Acoustical Monitoring of Biodiversity and Phenology: A Pilot Wildlife Monitoring Partnership for Adaptive Management
September 2009 - December 2012
- U.S. Geological Survey
- National Park Service
A primary principle guiding the management of the state and federal lands is to conserve and enhance habitats that support a full range of native flora and fauna. Two serious forces threaten the viability of native flora and fauna today: land use change and global climate change.
Confronting these resource management challenges requires, first and foremost, robust data to accurately predict how biodiversity will respond to land-use and climate change, and a process that links this information to landuse planning efforts and resource management in a continual way (i.e., adaptive management). The first step in this process, gathering and monitoring biodiversity data, is extremely challenging. First, the sampling area is vast. Second, not all wildlife species can be monitored; many are secretive or rare and are not easily counted by humans (e.g., black bears). Third, even if a few, target species were monitored, field-based monitoring by humans across the entire state of Vermont would be cost prohibitive.
One potential solution to these challenges is to establish an acoustical monitoring network, where 1) vocalizations made by indicator wildlife species are recorded continually at sampling stations located throughout the sampling area, 2) recorded sounds are delivered to a central database where computers are used to identify species-specific sounds, and 3) the acoustical data can be accessed and used by natural resource managers in a structured decision making/adaptive management framework.
Our goal in this pilot effort is to field test acoustical techniques, database development, computer-automated animal identification, and programmatic methodologies. Through this study, we hope to identify opportunities and constraints for establishing a large-scale acoustic monitoring program. This pilot study is a partnership between the National Park Service, the National Phenology Network, the Vermont Fish and Wildlife Department, and the Vermont Cooperative Fish and Wildlife Research Unit.
|Research Publications||Publication Date|
|Brauer, C., T. Donovan, R. Mickey, J. Katz, and B. Mitchell. 2016. A comparison of acoustic montoring methods for common anurans of the northeastern United States. Wildlife Society Bulletin 40:140-149. | Publisher Website||February 2016|
|Katz, J., S. Hafner, and T. Donovan. 2016. Assessment of Error Rates in Acoustic Monitoring with the R package monitoR. Bioacoustics. DOI:10.1080/09524622.2015.1133320 | Abstract | Publisher Website||January 2016|
|Katz, J., S. Hafner, and T. Donovan. 2016. Tools for automated acoustic monitoring within the R package monitoR. Bioacoustics. DOI:10.1080/09524622.2016.1138415 | Abstract | Publisher Website||January 2016|
|Technical Publications||Publication Date|
|Tierney, G., B. Mitchell, A. Miller-Rushing, J. Katz, E. Denny, C. Brauer, T. Donovan, A. Richardson, M. Toomey, A. Kozlowski, J. Weltzin, K. Gerst, E. Sharron, O. Sonnentag, F. Dieffenbach . 2013. Phenology monitoring protocol: Northeast Temperate Network. Natural Resource Report. NPS/NETN/NRR—2013/681. National Park Service. Fort Collins, Colorado. Published Report-2197242.||July 2013|
|Katz, J. E., S. Hafner, and T. M. Donovan. 2014. monitor: an R package for automated acoustic monitoring, tested on two northeastern warblers. 70th Annual Northeast Fish and Wildlife Conference, Portland, ME.||April 2014|
|Katz, J. E., S. Hafner, and T. M. Donovan. 2014. Automated acoustic monitoring: reporting survey presence for a northeastern warbler . 70th Annual Northeast Fish and Wildlife Conference, Portland, ME.||April 2014|
|Theses and Dissertations||Publication Date|
|Katz, J. E. 2015. monitoR: Automation tools for landscape-scale acoustic monitoring. PhD Dissertation. University of Vermont, Burlington, VT USA.||May 2015|
|Brauer, Corinne L. 2012. A comparison of acoustic monitoring methods for common anurans of the northeastern United States. MS Thesis, University of Vermont, Burlington VT USA.||June 2012|