Cooperative Research Units
Education, Research And Technical Assistance For Managing Our Natural Resources
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Advancing Adaptive Management in the Riverside East Solar Energy Zone

Cathleen Balantic setting up a cell phone monitoring station in the Riverside East Solar Energy Zone.

Duration

April 2015 - January 2019

Narrative

In a world confronting climate change and rapidly shifting land uses, effective methods for monitoring natural resources are critical to support scientifically-informed management decisions. By taking audio recordings of the environment, scientists can acquire presence-absence data to characterize populations of sound-producing wildlife over time and across vast spatial scales. Remote acoustic monitoring presents new challenges, however: monitoring programs are often constrained in the total time they can record, automated detection algorithms typically produce a prohibitive number of detection mistakes, and there is no streamlined framework for moving from raw acoustic data to models of wildlife occurrence dynamics. In partnership with a proof-of-concept field study in the U.S Bureau of Land Management’s Riverside East Solar Energy Zone in southern California, this study introduces a new R software package, AMMonitor, alongside a novel body of work: 1) temporally-adaptive acoustic sampling to maximize the detection probabilities of target species despite recording constraints, 2) values-driven statistical learning tools for template-based automated detection of target species, and 3) methods supporting the construction of dynamic species occurrence models from automated acoustic detection data. Unifying these methods with streamlined data management, the AMMonitor software package supports the tracking of species occurrence, colonization, and extinction patterns through time, introducing the potential to perform adaptive management at landscape scales.

This project is a collaboration of BLM, the Vermont Cooperative Fish and Wildlife Research Unit, and the UVM IGERT SMART program.

Research Products and Activities

Peer Reviewed Publications

  • Balantic, C., and T. M. Donovan. Dynamic wildlife occupancy models using automated acoustic monitoring data. Ecological Indicators.
  • Balantic, C., and T. M. Donovan. Statistical learning mitigation of false positive detections in automated acoustic wildlife monitoring. Methods in Ecology and Evolution.
  • Balantic, C., and T. M. Donovan. Temporally-adaptive acoustic sampling to maximize detection across a suite of focal wildlife species. Methods in Ecology and Evolution.

Presentations

  • Balantic, C., T. M. Donovan, J. Katz, and M. Massar. Temporally-adaptive acoustic sampling to maximize detection across a suite of focal wildlife species with the R package AMMonitoR. Northeast Regional Environmental Acoustics Symposium, University of New Hampshire. March 20, 2018. Durham, NH.
  • Balantic, C., T. M. Donovan, J. Katz, and M. Massar. Machine learning mitigation of false positives in automated acoustic wildlife monitoring with the R package AMMonitor. April 15-17, 2018. 74th Annual Northeast Fish and Wildlife Conference, Burlington, Vermont.
  • Balantic, C., T. M. Donovan, J. Katz, and M. Massar. Temporally-adaptive acoustic sampling to maximize detection across a suite of focal wildlife species with the R package AMMonitor. April 15-17, 2018. 74th Annual Northeast Fish and Wildlife Conference, Burlington, Vermont.
 

Current Staff

Federal Staff: 2

Masters Students: 1

Phd Students: 4

Post Docs: 1

University Staff: 2

5 Year Summary

Students graduated: 6

Scientific Publications: 18

Presentations: 36

 

Personnel

Funding Agencies

  • Bureau of Land Management

Links

Vermont Cooperative Fish and Wildlife Research Unit Cooperators

  1. U.S. Geological Survey
  2. University of Vermont
  3. Vermont Fish and Wildlife Department
  4. Wildlife Management Institute