Motivation: The intrinsic characteristics of islands make them a unique study system for the investigation of ecological and evolutionary dynamics. The Mediterranean Basin, an island-rich biodiversity hotspot, still lacks a comprehensive spatial database for these geographic features. This study presents the first comprehensive spatial database of all Mediterranean islands larger than 0.01 km(2), aiding ecological investigations and interdisciplinary research. Main types of variable contained: The MEDIS spatial database offers detailed information on 39 geographic, climatic, ecological and land-use variables, including island area, perimeter, isolation metrics, climatic space, terrain data, land cover, palaeogeography, road networks and geological information, providing a multifaceted view of each island's characteristics. Spatial location and grain: The study encompasses 2217 islands in the Mediterranean Basin larger than 0.01 km(2). The spatial grain of the datasets on which the selected variables are based varies from 10 m (ESA WorldCover) to 1 km (CHELSA-BIOCLIM+). Time period and grain: The spatial database incorporates data from various sources, each with its own timeframe, such as the Global Shoreline Vector from 2014 Landsat imagery and the WorldCover dataset from 2021. Historical data like the Paleocoastlines GIS dataset offer insights into island configurations during the Last Glacial Maximum. Major taxa and level of measurement: While not focusing on specific taxa, the study lays the foundation for comprehensive research on Mediterranean islands, facilitating comparisons and investigations into the distribution of native, endemic or alien species. The level of measurement is extensive, encompassing a wide range of variables and providing polygonal features rather than centroids' coordinates.

MEDIS—A comprehensive spatial database on Mediterranean islands for biogeographical and evolutionary research

Bacchetta, Gianluigi;Fois, Mauro;
2024-01-01

Abstract

Motivation: The intrinsic characteristics of islands make them a unique study system for the investigation of ecological and evolutionary dynamics. The Mediterranean Basin, an island-rich biodiversity hotspot, still lacks a comprehensive spatial database for these geographic features. This study presents the first comprehensive spatial database of all Mediterranean islands larger than 0.01 km(2), aiding ecological investigations and interdisciplinary research. Main types of variable contained: The MEDIS spatial database offers detailed information on 39 geographic, climatic, ecological and land-use variables, including island area, perimeter, isolation metrics, climatic space, terrain data, land cover, palaeogeography, road networks and geological information, providing a multifaceted view of each island's characteristics. Spatial location and grain: The study encompasses 2217 islands in the Mediterranean Basin larger than 0.01 km(2). The spatial grain of the datasets on which the selected variables are based varies from 10 m (ESA WorldCover) to 1 km (CHELSA-BIOCLIM+). Time period and grain: The spatial database incorporates data from various sources, each with its own timeframe, such as the Global Shoreline Vector from 2014 Landsat imagery and the WorldCover dataset from 2021. Historical data like the Paleocoastlines GIS dataset offer insights into island configurations during the Last Glacial Maximum. Major taxa and level of measurement: While not focusing on specific taxa, the study lays the foundation for comprehensive research on Mediterranean islands, facilitating comparisons and investigations into the distribution of native, endemic or alien species. The level of measurement is extensive, encompassing a wide range of variables and providing polygonal features rather than centroids' coordinates.
2024
spatial database
biodiversity hotspot
biogeography
conservation biology
ecological dynamics
endemism
evolutionary research
GeoJSON
island ecology
Mediterranean islands
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11584/402043
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