Feasibility of implementing an integrated long-term database to advance ecosystem-based management in the Laurentian Great Lakes basin.

Autor: Budnik RR; Aquatic Ecology Laboratory, Department of Evolution, Ecology, and Organismal Biology, The Ohio State University, Columbus, OH 43212, USA., Frank KT; Ocean Sciences Division, Bedford Institute of Oceanography, Dartmouth, NS B2Y 4A2, Canada.; Department of Biology, Queen's University, Kingston, ON K7L 3N6, Canada., Collis LM; Aquatic Ecology Laboratory, Department of Evolution, Ecology, and Organismal Biology, The Ohio State University, Columbus, OH 43212, USA.; National Oceanic and Atmospheric Administration, Great Lakes Environmental Research Laboratory, Ann Arbor, MI 48108, USA., Fraker ME; Cooperative Institute for Great Lakes Research (CIGLR) and Michigan Sea Grant, University of Michigan, Ann Arbor, MI 48108, USA., Mason LA; National Oceanic and Atmospheric Administration, Great Lakes Environmental Research Laboratory, Ann Arbor, MI 48108, USA., Muir AM; Great Lakes Fishery Commission, Ann Arbor, MI 48105, USA., Pothoven SA; National Oceanic and Atmospheric Administration, Great Lakes Environmental Research Laboratory, Lake Michigan Field Station, Muskegon, MI 49441, USA., Clapp DF; Charlevoix Fisheries Research Station, Michigan Department of Natural Resources, Charlevoix, Michigan,49720, USA., Collingsworth PD; Department of Forestry and Natural Resources and Illinois-Indiana Sea Grant, Purdue University, West Lafayette, USA., Hoffman JC; United State Environmental Protection Agency, Office of Research and Development, Great Lakes Toxicology and Ecology Division, Duluth, Minnesota, 55804, USA., Hood JM; Aquatic Ecology Laboratory, Department of Evolution, Ecology, and Organismal Biology, The Ohio State University, Columbus, OH 43212, USA.; Translational Data Analytics Institute, The Ohio State University, Columbus, Ohio 43212 USA., Johnson TB; Ontario Ministry of Northern Development, Mines, Natural Resources and Forestry, Glenora Fisheries Station, Pickton, ON, Canada, K0K 2T0., Koops MA; Great Lakes Laboratory for Fisheries and Aquatic Sciences, Fisheries and Oceans Canada, 867 Lakeshore Road, Burlington, ON L7S 1A1, Canada., Rudstam LG; Department of Natural Resources and the Environment, Cornell University, Ithaca, New York, USA., Ludsin SA; Aquatic Ecology Laboratory, Department of Evolution, Ecology, and Organismal Biology, The Ohio State University, Columbus, OH 43212, USA.
Jazyk: angličtina
Zdroj: Journal of Great Lakes research [J Great Lakes Res] 2024 Feb 21; Vol. 50, pp. 1-13.
DOI: 10.1016/j.jglr.2024.102308
Abstrakt: The North American Great Lakes have been experiencing dramatic change during the past half-century, highlighting the need for holistic, ecosystem-based approaches to management. To assess interest in ecosystem-based management (EBM), including the value of a comprehensive public database that could serve as a repository for the numerous physical, chemical, and biological monitoring Great Lakes datasets that exist, a two-day workshop was organized, which was attended by 40+ Great Lakes researchers, managers, and stakeholders. While we learned during the workshop that EBM is not an explicit mission of many of the participating research, monitoring, and management agencies, most have been conducting research or monitoring activities that can support EBM. These contributions have ranged from single-resource (-sector) management to considering the ecosystem holistically in a decision-making framework. Workshop participants also identified impediments to implementing EBM, including: 1) high anticipated costs; 2) a lack of EBM success stories to garner agency buy-in; and 3) difficulty in establishing common objectives among groups with different mandates (e.g., water quality vs. fisheries production). We discussed as a group solutions to overcome these impediments, including construction of a comprehensive, research-ready database, a prototype of which was presented at the workshop. We collectively felt that such a database would offer a cost-effective means to support EBM approaches by facilitating research that could help identify useful ecosystem indicators and management targets and allow for management strategy evaluations that account for risk and uncertainty when contemplating future decision-making.
Databáze: MEDLINE