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Predicting foundation bunchgrass species and abundances: model-assisted decision-making in protected-area sagebrush steppe

Author:
Rodhouse, Thomas J., Irvine, Kathryn M., Sheley, Roger L., Smith, Brenda S., Hoh, Shirley, Esposito, Daniel M., Mata-Gonzalez, Ricardo
Source:
ARS USDA Submissions 2014 v.5 no.9 pp. 1
Subject:
Artemisia, Poaceae, biogeography, conifers, conservation areas, decision making, decision support systems, ecological invasion, ecosystems, fire ecology, grasses, invasive species, land use change, landscapes, models, plant communities, prediction, probability, space and time, steppes, terraces, topographic slope, weeds, wildfires
Abstract:
Foundation species are structurally dominant members of ecological communities that can stabilize ecological processes and influence ecosystem resilience to disturbance and resistance to invasion. Being common, they are often overlooked as targets for conservation but are increasingly threatened from land use change, biological invasions, and over-exploitation. The pattern of foundation species distributions and abundances over space and time may be used to guide management decision-making, particularly in protected areas for which they are iconic. We developed predictive models and maps of a foundation bunchgrass species’ abundance to guide implementation of a management decision-support tool across degraded protected-area steppe. Models indicated that steep north-facing slopes in higher and more remote portions of the landscape outside of recently burned areas where invasive annual grasses were less abundant were most likely to support remnant bunchgrass stands. These areas represented only 25% of the landscape and were prioritized for weed and conifer encroachment prevention. Most of the remaining area was mapped as heavily infested and given low priority for active management due to the high costs and low probability of success associated with such areas. Some accessible oldfields and flat alluvial terraces were identified for restoration.
Agid:
59746
Handle:
10113/59746