DOI QR코드

DOI QR Code

Development of Benthic Macroinvertebrates Family-Level Biotic Index for Biological Assessment on Korean Stream Environment

한국의 하천환경 평가를 위한 저서성 대형무척추동물의 과 범주 생물지수 개발

  • Kong, Dongsoo (Department of Bioconvergence, Kyonggi University) ;
  • Min, Jeong-Ki (Department of Bioconvergence, Kyonggi University) ;
  • Noh, Seong-Yoo (Water Environment Research Department, National Institute of Environmental Research)
  • 공동수 (경기대학교 바이오융합학부) ;
  • 민정기 (경기대학교 바이오융합학부) ;
  • 노성유 (국립환경과학원 물환경연구부)
  • Received : 2019.02.15
  • Accepted : 2018.03.28
  • Published : 2019.03.30

Abstract

In this study, a Benthic Macroinvertebrates Family Index (BMFI) was developed using 100 indicator groups (99 families including Chironomidae with 2 phena). Families were assigned a score between 1 and 10 depending on their sensitivity to organic pollution. The BMFI was composed of the sensitivity and relative abundance of the indicator taxa. Sensitivity values of each group were generally similar to Biological Monitoring Working Party (BMWP) scores or Walley, Hawkes, Paisley, Trigg (WHPT) scores of UK, Japanese BMWP scores, and the FBI tolerance values of North America. However, sensitivity values of some taxa were significantly different from those of foreign countries, which seemed to have resulted from discrepancy in species composition, difference of taxonomic classification system, or methodological difference for estimation of sensitivity. As an annual average level, BMFI showed significant correlation with concentration of 5-day biochemical oxygen demand (BOD5) (correlation coefficient r = -0.80, n = 569 sites), total suspended solids (r = -0.68), and total phosphorus (r = -0.79). In addition, BMFI revealed strong correlation with Shannon-Weaver's species diversity (r = 0.85), Margalef's species richness (r = 0.85) and McNaughton's dominance (r = -0.84). Correlation between BMFI and water quality parameters or community indices such as species diversity did not show significant difference compared to that of species-level indices such as BMI (Benthic Macroinvertebrates Index). This means that BMFI is a more useful indicator in terms of easy identification of organisms. BMFI was used to assess the environmental status of 3,017 sites of Stream Ecosystem Survey conducted by the Korean Ministry of Environment between 2016 and 2018. As a result, about half of all sites appeared to be in good condition, and a quarter in poor condition.

Keywords

SJBJB8_2019_v35n2_152_f0001.png 이미지

Fig. 1. Relationship between Benthic Macroinvertebrates Family Index (BMFI) and (a) water quality (BOD5, total suspended solids (TSS), and total phosphorus (T-P)) (b) community indices (Shannon-Weaver's species diversity (H'), Margalef's species richness (R), McNaughton's dominance index (DI)).

SJBJB8_2019_v35n2_152_f0002.png 이미지

Fig. 2. Frequency of environmental status evaluated by BMFI in the 3,017 sites of Stream Ecosystem Survey by Ministry of Environment during 2016 ~ 2018.

Table 1. Scheme of BOD5 concentration according to saprobic series from Kong, Min et al. (2018), Kong, Son et al. (2018)

SJBJB8_2019_v35n2_152_t0001.png 이미지

Table 2. Sensitivity values according to saprobic values

SJBJB8_2019_v35n2_152_t0002.png 이미지

Table 3. Scheme of relative abundance (hi) according to rank percentage of individual abundance (Ri)

SJBJB8_2019_v35n2_152_t0003.png 이미지

Table 4. Community indices used in this study

SJBJB8_2019_v35n2_152_t0004.png 이미지

Table 5. Comparative analysis on sensitivity values and tolerance values of Benthic Macroinvertebrate Family

SJBJB8_2019_v35n2_152_t0005.png 이미지

Table 5. Comparative analysis on sensitivity values and tolerance values of Benthic Macroinvertebrate Family (continued)

SJBJB8_2019_v35n2_152_t0006.png 이미지

Table 5. Comparative analysis on sensitivity values and tolerance values of Benthic Macroinvertebrate Family (continued)

SJBJB8_2019_v35n2_152_t0007.png 이미지

Table 6. Scheme of BMFI based on criteria of BOD5, TSS and TP concentration

SJBJB8_2019_v35n2_152_t0008.png 이미지

References

  1. 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, Second Edition, EPA 841-B-99-002, United States Environmental Protection Agency; Office of Water, Washington, D.C., xiv, 11 chapters, 4 appendices.
  2. Bode, R. W., Novak, M. A., and Abele, L. E. (1996). Quality assurance work plan for biological stream monitoring in New York State, NYS Department of Environmental Conservation, Albany, NY, 1-89.
  3. Bode, R. W., Novak, M. A., Abele, L. E., Heitzman, D. L., and Smith, A. J. (2002). Quality assurance work plan for biological stream monitoring in New York State, NYS Department of Environmental Conservation, Albany, NY, 1-115.
  4. Chandler, J. R. (1970). A biological approach to water quality management, Water Pollution Control, 69(4), 415-422.
  5. Clarke R. T. and Davy-Boeker, J. (2014). River invertebrate classification tool science development project: modifications for WHPT and other abundance-weighted indices, a report to the Scottish Environment Protection Agency, FBA Project Code S/0008/R, Scottish Environment Protection Agency, 1-85.
  6. Dufrene, M. and Legendre, P. (1997). Species assemblages and indicator species: the need for a flexible asymmetrical approach, Ecological Monographs, 67(3), 345-366. https://doi.org/10.1890/0012-9615(1997)067[0345:SAAIST]2.0.CO;2
  7. Hawkes H. A. (1997). Origin and development of the biological monitoring working party score system, Water Research, 32(3), 964-968. https://doi.org/10.1016/S0043-1354(97)00275-3
  8. Hilsenhoff, W. L. (1988). Rapid field assessment of organic pollution with a family-level biotic index, Journal of the North American Benthological Society, 7(1), 65-68. https://doi.org/10.2307/1467832
  9. Kong, D., Min, J. K., and Noh, S. Y. (2018). Development of simple benthic macroinvertebrates index (SBMI) for biological assessment on stream environment, Journal of Korean Society on Water Environment, 34(5), 514-536. [Korean Literature] https://doi.org/10.15681/KSWE.2018.34.5.514
  10. Kong, D., Son, S. H., Hwang S. J., Won, D. H., Kim, M. C., Park, J. H., Jeon, T. S., Lee, J. E., Kim, J. H., Kim, J. S., Park J., Kwak, I. S., Jun, Y. C., Park, Y. S., Ham, S. A., Lee, J. K., Lee, S. W., Park, C. H., Moon, J. S., Kim, J. Y., Park, H. K., Park, S. J., Kwon Y., Kim P., and Kim, A. R. (2018). Development of benthic macroinvertebrates index (BMI) for biological assessment on stream environment, Journal of Korean Society on Water Environment, 34(2), 183-201. [Korean Literature] https://doi.org/10.15681/KSWE.2018.34.2.183
  11. Margalef, R. (1958). Information theory in ecology, General Systems, 3, 36-71.
  12. McNaughton, S. J. (1967). Relationship among functional properties of California Grassland, Nature, 216, 168-169. https://doi.org/10.1038/216168b0
  13. Nojaki, T. (2012). Biological assessment based on macroinvertebrate communities -average score system for Japanes rivers-, Journal of Japan Society on Water Environment, 35(A)(4), 118-121. [Japanese Literature]
  14. Paisley, M. F., Trigg, D. J., and Walley, W. J. (2014). Revision of the Biological Monitoring Working Party (BMWP) score system : derivation of present-only and abundance-related scores from field data, River Research and Applications, 30(7), 887-904. https://doi.org/10.1002/rra.2686
  15. Pantle, R. and Buck, H. (1955). Die biologische Uberwachung der Gewasser und Darstellung Ergebnisse, Gas-und Wasserfach, 96, 604-624.
  16. Plafkin, J. L., Barbour, M. T., Porter, K. D., Gross, S. K., and Hughes, R. M. (1989). Rapid bioassessment protocols for use in streams and rivers: Benthic macroinvertebrates and fish, EPA 440/4-89/001, United States Environmental Protection Agency, 8 chapters, Appendices A-D.
  17. Shannon, C. E. and Weaver, W. (1949). The mathematical theory of communication, University of Illinois Press, Urbana.
  18. Soil & Water Conservation Society of Metro Halifax (SWCSMH). (2015). Taxa tolerance values, http://lakes.chebucto.org/ZOOBENTH/BENTHOS/tolerance.html (accessed Jan. 2019).
  19. UK Legislation. (2015). The Water Framework Directive (Standards and Classification) Directions (England and Wales) 2015, https://www.legislation.gov.uk/uksi/2015/1623/resources (accessed Jan. 2019).
  20. 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 Research, 30(9), 2086-2094. https://doi.org/10.1016/0043-1354(96)00013-9
  21. 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 Research, 31(2), 201-210. https://doi.org/10.1016/S0043-1354(96)00249-7
  22. Water Framework Directive-United Kingdom Advisory Group (WFD-UKTAG). (2014). UKTAG river assessment method - benthic invertebrate fauna -. Invertebrates (General Degradation): Whalley, Hawkes, Paisley & Trigg (WHPT) metric in River Invertebrate Classification Tool (RICT), https://www.wfduk.org/resources/category/biological-standard-methods-201 (accessed Jan. 2019).
  23. 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, Cumbria, UK, 1-24.
  24. Yoon, I. B., Kong, D., and Ryu, J. K. (1992a). Studies on the biological evaluation of water quality by benthic macroinvertebrates (1) saprobic valency and indicative value, Korean Society of Environmental Biology, 10(1), 24-49. [Korean Literature]
  25. Yoon, I. B., Kong, D., and Ryu, J. K. (1992b). Studies on the biological evaluation of water quality by benthic macroinvertebrates (3) macroscopic simple water quality evaluation, Korean Society of Environmental Biology, 10(2), 77-84. [Korean Literature]
  26. Zelinka, M. and Marvan. P. (1961). Zur prazisierung der biologischen klassifikation der reinheid fliessender gewasser, Archiv fur Hydrobiologie, 57(3), 389-407.