Sequential sampling: A cost-effective approach for monitoring benthic macroinvertebrates in environmental impact assessments
- 169 Downloads
Sequential sampling is a method for monitoring benthic macroinvertebrates that can significantly reduce the number of samples required to reach a decision, and consequently, decrease the cost of benthic sampling in environmental impact assessments.
Rather than depending on a fixed number of samples, this analysis cumulatively compares measured parameter values (for example, density, community diversity) from individual samples, with thresholds that are based on specified degrees of precision.
In addition to reducing sample size, a monitoring program based on sequential sampling can provide clear-cut decisions as to whethera priori-defined changes in the measured parameter(s) have or have not occurred. As examples, sequential sampling programs have been developed to evaluate the impact of geothermal energy development on benthic macroinvertebrate diversity at The Geysers, California, and for monitoring the impact of crude oil contamination on chironomid midge [Cricotopus bicinctus (Meigen) andC. mackenziensis Oliver] population densities in the Trail River, Northwest Territories, Canada.
Key wordsSequential sampling Benthic macroinvertebrates Environmental impact assessments Benthic monitoring programs Geothermal energy Crude oil contamination Cricotopus Sequential comparison index
Unable to display preview. Download preview PDF.
- Cairns, J. Jr., D. W. Albaugh, F. Busey, and M. D. Chaney. 1968. The sequential comparison index—a simplified method for non-biologists to estimate relative differences in biological diversity in stream pollution studies.Journal of the Water Pollution Control Federation 40:1607–1613.PubMedGoogle Scholar
- Eberhardt, L. L. 1978. Appraising variability in population studies.Journal of Wildlife Management 42:207–238.Google Scholar
- Green, R. H. 1979. Sampling design and statistical methods for environmental biologists. John Wiley and Sons, Inc., New York, NY. 257 pp.Google Scholar
- Hawkes, H. A. 1979. Invertebrates as indicators of river water quality. Pages 2-1–2-45in A. James and L. Evison (eds.), Biological indicators of water quality. John Wiley and Sons, Inc., New York, NY. 597 pp.Google Scholar
- Hellawell, J. M. 1978. Macroinvertebrate methods. Biological surveillance of rivers. A biological monitoring handbook. Dorset Press, Dorchester, England. 333 pp.Google Scholar
- Herricks, E. E., and J. Cairns, Jr. 1982. Biological monitoring. Part III-Receiving system methodology based on community structure.Water Research 16:141–153.Google Scholar
- Loesch, J. G. 1974. A sequential sampling plan for hard clams in lower Chesapeake Bay.Chesapeake Science 15:134–139.Google Scholar
- Oakland, G. B. 1950. An application of sequential analysis to whitefish sampling.Biometrics 6:59–67.Google Scholar
- Oliver, D. R. 1977.Bicinctus—group of the genusCricotopus van der Wulp (Diptera: Chironomidae) in the Nearctic with a description of a new species.Journal of the Fisheries Research Board of Canada. 34:98–104.Google Scholar
- Onsager, J. A. 1976. The rationale of sequential sampling, with emphasis on its use in pest management. Technical Bulletin No. 1526, Agricultural Research Service, US Dept. Agriculture. 19 pp.Google Scholar
- Patil, G. P., and C. Taillie. 1976. Ecological diversity: concepts, indices, and applications.Proceedings of the International Biometrics Conference 9:383–411.Google Scholar
- Pieters, E. P. 1978. Bibliography of sequential sampling plans for insects.Bulletin of the Entomological Society of America 24:372–374.Google Scholar
- Resh, V. H. 1979a. Biomonitoring, species diversity indices, and taxonomy. Pages 241–253in J. F. Grassle, G. P. Patil, W. K. Smith, and C. Taillie (eds.), Ecological diversity in theory and practice. International Cooperative Publishing House, Fairland, MD. 365 pp.Google Scholar
- Resh, V. H. 1979b. Sampling variability and life history features: basic considerations in the design of aquatic insect studies.Journal of the Fisheries Research Board of Canada 36:290–311.Google Scholar
- Resh, V. H., T. S. Flynn, G. A. Lamberti, E. P. McElravy, K. L. Sorg, and J. R. Wood. 1981. Responses of the sericostomatid caddisflyGumaga nigricula (McL.) to environmental disruptions.Proceedings of the 3rd International Symposium on Trichoptera.Series Entomologica (The Hague) 20:311–318.Google Scholar
- Rosenberg, D. M., and A. P. Wiens. 1976. Community and species responses of Chironomidae (Diptera) to contamination of fresh waters by crude oil and petroleum products, with special reference to the Trail River, Northwest Territories.Journal of the Fisheries Research Board of Canada 33:1955–1963.Google Scholar
- Rosenberg, D. M., A. P. Wiens, and O. A. Saether. 1977. Responses to crude oil contamination byCricotopus (Cricotopus) bicinctus andC. (C.) rnackenziensis (Diptera: Chironomidae) in the Fort Simpson area, Northwest Territories.Journal of the Fisheries Research Board of Canada 34:254–261.Google Scholar
- Rosenberg, D. M., V. H. Resh, S. S. Balling, M. A. Barnby, J. N. Collins, D. V. Durbin, T. S. Flynn, D. D. Hart, G. A. Lamberti, E. P. McElravy, J. R. Wood, T. E. Blank, D. M. Schultz, D. L. Marrin, and D. G. Price. 1981. Recent trends in environmental impact assessment.Canadian Journal of Fisheries and Aquatic Sciences 28:591–624.Google Scholar
- Rosenberg, D. M., and V. H. Resh. 1982. The use of artificial substrates in the study of freshwater benthic macroinvertebrates. Pages 175–235in J. Cairns, Jr. (ed.), Artificial substrates. Ann Arbor Scientific Publishers, Ann Arbor, MI. 279 pp.Google Scholar
- Saila, S. B., J. M. Flowers, and R. Campbell. 1965. Applications of sequential sampling to marine resource surveys.Ocean Sciences and Ocean Engineering 2:782–802.Google Scholar
- Wald, A. 1947.Sequential analysis. John Wiley and Sons, Inc., New York, NY. 212 pp.Google Scholar
- Waters, W. E. 1955. Sequential sampling in forest insect surveys.Forest Science 1:68–79.Google Scholar
- Waters, W. E. 1974. Sequential sampling applied to forest insect surveys. Pages 290–311in Proceedings, Monitoring forest environment through successive sampling. T. Cunia (ed.), State University of New York College of Environmental Science and Forestry, Syracuse, NY. 390 pp.Google Scholar
- Wetherill, G. B. 1975. Sequential methods in statistics, 2nd ed. Chapman and Hall, London. 232 pp. [Distributed by Halsted Press, New York, NY].Google Scholar