Journal
JOURNAL OF GREAT LAKES RESEARCH
Volume 36, Issue 4, Pages 757-771Publisher
ELSEVIER SCI LTD
DOI: 10.1016/j.jglr.2010.09.005
Keywords
Aquatic habitat classification; Nearshore; Fish assemblages; Neural network models; Great Lakes
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Classification is a valuable conservation tool for examining natural resource status and problems and is being developed for coastal aquatic habitats. We present an objective, multi-scale hydrospatial framework for nearshore areas of the Great Lakes. The hydrospatial framework consists of spatial units at eight hierarchical scales from the North American Continent to the individual 270-m spatial cell. Characterization of spatial units based on fish abundance and diversity provides a fish-guided classification of aquatic areas at each spatial scale and demonstrates how classifications may be generated from that framework. Those classification units then provide information about habitat, as well as biotic conditions, which can be compared, contrasted, and hierarchically related spatially. Examples within several representative coastal or open water zones of the Western Lake Erie pilot area highlight potential application of this classification system to management problems. This classification system can assist natural resource managers with planning and establishing priorities for aquatic habitat protection, developing rehabilitation strategies, or identifying special management actions. Published by Elsevier B.V. on behalf of International Association for Great Lakes Research.
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