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Identifying optimum locations for new ponds

Identifying optimum locations for new ponds 1. Pond ecological quality is influenced by surrounding land uses. Continued intensification of land use has led to a progressive decline in the ecological quality of the pond stock within Britain. 2. To reverse this trend new ponds need to be carefully designed and sited using a targeted approach. Consequently, this study uses a Geographical Information System (GIS) to identify optimum locations for new ponds within the Chiltern Hills Area of Outstanding Natural Beauty. 3. Multiple regression analysis was used to identify the relationship between macrophyte pond quality indicators and environmental data from 300 ponds to produce models that could predict pond quality. 4. These models were tested at 10 locations in the study area by comparing predicted pond qualities with the actual pond qualities, established by identifying all plants in each pond. Aquatic plants successfully predicted pond quality, while emergent plants and total wetland plant species did not. 5. The regression model for aquatic plants was used in the GIS to identify locations within the study area where new ponds could be located to obtain maximum ecological quality. Six scenarios were tested and the optimum situation identified. 6. The study demonstrated the potential and importance of using GIS in a strategic approach for pond conservation. Copyright © 2003 John Wiley & Sons, Ltd. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Aquatic Conservation: Marine and Freshwater Ecosystems Wiley

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References (13)

Publisher
Wiley
Copyright
Copyright © 2003 John Wiley & Sons, Ltd.
ISSN
1052-7613
eISSN
1099-0755
DOI
10.1002/aqc.574
Publisher site
See Article on Publisher Site

Abstract

1. Pond ecological quality is influenced by surrounding land uses. Continued intensification of land use has led to a progressive decline in the ecological quality of the pond stock within Britain. 2. To reverse this trend new ponds need to be carefully designed and sited using a targeted approach. Consequently, this study uses a Geographical Information System (GIS) to identify optimum locations for new ponds within the Chiltern Hills Area of Outstanding Natural Beauty. 3. Multiple regression analysis was used to identify the relationship between macrophyte pond quality indicators and environmental data from 300 ponds to produce models that could predict pond quality. 4. These models were tested at 10 locations in the study area by comparing predicted pond qualities with the actual pond qualities, established by identifying all plants in each pond. Aquatic plants successfully predicted pond quality, while emergent plants and total wetland plant species did not. 5. The regression model for aquatic plants was used in the GIS to identify locations within the study area where new ponds could be located to obtain maximum ecological quality. Six scenarios were tested and the optimum situation identified. 6. The study demonstrated the potential and importance of using GIS in a strategic approach for pond conservation. Copyright © 2003 John Wiley & Sons, Ltd.

Journal

Aquatic Conservation: Marine and Freshwater EcosystemsWiley

Published: Jan 1, 2004

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