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Colorado State University (2012)

An alternate state approach to range management in the sagebrush steppe

Kachergis, Emily

Titre : An alternate state approach to range management in the sagebrush steppe

Auteur : Kachergis, Emily

Université de soutenance : Colorado State University

Grade : Doctor of Philosophy (Ph.D.) 2012

Résumé
Describing and predicting sudden shifts between alternate states in ecosystems is a frontier in ecology with important implications for natural resource management and human well-being. The range profession has recently adopted an approach to land management decision-making based on alternate state theory. The Natural Resource Conservation Service and partners are creating state and transition models (STMs), conceptual models that describe shifts in ecosystems, for many types of land throughout the US. Motivated by this national STM-building effort, this dissertation has two practical objectives : 1) to create data-driven STMs that describe sagebrush steppe ecosystem response to management, and 2) to develop guidelines for STM creation. A third objective grew out of the need to create theoretically accurate STMs : to determine whether spatial and temporal patterns of vegetation in northwest Colorado sagebrush steppe are consistent with predictions of alternate state theory. The first chapter introduces this work with a review of alternate state theory and how it is applied in constructing STMs. I conducted an observational study of sagebrush steppe response to management practices and ecological disturbances on two soil types in the lower Elkhead watershed. The second chapter examines plant species composition as an indicator of alternate states, a test of the current approach to building STMs. The third chapter investigates whether areas with different structure also differ in function, as predicted by alternate state theory. The fourth chapter compares trait-based group composition to species composition as an indicator of alternate states. From these chapters, I conclude that there are large, management-relevant differences in species composition within environmentally similar areas and that many of these differences are related to site history, as would be expected if these represent alternate states. The Indicators of Rangeland Health show that some states defined by species composition are associated with unique processes that may serve as positive feedback mechanisms which maintain alternate states. Relationships between species composition, processes and environmental gradients suggest that environmental variation may make some transitions between states more likely and should be acknowledged in STMs. Multiple-trait based group composition identifies many of the same potential states and transitions as species composition, but is also sensitive to some different management practices. The Indicators of Rangeland Health and plant traits are simple additions to current STM-building methods that can improve and expedite STM creation. In the final chapter, I describe long-term sagebrush steppe dynamics based on 50 years of monitoring data from the upper Elkhead watershed and evaluate evidence for alternate states. Gradual changes in composition after spraying and the steady increase of a non-native grass suggest that this high-elevation sagebrush steppe ecosystem does not experience sudden shifts between alternate states. I conclude that the alternate state approach to range management shows promise for describing management-relevant ecosystem dynamics and organizing current knowledge. Given the equivocal evidence supporting predictions of alternate state theory for Elkhead watershed sagebrush steppe, further research should determine which aspects of alternate state theory must be confirmed to create useful STMs. In addition, long-term monitoring, modeling, and experiments are needed to validate and update models as we learn more about the sagebrush steppe.

Mots Clés : decision-making tool ; ecological site ; northwestern Colorado ; USA ; plant traits ; state-and-transition model ; vegetation dynamics

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Page publiée le 27 octobre 2012, mise à jour le 8 septembre 2017