EDP Sciences logo
Subscriber Authentication Point
Search
Menu
All issues Volume 47 (2011) Suppl. 1 Ann. Limnol. - Int. J. Lim., 47 (2011) S51-S62 References
Free Access
Issue
Ann. Limnol. - Int. J. Lim.
Volume 47, 2011
River ecosystem health assessment: the value in the management and restoration
Page(s) S51 - S62
DOI https://doi.org/10.1051/limn/2011019
Published online 08 July 2011
  • Armitage P.D., Moss D., Wright J.F. and Furse M.T., 1983. The performance of a new biological water quality score system based on macroinvertebrates over a wide range of unpolluted running-water sites. Water Res., 17, 333–347. [CrossRef] [Google Scholar]
  • Barbour M.T., Stribling J.B. and Karr J.R. 1995. The multimetric approach for establishing biocriteria and measuring biological conditions. In: Davis W.S. and Simon T.P. (eds.), Biological Assessment and Criteria, Tools for Water Resource Planning and Decision Making, Lewis Publishers, FL. [Google Scholar]
  • Barbour M.T., Gerritsen J., Griffith G.E., Frydenborg R., McCarron E., White J.S. and Bastian M.L., 1996. A framework for biological criteria for Florida streams using benthic macroinvertebrates. J. N. Am. Benthol. Soc., 15, 185–211. [Google Scholar]
  • Barbour M.T., Gerritsen J., Snyder B.D. and Stribling J.B., 1999. Rapid bioassessment protocols for use in streams and wadeable rivers: periphyton, benthic macroinvertebrates and fish, Environmental Protection Agency, Washington, DC. [Google Scholar]
  • Blocksom K.A., 2003. A performance comparison of metric scoring methods for a multimetric index for Mid-Atlantic Highlands streams. Environ. Manage., 31, 670–682. [Google Scholar]
  • Blocksom K.A., Kurtenbach J.P., Klemm D.J., Fulk F.A. and Cormier S.M., 2002. Development and evaluation of the Lake Macroinvertebrate Integrity Index (LMII) for New Jersey lakes and reservoirs. Environ. Monit. Assess., 77, 311–333. [Google Scholar]
  • Böhmer J., Rawer-Jost C., Zenker A., Meier C., Feld C.K., Biss R. and Hering D., 2004. Assessing streams in Germany with benthic invertebrates: Development of a multimetric invertebrate based assessment system. Limnologica, 34, 416–432. [Google Scholar]
  • Butcher J.T., Stewart P.M. and Simon T.P., 2003. A benthic community index for streams in the northern lakes and forests ecoregion. Ecol. Indic., 3, 181–193. [Google Scholar]
  • Carlisle D.M. and Clements W.H., 1999. Sensitivity and variability of metrics used in biological assessments of running waters. Environ. Toxicol. Chem., 18, 285–291. [Google Scholar]
  • Chon T.-S., Park Y.-S., Moon K.H. and Cha E.Y., 1996. Patternizing communities by using an artificial neural network. Ecol. Model., 90, 69–78. [Google Scholar]
  • Green J., Passmore M. and Childers H., 2000. A survey of the condition of streams in the primary region of mountaintop mining/valley fill coal mining. Appendix. In: Mountaintop Mining/valley Fills in Appalachia. Final programmatic environmental impact statement, US Environmental Protection Agency, Philadelphia, PA. [Google Scholar]
  • Hargett E.G. and ZumBerge J.R., 2006. Redevelopment of the Wyoming Stream Integrity Index (WSII) for assessing the biological condition of wadeable streams in Wyoming, Wyoming Department of Environmental Quality, Water Quality Division, Cheyenne, WY. [Google Scholar]
  • Hawkes H., 1979. Invertebrates as indicators of river water quality. In: James A. and Evision L. (eds.), Biological Indicators of Water Quality, John Wiley and Sons, Chichester. [Google Scholar]
  • Hilsenhoff W.L., 1987. An improved biotic index of organic stream pollution. Great Lake Entomol., 20, 31–40. [Google Scholar]
  • Karr J.R. and Chu E.W., 1999. Restoring life in running waters: better biological monitoring, Island Press, Washington, DC, 206 p. [Google Scholar]
  • Kerans B.L. and Karr J.R., 1994. A Benthic Index of Biotic Integrity (B-IBI) for Rivers of the Tennessee Valley. Ecol. Appl., 4, 768–785. [Google Scholar]
  • Klemm D.J., Blocksom K.A., Thoeny W.T., Fulk F.A., Herlihy A.T., Kaufmann P.R. and Cormier S.M., 2002. Methods development and use of macroinvertebrates as indicators of ecological conditions for streams in the Mid-Atlantic Highlands Region. Environ. Monit. Assess., 78, 169–212. [Google Scholar]
  • Klemm D.J., Blocksom K.A., Fulk F.A., Herlihy A.T., Hughes R.M., Kaufmann P.R., Peck D.V., Stoddard J.L., Thoeny W.T. and Griffith M.B., 2003. Development and evaluation of a macroinvertebrate biotic integrity index (MBII) for regionally assessing Mid-Atlantic Highlands streams. Environ. Manage., 31, 656–669. [CrossRef] [PubMed] [Google Scholar]
  • Lenat D.R., 1988. Water quality assessment of streams using a qualitative collection method for benthic macroinvertebrates. J. N. Am. Benthol. Soc., 7, 222–233. [Google Scholar]
  • Lenat D.R., 1993. A biotic index for the southeastern United States: derivation and list of tolerance values, with criteria for assigning water-quality ratings. J. N. Am. Benthol. Soc., 12, 279–290. [CrossRef] [Google Scholar]
  • McNaughton S.J., 1967. Relationship among functional properties of California grassland. Nature, 216, 168–169. [CrossRef] [Google Scholar]
  • MOE/NIER, 2008. The survey and evaluation of aquatic ecosystem health in Korea, The Ministry of Environment/National Institute of Environmental Research, Incheon, Korea (in Korean with English summary). [Google Scholar]
  • Ode P.R., Rehn A.C. and May J.T., 2005. A quantitative tool for assessing the integrity of southern coastal California streams. Environ. Manage., 35, 493–504. [Google Scholar]
  • Park Y.-S., Cereghino R., Compin A. and Lek S., 2003. Applications of artificial neural networks for patterning and predicting aquatic insect species richness in running waters. Ecol. Model., 160, 265–280. [Google Scholar]
  • Pielou E.C., 1975. Ecological Diversity, Wiley, New York. [Google Scholar]
  • Pond G.J., Passmore M.E., Borsuk F.A., Reynolds L. and Rose C.J., 2008. Downstream effects of mountaintop coal mining: comparing biological conditions using family- and genus-level macroinvertebrate bioassessment tools. J. N. Am. Benthol. Soc., 27, 717–737. [Google Scholar]
  • Purcell A.H., Bressler D.W., Paul M.J., Barbour M.T., Rankin E.T., Carter J.L. and Resh V.H., 2009. Assessment tools for urban catchments: developing biological indicators based on benthic macroinvertebrates. J. Am. Water Resour. Assoc., 45, 306–319. [CrossRef] [Google Scholar]
  • Resh V.H., Norris R.H. and Barbour M.T., 1995. Design and implementation of rapid assessment approaches for water resource monitoring using benthic macroinvertebrates. Aust. J. Ecol., 20, 108–121. [CrossRef] [Google Scholar]
  • Reynoldson T.B., Norris R.H., Resh V.H., Day K.E. and Rosenberg D.M., 1997. The reference condition: a comparison of multimetric and multivariate approaches to assess water-quality impairment using benthic macroinvertebrates. J. N. Am. Benthol. Soc., 16, 833–852. [CrossRef] [Google Scholar]
  • Rosenberg D.M. and Resh V., 1993. Freshwater Biomonitoring and Benthic Macroinvertebrates, Chapman and Hall, London, 488 p. [Google Scholar]
  • Shannon C.E. and Weaver W., 1949. The Mathematical Theory of Communication, University of Illinois Press, Urbana, IL. [Google Scholar]
  • Simon T.P. and Lyons J., 1995. Application of the index of biotic integrity to evaluate water resource integrity in freshwater ecosystems. In: Davis W.S. and Simon T.P. (eds.), Biological Assessment and Criteria: Tools for Water Resource Planning and Decision Making, Lewis Publishers, Chelsea, MI. [Google Scholar]
  • Solimini A.G., Bazzanti M., Ruggiero A. and Carchini G., 2008. Developing a multimetric index of ecological integrity based on macroinvertebrates of mountain ponds in central Italy. Hydrobiologia, 597, 109–123. [CrossRef] [Google Scholar]
  • Song M.-Y., Hwang H.-J., Kwak I.-S., Ji C.W., Oh Y.-N., Youn B.J. and Chon T.-S., 2007. Self-organizing mapping of benthic macroinvertebrate communities implemented to community assessment and water quality evaluation. Ecol. Model., 203, 18–25. [Google Scholar]
  • Stoddard J.L., Herlihy A.T., Peck D.V., Hughes R.M., Whittier T.R. and Tarquinio E., 2009. A process for creating multimetric indices for large-scale aquatic surveys. J. N. Am. Benthol. Soc., 27, 878–891. [Google Scholar]
  • Taowu M., Qinghui H., Hai W., Zijian W., Chunxia W. and Shengbiao H., 2008. Selection of benthic macroinvertebrate-based multimetrics and preliminary establishment of biocriteria for the bioassessment of the water quality of Taihu Lake, China. Acta Ecol. Sin., 28, 1192–1200. [CrossRef] [Google Scholar]
  • The Mathworks Inc., 2001. Matlab. Version 6.1, The Mathworks Inc., Massachusetts. [Google Scholar]
  • Trigal-Domínguez C., Fernández-Aláez C. and García-Criado F., 2010. Ecological assessment of highly heterogeneous systems: The importance of taxonomic sufficiency. Limnologica, 40, 208–214. [Google Scholar]
  • Trigal C., Garcia-Criado F. and Fernandez-Alaez C., 2009. Towards a multimetric index for ecological assessment of Mediterranean flatland ponds: the use of macroinvertebrates as bioindicators. Hydrobiologia, 618, 109–123. [CrossRef] [Google Scholar]
  • Vesanto J., Himberg J., Alhoniemi E., Parhankangas J., Team S. and Oy L., 2000. SOM Toolbox for Matlab, Techn. Ber. Helsinki University of Technology. [Google Scholar]
  • Waite I.R., Herlihy A.T., Larsen D.P., Urquhart N.S. and Klemm D.J., 2004. The effects of macroinvertebrate taxonomic resolution in large landscape bioassessments: an example from the Mid-Atlantic Highlands, USA. Freshwater Biol., 49, 474–489. [Google Scholar]
  • Walley W.J. and Hawkes H.A., 1996. A computer-based reappraisal of the Biological Monitoring Working Party scores using data from the 1990 river quality survey of England and Wales. Water Res., 30, 2086–2094. [Google Scholar]
  • Walley W.J. and Hawkes H.A., 1997. A computer-based development of the Biological Monitoring Working Party score system incorporating abundance rating, site type and indicator value. Water Res., 31, 201–210. [Google Scholar]
  • Ward J.H., 1963. Hierarchical grouping to optimize an objective function. J. Am. Stat. Assoc., 58, 236–244. [Google Scholar]
  • Whittier T.R., Hughes R.M., Stoddard J.L., Lomnicky G.A., Peck D.V. and Herlihy A.T., 2007. A structured approach to developing indices of biotic integrity: three examples from western USA streams and rivers. Am. Fish. Soc., 136, 718–735. [Google Scholar]
  • Won D.H., Jun T.C., Kwon S.J., Hwang S.J., Ahn K.G. and Lee J.K., 2006. Development of Korean Saprobic Index using benthic macroinvertebrate and its application to biological stream environment assessment. J. Korean Soc. Water Qual., 22, 768–783. [Google Scholar]
  • Wright J.F., Sutcliffe D.W. and Furse M.T., 2000. Assessing the biological quality of fresh waters: RIVPACS and other techniques, Freshwater Biological Association, Ambleside, 400 p. [Google Scholar]
  • Zurada J., 1992. Introduction to artificial neural systems, West Publishing Co., NY, 683 p. [Google Scholar]

Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.

Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.

Initial download of the metrics may take a while.