A data management system for long-term natural resource monitoring and management projects with multiple cooperators

Collection, processing, and long-term storage of data for broad-scale, collaborative natural resource monitoring and management projects poses technical and administrative challenges that, if not properly addressed, result in suboptimal management and learning. Data from many cooperators, often span...

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Veröffentlicht in:Wildlife Society bulletin 2015-09, Vol.39 (3), p.464-471
Hauptverfasser: Hunt, Victoria M., Jacobi, Sarah K., Knutson, Melinda G., Lonsdorf, Eric V., Papon, Shawn, Zorn, Jennifer
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Sprache:eng
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Zusammenfassung:Collection, processing, and long-term storage of data for broad-scale, collaborative natural resource monitoring and management projects poses technical and administrative challenges that, if not properly addressed, result in suboptimal management and learning. Data from many cooperators, often spanning multiple organizations, must be efficiently centralized and processed, and must be consistent in content and quality over the lifespan of such projects. We present a data management system for natural resource monitoring and management consisting of 2 components: a centralized, web-based platform for data entry and a connected relational database for data processing, modeling, and analysis. After the data management system has been customized to meet the needs of a specific project, operation and system maintenance require minimal external technical support, making it suitable for long-term projects that face potential staffing and budgeting constraints. We discuss the scope of projects for which this approach is applicable and document 2 U.S. Fish and Wildlife Service adaptive management case studies demonstrating this data management system: 1) Native Prairie Adaptive Management, and 2) Wetland Restoration and Sediment Removal. The standardized approach presented within is broadly applicable in collaborative natural resource monitoring and management settings and has the potential to improve management outcomes and facilitate deeper ecological understanding of systems being managed.
ISSN:1938-5463
1938-5463
2328-5540
DOI:10.1002/wsb.547