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

30 Scopus citations

Abstract

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
Volume41
Issue number2
DOIs
StatePublished - Jun 1 2015

Bibliographical note

Funding Information:
We thank Paul Seelbach, Michael Wiley, Jan Ciborowski, Scudder Mackey, Travis Brenden, John Dettmers, Karen Rodriguez, Mark Burrows, and Michael Laitta for their support and strategic thinking in the development of the Great Lakes spatial framework and database. We are grateful to the GIS and data acquisition support from Jason Breck, Danielle Forsyth, Beth Sparks-Jackson, and Gust Annis. This project was funded by the Great Lakes Fishery Trust ( 2010 1206 ) and received in-kind support from the University of Michigan , Michigan Department of Natural Resources , International Joint Commission , Ontario Ministry of Natural Resources , NOAA Great Lakes Environmental Research Laboratory , U.S. Geological Survey , U.S. Fish and Wildlife Services , U.S. Environmental Protection Agency , Environment Canada , The Nature Conservancy , The Great Lakes Fishery Commission , Michigan State University , University of Minnesota-Duluth , and University of Windsor . This is contribution 1914 of the USGS Great Lakes Science Center and contribution 1747 of the NOAA Great Lakes Environmental Research Laboratory.

Publisher Copyright:
© 2015 .

Copyright:
Copyright 2015 Elsevier B.V., All rights reserved.

Keywords

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

Fingerprint

Dive into the research topics of 'A spatial classification and database for management, research, and policy making: The Great Lakes aquatic habitat framework'. Together they form a unique fingerprint.

Cite this