considered hazardous compounds for Mediterranean coastal wetland ecosystems. Although many of these compounds co-occur in environmental samples, only a few studies have been dedicated to assessing the ecotoxicological risks of complex contaminant mixtures. We evaluated the occurrence of 133 pharmaceuticals and pesticides in 12 sites in a protected Mediterranean wetland, the Albufera Natural Park (ANP), based on conventional grab sampling and polar organic chemical integrative samplers (POCIS). We assessed acute and chronic ecological risks posed by these contaminant mixtures using the multi-substance Potentially Affected Fraction (msPAF) approach and investigated the capacity of a constructed wetland to reduce chemical exposure and risks. This study shows that pharmaceuticals and pesticides are widespread contaminants in the ANP, with samples containing up to 75 different compounds. POCIS samplers were found to be useful for the determination of less predictable exposure profiles of pesticides occurring at the end of the rice cultivation cycle, while POCIS and grab samples provide an accurate method to determine (semi-)continuous pharmaceutical exposure. Acute risks were identified in one sample, while chronic risks were determined in most of the collected samples, with 5-25% of aquatic species being potentially affected. The compounds that contributed to the chronic risks were azoxystrobin, ibuprofen, furosemide, caffeine, and some insecticides (diazinon, imidacloprid, and acetamiprid). The evaluated constructed wetland reduced contaminant loads by 45-73% and reduced the faction of species affected from 25 to 6%. Our study highlights the need of addressing contaminant mixture effects in Mediterranean wetlands and supports the use of constructed wetlands to reduce contaminant loads and risks in areas with high anthropogenic pressure.

Using a Bayesian Network Model to Predict Risk of Pesticides on Aquatic Community Endpoints in a Rice Field-A Southern European Case Study

Bayesian network (BN) models are increasingly used as tools to support probabilistic environmental risk assessments (ERAs), because they can better account for uncertainty compared with the simpler approaches commonly used in traditional ERA. We used BNs as metamodels to link various sources of information in a probabilistic framework, to predict the risk of pesticides to aquatic communities under given scenarios. The research focused on rice fields surrounding the Albufera Natural Park (Valencia, Spain), and considered three selected pesticides: acetamiprid (an insecticide), 2-methyl-4-chlorophenoxyacetic acid (MCPA; a herbicide), and azoxystrobin (a fungicide). The developed BN linked the inputs and outputs of two pesticide models: a process-based exposure model (Rice Water Quality [RICEWQ]), and a probabilistic effects model (Predicts the Ecological Risk of Pesticides [PERPEST]) using case-based reasoning with data from microcosm and mesocosm experiments. The model characterized risk at three levels in a hierarchy: biological endpoints (e.g., molluscs, zooplankton, insects, etc.), endpoint groups (plants, invertebrates, vertebrates, and community processes), and community. The pesticide risk to a biological endpoint was characterized as the probability of an effect for a given pesticide concentration interval. The risk to an endpoint group was calculated as the joint probability of effect on any of the endpoints in the group. Likewise, community-level risk was calculated as the joint probability of any of the endpoint groups being affected. This approach enabled comparison of risk to endpoint groups across different pesticide types. For example, in a scenario for the year 2050, the predicted risk of the insecticide to the community (40% probability of effect) was dominated by the risk to invertebrates (36% risk). In contrast, herbicide-related risk to the community (63%) resulted from risk to both plants (35%) and invertebrates (38%); the latter might represent (in the present study) indirect effects of toxicity through the food chain. This novel approach combines the quantification of spatial variability of exposure with probabilistic risk prediction for different components of aquatic ecosystems. Environ Toxicol Chem 2024;43:182-196. © 2023 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.