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Showing results for: [ 1173.3 Strat: WPC Global Prot Area Ass ]
Compositional turnover patterns in mammal species across continental Australia were derived using Generalised Dissimilarity Modelling (GDM). These models use best-available biological data extracted f... morerom the Atlas of Living Australia current to 26th February 2014 and spatial environmental predictor data compiled at 9 second resolution (with novel climate seasonality predictors, undersampling covariates and >3 species aggregated per 9-second grid cell). The models were developed to underpin continental assessments of biodiversity significance and identify gaps in biological surveys. GDM is a statistical technique that models the dissimilarity in composition of species between pairs of surveyed locations, as a function of environmental differences between these locations. The compositional dissimilarity between a given pair of locations can be thought of as the proportion of species occurring at one location that do not occur at the other location (averaged across the two locations) - ranging from ‘0’ if the two locations have exactly the same species through to ‘1’ if they have no species in common. GDM effectively weights and transforms the environmental variables such that distances between locations in this transformed multidimensional environmental space now correlate, as closely as possible, with the observed biological compositional dissimilarities between these same locations. Once a GDM model has been fitted to the biological data from the sampled locations using environmental predictor data, it can be used to predict compositional dissimilarity values for sites lacking biological data, based purely on their mapped environmental attributes. For this purpose, a set of GDM-scaled environmental grids are produced for use in subsequent spatial assessments of biodiversity significance. This collection includes the source biological and environmental data, the GDM-fitted model, the GDM-scaled environmental predictors for the fitted-model which comprises substrate (constant) and 1990-centred climates, and a derived classification. Projections using past and future climates are not included here (available upon request). This model was used in the AdaptNRM series of reports by Williams et al. (2013) and Prober et al. (2014). less
1173.3 Strat: WPC Global Prot Area Ass - Macroecological Modelling - Published 09 Jan 2017
Compositional turnover patterns in amphibian species across continental Australia were derived using Generalised Dissimilarity Modelling (GDM). These models use best-available biological data extracte... mored from the Atlas of Living Australia current to 27th February 2014 and spatial environmental predictor data compiled at 9 second resolution (with novel climate seasonality predictors, undersampling covariates and >3 species aggregated per 9-second grid cell). The models were developed to underpin continental assessments of biodiversity significance and identify gaps in biological surveys. GDM is a statistical technique that models the dissimilarity in composition of species between pairs of surveyed locations, as a function of environmental differences between these locations. The compositional dissimilarity between a given pair of locations can be thought of as the proportion of species occurring at one location that do not occur at the other location (averaged across the two locations) - ranging from ‘0’ if the two locations have exactly the same species through to ‘1’ if they have no species in common. GDM effectively weights and transforms the environmental variables such that distances between locations in this transformed multidimensional environmental space now correlate, as closely as possible, with the observed biological compositional dissimilarities between these same locations. Once a GDM model has been fitted to the biological data from the sampled locations using environmental predictor data, it can be used to predict compositional dissimilarity values for sites lacking biological data, based purely on their mapped environmental attributes. For this purpose, a set of GDM-scaled environmental grids are produced for use in subsequent spatial assessments of biodiversity significance. This collection includes the source biological and environmental data, the GDM-fitted model, the GDM-scaled environmental predictors for the fitted-model which comprises substrate (constant) and 1990-centred climates, and a derived classification. Projections using past and future climates are not included here (available upon request). This model was used in the AdaptNRM series of reports by Williams et al. (2013) and Prober et al. (2014). less
1173.3 Strat: WPC Global Prot Area Ass - Macroecological Modelling - Published 06 Jan 2017
Compositional turnover patterns in land snail species across continental Australia were derived using Generalised Dissimilarity Modelling (GDM). These models use best-available biological data extract... moreed from the ANHAT (Courtesy Australian Government Department of the Environment) current to April 2013 and spatial environmental predictor data compiled at 9 second resolution (with novel climate seasonality predictors, undersampling covariates and >2 species aggregated per 9-second grid cell). The models were developed to underpin continental assessments of biodiversity significance and identify gaps in biological surveys. GDM is a statistical technique that models the dissimilarity in composition of species between pairs of surveyed locations, as a function of environmental differences between these locations. The compositional dissimilarity between a given pair of locations can be thought of as the proportion of species occurring at one location that do not occur at the other location (averaged across the two locations) - ranging from ‘0’ if the two locations have exactly the same species through to ‘1’ if they have no species in common. GDM effectively weights and transforms the environmental variables such that distances between locations in this transformed multidimensional environmental space now correlate, as closely as possible, with the observed biological compositional dissimilarities between these same locations. Once a GDM model has been fitted to the biological data from the sampled locations using environmental predictor data, it can be used to predict compositional dissimilarity values for sites lacking biological data, based purely on their mapped environmental attributes. For this purpose, a set of GDM-scaled environmental grids are produced for use in subsequent spatial assessments of biodiversity significance. This collection includes the source biological and environmental data, the GDM-fitted model, the GDM-scaled environmental predictors for the fitted-model which comprises substrate (constant) and 1990-centred climates, and a derived classification. Projections using past and future climates are not included here (available upon request).less
Compositional turnover patterns in reptiles species across continental Australia were derived using Generalised Dissimilarity Modelling (GDM). These models use best-available biological data extracted... more from the Atlas of Living Australia current to 28th February 2014 and spatial environmental predictor data compiled at 9 second resolution (with novel climate seasonality predictors, undersampling covariates and >3 species aggregated per 9-second grid cell). The models were developed to underpin continental assessments of biodiversity significance and identify gaps in biological surveys. GDM is a statistical technique that models the dissimilarity in composition of species between pairs of surveyed locations, as a function of environmental differences between these locations. The compositional dissimilarity between a given pair of locations can be thought of as the proportion of species occurring at one location that do not occur at the other location (averaged across the two locations) - ranging from ‘0’ if the two locations have exactly the same species through to ‘1’ if they have no species in common. GDM effectively weights and transforms the environmental variables such that distances between locations in this transformed multidimensional environmental space now correlate, as closely as possible, with the observed biological compositional dissimilarities between these same locations. Once a GDM model has been fitted to the biological data from the sampled locations using environmental predictor data, it can be used to predict compositional dissimilarity values for sites lacking biological data, based purely on their mapped environmental attributes. For this purpose, a set of GDM-scaled environmental grids are produced for use in subsequent spatial assessments of biodiversity significance. This collection includes the source biological and environmental data, the GDM-fitted model, the GDM-scaled environmental predictors for the fitted-model which comprises substrate (constant) and 1990-centred climates, and a derived classification. Projections using past and future climates are not included here (available upon request). This model was used in the AdaptNRM series of reports by Williams et al. (2013) and Prober et al. (2014). less
A global map of 5 land use types at 30s (approx. 1km) resolution for 2005. The data set was generated through the statistical downscaling of the Land-use Harmonisation data set (Hurt et al 2011) at ht... moretp://luh.umd.edu/. Five land use types (primary, secondary, pasture, crop, urban) are provided as separate raster layers, with the value of each cell representing the proportion of the grid cell occupied by that land use type. An additional layer representing cells defined as permanent ice (value of 1) is also provided.less
1173.3 Strat: WPC Global Prot Area Ass - Land-use downscaling - Published 04 Apr 2016
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
Need for assisted dispersal for Vascular Plants 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 ... moremodel (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
Need for assisted dispersal for Vascular Plants 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 ESM... more2 model (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
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 MIROC5 model (... moreRCP 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
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
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
Need for assisted dispersal for Mammals 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
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
Need for assisted dispersal for Mammals 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 (R... moreCP 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
Need for assisted dispersal for Amphibians 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. 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
Need for assisted dispersal for Amphibians 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. 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 22 Jun 2015
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
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
