Location: Rangeland Resources & Systems Research
Project Number: 3012-21500-001-008-S
Project Type: Non-Assistance Cooperative Agreement
Start Date: Apr 26, 2021
End Date: Jun 30, 2024
Objective:
Conduct a strategic planning and visioning process for the Long-Term Agroecosystem Research (LTAR) Network that will result in clarity and direction for network research including air quality, climate change and other emphasis areas.
Approach:
The Cooperator and ARS will collaborate through a professional facilitator to lead the strategic planning and visioning process for the Long-Term Agroecosystem Research (LTAR) network. The LTAR Network was established in 2014 to perform coordinated, stakeholder-engaged research across geographically distributed sites to accelerate the sustainable intensification of US agriculture. The LTAR Network now uses region-specific coordinated experiments, cross-site and transdisciplinary collaboration via working groups, coordinated data management and tool development, and site and network-level stakeholder engagement to pursue sustainable intensification goals. The guiding principles of the LTAR Network (LTAR Shared Research Strategy) were established in 2014, but agricultural science concepts, tools, and the policy context have changed significantly since that time. The LTAR Network needs updated internal guidance on sustainability goals and operational procedures as well as how to scale up impacts and evaluate progress. The Network also needs assistance to integrate its diverse activities into an understandable form, both internally within USDA as well as for USDA’s diverse stakeholders. The strategic planning process would involve structured interviews and surveys followed up by several workshop activities involving LTAR leadership (including ARS Office of National Programs), LTAR scientists and staff, and key stakeholders. An outcome is development of iterative drafts culminating in a final strategic plan. A glossy brochure and web-ready materials will be developed to summarize the strategic plan and this material will be delivered to stakeholders. It is foreseen that this LTAR strategic planning effort will lead to improved standardization and automation of data being collected across the LTAR Network. Developing this type of an interoperable data system directly supports the development of Artificial Intelligence (AI) and machine learning (ML) tools needed for future air quality and climate change research.
