Improving state-and-transition models for management of sagebrush steppe ecosystems - Tipton, Crystal Yates-White, author; Fernandez-Gimenez, Maria, advisor; Ocheltree, Troy, advisor; Aldridge, Cameron, committee member (Colorado State University. Libraries, 2015)
The sagebrush biome was once the most widely-distributed in North America, but has recently experienced range reductions of up to 45% and has been considered one of the most endangered ecosystems in the United States (West 1983, Noss et al. 1995, Miller et al. 2011). Management for multiple land-use goals in this biome is complex, requiring an intricate understanding of biotic and abiotic interactions, their responses to disturbance, and the potential for catastrophic ecosystem shifts in response to stress. State-and-transition models (STMs) illustrate the complex relationships between ecosystem components and convey both equilibrial and non-equilibrial dynamics, in a conceptual, visual framework (Westoby et al. 1989, Walker and Westoby 2011). Recognizing their potential to guide both research and management decision-making, the Natural Resource Conservation Service, U.S. Forest Service, and Bureau of Land Management recently signed an interagency agreement to develop and use STMs to guide rangeland management decision-making nation-wide (Caudle et al. 2013). The growing popularity of STMs has brought them under increased scrutiny (Knapp et al. 2011, Tidwell et al. 2013). Common criticisms of STMs include: 1) reliance on insufficient empirical datasets or knowledge-based data prone to bias; 2) failure to explicitly identify the spatial and temporal scale of the model and the limitations of its generalizability; 3) dependency on assumptions of linear, reversible succession toward a climax reference community while ignoring the roles of non-equilibrial change, multiple disturbance types and abiotic gradients in shaping system resilience; 4) focus on the practices associated with structural change, while overlooking the ecological process feedbacks that influence disturbance response; 5) failure to validate STMs by testing model predictions. Motivated by the need for improved sagebrush-steppe management tools, my thesis addresses these criticisms and challenges by exploring new approaches to build and refine STMs. The first chapter provides a review of sagebrush-steppe ecosystem dynamics, paradigms of vegetation change, and the application of STMs to natural resource management. The second chapter presents work to apply a collaborative, iterative approach proposed by Kachergis et al. (2013c) that integrates knowledge-based and empirical datasets to develop an STM for a Wyoming big sagebrush-steppe ecosystem in Moffat County, Colorado. The third chapter presents a pilot project to revise an existing STM by incorporating the role of specific ecological processes (nitrogen cycling) into a state transition. I conclude that the approaches employed here can address many of the challenges and criticisms of current STMs, but should be coupled with rigorous experimental testing of model assumptions and uncertainties and long-term monitoring of experimental outcomes. In addition, collaborative approaches should take care to carefully balance resource limitations with the desire to include a broad base of stakeholders and research interests, carefully manage stakeholder expectations, and explicitly define success in terms of both the collaborative process and the scientific outcomes.
Keywords: adaptive management; brush management; cheatgrass; nitrogen; sagebrush; state-and-transition