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Showing results for: [ Storey, Randal ]
These data provide consistent rasterised layers of edaphic (physical and chemical conditions of the soil) and land surface physiography (landform and geomorphology) variables hypothesised to explain s... morepatial patterns in biological diversity at continental scales for immediate use with statistical modelling tools. These data are intended to be used along with a similarly compiled and spatially standardised set of climatic layers. Consistent "stacks" of raster variables are needed for spatially-explicit biodiversity modelling using tools such as MAXENT or Generalised Dissimilarity Modelling (GDM). Full details of each dataset, with a list of data sources and bibliography, are provided in a table as part of the data collection. Additional information provided with the 1km gridded raster is relevant to some these data and provided here also. Each dataset will need to be separately cited. These data have also been made available for use in the Atlas of Living Australia's Spatial Portal. less
Closed DIISR ALA Exp-Geosptl Data Mngmnt - - Published 21 Oct 2019
These data provide rasterised layers of edaphic (physical and chemical conditions of the soil) and land surface physiography (landform and geomorphology) attributes hypothesised to explain spatial pat... moreterns in biological diversity at continental scales for immediate use with statistical modelling tools. These data are intended to be used along with a similarly compiled and spatially standardised set of climatic layers (See " 0.01 degree stack of climate layers for continental analysis of biodiversity pattern: version 1.0 " in related materials).NOTE: Full details of the data, with a list of data sources and bibliography, are provided in a PDF file included as part of the data collection.less
Closed DEWHA Harness Cntnnt-wide Bdvrsty - Spatial Environmental Data Preparation - Published 11 Dec 2018
Refugial potential index for Amphibians as a function of climate change based on Generalised Dissimilarity Modelling (GDM) of compositional turnover. This metric represents a relative measure of the ... morepotential of each grid cell to act as a climate change refugia for the local (100km radius) area, taking the representation of current ecological environments by the future state of the cell, and the area of similar ecological environments in the future into account. This metric was developed along with others for use in an assessment of the efficacy of the protected area system for biodiversity under climate change at continental and global scales, presented at the IUCN World Parks Congress 2014. It is described in the AdaptNRM Guide “Helping Biodiversity Adapt: Supporting climate adaptation planning using a community-level modelling approach”, available online at: www.adaptnrm.org. Data are provided in two forms: 1. Zipped ESRI float grids: Binary float grids (*.flt) with associated ESRI header files (*.hdr) and projection files (*.prj). After extracting from the zip archive, these files can be imported into most GIS software packages, and can be used as other binary file formats by substituting the appropriate header file. 2. ArcGIS layer package (*.lpk): These packages contain can be unpacked by ArcGIS as a raster with associated legend. Additionally a short methods summary is provided in the file BiodiversityModellingMethodsSummary.pdf for further information. Layers in this 9s series use a consistent naming convention: BIOLOGICAL GROUP _ FROM BASE_ TO SCENARIO_ ANALYSIS e.g. A_90_CAN85_S or R_90_MIR85_L where BIOLOGICAL GROUP is A: amphibians, M: mammals, R: reptiles and V: vascular plantsless
1173.3 Strat: WPC Global Prot Area Ass - Biodiversity Adaptation Analyses - Published 24 Jun 2015
Refugial potential index for Reptiles as a function of climate change based on Generalised Dissimilarity Modelling (GDM) of compositional turnover. This metric represents a relative measure of the po... moretential of each grid cell to act as a climate change refugia for the local (100km radius) area, taking the representation of current ecological environments by the future state of the cell, and the area of similar ecological environments in the future into account. This metric was developed along with others for use in an assessment of the efficacy of the protected area system for biodiversity under climate change at continental and global scales, presented at the IUCN World Parks Congress 2014. It is described in the AdaptNRM Guide “Helping Biodiversity Adapt: Supporting climate adaptation planning using a community-level modelling approach”, available online at: www.adaptnrm.org. Data are provided in two forms: 1. Zipped ESRI float grids: Binary float grids (*.flt) with associated ESRI header files (*.hdr) and projection files (*.prj). After extracting from the zip archive, these files can be imported into most GIS software packages, and can be used as other binary file formats by substituting the appropriate header file. 2. ArcGIS layer package (*.lpk): These packages contain can be unpacked by ArcGIS as a raster with associated legend. Additionally a short methods summary is provided in the file BiodiversityModellingMethodsSummary.pdf for further information. Layers in this 9s series use a consistent naming convention: BIOLOGICAL GROUP _ FROM BASE_ TO SCENARIO_ ANALYSIS e.g. A_90_CAN85_S or R_90_MIR85_L where BIOLOGICAL GROUP is A: amphibians, M: mammals, R: reptiles and V: vascular plantsless
Refugial potential index for Mammals as a function of climate change based on Generalised Dissimilarity Modelling (GDM) of compositional turnover. This metric represents a relative measure of the pot... moreential of each grid cell to act as a climate change refugia for the local (100km radius) area, taking the representation of current ecological environments by the future state of the cell, and the area of similar ecological environments in the future into account. This metric was developed along with others for use in an assessment of the efficacy of the protected area system for biodiversity under climate change at continental and global scales, presented at the IUCN World Parks Congress 2014. It is described in the AdaptNRM Guide “Helping Biodiversity Adapt: Supporting climate adaptation planning using a community-level modelling approach”, available online at: www.adaptnrm.org. Data are provided in two forms: 1. Zipped ESRI float grids: Binary float grids (*.flt) with associated ESRI header files (*.hdr) and projection files (*.prj). After extracting from the zip archive, these files can be imported into most GIS software packages, and can be used as other binary file formats by substituting the appropriate header file. 2. ArcGIS layer package (*.lpk): These packages contain can be unpacked by ArcGIS as a raster with associated legend. Additionally a short methods summary is provided in the file BiodiversityModellingMethodsSummary.pdf for further information. Layers in this 9s series use a consistent naming convention: BIOLOGICAL GROUP _ FROM BASE_ TO SCENARIO_ ANALYSIS e.g. A_90_CAN85_S or R_90_MIR85_L where BIOLOGICAL GROUP is A: amphibians, M: mammals, R: reptiles and V: vascular plantsless
Benefits of revegetation index for Mammals as a function of land clearing within the present long term (30 year average) climate (1990 centred) based on Generalised Dissimilarity Modelling (GDM) of c... moreompositional turnover. This metric represents the marginal benefit from a unit increase of vegetation at the site, which is a direct function of the slope of the species area curve at the test state of the site. In practice, revegetation of the whole cell is likely to be impractical due to the availability of cleared land within the cell, and practical limitations such as land ownership and revegetation cost. The metric therefore excludes these factors from the analysis, allowing direct comparison of the relative benefit of a given area of revegetation between cells. The values of the index generated according to the above formula are generally low (since a significant area is required to support additional species) and the index is rescaled by multiplying by 1000 to bring it into an approximate 0-1 range. This metric was developed along with others for use in an assessment of the efficacy of the protected area system for biodiversity under climate change at continental and global scales, presented at the IUCN World Parks Congress 2014. It is described in the AdaptNRM Guide “Helping Biodiversity Adapt: Supporting climate adaptation planning using a community-level modelling approach”, available online at: www.adaptnrm.org. Data are provided in two forms: 1. Zipped ESRI float grids: Binary float grids (*.flt) with associated ESRI header files (*.hdr) and projection files (*.prj). After extracting from the zip archive, these files can be imported into most GIS software packages, and can be used as other binary file formats by substituting the appropriate header file. 2. ArcGIS layer package (*.lpk): These packages contain can be unpacked by ArcGIS as a raster with associated legend. Additionally a short methods summary is provided in the file BiodiversityModellingMethodsSummary.pdf for further information. Layers in this 9s series use a consistent naming convention: BIOLOGICAL GROUP _ FROM BASE_ TO SCENARIO_ ANALYSIS e.g. A_90_CAN85_S or R_90_MIR85_L where BIOLOGICAL GROUP is A: amphibians, M: mammals, R: reptiles and V: vascular plants less
1173.3 Strat: WPC Global Prot Area Ass - Biodiversity Adaptation Analyses - Published 23 Jun 2015
Benefits of revegetation index for Mammals as a function of land clearing and climate change based on Generalised Dissimilarity Modelling (GDM) of compositional turnover. This metric represents the m... morearginal benefit from a unit increase of vegetation at the site, which is a direct function of the slope of the species area curve at the test state of the site. In practice, revegetation of the whole cell is likely to be impractical due to the availability of cleared land within the cell, and practical limitations such as land ownership and revegetation cost. The metric therefore excludes these factors from the analysis, allowing direct comparison of the relative benefit of a given area of revegetation between cells. The values of the index generated according to the above formula are generally low (since a significant area is required to support additional species) and the index is rescaled by multiplying by 1000 to bring it into an approximate 0-1 range. This metric was developed along with others for use in an assessment of the efficacy of the protected area system for biodiversity under climate change at continental and global scales, presented at the IUCN World Parks Congress 2014. It is described in the AdaptNRM Guide “Helping Biodiversity Adapt: Supporting climate adaptation planning using a community-level modelling approach”, available online at: www.adaptnrm.org. Data are provided in two forms: 1. Zipped ESRI float grids: Binary float grids (*.flt) with associated ESRI header files (*.hdr) and projection files (*.prj). After extracting from the zip archive, these files can be imported into most GIS software packages, and can be used as other binary file formats by substituting the appropriate header file. 2. ArcGIS layer package (*.lpk): These packages contain can be unpacked by ArcGIS as a raster with associated legend. Additionally a short methods summary is provided in the file BiodiversityModellingMethodsSummary.pdf for further information. Layers in this 9s series use a consistent naming convention: BIOLOGICAL GROUP _ FROM BASE_ TO SCENARIO_ ANALYSIS e.g. A_90_CAN85_S or R_90_MIR85_L where BIOLOGICAL GROUP is A: amphibians, M: mammals, R: reptiles and V: vascular plants less
Benefits of revegetation index for Vascular Plants as a function of land clearing and changing climate based on Generalised Dissimilarity Modelling (GDM) of compositional turnover. This metric repres... moreents the marginal benefit from a unit increase of vegetation at the site, which is a direct function of the slope of the species area curve at the test state of the site. In practice, revegetation of the whole cell is likely to be impractical due to the availability of cleared land within the cell, and practical limitations such as land ownership and revegetation cost. The metric therefore excludes these factors from the analysis, allowing direct comparison of the relative benefit of a given area of revegetation between cells. The values of the index generated according to the above formula are generally low (since a significant area is required to support additional species) and the index is rescaled by multiplying by 1000 to bring it into an approximate 0-1 range. This metric was developed along with others for use in an assessment of the efficacy of the protected area system for biodiversity under climate change at continental and global scales, presented at the IUCN World Parks Congress 2014. It is described in the AdaptNRM Guide “Helping Biodiversity Adapt: Supporting climate adaptation planning using a community-level modelling approach”, available online at: www.adaptnrm.org. Data are provided in two forms: 1. Zipped ESRI float grids: Binary float grids (*.flt) with associated ESRI header files (*.hdr) and projection files (*.prj). After extracting from the zip archive, these files can be imported into most GIS software packages, and can be used as other binary file formats by substituting the appropriate header file. 2. ArcGIS layer package (*.lpk): These packages contain can be unpacked by ArcGIS as a raster with associated legend. Additionally a short methods summary is provided in the file BiodiversityModellingMethodsSummary.pdf for further information. Layers in this 9s series use a consistent naming convention: BIOLOGICAL GROUP _ FROM BASE_ TO SCENARIO_ ANALYSIS e.g. A_90_CAN85_S or R_90_MIR85_L where BIOLOGICAL GROUP is A: amphibians, M: mammals, R: reptiles and V: vascular plantsless
1173.3 Strat: WPC Global Prot Area Ass - Biodiversity Adaptation Analyses - Published 22 Jun 2015
Benefits of revegetation index for Vascular Plants as a function of land clearing and climate change based on Generalised Dissimilarity Modelling (GDM) of compositional turnover. This metric represen... morets the marginal benefit from a unit increase of vegetation at the site, which is a direct function of the slope of the species area curve at the test state of the site. In practice, revegetation of the whole cell is likely to be impractical due to the availability of cleared land within the cell, and practical limitations such as land ownership and revegetation cost. The metric therefore excludes these factors from the analysis, allowing direct comparison of the relative benefit of a given area of revegetation between cells. The values of the index generated according to the above formula are generally low (since a significant area is required to support additional species) and the index is rescaled by multiplying by 1000 to bring it into an approximate 0-1 range. This metric was developed along with others for use in an assessment of the efficacy of the protected area system for biodiversity under climate change at continental and global scales, presented at the IUCN World Parks Congress 2014. It is described in the AdaptNRM Guide “Helping Biodiversity Adapt: Supporting climate adaptation planning using a community-level modelling approach”, available online at: www.adaptnrm.org. Data are provided in two forms: 1. Zipped ESRI float grids: Binary float grids (*.flt) with associated ESRI header files (*.hdr) and projection files (*.prj). After extracting from the zip archive, these files can be imported into most GIS software packages, and can be used as other binary file formats by substituting the appropriate header file. 2. ArcGIS layer package (*.lpk): These packages contain can be unpacked by ArcGIS as a raster with associated legend. Additionally a short methods summary is provided in the file BiodiversityModellingMethodsSummary.pdf for further information. Layers in this 9s series use a consistent naming convention: BIOLOGICAL GROUP _ FROM BASE_ TO SCENARIO_ ANALYSIS e.g. A_90_CAN85_S or R_90_MIR85_L where BIOLOGICAL GROUP is A: amphibians, M: mammals, R: reptiles and V: vascular plantsless
Benefits of revegetation index for Vascular Plants as a function of land clearing within the present long term (30 year average) climate (1990 centred) based on Generalised Dissimilarity Modelling (G... moreDM) of compositional turnover. This metric represents the marginal benefit from a unit increase of vegetation at the site, which is a direct function of the slope of the species area curve at the test state of the site. In practice, revegetation of the whole cell is likely to be impractical due to the availability of cleared land within the cell, and practical limitations such as land ownership and revegetation cost. The metric therefore excludes these factors from the analysis, allowing direct comparison of the relative benefit of a given area of revegetation between cells. The values of the index generated according to the above formula are generally low (since a significant area is required to support additional species) and the index is rescaled by multiplying by 1000 to bring it into an approximate 0-1 range. This metric was developed along with others for use in an assessment of the efficacy of the protected area system for biodiversity under climate change at continental and global scales, presented at the IUCN World Parks Congress 2014. It is described in the AdaptNRM Guide “Helping Biodiversity Adapt: Supporting climate adaptation planning using a community-level modelling approach”, available online at: www.adaptnrm.org. Data are provided in two forms: 1. Zipped ESRI float grids: Binary float grids (*.flt) with associated ESRI header files (*.hdr) and projection files (*.prj). After extracting from the zip archive, these files can be imported into most GIS software packages, and can be used as other binary file formats by substituting the appropriate header file. 2. ArcGIS layer package (*.lpk): These packages contain can be unpacked by ArcGIS as a raster with associated legend. Additionally a short methods summary is provided in the file BiodiversityModellingMethodsSummary.pdf for further information. Layers in this 9s series use a consistent naming convention: BIOLOGICAL GROUP _ FROM BASE_ TO SCENARIO_ ANALYSIS e.g. A_90_CAN85_S or R_90_MIR85_L where BIOLOGICAL GROUP is A: amphibians, M: mammals, R: reptiles and V: vascular plantsless
Benefits of revegetation index for Reptiles as a function of land clearing within the present long term (30 year average) climate (1990 centred) based on Generalised Dissimilarity Modelling (GDM) of ... morecompositional turnover. This metric represents the marginal benefit from a unit increase of vegetation at the site, which is a direct function of the slope of the species area curve at the test state of the site. In practice, revegetation of the whole cell is likely to be impractical due to the availability of cleared land within the cell, and practical limitations such as land ownership and revegetation cost. The metric therefore excludes these factors from the analysis, allowing direct comparison of the relative benefit of a given area of revegetation between cells. The values of the index generated according to the above formula are generally low (since a significant area is required to support additional species) and the index is rescaled by multiplying by 1000 to bring it into an approximate 0-1 range. This metric was developed along with others for use in an assessment of the efficacy of the protected area system for biodiversity under climate change at continental and global scales, presented at the IUCN World Parks Congress 2014. It is described in the AdaptNRM Guide “Helping Biodiversity Adapt: Supporting climate adaptation planning using a community-level modelling approach”, available online at: www.adaptnrm.org. Data are provided in two forms: 1. Zipped ESRI float grids: Binary float grids (*.flt) with associated ESRI header files (*.hdr) and projection files (*.prj). After extracting from the zip archive, these files can be imported into most GIS software packages, and can be used as other binary file formats by substituting the appropriate header file. 2. ArcGIS layer package (*.lpk): These packages contain can be unpacked by ArcGIS as a raster with associated legend. Additionally a short methods summary is provided in the file BiodiversityModellingMethodsSummary.pdf for further information. Layers in this 9s series use a consistent naming convention: BIOLOGICAL GROUP _ FROM BASE_ TO SCENARIO_ ANALYSIS e.g. A_90_CAN85_S or R_90_MIR85_L where BIOLOGICAL GROUP is A: amphibians, M: mammals, R: reptiles and V: vascular plantsless
Benefits of revegetation index for Reptiles as a function of land clearing and changing climate based on Generalised Dissimilarity Modelling (GDM) of compositional turnover. This metric represents th... moree marginal benefit from a unit increase of vegetation at the site, which is a direct function of the slope of the species area curve at the test state of the site. In practice, revegetation of the whole cell is likely to be impractical due to the availability of cleared land within the cell, and practical limitations such as land ownership and revegetation cost. The metric therefore excludes these factors from the analysis, allowing direct comparison of the relative benefit of a given area of revegetation between cells. The values of the index generated according to the above formula are generally low (since a significant area is required to support additional species) and the index is rescaled by multiplying by 1000 to bring it into an approximate 0-1 range. This metric was developed along with others for use in an assessment of the efficacy of the protected area system for biodiversity under climate change at continental and global scales, presented at the IUCN World Parks Congress 2014. It is described in the AdaptNRM Guide “Helping Biodiversity Adapt: Supporting climate adaptation planning using a community-level modelling approach”, available online at: www.adaptnrm.org. Data are provided in two forms: 1. Zipped ESRI float grids: Binary float grids (*.flt) with associated ESRI header files (*.hdr) and projection files (*.prj). After extracting from the zip archive, these files can be imported into most GIS software packages, and can be used as other binary file formats by substituting the appropriate header file. 2. ArcGIS layer package (*.lpk): These packages contain can be unpacked by ArcGIS as a raster with associated legend. Additionally a short methods summary is provided in the file BiodiversityModellingMethodsSummary.pdf for further information. Layers in this 9s series use a consistent naming convention: BIOLOGICAL GROUP _ FROM BASE_ TO SCENARIO_ ANALYSIS e.g. A_90_CAN85_S or R_90_MIR85_L where BIOLOGICAL GROUP is A: amphibians, M: mammals, R: reptiles and V: vascular plantsless
Benefits of revegetation index for Amphibians as a function of land clearing within the present long term (30 year average) climate (1990 centred) based on Generalised Dissimilarity Modelling (GDM) o... moref compositional turnover. This metric represents the marginal benefit from a unit increase of vegetation at the site, which is a direct function of the slope of the species area curve at the test state of the site. In practice, revegetation of the whole cell is likely to be impractical due to the availability of cleared land within the cell, and practical limitations such as land ownership and revegetation cost. The metric therefore excludes these factors from the analysis, allowing direct comparison of the relative benefit of a given area of revegetation between cells. The values of the index generated according to the above formula are generally low (since a significant area is required to support additional species) and the index is rescaled by multiplying by 1000 to bring it into an approximate 0-1 range. This metric was developed along with others for use in an assessment of the efficacy of the protected area system for biodiversity under climate change at continental and global scales, presented at the IUCN World Parks Congress 2014. It is described in the AdaptNRM Guide “Helping Biodiversity Adapt: Supporting climate adaptation planning using a community-level modelling approach”, available online at: www.adaptnrm.org. Data are provided in two forms: 1. Zipped ESRI float grids: Binary float grids (*.flt) with associated ESRI header files (*.hdr) and projection files (*.prj). After extracting from the zip archive, these files can be imported into most GIS software packages, and can be used as other binary file formats by substituting the appropriate header file. 2. ArcGIS layer package (*.lpk): These packages contain can be unpacked by ArcGIS as a raster with associated legend. Additionally a short methods summary is provided in the file BiodiversityModellingMethodsSummary.pdf for further information. Layers in this 9s series use a consistent naming convention: BIOLOGICAL GROUP _ FROM BASE_ TO SCENARIO_ ANALYSIS e.g. A_90_CAN85_S or R_90_MIR85_L where BIOLOGICAL GROUP is A: amphibians, M: mammals, R: reptiles and V: vascular plantsless
Benefits of revegetation index for Mammals as a function of land clearing and changing climate based on Generalised Dissimilarity Modelling (GDM) of compositional turnover. This metric represents the... more marginal benefit from a unit increase of vegetation at the site, which is a direct function of the slope of the species area curve at the test state of the site. In practice, revegetation of the whole cell is likely to be impractical due to the availability of cleared land within the cell, and practical limitations such as land ownership and revegetation cost. The metric therefore excludes these factors from the analysis, allowing direct comparison of the relative benefit of a given area of revegetation between cells. The values of the index generated according to the above formula are generally low (since a significant area is required to support additional species) and the index is rescaled by multiplying by 1000 to bring it into an approximate 0-1 range. This metric was developed along with others for use in an assessment of the efficacy of the protected area system for biodiversity under climate change at continental and global scales, presented at the IUCN World Parks Congress 2014. It is described in the AdaptNRM Guide “Helping Biodiversity Adapt: Supporting climate adaptation planning using a community-level modelling approach”, available online at: www.adaptnrm.org. Data are provided in two forms: 1. Zipped ESRI float grids: Binary float grids (*.flt) with associated ESRI header files (*.hdr) and projection files (*.prj). After extracting from the zip archive, these files can be imported into most GIS software packages, and can be used as other binary file formats by substituting the appropriate header file. 2. ArcGIS layer package (*.lpk): These packages contain can be unpacked by ArcGIS as a raster with associated legend. Additionally a short methods summary is provided in the file BiodiversityModellingMethodsSummary.pdf for further information. Layers in this 9s series use a consistent naming convention: BIOLOGICAL GROUP _ FROM BASE_ TO SCENARIO_ ANALYSIS e.g. A_90_CAN85_S or R_90_MIR85_L where BIOLOGICAL GROUP is A: amphibians, M: mammals, R: reptiles and V: vascular plantsless
These data provide rasterised layers of climatic variables hypothesised to explain spatial patterns in biological diversity at continental scales for use with statistical modelling tools. Specificall... morey, these data were derived for modelling the compositional pattern of multiple species with environmental factors such as climate, soil and topography using the statistical technique Generalised Dissimilarity Modelling applied to continental Australia. Climate variables are monthly mean values for minimum temperature, maximum temperature, relative humidity, vapour pressure, precipitation, aridity, solar radiation, evaporation, wind and others. Some of these monthly variables were used to generate growth indices (using the GROCLIM module of ANUCLIM). These data for Generalised Dissimilarity Modelling (GDM) analysis were masked to consistently define data/nodata values and supplied in DIVA-GIS floating-grid format in the WGS84 geographic reference system. NOTE: Full details of the data, with a list of data sources and bibliography, are provided in a PDF file included as part of the data collection.less
Closed DEWHA Harness Cntnnt-wide Bdvrsty - Spatial Environmental Data Preparation - Published 29 Jan 2015
Proportional change in effective area of similar ecological environments for vascular plants as a function of land clearing and change in long term (30 year average) climates between the present (1990... more centred) and projected future (2050 centred) under the CanESM2 model (RCP 8.5) based on Generalised Dissimilarity Modelling (GDM) of compositional turnover. This metric describes the combined effects of climate change and land clearing on the area of similar environments to each grid cell as a proportion. Each cell is compared with a sample of 60,000 points in both the present uncleared landscape and an alternative scenario (either present with clearing, or future with clearing), and the pairwise similarities summed (e.g. a completely similar cell will contribute 1, a dissimilar cell 0, with a range of values in between). The contribution of each cell is scaled by the land condition. For each time point, this describes the area of similar environments, which will be low for rare environments and high for widely distributed environments. By dividing the test area by the current area, we are able to quantify the reduction in area as a function of land use/climate change. Values less than one indicate a reduction, values of 1 no change, and values greater than 1 (rare cases in the north) show an increase in similar environments. This metric was developed along with others for use in an assessment of the efficacy of the protected area system for biodiversity under climate change at continental and global scales, presented at the IUCN World Parks Congress 2014. It is described in the AdaptNRM Guide “Implications of Climate Change for Biodiversity: a community-level modelling approach”, available online at: www.adaptnrm.org. Data are provided in two forms: 1. Zipped ESRI float grids: Binary float grids (*.flt) with associated ESRI header files (*.hdr) and projection files (*.prj). After extracting from the zip archive, these files can be imported into most GIS software packages, and can be used as other binary file formats by substituting the appropriate header file. 2. ArcGIS layer package (*.lpk): These packages contain can be unpacked by ArcGIS as a raster with associated legend. Additionally a short methods summary is provided in the file 9sMethodsSummary.pdf for further information. Layers in this 9s series use a consistent naming convention: BIOLOGICAL GROUP _ FROM BASE_ TO SCENARIO_ ANALYSIS e.g. A_90_CAN85_S or R_90_MIR85_L where BIOLOGICAL GROUP is A: Vascular Plants, M: Vascular Plants, R: Vascular Plants and V: vascular plants less
1173.3 Strat: WPC Global Prot Area Ass - Biodiversity Impact Analyses - Published 10 Dec 2014
Proportional change in effective area of similar ecological environments for Vascular plants as a function of land clearing within the present long term (30 year average) climate (1990 centred) based... more on Generalised Dissimilarity Modelling (GDM) of compositional turnover. This metric describes the effects of land clearing on the area of similar environments to each grid cell as a proportion. Each cell is compared with a sample of 60,000 points in both uncleared landscape and degraded landscape (pairwise similarities summed (e.g. a completely similar cell will contribute 1, a dissimilar cell 0, with a range of values in between). The contribution of each cell is then multiplied by a 0 (cleared) to 1 (intact) condition index based on the natural areas layer. By dividing the test area by the current area, we are able to quantify the reduction in area as a function of land use/climate change. Values less than one indicate a reduction, values of 1 no change, and values greater than 1 (rare cases in the north) show an increase in similar environments. This metric was developed along with others for use in an assessment of the efficacy of the protected area system for biodiversity under climate change at continental and global scales, presented at the IUCN World Parks Congress 2014. It is described in the AdaptNRM Guide “Implications of Climate Change for Biodiversity: a community-level modelling approach”, available online at: www.adaptnrm.org. Data are provided in two forms: 1. Zipped ESRI float grids: Binary float grids (*.flt) with associated ESRI header files (*.hdr) and projection files (*.prj). After extracting from the zip archive, these files can be imported into most GIS software packages, and can be used as other binary file formats by substituting the appropriate header file. 2. ArcGIS layer package (*.lpk): These packages contain can be unpacked by ArcGIS as a raster with associated legend. Additionally a short methods summary is provided in the file 9sMethodsSummary.pdf for further information. Layers in this 9s series use a consistent naming convention: BIOLOGICAL GROUP _ FROM BASE_ TO SCENARIO_ ANALYSIS e.g. A_90_CAN85_S or R_90_MIR85_L where BIOLOGICAL GROUP is A: amphibians, M: mammals, R: reptiles and V: vascular plants less
