Literature DB >> 16937795

The biological condition gradient: a descriptive model for interpreting change in aquatic ecosystems.

Susan P Davies1, Susan K Jackson.   

Abstract

The United States Clean Water Act (CWA; 1972, and as amended, U.S. Code title 33, sections 1251-1387) provides the long-term, national objective to "restore and maintain the ... biological integrity of the Nation's waters" (section 1251). However, the Act does not define the ecological components, or attributes, that constitute biological integrity nor does it recommend scientific methods to measure the condition of aquatic biota. One way to define biological integrity was described over 25 years ago as a balanced, integrated, adaptive system. Since then a variety of different methods and indices have been designed and applied by each state to quantify the biological condition of their waters. Because states in the United States use different methods to determine biological condition, it is currently difficult to determine if conditions vary across states or to combine state assessments to develop regional or national assessments. A nationally applicable model that allows biological condition to be interpreted independently of assessment methods will greatly assist the efforts of environmental practitioners in the United States to (1) assess aquatic resources more uniformly and directly and (2) communicate more clearly to the public both the current status of aquatic resources and their potential for restoration. To address this need, we propose a descriptive model, the Biological Condition Gradient (BCG) that describes how 10 ecological attributes change in response to increasing levels of stressors. We divide this gradient of biological condition into six tiers useful to water quality scientists and managers. The model was tested by determining how consistently a regionally diverse group of biologists assigned samples of macroinvertebrates or fish to the six tiers. Thirty-three macroinvertebrate biologists concurred in 81% of their 54 assignments. Eleven fish biologists concurred in 74% of their 58 assignments. These results support our contention that the BCG represents aspects of biological condition common to existing assessment methods. We believe the model is consistent with ecological theory and will provide a means to make more consistent, ecologically relevant interpretations of the response of aquatic biota to stressors and to better communicate this information to the public.

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Year:  2006        PMID: 16937795     DOI: 10.1890/1051-0761(2006)016[1251:tbcgad]2.0.co;2

Source DB:  PubMed          Journal:  Ecol Appl        ISSN: 1051-0761            Impact factor:   4.657


  34 in total

1.  Identifying biotic integrity and water chemistry relations in nonwadeable rivers of Wisconsin: toward the development of nutrient criteria.

Authors:  Brian M Weigel; Dale M Robertson
Journal:  Environ Manage       Date:  2007-07-18       Impact factor: 3.266

2.  An implementation plan for using biological indicators to improve assessment of water quality in Thailand.

Authors:  Boonsatien Boonsoong; Narumon Sangpradub; Michael T Barbour; Wijarn Simachaya
Journal:  Environ Monit Assess       Date:  2009-05-07       Impact factor: 2.513

3.  A method for comparative analysis of recovery potential in impaired waters restoration planning.

Authors:  Douglas J Norton; James D Wickham; Timothy G Wade; Kelly Kunert; John V Thomas; Paul Zeph
Journal:  Environ Manage       Date:  2009-05-19       Impact factor: 3.266

4.  A Stream-Wetland-Riparian (SWR) index for assessing condition of aquatic ecosystems in small watersheds along the Atlantic slope of the eastern U.S.

Authors:  R Brooks; M McKenney-Easterling; M Brinson; R Rheinhardt; K Havens; D O'Brien; J Bishop; J Rubbo; B Armstrong; J Hite
Journal:  Environ Monit Assess       Date:  2008-12-12       Impact factor: 2.513

5.  A macroinvertebrate assessment of Ozark streams located in lead-zinc mining areas of the Viburnum Trend in southeastern Missouri, USA.

Authors:  Barry C Poulton; Ann L Allert; John M Besser; Christopher J Schmitt; William G Brumbaugh; James F Fairchild
Journal:  Environ Monit Assess       Date:  2009-04-04       Impact factor: 2.513

6.  Predicting the biological condition of streams: use of geospatial indicators of natural and anthropogenic characteristics of watersheds.

Authors:  Daren M Carlisle; James Falcone; Michael R Meador
Journal:  Environ Monit Assess       Date:  2008-05-21       Impact factor: 2.513

7.  Predicting biological impairment from habitat assessments.

Authors:  Jason C Doll
Journal:  Environ Monit Assess       Date:  2011-02-02       Impact factor: 2.513

8.  Predicting fish growth potential and identifying water quality constraints: a spatially-explicit bioenergetics approach.

Authors:  Phaedra Budy; Matthew Baker; Samuel K Dahle
Journal:  Environ Manage       Date:  2011-07-17       Impact factor: 3.266

9.  An approach for determining bioassessment performance and comparability.

Authors:  Jerry Diamond; James B Stribling; James R Stribling; Lisa Huff; Jaime Gilliam
Journal:  Environ Monit Assess       Date:  2011-05-25       Impact factor: 2.513

10.  The areal extent of brown shrimp habitat suitability in Mobile Bay, Alabama, USA: targeting vegetated habitat restoration.

Authors:  Lisa M Smith; Janet A Nestlerode; Linda C Harwell; Pete Bourgeois
Journal:  Environ Monit Assess       Date:  2010-01-16       Impact factor: 2.513

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