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AbstractThis study provides with evidence of the presence of sea surface microplastics in a UNESCO marine biosphere reserve: the island of Menorca in the north-western Mediterranean Sea. From a total of 90 samples, in 100% of the samples, microplastics were observed with a mean value of 0.18 ± 0.01 items/m2. According to data, no significant differences were observed for sampling period with very similar values between 2021 (0.17 ± 0.02 items/m2) and 2022 (0.18 ± 0.02 items/m2). However, significant differences were observed regarding sampling area (both site and locality) suggesting that sea surface plastics in the study area might be more dependent of the spatial scale rather than on the temporal scale. Fibre type microplastics predominated over fragments, films, pellets, and foams, but in the commercial Port de Maó, almost 50% of the identified items were foams which could be related to the transportation of packed goods to this port. Results from the model applied to study the relation between waste management indicators and microplastic abundance indicate that when considering all marine litter categories, the explanatory variables are plastic waste generated by residents population (tonnes/year/km2) and waste collection rate (%), whereas if only plastics are considered, the indicator regarding waste per capita (kg/hab/year) is also included. Data in this study is obtained through a harmonized protocol which can be used to define baseline and threshold values to evaluate good environmental status regarding descriptor 10 of the Marine Strategy Framework Directive.

Este artículo contiene 18 páginas, 5 figuras, 3 tablas ; Species distribution models (SDMs) have been used to predict potential distributions of habitats and to model the effects of environmental changes. Despite their usefulness, currently there is no standardized sampling strategy that provides suitable and sufficiently representative predictive models for littoral marine benthic habitats. Here we aim to establish the best performing and most cost-effective sample design to predict the distribution of littoral habitats in unexplored areas. We also study how environmental variability, sample size, and habitat prevalence may influence the accuracy and performance of spatial predictions. For first time, a large database of littoral habitats (16,098 points over 562,895 km of coastline) is used to build up, evaluate, and validate logistic predictive models according to a variety of sampling strategies. A regularly interspaced strategy with a sample of 20% of the coastline provided the best compromise between usefulness (in terms of sampling cost and effort) and accuracy. However, model performance was strongly depen upon habitat characteristics. The proposed sampling strategy may help to predict the presence or absence of target species or habitats thus improving extensive cartographies, detect high biodiversity areas, and, lastly, develop (the best) environmental management plans, especially in littoral environments. ; This study was supported by INTRAMURAL CSIC (0065) and the European Union's Horizon 2020 (689518) MERCES. ; Peer reviewed