Biodiversity
The GLOBIO3 model calculates the global biodiversity indicated by the surface area of natural ecosystems and the mean species abundance (MSA).
Model descriptionThe GLOBIO 3 model framework describes biodiversity by means of estimating remaining mean species abundance of original species relative to their abundance in primary vegetation. This measure of mean species abundance (MSA) is similar to the Biodiversity Integrity Index (Majer and Beeston, 1996) and the Biodiversity Intactness Index (Scholes and Biggs, 2005) and can be considered as a proxy for CBD indicators (UNEP, 2004). The core of GLOBIO 3 is a set of regression equations describing the impact on biodiversity of the degree of pressure using dose–response relationships. These dose–response relationships are derived from a database of observations of species response to change. The database includes separate measures of MSA, each in relation to different degrees of pressure exerted by various pressure factors or driving forces. The entries in the database are all derived from studies in peer-reviewed literature, reporting either on change through time in a single plot, or on response in parallel plots undergoing different pressures. The current version of the database includes data from about 500 reports: about 140 reports on the relationship between species abundance and land cover or land use, 50 on atmospheric N deposition (Bobbink, 2004), over 300 on impacts of infrastructure (UNEP, 2001) and several literature reports on minimal area requirements of species. Dose–response relationships for climate change are based on model studies (Bakkenes et al., 2002; Leemans and Eickhout, 2004). Many studies address the effects of human pressure on global biodiversity and distinguish various indirect and direct drivers or pressure factors. A direct driver unequivocally influences ecosystem processes and can therefore be identified and measured with varying degrees of accuracy. Main categories of direct drivers are changes in land cover and land use, species introduction and removal, and external inputs such as fertilizer use, pest control or irrigation water (Millennium Assessment, 2003). An indirect driver operates more diffusely, often by altering one or more direct drivers. Major indirect drivers include demographic, economic and socio-political circumstances as well as scientific and technologal and cultural factors. The driving forces (pressures) considered by GLOBIO 3 include land-cover change (taken from IMAGE), land-use intensity (taken partly from IMAGE), atmospheric nitrogen (N) deposition, infrastructure development (as applied in GLOBIO 2), fragmentation and climate change (both taken from IMAGE). The GLOBIO 3 model calculates the overall MSA value by multiplying the MSA values for each driver for each IMAGE 0.5 by 0.5 degree grid cell according to:
where i is the index for the grid-cell, MSAXi the relative mean species abundance corresponding to the drivers LU (land-cover/use), N (atmospheric N deposition), I (infrastructural development), F (fragmentation) and CC (climate change). MSALUi is the area-weighted mean over all land-use categories within a grid cell. The figure below shows the overall MSA for the world for the year 2000. Indirect drivers, such as human population density and energy use, are not used explicitly in the GLOBIO 3 framework, but have an impact on biodiversity through their influence on other –direct – drivers. For example, changes in the direct drivers (land use, climate, atmospheric N deposition and forestry) due to changing demography and socio-economic developments are calculated with IMAGE. Changes in infrastructure are calculated with the GLOBIO 2 model (UNEP, 2001).
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