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Variables included are monthly total precipitation, and monthly mean, minimum and maximum temperature, and 19 derived bioclimatic variables.\r\n\r\nThe WorldClim interpolated climate layers were made using:\r\n    * Major climate databases compiled by the Global Historical Climatology Network (GHCN), the FAO, the WMO, the International Center for Tropical Agriculture (CIAT), R-HYdronet, and a number of additional minor databases for Australia, New Zealand, the Nordic European Countries, Ecuador, Peru, Bolivia, among others.\r\n    * The SRTM elevation database (aggregeated to 30 arc-seconds, 1 km)\r\n    * The ANUSPLIN software. ANUSPLIN is a program for interpolating noisy multi-variate data using thin plate smoothing splines. We used latitude, longitude, and elevation as independent variables.","maxlatitude":90.0,"classification1":"Climate","respparty_role":"custodian","mddatest":"2010-07","licence_level":"1","id":798},{"lookuptablepath":"","licence_link":"http://www.worldclim.org/current","enabled":true,"displayname":"WorldClim: Precipitation - warmest quarter","metadatapath":"https://gist.github.com/tucotuco/1152668","source":"WorldClim","name":"worldclim_bio_18","uid":"797","maxlongitude":180.0,"dt_added":1308837600000,"pid":"","citation_date":"","path":"/mnt/transfer/worldclim/bio_18.tif","minlongitude":-180.0,"environmentalvalueunits":"mm","path_orig":"layer/worldclim_bio_18","mdhrlv":"","scale":"0.01 degree (~1km)","classification2":"Precipitation","minlatitude":-60.0,"keywords":"rain, bio18","licence_notes":"This dataset is freely available for academic and other non-commercial use. 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Variables included are monthly total precipitation, and monthly mean, minimum and maximum temperature, and 19 derived bioclimatic variables.\r\n\r\nThe WorldClim interpolated climate layers were made using:\r\n    * Major climate databases compiled by the Global Historical Climatology Network (GHCN), the FAO, the WMO, the International Center for Tropical Agriculture (CIAT), R-HYdronet, and a number of additional minor databases for Australia, New Zealand, the Nordic European Countries, Ecuador, Peru, Bolivia, among others.\r\n    * The SRTM elevation database (aggregeated to 30 arc-seconds, 1 km)\r\n    * The ANUSPLIN software. ANUSPLIN is a program for interpolating noisy multi-variate data using thin plate smoothing splines. 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We used latitude, longitude, and elevation as independent variables.","maxlatitude":90.0,"classification1":"Climate","keywords":"bio10","respparty_role":"custodian","mddatest":"2010-07","licence_level":"1","displaypath":"https://spatial.ala.org.au/geoserver/gwc/service/wms?service=WMS&version=1.1.0&request=GetMap&layers=ALA:worldclim_bio_10&format=image/png&styles=","id":792},{"description":"Mean Temperature of Wettest Quarter","lookuptablepath":"","licence_link":"http://www.worldclim.org/current","enabled":true,"metadatapath":"https://gist.github.com/tucotuco/1152668","source":"WorldClim","path_orig":"layer/worldclim_bio_8","maxlongitude":180.0,"dt_added":1308837600000,"pid":"","citation_date":"","displayname":"WorldClim: Temperature - wettest quarter mean","minlongitude":-180.0,"displaypath":"https://spatial.ala.org.au/geoserver/gwc/service/wms?service=WMS&version=1.1.0&request=GetMap&layers=ALA:worldclim_bio_8&format=image/png&styles=","path":"/mnt/transfer/worldclim/bio_8.tif","mdhrlv":"","scale":"0.01 degree (~1km)","environmentalvaluemin":"-285","minlatitude":-60.0,"uid":"784","licence_notes":"This dataset is freely available for academic and other non-commercial use. Redistribution, or commercial use, is not allowed without prior permission.","environmentalvalueunits":"degrees C * 10","datalang":"eng","source_link":"http://www.worldclim.org/","environmentalvaluemax":"378","path_1km":"","type":"Environmental","domain":"Terrestrial","classification2":"Temperature","notes":"(From http://www.worldclim.org/methods) - For a complete description, see:\r\n\r\nHijmans, R.J., S.E. Cameron, J.L. Parra, P.G. Jones and A. Jarvis, 2005. Very high resolution interpolated climate surfaces for global land areas. International Journal of Climatology 25: 1965-1978.\r\n\r\nThe data layers were generated through interpolation of average monthly climate data from weather stations on a 30 arc-second resolution grid (often referred to as 1 km2 resolution). Variables included are monthly total precipitation, and monthly mean, minimum and maximum temperature, and 19 derived bioclimatic variables.\r\n\r\nThe WorldClim interpolated climate layers were made using:\r\n    * Major climate databases compiled by the Global Historical Climatology Network (GHCN), the FAO, the WMO, the International Center for Tropical Agriculture (CIAT), R-HYdronet, and a number of additional minor databases for Australia, New Zealand, the Nordic European Countries, Ecuador, Peru, Bolivia, among others.\r\n    * The SRTM elevation database (aggregeated to 30 arc-seconds, 1 km)\r\n    * The ANUSPLIN software. ANUSPLIN is a program for interpolating noisy multi-variate data using thin plate smoothing splines. We used latitude, longitude, and elevation as independent variables.","maxlatitude":90.0,"classification1":"Climate","respparty_role":"custodian","mddatest":"2010-07","licence_level":"1","keywords":"rain, precipitation, bio08","name":"worldclim_bio_8","id":784},{"lookuptablepath":"","licence_link":"http://www.worldclim.org/current","enabled":true,"name":"worldclim_bio_5","metadatapath":"https://gist.github.com/tucotuco/1152668","source":"WorldClim","maxlongitude":180.0,"path_orig":"layer/worldclim_bio_5","dt_added":1308837600000,"pid":"","displayname":"WorldClim: Temperature - warmest month max","citation_date":"","displaypath":"https://spatial.ala.org.au/geoserver/gwc/service/wms?service=WMS&version=1.1.0&request=GetMap&layers=ALA:worldclim_bio_5&format=image/png&styles=","minlongitude":-180.0,"mdhrlv":"","environmentalvaluemin":"-96","keywords":"bio05","scale":"0.01 degree (~1km)","path":"/mnt/transfer/worldclim/bio_5.tif","minlatitude":-60.0,"licence_notes":"This dataset is freely available for academic and other non-commercial use. Redistribution, or commercial use, is not allowed without prior permission.","description":"Max Temperature of Warmest Month","environmentalvalueunits":"degrees C * 10","uid":"789","datalang":"eng","source_link":"http://www.worldclim.org/","path_1km":"","type":"Environmental","domain":"Terrestrial","classification2":"Temperature","notes":"(From http://www.worldclim.org/methods) - For a complete description, see:\r\n\r\nHijmans, R.J., S.E. Cameron, J.L. Parra, P.G. Jones and A. Jarvis, 2005. Very high resolution interpolated climate surfaces for global land areas. International Journal of Climatology 25: 1965-1978.\r\n\r\nThe data layers were generated through interpolation of average monthly climate data from weather stations on a 30 arc-second resolution grid (often referred to as 1 km2 resolution). Variables included are monthly total precipitation, and monthly mean, minimum and maximum temperature, and 19 derived bioclimatic variables.\r\n\r\nThe WorldClim interpolated climate layers were made using:\r\n    * Major climate databases compiled by the Global Historical Climatology Network (GHCN), the FAO, the WMO, the International Center for Tropical Agriculture (CIAT), R-HYdronet, and a number of additional minor databases for Australia, New Zealand, the Nordic European Countries, Ecuador, Peru, Bolivia, among others.\r\n    * The SRTM elevation database (aggregeated to 30 arc-seconds, 1 km)\r\n    * The ANUSPLIN software. ANUSPLIN is a program for interpolating noisy multi-variate data using thin plate smoothing splines. We used latitude, longitude, and elevation as independent variables.","environmentalvaluemax":"490","maxlatitude":90.0,"classification1":"Climate","respparty_role":"custodian","mddatest":"2010-07","licence_level":"1","id":789},{"lookuptablepath":"","licence_link":"http://www.worldclim.org/current","name":"worldclim_bio_4","enabled":true,"metadatapath":"https://gist.github.com/tucotuco/1152668","source":"WorldClim","maxlongitude":180.0,"dt_added":1308837600000,"pid":"","citation_date":"","keywords":"range, mean, ratio, bio04","environmentalvalueunits":"standard deviation (degrees C * 10) * 100","minlongitude":-180.0,"environmentalvaluemax":"22721","mdhrlv":"","path":"/mnt/transfer/worldclim/bio_4.tif","scale":"0.01 degree (~1km)","minlatitude":-60.0,"uid":"783","licence_notes":"This dataset is freely available for academic and other non-commercial use. Redistribution, or commercial use, is not allowed without prior permission.","displaypath":"https://spatial.ala.org.au/geoserver/gwc/service/wms?service=WMS&version=1.1.0&request=GetMap&layers=ALA:worldclim_bio_4&format=image/png&styles=","description":"Temperature Seasonality","datalang":"eng","source_link":"http://www.worldclim.org/","environmentalvaluemin":"62","path_1km":"","type":"Environmental","domain":"Terrestrial","classification2":"Temperature","notes":"(From http://www.worldclim.org/methods) - For a complete description, see:\r\n\r\nHijmans, R.J., S.E. Cameron, J.L. Parra, P.G. Jones and A. Jarvis, 2005. Very high resolution interpolated climate surfaces for global land areas. International Journal of Climatology 25: 1965-1978.\r\n\r\nThe data layers were generated through interpolation of average monthly climate data from weather stations on a 30 arc-second resolution grid (often referred to as 1 km2 resolution). Variables included are monthly total precipitation, and monthly mean, minimum and maximum temperature, and 19 derived bioclimatic variables.\r\n\r\nThe WorldClim interpolated climate layers were made using:\r\n    * Major climate databases compiled by the Global Historical Climatology Network (GHCN), the FAO, the WMO, the International Center for Tropical Agriculture (CIAT), R-HYdronet, and a number of additional minor databases for Australia, New Zealand, the Nordic European Countries, Ecuador, Peru, Bolivia, among others.\r\n    * The SRTM elevation database (aggregeated to 30 arc-seconds, 1 km)\r\n    * The ANUSPLIN software. ANUSPLIN is a program for interpolating noisy multi-variate data using thin plate smoothing splines. We used latitude, longitude, and elevation as independent variables.","maxlatitude":90.0,"classification1":"Climate","respparty_role":"custodian","path_orig":"layer/worldclim_bio_4","mddatest":"2010-07","licence_level":"1","displayname":"WorldClim: Temperature - seasonality","id":783},{"maxlatitude":-9.0,"lookuptablepath":"","enabled":true,"uid":"899","pid":"","keywords":"diversity, occurrence, sample, average","citation_date":"","path_orig":"layer/srichness","minlatitude":-43.8,"domain":"Terrestrial,Marine","name":"srichness","environmentalvaluemax":"7791","mdhrlv":"","description":"Species Richness","respparty_role":"","licence_link":"","scale":"0.01 degree (~1km)","displayname":"Species Richness","environmentalvaluemin":"0","mddatest":"","maxlongitude":153.64,"licence_notes":"","source_link":"","path_1km":"","notes":"Species Richness is derived by applying a moving average to all point occurrences held by the Atlas of Living Australia. If all occurrences are mapped (over terrestrial and marine areas), a moving average is like moving a window with many panes over the area, noting the number of differences species in each pane and placing the average of all panes at the centre pane. The window is moved to the next sample location and the process repeated. Species Richness uses a 9 by 9 pane window where each pane is 0.01 degrees latitude/longitude. Each move of the window is 0.01 degrees.\r\n\r\nScope: World","type":"Environmental","displaypath":"https://spatial.ala.org.au/geoserver/gwc/service/wms?service=WMS&version=1.1.0&request=GetMap&layers=ALA:srichness&format=image/png&styles=","classification2":"","minlongitude":112.9,"datalang":"","licence_level":"1","dt_added":1439301600000,"classification1":"Biodiversity","environmentalvalueunits":"frequency","path":"/data/ala/data/source/occurrence_layers/layer_species_av_1.tif","metadatapath":"http://www.ala.org.au/","source":"ALA-SPATIAL","id":899},{"lookuptablepath":"","licence_link":"http://www.worldclim.org/current","enabled":true,"metadatapath":"https://gist.github.com/tucotuco/1152668","source":"WorldClim","name":"worldclim_bio_6","maxlongitude":180.0,"displayname":"WorldClim: Temperature - coldest month min","environmentalvaluemin":"-573","path_orig":"layer/worldclim_bio_6","dt_added":1308837600000,"pid":"","citation_date":"","minlongitude":-180.0,"displaypath":"https://spatial.ala.org.au/geoserver/gwc/service/wms?service=WMS&version=1.1.0&request=GetMap&layers=ALA:worldclim_bio_6&format=image/png&styles=","mdhrlv":"","keywords":"bio06","scale":"0.01 degree (~1km)","uid":"781","minlatitude":-60.0,"licence_notes":"This dataset is freely available for academic and other non-commercial use. Redistribution, or commercial use, is not allowed without prior permission.","description":"Min Temperature of Coldest Month","environmentalvalueunits":"degrees C * 10","datalang":"eng","source_link":"http://www.worldclim.org/","environmentalvaluemax":"258","path_1km":"","type":"Environmental","domain":"Terrestrial","classification2":"Temperature","notes":"(From http://www.worldclim.org/methods) - For a complete description, see:\r\n\r\nHijmans, R.J., S.E. Cameron, J.L. Parra, P.G. Jones and A. Jarvis, 2005. Very high resolution interpolated climate surfaces for global land areas. International Journal of Climatology 25: 1965-1978.\r\n\r\nThe data layers were generated through interpolation of average monthly climate data from weather stations on a 30 arc-second resolution grid (often referred to as 1 km2 resolution). Variables included are monthly total precipitation, and monthly mean, minimum and maximum temperature, and 19 derived bioclimatic variables.\r\n\r\nThe WorldClim interpolated climate layers were made using:\r\n    * Major climate databases compiled by the Global Historical Climatology Network (GHCN), the FAO, the WMO, the International Center for Tropical Agriculture (CIAT), R-HYdronet, and a number of additional minor databases for Australia, New Zealand, the Nordic European Countries, Ecuador, Peru, Bolivia, among others.\r\n    * The SRTM elevation database (aggregeated to 30 arc-seconds, 1 km)\r\n    * The ANUSPLIN software. ANUSPLIN is a program for interpolating noisy multi-variate data using thin plate smoothing splines. We used latitude, longitude, and elevation as independent variables.","maxlatitude":90.0,"classification1":"Climate","respparty_role":"custodian","mddatest":"2010-07","licence_level":"1","path":"/mnt/transfer/worldclim/bio_6.tif","id":781},{"maxlatitude":-9.0,"enabled":true,"notes":"Data derived using ANUCLIM v6 (beta) with the new set of climate surfaces (centred on 1990), by Dr. Kristen Williams.","environmentalvalueunits":"degrees C","dt_added":1308837600000,"path":"/data/ala/data/source/bioclim1990-asc/bio9.tif","uid":"875","licence_notes":"Permission to re-distribute ANUCLIM outputs should be obtained from Prof. Michael Hutchinson - http://fennerschool.anu.edu.au/publications/software/","source_link":"http://www.csiro.au/Organisation-Structure/Divisions/Ecosystem-Sciences.aspx","displayname":"Temperature - driest quarter mean (Bio09)","displaypath":"https://spatial.ala.org.au/geoserver/gwc/service/wms?service=WMS&version=1.1.0&request=GetMap&layers=ALA:bioclim_bio9&format=image/png&styles=","path_orig":"layer/bioclim_bio9","minlatitude":-43.8,"name":"bioclim_bio9","metadatapath":"http://fennerschool.anu.edu.au/publications/software/","environmentalvaluemax":"28.2999992370605","source":"CSIRO Ecosystem Sciences","scale":"0.01 degree (~1km)","maxlongitude":153.64,"datalang":"eng","type":"Environmental","domain":"Terrestrial","environmentalvaluemin":"2.5","classification2":"Temperature","description":"Temperature - driest quarter mean (Bio09)","minlongitude":112.9,"classification1":"Climate","mddatest":"2010-08","licence_level":"1","citation_date":"2008-02","id":875},{"maxlatitude":-9.0,"enabled":true,"uid":"894","environmentalvaluemin":"15.3999996185303","notes":"Data derived using ANUCLIM v6 (beta) with the new set of climate surfaces (centred on 1990), by Dr. Kristen Williams.","displaypath":"https://spatial.ala.org.au/geoserver/gwc/service/wms?service=WMS&version=1.1.0&request=GetMap&layers=ALA:bioclim_bio26&format=image/png&styles=","dt_added":1308837600000,"environmentalvaluemax":"28.3999996185303","licence_notes":"Permission to re-distribute ANUCLIM outputs should be obtained from Prof. Michael Hutchinson - http://fennerschool.anu.edu.au/publications/software/","source_link":"http://www.csiro.au/Organisation-Structure/Divisions/Ecosystem-Sciences.aspx","minlatitude":-43.8,"metadatapath":"http://fennerschool.anu.edu.au/publications/software/","name":"bioclim_bio26","source":"CSIRO Ecosystem Sciences","environmentalvalueunits":"MJ/m2/day","keywords":"solar, sun","description":"Radiation - warmest quarter  (Bio26)","displayname":"Radiation - warmest quarter  (Bio26)","scale":"0.01 degree (~1km)","maxlongitude":153.64,"datalang":"eng","classification2":"Solar radiation","type":"Environmental","domain":"Terrestrial","minlongitude":112.9,"path":"/data/ala/data/source/bioclim1990-asc/bio26.tif","classification1":"Climate","path_orig":"layer/bioclim_bio26","mddatest":"2010-08","licence_level":"1","citation_date":"2008-02","id":894},{"maxlatitude":-9.0,"enabled":true,"description":"Precipitation - coldest quarter (Bio19)","notes":"Data derived using ANUCLIM v6 (beta) with the new set of climate surfaces (centred on 1990), by Dr. Kristen Williams.","dt_added":1308837600000,"licence_notes":"Permission to re-distribute ANUCLIM outputs should be obtained from Prof. Michael Hutchinson - http://fennerschool.anu.edu.au/publications/software/","source_link":"http://www.csiro.au/Organisation-Structure/Divisions/Ecosystem-Sciences.aspx","minlatitude":-43.8,"metadatapath":"http://fennerschool.anu.edu.au/publications/software/","environmentalvalueunits":"mm","source":"CSIRO Ecosystem Sciences","path_orig":"layer/bioclim_bio19","path":"/data/ala/data/source/bioclim1990-asc/bio19.tif","scale":"0.01 degree (~1km)","classification2":"Precipitation","environmentalvaluemin":"2","uid":"863","displaypath":"https://spatial.ala.org.au/geoserver/gwc/service/wms?service=WMS&version=1.1.0&request=GetMap&layers=ALA:bioclim_bio19&format=image/png&styles=","keywords":"rain","maxlongitude":153.64,"datalang":"eng","type":"Environmental","domain":"Terrestrial","environmentalvaluemax":"1044","minlongitude":112.9,"classification1":"Climate","mddatest":"2010-08","name":"bioclim_bio19","displayname":"Precipitation - coldest quarter (Bio19)","licence_level":"1","citation_date":"2008-02","id":863},{"maxlatitude":-9.0,"enabled":true,"environmentalvaluemax":"2817","notes":"Data derived using ANUCLIM v6 (beta) with the new set of climate surfaces (centred on 1990), by Dr. Kristen Williams.","dt_added":1308837600000,"licence_notes":"Permission to re-distribute ANUCLIM outputs should be obtained from Prof. Michael Hutchinson - http://fennerschool.anu.edu.au/publications/software/","description":"Precipitation - wettest quarter (Bio16)","source_link":"http://www.csiro.au/Organisation-Structure/Divisions/Ecosystem-Sciences.aspx","minlatitude":-43.8,"metadatapath":"http://fennerschool.anu.edu.au/publications/software/","environmentalvaluemin":"46","environmentalvalueunits":"mm","source":"CSIRO Ecosystem Sciences","path_orig":"layer/bioclim_bio16","displaypath":"https://spatial.ala.org.au/geoserver/gwc/service/wms?service=WMS&version=1.1.0&request=GetMap&layers=ALA:bioclim_bio16&format=image/png&styles=","scale":"0.01 degree (~1km)","classification2":"Precipitation","path":"/data/ala/data/source/bioclim1990-asc/bio16.tif","keywords":"rain","uid":"886","maxlongitude":153.64,"datalang":"eng","type":"Environmental","domain":"Terrestrial","displayname":"Precipitation - wettest quarter (Bio16)","name":"bioclim_bio16","minlongitude":112.9,"classification1":"Climate","mddatest":"2010-08","licence_level":"1","citation_date":"2008-02","id":886},{"description":"Elevation (metres above mean sea level)","lookuptablepath":"","enabled":true,"uid":"674","environmentalvaluemin":"-15","pid":"","maxlongitude":157.23401,"metadatapath":"http://www.ga.gov.au/nmd/products/digidat/dem_9s.jsp","environmentalvaluemax":"2137","displayname":"Elevation ","licence_link":"http://adl.brs.gov.au/anrdl/licence/AuGovBRS.txt, http://adl.brs.gov.au/anrdl/metadata_files/pb_dpk09g9abl_01411a02.xml","source":"GA","minlongitude":109.49867,"keywords":"height, dem","path_orig":"layer/elevation","dt_added":1317646800000,"name":"elevation","mdhrlv":"","environmentalvalueunits":"m","respparty_role":"","source_link":"http://www.daff.gov.au/abares/data/mcass","scale":"0.01 degree (~1km)","classification1":"Topography","citation_date":"2001","extents":"","datalang":"eng","path":"/mnt/transfer/MCAS_1k_Datapack/Land/elevation.tif","path_1km":"","type":"Environmental","domain":"Terrestrial","classification2":"","maxlatitude":-8.19539,"minlatitude":-44.38263,"displaypath":"https://spatial.ala.org.au/geoserver/gwc/service/wms?service=WMS&version=1.1.0&request=GetMap&layers=ALA:elevation&format=image/png&styles=","mddatest":"2009-08","licence_level":"2","notes":"Derived from the 9 second digital elevation data version 3 by integerising using ArcGIS 9.3. This dataset was created in 2008 from DEM data current for 2001.","licence_notes":"Copyright Commonwealth of Australia 2009The Commonwealth gives no warranty regarding the Products accuracy, completeness, currency or suitability for any particular purpose. Visit the Bureau of Rural Sciences website (http://adl.brs.gov.au/) to access the most current version of the Product.","id":674},{"name":"worldclim_bio_3","lookuptablepath":"","licence_link":"http://www.worldclim.org/current","enabled":true,"metadatapath":"https://gist.github.com/tucotuco/1152668","source":"WorldClim","maxlongitude":180.0,"dt_added":1308837600000,"pid":"","path":"/mnt/transfer/worldclim/bio_3.tif","citation_date":"","environmentalvalueunits":"%","minlongitude":-180.0,"mdhrlv":"","description":"Isothermality","displayname":"WorldClim: Temperature - isothermality","uid":"790","scale":"0.01 degree (~1km)","environmentalvaluemin":"7","minlatitude":-60.0,"extents":"","licence_notes":"This dataset is freely available for academic and other non-commercial use. Redistribution, or commercial use, is not allowed without prior permission.","displaypath":"https://spatial.ala.org.au/geoserver/gwc/service/wms?service=WMS&version=1.1.0&request=GetMap&layers=ALA:worldclim_bio_3&format=image/png&styles=","environmentalvaluemax":"96","datalang":"eng","source_link":"http://www.worldclim.org/","path_1km":"","type":"Environmental","domain":"Terrestrial","classification2":"Temperature","notes":"(From http://www.worldclim.org/methods) - For a complete description, see:\r\n\r\nHijmans, R.J., S.E. Cameron, J.L. Parra, P.G. Jones and A. Jarvis, 2005. Very high resolution interpolated climate surfaces for global land areas. International Journal of Climatology 25: 1965-1978.\r\n\r\nThe data layers were generated through interpolation of average monthly climate data from weather stations on a 30 arc-second resolution grid (often referred to as 1 km2 resolution). Variables included are monthly total precipitation, and monthly mean, minimum and maximum temperature, and 19 derived bioclimatic variables.\r\n\r\nThe WorldClim interpolated climate layers were made using:\r\n    * Major climate databases compiled by the Global Historical Climatology Network (GHCN), the FAO, the WMO, the International Center for Tropical Agriculture (CIAT), R-HYdronet, and a number of additional minor databases for Australia, New Zealand, the Nordic European Countries, Ecuador, Peru, Bolivia, among others.\r\n    * The SRTM elevation database (aggregeated to 30 arc-seconds, 1 km)\r\n    * The ANUSPLIN software. ANUSPLIN is a program for interpolating noisy multi-variate data using thin plate smoothing splines. We used latitude, longitude, and elevation as independent variables.","maxlatitude":90.0,"classification1":"Climate","keywords":"diurnal, day, daily, season, ratio, bio03","path_orig":"layer/worldclim_bio_3","respparty_role":"custodian","mddatest":"2010-07","licence_level":"2","id":790},{"enabled":true,"environmentalvaluemax":"9.0","maxlongitude":180.0,"notes":"Collection description\r\nMrVBF is a topographic index designed to identify areas of deposited material at a range of scales based on the observations that valley bottoms are low and flat relative to their surroundings and that large valley bottoms are flatter than smaller ones. Zero values indicate erosional terrain with values 1 and larger indicating progressively larger areas of deposition. There is some evidence that MrVBF values correlate with depth of deposited material.\r\n\r\nThis collection includes 1 arc-second and 3 arc-second resolution versions of MrVBF.\r\n\r\nThe 3 arc-second resolution product was generated from the 1 arc-second MrVBF product and masked by the 3” water and ocean mask datasets.\r\n\r\nStart date\r\n2000-02-11\r\n\r\nEnd date\r\n2000-02-22\r\n\r\nAccess\r\nThe metadata and files (if any) are available to the public.\r\n\r\nLineage\r\nSource data\r\n1. 1 arc-second SRTM-derived Smoothed Digital Elevation Model (DEM-S; ANZCW0703014016).\r\n2. The 1 arc-second MrVBF product\r\n3. 3 arc-second resolution SRTM water body and ocean mask datasets\r\n\r\nMrVBF calculation\r\nThe MrVBF method is described in Gallant and Dowling (2003). It is based on slope and position in landscape (ranking within a 3- or 6-cell circular window) calculated from the original DEM and progressively generalised DEMs. The algorithm used to create this product is version 6g-a5, which is slightly different to that in the original paper.\r\n\r\nEach value of MrVBF is associated with a particular scale and slope threshold. For each successive value the slope threshold halves and the scale triples. At each scale a location is considered erosional if it is high (ranked above the majority of the surrounding cells) or steep (slope greater than the threshold), and depositional otherwise. The largest value takes precedence at each location, so a value of zero indicates the site is considered to be erosional at all scales.\r\n\r\nValue Threshold Resolution Interpretation\r\nslope (%) (approx)\r\n0 30 m Erosional\r\n1 16 30 Small hillside deposit\r\n2 8 30 Narrow valley floor\r\n3 4 90\r\n4 2 270 Valley floor\r\n5 1 800 Extensive valley floor\r\n6 0.5 2.4 km\r\n7 0.25 7.2 km Depositional basin\r\n8 0.125 22 km\r\n9 0.0625 66 km Extensive depositional basin\r\n\r\nThe 3 arc-second version of MrVBF was derived from the 1 arc-second MrVBF using the median value in each 3 x 3 group of 1 arc-second grid cells.\r\n\r\nMrVBF has been used with topographic wetness index (TWI) to predict soil depths; see McKenzie, Gallant and Gregory (2003) for details.\r\n\r\nGallant, J.C. and Dowling T.I. (2003) A multiresolution index of valley bottom flatness for mapping depositional areas. Water Resources Research 39(12) 1347-1360.\r\n\r\nMcKenzie, N.J., Gallant, J.C. and Gregory, L. (2003) Estimating water storage capacities in soil at catchment scales. Cooperative Research Centre for Catchment Hydrology Technical Report 03/3.","source":"CSIRO Data Access Portal","source_link":"https://data.csiro.au/collection/csiro:5681v3","dt_added":1718580090467,"minlongitude":-180.0,"path_orig":"layer/multires_valley_bottom_flatness_index_2000_3s","displayname":"Multi Resolution Valley Bottom Flatness (MRVBF)","classification1":"Topography","environmentalvaluemin":"0.0","description":"MrVBF is a topographic index designed to identify areas of deposited material at a range of scales based on the observations that valley bottoms are low and flat relative to their surroundings and that large valley bottoms are flatter than smaller ones. Zero values indicate erosional terrain with values 1 and larger indicating progressively larger areas of deposition. There is some evidence that MrVBF values correlate with depth of deposited material.","datalang":"eng","licence_link":"https://creativecommons.org/licenses/by/4.0/","type":"Environmental","domain":"Terrestrial","respparty_role":"Distributor","licence_notes":"CC-BY 4.0 International","maxlatitude":90.0,"metadatapath":"https://data.csiro.au/collection/csiro:5681v3","citation_date":"2601-04-04","mddatest":"2016-04-04","minlatitude":-90.0,"licence_level":"1","name":"multires_valley_bottom_flatness_index_2000_3s","displaypath":"https://spatial.ala.org.au/geoserver/gwc/service/wms?service=WMS&version=1.1.0&request=GetMap&layers=ALA:multires_valley_bottom_flatness_index_2000_3s&format=image/png&styles=","keywords":"ridge, elevation, topography, mrvbf","environmentalvalueunits":"Index","id":11098},{"keywords":"ridge, elevation, topography, mrrtf","enabled":true,"environmentalvaluemax":"9.0","maxlongitude":180.0,"source":"CSIRO Data Access Portal","name":"multires_ridgetop_flatness_index_2000_3s","dt_added":1718580084858,"metadatapath":"https://data.csiro.au/collection/csiro:6239v2","displaypath":"https://spatial.ala.org.au/geoserver/gwc/service/wms?service=WMS&version=1.1.0&request=GetMap&layers=ALA:multires_ridgetop_flatness_index_2000_3s&format=image/png&styles=","citation_date":"2016-03-17","notes":"Collection description\r\nMrRTF is a topographic index designed to identify high flat areas at a range of scales. It complements the MrVBF index that is designed to identify areas of deposited material in flat valley bottoms. Unlike MrVBF, the MrRTF index does not have a clear link to landform processes but it has been found to be a useful adjunct to MrVBF in landform classification. Zero values indicate areas that are steep or low, with values 1 and larger indicating progressively larger areas of high flat land.\r\n\r\nThis collection includes MrRTF data at 1 arc-second and 3 arc-second resolutions.\r\n\r\nThe 3 arc-second resolution product was generated from the 1 arc-second MrRTF product and masked by the 3” water and ocean mask datasets.\r\n\r\nStart date\r\n2000-02-11\r\n\r\nEnd date\r\n2000-02-22\r\n\r\nAccess\r\nThe metadata and files (if any) are available to the public.\r\n\r\nLineage\r\nSource data\r\n1. The 1 arc-second SRTM DEM-S (ANZCW0703014016)\r\n2. The 1 arc-second MrRTF product\r\n3. 3 arc-second resolution SRTM water body and ocean mask datasets\r\n\r\nMrRTF calculation\r\nThe MrRTF and MrVBF method is described in Gallant and Dowling (2003). It is based on slope and position in landscape (ranking within a 3- or 6-cell circular window) calculated from the original DEM and progressively generalised DEMs. The algorithm used to create this product is version 6g-a5, which is slightly different to that in the original paper.\r\n\r\nEach value of MrRTF is associated with a particular scale and slope threshold. For each successive value the slope threshold halves and the scale triples. At each scale a location is assigned the value for that scale if it is sufficiently high (ranked above the majority of the surrounding cells) and flat (slope less than the threshold), and zero otherwise. The largest value takes precedence at each location.\r\n\r\nValue Threshold Resolution\r\nslope (%) (approx)\r\n0 30 m\r\n1 16 30\r\n2 8 30\r\n3 4 90\r\n4 2 270\r\n5 1 800\r\n6 0.5 2.4 km\r\n7 0.25 7.2 km\r\n8 0.125 22 km\r\n9 0.0625 66 km\r\n\r\nThe 3 arc-second version of MrRTF was derived from the 1 arc-second MrRTF using the median value in each 3 x 3 group of 1 arc-second cells.\r\n\r\n\r\nGallant, J.C. and Dowling T.I. (2003) A multiresolution index of valley bottom flatness for mapping depositional areas. Water Resources Research 39(12) 1347-1360.","minlongitude":-180.0,"classification1":"Topography","environmentalvaluemin":"0.0","datalang":"eng","description":"MrRTF is a topographic index designed to identify high flat areas at a range of scales. It complements the MrVBF index that is designed to identify areas of deposited material in flat valley bottoms. Unlike \r\nMrVBF, the MrRTF index does not have a clear link to landform processes but it has been found to be a useful adjunct to MrVBF in landform classification. Zero values indicate areas that are steep or low, with values 1 and larger indicating progressively larger areas of high flat land.","displayname":"Multi Resolution Ridge Top Flatness (MRRTF)","licence_link":"https://creativecommons.org/licenses/by/4.0/","type":"Environmental","domain":"Terrestrial","respparty_role":"Distributor","licence_notes":"CC-BY 4.0 International","source_link":"https://data.csiro.au/collection/csiro:6239v2","maxlatitude":90.0,"path_orig":"layer/multires_ridgetop_flatness_index_2000_3s","minlatitude":-90.0,"licence_level":"1","mddatest":"2016-03-17","environmentalvalueunits":"Index","id":11096},{"path_orig":"layer/bioclim_bio7","maxlatitude":-9.0,"enabled":true,"notes":"Data derived using ANUCLIM v6 (beta) with the new set of climate surfaces (centred on 1990), by Dr. Kristen Williams.","environmentalvalueunits":"degrees C","description":"Temperature - annual range (Bio07)","dt_added":1308837600000,"licence_notes":"Permission to re-distribute ANUCLIM outputs should be obtained from Prof. Michael Hutchinson - 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seasonality (Bio15)","dt_added":1308837600000,"licence_notes":"Permission to re-distribute ANUCLIM outputs should be obtained from Prof. Michael Hutchinson - http://fennerschool.anu.edu.au/publications/software/","source_link":"http://www.csiro.au/Organisation-Structure/Divisions/Ecosystem-Sciences.aspx","minlatitude":-43.8,"path":"/data/ala/data/source/bioclim1990-asc/bio15.tif","metadatapath":"http://fennerschool.anu.edu.au/publications/software/","environmentalvalueunits":"mm","path_orig":"layer/bioclim_bio15","environmentalvaluemax":"141","source":"CSIRO Ecosystem Sciences","displaypath":"https://spatial.ala.org.au/geoserver/gwc/service/wms?service=WMS&version=1.1.0&request=GetMap&layers=ALA:bioclim_bio15&format=image/png&styles=","scale":"0.01 degree (~1km)","classification2":"Precipitation","uid":"882","keywords":"rain","maxlongitude":153.64,"datalang":"eng","type":"Environmental","domain":"Terrestrial","environmentalvaluemin":"9","name":"bioclim_bio15","minlongitude":112.9,"classification1":"Climate","mddatest":"2010-08","licence_level":"1","description":"Precipitation - seasonality ( (Bio15)","citation_date":"2008-02","id":882},{"uid":"892","maxlatitude":-9.0,"lookuptablepath":"","enabled":true,"path_orig":"layer/bioclim_bio4","notes":"Data derived using ANUCLIM v6 (beta) with the new set of climate surfaces (centred on 1990), by Dr. Kristen Williams.","dt_added":1308837600000,"environmentalvalueunits":"dimensionless","environmentalvaluemax":"2.22000002861023","displayname":"Temperature - seasonality (Bio04)","pid":"","licence_notes":"Permission to re-distribute ANUCLIM outputs should be obtained from Prof. Michael Hutchinson - http://fennerschool.anu.edu.au/publications/software/","path":"/data/ala/data/source/bioclim1990-asc/bio4.tif","source_link":"http://www.csiro.au/Organisation-Structure/Divisions/Ecosystem-Sciences.aspx","minlatitude":-43.8,"metadatapath":"http://fennerschool.anu.edu.au/publications/software/","source":"CSIRO Ecosystem Sciences","mdhrlv":"","respparty_role":"","name":"bioclim_bio4","licence_link":"","scale":"0.01 degree (~1km)","extents":"","maxlongitude":153.64,"datalang":"eng","displaypath":"https://spatial.ala.org.au/geoserver/gwc/service/wms?service=WMS&version=1.1.0&request=GetMap&layers=ALA:bioclim_bio4&format=image/png&styles=","path_1km":"","type":"Environmental","domain":"Terrestrial","classification2":"Temperature","minlongitude":112.9,"description":"Temperature - seasonality (Bio04)","classification1":"Climate","mddatest":"2010-08","environmentalvaluemin":"0.340000003576279","licence_level":"1","keywords":"variation, mean, ratio","citation_date":"2008-02","id":892},{"uid":"870","maxlatitude":-9.0,"lookuptablepath":"","enabled":true,"notes":"Data derived using ANUCLIM v6 (beta) with the new set of climate surfaces (centred on 1990), by Dr. Kristen Williams.","environmentalvalueunits":"degrees C","environmentalvaluemin":"-1.29999995231628","dt_added":1308837600000,"path":"/data/ala/data/source/bioclim1990-asc/bio8.tif","displaypath":"https://spatial.ala.org.au/geoserver/gwc/service/wms?service=WMS&version=1.1.0&request=GetMap&layers=ALA:bioclim_bio8&format=image/png&styles=","pid":"","licence_notes":"Permission to re-distribute ANUCLIM outputs should be obtained from Prof. Michael Hutchinson - http://fennerschool.anu.edu.au/publications/software/","source_link":"http://www.csiro.au/Organisation-Structure/Divisions/Ecosystem-Sciences.aspx","path_orig":"layer/bioclim_bio8","minlatitude":-43.8,"name":"bioclim_bio8","description":"Temperature - wettest quarter mean (Bio08)","metadatapath":"http://fennerschool.anu.edu.au/publications/software/","source":"CSIRO Ecosystem Sciences","mdhrlv":"","respparty_role":"","licence_link":"","scale":"0.01 degree (~1km)","extents":"","maxlongitude":153.64,"datalang":"eng","displayname":"Temperature - wettest quarter mean (Bio08)","path_1km":"","type":"Environmental","domain":"Terrestrial","classification2":"Temperature","minlongitude":112.9,"classification1":"Climate","mddatest":"2010-08","licence_level":"1","environmentalvaluemax":"32.7000007629395","citation_date":"2008-02","keywords":"rain, precipitation","id":870},{"path_orig":"layer/bioclim_bio6","description":"Temperature - coldest period min (Bio06)","maxlatitude":-9.0,"enabled":true,"keywords":"","environmentalvalueunits":"degrees C","dt_added":1308837600000,"licence_notes":"Permission to re-distribute ANUCLIM outputs should be obtained from Prof. Michael Hutchinson - http://fennerschool.anu.edu.au/publications/software/","environmentalvaluemax":"22.6000003814697","source_link":"http://www.csiro.au/Organisation-Structure/Divisions/Ecosystem-Sciences.aspx","minlatitude":-43.8,"metadatapath":"http://fennerschool.anu.edu.au/publications/software/","name":"bioclim_bio6","source":"CSIRO Ecosystem Sciences","respparty_role":"","licence_link":"","scale":"0.01 degree (~1km)","path":"/data/ala/data/source/bioclim1990-asc/bio6.tif","environmentalvaluemin":"-5.69999980926514","uid":"867","maxlongitude":153.64,"datalang":"eng","notes":"Data derived using ANUCLIM v6 (beta) with the new set of climate surfaces (centred on 1990), by Dr. Kristen Williams. \"Period\" is used here as the month used for the values may not correspond to a single month. For example it may span two months as for example January 15 to February 15.","type":"Environmental","domain":"Terrestrial","classification2":"Temperature","minlongitude":112.9,"classification1":"Climate","mddatest":"2010-08","licence_level":"1","displaypath":"https://spatial.ala.org.au/geoserver/gwc/service/wms?service=WMS&version=1.1.0&request=GetMap&layers=ALA:bioclim_bio6&format=image/png&styles=","citation_date":"2008-02","displayname":"Temperature - coldest period min (Bio06)","id":867},{"maxlatitude":-9.0,"enabled":true,"notes":"Data derived using ANUCLIM v6 (beta) with the new set of climate surfaces (centred on 1990), by Dr. Kristen Williams.","dt_added":1308837600000,"classification1":"Substrate","environmentalvalueunits":"Dimensionless","environmentalvaluemax":"1","licence_notes":"Permission to re-distribute ANUCLIM outputs should be obtained from Prof. Michael Hutchinson - http://fennerschool.anu.edu.au/publications/software/","displaypath":"https://spatial.ala.org.au/geoserver/gwc/service/wms?service=WMS&version=1.1.0&request=GetMap&layers=ALA:bioclim_bio32&format=image/png&styles=","name":"bioclim_bio32","source_link":"http://www.csiro.au/Organisation-Structure/Divisions/Ecosystem-Sciences.aspx","minlatitude":-43.8,"description":"Moisture Index - highest quarter mean (Bio32)","metadatapath":"http://fennerschool.anu.edu.au/publications/software/","classification2":"Moisture","source":"CSIRO Ecosystem Sciences","path":"/data/ala/data/source/bioclim1990-asc/bio32.tif","scale":"0.01 degree (~1km)","keywords":"soil, water, saturation","uid":"865","maxlongitude":153.64,"datalang":"eng","displayname":"Moisture Index - highest quarter mean (Bio32)","path_orig":"layer/bioclim_bio32","type":"Environmental","domain":"Terrestrial","environmentalvaluemin":"0.0799999982118607","minlongitude":112.9,"mddatest":"2010-08","licence_level":"1","citation_date":"2008-02","id":865},{"maxlatitude":-9.0,"lookuptablepath":"","enabled":true,"path_orig":"layer/bioclim_bio3","notes":"Data derived using ANUCLIM v6 (beta) with the new set of climate surfaces (centred on 1990), by Dr. Kristen Williams.","dt_added":1308837600000,"pid":"","licence_notes":"Permission to re-distribute ANUCLIM outputs should be obtained from Prof. Michael Hutchinson - http://fennerschool.anu.edu.au/publications/software/","source_link":"http://www.csiro.au/Organisation-Structure/Divisions/Ecosystem-Sciences.aspx","minlatitude":-43.8,"environmentalvalueunits":"%","metadatapath":"http://fennerschool.anu.edu.au/publications/software/","displaypath":"https://spatial.ala.org.au/geoserver/gwc/service/wms?service=WMS&version=1.1.0&request=GetMap&layers=ALA:bioclim_bio3&format=image/png&styles=","environmentalvaluemin":"0.300000011920929","source":"CSIRO Ecosystem Sciences","path":"/data/ala/data/source/bioclim1990-asc/bio3.tif","mdhrlv":"","respparty_role":"","licence_link":"","name":"bioclim_bio3","description":"Temperature - isothermality (Bio03)","scale":"0.01 degree (~1km)","displayname":"Temperature - isothermality (Bio03)","uid":"883","extents":"","maxlongitude":153.64,"datalang":"eng","path_1km":"","type":"Environmental","domain":"Terrestrial","classification2":"Temperature","minlongitude":112.9,"classification1":"Climate","mddatest":"2010-08","licence_level":"1","environmentalvaluemax":"0.660000026226044","keywords":"day, daily, season, ratio","citation_date":"2008-02","id":883},{"maxlatitude":-9.0,"uid":"891","enabled":true,"notes":"Data derived using ANUCLIM v6 (beta) with the new set of climate surfaces (centred on 1990), by Dr. Kristen Williams.","dt_added":1308837600000,"classification1":"Substrate","environmentalvalueunits":"Dimensionless","environmentalvaluemax":"1","licence_notes":"Permission to re-distribute ANUCLIM outputs should be obtained from Prof. Michael Hutchinson - http://fennerschool.anu.edu.au/publications/software/","source_link":"http://www.csiro.au/Organisation-Structure/Divisions/Ecosystem-Sciences.aspx","minlatitude":-43.8,"metadatapath":"http://fennerschool.anu.edu.au/publications/software/","name":"bioclim_bio28","classification2":"Moisture","source":"CSIRO Ecosystem Sciences","path":"/data/ala/data/source/bioclim1990-asc/bio28.tif","description":"Moisture Index - annual mean (Bio28)","displaypath":"https://spatial.ala.org.au/geoserver/gwc/service/wms?service=WMS&version=1.1.0&request=GetMap&layers=ALA:bioclim_bio28&format=image/png&styles=","environmentalvaluemin":"0.0500000007450581","scale":"0.01 degree (~1km)","keywords":"soil, water, saturation","displayname":"Moisture Index - annual mean (Bio28)","maxlongitude":153.64,"datalang":"eng","type":"Environmental","domain":"Terrestrial","path_orig":"layer/bioclim_bio28","minlongitude":112.9,"mddatest":"2010-08","licence_level":"1","citation_date":"2008-02","id":891},{"maxlatitude":-9.0,"lookuptablepath":"","enabled":true,"notes":"Data derived using ANUCLIM v6 (beta) with the new set of climate surfaces (centred on 1990), by Dr. Kristen Williams.","dt_added":1308837600000,"environmentalvalueunits":"dimensionless","pid":"","licence_notes":"Permission to re-distribute ANUCLIM outputs should be obtained from Prof. Michael Hutchinson - http://fennerschool.anu.edu.au/publications/software/","displayname":"Radiation - seasonality (Bio23)","source_link":"http://www.csiro.au/Organisation-Structure/Divisions/Ecosystem-Sciences.aspx","minlatitude":-43.8,"path":"/data/ala/data/source/bioclim1990-asc/bio23.tif","metadatapath":"http://fennerschool.anu.edu.au/publications/software/","source":"CSIRO Ecosystem Sciences","environmentalvaluemax":"55","mdhrlv":"","keywords":"solar, sun","respparty_role":"","licence_link":"","scale":"0.01 degree (~1km)","environmentalvaluemin":"7","extents":"","uid":"887","displaypath":"https://spatial.ala.org.au/geoserver/gwc/service/wms?service=WMS&version=1.1.0&request=GetMap&layers=ALA:bioclim_bio23&format=image/png&styles=","maxlongitude":153.64,"datalang":"eng","classification2":"Solar radiation","path_1km":"","name":"bioclim_bio23","type":"Environmental","domain":"Terrestrial","path_orig":"layer/bioclim_bio23","minlongitude":112.9,"classification1":"Climate","description":"Radiation - seasonality (Bio23)","mddatest":"2010-08","licence_level":"1","citation_date":"2008-02","id":887},{"maxlatitude":-9.0,"enabled":true,"description":"Temperature - diurnal range mean (Bio02)","path_orig":"layer/bioclim_bio2","notes":"Data derived using ANUCLIM v6 (beta) with the new set of climate surfaces (centred on 1990), by Dr. Kristen Williams.","environmentalvalueunits":"degrees C","dt_added":1308837600000,"licence_notes":"Permission to re-distribute ANUCLIM outputs should be obtained from Prof. Michael Hutchinson - http://fennerschool.anu.edu.au/publications/software/","displaypath":"https://spatial.ala.org.au/geoserver/gwc/service/wms?service=WMS&version=1.1.0&request=GetMap&layers=ALA:bioclim_bio2&format=image/png&styles=","source_link":"http://www.csiro.au/Organisation-Structure/Divisions/Ecosystem-Sciences.aspx","minlatitude":-43.8,"metadatapath":"http://fennerschool.anu.edu.au/publications/software/","source":"CSIRO Ecosystem Sciences","name":"bioclim_bio2","scale":"0.01 degree (~1km)","environmentalvaluemin":"5.09999990463257","uid":"888","maxlongitude":153.64,"datalang":"eng","environmentalvaluemax":"16.8999996185303","path":"/data/ala/data/source/bioclim1990-asc/bio2.tif","type":"Environmental","domain":"Terrestrial","classification2":"Temperature","minlongitude":112.9,"classification1":"Climate","mddatest":"2010-08","licence_level":"1","citation_date":"2008-02","displayname":"Temperature - diurnal range mean (Bio02)","id":888},{"maxlatitude":-9.0,"enabled":true,"notes":"Data derived using ANUCLIM v6 (beta) with the new set of climate surfaces (centred on 1990), by Dr. Kristen Williams.","dt_added":1308837600000,"uid":"878","path":"/data/ala/data/source/bioclim1990-asc/bio18.tif","licence_notes":"Permission to re-distribute ANUCLIM outputs should be obtained from Prof. Michael Hutchinson - http://fennerschool.anu.edu.au/publications/software/","source_link":"http://www.csiro.au/Organisation-Structure/Divisions/Ecosystem-Sciences.aspx","minlatitude":-43.8,"environmentalvaluemax":"2045","metadatapath":"http://fennerschool.anu.edu.au/publications/software/","environmentalvalueunits":"mm","path_orig":"layer/bioclim_bio18","source":"CSIRO Ecosystem Sciences","displayname":"Precipitation - warmest quarter (Bio18)","scale":"0.01 degree (~1km)","classification2":"Precipitation","keywords":"rain","description":"Precipitation - warmest quarter  (Bio18)","environmentalvaluemin":"20","maxlongitude":153.64,"datalang":"eng","type":"Environmental","domain":"Terrestrial","displaypath":"https://spatial.ala.org.au/geoserver/gwc/service/wms?service=WMS&version=1.1.0&request=GetMap&layers=ALA:bioclim_bio18&format=image/png&styles=","minlongitude":112.9,"name":"bioclim_bio18","classification1":"Climate","mddatest":"2010-08","licence_level":"1","citation_date":"2008-02","id":878},{"maxlatitude":-9.0,"enabled":true,"notes":"Data derived using ANUCLIM v6 (beta) with the new set of climate surfaces (centred on 1990), by Dr. Kristen Williams.","dt_added":1308837600000,"description":"Precipitation - driest quarter  (Bio17)","licence_notes":"Permission to re-distribute ANUCLIM outputs should be obtained from Prof. Michael Hutchinson - http://fennerschool.anu.edu.au/publications/software/","source_link":"http://www.csiro.au/Organisation-Structure/Divisions/Ecosystem-Sciences.aspx","minlatitude":-43.8,"metadatapath":"http://fennerschool.anu.edu.au/publications/software/","path_orig":"layer/bioclim_bio17","environmentalvalueunits":"mm","source":"CSIRO Ecosystem Sciences","scale":"0.01 degree (~1km)","classification2":"Precipitation","keywords":"rain","environmentalvaluemin":"1","uid":"889","maxlongitude":153.64,"datalang":"eng","environmentalvaluemax":"599","type":"Environmental","domain":"Terrestrial","displaypath":"https://spatial.ala.org.au/geoserver/gwc/service/wms?service=WMS&version=1.1.0&request=GetMap&layers=ALA:bioclim_bio17&format=image/png&styles=","minlongitude":112.9,"classification1":"Climate","name":"bioclim_bio17","mddatest":"2010-08","displayname":"Precipitation - driest quarter  (Bio17)","path":"/data/ala/data/source/bioclim1990-asc/bio17.tif","licence_level":"1","citation_date":"2008-02","id":889},{"maxlatitude":-9.0,"enabled":true,"environmentalvaluemin":"137","uid":"893","notes":"Data derived using ANUCLIM v6 (beta) with the new set of climate surfaces (centred on 1990), by Dr. Kristen Williams.","dt_added":1308837600000,"licence_notes":"Permission to re-distribute ANUCLIM outputs should be obtained from Prof. Michael Hutchinson - 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This version was released in January 2020.\r\n\r\nFick, S.E. and R.J. Hijmans, 2017. WorldClim 2: new 1km spatial resolution climate surfaces for global land areas. 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This version was released in January 2020.\r\n\r\nFick, S.E. and R.J. Hijmans, 2017. WorldClim 2: new 1km spatial resolution climate surfaces for global land areas. International Journal of Climatology 37 (12): 4302-4315. https://rmets.onlinelibrary.wiley.com/doi/abs/10.1002/joc.5086","licence_level":"1","id":10987},{"enabled":true,"source":"WorldClim","keywords":"","licence_notes":"CC BY-SA 4.0","maxlongitude":180.0,"metadatapath":"https://www.worldclim.org/data/worldclim21.html","displayname":"WorldClim 2.1: Temperature - coldest quarter mean","minlongitude":-180.0,"dt_added":1620638015130,"environmentalvaluemin":"","licence_link":"https://creativecommons.org/licenses/by-sa/4.0/","mddatest":"2020-01","name":"worldclim21_bio11","environmentalvalueunits":"°C","datalang":"eng","path_orig":"layer/worldclim21_bio11","respparty_role":"Custodian","displaypath":"https://spatial.ala.org.au/geoserver/gwc/service/wms?service=WMS&version=1.1.0&request=GetMap&layers=ALA:worldclim21_bio11&format=image/png&styles=","type":"Environmental","domain":"Terrestrial","classification2":"Temperature","source_link":"https://www.worldclim.org/data/worldclim21.html","maxlatitude":90.0,"classification1":"Climate","environmentalvaluemax":"","citation_date":"2017","minlatitude":-90.0,"notes":"This is WorldClim version 2.1 climate data for 1970-2000. This version was released in January 2020.\r\n\r\nFick, S.E. and R.J. Hijmans, 2017. WorldClim 2: new 1km spatial resolution climate surfaces for global land areas. International Journal of Climatology 37 (12): 4302-4315. https://rmets.onlinelibrary.wiley.com/doi/abs/10.1002/joc.5086","licence_level":"1","description":"Mean Temperature of Coldest Quarter","id":10988},{"description":"Mean Temperature of Wettest Quarter","enabled":true,"source":"WorldClim","keywords":"","licence_notes":"CC BY-SA 4.0","maxlongitude":180.0,"metadatapath":"https://www.worldclim.org/data/worldclim21.html","minlongitude":-180.0,"environmentalvaluemin":"","licence_link":"https://creativecommons.org/licenses/by-sa/4.0/","displayname":"WorldClim 2.1: Temperature - wettest quarter mean","mddatest":"2020-01","dt_added":1620629233127,"displaypath":"https://spatial.ala.org.au/geoserver/gwc/service/wms?service=WMS&version=1.1.0&request=GetMap&layers=ALA:worldclim21_bio8&format=image/png&styles=","environmentalvalueunits":"°C","datalang":"eng","respparty_role":"Custodian","type":"Environmental","domain":"Terrestrial","path_orig":"layer/worldclim21_bio8","classification2":"Temperature","source_link":"https://www.worldclim.org/data/worldclim21.html","maxlatitude":90.0,"classification1":"Climate","name":"worldclim21_bio8","environmentalvaluemax":"","citation_date":"2017","minlatitude":-90.0,"notes":"This is WorldClim version 2.1 climate data for 1970-2000. This version was released in January 2020.\r\n\r\nFick, S.E. and R.J. Hijmans, 2017. WorldClim 2: new 1km spatial resolution climate surfaces for global land areas. International Journal of Climatology 37 (12): 4302-4315. https://rmets.onlinelibrary.wiley.com/doi/abs/10.1002/joc.5086","licence_level":"1","id":10985},{"lookuptablepath":"","licence_link":"http://www.worldclim.org/current","enabled":true,"environmentalvaluemax":"725","metadatapath":"https://gist.github.com/tucotuco/1152668","source":"WorldClim","path_orig":"layer/worldclim_bio_7","maxlongitude":180.0,"dt_added":1308837600000,"environmentalvaluemin":"53","pid":"","citation_date":"","path":"/mnt/transfer/worldclim/bio_7.tif","minlongitude":-180.0,"displayname":"WorldClim: Temperature - annual range","mdhrlv":"","keywords":"bio07","displaypath":"https://spatial.ala.org.au/geoserver/gwc/service/wms?service=WMS&version=1.1.0&request=GetMap&layers=ALA:worldclim_bio_7&format=image/png&styles=","description":"Temperature Annual Range","scale":"0.01 degree (~1km)","minlatitude":-60.0,"licence_notes":"This dataset is freely available for academic and other non-commercial use. Redistribution, or commercial use, is not allowed without prior permission.","uid":"787","environmentalvalueunits":"degrees C * 10","datalang":"eng","source_link":"http://www.worldclim.org/","path_1km":"","type":"Environmental","domain":"Terrestrial","classification2":"Temperature","notes":"(From http://www.worldclim.org/methods) - For a complete description, see:\r\n\r\nHijmans, R.J., S.E. Cameron, J.L. Parra, P.G. Jones and A. Jarvis, 2005. Very high resolution interpolated climate surfaces for global land areas. International Journal of Climatology 25: 1965-1978.\r\n\r\nThe data layers were generated through interpolation of average monthly climate data from weather stations on a 30 arc-second resolution grid (often referred to as 1 km2 resolution). Variables included are monthly total precipitation, and monthly mean, minimum and maximum temperature, and 19 derived bioclimatic variables.\r\n\r\nThe WorldClim interpolated climate layers were made using:\r\n    * Major climate databases compiled by the Global Historical Climatology Network (GHCN), the FAO, the WMO, the International Center for Tropical Agriculture (CIAT), R-HYdronet, and a number of additional minor databases for Australia, New Zealand, the Nordic European Countries, Ecuador, Peru, Bolivia, among others.\r\n    * The SRTM elevation database (aggregeated to 30 arc-seconds, 1 km)\r\n    * The ANUSPLIN software. ANUSPLIN is a program for interpolating noisy multi-variate data using thin plate smoothing splines. We used latitude, longitude, and elevation as independent variables.","maxlatitude":90.0,"classification1":"Climate","respparty_role":"custodian","mddatest":"2010-07","licence_level":"1","name":"worldclim_bio_7","id":787},{"lookuptablepath":"","licence_link":"http://www.worldclim.org/current","enabled":true,"path":"/mnt/transfer/worldclim/bio_19.tif","name":"worldclim_bio_19","metadatapath":"https://gist.github.com/tucotuco/1152668","source":"WorldClim","maxlongitude":180.0,"dt_added":1308837600000,"pid":"","citation_date":"","minlongitude":-180.0,"environmentalvalueunits":"mm","path_orig":"layer/worldclim_bio_19","mdhrlv":"","scale":"0.01 degree (~1km)","classification2":"Precipitation","minlatitude":-60.0,"description":"Precipitation of Coldest Quarter","uid":"786","licence_notes":"This dataset is freely available for academic and other non-commercial use. Redistribution, or commercial use, is not allowed without prior permission.","environmentalvaluemin":"0","displaypath":"https://spatial.ala.org.au/geoserver/gwc/service/wms?service=WMS&version=1.1.0&request=GetMap&layers=ALA:worldclim_bio_19&format=image/png&styles=","datalang":"eng","source_link":"http://www.worldclim.org/","keywords":"rain, bio19","path_1km":"","type":"Environmental","domain":"Terrestrial","notes":"(From http://www.worldclim.org/methods) - For a complete description, see:\r\n\r\nHijmans, R.J., S.E. Cameron, J.L. Parra, P.G. Jones and A. Jarvis, 2005. Very high resolution interpolated climate surfaces for global land areas. International Journal of Climatology 25: 1965-1978.\r\n\r\nThe data layers were generated through interpolation of average monthly climate data from weather stations on a 30 arc-second resolution grid (often referred to as 1 km2 resolution). Variables included are monthly total precipitation, and monthly mean, minimum and maximum temperature, and 19 derived bioclimatic variables.\r\n\r\nThe WorldClim interpolated climate layers were made using:\r\n    * Major climate databases compiled by the Global Historical Climatology Network (GHCN), the FAO, the WMO, the International Center for Tropical Agriculture (CIAT), R-HYdronet, and a number of additional minor databases for Australia, New Zealand, the Nordic European Countries, Ecuador, Peru, Bolivia, among others.\r\n    * The SRTM elevation database (aggregeated to 30 arc-seconds, 1 km)\r\n    * The ANUSPLIN software. ANUSPLIN is a program for interpolating noisy multi-variate data using thin plate smoothing splines. We used latitude, longitude, and elevation as independent variables.","maxlatitude":90.0,"classification1":"Climate","displayname":"WorldClim: Precipitation - coldest quarter","environmentalvaluemax":"5162","respparty_role":"custodian","mddatest":"2010-07","licence_level":"1","id":786},{"lookuptablepath":"","licence_link":"http://www.worldclim.org/current","enabled":true,"metadatapath":"https://gist.github.com/tucotuco/1152668","source":"WorldClim","maxlongitude":180.0,"dt_added":1308837600000,"name":"worldclim_bio_2","pid":"","citation_date":"","minlongitude":-180.0,"mdhrlv":"","scale":"0.01 degree (~1km)","minlatitude":-60.0,"licence_notes":"This dataset is freely available for academic and other non-commercial use. Redistribution, or commercial use, is not allowed without prior permission.","uid":"785","environmentalvalueunits":"degrees C * 10","description":"Mean Diurnal Range","datalang":"eng","source_link":"http://www.worldclim.org/","environmentalvaluemax":"214","path_1km":"","type":"Environmental","domain":"Terrestrial","environmentalvaluemin":"9","classification2":"Temperature","notes":"(From http://www.worldclim.org/methods) - For a complete description, see:\r\n\r\nHijmans, R.J., S.E. Cameron, J.L. Parra, P.G. Jones and A. Jarvis, 2005. Very high resolution interpolated climate surfaces for global land areas. International Journal of Climatology 25: 1965-1978.\r\n\r\nThe data layers were generated through interpolation of average monthly climate data from weather stations on a 30 arc-second resolution grid (often referred to as 1 km2 resolution). Variables included are monthly total precipitation, and monthly mean, minimum and maximum temperature, and 19 derived bioclimatic variables.\r\n\r\nThe WorldClim interpolated climate layers were made using:\r\n    * Major climate databases compiled by the Global Historical Climatology Network (GHCN), the FAO, the WMO, the International Center for Tropical Agriculture (CIAT), R-HYdronet, and a number of additional minor databases for Australia, New Zealand, the Nordic European Countries, Ecuador, Peru, Bolivia, among others.\r\n    * The SRTM elevation database (aggregeated to 30 arc-seconds, 1 km)\r\n    * The ANUSPLIN software. ANUSPLIN is a program for interpolating noisy multi-variate data using thin plate smoothing splines. We used latitude, longitude, and elevation as independent variables.","displayname":"WorldClim: Temperature - diurnal range mean","maxlatitude":90.0,"classification1":"Climate","respparty_role":"custodian","mddatest":"2010-07","path":"/mnt/transfer/worldclim/bio_2.tif","licence_level":"1","displaypath":"https://spatial.ala.org.au/geoserver/gwc/service/wms?service=WMS&version=1.1.0&request=GetMap&layers=ALA:worldclim_bio_2&format=image/png&styles=","path_orig":"layer/worldclim_bio_2","keywords":"day, daily, max, ratio, bio02","id":785},{"name":"worldclim_bio_17","lookuptablepath":"","licence_link":"http://www.worldclim.org/current","enabled":true,"metadatapath":"https://gist.github.com/tucotuco/1152668","source":"WorldClim","maxlongitude":180.0,"dt_added":1308837600000,"pid":"","citation_date":"","displayname":"WorldClim: Precipitation - driest quarter","minlongitude":-180.0,"environmentalvalueunits":"mm","mdhrlv":"","description":"Precipitation of Driest Quarter","path_orig":"layer/worldclim_bio_17","scale":"0.01 degree (~1km)","uid":"782","classification2":"Precipitation","minlatitude":-60.0,"keywords":"rain, bio17","path":"/mnt/transfer/worldclim/bio_17.tif","licence_notes":"This dataset is freely available for academic and other non-commercial use. Redistribution, or commercial use, is not allowed without prior permission.","displaypath":"https://spatial.ala.org.au/geoserver/gwc/service/wms?service=WMS&version=1.1.0&request=GetMap&layers=ALA:worldclim_bio_17&format=image/png&styles=","environmentalvaluemin":"0","datalang":"eng","source_link":"http://www.worldclim.org/","path_1km":"","type":"Environmental","domain":"Terrestrial","environmentalvaluemax":"2495","notes":"(From http://www.worldclim.org/methods) - For a complete description, see:\r\n\r\nHijmans, R.J., S.E. Cameron, J.L. Parra, P.G. Jones and A. Jarvis, 2005. Very high resolution interpolated climate surfaces for global land areas. International Journal of Climatology 25: 1965-1978.\r\n\r\nThe data layers were generated through interpolation of average monthly climate data from weather stations on a 30 arc-second resolution grid (often referred to as 1 km2 resolution). Variables included are monthly total precipitation, and monthly mean, minimum and maximum temperature, and 19 derived bioclimatic variables.\r\n\r\nThe WorldClim interpolated climate layers were made using:\r\n    * Major climate databases compiled by the Global Historical Climatology Network (GHCN), the FAO, the WMO, the International Center for Tropical Agriculture (CIAT), R-HYdronet, and a number of additional minor databases for Australia, New Zealand, the Nordic European Countries, Ecuador, Peru, Bolivia, among others.\r\n    * The SRTM elevation database (aggregeated to 30 arc-seconds, 1 km)\r\n    * The ANUSPLIN software. ANUSPLIN is a program for interpolating noisy multi-variate data using thin plate smoothing splines. We used latitude, longitude, and elevation as independent variables.","maxlatitude":90.0,"classification1":"Climate","respparty_role":"custodian","mddatest":"2010-07","licence_level":"1","id":782},{"lookuptablepath":"","licence_link":"http://www.worldclim.org/current","enabled":true,"metadatapath":"https://gist.github.com/tucotuco/1152668","uid":"794","source":"WorldClim","maxlongitude":180.0,"name":"worldclim_bio_15","dt_added":1308837600000,"environmentalvalueunits":"dimensionless","environmentalvaluemax":"265","pid":"","description":"Precipitation Seasonality","citation_date":"","minlongitude":-180.0,"mdhrlv":"","path_orig":"layer/worldclim_bio_15","displaypath":"https://spatial.ala.org.au/geoserver/gwc/service/wms?service=WMS&version=1.1.0&request=GetMap&layers=ALA:worldclim_bio_15&format=image/png&styles=","scale":"0.01 degree (~1km)","keywords":"rain, bio15","classification2":"Precipitation","minlatitude":-60.0,"licence_notes":"This dataset is freely available for academic and other non-commercial use. Redistribution, or commercial use, is not allowed without prior permission.","environmentalvaluemin":"0","datalang":"eng","source_link":"http://www.worldclim.org/","path_1km":"","type":"Environmental","domain":"Terrestrial","notes":"(From http://www.worldclim.org/methods) - For a complete description, see:\r\n\r\nHijmans, R.J., S.E. Cameron, J.L. Parra, P.G. Jones and A. Jarvis, 2005. Very high resolution interpolated climate surfaces for global land areas. International Journal of Climatology 25: 1965-1978.\r\n\r\nThe data layers were generated through interpolation of average monthly climate data from weather stations on a 30 arc-second resolution grid (often referred to as 1 km2 resolution). Variables included are monthly total precipitation, and monthly mean, minimum and maximum temperature, and 19 derived bioclimatic variables.\r\n\r\nThe WorldClim interpolated climate layers were made using:\r\n    * Major climate databases compiled by the Global Historical Climatology Network (GHCN), the FAO, the WMO, the International Center for Tropical Agriculture (CIAT), R-HYdronet, and a number of additional minor databases for Australia, New Zealand, the Nordic European Countries, Ecuador, Peru, Bolivia, among others.\r\n    * The SRTM elevation database (aggregeated to 30 arc-seconds, 1 km)\r\n    * The ANUSPLIN software. ANUSPLIN is a program for interpolating noisy multi-variate data using thin plate smoothing splines. We used latitude, longitude, and elevation as independent variables.","maxlatitude":90.0,"classification1":"Climate","path":"/mnt/transfer/worldclim/bio_15.tif","respparty_role":"custodian","mddatest":"2010-07","licence_level":"1","displayname":"WorldClim: Precipitation - seasonality","id":794},{"lookuptablepath":"","licence_link":"http://www.worldclim.org/current","enabled":true,"metadatapath":"https://gist.github.com/tucotuco/1152668","source":"WorldClim","displaypath":"https://spatial.ala.org.au/geoserver/gwc/service/wms?service=WMS&version=1.1.0&request=GetMap&layers=ALA:worldclim_bio_14&format=image/png&styles=","path":"/mnt/transfer/worldclim/bio_14.tif","maxlongitude":180.0,"dt_added":1308837600000,"name":"worldclim_bio_14","pid":"","citation_date":"","displayname":"WorldClim: Precipitation - driest month","minlongitude":-180.0,"environmentalvalueunits":"mm","mdhrlv":"","path_orig":"layer/worldclim_bio_14","uid":"791","scale":"0.01 degree (~1km)","classification2":"Precipitation","minlatitude":-60.0,"licence_notes":"This dataset is freely available for academic and other non-commercial use. Redistribution, or commercial use, is not allowed without prior permission.","environmentalvaluemin":"0","keywords":"rain, bio14","description":"Precipitation of Driest Month","datalang":"eng","source_link":"http://www.worldclim.org/","environmentalvaluemax":"752","path_1km":"","type":"Environmental","domain":"Terrestrial","notes":"(From http://www.worldclim.org/methods) - For a complete description, see:\r\n\r\nHijmans, R.J., S.E. Cameron, J.L. Parra, P.G. Jones and A. Jarvis, 2005. Very high resolution interpolated climate surfaces for global land areas. International Journal of Climatology 25: 1965-1978.\r\n\r\nThe data layers were generated through interpolation of average monthly climate data from weather stations on a 30 arc-second resolution grid (often referred to as 1 km2 resolution). Variables included are monthly total precipitation, and monthly mean, minimum and maximum temperature, and 19 derived bioclimatic variables.\r\n\r\nThe WorldClim interpolated climate layers were made using:\r\n    * Major climate databases compiled by the Global Historical Climatology Network (GHCN), the FAO, the WMO, the International Center for Tropical Agriculture (CIAT), R-HYdronet, and a number of additional minor databases for Australia, New Zealand, the Nordic European Countries, Ecuador, Peru, Bolivia, among others.\r\n    * The SRTM elevation database (aggregeated to 30 arc-seconds, 1 km)\r\n    * The ANUSPLIN software. ANUSPLIN is a program for interpolating noisy multi-variate data using thin plate smoothing splines. We used latitude, longitude, and elevation as independent variables.","maxlatitude":90.0,"classification1":"Climate","respparty_role":"custodian","mddatest":"2010-07","licence_level":"1","id":791},{"uid":"793","lookuptablepath":"","licence_link":"http://www.worldclim.org/current","enabled":true,"metadatapath":"https://gist.github.com/tucotuco/1152668","source":"WorldClim","maxlongitude":180.0,"name":"worldclim_bio_1","dt_added":1308837600000,"environmentalvaluemax":"320","pid":"","citation_date":"","minlongitude":-180.0,"mdhrlv":"","keywords":"bio01","scale":"0.01 degree (~1km)","minlatitude":-60.0,"licence_notes":"This dataset is freely available for academic and other non-commercial use. Redistribution, or commercial use, is not allowed without prior permission.","environmentalvalueunits":"degrees C * 10","datalang":"eng","source_link":"http://www.worldclim.org/","displayname":"WorldClim: Temperature - annual mean","path_1km":"","type":"Environmental","domain":"Terrestrial","displaypath":"https://spatial.ala.org.au/geoserver/gwc/service/wms?service=WMS&version=1.1.0&request=GetMap&layers=ALA:worldclim_bio_1&format=image/png&styles=","classification2":"Temperature","notes":"(From http://www.worldclim.org/methods) - For a complete description, see:\r\n\r\nHijmans, R.J., S.E. Cameron, J.L. Parra, P.G. Jones and A. Jarvis, 2005. Very high resolution interpolated climate surfaces for global land areas. International Journal of Climatology 25: 1965-1978.\r\n\r\nThe data layers were generated through interpolation of average monthly climate data from weather stations on a 30 arc-second resolution grid (often referred to as 1 km2 resolution). Variables included are monthly total precipitation, and monthly mean, minimum and maximum temperature, and 19 derived bioclimatic variables.\r\n\r\nThe WorldClim interpolated climate layers were made using:\r\n    * Major climate databases compiled by the Global Historical Climatology Network (GHCN), the FAO, the WMO, the International Center for Tropical Agriculture (CIAT), R-HYdronet, and a number of additional minor databases for Australia, New Zealand, the Nordic European Countries, Ecuador, Peru, Bolivia, among others.\r\n    * The SRTM elevation database (aggregeated to 30 arc-seconds, 1 km)\r\n    * The ANUSPLIN software. ANUSPLIN is a program for interpolating noisy multi-variate data using thin plate smoothing splines. We used latitude, longitude, and elevation as independent variables.","maxlatitude":90.0,"path":"/mnt/transfer/worldclim/bio_1.tif","classification1":"Climate","description":"Annual Mean Temperature","respparty_role":"custodian","mddatest":"2010-07","path_orig":"layer/worldclim_bio_1","licence_level":"1","environmentalvaluemin":"-290","id":793},{"lookuptablepath":"","licence_link":"http://www.worldclim.org/current","enabled":true,"metadatapath":"https://gist.github.com/tucotuco/1152668","source":"WorldClim","maxlongitude":180.0,"name":"worldclim_bio_12","dt_added":1308837600000,"pid":"","citation_date":"","displaypath":"https://spatial.ala.org.au/geoserver/gwc/service/wms?service=WMS&version=1.1.0&request=GetMap&layers=ALA:worldclim_bio_12&format=image/png&styles=","path_orig":"layer/worldclim_bio_12","minlongitude":-180.0,"environmentalvalueunits":"mm","description":"Annual Precipitation","mdhrlv":"","scale":"0.01 degree (~1km)","path":"/mnt/transfer/worldclim/bio_12.tif","classification2":"Precipitation","minlatitude":-60.0,"licence_notes":"This dataset is freely available for academic and other non-commercial use. Redistribution, or commercial use, is not allowed without prior permission.","environmentalvaluemax":"11401","keywords":"rain, bio12","environmentalvaluemin":"0","uid":"788","datalang":"eng","source_link":"http://www.worldclim.org/","path_1km":"","type":"Environmental","domain":"Terrestrial","notes":"(From http://www.worldclim.org/methods) - For a complete description, see:\r\n\r\nHijmans, R.J., S.E. Cameron, J.L. Parra, P.G. Jones and A. Jarvis, 2005. Very high resolution interpolated climate surfaces for global land areas. International Journal of Climatology 25: 1965-1978.\r\n\r\nThe data layers were generated through interpolation of average monthly climate data from weather stations on a 30 arc-second resolution grid (often referred to as 1 km2 resolution). Variables included are monthly total precipitation, and monthly mean, minimum and maximum temperature, and 19 derived bioclimatic variables.\r\n\r\nThe WorldClim interpolated climate layers were made using:\r\n    * Major climate databases compiled by the Global Historical Climatology Network (GHCN), the FAO, the WMO, the International Center for Tropical Agriculture (CIAT), R-HYdronet, and a number of additional minor databases for Australia, New Zealand, the Nordic European Countries, Ecuador, Peru, Bolivia, among others.\r\n    * The SRTM elevation database (aggregeated to 30 arc-seconds, 1 km)\r\n    * The ANUSPLIN software. ANUSPLIN is a program for interpolating noisy multi-variate data using thin plate smoothing splines. We used latitude, longitude, and elevation as independent variables.","maxlatitude":90.0,"classification1":"Climate","respparty_role":"custodian","mddatest":"2010-07","licence_level":"1","displayname":"WorldClim: Precipitation - annual","id":788},{"displayname":"Occurrence Density","dt_added":1439388000000,"lookuptablepath":"","enabled":true,"uid":"898","pid":"","path":"/data/ala/data/source/occurrence_layers/layer_occurrence_av_1.tif","citation_date":"","displaypath":"https://spatial.ala.org.au/geoserver/gwc/service/wms?service=WMS&version=1.1.0&request=GetMap&layers=ALA:odensity&format=image/png&styles=","name":"odensity","environmentalvaluemax":"446649","domain":"Terrestrial,Marine","maxlongitude":159.23333,"minlongitude":96.79992,"mdhrlv":"","respparty_role":"","keywords":"average, sample","licence_link":"","scale":"0.01 degree (~1km)","notes":"Occurrence Density is derived by applying a moving average to all point occurrences held by the Atlas of Living Australia. If all occurrences are mapped (over terrestrial and marine areas), a moving average is like moving a window with many panes over the area, noting the number of occurrences in each pane and placing the average of all panes at the centre pane. The window is moved to the next sample location and the process repeated. Occurrence density uses a 9 by 9 pane window where each pane is 0.01 degrees latitude/longitude. Each move of the window is 0.01 degrees.\r\n\r\nScope: World","maxlatitude":-10.46623,"environmentalvaluemin":"0","mddatest":"","path_orig":"layer/odensity","licence_notes":"","source_link":"","path_1km":"","minlatitude":-36.41364,"type":"Environmental","classification2":"","datalang":"","licence_level":"1","classification1":"Biodiversity","environmentalvalueunits":"frequency","metadatapath":"http://www.ala.org.au/","source":"ALA-SPATIAL","description":"Occurrence Density","id":898}]