Spatial prediction of ecosystem state transitions on the Taos Plateau

TitleSpatial prediction of ecosystem state transitions on the Taos Plateau
Publication TypeConference Proceedings
Year of Publication2020
AuthorsHeller A., Webb N., Bestelmeyer BT, McCord S.E.
Conference NameSociety for Rangeland Meetings
Volume88
Date Published02/16/2020
Conference LocationDenver, CO
ARIS Log Number372936
Abstract

Land use, climate, and landscape context jointly determine the occurrence of state transitions in terrestrial ecosystems. State-and­ transition models (STM) are used to clarify the roles of drivers, and ecological sites (climoedaphic land units) represent the effects of landscape context. On the Taos Plateau in northern New Mexico, uncertainty about the patterns and drivers of vegetation state transitions impedes sustainable land management. The efficacy of restoration treatments is highly variable, likely due to unrecognized variation in climate and soils. Similar challenges are ubiquitous across terrestrial ecosystems and in particular landscapes with high spatial variability in soils. We used data from federal vegetation monitoring programs and spatial, environmental, and land use data to test for the role of climate, geomorphology, soils, and land use history on restoration success on the Taos Plateau. The large dataset comprises a suite of recently-established core monitoring methods that are consistent across agencies and provide scalable estimates of resource distribution and land change trends across the western U.S. We used a suite of multivariate methods to characterize vegetation states and their relationships to environmental variables to test propositions in conceptual STMs. Preliminary analysis verified the six ecological site concepts which were hypothesized for the study area. Plant functional group abundance and vegetation structure varied within ecological site group based on management history, indicating that multiple vegetation states are present on the landscape and correlated with land use legacies. A workflow for using multivariate analysis of core methods data to inform ecological site and STM concept development is presented for use in other study areas.