{"id":"177e2331-17a6-49c6-9825-f6af3d6ccef3","uri":"https://data.inms.international/id/177e2331-17a6-49c6-9825-f6af3d6ccef3","type":"model","title":"IMAGE-GLOBIO terrestrial","description":"GLOBIO uses all biophysical information from IMAGE, such as climate, vegetation, agricultural land use, and it uses soil information. Atmospheric deposition is from an ensemble of chemistry transport models","metadataDate":"2024-11-04T09:32:44","resourceIdentifiers":[{"code":"https://catalogue.ceh.ac.uk/id/31f92f89-9c1b-475f-9b04-303020907bbf"},{"code":"https://data.inms.international/id/177e2331-17a6-49c6-9825-f6af3d6ccef3"}],"keywords":[{"value":"Impact Model","uri":"blah blah"},{"value":"Global","uri":"http://vocabs.ceh.ac.uk/inms/scale/global"},{"value":"Biodiversity","uri":"http://vocabs.ceh.ac.uk/inms/topic/biodiversity"},{"value":"Agricultural Practices","uri":"http://vocabs.ceh.ac.uk/inms/topic/agricultural-practices"},{"value":"INMS","uri":"http://vocabs.ceh.ac.uk/inms/project/inms"}],"primaryPurpose":"GLOBIO-Terrestrial  is a spatially explicit model to simulate the impacts of socio-economic drivers on the physical environment, such as climate change, land-use change and pollution, and these are input to the GLOBIO model to evaluate their impacts on biodiversity in terrestrial and aquatic ecosystems at the global scale\n\nIMAGE is especially designed for scenario analysis. GLOBIO-Terrestrial has been used to analyze the impacts of many changes, examples of those relevant to nitrogen including changes in agricultural intensity (livestock, crops), production of biofuels human consumption and dietary changes.","modelCalibration":"GLOBIO builds on data from literature reviews to construct relationships between biodiversity metrics (MSA) and environmental factors, such as land use, climate, and infrastructure. These are mainly local data on a large variety of ecosystems. Although systematically reviewed, representativeness is not guaranteed and bias may occur towards well-studied species groups, such as birds, and biodiversity-rich regions, such as tropical forests.","spatialDomain":"Global","spatialResolution":"0.5 by 0.5 degree and 5 by 5 minutes","temporalResolutionMin":"1 year","inputVariables":[{"title":"The drivers of biodiversity loss considered are land-cover change, land-use intensity, fragmentation, climate change, atmospheric nitrogen deposition and infrastructural development."}],"outputVariables":[{"title":"Mean species abundance (MSA), reflecting the degree to which the ecosystem is intact,  and Species Richness Index (SRI), which combines MSA estimates and species area relationships"}],"onlineResources":[{"url":"http://themasites.pbl.nl/models/image","function":"website","type":"OTHER"}],"responsibleParties":[{"role":"owner","email":"arthur.beusen@pbl.nl"}]}