Synthesizing and analyzing long-term monitoring data: A greater sage-grouse case study
Long-term monitoring of natural resources is imperative for increasing the understanding of ecosystem processes, services, and how to manage those ecosystems to maintain or improve function. Challenges with using these data may occur because methods of monitoring changed over time, multiple organizations collect and manage data differently, and monetary resources fluctuate, affecting many aspects of data. Because many species respond to changes in habitat conditions and predator-prey relationships across different spatial scales that span management boundaries, greater efforts for collaborating are essential. We demonstrate the challenges and methods for standardizing greater sage-grouse (Centrocercus urophasianus) long-term monitoring data across the species range in the western United States to inform population modeling needs identified by the Western Association of Fish and Wildlife Agencies. We used automated and repeatable methods of standardizing data via custom open-source software (grsg_lekdb) to improve the scientific integrity of future sage-grouse population assessments within and among states. Data standardization included reconciling uses of different terminology and expunging unusable data, resulting in the removal of 26% of data records due to database insertion errors and modifications to >1 million values to correct formatting and typing errors. Our approaches maximized the inclusion of usable data and identified data that could inform detection probabilities, population trends, and monitoring guidelines. Using sage-grouse databases as an example, we identified the importance of data management and how quality assurance and quality control measures can improve the usefulness of these data for future research needs. Our methods of using informatics and concluding recommendations can support similar endeavors of flora and fauna monitoring programs, whether those efforts are to use existing data or support new monitoring programs.
Citation Information
| Publication Year | 2021 |
|---|---|
| Title | Synthesizing and analyzing long-term monitoring data: A greater sage-grouse case study |
| DOI | 10.1016/j.ecoinf.2021.101327 |
| Authors | Michael O’Donnell, David Edmunds, Cameron Aldridge, Julie Heinrichs, Adrian P. Monroe, Peter Coates, Brian Prochazka, Thomas Christiansen, Steve Hanser, Lief Wiechman, Avery Cook, Shawn Espinosa, Lee Foster, Kathleen Griffin, Jesse Kolar, Katherine Miller, Ann Moser, Thomas Remington, Travis Runia, Leslie Schreiber, Michael Schroeder, San J Stiver, Nyssa Whitford, Catherine Wightman |
| Publication Type | Article |
| Publication Subtype | Journal Article |
| Series Title | Ecological Informatics |
| Index ID | 70221158 |
| Record Source | USGS Publications Warehouse |
| USGS Organization | Fort Collins Science Center |