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This inventory was originally created by Gorum and others (2014) describing the landslides triggered by a sequence of earthquakes, with the largest being the M 6.2 17 km N of Puerto Aisen, Chile earthquake that occurred on 21 April 2007 at 23:45:56 UTC. Care should be taken when comparing with other inventories because different authors use different mapping techniques. This inventory includes landslides triggered by a sequence of earthquakes rather than a single mainshock. Please check the author methods summary and the original data source for more information on these details and to confirm the viability of this inventory for your specific use. With the exception of the data from USGS sources, the inventory...
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This contains the South American portion of the Hydrologic Derivatives for Modeling and Analysis (HDMA) database. The HDMA database provides comprehensive and consistent global coverage of raster and vector topographically derived layers, including raster layers of digital elevation model (DEM) data, flow direction, flow accumulation, slope, and compound topographic index (CTI); and vector layers of streams and catchment boundaries. The coverage of the data is global (-180º, 180º, -90º, 90º) with the underlying DEM being a hybrid of three datasets: HydroSHEDS (Hydrological data and maps based on SHuttle Elevation Derivatives at multiple Scales), Global Multi-resolution Terrain Elevation Data 2010 (GMTED2010) and...
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The integrity of Amazon forests are currently threatened by climate change, deforestation, and fire. However, it is unclear how these agents of change interact over large spatial and temporal domains and reducing this uncertainty is important for projecting changes in carbon stocks and species biogeography, and could better inform continental scale conservation programs. With this in mind, aboveground biomass and tree cover data were produced using the dynamic global vegetation model, LPJmL, with 9 different global climate models (using the SRES A2 emissions storyline) and 2 different deforestation scenarios (from Soares et al.). The existing fire module was modified to include 'escaped fire' associated with deforestation,...
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The integrity of Amazon forests are currently threatened by climate change, deforestation, and fire. However, it is unclear how these agents of change interact over large spatial and temporal domains and reducing this uncertainty is important for projecting changes in carbon stocks and species biogeography, and could better inform continental scale conservation programs. With this in mind, aboveground biomass and tree cover data were produced using the dynamic global vegetation model, LPJmL, with 9 different global climate models (using the SRES A2 emissions storyline) and 2 different deforestation scenarios (from Soares et al.). The existing fire module was modified to include 'escaped fire' associated with deforestation,...
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The integrity of Amazon forests are currently threatened by climate change, deforestation, and fire. However, it is unclear how these agents of change interact over large spatial and temporal domains and reducing this uncertainty is important for projecting changes in carbon stocks and species biogeography, and could better inform continental scale conservation programs. With this in mind, above ground biomass and tree cover data were produced using the dynamic global vegetation model, LPJmL, with 9 different global climate models (using the SRES A2 emissions storyline) and 2 different deforestation scenarios (from Soares et al.). The existing fire module was modified to include 'escaped fire' associated with deforestation,...
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The integrity of Amazon forests are currently threatened by climate change, deforestation, and fire. However, it is unclear how these agents of change interact over large spatial and temporal domains and reducing this uncertainty is important for projecting changes in carbon stocks and species biogeography, and could better inform continental scale conservation programs. With this in mind, above ground biomass and tree cover data were produced using the dynamic global vegetation model, LPJmL, with 9 different global climate models (using the SRES A2 emissions storyline) and 2 different deforestation scenarios (from Soares et al.). The existing fire module was modified to include 'escaped fire' associated with deforestation,...
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The integrity of Amazon forests are currently threatened by climate change, deforestation, and fire. However, it is unclear how these agents of change interact over large spatial and temporal domains and reducing this uncertainty is important for projecting changes in carbon stocks and species biogeography, and could better inform continental scale conservation programs. With this in mind, above ground biomass and tree cover data were produced using the dynamic global vegetation model, LPJmL, with 9 different global climate models (using the SRES A2 emissions storyline) and 2 different deforestation scenarios (from Soares et al.). The existing fire module was modified to include 'escaped fire' associated with deforestation,...
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The integrity of Amazon forests are currently threatened by climate change, deforestation, and fire. However, it is unclear how these agents of change interact over large spatial and temporal domains and reducing this uncertainty is important for projecting changes in carbon stocks and species biogeography, and could better inform continental scale conservation programs. With this in mind, aboveground biomass and tree cover data were produced using the dynamic global vegetation model, LPJmL, with 9 different global climate models (using the SRES A2 emissions storyline) and 2 different deforestation scenarios (from Soares et al.). The existing fire module was modified to include 'escaped fire' associated with deforestation,...
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The integrity of Amazon forests are currently threatened by climate change, deforestation, and fire. However, it is unclear how these agents of change interact over large spatial and temporal domains and reducing this uncertainty is important for projecting changes in carbon stocks and species biogeography, and could better inform continental scale conservation programs. With this in mind, aboveground biomass and tree cover data were produced using the dynamic global vegetation model, LPJmL, with 9 different global climate models (using the SRES A2 emissions storyline) and 2 different deforestation scenarios (from Soares et al.). The existing fire module was modified to include 'escaped fire' associated with deforestation,...
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The integrity of Amazon forests are currently threatened by climate change, deforestation, and fire. However, it is unclear how these agents of change interact over large spatial and temporal domains and reducing this uncertainty is important for projecting changes in carbon stocks and species biogeography, and could better inform continental scale conservation programs. With this in mind, aboveground biomass and tree cover data were produced using the dynamic global vegetation model, LPJmL, with 9 different global climate models (using the SRES A2 emissions storyline) and 2 different deforestation scenarios (from Soares et al.). The existing fire module was modified to include 'escaped fire' associated with deforestation,...


map background search result map search result map Percent change in above ground tree cover for the Amazon Basin under UKMO HADCM3 climate and GOVernance deforestation scenarios with no fire (2020s) Percent change in above ground tree cover for the Amazon Basin under UKMO HADCM3 climate scenario and current deforestation with no fire (2080s) Percent change in above ground tree cover for the Amazon Basin under MPI ECHAM 5 climate and GOVernance deforestation scenarios with fire (2020s) Aboveground biomass (Mg C/ha) for the Amazon Basin under UKMO HADGEM1 climate, no deforestation, and no fire scenarios (2040s) Aboveground biomass (Mg C/ha) for the Amazon Basin under UKMO HADGEM1 climate, no deforestation, and fire scenarios (2060s) Aboveground biomass (Mg C/ha) for the Amazon Basin under UKMO HADGEM1 climate, current deforestation (BAU), and fire scenarios (2080s) Aboveground biomass (Mg C/ha) for the Amazon Basin under GISS climate, no deforestation, and no fire scenarios (2020s) Aboveground biomass (Mg C/ha) for the Amazon Basin under GFDL CM2 climate, no deforestation, and fire scenarios (2080s) Gorum and others (2014) Hydrologic Derivatives for Modeling and Analysis (HDMA) database -- South America Gorum and others (2014) Percent change in above ground tree cover for the Amazon Basin under UKMO HADCM3 climate and GOVernance deforestation scenarios with no fire (2020s) Percent change in above ground tree cover for the Amazon Basin under UKMO HADCM3 climate scenario and current deforestation with no fire (2080s) Percent change in above ground tree cover for the Amazon Basin under MPI ECHAM 5 climate and GOVernance deforestation scenarios with fire (2020s) Aboveground biomass (Mg C/ha) for the Amazon Basin under UKMO HADGEM1 climate, no deforestation, and no fire scenarios (2040s) Aboveground biomass (Mg C/ha) for the Amazon Basin under UKMO HADGEM1 climate, no deforestation, and fire scenarios (2060s) Aboveground biomass (Mg C/ha) for the Amazon Basin under UKMO HADGEM1 climate, current deforestation (BAU), and fire scenarios (2080s) Aboveground biomass (Mg C/ha) for the Amazon Basin under GISS climate, no deforestation, and no fire scenarios (2020s) Aboveground biomass (Mg C/ha) for the Amazon Basin under GFDL CM2 climate, no deforestation, and fire scenarios (2080s) Hydrologic Derivatives for Modeling and Analysis (HDMA) database -- South America