U.S. Department of Agriculture1. Hourly streambed and air temperature data for the South Umpqua Experimental Forest
- Author(s):
- Anderson, Paul D.
2. Greenhouse gas emissions and removals from forest land and woodlands in the United States, 1990-2024: Estimates and quantitative uncertainty for individual states, regional ownerships, National Forests, and Tribal ownership
- Author(s):
- Walters, Brian F.; Domke, Grant M.; Knott, Jonathan A.; Smith, James E.; Nash, Joseph M.; Ogle, Stephen M.
3. Fossil Creek Wild and Scenic River: Visitor experience monitoring survey 2024
- Author(s):
- Rushing, Jaclyn Fox; Armatas, Christopher A.; Bramblett, Timothy; Thomsen, Jennifer M.
4. Manitou Experimental Forest hourly meteorology data (4th Edition)
- Author(s):
- Frank, John M.; Fornwalt, Paula J.; Asherin, Lance A.; Alton, Steven K.; Valentine, George P.
5. Soil and foliar elements and overstory tree and regeneration data from the biomass harvest and prescribed fire experiment at the Penobscot Experimental Forest, Maine, USA, 2014-2025
- Author(s):
- Abramoff, Rose Z.; Muñoz Delgado, Bethany L.; Kenefic, Laura S.; Fernandez, Ivan J.
6. Greenhouse gas emissions and removals from forest land, woodlands, urban trees, and harvested wood products in the United States, 1990-2023: Estimates and quantitative uncertainty for individual states, regional ownerships, National Forests, and Tribal ownership
- Author(s):
- Walters, Brian F.; Domke, Grant M.; Greenfield, Eric J.; Smith, James E.; Ogle, Stephen M.; Knott, Jonathan A.
7. Vegetation structure and composition of ecological succession stages and land uses in Puerto Rico
- Author(s):
- Crespo-Zapata, Johann D.; Maldonado-Silvestrini, Steve; García-García, Neishaly; Gould, William A.
8. Ponderosa pine growth and yield measurements before and after mountain pine beetle attack on Black Hills Experimental Forest growing stock level plots
- Author(s):
- Graham, Russell T.; Asherin, Lance A.; Jain, Theresa B.; Baggett, L. Scott; Battaglia, Michael A.
9. Testing and training data for machine learning models to detect, classify and count blackbirds damaging agriculture using drone-based imagery
- Author(s):
- Duttenhefner, Jessica L.; ElSaid, AbdElRahman A.; Klug, Page E.
10. Uncrewed aerial system imagery and collocated validation field plots from assessment of forest spatial pattern in Black Hills South Dakota, USA restoration treatments
- Author(s):
- Tinkham, Wade T.; Battaglia, Michael A.; Woolsey, George A.