Publication Details
- Title:
- Maps of abiotic susceptibility versus fire-induced conversion to cheatgrass dominance in the sagebrush biome and associated data
- Author(s):
-
Board, David I.; Urza, Alexandra K.; Bradford, John B.; Brown, Jessi L.; Chambers, Jeanne C.; Schlaepfer, Daniel R.; Short, Karen C. - Publication Year:
- 2024
- How to Cite:
-
These data were collected using funding from the U.S. Government and can be used without additional permissions or fees. If you use these data in a publication, presentation, or other research product please use the following citation:
Board, David I.; Urza, Alexandra K.; Bradford, John B.; Brown, Jessi L.; Chambers, Jeanne C.; Schlaepfer, Daniel R.; Short, Karen C. 2024. Maps of abiotic susceptibility versus fire-induced conversion to cheatgrass dominance in the sagebrush biome and associated data. Fort Collins, CO: Forest Service Research Data Archive. https://doi.org/10.2737/RDS-2024-0041
- Abstract:
- This data publication contains the results of four models of cheatgrass presence or dominance within the sagebrush biome from plot level data collected from 2004 through 2019 projected onto simulated predictions of climate and soil water availability based on the norms from 1980 through 2019 for the sagebrush biome of the western United States and two associated maps that combine the conditional models with fire risk assessment of 2020 fuelscape to better understand the impact of fire risk on cheatgrass presence or dominance risk. These data include: 1) predictive maps for the probability of the presence or dominance (>15% relative cover) for cheatgrass, Bromus tectorum, under burned and unburned conditions (4 raster files); 2) predictive maps for the total risk of cheatgrass presence or dominance given the determined fire risk (2 raster files); and 3) predictive maps of susceptibility of cheatgrass presence or dominance categories (susceptible to presence or dominance regardless of fire, resistant to presence or dominance regardless of fire, fire-induced dominance, and fire-reduced dominance) (2 raster files).
Also included are the plot level data used to create the models, which includes plot level climate and soil water availability predictions based on SOILWAT2 ecohydrological model and cheatgrass cover as recorded on site and cheatgrass relative cover (cheatgrass cover / sum of all species covers recorded on site) used to build the models (1 tabular file). Additionally, the raster of ecohydrologic conditions that the model was projected on to which includes predictive maps of climate and soil water availability long-term normals and interannual variability (1980-2019) that allowed the mapping of the models across the sagebrush biome (1 categorical raster file and 1 raster attribute table). - Keywords:
- biota; Ecology, Ecosystems, & Environment; Ecology; Landscape ecology; Plant ecology; Geography; Fire; Fire ecology; Forest & Plant Health; Botany; Invasive species; Rangeland plants; Natural Resource Management & Use; Range management & grazing; Landscape management; biogeography; sagebrush; cheatgrass; resistance to invasion; resistance; dominance; fire-induced conversion; grass-fire cycle; invasive annual grass; species distribution model; climate suitability; arid; semi-arid; invasive plants; JFSP; Joint Fire Science Program; western United States; Utah; Nevada; California; Oregon; Washington; Montana; Idaho; Wyoming; Arizona; New Mexico; Colorado; North Dakota; South Dakota; North America; Intermountain West; Great Basin; sagebrush biome
- Related publications:
- Urza, Alexandra K.; Board, David I.; Bradford, John B.; Brown, Jessi L.; Chambers, Jeanne C.; Schlaepfer, Daniel R.; Short, Karen C. 2024. Disentangling drivers of annual grass invasion: Abiotic susceptibility vs. fire-induced conversion to cheatgrass dominance in the sagebrush biome. Biological Conservation. 297: 110737. https://doi.org/10.1016/j.biocon.2024.110737
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More details - Data Access:
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- Download all files below for the complete publication:
- RDS-2024-0041_Metadata_Fileindex.zip (47.73 KB; sha256: 455da8b594b98b3e39fa59712df9eabee0dfe154001163647a824e1db48daa6fChecksum)
- RDS-2024-0041_Data_1_Conditional_Models.zip (5.91 GB; SHA256: 5f5a62ab8adaa7339d8af258a7235650a52d020e496a0ef3b93809b0a9f0fcc7Checksum)
- RDS-2024-0041_Data_2_Total_Risk.zip (8.95 GB; SHA256: ebc19987aee2f1e1f393ff018b97881920e3562136cc38891571bc52631fd088Checksum)
- RDS-2024-0041_Data_3_Susceptability_Categories.zip (1.58 GB; SHA256: 0e82acd984e9ecbc7ef8153600f14f8a792de536aeb0963ceebbd7e01bbb2d23Checksum)
- RDS-2024-0041_Data_S1_Plot_Data.zip (4.18 MB; sha256: 30086f9964f92474c461424c167325c81ce78f6d2bc027de28758b4db96f2889Checksum)
- RDS-2024-0041_Data_S2_Prediction_Surface.zip (318 MB; sha256: d3bf5366594667e60a55f9314fba617c1d56f17121cfc8456a134ae897b84ffdChecksum)
- RDS-2024-0041_Metadata_Fileindex.zip (47.73 KB;
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