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The rise of “fast fashion” has driven up the production of low-cost, short-lived clothing, significantly increasing global textile fiber production and, consequently, exacerbating environmental pollution. This study investigated the ecotoxicological effects of different types of anthropogenic microfibers—cotton, polyester, and mixed fibers (50% cotton: 50% polyester)—on marine organisms, specifically sea urchin embryos. All tested fibers exhibited toxicity, with cotton fibers causing notable effects on embryonic development even at environmentally relevant concentrations. The research also simulated a scenario where microfibers were immersed in seawater for 30 days to assess changes in toxicity over time. The results showed that the toxicity of microfibers increased with both concentration and exposure duration, with polyester being the most toxic among the fibers tested. Although synthetic fibers have been the primary focus of previous research, this study highlights that natural fibers like cotton, which are often overlooked, can also be toxic due to the presence of harmful additives. These natural fibers, despite decomposing faster than synthetic ones, can persist in aquatic environments for extended periods. The findings underline the critical need for further research on both natural and synthetic microfibers to understand their environmental impact and potential threats to marine ecosystems and sea urchin populations.

In this work, multivariate and numeric methods were used to integrate the chemical and ecotoxicological data obtained for the sediments from the Santos Estuarine System, and for the vicinity of the discharges of the Submarine Sewage Outfall of Santos, in order to establish more accurately the environmental risks, identify the priority areas and thus provide guidance to control the programs and public policies. For both the datasets, the concentrations which exceeded numeric sediment guidelines tended to be associated to toxicity. For the estuary, this trend was corroborated by the correlations between the toxicity and Cu and PAHs levels, whereas for the sewage outfall region, this was observed through the correlation between the toxicity and Hg contents. Ratio-to-mean values were calculated for each sample, in order to rank them according to the toxicity and contamination. Cluster analyses confirmed the ranking results. For the estuary, three categories of sediments were established: stations SSV-2, SSV-3 and SSV-4 were under major risks, followed by SSV-6. Stations SSV-1 and SSV-5 were not altered. Concerning to the sewage outfall, stations 1 and 2 presented better quality, whereas station 5 seemed to be under risk, followed by stations 3 and 4, which exhibited some signs of alteration.O presente trabalho utilizou métodos multivariados e matemáticos para integrar dados químicos e ecotoxicológicos obtidos para o Sistema Estuarino de Santos e para a região próxima à zona de lançamento do emissário submarino de Santos, com a finalidade de estabelecer com maior exatidão os riscos ambientais, e assim identificar áreas prioritárias e orientar programas de controle e políticas públicas. Para ambos os conjuntos de dados, as violações de valores numéricos de qualidade de sedimento tenderam a estar associadas com a ocorrência de toxicidade. Para o estuário, essa tendência foi corroborada pelas correlações entre a toxicidade e as concentrações de HPAs e Cu, enquanto para a região do emissário, pela correlação entre toxicidade e conteúdo de mercúrio no sedimento. Valores normalizados em relação às medias foram calculados para cada amostra, permitindo classificá-las de acordo com a toxicidade e a contaminação. As análises de agrupamento confirmaram os resultados das classificações. Para os dados de sistema estuarino, houve a separação das amostras em três categorias: as estações SSV-2, SSV-3 e SSV-4 encontram-se sob maior risco, seguidas da estação SSV-6. As estações SSV-1 e SSV-5 demonstraram melhores condições. Já em relação ao emissário, as amostras 1 e 2 apresentaram melhores condições, enquanto a estação 5 pareceu apresentar um maior risco, seguida das estações 3 e 4 que tiveram apenas alguns indícios de alteração.

This study illustrate the use of indicators and models to support the Ecosystem Approach to Fisheries and Aquaculture management using two case studies in Chile: prediction of environmental variability effects upon anchovy (Engraulis ringens) fishery of northern Chile and prediction of suitable sites and carrying capacity of Pacific oyster (Crassostrea gigas) culture using FARM and geographic information system (GIS) models in the Valdivia estuary. A three stage approach was applied: Stage 1 considers spatiotemporal ecosystem indicators (fisheries, aquaculture, environmental, and regulatory), Stage 2 uses statistical relationships between indicators, GIS, and other simulation models (e.g., artificial neural networks and FARM) of environment-resources interaction, and Stage 3 is the analysis and validation of models outputs. The methodology illustrates how indicators and models may be used to assist decision-makers in developing an ecosystem approach to fisheries and aquaculture. The application of these approaches provides an integrative methodology for abundance prediction of anchovy and site selection for shellfish aquaculture, despite limitations in the available data.Este trabajo muestra el uso de indicadores y modelos para apoyar la aplicación del enfoque ecosistémico en la gestión de la pesca y la acuicultura, mediante dos casos de estudios en Chile: predicción de los efectos de la variabilidad ambiental en la pesquería de anchoveta (Engraulis ringens) en la zona norte de Chile y la predicción de sitios aptos y capacidad de carga para el cultivo de la ostra del Pacífico (Crassostrea gigas) en el estuario de Valdivia. Se aplicó un enfoque metodológico de tres etapas: etapa 1 considera indicadores espacio-temporales del ecosistema (pesca, acuicultura, medio ambiente y legislación); etapa 2 utiliza relaciones estadísticas entre los indicadores, funciones de SIG (Sistemas de Información Geográfica), y otros modelos de simulación (Redes Neuronales Artificiales y Capacidad de Carga) de interacciones entre el ambiente y los recursos; y etapa 3 es el análisis y validación de los resultados de los modelos. La metodología y resultados ilustran cómo los indicadores y modelos pueden ser utilizados para ayudar a los tomadores de decisiones en el desarrollo de un enfoque ecosistémico en pesca y acuicultura. La aplicación de estos enfoques ofrece una metodología integradora para la predicción de la abundancia de la anchoveta y la selección de sitios para el cultivo de moluscos, a pesar de las limitaciones de los datos disponibles.