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Environmental Management

, Volume 62, Issue 3, pp 571–583 | Cite as

Using Cluster Analysis to Compartmentalize a Large Managed Wetland Based on Physical, Biological, and Climatic Geospatial Attributes

  • Ian Hahus
  • Kati Migliaccio
  • Kyle Douglas-Mankin
  • Geraldine Klarenberg
  • Rafael Muñoz-Carpena
Article
  • 89 Downloads

Abstract

Hierarchical and partitional cluster analyses were used to compartmentalize Water Conservation Area 1, a managed wetland within the Arthur R. Marshall Loxahatchee National Wildlife Refuge in southeast Florida, USA, based on physical, biological, and climatic geospatial attributes. Single, complete, average, and Ward’s linkages were tested during the hierarchical cluster analyses, with average linkage providing the best results. In general, the partitional method, partitioning around medoids, found clusters that were more evenly sized and more spatially aggregated than those resulting from the hierarchical analyses. However, hierarchical analysis appeared to be better suited to identify outlier regions that were significantly different from other areas. The clusters identified by geospatial attributes were similar to clusters developed for the interior marsh in a separate study using water quality attributes, suggesting that similar factors have influenced variations in both the set of physical, biological, and climatic attributes selected in this study and water quality parameters. However, geospatial data allowed further subdivision of several interior marsh clusters identified from the water quality data, potentially indicating zones with important differences in function. Identification of these zones can be useful to managers and modelers by informing the distribution of monitoring equipment and personnel as well as delineating regions that may respond similarly to future changes in management or climate.

Keywords

Cluster analysis Everglades Wetlands Ecosystem management 

Notes

Acknowledgements

The authors thank Dr. Mike Waldon for his insights into Refuge hydrology and modeling; Dr. Donatto Surratt for providing data and resources, improving our understanding of the Refuge, and for his help improving drafts of this manuscript; and the South Florida Water Management District, the Everglades Depth Estimation Network (EDEN) project, and the US Geological Survey for providing data for this study.

Compliance with Ethical Standards

Conflict of Interest

The authors declare that they have no conflict of interest.

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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Department of Agricultural and Biological EngineeringUniversity of FloridaGainesvilleUSA
  2. 2.New Mexico Water Science CenterU.S. Geological SurveyAlbuquerqueUSA

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