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Showing results for: [ 1173.3 WPC Global Protected Area Assessm ]
A selection of 9sec gridded National climate change variables for biodiversity modelling. This collection represents 30-year averages centred on each of 1990, 2050, 2070, 2090. Projected future climat... morees were generated by applying within-model changes for two circulation model outputs: GFDL and ACCESS1.0; and for two representative concentration pathways (RCP 4.5, 8.5), calculated at the native general circulation model grid resolution to these current surfaces, using ANUCLIM 6.1 prior to radiative adjustment. That the maximum temperature variables have been adjusted for topographic slope/aspect and shading effects. A short methods summary is provided in the file 9sClimateMethodsSummary.pdf for further information, including a nomenclature for files. The selected climate variables provided in this collection are: TNM - mean annual minimum temperature TXM - mean annual maximum temperature TXX - mean maximum monthly maximum temperature TXI - mean minimum monthly maximum temperature TNI - mean minimum monthly minimum temperature TNX - mean maximum monthly minimum temperature PTA - Average total annual rainfall PTX - mean maximum monthly rainfall PTI - mean minimum monthly rainfall Other variables (evaporation and water balance, temperature range, and seasonality, etc) are available upon application. The data are provided in ESRI binary float grid format (*.hdr, *.flt), Projection is geographic GDA94. less
1173.3 WPC Global Protected Area Assessm - climate change scenarios - Published 12 Sep 2018
Compositional turnover patterns in vascular plant species across continental Australia were derived using Generalised Dissimilarity Modelling (GDM). These models use best-available biological data ext... moreracted from the Australian Natural Heritage Assessment Tool (ANHAT) Database current to April 2013 (courtesy the Australian Government Department of the Environment and the BushBlitz program) and spatial environmental predictor data compiled at 9 second resolution. 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 describes the GDM-fitted model, the GDM-scaled environmental predictors for the fitted-model which comprises substrate (constant) and 1990-centred climates, and four projected models using past and future climates: 1960-centred climates and six 2050 climate change scenarios (3 GCMs, 3 RCPs). The past climate scenario for 1960 was generated using the c.75-year average monthly climate surfaces in ANUCLIM. The future climate projections (for two representative concentration pathways 8.5 and 4.5 greenhouse gas future emission scenario) were generated as 30 year averages centred on 2050 extracted from the CMIP5 database for three earth system models: MPI-ESM2 (Stevens (ed), 2013); CanESM2 (Chylek et al., 2011).; MIROC5 (Watanabe et al., 2010). Within model change grids (future minus 1990 ESM climates) were applied in ANUCLIM 6.1 and downscale to 0.0025 degrees by matching the spatial pattern of the 1990-centred surfaces (errors in the alignment of change grids have been corrected and the scenarios regenerated). Actual evapotranspiration was projected by modelling relative to the Budyko framework, using a topographically-scaled measure of soil water holding capacity (Claridge et al., 2000). Details are published in Reside et al. 2013 (http://www.nccarf.edu.au/publications/climate-change-refugia-terrestrial-biodiversity) and summarised in the methods summary report at related information. This GDM version was created 27 April 2014 with novel climate seasonality predictors and >10 species aggregated per 9-second grid cell, and used as the vascular plant model in the AdaptNRM biodiversity modules. The data are provided in ESRI binary float format, GDA 94. less
1173.3 WPC Global Protected Area Assessm - Macroecological Modelling - Published 16 Jun 2015
Composite ecological change as a function of three metrics (the potential degree of ecological change and of disappearing and novel ecological environments) shows where change might be greatest and di... morefferent types of vulnerability using 30-year climate averages between the present (1990:1976- 2005) and projected future (2050:2036-2065) under the MIROC5 global climate model (RCP 8.5), based on a Generalised Dissimilarity Modelling (GDM) of compositional turnover for vascular plants (VAS_v5_r11). Wherever the Potential degree of ecological change is scored low, ecological environments can neither be novel nor disappearing and minimal change is expected. But when the Potential degree of ecological change is scored high, a variety of possible types of change can occur depending on whether scores for Novel and/or Disappearing ecological environments are also high. To create a composite view, we assigned each of the three component measures to a colour band in a composite-band raster: local similarity as shades of green (inverted, 1-0 rescaled 0-255); novel as shades of blue (0-1 rescaled 0-255); and disappearing as shades of red (0-1 rescaled 0-255). The three layers can then be mapped simultaneously (red: band 3; green: band 1; blue: band 2) each scaled 0-255 to show the varying degrees of similar, novel and disappearing ecological environments and their combinations. 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 as zipped ESRI tiff grids containing: raster image (*.tif) with associated header (*.tfw) and projection (*.xml) files. After extracting from the zip archive, these files can be imported into most GIS software packages. A readme file describes how to correctly reproduce the colour legend. In ArcGIS, the symbology statistics file can be used: "SND_display.stat.XML". Reproducing RGB composite colours for 3-band raster in ArcGIS: 1. In file properties in ARCGIS, Symbology tab, Load XML "SND_display.stat.XML" 2. RED = BAND_3 (Disappearing) 3. GREEN = BAND_1 (Similarity ) 4. BLUE = BAND_2 (Novel) 5. Always use min-max legend 6. Set each band in the custom range 0-255, mean = 126, std = 0 Layers in this 9s series use a consistent naming convention: BIOLOGICAL GROUP _ FROM BASE TO SCENARIO _ ANALYSIS e.g. A_90CAN85_SND or R_90MIR85_SND where BIOLOGICAL GROUP is A: amphibians, M: mammals, R: reptiles and V: vascular plants and scenario is CAN: CanESM2; MIR: MIROC5 analysis, SND refers to – similarity, novel, disappearing less
1173.3 WPC Global Protected Area Assessm - Biodiversity Impact Analyses - Published 16 Jun 2015
Composite ecological change as a function of three metrics (the potential degree of ecological change and of disappearing and novel ecological environments) shows where change might be greatest and di... morefferent types of vulnerability using 30-year climate averages between the present (1990:1976- 2005) and projected future (2050:2036-2065) under the CanESM2 global climate model (RCP 8.5), based on a Generalised Dissimilarity Modelling (GDM) of compositional turnover for vascular plants (VAS_v5_r11). Wherever the Potential degree of ecological change is scored low, ecological environments can neither be novel nor disappearing and minimal change is expected. But when the Potential degree of ecological change is scored high, a variety of possible types of change can occur depending on whether scores for Novel and/or Disappearing ecological environments are also high. To create a composite view, we assigned each of the three component measures to a colour band in a composite-band raster: local similarity as shades of green (inverted, 1-0 rescaled 0-255); novel as shades of blue (0-1 rescaled 0-255); and disappearing as shades of red (0-1 rescaled 0-255). The three layers can then be mapped simultaneously (red: band 3; green: band 1; blue: band 2) each scaled 0-255 to show the varying degrees of similar, novel and disappearing ecological environments and their combinations. 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 as zipped ESRI tiff grids containing: raster image (*.tif) with associated header (*.tfw) and projection (*.xml) files. After extracting from the zip archive, these files can be imported into most GIS software packages. A readme file describes how to correctly reproduce the colour legend. In ArcGIS, the symbology statistics file can be used: "SND_display.stat.XML". Reproducing RGB composite colours for 3-band raster in ArcGIS: 1. In file properties in ARCGIS, Symbology tab, Load XML "SND_display.stat.XML" 2. RED = BAND_3 (Disappearing) 3. GREEN = BAND_1 (Similarity ) 4. BLUE = BAND_2 (Novel) 5. Always use min-max legend 6. Set each band in the custom range 0-255, mean = 126, std = 0 Layers in this 9s series use a consistent naming convention: BIOLOGICAL GROUP _ FROM BASE TO SCENARIO _ ANALYSIS e.g. A_90CAN85_SND or R_90MIR85_SND where BIOLOGICAL GROUP is A: amphibians, M: mammals, R: reptiles and V: vascular plants and scenario is CAN: CanESM2; MIR: MIROC5 analysis, SND refers to – similarity, novel, disappearing less
Composite ecological change as a function of three metrics (the potential degree of ecological change and of disappearing and novel ecological environments) shows where change might be greatest and di... morefferent types of vulnerability using 30-year climate averages between the present (1990:1976- 2005) and projected future (2050:2036-2065) under the MIROC5 global climate model (RCP 8.5), based on a Generalised Dissimilarity Modelling (GDM) of compositional turnover for reptiles (REP_R3_V2). Wherever the Potential degree of ecological change is scored low, ecological environments can neither be novel nor disappearing and minimal change is expected. But when the Potential degree of ecological change is scored high, a variety of possible types of change can occur depending on whether scores for Novel and/or Disappearing ecological environments are also high. To create a composite view, we assigned each of the three component measures to a colour band in a composite-band raster: local similarity as shades of green (inverted, 1-0 rescaled 0-255); novel as shades of blue (0-1 rescaled 0-255); and disappearing as shades of red (0-1 rescaled 0-255). The three layers can then be mapped simultaneously (red: band 3; green: band 1; blue: band 2) each scaled 0-255 to show the varying degrees of similar, novel and disappearing ecological environments and their combinations. 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 as zipped ESRI tiff grids containing: raster image (*.tif) with associated header (*.tfw) and projection (*.xml) files. After extracting from the zip archive, these files can be imported into most GIS software packages. A readme file describes how to correctly reproduce the colour legend. In ArcGIS, the symbology statistics file can be used: "SND_display.stat.XML". Reproducing RGB composite colours for 3-band raster in ArcGIS: 1. In file properties in ARCGIS, Symbology tab, Load XML "SND_display.stat.XML" 2. RED = BAND_3 (Disappearing) 3. GREEN = BAND_1 (Similarity ) 4. BLUE = BAND_2 (Novel) 5. Always use min-max legend 6. Set each band in the custom range 0-255, mean = 126, std = 0 Layers in this 9s series use a consistent naming convention: BIOLOGICAL GROUP _ FROM BASE TO SCENARIO _ ANALYSIS e.g. A_90CAN85_SND or R_90MIR85_SND where BIOLOGICAL GROUP is A: amphibians, M: mammals, R: reptiles and V: vascular plants and scenario is CAN: CanESM2; MIR: MIROC5 analysis, SND refers to – similarity, novel, disappearing less
Composite ecological change as a function of three metrics (the potential degree of ecological change and of disappearing and novel ecological environments) shows where change might be greatest and di... morefferent types of vulnerability using 30-year climate averages between the present (1990:1976- 2005) and projected future (2050:2036-2065) under the MIROC5 global climate model (RCP 8.5), based on a Generalised Dissimilarity Modelling (GDM) of compositional turnover for mammals (MAM_R2). Wherever the Potential degree of ecological change is scored low, ecological environments can neither be novel nor disappearing and minimal change is expected. But when the Potential degree of ecological change is scored high, a variety of possible types of change can occur depending on whether scores for Novel and/or Disappearing ecological environments are also high. To create a composite view, we assigned each of the three component measures to a colour band in a composite-band raster: local similarity as shades of green (inverted, 1-0 rescaled 0-255); novel as shades of blue (0-1 rescaled 0-255); and disappearing as shades of red (0-1 rescaled 0-255). The three layers can then be mapped simultaneously (red: band 3; green: band 1; blue: band 2) each scaled 0-255 to show the varying degrees of similar, novel and disappearing ecological environments and their combinations. 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 as zipped ESRI tiff grids containing: raster image (*.tif) with associated header (*.tfw) and projection (*.xml) files. After extracting from the zip archive, these files can be imported into most GIS software packages. A readme file describes how to correctly reproduce the colour legend. In ArcGIS, the symbology statistics file can be used: "SND_display.stat.XML". Reproducing RGB composite colours for 3-band raster in ArcGIS: 1. In file properties in ARCGIS, Symbology tab, Load XML "SND_display.stat.XML" 2. RED = BAND_3 (Disappearing) 3. GREEN = BAND_1 (Similarity ) 4. BLUE = BAND_2 (Novel) 5. Always use min-max legend 6. Set each band in the custom range 0-255, mean = 126, std = 0 Layers in this 9s series use a consistent naming convention: BIOLOGICAL GROUP _ FROM BASE TO SCENARIO _ ANALYSIS e.g. A_90CAN85_SND or R_90MIR85_SND where BIOLOGICAL GROUP is A: amphibians, M: mammals, R: reptiles and V: vascular plants and scenario is CAN: CanESM2; MIR: MIROC5 analysis, SND refers to – similarity, novel, disappearing less
Composite ecological change as a function of three metrics (the potential degree of ecological change and of disappearing and novel ecological environments) shows where change might be greatest and di... morefferent types of vulnerability using 30-year climate averages between the present (1990:1976- 2005) and projected future (2050:2036-2065) under the CanESM2 global climate model (RCP 8.5), based on a Generalised Dissimilarity Modelling (GDM) of compositional turnover for reptiles (REP_R3_V2). Wherever the Potential degree of ecological change is scored low, ecological environments can neither be novel nor disappearing and minimal change is expected. But when the Potential degree of ecological change is scored high, a variety of possible types of change can occur depending on whether scores for Novel and/or Disappearing ecological environments are also high. To create a composite view, we assigned each of the three component measures to a colour band in a composite-band raster: local similarity as shades of green (inverted, 1-0 rescaled 0-255); novel as shades of blue (0-1 rescaled 0-255); and disappearing as shades of red (0-1 rescaled 0-255). The three layers can then be mapped simultaneously (red: band 3; green: band 1; blue: band 2) each scaled 0-255 to show the varying degrees of similar, novel and disappearing ecological environments and their combinations. 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 as zipped ESRI tiff grids containing: raster image (*.tif) with associated header (*.tfw) and projection (*.xml) files. After extracting from the zip archive, these files can be imported into most GIS software packages. A readme file describes how to correctly reproduce the colour legend. In ArcGIS, the symbology statistics file can be used: "SND_display.stat.XML". Reproducing RGB composite colours for 3-band raster in ArcGIS: 1. In file properties in ARCGIS, Symbology tab, Load XML "SND_display.stat.XML" 2. RED = BAND_3 (Disappearing) 3. GREEN = BAND_1 (Similarity ) 4. BLUE = BAND_2 (Novel) 5. Always use min-max legend 6. Set each band in the custom range 0-255, mean = 126, std = 0 Layers in this 9s series use a consistent naming convention: BIOLOGICAL GROUP _ FROM BASE TO SCENARIO _ ANALYSIS e.g. A_90CAN85_SND or R_90MIR85_SND where BIOLOGICAL GROUP is A: amphibians, M: mammals, R: reptiles and V: vascular plants and scenario is CAN: CanESM2; MIR: MIROC5 analysis, SND refers to – similarity, novel, disappearing less
Composite ecological change as a function of three metrics (the potential degree of ecological change and of disappearing and novel ecological environments) shows where change might be greatest and di... morefferent types of vulnerability using 30-year climate averages between the present (1990:1976- 2005) and projected future (2050:2036-2065) under the MIROC5 global climate model (RCP 8.5), based on a Generalised Dissimilarity Modelling (GDM) of compositional turnover for amphibian (AMP_R2_PTS1). Wherever the Potential degree of ecological change is scored low, ecological environments can neither be novel nor disappearing and minimal change is expected. But when the Potential degree of ecological change is scored high, a variety of possible types of change can occur depending on whether scores for Novel and/or Disappearing ecological environments are also high. To create a composite view, we assigned each of the three component measures to a colour band in a composite-band raster: local similarity as shades of green (inverted, 1-0 rescaled 0-255); novel as shades of blue (0-1 rescaled 0-255); and disappearing as shades of red (0-1 rescaled 0-255). The three layers can then be mapped simultaneously (red: band 3; green: band 1; blue: band 2) each scaled 0-255 to show the varying degrees of similar, novel and disappearing ecological environments and their combinations. 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 as zipped ESRI tiff grids containing: raster image (*.tif) with associated header (*.tfw) and projection (*.xml) files. After extracting from the zip archive, these files can be imported into most GIS software packages. A readme file describes how to correctly reproduce the colour legend. In ArcGIS, the symbology statistics file can be used: "SND_display.stat.XML". Reproducing RGB composite colours for 3-band raster in ArcGIS: 1. In file properties in ARCGIS, Symbology tab, Load XML "SND_display.stat.XML" 2. RED = BAND_3 (Disappearing) 3. GREEN = BAND_1 (Similarity ) 4. BLUE = BAND_2 (Novel) 5. Always use min-max legend 6. Set each band in the custom range 0-255, mean = 126, std = 0 Layers in this 9s series use a consistent naming convention: BIOLOGICAL GROUP _ FROM BASE TO SCENARIO _ ANALYSIS e.g. A_90CAN85_SND or R_90MIR85_SND where BIOLOGICAL GROUP is A: amphibians, M: mammals, R: reptiles and V: vascular plants and scenario is CAN: CanESM2; MIR: MIROC5 analysis, SND refers to – similarity, novel, disappearing less
Composite ecological change as a function of three metrics (the potential degree of ecological change and of disappearing and novel ecological environments) shows where change might be greatest and di... morefferent types of vulnerability using 30-year climate averages between the present (1990:1976- 2005) and projected future (2050:2036-2065) under the CanESM2 global climate model (RCP 8.5), based on a Generalised Dissimilarity Modelling (GDM) of compositional turnover for mammals (MAM_R2). Wherever the Potential degree of ecological change is scored low, ecological environments can neither be novel nor disappearing and minimal change is expected. But when the Potential degree of ecological change is scored high, a variety of possible types of change can occur depending on whether scores for Novel and/or Disappearing ecological environments are also high. To create a composite view, we assigned each of the three component measures to a colour band in a composite-band raster: local similarity as shades of green (inverted, 1-0 rescaled 0-255); novel as shades of blue (0-1 rescaled 0-255); and disappearing as shades of red (0-1 rescaled 0-255). The three layers can then be mapped simultaneously (red: band 3; green: band 1; blue: band 2) each scaled 0-255 to show the varying degrees of similar, novel and disappearing ecological environments and their combinations. 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 as zipped ESRI tiff grids containing: raster image (*.tif) with associated header (*.tfw) and projection (*.xml) files. After extracting from the zip archive, these files can be imported into most GIS software packages. A readme file describes how to correctly reproduce the colour legend. In ArcGIS, the symbology statistics file can be used: "SND_display.stat.XML". Reproducing RGB composite colours for 3-band raster in ArcGIS: 1. In file properties in ARCGIS, Symbology tab, Load XML "SND_display.stat.XML" 2. RED = BAND_3 (Disappearing) 3. GREEN = BAND_1 (Similarity ) 4. BLUE = BAND_2 (Novel) 5. Always use min-max legend 6. Set each band in the custom range 0-255, mean = 126, std = 0 Layers in this 9s series use a consistent naming convention: BIOLOGICAL GROUP _ FROM BASE TO SCENARIO _ ANALYSIS e.g. A_90CAN85_SND or R_90MIR85_SND where BIOLOGICAL GROUP is A: amphibians, M: mammals, R: reptiles and V: vascular plants and scenario is CAN: CanESM2; MIR: MIROC5 analysis, SND refers to – similarity, novel, disappearing less
Composite ecological change as a function of three metrics (the potential degree of ecological change and of disappearing and novel ecological environments) shows where change might be greatest and di... morefferent types of vulnerability using 30-year climate averages between the present (1990:1976- 2005) and projected future (2050:2036-2065) under the CanESM2 global climate model (RCP 8.5), based on a Generalised Dissimilarity Modelling (GDM) of compositional turnover for amphibian (AMP_R2_PTS1). Wherever the Potential degree of ecological change is scored low, ecological environments can neither be novel nor disappearing and minimal change is expected. But when the Potential degree of ecological change is scored high, a variety of possible types of change can occur depending on whether scores for Novel and/or Disappearing ecological environments are also high. To create a composite view, we assigned each of the three component measures to a colour band in a composite-band raster: local similarity as shades of green (inverted, 1-0 rescaled 0-255); novel as shades of blue (0-1 rescaled 0-255); and disappearing as shades of red (0-1 rescaled 0-255). The three layers can then be mapped simultaneously (red: band 3; green: band 1; blue: band 2) each scaled 0-255 to show the varying degrees of similar, novel and disappearing ecological environments and their combinations. 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 as zipped ESRI tiff grids containing: raster image (*.tif) with associated header (*.tfw) and projection (*.xml) files. After extracting from the zip archive, these files can be imported into most GIS software packages. A readme file describes how to correctly reproduce the colour legend. In ArcGIS, the symbology statistics file can be used: "SND_display.stat.XML". Reproducing RGB composite colours for 3-band raster in ArcGIS: 1. In file properties in ARCGIS, Symbology tab, Load XML "SND_display.stat.XML" 2. RED = BAND_3 (Disappearing) 3. GREEN = BAND_1 (Similarity ) 4. BLUE = BAND_2 (Novel) 5. Always use min-max legend 6. Set each band in the custom range 0-255, mean = 126, std = 0 Layers in this 9s series use a consistent naming convention: BIOLOGICAL GROUP _ FROM BASE TO SCENARIO _ ANALYSIS e.g. A_90CAN85_SND or R_90MIR85_SND where BIOLOGICAL GROUP is A: amphibians, M: mammals, R: reptiles and V: vascular plants and scenario is CAN: CanESM2; MIR: MIROC5 analysis, SND refers to – similarity, novel, disappearing less
