Justin L Welty
Biographic Data
| ID | 7992375 |
|---|---|
| NAME | Justin L Welty |
| GIVEN NAMES | Justin L |
| FAMILY NAME | Welty |
| SIGNATURE | WELTY J L |
| AFFILIATIONS | United States Geological Survey |
| ORCID | 0000-0001-7829-7324 |
| VERIFIED | Yes |
| TOTAL WORKS | 2 |
| TOTAL CITATIONS | 0 |
| AUTHOR COUNT | 2 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2021 |
| LATEST PUBLICATION YEAR | 2022 |
| H-INDEX | 0 |
Ten practical questions to improve data quality
High-quality rangeland data are critical to supporting adaptive management. However, concrete, cost-saving steps to ensure data quality are often poorly defined and understood. Data quality is more than data management. Ensuring data quality requires 1) clear communication among team members; 2) appropriate sample design; 3) training of data collectors, data managers, and data users; 4) observer and sensor calibration; and 5) active data manageme…
Evaluating establishment of conservation practices in the Conservation Reserve Program across the central and western United States
The U.S. Department of Agriculture’s Conservation Reserve Program (CRP) is one of the largest private lands conservation programs in the United States, establishing perennial vegetation on environmentally sensitive lands formerly in agricultural production. Over its 35 year existence, the CRP has evolved to include diverse conservation practices (CPs) while concomitantly meeting its core goals of reducing soil erosion, improving water quality, an…
No prominent works on this page.
Evaluating establishment of conservation practices in the Conservation Reserve Program across the central and western United States
The U.S. Department of Agriculture’s Conservation Reserve Program (CRP) is one of the largest private lands conservation programs in the United States, establishing perennial vegetation on environmentally sensitive lands formerly in agricultural production. Over its 35 year existence, the CRP has evolved to include diverse conservation practices (CPs) while concomitantly meeting its core goals of reducing soil erosion, improving water quality, an…
Ten practical questions to improve data quality
High-quality rangeland data are critical to supporting adaptive management. However, concrete, cost-saving steps to ensure data quality are often poorly defined and understood. Data quality is more than data management. Ensuring data quality requires 1) clear communication among team members; 2) appropriate sample design; 3) training of data collectors, data managers, and data users; 4) observer and sensor calibration; and 5) active data manageme…
Environmental Science (2 works) · Rangeland and Wildlife Management (2 works) · Agriculture (1 works) · Agroforestry (1 works) · Biology (1 works) · Business (1 works) · Citizen science (1 works) · Computer Science (1 works) · Conservation Reserve Program (1 works) · Cover crop (1 works)