Project Number: 2070-21630-003-011-S
Project Type: Non-Assistance Cooperative Agreement
Start Date: Sep 15, 2019
End Date: Sep 14, 2024
ARS Burns has been a strong science partner in Cooperator, High Desert Partnership (HDP), which has convened and supported collaborative ecological initiatives for over 10 years. The principles (i.e., shared science and learning) the Cooperator uses for supporting collaboration have been key in achieving consensus among diverse partners and producing tangible strategies for restoration or conservation of millions of acres of ag-associated rangelands and meadows in eastern Oregon. Science is an integral part of the collaborative process, because these collaboratives address complex problems that have no easy management solutions and thus require an adaptive approach. Science helps bring diverse stakeholders to consensus and project-associated science and monitoring activities complete the feedback loop that allows adaptive management to occur. Ongoing science outreach by ARS Burns has resulted in collaboratively derived, science-based frameworks that are accepted by a diverse array of stakeholders including agricultural producers, federal and state land management agencies, multiple non-governmental organizations (NGO's), state wildlife agencies, federal regulatory agencies, local and county government, and local conservation entities. These frameworks are helping to mitigate the complex management issues impacting availability of rangeland forage resources (e.g., exotic annual grass invasion, expansion of native conifer species, and wildfire). ARS participation as science advisors in these collaborative efforts creates a mechanism for ARS to apply existing research results at management-relevant scales and provides the opportunity to imbed new research questions into large scale management activities. However, ARS has limited capacity to monitor the results of large scale management projects. The Cooperator has the potential to carry out monitoring to inform the partners in shared decision making that supports adaptive management of complex ecosystem problems and simultaneously provides ARS data to help advance the science behind that management. Specific objectives of this agreement are: 1. With technical input from ARS Burns, the Cooperator will collect monitoring data on large scale collaborative management initiatives focused on reducing exotic annual grasses, limiting spread and stand development of native conifers, and fuels management to reduce wildfire potential. 2. The Cooperator will provide data collected to ARS for analysis, interpretation, and development of reports and publications that will be used to inform structured decision-making within a collaborative adaptive management framework and will be the basis of peer-review publications and management bulletins to inform similar efforts to address complex problems in other parts of the Great Basin or similar ecosystems.
The Cooperator will assist ARS scientists by implementing collaboratively developed monitoring of restoration projects that are part of the collaborative ecological initiatives supported by the Cooperator. ARS and the Cooperator will work together with stakeholders in collaboratives to design and implement ecologically-based adaptive management plans, with an emphasis on the development of monitoring protocols to collect data needed for shared learning and adaptive decision-making. Cooperator-conducted monitoring will result in increased capacity for ARS science delivery to meet the ongoing and increasing needs and demands of solving complex landscape scale issues. Collaboratively-developed projects provide unique opportunities for ARS to adaptively test management alternatives at the landscape scale; the scale at which primary threats to the ecosystem unfold and solutions are needed. Plot scale research remains a vital component of ARS research but landscape scale implementation of innovative solutions within Cooperator-supported ecological initiatives would afford ARS scientists opportunity to test alternatives at scales most relevant for developing viable solutions.