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.

Influence of climate change and pesticide use practices on the ecological risks of pesticides in a protected Mediterranean wetland: A Bayesian network approach.

Pollution by agricultural pesticides is one of the most important pressures affecting Mediterranean coastal wetlands. Pesticide risks are expected to be influenced by climate change, which will result in an increase of temperatures and a decrease in annual precipitation. On the other hand, pesticide dosages are expected to change given the increase in pest resistance and the implementation of environmental policies like the European ´Farm-to-Fork` strategy, which aims for a 50 % reduction in pesticide usage by 2030. The influence of climate change and pesticide use practices on the ecological risks of pesticides needs to be evaluated making use of realistic environmental scenarios. This study investigates how different climate change and pesticide use practices affect the ecological risks of pesticides in the Albufera Natural Park (Valencia, Spain), a protected Mediterranean coastal wetland. We performed a probabilistic risk assessment for nine pesticides applied in rice production using three climatic scenarios (for the years 2008, 2050 and 2100), three pesticide dosage regimes (the recommended dose, and 50 % increase and 50 % decrease), and their combinations. The scenarios were used to simulate pesticide exposure concentrations in the water column of the rice paddies using the RICEWQ model. Pesticide effects were characterized using acute and chronic Species Sensitivity Distributions built with toxicity data for aquatic organisms. Risk quotients were calculated as probability distributions making use of Bayesian networks. Our results show that future climate projections will influence exposure concentrations for some of the studied pesticides, yielding higher dissipation and lower exposure in scenarios dominated by an increase of temperatures, and higher exposure peaks in scenarios where heavy precipitation events occur right after pesticide application. Our case study shows that pesticides such as azoxystrobin, difenoconazole and MCPA are posing unacceptable ecological risks for aquatic organisms, and that the implementation of the ´Farm-to-Fork` strategy is crucial to reduce them.

Biodiversity impacts by multiple anthropogenic stressors in Mediterranean coastal wetlands.

Mediterranean coastal wetlands are considered biodiversity hot-spots and contain a high number of endemic species. The biodiversity of these ecosystems is endangered by several pressures resulting from agricultural and urban expansion, climate change, and the alteration of their hydrological cycle. In this study we assess the state-of-the-art regarding the impact of several stressor groups on the biodiversity of Mediterranean coastal wetlands (i.e., lagoons, marshes, estuaries). Particularly, we describe the impacts of eutrophication, chemical pollution, invasive species, salinization, and temperature rise, and analyze the existing literature regarding the impact of multiple stressors on these ecosystems. Our study denotes a clear asymmetry both in terms of study areas and stressors evaluated. The majority of studies focus on lagoons and estuaries of the north-west parts of the Mediterranean basin, while the African and the Asian coast have been less represented. Eutrophication and chemical pollution were the most studied stressors compared to others like temperature rise or species invasions. Most studies evaluating these stressors individually show direct or indirect effects on the biodiversity of primary producers and invertebrate communities, and changes in species dominance patterns that contribute to a decline of endemic populations. The few available studies addressing stressor interactions have shown non-additive responses, which are important to define appropriate ecosystem management and restoration measures. Finally, we propose research needs to advance our understanding on the impacts of anthropogenic stressors on Mediterranean coastal wetlands and to guide future interventions to protect biodiversity.