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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,...
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,...
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,...
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,...
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,...
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,...
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,...
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,...
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,...
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,...
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,...
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,...
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,...
This dataset represents the historical majority vegetation type (30 year mode), for each HUC5 watershed, simulated by the model MC1 for the 30-year period 1971-2000. Majority vegetation type was determined for each HUC5 watershed by calculating the 30 year mode from original ~ 4 km raster data. Watersheds represent 5th level (HUC5, 10-digit) hydrologic unit boundaries and were acquired from the Natural Resources Conservation Service. Background: The dynamic global vegetation model MC1 (see Bachelet et al.2001) was used to simulate vegetation dynamics, associated carbon and nitrogen cycle, water budget, a nd wild fire impacts for OR, WA, AZ and NM, for a project funded by the USDA Forest Service (PNW09-JV-11261900-003)....
Percent change in average soil carbon for each HUC5 watershed between historical (1971-2000) and future (2071-2100) time periods. The MC1 dynamic vegetation model was run under the CSIRO, MIROC, and Hadley climate change projections and the A2 anthropogenic emissions scenario. Soil carbon, in g m-2., was determined for each HUC5 watershed. Watersheds represent 5th level (HUC5, 10-digit) hydrologic unit boundaries and were acquired from the Natural Resources Conservation Service. Background: The dynamic global vegetation model MC1 (see Bachelet et al. 2001) was used to simulate vegetation dynamics, associated carbon and nitrogen cycle, water budget, and wild fire impacts for OR, WA, AZ and NM, for a project funded...
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,...
This dataset represents the historical mean annual area burned per ~ 4 km pixel, averaged for each HUC5 watershed, simulated by the model MC1 for the 30-year period 1971-2000. Historical mean area burned per year (in square meters) per ~4 km pixel was averaged across each HUC5 watershed. Watersheds represent 5th level (HUC5, 10-digit) hydrologic unit boundaries and were acquired from the Natural Resources Conservation Service. Background: The dynamic global vegetation model MC1 (see Bachelet et al.2001) was used to simulate vegetation dynamics, associated carbon and nitrogen cycle, water budget, and wild fire impacts for OR, WA, AZ and NM, for a project funded by the USDA Forest Service (PNW09-JV-11261900-003)....
Percent change in the average annual precipitation for each HUC5 watershed between historical (1971-2000) and future (2071-2100) time periods. The MC1 dynamic vegetation model was run under the CSIRO, MIROC, and Hadley climate change projections and the A2 anthropogenic emissions scenario. Simulated mean annual precipitation (in mm H2O yr-1), was determined for each HUC5 watershed by averaging values of original ~ 4 km raster data. Watersheds represent 5th level (HUC5, 10-digit) hydrologic unit boundaries and were acquired from the Natural Resources Conservation Service. Background: The dynamic global vegetation model MC1 (see Bachelet et al. 2001) was used to simulate vegetation dynamics, associated carbon...
Percent change in the average potential evaporation for each HUC5 watershed between historical (1971-2000) and future (2071-2100) time periods. The MC1 dynamic vegetation model was run under the CSIRO, MIROC, and Hadley climate change projections and the A2 anthropogenic emissions scenario. Simulated mean potential evaporation (in mm H2O yr-1), was determined for each HUC5 watershed by averaging values of original ~ 4 km raster data. Watersheds represent 5th level (HUC5, 10-digit) hydrologic unit boundaries and were acquired from the Natural Resources Conservation Service. Background: The dynamic global vegetation model MC1 (see Bachelet et al. 2001) was used to simulate vegetation dynamics, associated carbon...
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