Quantifying regional ecological dynamics using agency monitoring data, ecological sSite descriptions, and ecological sSite groups

Authors: DUNIWAY, MICHAEL - Us Geological Survey; KNIGHT, ANNA - Us Geological Survey; NAUMAN, TRAVIS - US Department Of Agriculture (USDA); BISHOP, TARA - Utah Valley University; McCord, Sarah; Webb, Nicholas; Williams, Christopher; HUMPHRIES, JOEL - Bureau Of Land Management

Submitted to: Rangeland Ecology and Management
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 12/18/2024
Publication Date: 2/18/2025
Citation: Duniway, M.C., Knight, A., Nauman, T., Bishop, T.B., McCord, S.E., Webb, N.P., Williams, C.J., Humphries, J.T. 2025. Quantifying regional ecological dynamics using agency monitoring data, ecological sSite descriptions, and ecological sSite groups. Rangeland Ecology and Management. 99:119-142. https://doi.org/10.1016/j.rama.2024.12.006.
DOI: https://doi.org/10.1016/j.rama.2024.12.006

Interpretive Summary: Land condition concepts that are broadly applicable and mappable are tremendously valuable for policy and management at the landscape scale. This is especially important as rangeland land-use pressures shift and intensify, climate change and associated drought conditions intensify, and the value of land conservation grows. The work presented here is novel in that it is firmly rooted in fundamental concepts land potential as defined by soils, topography, and climate, that were mapped using digital soil mapping workflows, then connected to an extensive network of field observations to develop state concepts. Because these were all developed using nationally available data and information sources, we view the workflow as part of a broader and nationally scalable framework.The workflow we present here can be used to move STM research and creation of actionable and management-relevant information forward through integration with new agroecosystem information tools. The datasets, tools, and models used to do this work are available in the Landscape Data Commons, a cyberinfrastructure platform maintained by the USDA-ARS (https://landscapedatacommons.org/), allowing for the workflow to be updated as more monitoring data become available and ESD STMs are created or improved. There are several areas of improvement or refinement of the workflow and STMs presented here. However, we expect adoption of a version of work demonstrated here can be used to complete ESG Descriptions (ESGDs; e.g., Supplemental Material) for the remaining units mapped by Nauman et al. (2022) and for other ESG efforts nationally.

Technical Abstract: Information about what ecological conditions are likely, causes or drivers of degradation, and potential management actions to restore degraded lands may support land conservation and restoration decisions. State-and-transition models (STMs) describe persistent plant and ecological conditions that are possible (the “state”) within a given abiotic setting and drivers or actions that can cause shifts between states (the “transitions”). These primarily conceptual models are widely used to inform resource and conservation decisions. Data-driven STMs have been developed for some lands, but not at regional or national scales. Here, we demonstrate a new repeatable workflow for developing data-driven STMs in the United States (US). The approach leverages predictive maps of Ecological Site Groups (ESGs), extensive field-based Federal monitoring databases, information from Ecological Site Description (ESD) STMs, soil erosion models, remotely sensed productivity, and other available spatial information (fire, land protection, and drought) to provide context and descriptions of the data-driven states, including likely drivers of transitions. Results of this workflow applied to one dryland ESG in the Upper Colorado River Basin in the southwestern US suggest that an Invaded state (16% of 1352 plots) and some occurrences of a Grassland state (30% of plots) are in a degraded or at-risk condition with reduced ecosystem services. The most common drivers of state transitions in the associated ESDs (n'='26) are related to livestock grazing and fire. The Invaded state in the ESG has evidence of degraded habitat quality and accelerated run-off while the Grassland state occurrences show reduced richness, productivity, and elevated erosion risk by wind. Areas subject to wildfire and with lower protection status had greater probability of Invaded state occurrence, generally supporting drivers in ESDs. The workflow presented here can serve as a template for describing ecological dynamics at regional scales, and support prioritization of land for conservation and climate adaptation activities.