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Integrating Remote Sensing with Species Distribution Models; Mapping Tamarisk Invasions Using the Software for Assisted Habitat Modeling SAHM
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Assessing vegetation recovery from energy development using a dynamic reference approach.

Adrian P Monroe1,2, Travis W Nauman3, Cameron L Aldridge1,2

  • 1U.S. Geological Survey Fort Collins Science Center Fort Collins Colorado USA.

Ecology and Evolution
|February 28, 2022
PubMed
Summary
This summary is machine-generated.

Dynamic reference sites improve ecosystem recovery assessments, especially for sagebrush (Artemisia spp.) landscapes. This approach reveals varied recovery rates influenced by environmental conditions, informing better land management strategies.

Keywords:
Artemisiaquantile regressionresiliencesagebrushsoil propertiesweather

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Area of Science:

  • Ecological restoration and resilience assessment.
  • Remote sensing applications in vegetation dynamics.

Background:

  • Static ecological references are insufficient for heterogeneous environments like sagebrush (Artemisia spp.) ecosystems, which have long recovery times.
  • Assessing recovery on disturbed lands, such as former oil and gas well pads, requires adaptable monitoring methods.

Purpose of the Study:

  • To demonstrate a dynamic reference approach for evaluating sagebrush recovery.
  • To model and project vegetation recovery on disturbed sites using remote sensing data.
  • To incorporate quantile regression for accounting for heterogeneity in recovery processes.

Main Methods:

  • Utilized three decades (1985-2018) of satellite-derived sagebrush cover estimates.
  • Modeled recovery on 1200 former oil and gas well pads in Wyoming, USA.
  • Employed the Disturbance Automated Reference Toolset to identify paired reference sites and quantile regression to analyze recovery heterogeneity.

Main Results:

  • Sagebrush recovery rates varied significantly based on reference site conditions and environmental factors, differing across quantiles.
  • Recovery on well pads was faster when paired reference sites exhibited higher sagebrush cover.
  • Projections indicated limited landscape recovery (<5%) within 100 years for low to mid recovery quantiles, favoring cooler, moister conditions.

Conclusions:

  • Dynamic reference sites offer significant advantages over static ones for studying vegetation recovery, particularly in variable environments.
  • Quantile regression provides valuable insights into the range of recovery trajectories and influencing factors.
  • Findings inform land management by highlighting conditions conducive to rapid sagebrush recovery and projecting long-term restoration potential.