A continuous classification of the 476,697 lakes of the conterminous US based on geographic archetypes

Author:

Lapierre Jean‐Francois12,Webster Katherine E.34,Hanks Ephraim M.5,Wagner Tyler56ORCID,Soranno Patricia A.3ORCID,McCullough Ian M.3,Reinl Kaitlin L.7,Domka Marcella3,Lotting Noah R.8ORCID

Affiliation:

1. Département de Sciences Biologiques, Faculté des Arts et Sciences Université de Montréal Montreal Quebec Canada

2. Groupe de Recherche Interuniversitaire en Limnologie (GRIL) Montreal Quebec Canada

3. Department of Fisheries and Wildlife Michigan State University East Lansing Michigan USA

4. Center for Limnology Hasler Laboratory of Limnology University of Wisconsin Madison Madison Wisconsin USA

5. Department of Statistics The Pennsylvania State University Pennsylvania USA

6. U.S. Geological Survey, Pennsylvania Cooperative Fish and Wildlife Research Unit Pennsylvania State University Pennsylvania USA

7. University of Wisconsin‐Madison Division of Extension Natural Resources Institute Lake Superior National Estuarine Research Reserve Madison Wisconsin USA

8. Center for Limnology Trout Lake Station University of Wisconsin‐Madison Madison Wisconsin USA

Abstract

AbstractA variety of classification approaches are used to facilitate understanding, prediction, monitoring, and the management of lakes. However, broad‐scale applicability of current approaches is limited by either the need for in situ lake data, incompatibilities among approaches, or a lack of empirical testing of approaches based on ex situ data. We developed a new geographic classification approach for 476,697 lakes ≥ 1 ha in the conterminous U.S. based on lake archetypes representing end members along gradients of multiple geographic features. We identified seven lake archetypes with distinct combinations of climate, hydrologic, geologic, topographic, and morphometric properties. Individual lakes were assigned weights for each of the seven archetypes such that groups of lakes with similar combinations of archetype weights tended to cluster spatially (although not strictly contiguous) and to have similar limnological properties (e.g., concentrations of nutrients, chlorophyll a (Chl a), and dissolved organic carbon). Further, archetype lake classification improved commonly measured limnological relationships (e.g., between nutrients and Chl a) compared to a global model; a discrete archetype classification slightly outperformed an ecoregion classification; and considering lakes as continuous mixtures of archetypes in a more complex model further improved fit. Overall, archetype classification of US lakes as continuous mixtures of geographic features improved understanding and prediction of lake responses to limnological drivers and should help researchers and managers better characterize and forecast lake states and responses to environmental change.

Funder

National Institute of Food and Agriculture

National Science Foundation of Sri Lanka

Publisher

Wiley

Subject

Aquatic Science,Oceanography

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