An evaluation of state-and-transition model development for ecological sites in northern Utah.

摘要

Ecological sites and state-transition models (STMs) have become the preferred means of summarizing plant community dynamics on distinctive types of rangeland. Ecological sites classify rangeland types based on soil-geomorphic and climatic conditions capable of producing a known plant community, while a STM depicts the vegetation dynamics of an ecological site. STMs are usually based on expert opinion rather than site-specific data; however, if they are to gain credibility, STMs must accurately describe the processes that drive plant community dynamics. This study examined three ways of developing process-based STMs using three levels of commonly collected field data. We began by taking field inventories of three ecological sites already mapped in northwestern Utah: Loamy Bottom, Mountain Gravelly Loam, and Upland Loam. The Loamy Bottom site was ideal for developing a data-rich, process-based STM because 1) the site concepts were well-defined, 2) the site was easy to recognize, 3) potential states and transitions had already been hypothesized, and 4) the site was easily accessible. The Loamy Bottom study was designed to link plant community structural indicators to measurable indicators of ecological process. Principal components analysis and cluster analysis were used to classify 14 study plots into four distinct states. Simple linear regression showed relationships between perennial grass cover, perennial canopy gaps, and soil organic carbon. Analysis of variance (ANOVA) linked four general vegetation classes to soil stability measurements. The resulting STM describes the structure and function of four alternative states. The other two STMs, developed for the Mountain Gravelly Loam and Upland Loam ecological sites, used less-intensive data collection methods. Rangeland health assessments, used for the Upland Loam STM, are useful for refining initial ecological site and STM concepts, documenting states, hypothesizing transitions, and locating study locations for future research. Quantitative production and cover estimates, used for the Mountain Gravelly Loam STM, are useful for describing the structure of states, but structural indicators must be coupled with process measurements, as with the Loamy Bottom STM to understand the drivers of state change. A coordinated data collection effort is needed to produce STMs that accurately depict the plant community dynamics of ecological sites.