干旱区生态环境知识资源中心

State-and-transition models (STMs), conceptual models of vegetation change based on alternate state theory, are increasingly applied as tools for land management decision-making. As STMs are created throughout the United States, it is crucial to ensure that they are supported by ecological evidence. Plant species composition reflects ecosystem processes that are difficult to measure and may be a useful indicator of alternate states. This study aims to create data-driven STMs based on plant species composition for two ecological sites (Claypan and Mountain Loam) in northwestern Colorado sagebrush steppe. We sampled 76 plots with different management and disturbance histories. Drawing on the hierarchical approach currently taken to build STMs, we hypothesized that A) differences in species composition between the two ecological sites would be related to environmental factors and B) differences in species composition within each ecological site would be related to management and disturbance history. Relationships among species composition, site history, and environmental variables were evaluated using multivariate statistics. We found that between ecological sites, species composition was related to differences in soil texture, supporting Hypothesis A and the creation of separate STMs for each site. Within ecological sites, species composition was related to site history and also to environmental variation. This finding partially supports Hypothesis B and the identification of alternate states using species composition, but also suggests that these ecological sites are not uniform physical templates upon which plant community dynamics play out. This data-driven, plant species based approach created two objective, credible STMs with states and transitions that are consistent with the sagebrush steppe literature. Our findings support the hierarchical view of landscapes currently applied in building STMs. An approach that acknowledges environmental heterogeneity within ecological sites is necessary to help define finer-resolution ecological sites and elucidate cases in which specific abiotic conditions make transitions between states more likely.