The geospatial dataset includes raster and vector data for visualizing the spatial distribution of risk of wildfire-caused carbon loss in Peeler et al. 2023. Raster data evaluate carbon exposure, sensitivity, and vulnerability at the pixel-level across western US carbon forests. Vector data aggregate pixel-level findings into project area and fireshed spatial units to identify target geographies (or “opportunity hot spots”) where proactive forest management could reduce the greatest risk from wildfire to carbon. Vector data also identifies firesheds in which proactive forest management could simultaneously reduce the risk from wildfire to carbon and human communities.
Raster data: The geospatial dataset includes raster data representing exposure (“exposure.tif”), sensitivity (“sensitivity.tif”), and vulnerability (“vulnerability.tif”) of carbon to wildfire at the pixel-level (30 m resolution). Exposure is visualized as a bivariate map in which normalized indicators are divided into three quantiles to create low, moderate, and high categories for total carbon (not including carbon in organic soils) and annual burn probability. Similarly, normalized indicators of carbon loss (i.e., wildfire-caused carbon loss through emissions and decomposition) and carbon recovery (i.e., site productivity and post-wildfire conifer regeneration probability) are divided into three quantiles to create a bivariate map for sensitivity. Finally, three quantiles are applied to normalized composite indicators for exposure and sensitivity to create categories and a bivariate map for vulnerability. All individual indicators were derived from pre-existing geospatial datasets that are detailed in the metadata.
Vector data: This geospatial dataset includes vector data representing opportunity hot spots for reducing wildfire-caused carbon loss at the project area-level (~10,000 ha) (“proj_area_carbon.shp”) and fireshed-level (~100,000 ha) (“fireshed_carbon.shp”). Project areas are considered opportunity hot spots if they contain the greatest area (top 10%) of carbon most vulnerable to wildfire-caused loss and enough treatable forest area (>18%) to reduce wildfire hazard. A fireshed is considered an opportunity hot spot if it contains at least one project area meeting these criteria. Treatable forest area is estimated using biological, legal, and operational constraints from pre-existing geospatial datasets that are detailed in the metadata.
Vector data also visualizes where opportunity hot spots at the fireshed-level overlap with high risk firesheds in the US Forest Service’s Wildfire Crisis Strategy (“fireshed_carbon_communities.shp”). High risk firesheds identify locations in the western US that contain the greatest community exposure to wildfire (see Ager et al. 2019 and Ager et al. 2021 for more details). Accordingly, areas of overlap suggest that these locations contain opportunties for proactive forest management to simultaneously reduce the greatest risk from wildfire to carbon and communities.
The geospatial dataset is only accessible on datadryad.org. As noted, pre-existing geospatial datasets were used to create the raster and vector data. Details on the pre-existing geospatial datasets are included in the metadata.