Above ground Water Tank points in Fuquay-Varina. Please note that ALL public utility data layers can be downloaded in one .lpk ArcGIS layer package file (click here), for use in any version of ArcGIS Pro or ArcMap software. You can also use QGIS, a powerful free open source software, but you must extract the file geodatabase from the .lpk file using a zip program like 7zip or WinRAR.The Town of Fuquay-Varina creates, maintains, and serves out a variety of utility information to the public, including its Potable Water System, Sanitary Sewer System, and Stormwater Collection System features. This is the same utility data displayed in our public web map. This utility data includes some features designated as 'private' that are not owned or maintained by the Town, but may be helpful for modeling and other informational purposes. Please pay particular attention to the terms of use and disclaimer associated with these data. Some data includes the use of Subtypes and Domains that may not translate well to Shapefile or GeoJSON downloads available through our Open Data site. Please beware the dangers of cartographic misrepresentation if you are unfamiliar with filtering and symbolizing data based on attributes. Water System Layers:Water LinesWater ValvesWater ManholesFire HydrantsFire Department ConnectionsWater MetersWater Meter VaultsRPZ (Backflow Preventers)Water TankWater Booster StationsHarnett County Water District AreaSewer System Layers:Gravity Sewer LinesForced Sewer LinesSewer ManholesSewer ValvesSewer CleanoutsSewer Pump StationsWastewater Treatment PlantsStormwater System Layers:Stormwater Lines (Pipes)Stormwater Points (Inlets/Outlets/Manholes)Stormwater Control Measure Points (SCM's, such as Wet Ponds / Retention Basins)

Data sets used to produce all maps for: Hennings et al. (2023) STOTEN Development of complex patterns of anthropogenic uplift and subsidence in the Delaware Basin of West Texas and southeast New Mexico, USA. Data is shared in the form of an ArcGIS LPK file. The LPK file will open in ArcGIS Pro and ArcMap, but will need to be uncompressed in order to be used in non-Esri software like QGIS

Sewer system valve points in Fuquay-Varina. These are primarily forced sewer pipe valves. Please note that ALL public utility data layers can be downloaded in one .lpk ArcGIS layer package file (click here), for use in any version of ArcGIS Pro or ArcMap software. You can also use QGIS, a powerful free open source software, but you must extract the file geodatabase from the .lpk file using a zip program like 7zip or WinRAR.The Town of Fuquay-Varina creates, maintains, and serves out a variety of utility information to the public, including its Potable Water System, Sanitary Sewer System, and Stormwater Collection System features. This is the same utility data displayed in our public web map. This utility data includes some features designated as 'private' that are not owned or maintained by the Town, but may be helpful for modeling and other informational purposes. Please pay particular attention to the terms of use and disclaimer associated with these data. Some data includes the use of Subtypes and Domains that may not translate well to Shapefile or GeoJSON downloads available through our Open Data site. Please beware the dangers of cartographic misrepresentation if you are unfamiliar with filtering and symbolizing data based on attributes. Water System Layers:Water LinesWater ValvesWater ManholesFire HydrantsFire Department ConnectionsWater MetersWater Meter VaultsRPZ (Backflow Preventers)Water TankWater Booster StationsHarnett County Water District AreaSewer System Layers:Gravity Sewer LinesForced Sewer LinesSewer ManholesSewer ValvesSewer CleanoutsSewer Pump StationsWastewater Treatment PlantsStormwater System Layers:Stormwater Lines (Pipes)Stormwater Points (Inlets/Outlets/Manholes)Stormwater Control Measure Points (SCM's, such as Wet Ponds / Retention Basins)

This map is designed to be used as a basemap by marine GIS professionals and as a reference map by anyone interested in ocean data. The base map includes bathymetry, marine water body names, undersea feature names, and derived depth values in meters. Land features include administrative boundaries, cities, inland waters, roads, overlaid on land cover and shaded relief imagery.The map was compiled from a variety of best available sources from several data providers, including General Bathymetric Chart of the Oceans GEBCO_08 Grid and IHO-IOC GEBCO Gazetteer of Undersea Feature Names August 2010 version(https://www.gebco.net) (subject to the finalization of data agreements), National Oceanic and Atmospheric Administration (NOAA), National Geographic, DeLorme, and Esri. The basemap was designed and developed by Esri.For more information, please visit the Ocean Basemap map service description. To add this map service into ArcGIS for Desktop, choose File > Add Data > Add Basemap in version 10 (or File > Add Data From ArcGIS Online in version 9.3) and select the 'Oceans' basemap. Alternatively, here's a layer package (LPK file) referencing the Ocean basemap that you can add into your map or globe. Tip: Here are some famous oceanic locations as they appear in this map. Each URL below launches this map at a particular location via parameters specified in the URL:Challenger DeepGalapagos IslandsHawaiian IslandsMaldive IslandsMariana TrenchTahitiQueen Charlotte SoundNotre Dame BayLabrador TroughNew York BightMassachusetts BayMississippi Sound

Proportional change in effective area of similar ecological environments 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 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

Lineage: Proportional change in the area of similar ecological environments was calculated using the highly parallel bespoke CSIRO Muru software running on a LINUX high-performance-computing cluster, taking GDM model transformed environmental grids as inputs. Proportional change was calculated by taking the area of baseline ecological environments similar to each present cell as the denominator and the area of present cells with their contribution scaled by the natural areas condition index (0 degraded to 1 intact) as the numerator. More detail of the calculations and methods are given in the document “9sMethodsSummary.pdf” provided with the data download. GDM Model: Generalised dissimilarity model of compositional turnover in reptile species for continental Australia at 9 second resolution using ALA data extracted 28 February 2014 (GDM: REP_r3_v2) Climate data. Models were built and projected using: a) 9-second gridded climatology for continental Australia 1976-2005: Summary variables with elevation and radiative adjustment b) 9-second gridded climatology for continental Australia 2036-2065 CanESM2 RCP 8.5 (CMIP5): Summary variables with elevation and radiative adjustment Natural Areas Layer (intact to degraded land) Australian Government Department of the Environment (2014) Natural areas of Australia - 100 metre (digital dataset and metadata). Available at http://www.environment.gov.au/metadataexplorer/explorer.jsp and up to date information for Western Australia were provided at 25m Albers projection were reprojected to GDA94, merged and aggregated to a continuous measure of proportion of intact area per grid cell at 9s.

Fire Department Connections (FDC's) points within Fuquay-Varina. These are primarily privately owned and maintained. Mapping of FDC's primarily began from 2015 and later from as-built information provided by new developments, so this should be considered a very limited dataset. Please note that ALL public utility data layers can be downloaded in one .lpk ArcGIS layer package file (click here), for use in any version of ArcGIS Pro or ArcMap software. You can also use QGIS, a powerful free open source software, but you must extract the file geodatabase from the .lpk file using a zip program like 7zip or WinRAR.The Town of Fuquay-Varina creates, maintains, and serves out a variety of utility information to the public, including its Potable Water System, Sanitary Sewer System, and Stormwater Collection System features. This is the same utility data displayed in our public web map. This utility data includes some features designated as 'private' that are not owned or maintained by the Town, but may be helpful for modeling and other informational purposes. Please pay particular attention to the terms of use and disclaimer associated with these data. Some data includes the use of Subtypes and Domains that may not translate well to Shapefile or GeoJSON downloads available through our Open Data site. Please beware the dangers of cartographic misrepresentation if you are unfamiliar with filtering and symbolizing data based on attributes. Water System Layers:Water LinesWater ValvesWater ManholesFire HydrantsFire Department ConnectionsWater MetersWater Meter VaultsRPZ (Backflow Preventers)Water TankWater Booster StationsHarnett County Water District AreaSewer System Layers:Gravity Sewer LinesForced Sewer LinesSewer ManholesSewer ValvesSewer CleanoutsSewer Pump StationsWastewater Treatment PlantsStormwater System Layers:Stormwater Lines (Pipes)Stormwater Points (Inlets/Outlets/Manholes)Stormwater Control Measure Points (SCM's, such as Wet Ponds / Retention Basins)

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 …Show full descriptionProportional 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 future (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: 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. 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 The metadata and files (if any) are available to the public.

This data is associated with the Nevada Play Fairway project and includes excel files containing raw 2-meter temperature data and corrections. GIS shapefiles and layer files contain ing location and attribute information for the data are included. Well data includes both deep and shallow TG holes, GIS shapefiles and layer files. Geochemistry data

Proportional change in effective area of similar ecological environments for Mammals as a function of land clearing and change in long term (30 year average) climates between the present (1990 …Show full descriptionProportional change in effective area of similar ecological environments for Mammals as a function of land clearing and change in long term (30 year average) climates between the present (1990 centred) 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: 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. 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 The metadata and files (if any) are available to the public.

Stormwater collection/conveyance point features in Fuquay-Varina (e.g. inlets and outlets, and stormwater manholes/junction boxes). Please note that many of the stormwater point features represent privately owned and maintained stormwater features, and these are essential for mapping and understanding the stormwater drainage network sub-systems at the neighborhood level. Please pay attention to the Subtype field to identify the different categories of public vs. private; inlet vs. outlet; and manhole types of stormwater features. Directionality (start vs. end vertices) of these line features reflects real world flow direction. The GIS data in the area of Downtown Fuquay-Varina has a lot of old and erroneous stormwater features. A project is currently underway to correct much of this inaccurate stormwater data. Please note that ALL public utility data layers can be downloaded in one .lpk ArcGIS layer package file (click here), for use in any version of ArcGIS Pro or ArcMap software. You can also use QGIS, a powerful free open source software, but you must extract the file geodatabase from the .lpk file using a zip program like 7zip or WinRAR.The Town of Fuquay-Varina creates, maintains, and serves out a variety of utility information to the public, including its Potable Water System, Sanitary Sewer System, and Stormwater Collection System features. This is the same utility data displayed in our public web map. This utility data includes some features designated as 'private' that are not owned or maintained by the Town, but may be helpful for modeling and other informational purposes. Please pay particular attention to the terms of use and disclaimer associated with these data. Some data includes the use of Subtypes and Domains that may not translate well to Shapefile or GeoJSON downloads available through our Open Data site. Please beware the dangers of cartographic misrepresentation if you are unfamiliar with filtering and symbolizing data based on attributes. Water System Layers:Water LinesWater ValvesWater ManholesFire HydrantsFire Department ConnectionsWater MetersWater Meter VaultsRPZ (Backflow Preventers)Water TankWater Booster StationsHarnett County Water District AreaSewer System Layers:Gravity Sewer LinesForced Sewer LinesSewer ManholesSewer ValvesSewer CleanoutsSewer Pump StationsWastewater Treatment PlantsStormwater System Layers:Stormwater Lines (Pipes)Stormwater Points (Inlets/Outlets/Manholes)Stormwater Control Measure Points (SCM's, such as Wet Ponds / Retention Basins)

This data is associated with the Nevada Play Fairway project and includes excel files containing raw 2-meter temperature data and corrections. GIS shapefiles and layer files contain ing location and attribute information for the data are included. Well data includes both deep and shallow TG holes, GIS shapefiles and layer files. Granite Springs Valley, Fireball Ridge, and Black Warrior well data

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 (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

Lineage: Need for assisted dispersal was calculated calculated using the highly parallel bespoke CSIRO Muru software running on a LINUX high-performance-computing cluster, taking GDM model transformed environmental grids as inputs. The distance to the nearest future cell with an ecological similarity > 0.5 to the present cell was calculated. More detail of the calculations and methods are given in the document “BiodiversityModellingMethodsSummary.pdf” provided with the data download. GDM Model: Generalised dissimilarity model of compositional turnover in mammal species for continental Australia at 9 second resolution using ALA data extracted 27 February 2014 (GDM: MAM_r2) Climate data. Models were built and projected using: a) 9-second gridded climatology for continental Australia 1976-2005: Summary variables with elevation and radiative adjustment b) 9-second gridded climatology for continental Australia 2036-2065 CAN ESM2 RCP 8.5 (CMIP5): Summary variables with elevation and radiative adjustment

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 centred) and projected future (2050 centred) under the CanESM2 model (RCP 8.5) based on Generalised Dissimilarity Modelling (GDM) of compositional turnover.

This metric describes the combined effects of climate change and land clearing on the area of similar environments to each grid cell as a proportion. Each cell is compared with a sample of 60,000 points in both the present uncleared landscape and an alternative scenario (either present with clearing, or future with clearing), and the pairwise similarities summed (e.g. a completely similar cell will contribute 1, a dissimilar cell 0, with a range of values in between). 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 Lineage: Proportional change in the area of similar ecological environments was calculated using the highly parallel bespoke CSIRO Muru software running on a LINUX high-performance-computing cluster, taking GDM model transformed environmental grids as inputs. Proportional change was calculated by taking the area of baseline ecological environments similar to each present cell as the denominator and the area of future degraded (based on Natural Areas Mask) ecological environments similar to each present cell as the numerator. In both cases, all land was assumed to be available for biodiversity (i.e. land degradation excluded). More detail of the calculations and methods are given in the document “9sMethodsSummary.pdf” provided with the data download. GDM Model:
Generalised dissimilarity model of compositional turnover in reptile species for continental Australia at 9 second resolution using ALA data extracted 28 February 2014 (GDM: REP_r3_v2) Climate data. Models were built and projected using: a) 9-second gridded climatology for continental Australia 1976-2005: Summary variables with elevation and radiative adjustment b) 9-second gridded climatology for continental Australia 2036-2065 CanESM2 RCP 8.5 (CMIP5): Summary variables with elevation and radiative adjustment Natural Areas Mask (intact/degraded land) Australian Government Department of the Environment (2014) Natural areas of Australia - 100 metre (digital dataset and metadata). Available at http://www.environment.gov.au/metadataexplorer/explorer.jsp and up to date information for Western Australia were provided at 25m Albers projection were reprojected to GDA94, merged and aggregated to a continuous measure of proportion of intact area per grid cell at 9s.

Proportional change in effective area of similar ecological environments for 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 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: Vascular Plants, M: Vascular Plants, R: Vascular Plants and V: vascular plants Lineage: Proportional change in the area of similar ecological environments was calculated using the highly parallel bespoke CSIRO Muru software running on a LINUX high-performance-computing cluster, taking GDM model transformed environmental grids as inputs. Proportional change was calculated by taking the area of baseline ecological environments similar to each present cell as the denominator and the area of future ecological environments similar to each present cell as the numerator. In both cases, all land was assumed to be available for biodiversity (i.e. land degradation excluded). More detail of the calculations and methods are given in the document “9sMethodsSummary.pdf” provided with the data download. GDM Model:
Generalised dissimilarity model of compositional turnover in vascular plant species for continental Australia at 9 second resolution using ANHAT data extracted 4 April 2013 (GDM: VAS_v5_r11) Climate data. Models were built and projected using: a) 9-second gridded climatology for continental Australia 1976-2005: Summary variables with elevation and radiative adjustment b) 9-second gridded climatology for continental Australia 2036-2065 CanESM2 RCP 8.5 (CMIP5): Summary variables with elevation and radiative adjustment

Disappearing ecological environments for 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 …Show full descriptionDisappearing ecological environments for 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 CanESM2 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: 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. ArcGIS layer package (.lpk): These packages contain can be unpacked by ArcGIS as a raster with associated legend. Additionally a short methods summary is provided in the file 9sMethodsSummary.pdf for further information. Layers in this 9s series use a consistent naming convention: BIOLOGICAL GROUP _ FROM BASE_ TO SCENARIO_ ANALYSIS e.g. A_90_CAN85_S or R_90_MIR85_L where BIOLOGICAL GROUP is A: Vascular Plants, M: Vascular Plants, R: Vascular Plants and V: vascular plants The metadata and files (if any) are available to the public.

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 potential 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 plants Lineage: Refugial potential index was calculated using the highly parallel bespoke CSIRO Muru software running on a LINUX high-performance-computing cluster, taking GDM model transformed environmental grids as inputs. The index of revegetation was calculated as the marginal gain from revegetation actions at a cleared location as a function of the area of similar ecological environments More detail of the calculations and methods are given in the document “BiodiversityModellingMethodsSummary.pdf” provided with the data download. GDM Model: Generalised dissimilarity model of compositional turnover in amphibian species for continental Australia at 9 second resolution using ALA data extracted 27 February 2014 (GDM: AMP_r2_PTS1) Climate data. Models were built and projected using: a) 9-second gridded climatology for continental Australia 1976-2005: Summary variables with elevation and radiative adjustment b) 9-second gridded climatology for continental Australia 2036-2065 MIROC5 RCP 8.5 (CMIP5): Summary variables with elevation and radiative adjustment

Novel ecological environments 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 model (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: amphibians, M: mammals, R: reptiles and V: vascular plants

Lineage: Novel ecological environments were calculated using the highly parallel bespoke CSIRO Muru software running on a LINUX high-performance-computing cluster, taking GDM model transformed environmental grids as inputs. The similarity of the most similar present cell to the future environment of each cell was calculated. More detail of the calculations and methods are given in the document “9sMethodsSummary.pdf” provided with the data download. GDM Model: Generalised dissimilarity model of compositional turnover in amphibian species for continental Australia at 9 second resolution using ALA data extracted 27 February 2014 (GDM: AMP_r2_PTS1) Climate data. Models were built and projected using: a) 9-second gridded climatology for continental Australia 1976-2005: Summary variables with elevation and radiative adjustment b) 9-second gridded climatology for continental Australia 2036-2065 CanESM2 RCP 8.5 (CMIP5): Summary variables with elevation and radiative adjustment

Proportional change in effective area of similar ecological environments 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 (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.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

Lineage: Proportional change in the area of similar ecological environments was calculated using the highly parallel bespoke CSIRO Muru software running on a LINUX high-performance-computing cluster, taking GDM model transformed environmental grids as inputs. Proportional change was calculated by taking the area of baseline ecological environments similar to each present cell as the denominator and the area of future ecological environments similar to each present cell as the numerator. In both cases, all land was assumed to be available for biodiversity (i.e. land degradation excluded).. More detail of the calculations and methods are given in the document “9sMethodsSummary.pdf” provided with the data download. GDM Model: Generalised dissimilarity model of compositional turnover in mammal species for continental Australia at 9 second resolution using ALA data extracted 26 February 2014 (GDM: MAM_r2) Climate data. Models were built and projected using: a) 9-second gridded climatology for continental Australia 1976-2005: Summary variables with elevation and radiative adjustment b) 9-second gridded climatology for continental Australia 2036-2065 MIROC5 RCP 8.5 (CMIP5): Summary variables with elevation and radiative adjustment

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 CanESM2 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

Lineage: Disappearing ecological environments were calculated using the highly parallel bespoke CSIRO Muru software running on a LINUX high-performance-computing cluster, taking GDM model transformed environmental grids as inputs. The similarity of the most similar future cell to the present environment of each cell was calculated. More detail of the calculations and methods are given in the document “9sMethodsSummary.pdf” provided with the data download. GDM Model:
Generalised dissimilarity model of compositional turnover in reptile species for continental Australia at 9 second resolution using ALA data extracted 28 February 2014 (GDM: REP_r3_v2) Climate data. Models were built and projected using: a) 9-second gridded climatology for continental Australia 1976-2005: Summary variables with elevation and radiative adjustment b) 9-second gridded climatology for continental Australia 2036-2065 CanESM2 RCP 8.5 (CMIP5): Summary variables with elevation and radiative adjustment

Spatial data to support the article 'Shoreline change on a tropical beach: the influence of beachrock and shore protection structures' that describes historical erosion and the effects of coastal structures and erosion abatement measures for Seven Mile Beach, Grand Cayman, Cayman Islands. This is largely data that was derived using the ArcGIS extension Digital Shoreline Analysis System (DSAS) https://www.usgs.gov/centers/whcmsc/science/digital-shoreline-analysis-system-dsas As the output of the DSAS extension are symbolized feature classes, an ArcGIS layer package (.lpk) is included. There is also a zip file containing other spatial data in shapefile format.