Linking indices of biotic integrity to environmental and land use variables: Multimetric clustering and predictive models

Water Science and Technology

Volumn 59, Issue 1, 2009, Pages 1-8

  Novotny, Vladimir ^a   Bedoya, David ^a   Virani, Hardik ^b   Manolakos, Elias ^a  

^a Northeastern University   (United States)

^b MATHWORKS INC   (United States)

Author keywords

Aquatic biota; Artificial neural networks; Canonical correspondence analysis; Environmental stressors; Fish community clusters; Habitat parameters; Indices of biotic integrity; Water quality

Indexed keywords

AQUATIC BIOTA; ARTIFICIAL NEURAL NETWORK; CANONICAL CORRESPONDENCE ANALYSIS; ENVIRONMENTAL STRESSORS; FISH COMMUNITIES; HABITAT PARAMETERS; INDICES OF BIOTIC INTEGRITIES;

ECOLOGY; FISH; FORESTRY; LAND USE; PRINCIPAL COMPONENT ANALYSIS; QUALITY ASSURANCE; REGRESSION ANALYSIS; WATER POLLUTION; WATER QUALITY;

NEURAL NETWORKS;

AQUATIC COMMUNITY; ARTIFICIAL NEURAL NETWORK; BIOTIC FACTOR; CANONICAL ANALYSIS; COMPUTER SIMULATION; CORRESPONDENCE ANALYSIS; DATABASE; ENVIRONMENTAL FACTOR; ENVIRONMENTAL STRESS; FISH; HABITAT FRAGMENTATION; LAND USE; MACROINVERTEBRATE; PRINCIPAL COMPONENT ANALYSIS; REGRESSION ANALYSIS; RESEARCH WORK; WATER QUALITY;

AGRICULTURAL LAND; ANALYSIS OF VARIANCE; ARTICLE; ARTIFICIAL NEURAL NETWORK; BIOTA; CLUSTER ANALYSIS; CORRELATION ANALYSIS; ENVIRONMENT; HABITAT; METHODOLOGY; MULTIPLE REGRESSION; PREDICTION; PRINCIPAL COMPONENT ANALYSIS; STATISTICAL PARAMETERS; ANIMAL; BIODIVERSITY; ENVIRONMENTAL MONITORING; FISH; INVERTEBRATE; PREDICTION AND FORECASTING; REGRESSION ANALYSIS; RIVER; STATISTICAL MODEL; STATISTICS; UNITED STATES; WATER POLLUTANT;

UNITED STATES;

ANALYSIS OF VARIANCE; ANIMALS; BIODIVERSITY; CLUSTER ANALYSIS; ENVIRONMENTAL MONITORING; FISHES; INVERTEBRATES; MODELS, STATISTICAL; NEURAL NETWORKS (COMPUTER); PREDICTIVE VALUE OF TESTS; PRINCIPAL COMPONENT ANALYSIS; REGRESSION ANALYSIS; RIVERS; UNITED STATES; WATER POLLUTANTS;

EID: 63649101152     PISSN: 02731223     EISSN: None     Source Type: Journal    
DOI: 10.2166/wst.2009.769     Document Type: Article

References (12)

1. Barbour, M. T., Gerritsen, J., Snyder, B. D. & Stribling, J. B. 1999 Rapid Bioassessment Protocols for Use in Streams and Wadeable Rivers: Periphyton, Benthic Macroinvertebrates, and Fish, Second Edition, EPA841-B-99/002, US Environmental Protection Agency, Washington, DC.
2. Bedoya, D. 2007 Development of a Predicting Model for Biotic Integrity Based on Variable Selection with Self-Organizing Maps(SOM), Polynomial Canonical Correspondence Analysis (PCCA) and Quadratic Regressions, Technical Report # 12, Center for Urban Environmental Studies, Northeastern University, Boston. Available on line from www.coe.neu.edu/environment
3. Demuth, H. & Beale, M. 1992 Neural Network Toolbox User's Guide. The MathWorks Inc, Natick, MA.
4. Duncan, D. B. 1955 Multiple range and multiple F tests. Biometrics 11, 1-42.
5. Karr, J. R., Fausch, K. D., Angermeier, P. L., Yant, P. R. & Schlosser, I. J. 1986 Assessing Biological Integrity in Running Waters: a Method and its Rationale, Special Publ. 5, Illinois Natural History Survey, Champaign, IL.
6. Kohonen, T. 1990 The self-organizing map. Proc. IEEE 78, 1464-1480.
7. Legendre, P. & Legendre, L. 1998 Numerical Ecology. Elsevier Science BV, Amsterdam.
8. Novotny, V., Bartošová, A., O'Reilly, N. & Ehlinger, T. 2005 Unlocking the relationship of biotic integrity of impaired waters to anthropogenic stresses. Water Res. 39, 184-198. (Pubitemid 40017767)
9. Novotny, V. et al. 2007 Developing Risk Propagation Model for Estimating Ecological Responses of Streams to Anthropogenic Watershed Stresses and Stream Modifications, Final Report, Center for Urban Environmental Studies, Northeastern University, Boston. Available on line from www.coe.neu.edu/ environment
10. Yoder, C. O. & Rankin, E. T. 1999 Biological criteria for water resources management. Measures of Environmental Performance and Ecosystem Condition. National Academy Press, Washington, DC, pp. 227-259.
11. Virani, H., Manolakos, E. & Novotny, V. 2005 Self Organizing Feature Maps Combined with Ecological Ordination Techniques for Effective Watershed Management, Technical Report # 4 Center for Urban Environmental Studies, Northeastern University, Boston. Available on line from www.coe.neu.edu/ environment
12. Wang, L., Lyons, J., Kanehl, P., Bannerman, R. & Emmons, E. 2000 Watershed urbanization and changes in fish communities in southeastern Wisconsin streams. J. AWRA 6(59), 1173-1189.