This study assesses the ecological risks (ERA) of pesticides to aquatic organisms in the River Madre de Dios (RMD), which receives surface runoff water from banana, pineapple, and rice plantations on the Caribbean coast of Costa Rica. Water samples collected over 2 years at five sites in the RMD revealed a total of 26 pesticides. Their toxicity risk to aquatic organisms was assessed using three recent ERA models. (1) The PERPEST model showed a high probability (>50 %) of clear toxic effects of pesticide mixtures on algae, macrophytes, zooplankton, macroinvertebrates, and community metabolism and a low probability (<50 %) of clear effects on fish. (2) Species sensitivity distributions (SSD) showed a moderate to high risk of three herbicides: ametryn, bromacil, diuron and four insecticides: carbaryl, diazinon, ethoprophos, terbufos. (3) The multi-substance potentially affected fraction (msPAF) model showed results consistent with PERPEST: high risk to algae (maximum msPAF: 73 %), aquatic plants (61 %), and arthropods (25 %) and low risk to fish (0.2 %) from pesticide mixtures. The pesticides posing the highest risks according to msPAF and that should be substituted with less toxic substances were the herbicides ametryn, diuron, the insecticides carbaryl, chlorpyrifos, diazinon, ethoprophos, and the fungicide difenoconazole. Ecological risks were highest near the plantations and decreased progressively further downstream. The risk to fish was found to be relatively low in these models, but water samples were not collected during fish kill events and some highly toxic pesticides known to be used were not analyzed for in this study. Further sampling and analysis of water samples is needed to determine toxicity risks to fish during peaks of pesticide mixture concentrations. The msPAF model, which estimates the ecological risks of mixtures based on their toxic modes of action, was found to be the most suitable model to assess toxicity risks to aquatic organisms in the RMD. The PERPEST model was found to be a strong tool for screening risk assessments. The SSD approach is useful in deriving water quality criteria for specific pesticides. This study, through the application of three ERA models, clearly shows that pesticides used in plantations within the RMD watershed are expected to have severe adverse effects on most groups of aquatic organisms and that actions are urgently needed to reduce pesticide pollution in this high biodiversity ecosystem.
Abstract-Roskilde University (Denmark) hosted a November 2015 workshop, Environmental Risk-Assessing and Managing Multiple Risks in a Changing World. This Focus article presents the consensus recommendations of 30 attendees from 9 countries regarding implementation of a common currency (ecosystem services) for holistic environmental risk assessment and management; improvements to risk assessment and management in a complex, human-modified, and changing world; appropriate development of protection goals in a 2-stage process; dealing with societal issues; risk-management information needs; conducting risk assessment of risk management; and development of adaptive and flexible regulatory systems. The authors encourage both cross-disciplinary and interdisciplinary approaches to address their 10 recommendations: 1) adopt ecosystem services as a common currency for risk assessment and management; 2) consider cumulative stressors (chemical and nonchemical) and determine which dominate to best manage and restore ecosystem services; 3) fully integrate risk managers and communities of interest into the risk-assessment process; 4) fully integrate risk assessors and communities of interest into the riskmanagement process; 5) consider socioeconomics and increased transparency in both risk assessment and risk management; 6) recognize the ethical rights of humans and ecosystems to an adequate level of protection; 7) determine relevant reference conditions and the proper ecological context for assessments in human-modified systems; 8) assess risks and benefits to humans and the ecosystem and consider unintended consequences of management actions; 9) avoid excessive conservatism or In This Issue: ET&C FOCUSFocus articles are part of a regular series intended to sharpen understanding of current and emerging topics of interest to the scientific community.
Costa Rica is a tropical country with one of the highest biodiversity on Earth. It also has an intensive agriculture, and pesticide runoff from banana and pineapple plantations may cause a high toxicity risk to non-target species in rivers downstream the plantations. We performed a first tier risk assessment of the maximum measured concentrations of 32 pesticides detected over 4 years in the River Madre de Dios (RMD) and its coastal lagoon on the Caribbean coast of Costa Rica. Species sensitivity distributions (SSDs) were plotted in order to derive HC values for each pesticide, i.e., hazard concentrations for 5 % of the species, often used as environmental criteria values in other countries. We also carried out toxicity tests for selected pesticides with native Costa Rican species in order to calculate risk coefficients according to national guidelines in Costa Rica. The concentrations of herbicides diuron and ametryn and insecticides carbofuran, diazinon, and ethoprophos exceeded either the HC value or the lower limit of its 90 % confidence interval suggesting toxic risks above accepted levels. Risk coefficients of diuron and carbofuran derived using local guidelines indicate toxicity risks as well. The assessed fungicides did not present acute toxic risks according to our analysis. Overall, these results show a possible toxicity of detected pesticides to aquatic organisms and provide a comparison of Costa Rican national guidelines with more refined methods for risk assessment based on SSDs. Further higher tier risk assessments of pesticides in this watershed are also necessary in order to consider pesticide water concentrations over time, toxicity from pesticide mixtures, and eventual effects on ecosystem functions.
Growth of human populations and increased human activity, particularly in coastal areas, increase pressure on coastal ecosystems and the ecosystem services (ES) they provide. As a means toward being able to assess the impact of multiple stressors on ES, in the present study we propose an 8‐step conceptual approach for assessing effects of chemical mixtures and other stressors on ES in coastal areas: step A, identify the relevant problems and policy aims; step B, identify temporal and spatial boundaries; step C, identify relevant ES; step D, identify relevant stressors (e.g., chemicals); step E, translate impacts into ES units; step F, assess cumulative risk in ES units; step G, rank stressors based on their contribution to adverse effects on ES; and step H, implement regulation and management as appropriate and necessary. Two illustrative case studies (Swedish coastal waters and a coastal lagoon in Costa Rica) are provided; one focuses on chemicals that affect human food supply and the other addresses pesticide runoff and trade‐offs among ES. The 2 cases are used to highlight challenges of such risk assessments, including use of standardized versus ES‐relevant test species, data completeness, and trade‐offs among ES. Lessons learned from the 2 case studies are discussed in relation to environmental risk assessment and management of chemical mixtures. Integr Environ Assess Manag 2017;13:376–386. © 2016 SETAC
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2025 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.