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1 June 2010 Using Landscape Limnology to Classify Freshwater Ecosystems for Multi-Ecosystem Management and Conservation
Patricia A. Soranno, Kendra Spence Cheruvelil, Katherine E. Webster, Mary T. Bremigan, Tyler Wagner, Craig A. Stow
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Abstract

Governmental entities are responsible for managing and conserving large numbers of lake, river, and wetland ecosystems that can be addressed only rarely on a case-by-case basis. We present a system for predictive classification modeling, grounded in the theoretical foundation of landscape limnology, that creates a tractable number of ecosystem classes to which management actions may be tailored. We demonstrate our system by applying two types of predictive classification modeling approaches to develop nutrient criteria for eutrophication management in 1998 north temperate lakes. Our predictive classification system promotes the effective management of multiple ecosystems across broad geographic scales by explicitly connecting management and conservation goals to the classification modeling approach, considering multiple spatial scales as drivers of ecosystem dynamics, and acknowledging the hierarchical structure of freshwater ecosystems. Such a system is critical for adaptive management of complex mosaics of freshwater ecosystems and for balancing competing needs for ecosystem services in a changing world.

© 2010 by American Institute of Biological Sciences. All rights reserved. Request permission to photocopy or reproduce article content at the University of California Press's Rights and Permissions Web site at www.ucpressjournals.com/reprintinfo.asp.
Patricia A. Soranno, Kendra Spence Cheruvelil, Katherine E. Webster, Mary T. Bremigan, Tyler Wagner, and Craig A. Stow "Using Landscape Limnology to Classify Freshwater Ecosystems for Multi-Ecosystem Management and Conservation," BioScience 60(6), 440-454, (1 June 2010). https://doi.org/10.1525/bio.2010.60.6.8
Published: 1 June 2010
JOURNAL ARTICLE
15 PAGES

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KEYWORDS
conservation
ecosystem management
landscape limnology
modeling
predictive classification
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