A spatial classification and database for management, research, and policy making: The Great Lakes aquatic habitat framework

Lizhu Wang, Catherine M. Riseng, Lacey A. Mason, Kevin E. Wehrly, Edward S. Rutherford, James E. McKenna, Chris Castiglione, Lucinda B. Johnson, Dana M. Infante, Scott Sowa, Mike Robertson, Jeff Schaeffer, Mary Khoury, John Gaiot, Tom Hollenhorst, Colin Brooks, Mark Coscarelli

Research output: Contribution to journalArticlepeer-review

50 Scopus citations


Managing the world's largest and most complex freshwater ecosystem, the Laurentian Great Lakes, requires a spatially hierarchical basin-wide database of ecological and socioeconomic information that is comparable across the region. To meet such a need, we developed a spatial classification framework and database - Great Lakes Aquatic Habitat Framework (GLAHF). GLAHF consists of catchments, coastal terrestrial, coastal margin, nearshore, and offshore zones that encompass the entire Great Lakes Basin. The catchments captured in the database as river pour points or coastline segments are attributed with data known to influence physicochemical and biological characteristics of the lakes from the catchments. The coastal terrestrial zone consists of 30-m grid cells attributed with data from the terrestrial region that has direct connection with the lakes. The coastal margin and nearshore zones consist of 30-m grid cells attributed with data describing the coastline conditions, coastal human disturbances, and moderately to highly variable physicochemical and biological characteristics. The offshore zone consists of 1.8-km grid cells attributed with data that are spatially less variable compared with the other aquatic zones. These spatial classification zones and their associated data are nested within lake sub-basins and political boundaries and allow the synthesis of information from grid cells to classification zones, within and among political boundaries, lake sub-basins, Great Lakes, or within the entire Great Lakes Basin. This spatially structured database could help the development of basin-wide management plans, prioritize locations for funding and specific management actions, track protection and restoration progress, and conduct research for science-based decision making.

Original languageEnglish (US)
Pages (from-to)584-596
Number of pages13
JournalJournal of Great Lakes Research
Issue number2
StatePublished - Jun 1 2015

Bibliographical note

Publisher Copyright:
© 2015 .


  • Classification
  • Database
  • Framework
  • Great Lakes
  • Hierarchy
  • Spatial unit


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