Climatic Change

, Volume 138, Issue 1–2, pp 71–83 | Cite as

Fine-scale spatial variation in ice cover and surface temperature trends across the surface of the Laurentian Great Lakes

  • Lacey A. Mason
  • Catherine M. Riseng
  • Andrew D. Gronewold
  • Edward S. Rutherford
  • Jia Wang
  • Anne Clites
  • Sigrid D. P. Smith
  • Peter B. McIntyre


The effects of climate change on north temperate freshwater ecosystems include increasing water temperatures and decreasing ice cover. Here we compare those trends in the Laurentian Great Lakes at three spatial scales to evaluate how warming varies across the surface of these massive inland water bodies. We compiled seasonal ice cover duration (1973–2013) and lake summer surface water temperatures (LSSWT; 1994–2013), and analyzed spatial patterns and trends at lake-wide, lake sub-basin, and fine spatial scales and compared those to reported lake- and basin-wide trends. At the lake-wide scale we found declining ice duration and warming LSSWT patterns consistent with previous studies. At the lake sub-basin scale, our statistical models identified distinct warming trends within each lake that included significant breakpoints in ice duration for 13 sub-basins, consistent linear declines in 11 sub-basins, and no trends in 4 sub-basins. At the finest scale, we found that the northern- and eastern-most portions of each Great Lake, especially in nearshore areas, have experienced faster rates of LSSWT warming and shortening ice duration than those previously reported from trends at the lake scale. We conclude that lake-level analyses mask significant spatial and temporal variation in warming patterns within the Laurentian Great Lakes. Recognizing spatial variability in rates of change can inform both mechanistic modeling of ecosystem responses and planning for long-term management of these large freshwater ecosystems.


Ordinary Little Square Great Lake Warming Trend Lake Trout Fine Spatial Scale 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



The work presented in this manuscript was supported by the Great Lakes Fishery Trust (2010 1206), Michigan Department of Natural Resources, National Oceanic and Atmospheric Administration Great Lakes Environmental Research Laboratory, the University of Michigan, the Great Lakes Environmental Mapping and Assessment Project, the Erb Family Foundation, and the University of Wisconsin Water Resource Institute (WR11R02). The project was developed as part of the Great Lakes Aquatic Habitat Framework. Special thanks to Jason Breck for providing advice on data processing and coding statistical analyses. This is contribution #1822 of the NOAA GLERL.

Supplementary material

10584_2016_1721_MOESM1_ESM.docx (105 kb)
ESM 1 (DOCX 104 kb)


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Copyright information

© Springer Science+Business Media Dordrecht 2016

Authors and Affiliations

  • Lacey A. Mason
    • 1
    • 2
  • Catherine M. Riseng
    • 1
  • Andrew D. Gronewold
    • 3
  • Edward S. Rutherford
    • 3
  • Jia Wang
    • 3
  • Anne Clites
    • 3
  • Sigrid D. P. Smith
    • 1
  • Peter B. McIntyre
    • 4
  1. 1.School of Natural Resources and EnvironmentUniversity of MichiganAnn ArborUSA
  2. 2.Institute for Fisheries Research, University of Michigan and Michigan Department of Natural ResourcesAnn ArborUSA
  3. 3.National Oceanic and Atmospheric Administration, Great Lakes Environmental Research LaboratoryAnn ArborUSA
  4. 4.Center for LimnologyUniversity of Wisconsin-MadisonMadisonUSA

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