Location: Food Systems Research Unit
Title: Engaging stakeholders to strengthen coproduction of knowledge in the Long-Term Agroecosystem Research (LTAR) indicator frameworkAuthor
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DELONG, ALIA - Archbold Biological Station |
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McIntosh, Matthew |
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Donovan, Megan |
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Spiegal, Sheri |
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BOUGHTON, ELIZABETH - Archbold Biological Station |
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SWAIN, HILARY - Archbold Biological Station |
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SILVEIRA, MARIA LUCIA - University Of Florida |
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SELLERS, BRENT - University Of Florida |
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HURST, ZACHARY - Playa Lakes Joint Venture |
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Bestelmeyer, Brandon |
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Submitted to: Journal of Environmental Quality
Publication Type: Peer Reviewed Journal Publication Acceptance Date: 9/16/2025 Publication Date: 10/16/2025 Citation: Delong, A.N., Mcintosh, M.M., Donovan, M.E., Spiegal, S.A., Boughton, E.H., Swain, H.M., Silveira, M.A., Sellers, B., Hurst, Z.M., Bestelmeyer, B.T. 2025. Engaging stakeholders to strengthen coproduction of knowledge in the Long-Term Agroecosystem Research (LTAR) indicator framework. Journal of Environmental Quality. 54(6): 151-1534. https://doi.org/10.1002/jeq2.70102. DOI: https://doi.org/10.1002/jeq2.70102 Interpretive Summary: Changes in agriculture increase the pressure on researchers to address community needs. Scientists in the Long-term Agroecosystem Research (LTAR) network have been developing a framework to enable informed decision-making. The framework is for people interested in agricultural management and scientists. We compared two examples from LTAR sites where scientists addressed local needs through engagement to develop a more relevant framework. Examples are from the Jornada Experimental Range (JER; New Mexico) and Archbold Biological Station-University of Florida (ABS-UF). The JER approach involved less structured engagement, while the example from ABS-UF highlights a structured, exploratory process. Both approaches had different outcomes based on local community needs. To ensure the framework is useful to as many users as possible, stakeholder engagement in the future should combine the approaches to (1) confirm and explore the most important indicators to the community, and (2), verify the indicator framework is easy to use and based on the local community. Technical Abstract: Rapid change in climatic conditions drives agricultural production research and innovation forward at an unprecedented pace. Scientists in the Long-term Agroecosystem Research (LTAR) network have been developing a performance indicator framework to make informed decisions amidst fast-paced management uncertainty. The framework is designed for stakeholders (e.g., producers, land managers, and service providers, among others) as well as investigatory scientists. Stakeholder engagement strategies are in line with LTAR’s mission to produce tools that are “useful, usable, and used,” because they aim to identify and meet stakeholder needs in order to ensure general usability. We present two examples of methods for scientists to meet stakeholder needs at local and regional levels through direct researcher-stakeholder engagement in the development of a relevant sustainability framework (i.e., coproduction of knowledge). Both examples are from LTAR sites, the Jornada Experimental Range (JER; New Mexico) and Archbold Biological Station-University of Florida (ABS-UF). JER highlights one form of engagement that is less structured, while the example from ABS-UF demonstrates a structured, decision-making process. At the JER, a group of researchers proposed performance indicators informed by previous collaboration with ranchers, observations of rancher priorities, and standardized indicators of rangeland health. Participating ranchers identified prevailing and aspirational outcomes of interest to be used as the building blocks for benchmarking. At ABS-UF, an advisory council representing a cross-section of local stakeholders had the opportunity to propose high priority performance indicators for inclusion in a modified framework. These two examples demonstrate how to incorporate stakeholder engagement to strengthen LTAR’s overall indicator framework while meeting the needs of context-specific use cases. |
