Location: Forage and Range Research
Project Number: 2080-21500-002-002-S
Project Type: Non-Assistance Cooperative Agreement
Start Date: May 1, 2020
End Date: Apr 30, 2024
Objective:
1. Evaluate the economic and financial impact associated with improving rangelands by using improved native and introduced dryland cultivars/germplasm developed by, the USDA, ARS Forage and Range Research Unit (FRR) Logan, UT to rehab land after disturbances and fires.
2. Evaluate the economic and financial impact associated with improving irrigated pastures by using improved grass and legume cultivars and management practices developed by the USDA, ARS Forage and Range Research Unit, Logan, UT.
3. Evaluate the economic and financial impact associated with turfgrass research to including drought and saline tolerant grasses for use in limited water environments across the Western U.S.
Approach:
Ranchers/Farmers frequently ask, what is the economic return if we use the new plant materials and management strategies developed at the Forage and Range Research Unit (FRR)? To answer this question and other related to rangeland restoration, forage pasture production, and the economic savings of using turf varieties more drought and saline tolerant, we are proposing to form a collaborative research project with Agricultural Economists at Utah State University to provide economic expertise. The FRR has been improving rangeland, pasture, and Turf species and studying their adaptation and performance over the past 30 years. This data and others obtained from the private and public sector will be contributed by ARS scientists at Logan, Utah. Utah State University agricultural economists will provide the economic expertise and models to evaluate rangeland, pasture, and turf management alternatives. Expected outcomes will include an economical/financial analysis of improving rangelands, pastures, and turf environments with improved plant materials. The economical/financial analysis may include partial budgeting, net present value analysis, simulation, and regression models. In addition, it will likely identify gaps in the types of plant materials, seed traits, and management protocols that can be improved to become more economically sustainable.
