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Showing results for: [ Reptiles ]
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
1173.3 Strat: WPC Global Prot Area Ass - Biodiversity Adaptation Analyses - Published 24 Jun 2015
Need for assisted dispersal for Reptiles as a function of change in long term (30 year average) climates between the present (1990 centred) and projected future (2050 centred) under the CAN ESM2 model... more (RCP 8.5) based on Generalised Dissimilarity Modelling (GDM) of compositional turnover. The distance to the nearest grid cell with ecological similarity of at least 0.5 is given. This metric describes the nature of the projected 2050 centred future environmental conditions for each 9s grid square. Using a Generalised Dissimilarity Model of compositional turnover (the effects of changing environment on changing species), each future location is compared with the continent in the present. For each cell, the metric looks out to all other cells in the continent, and records the ecological similarity of the future state of the cell to the most similar cell in the present. A value of 1 indicates that the future environment is similar to a current location in the present, and perfect analogue can found somewhere in Australia. A value of 0 indicates that the most similar environment to be found in the present is ecologically so different that we would expect no species in common, i.e. there are no current analogues for this environment; it is novel. Intermediate values show how ecologically similar the most similar cell is. However, no weight is given to the proximity of the most similar cell. The environment may be similar, but the cells thousands of kilometres apart. 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
1173.3 Strat: WPC Global Prot Area Ass - Biodiversity Adaptation Analyses - Published 23 Jun 2015
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
1173.3 Strat: WPC Global Prot Area Ass - Biodiversity Adaptation Analyses - Published 22 Jun 2015
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 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
Disappearing ecological environments for Reptiles as a function of change in long term (30 year average) climates between the present (1990 centred) and projected future (2050 centred) under the MIROC... more5 model (RCP 8.5) based on Generalised Dissimilarity Modelling (GDM) of compositional turnover. This metric describes the extent to which the long term average environmental conditions for each 9s grid square in the present (1990 centred) will be present in a projected 2050 centred future. Using a Generalised Dissimilarity Model of compositional turnover (the effects of changing environment on changing species), each location is compared with the continent in the future. For each cell, the metric looks out to all other cells in the continent, and records the ecological similarity of the present state of the cell to the most similar cell in the future. A value of 1 indicates that the environment is not disappearing, and perfect analogue is found somewhere in Australia. A value of 0 indicates that the most similar environment to be found in the future is ecologically so different that we would expect no species in common. Intermediate values show how ecologically similar the most similar cell is. However, no weight is given to the proximity of the most similar cell. The environment may be similar, but the cells thousands of kilometres apart. 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.Tom HA 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: Mammals, M: mammals, R: reptiles and V: vascular plants less
1173.3 Strat: WPC Global Prot Area Ass - Biodiversity Impact Analyses - Published 10 Dec 2014
Disappearing ecological environments for Reptiles as a function of change in long term (30 year average) climates between the present (1990 centred) and projected future (2050 centred) under the CanES... moreM2 model (RCP 8.5) based on Generalised Dissimilarity Modelling (GDM) of compositional turnover. This metric describes the extent to which the long term average environmental conditions for each 9s grid square in the present (1990 centred) will be present in a projected 2050 centred future. Using a Generalised Dissimilarity Model of compositional turnover (the effects of changing environment on changing species), each location is compared with the continent in the future. For each cell, the metric looks out to all other cells in the continent, and records the ecological similarity of the present state of the cell to the most similar cell in the future. A value of 1 indicates that the environment is not disappearing, and perfect analogue is found somewhere in Australia. A value of 0 indicates that the most similar environment to be found in the future is ecologically so different that we would expect no species in common. Intermediate values show how ecologically similar the most similar cell is. However, no weight is given to the proximity of the most similar cell. The environment may be similar, but the cells thousands of kilometres apart. 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.Tom HA 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: Mammals, M: mammals, R: reptiles and V: vascular plants less
Proportional change in effective area of similar ecological environments for Reptiles as a function of change in long term (30 year average) climates between the present (1990 centred) and projected f... moreuture (2050 centred) under the MIROC5 model (RCP 8.5) based on Generalised Dissimilarity Modelling (GDM) of compositional turnover. This metric describes the effects of climate change on the area of similar environments to each grid cell, expressed as a proportion of original area. Each cell is compared with a sample of 60,000 points in both the present and the future, 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). For each time point, this describes the area of similar environments, which for the present will be low for rare environments and high for widely distributed environments. By dividing the future area by the current area, we are able to quantify the proportional reduction in area as a function of 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: Mammals, M: mammals, R: reptiles and V: vascular plants less
Proportional change in effective area of similar ecological environments for Reptiles as a function of change in long term (30 year average) climates between the present (1990 centred) and projected f... moreuture (2050 centred) under the CanESM2 model (RCP 8.5) based on Generalised Dissimilarity Modelling (GDM) of compositional turnover. This metric describes the effects of climate change on the area of similar environments to each grid cell, expressed as a proportion of original area. Each cell is compared with a sample of 60,000 points in both the present and the future, 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). For each time point, this describes the area of similar environments, which for the present will be low for rare environments and high for widely distributed environments. By dividing the future area by the current area, we are able to quantify the proportional reduction in area as a function of 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: Mammals, M: mammals, R: reptiles and V: vascular plants less
Proportional change in effective area of similar ecological environments for Reptiles as a function of land clearing and change in long term (30 year average) climates between the present (1990 centre... mored) and projected future (2050 centred) under the MIROC5 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). Only cells which are flagged as uncleared contribute. 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: Mammals, M: mammals, R: reptiles and V: vascular plants less
Proportional change in effective area of similar ecological environments for Reptiles as a function of land clearing and change in long term (30 year average) climates between the present (1990 centre... mored) 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). Only cells which are flagged as uncleared contribute. 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: Mammals, M: mammals, R: reptiles and V: vascular plantsless
Proportional change in effective area of similar ecological environments for Reptiles as a function of land clearing within the present long term (30 year average) climate (1990 centred) based on Gen... moreeralised 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
Novel ecological environments for Reptiles as a function of change in long term (30 year average) climates between the present (1990 centred) and projected future (2050 centred) under the CanESM2 mode... morel (RCP 8.5) based on Generalised Dissimilarity Modelling (GDM) of compositional turnover. This metric describes the nature of the projected 2050 centred future environmental conditions for each 9s grid square. Using a Generalised Dissimilarity Model of compositional turnover (the effects of changing environment on changing species), each future location is compared with the continent in the present. For each cell, the metric looks out to all other cells in the continent, and records the ecological similarity of the future state of the cell to the most similar cell in the present. A value of 1 indicates that the future environment is similar to a current location in the present, and perfect analogue can found somewhere in Australia. A value of 0 indicates that the most similar environment to be found in the present is ecologically so different that we would expect no species in common, i.e. there are no current analogues for this environment; it is novel. Intermediate values show how ecologically similar the most similar cell is. However, no weight is given to the proximity of the most similar cell. The environment may be similar, but the cells thousands of kilometres apart. 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: Reptiles, M: Reptiles, R: reptiles and V: vascular plants less
1173.3 Strat: WPC Global Prot Area Ass - Biodiversity Impact Analyses - Published 09 Dec 2014
Novel ecological environments for Reptiles as a function of change in long term (30 year average) climates between the present (1990 centred) and projected future (2050 centred) under the MIROC5 model... more (RCP 8.5) based on Generalised Dissimilarity Modelling (GDM) of compositional turnover. This metric describes the nature of the projected 2050 centred future environmental conditions for each 9s grid square. Using a Generalised Dissimilarity Model of compositional turnover (the effects of changing environment on changing species), each future location is compared with the continent in the present. For each cell, the metric looks out to all other cells in the continent, and records the ecological similarity of the future state of the cell to the most similar cell in the present. A value of 1 indicates that the future environment is similar to a current location in the present, and perfect analogue can found somewhere in Australia. A value of 0 indicates that the most similar environment to be found in the present is ecologically so different that we would expect no species in common, i.e. there are no current analogues for this environment; it is novel. Intermediate values show how ecologically similar the most similar cell is. However, no weight is given to the proximity of the most similar cell. The environment may be similar, but the cells thousands of kilometres apart. 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: Reptiles, M: Reptiles, R: reptiles and V: vascular plants less
Potential degree of ecological change in Reptiles as a function of change in long term (30 year average) climates between the present (1990 centred) and projected future (2050 centred) under the CanES... moreM2 model (RCP 8.5) based on Generalised Dissimilarity Modelling (GDM) of compositional turnover. This metric describes the change in long term average environmental conditions at a single location (9s grid square) from the present (1990 centred) to a 2050 centred future, scaled in terms of its expected effects on the turnover of species. Compositional turnover patterns in amphibian species across continental Australia were derived using Generalised Dissimilarity Modelling (GDM). These models use best-available biological data extracted from the Atlas of Living Australia (ALA) in 2013, and spatial environmental predictor data compiled at 9 second resolution. GDM-scaled environmental grids were used as the basis for pairwise cell comparisons across space and time using the highly parallel CSIRO Muru software to derive the potential degree of ecological change. Each location is compared with its future state. The difference in environment is presented as an expected ecological similarity, ranging from 1 (completely similar) to 0, for which we would expect no species in common. If this environmental difference was observed in a different spatial location within the present, we would expect to observe such a difference if we visited both sites. 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: Reptiles, M: Reptiles, R: reptiles and V: vascular plantsless
Potential degree of ecological change in Reptiles as a function of change in long term (30 year average) climates between the present (1990 centred) and projected future (2050 centred) under the MIROC... more5 model (RCP 8.5) based on Generalised Dissimilarity Modelling (GDM) of compositional turnover. This metric describes the change in long term average environmental conditions at a single location (9s grid square) from the present (1990 centred) to a 2050 centred future, scaled in terms of its expected effects on the turnover of species. Compositional turnover patterns in amphibian species across continental Australia were derived using Generalised Dissimilarity Modelling (GDM). These models use best-available biological data extracted from the Atlas of Living Australia (ALA) in 2013, and spatial environmental predictor data compiled at 9 second resolution. GDM-scaled environmental grids were used as the basis for pairwise cell comparisons across space and time using the highly parallel CSIRO Muru software to derive the potential degree of ecological change. Each location is compared with its future state. The difference in environment is presented as an expected ecological similarity, ranging from 1 (completely similar) to 0, for which we would expect no species in common. If this environmental difference was observed in a different spatial location within the present, we would expect to observe such a difference if we visited both sites. 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: Reptiles, M: Reptiles, R: reptiles and V: vascular plants less
