Medbiolitter database summarises results of scientific studies on biodiversity and marine litter interactions in the Mediterranean Sea. To this end, information is collected from different data sources, such as institutions or projects, as well as peer-reviewed publications. The main source of data currently is LITTERBASE/AWI, including only the coverage within the Mediterranean. Several spatial and data corrections were made from the previous version (v.3, Sep 2019). The database currently comprises 568 records on interactions. Interaction refers to encounters between wildlife and litter items and are classified in four categories: 1) Ingestion, which is the most frequently observed interaction, followed by 2) entanglement, which affects motility, often with fatal consequences, 3) colonization, which occurs when many species settle on floating litter, and 4) others, including different types of less frequent interaction. The database includes among others the location, the type of interaction and litter, marine realm (beach, sea surface, water column, seafloor), habitat, species, whether it occurs in a marine protected area and the type in such case, as well as references to the publication from which the data are extracted. The layer is represented in different ways in the MED Biodiversity platform: 1) Marine litter and biodiversity interactions: it shows the database by type of interaction (ingestion, entanglement, colonization and other) and marine realm (pelagic or benthic). 2) Knowledge update: changes in the number of records in each database version. It tries to represent the efforts of the PANACeA project to gather additional information on the Mediterranean Sea. 3) Marine litter knowledge from 1988 to present date: shows the years of publication of the source of the records in the database. In recent dates, especially since 2015, there has been a notable increase in the number of publications related to marine litter.

Medbiolitter database summarises results of scientific studies on biodiversity and marine litter interactions in the Mediterranean Sea. To this end, information is collected from different data sources, such as institutions or projects, as well as peer-reviewed publications. One of the main sources of data is LITTERBASE/AWI, only including the coverage within the Mediterranean Sea. The database currently comprises 1466 records on interactions. Interaction refers to encounters between wildlife and litter items and are classified in four categories: 1) Ingestion, which is the most frequently observed interaction, followed by 2) entanglement, which affects motility, often with fatal consequences, 3) colonization, which occurs when many species settle on floating litter, and 4) others, including different types of less frequent interaction. The database includes among others the location, the type of interaction and litter, marine realm (beach, sea surface, water column, seafloor), habitat, species, whether it occurs in a marine protected area and the type in such case, as well as references to the publication from which the data are extracted.

Data represents the percentage of change in the intensity of sailing vessels and pleasure craft traffic in the Mediterranean Sea between years 2019 and 2022. The map is based on AIS data aggregated at 1km2 by EMODnet and expressed as total time with presence of vessels in each cell throughout the year.

The dataset of The MED cooperation area NUTS3 regions as points is produced in the framework of DestiMED PLUS. DestiMED PLUS Project builds on the successes of MEET and DestiMED projects and aims to improve levels of integration between regional tourism and conservation policies in the protected areas of 9 Mediterranean Regions through the creation of ecotourism itineraries which are developed using a collaborative approach, both locally and regionally to develop ecotourism.

Vulnerability is calculated based on the percentage of Key Biodiversity Areas (KBAs) and the cumulative tourism pressure in each region. Percentage of KBAs not protected, with respect to the region, are classified into five groups, from very low to very high, according to the following thresholds: lower than 10%, 10 to 17%, 17 to 30%, 30 to 50% and higher than 50%. Theses classes and those of cumulative pressure are combined into a weighted sum and then reclassified in five vulnerability categories, from very low to very high.

Data shows the change in number of nights spent at tourist accommodation establishments by NUTS 2 coastal regions between year 2019 and 2022. No data available for non European Union areas. Coastal regions in these countries are shown on the map to highlight them.

Data shows the number of nights spent at tourist accommodation establishments per km2 in Mediterranean countries. Estimation made from a disaggregation of data at NUTS2 based on the distribution of accommodation sites available in OpenStreetMap.

Vulnerability is calculated based on the coverage of protected areas (PAs) and Important Areas for Biodiversity (IABs) and the cumulative tourism pressure in the Mediterranean Sea waters. PAs and IABs coverage is reclassified in scores, 1 and 2 respectively. These classes and those of cumulative pressure are combined in and reclassified into vulnerability classes according to a vulnerability matrix. IABs include: Key Biodiversity Areas (KBAs), Important Shark and Ray Areas (ISRAs), Important Marine Mammal Areas (IMMAs), Critical areas for the orca population of the Gibraltar Strait and Gulf of Cádiz, Biosphere Reserve, Cetaceans Critical Habitat, Ecologically or Biologically Significant Marine Areas (EBSAs), Particularly Sensitive Sea Areas (PSSAs), Proposed Sites of Community Importance, and World Heritage Sites.

Data represents the number of moorings in marina ports per kilometre of coastline for each NUTS3 or equivalent (e.g. province) region. The total number of moorings was obtained from the data compiled by ETC-UMA on the location and capacity of the marinas, assigning each port its corresponding NUTS3 code and counting the total number of moorings. This value was divided by the length of the region's coastline in km. Results show low to high intensive capacity for this activity by region.

Data showing the distibution of tourism hotspots based on the location of accomodation and attractions sites available in OpenStreetMap counted per km2. Areas without data cannot be interpreted as an absence of tourism activities, but as unmapped areas.