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Applying a Large, Statewide Database to the Assessment, Stressor Diagnosis, and Restoration of Stream Fish Communities

Applying a Large, Statewide Database to the Assessment, Stressor Diagnosis, and Restoration of... In this report, predictions of the species that were expected to occur at stream sites were generated and probable stressors to fish species that were predicted to occur but were absent were diagnosed. Predictions were generated based on the hierarchical screening method of Smith and Powell (1971, Am. Mus. Novit. 2458, 1–30), using fish abundance in conjunction with 25 environmental variables at 895 sites. The sites were sampled throughout Maryland and represent the entire range of environmental quality from severely degraded to minimally degraded. Stressor variable values that exceeded tolerance thresholds for species that were expected to occur, but were absent, were considered to be probable stressors. This method was tested for efficacy in stream site assessments and stressor diagnosis using an independent data set. Sites that were classified as degraded according to the IBI and to non-biological criteria had fewer predicted species present compared to minimally influenced sites, indicating that the proportion of predicted species present accurately represents the biological integrity of a stream site. The nine stressors that were applied to the test data set accounted for species absences in 43.7% of degraded sites. Impervious land cover was the most common stressor identified. In addition to assessing stream biological integrity and identifying stressors to fish species, this approach also provides tolerance thresholds for predicted fish species that are useful endpoints necessary to plan effective restoration of fish species in Maryland. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Environmental Monitoring and Assessment Springer Journals

Applying a Large, Statewide Database to the Assessment, Stressor Diagnosis, and Restoration of Stream Fish Communities

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References (35)

Publisher
Springer Journals
Copyright
Copyright © 2005 by Springer Science + Business Media, Inc.
Subject
Environment; Monitoring/Environmental Analysis; Environmental Management; Ecotoxicology; Atmospheric Protection/Air Quality Control/Air Pollution; Ecology
ISSN
0167-6369
eISSN
1573-2959
DOI
10.1007/s10661-005-3608-y
pmid
16160781
Publisher site
See Article on Publisher Site

Abstract

In this report, predictions of the species that were expected to occur at stream sites were generated and probable stressors to fish species that were predicted to occur but were absent were diagnosed. Predictions were generated based on the hierarchical screening method of Smith and Powell (1971, Am. Mus. Novit. 2458, 1–30), using fish abundance in conjunction with 25 environmental variables at 895 sites. The sites were sampled throughout Maryland and represent the entire range of environmental quality from severely degraded to minimally degraded. Stressor variable values that exceeded tolerance thresholds for species that were expected to occur, but were absent, were considered to be probable stressors. This method was tested for efficacy in stream site assessments and stressor diagnosis using an independent data set. Sites that were classified as degraded according to the IBI and to non-biological criteria had fewer predicted species present compared to minimally influenced sites, indicating that the proportion of predicted species present accurately represents the biological integrity of a stream site. The nine stressors that were applied to the test data set accounted for species absences in 43.7% of degraded sites. Impervious land cover was the most common stressor identified. In addition to assessing stream biological integrity and identifying stressors to fish species, this approach also provides tolerance thresholds for predicted fish species that are useful endpoints necessary to plan effective restoration of fish species in Maryland.

Journal

Environmental Monitoring and AssessmentSpringer Journals

Published: Jan 1, 2005

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