Terrestrial biodiversity
{{ComponentTemplate2 |InputVar=Management intensity crops; Management intensity livestock; Nitrogen deposition - grid; Global mean temperature; Protected area - grid; |Parameter=Species-area relationships; Road-map - grid; Nitrogen critical load; Biome and eco-region - grid; MSA effect values; High resolution land cover (GLC2000) - grid; |OutputVar=Wilderness area - grid; MSA (mean species abundance) - grid; SRI (species richness index) - grid; Land use and land-use intensity - grid; |Description=Biodiversity is declining rapidly with consequences for human well-being and ultimately even for the existence of humankind (MA, 2005). The Conference of Parties to the Convention on Biological Diversity (CBD) formulated the long-term vision: ‘By 2050, biodiversity is valued, conserved, restored and wisely used, maintaining ecosystem services, sustaining a healthy planet and delivering benefits essential for all people’. For the period up to 2020, five strategic goals comprising 20 biodiversity targets have been adopted, referred to as the Aichi targets (sCBD, 2010).
IMAGE assesses 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. GLOBIO was developed to provide information to policymakers at international level on current and future biodiversity, (Alkemade et al., 2009). The model delivers quantified results on the impact of environmental drivers and potential policy options on biodiversity. Potential trends in biodiversity are addressed in future scenarios, including the expected outcome in the absence of additional policies to prevent biodiversity loss.
GLOBIO builds on a series of cause–effect relationships between environmental drivers and biodiversity, based on state-of-the-art knowledge.
The key measure of biodiversity in GLOBIO is the mean abundance of original species relative to their abundance in undisturbed ecosystems. Referred to as the mean species abundance (MSA), this measure reflects the degree to which the ecosystem is intact and is similar to the Biodiversity Intactness Index (Scholes and Biggs, 2005). New methods combine <abbr title="<ul><li>The part "estimates and species area relationships to estimate species loss at different geographical levels (" of the query was not understood.Results might not be as expected.</li> <!--br--><li>The part ";" of the query was not understood.Results might not be as expected.</li> <!--br--><li>The part "). The resulting Species Richness Index (SRI) is calculated as one of the end points of GLOBIO. The current version of SRI only covers vertebrate species. In addition, natural areas with high MSA values, defined as wilderness areas, are identified by their extent, landcover type and regional spread. The drivers of biodiversity loss considered are land-cover change, land-use intensity, fragmentation, climate change, atmospheric nitrogen deposition and infrastructural development." of the query was not understood.Results might not be as expected.</li> <!--br--><li>The part "]]" of the query was not understood.Results might not be as expected.</li></ul>">MSA]] estimates and species area relationships to estimate species loss at different geographical levels (Faith et al., 2008; Musters et al., submitted). The resulting Species Richness Index (SRI) is calculated as one of the end points of GLOBIO. The current version of SRI only covers vertebrate species. In addition, natural areas with high MSA values, defined as wilderness areas, are identified by their extent, landcover type and regional spread. The drivers of biodiversity loss considered are land-cover change, land-use intensity, fragmentation, climate change, atmospheric nitrogen deposition and infrastructural development.
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