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Grazed rangeland ecosystems encompass diverse global land resources, and are complex social-ecological systems from which society demands both goods (e.g., livestock and forage production) and services (e.g., abundant and high quality water). Both quantitative and qualitative assessments indicate a key need for collaborative development, design, and testing of management hypotheses at scales most relevant to linked ecological and economic systems. To address this key need, our research team has partnered with diverse stakeholder groups to conduct a long-term, ranch-scale experiment evaluating the effectiveness of adaptive grazing management for multiple social-ecological services. We invited 55 rangeland stakeholders to two day-long workshops to identify land management goals and strategies for 485 hectares of annual, winter growing season rangeland at a University of California rangeland research facility in Northern California. These stakeholder participants included traditional ranchers running a livestock economic enterprise, conservation professionals who use grazing to pursue environmental goals, and professional rangeland managers who serve clientele with diverse goals. Participants in each workshop were divided into four groups (i.e., one homogenous group of each stakeholder type, as well as one mixed group) and asked to discuss goals, challenges to achieving goals, and management strategies they would like to see tested. Throughout the workshops, we used computer-based surveys to capture recommended goals, challenges and management strategies. We also used a network approach to examine the mental models and social learning processes within each of the four groups. Representatives from the workshops were asked to serve on an advisory board, which we have continued to work with in implementing, adapting, and examining the effectiveness of the stakeholder prescribed strategies. Here, we highlight lessons from this project, including ongoing results and benefits of this “bottom-up” network approach and the social and ecological constraints in integrating adaptive, landscape-level science and management.