[논문]저서성 대형무척추동물을 이용한 RIVPACS 유형의 하천생태계 건강성 평가법 국내 하천 적용성

이다영; 이대성; 민중혁; 박영석

doi:10.11614/ksl.2023.56.1.045

[국내논문] 저서성 대형무척추동물을 이용한 RIVPACS 유형의 하천생태계 건강성 평가법 국내 하천 적용성
Development and Testing of a RIVPACS-type Model to Assess the Ecosystem Health in Korean Streams: A Preliminary Study 원문보기

생태와 환경 = Korean journal of ecology and environment, v.56 no.1, 2023년, pp.45 - 56

이다영 (경희대학교 생물학과) , 이대성 (경희대학교 생물학과) , 민중혁 (국립환경과학원 유역총량연구과) , 박영석 (경희대학교 생물학과)

초록
AI-Helper

본 연구는 저서성 대형무척추동물을 이용한 RIVPACS 유형의 국내 실정에 맞는 수생태계 예측 및 평가모델을 구축하기 위한 사전 연구로서 수행되었다. 자연상태의 하천인 887개의 참조하천을 선정하고, 참조하천을 저차하천과 고차하천으로 구분한 뒤 random forest 알고리즘을 이용하여 각각의 과에 대하여 예측모델을 구축하였다. 저차하천은 학습과 검증 데이터를 7 : 3의 비율로 나누어 구축하였으며, 고차하천의 경우에는 leave-one-out 방법을 이용하였다. 예측모델에 사용된 환경변수는 비계량 다차원 척도법(NMDS)을 이용하여 선정되었으며, 고도, 경사각, 평년평균기온, 숲의 비율, 하폭, 여울 비율, 하상 구조의 큰돌의 비율로 7개의 변수가 선택되었다. 3,224개의 조사대상 지점을 하천차수에 따른 유형에 따라 구분한 뒤, 각각의 유형에 해당하는 모델을 이용하여 30개 과에 대한 과 단위의 생물상을 예측하였다. 예측된 생물상(E)은 실제 생물상(O)과 생물지수를 이용하여 비교되었다. 생물지수는 BMWPK 지수를 과의 수로 나눈 ASPT를 이용하였다. 그 이후 EQR 지수(O/E)를 이용하여 각 조사지점의 건강성을 평가하였다. 마지막으로, EQR 값을 기존에 이용되고 있는 BMI 값과 비교하였다. 건강성 점수 평가 결과, 실제 군집은 0~20과, 예측된 군집은 0~19과 범위로 예측되어 유사하게 나타났다. 실제 ASPT는 평균 4.82 (±2.04 SD), 예측된 ASPT는 6.30 (±0.79 SD)으로 예측된 값이 더 높게 나타났다. ASPT와 BMI의 비교 결과, 대체로 EQR이 BMI 지수보다 높은 값을 보였다. 이는 참조하천 선정에 있어서 조금 교란된 지점도 자연상태로 가정하여 참조하천으로 이용되었기 때문으로 보인다. RIVPACS 모델은 생태학적 상태에 대한 단순하지만 명확한 진단을 제공해줌으로써 국내 하천 관리에 도움이 될 것으로 기대된다. 본 연구는 연구가 미진하였던 우리나라 실정에 맞는 RIVPACS 유형의 평가법을 개발하는 선행 연구로서의 의의가 있다.

Abstract ▼ AI-Helper

In stream ecosystem assessment, RIVPACS, which makes a simple but clear evaluation based on macroinvertebrate community, is widely used. In this study, a preliminary study was conducted to develop a RIVPACS-type model suitable for Korean streams nationwide. Reference streams were classified into two types(upstream and downstream), and a prediction model for macroinvertebrates was developed based on each family. A model for upstream was divided into 7 (train): 3 (test), and that for downstream was made using a leave-one-out method. Variables for the models were selected by non-metric multidimensional scaling, and seven variables were chosen, including elevation, slope, annual average temperature, stream width, forest ratio in land use, riffle ratio in hydrological characteristics, and boulder ratio in substrate composition. Stream order classified 3,224 sites as upstream and downstream, and community compositions of sites were predicted. The prediction was conducted for 30 macroinvertebrate families. Expected (E) and observed fauna (O) were compared using an ASPT biotic index, which is computed by dividing the BMWPK score into the number of families in a community. EQR values (i.e. O/E) for ASPT were used to assess stream condition. Lastly, we compared EQR to BMI, an index that is commonly used in the assessment. In the results, the average observed ASPT was 4.82 (±2.04 SD) and the expected one was 6.30 (±0.79 SD), and the expected ASPT was higher than the observed one. In the comparison between EQR and BMI index, EQR generally showed a higher value than the BMI index.

Keyword

참고문헌 (40)

Armitage, P.D., D. Moss, J.F. Wright and M.T. Furse. 1983. The？performance of a new biological water quality score system？based on macroinvertebrates over a wide range of unpolluted running-water sites. Water Research 17: 333-347.

상세보기
Bae, M.-J., J.H. Chun, T.-S. Chon and Y.-S. Park. 2016. Spatiotemporal variability in benthic macroinvertebrate communities in headwater streams in South Korea. Water 8: 99.
Bae, M.-J., Y. Kwon, S.-J. Hwang, T.-S. Chon, H.-J. Yang, I.-S.？Kwak, J.-H. Park, S.-A. Ham and Y.-S. Park. 2011. Relationships between three major stream assemblages and their？environmental factors in multiple spatial scales. Annales de？Limnologie - International Journal of Limnology 47: S91-S105.
Bae, M.-J., F. Li, Y.-S. Kwon, N. Chung, H. Choi, S.-J. Hwang？and Y.-S. Park. 2014. Concordance of diatom, macroinvertebrate and fish assemblages in streams at nested spatial？scales: Implications for ecological integrity. Ecological？Indicators 47: 89-101.

상세보기
Bae, M.-J. and Y.-S. Park. 2019. Evaluation of precipitation impacts on benthic macroinvertebrate communities at three？different stream types. Ecological Indicators 102: 446-456.

상세보기
Breiman, L. 2001. Random Forests. Machine Learning 45: 5-32.
Cao, Y., D.P. Larsen and R.S.-J. Thorne. 2001. Rare species in multivariate analysis for bioassessment: Some considerations.？Journal of the North American Benthological Society？20: 144-153.
Clarke, R. 2000. Uncertainty in estimates of biological quality？based on RIVPACS. In: Assessing the biological quality of？fresh waters: RIVPACS and other techniques(Wright, J.F.,？D.W. Sutcliffe and M.T. Furse, eds.). Freshwater Biological？Association, Ambelside, UK.
Clarke, R.T., M.T. Furse, J.F. Wright and D. Moss. 1996. Derivation of a biological quality index for river sites: Comparison？of the observed with the expected fauna. Journal of Applied？Statistics 23: 311-332.
Clarke, R.T., J.F. Wright and M.T. Furse. 2003. RIVPACS models？for predicting the expected macroinvertebrate fauna and？assessing the ecological quality of rivers. Ecological Modelling 160: 219-233.

상세보기
ESRI. 2013. ArcGIS. Environmental Systems Research Incorporated (ESRI): Redlands, CA, USA.
Hallstan, S., R.K. Johnson, E. Willen and U. Grandin. 2012.？Comparison of classification-then-modelling and species-by-species modelling for predicting lake phytoplankton？assemblages. Ecological Modelling 231: 11-19.

상세보기
Hargett, E.G., J.R. ZumBerge, C.P. Hawkins and J.R. Olson. 2007.？Development of a RIVPACS-type predictive model for bioassessment of wadeable streams in Wyoming. Ecological？Indicators 7: 807-826.

상세보기
Hawkins, C.P. 2006. Quantifying biological integrity by taxonomic completeness: Its utility in regional and global assessments. Ecological Applications 16: 1277-1294.

상세보기
Hijmans, R.J., S. Phillips, J. Leathwick and J. Elith. 2017. Package？'dismo'. Circles 9.
Joy, M. 2013. Freshwater fish predictive modelling for bioassessment: A scoping study into fish bioassessment models as？national indicators in New Zealand. Available: http://www.mfe.govt.nz/publications/ser/freshwater-fish-predictive-modelling-bioassessment-scoping-study.html.
Jyvasjarvi, J., J. Aroviita and H. Hamalainen. 2011. Evaluation？of approaches for measuring taxonomic completeness of？lake profundal macroinvertebrate assemblages. Freshwater？Biology 56: 1876-1892.

상세보기
Kim, D.-H., T.-S. Chon, G.-S. Kwak, S.-B. Lee and Y.-S. Park.？2016. Effects of land use types on community structure？patterns of benthic macroinvertebrates in streams of urban？areas in the South of the Korea Peninsula. Water 8: 187.
Kong, D., J.-K. Min and S.-Y. Noh. 2019. Development of benthic macroinvertebrates family-level biotic index for biological assessment on Korean stream environment. Journal？of Korean Society on Water Environment 35: 152-164.
Kong, D., S.-H. Son, S.-J. Hwang, D.H. Won, M.C. Kim, J.H. Park,？T.S. Jeon, J.E. Lee, J.H. Kim, J.S. Kim, J. Park, I.S. Kwak,？S.A. Ham, Y.-C. Jun, Y.-S. Park, J.-K. Lee, S.-W. Lee, C.-H.？Park, J.-S. Moon, J.-Y. Kim, H.K. Park, S.J. Park, Y. Kwon,？P. Kim and A.R. Kim. 2018. Development of benthic？macroinvertebrates index (BMI) for biological assessment？on stream environment. Journal of Korean Society on Water？Environment 34: 183-201.
Kwak, I.-S., D.-S. Lee, C. Hong and Y.-S. Park. 2018. Distribution patterns of benthic macroinvertebrates in streams of？Korea. Korean Journal of Ecology and Environment 51: 60-70.
Lee, D.-S., Y.-S. Bae, B.-K. Byun, S. Lee, J.K. Park and Y.-S. Park.？2019. Occurrence prediction of the citrus flatid planthopper？(Metcalfa pruinosa (Say, 1830)) in South Korea using a？random forest model. Forest 10: 585.
Lee, D.-Y., D.-S. Lee, M.-J. Bae, S.-J. Hwang, S.-Y. Noh, J.-S.？Moon and Y.-S. Park. 2018. Distribution patterns of odonate assemblages in relation to environmental variables in？streams of South Korea. Insects 9: 152.

상세보기
Lee, D.-Y., D.-S. Lee, S.-J. Hwang, K.-L. Lee and Y.-S. Park.？2022. Distribution patterns and vulnerability of stoneflies？(Plecoptera: Insecta) in South Korean streams with conservation perspectives. Global Ecology and Conservation 34: e02030.

상세보기
Liaw, A. and M. Wiener. 2002. Classification and regression by？randomForest. R News 2.
Min, J.-K. 2022. Development of a predictive model based on？benthic macroinvertebrate community for the assessment of？biological integrity of rivers. Kyonggi University, Suwon.
Minister of Environment (MOE). 2009. Development of Field？Application Methods in Ecological Impact Assessment on？Environmental Pollutants Using Invertebrate Biological？Indicators. MOE, Gwacheon.
Minister of Environment (MOE) and National Institute of Environmental Research (NIER). 2015. Survey and Evaluation？Method for River and Stream Ecosystem Health Assessment. MOE/NIER, Incheon, Republic of Korea.
Muralidharan, M., C. Selvakumar, S. Sudar and M. Raja. 2010.？Macroinvertebrates as potential indicators of environmental？quality. International Journal of Biological Technology 1:？23-28.
National Institute of Environmental Research (NIER). 2019. Survey and Evaluation Method for River and Stream Ecosystem Health Assessment - Stream. NIER, Incheon, Republic？of Korea.
Oksanen, J., F.G. Blanchet, M. Friendly, R. Kindt, P. Legendre,？D. McGlinn, P.R. Minchin, R.B. O'Hara, G.L. Simpson, P.？Solymos, M.H.H. Stevens, E. Szoecs and H. Wagner. 2019.？vegan: Community ecology package. R package.
Ostermiller, J.D. and C.P. Hawkins. 2004. Effects of sampling？error on bioassessments of stream ecosystems: Application？to RIVPACS-type models. Journal of the North American？Benthological Society 23: 363-382.

상세보기
Resh, V.H. and J.D. Unzicker. 1975. Water quality monitoring and？aquatic organisms: The importance of species identification. Journal- Water Pollution Control Federation 47: 9-19.
Robin, X., N. Turck, A. Hainard, N. Tiberti, F. Lisacek, J.-C. Sanchez and M. Muller. 2011. pROC: An open-source package？for R and S+ to analyze and compare ROC curves. BMC？Bioinformatics 11: 77.
Rose, P.M., M.J. Kennard, D.B. Moffatt, F. Sheldon and G.L.？Butler. 2016. Testing three species distribution modelling？strategies to define fish assemblage reference conditions for？stream bioassessment and related applications. PLoS ONE？11: e0146728.
Shannon, C.E. 1948. A mathematical theory of communication.？The Bell System Technical Journal 27: 379-423.

상세보기
Smith, M.J., W.R. Kay, D.H.D. Edward, P.J. Papas, K.S.J. Richardson, J.C. Simpson, A.M. Pinder, D.J. Cale, P.H.J. Horwitz,？J.A. Davis, F.H. Yung, R.H. Norris and S.A. Halse. 1999.？AusRivAS: Using macroinvertebrates to assess ecological？condition of rivers in Western Australia. Freshwater Biology 41: 269-282.
Van Sickle, J. and C. Burch Johnson. 2008. Parametric distance？weighting of landscape influence on streams. Landscape？Ecology 23: 427-438.

상세보기
Wright, J.F. 2000. An introduction to RIVPACS. Assessing the？biological quality of fresh waters: RIVPACS and other？techniques. Freshwater Biological Association.
Yuan, L.L. 2006. Theoretical predictions of observed to expected？ratios in RIVPACS-type predictive model assessments of？stream biological condition. Journal of the North American？Benthological Society 25: 841-850.

상세보기

저자의 다른 논문 :

표제어: PCR

동의어: Packet Collision Rate

용어 설명 출처 목록 (6)

용어 설명: PCR은 세균 특이성이 있는 primer를 이용하여 적은 수의 세균이 있을지라도 쉽게 검출할 수 있는 유용한 방법이며, 이를 이용하여 구강 내 치면세균막이나 타액에서 직접 세균을 검출할 수 있게 되었다[8].

내보내기 구분	파일저장 인쇄 메일전송
구성항목	기본정보 상세정보 관리번호, 논문명, 저널/프로시딩명, 저자 , 발행년, 권, 호, 시작페이지, 끝페이지, 발행기관 관리번호, 논문명, 대등논문명, 저자 , 저널/프로시딩명, 발행기관, 발행년, 발행언어, 권, 호, 시작페이지, 끝페이지, ISBN, ISSN, 주제분야, 키워드, 초록(한글), 초록(영문), 저자(소속기관)
저장형식	Text(ASCII format) Excel format RefWorks Direct Export RIS format (for Reference Manager, ProCite, EndNote), Scholar's Aids, Mendeley
메일정보	받는사람 (필수) @ 보내는사람 (선택) @ 제목 내용 KISTI 검색결과 이메일 서비스
안내	총 건의 자료가 검색되었습니다. 다운받으실 자료의 인덱스를 입력하세요. (1-10,000) 검색결과의 순서대로 최대 10,000건 까지 다운로드가 가능합니다. 데이타가 많을 경우 속도가 느려질 수 있습니다.(최대 2~3분 소요) 다운로드 파일은 UTF-8 형태로 저장됩니다. 파일의 내용이 제대로 보이지 않을실 때는 웹브라우저 상단의 보기 -> 인코딩 -> 자동선택 여부를 확인하십시오. ~ Text(ASCII format) Excel format

연합인증