大型底栖无脊椎动物在水环境管理中的应用
|
摘要
一、底栖动物生物指数水质评价进展及在我国的应用前景
水质生物评价历经了一个多世纪的发展,其重要性已慢慢被人们所认知。大型底栖无脊椎动物是国家级水质生物评价方法中最常用的指示生物,本文回顾了基于底栖动物的3类广泛应用的水质生物评价参数：Saprobic指数、BI指数和记分系统以及群落多样性指数的发展简史,并分析了各指数的优缺点。我国的水质生物监测与发达国家之间相比有很大差距,鉴定资料匮乏,底栖动物的耐污值尚未科学建立,缺乏规范化的采样方法以及评价标准；另外,大众对生物监测的关注度低,这些都阻碍了生物监测在我国的发展。欧盟成员国、北美和澳大利亚等国都早已建立了适合本国(地区)的水质生物评价规划,而我国目前尚缺乏一个国家级的水质生物评价指数。目前,BI指数的应用已推广至各种水体(溪流、河流、湖泊和水库),这为BI指数在我国的推广应用创造了一个良好的契机。作者建议尽快深入开展BI指数的相关研究,解决BI指数在我国推广存在的问题,建立区域或流域的BI指数评价标准,最终建立基于BI指数的国家级水质生物评价规范,充分发挥生物监测在水环境管理中的应用。
二、秦淮河上游水体大型底栖无脊椎动物群落结构及水质生物评价
2009年4月用D形网半定量采样法调查了秦淮河上游25个点位的大型底栖无脊椎动物群落多样性,共获得63个大型底栖无脊椎动物分类单元；其中,水生昆虫5目12科30属,软体动物9科11属19种,寡毛纲2科7属9种。研究结果表明BI指数比Shannon-Wiener多样性指数的评价结果更接近实际情况,BI指数与TN(r=0.44,p<0.05)和NH4+(r=0.40,p<0.05)之间显著相关,多样性指数与TN(r=-0.187,p>0.05)和NH4+(r=0.44,p>0.05)相关性不明显。水质生物评价的结果是秦淮河上游水体受到的污染较严重,句容地区的水体质量要高于南京。
三、影响西苕溪底栖动物分布的关键环境变量指示种的建立
利用2003年西苕溪TM数据和DEM模型计算了55个样点上游3种空间尺度下(亚流域、沿岸和局部)的土地利用类型,通过冗余分析(Redundancy Analysis, RDA)筛选出能够在显著水平上最大程度解释西苕溪流域底栖动物分布的最小变量组合——氨氮、荫蔽度、电导率、亚流域农田百分比以及栖境复杂度。方差分解结果表明氨氮是研究区域影响底栖动物分布的最重要环境变量,亚流域尺度农田百分比也是一个重要影响变量。在50%-100%适合度范围内最终筛选得到短脉纹石蛾种1(Cheumatopsyche spl)和种2 (Cheumatopsyche sp2),在一定范围内短脉纹石蛾的数量随着水体氨氮浓度和亚流域尺度农田百分比的上升而增加。短脉纹石蛾分布广泛、采集容易、具备一定的耐污能力和主动漂流能力、幼虫个体较大且在水中的生活史较长以及具有一定的生态可塑性等优点决定了短脉纹石蛾可以作为西苕溪流域的受干扰水体氨氮和亚流域尺度农田百分比的指示种。
四、基于大型底栖无脊椎动物的河流营养盐浓度阈值研究——以西苕溪上游流域为例
水体富营养化是一个全球性的问题,我国也面临严峻的水体富营养化威胁。但我国的水体富营养化研究集中在湖泊和水库,河流富营养化研究极少。本文依据大型底栖无脊椎动物群落结构与营养盐之间的胁迫响应,运用非参数转变点分析方法计算西苕溪上游营养盐浓度的突变点。研究结果表明：总氮和总磷的突变点分别为1.409mg·L-1和0.033—0.035mg·L-1。参照点的总氮和总磷浓度基本都低于阈值,城市干扰点的总氮和总磷浓度都高于阈值,当总氮和总磷超过各自阈值时会导致大型底栖无脊椎动物群落结构的严重退化。希望通过建立与水生生物群落结构有关的水体营养盐标准,充分发挥生物监测在水环境管理中的作用,如为水体中总氮和总磷的最大日负荷总量的计算提供科学数据等。
1 The Advancement of Biotic Index of Water Quality Bioassessment Using Benthic Macroinvertebrate Assemblages and Its Perspective in China
The history of bioassessment of rivers is a good hundred years old, and the importance of bioassessment is recognized gradually. Among the biological communities, the macroinvertebrates are by far the most frequently used group for bioassessment in standard water management. This paper reviews the history and development of three principal bioassessment approaches--saprobic indices, biotic indices and scoring systems, diversity indices, and critically evaluates these three principal approaches. Comparing with the developed countries, the development of biomonitoring in China was far behind. Impediments to biomonitoring in our country include:the insufficient taxonomic literature, the tolerance values of benthic macroinvertebrates have not scientifically established, standard sampling tools and methods for benthic macroinvertebrates and bioassessment criteria of BI have not been established, besides these, people pay less attention to biomionitoring. EU member states, North America and Australia have already had their national river monitoring programmes, respectively. Lacking standard biotic index is the most important problem in China. Presently, the BI is extended to all kinds of water bodies (stream, river, lake and reservoir), which provides a good opportunity for popularizing BI. We suggested that it is urgent to conduct study on BI and its criteria in water quality biomontoring, and to set up a standard biomonitoring programmes based on BI eventually, giving full play to the importance of biological monitoring in water management.
2 Community Structures of Macroinvertebrates and Bioassessment of Upstream Qinhuai River
Benthic macroinvertebrates assemblages were collected from the upstream of the Qinhuai River in April,2009. A total of 63 macroinvertebrate taxa were found including 30 genera and 12 families of Insecta,19 species and 11 genera in 9 families of Mollusca,9 species and 7 genera in 2 families of Oligochaeta. Our study indicated that BI had a better discrimination than Shannon-Wiener diversity index. The Pearson's correlation analysis showed that BI corresponded strongly with TN (r=0.44, p<0.05) and NH4+(r=0.40, p<0.05), that Shannon-Wiener diversity index had no significant correlation with TN (r =-0.187, p=0.370) and NH4+(r=0.44, p=0.451). The results showed that the upper reaches of Qinhuai River suffered from severe pollution and the water quality of Nanjing area was worse than that of Jurong's.
3 Selection of indicator species of major environmental variables affecting macroinvertebrate communities in the Xitiao Stream, Zhejiang, China
The land covers for 55 sampling sites were estimated at sub-basin, riparian-zone and local scales using 2003 satellite image and a Digital Elevation Model. By applying the redundancy analysis (RDA) the minimum variables combination-NH4+, canopy, conductivity, sub-scale cropland% and habit complexity which can significantly explain the macroinvertebrate communities were screened. The result of variance partitioning showed that NH4+was the most important variables affecting macroinvertebrate communities in the Xitiao Stream, and sub-scale cropland% was also another important factor. Under the species fit range between 50% and 100%, Cheumatopsyche sp.1 and Cheumatopsyche sp.2 were finally obtained, the abundance of Cheumatopsyche increased as the NH4+ and the sub-scale cropland% increased. The Cheumatopsyche has following advantages:widely distributed, could be easily collected, with moderately tolerance, actively drift, large body size with slower turnover rates and ecological plasticity, they exhibit to be excellent indicators for the NH4+and the sub-basin scale cropland% of disturbed sites in the Xitiao Stream.
4 Research on the river nutrients threshold based on benthic macroinvertebrate
assemblages:a case study in the upstream of the Xitiao Stream, Zhejiang, China Eutrophication has become a global problem and is one of the major environmental problems faced by China. At present, studies on the water eutrophication were mainly focused on lakes and reservoirs in China, whereas studies of river eutrophication were few. Based on the stress-response between macroinvertebrate assemblages and nutrients, we used nonparametric deviance reduction (change point analysis) to determine breakpoints in nutrient concentrations at which there was the most abrupt biotic response in the upstream watershed of the Xitiao Stream. The results indicated that the threshold was 1.409mg·L-1for TN and 0.033—0.035mg-·L-1for TP. The TN and TP concentrations of reference sites and city sewage polluted sites are lower and higher than the changepoints respectively. Nutrient concentrations higher than the thresholds may lead to the degradation of macroinvertebrates structures. We wish to set up nutrients criteria based on aquatic organisms, and give full play to the importance of biological monitoring in water management, for example, a total maximum daily load (TMDL) estimate.
水质生物评价历经了一个多世纪的发展,其重要性已慢慢被人们所认知。大型底栖无脊椎动物是国家级水质生物评价方法中最常用的指示生物,本文回顾了基于底栖动物的3类广泛应用的水质生物评价参数：Saprobic指数、BI指数和记分系统以及群落多样性指数的发展简史,并分析了各指数的优缺点。我国的水质生物监测与发达国家之间相比有很大差距,鉴定资料匮乏,底栖动物的耐污值尚未科学建立,缺乏规范化的采样方法以及评价标准；另外,大众对生物监测的关注度低,这些都阻碍了生物监测在我国的发展。欧盟成员国、北美和澳大利亚等国都早已建立了适合本国(地区)的水质生物评价规划,而我国目前尚缺乏一个国家级的水质生物评价指数。目前,BI指数的应用已推广至各种水体(溪流、河流、湖泊和水库),这为BI指数在我国的推广应用创造了一个良好的契机。作者建议尽快深入开展BI指数的相关研究,解决BI指数在我国推广存在的问题,建立区域或流域的BI指数评价标准,最终建立基于BI指数的国家级水质生物评价规范,充分发挥生物监测在水环境管理中的应用。
二、秦淮河上游水体大型底栖无脊椎动物群落结构及水质生物评价
2009年4月用D形网半定量采样法调查了秦淮河上游25个点位的大型底栖无脊椎动物群落多样性,共获得63个大型底栖无脊椎动物分类单元；其中,水生昆虫5目12科30属,软体动物9科11属19种,寡毛纲2科7属9种。研究结果表明BI指数比Shannon-Wiener多样性指数的评价结果更接近实际情况,BI指数与TN(r=0.44,p<0.05)和NH4+(r=0.40,p<0.05)之间显著相关,多样性指数与TN(r=-0.187,p>0.05)和NH4+(r=0.44,p>0.05)相关性不明显。水质生物评价的结果是秦淮河上游水体受到的污染较严重,句容地区的水体质量要高于南京。
三、影响西苕溪底栖动物分布的关键环境变量指示种的建立
利用2003年西苕溪TM数据和DEM模型计算了55个样点上游3种空间尺度下(亚流域、沿岸和局部)的土地利用类型,通过冗余分析(Redundancy Analysis, RDA)筛选出能够在显著水平上最大程度解释西苕溪流域底栖动物分布的最小变量组合——氨氮、荫蔽度、电导率、亚流域农田百分比以及栖境复杂度。方差分解结果表明氨氮是研究区域影响底栖动物分布的最重要环境变量,亚流域尺度农田百分比也是一个重要影响变量。在50%-100%适合度范围内最终筛选得到短脉纹石蛾种1(Cheumatopsyche spl)和种2 (Cheumatopsyche sp2),在一定范围内短脉纹石蛾的数量随着水体氨氮浓度和亚流域尺度农田百分比的上升而增加。短脉纹石蛾分布广泛、采集容易、具备一定的耐污能力和主动漂流能力、幼虫个体较大且在水中的生活史较长以及具有一定的生态可塑性等优点决定了短脉纹石蛾可以作为西苕溪流域的受干扰水体氨氮和亚流域尺度农田百分比的指示种。
四、基于大型底栖无脊椎动物的河流营养盐浓度阈值研究——以西苕溪上游流域为例
水体富营养化是一个全球性的问题,我国也面临严峻的水体富营养化威胁。但我国的水体富营养化研究集中在湖泊和水库,河流富营养化研究极少。本文依据大型底栖无脊椎动物群落结构与营养盐之间的胁迫响应,运用非参数转变点分析方法计算西苕溪上游营养盐浓度的突变点。研究结果表明：总氮和总磷的突变点分别为1.409mg·L-1和0.033—0.035mg·L-1。参照点的总氮和总磷浓度基本都低于阈值,城市干扰点的总氮和总磷浓度都高于阈值,当总氮和总磷超过各自阈值时会导致大型底栖无脊椎动物群落结构的严重退化。希望通过建立与水生生物群落结构有关的水体营养盐标准,充分发挥生物监测在水环境管理中的作用,如为水体中总氮和总磷的最大日负荷总量的计算提供科学数据等。
1 The Advancement of Biotic Index of Water Quality Bioassessment Using Benthic Macroinvertebrate Assemblages and Its Perspective in China
The history of bioassessment of rivers is a good hundred years old, and the importance of bioassessment is recognized gradually. Among the biological communities, the macroinvertebrates are by far the most frequently used group for bioassessment in standard water management. This paper reviews the history and development of three principal bioassessment approaches--saprobic indices, biotic indices and scoring systems, diversity indices, and critically evaluates these three principal approaches. Comparing with the developed countries, the development of biomonitoring in China was far behind. Impediments to biomonitoring in our country include:the insufficient taxonomic literature, the tolerance values of benthic macroinvertebrates have not scientifically established, standard sampling tools and methods for benthic macroinvertebrates and bioassessment criteria of BI have not been established, besides these, people pay less attention to biomionitoring. EU member states, North America and Australia have already had their national river monitoring programmes, respectively. Lacking standard biotic index is the most important problem in China. Presently, the BI is extended to all kinds of water bodies (stream, river, lake and reservoir), which provides a good opportunity for popularizing BI. We suggested that it is urgent to conduct study on BI and its criteria in water quality biomontoring, and to set up a standard biomonitoring programmes based on BI eventually, giving full play to the importance of biological monitoring in water management.
2 Community Structures of Macroinvertebrates and Bioassessment of Upstream Qinhuai River
Benthic macroinvertebrates assemblages were collected from the upstream of the Qinhuai River in April,2009. A total of 63 macroinvertebrate taxa were found including 30 genera and 12 families of Insecta,19 species and 11 genera in 9 families of Mollusca,9 species and 7 genera in 2 families of Oligochaeta. Our study indicated that BI had a better discrimination than Shannon-Wiener diversity index. The Pearson's correlation analysis showed that BI corresponded strongly with TN (r=0.44, p<0.05) and NH4+(r=0.40, p<0.05), that Shannon-Wiener diversity index had no significant correlation with TN (r =-0.187, p=0.370) and NH4+(r=0.44, p=0.451). The results showed that the upper reaches of Qinhuai River suffered from severe pollution and the water quality of Nanjing area was worse than that of Jurong's.
3 Selection of indicator species of major environmental variables affecting macroinvertebrate communities in the Xitiao Stream, Zhejiang, China
The land covers for 55 sampling sites were estimated at sub-basin, riparian-zone and local scales using 2003 satellite image and a Digital Elevation Model. By applying the redundancy analysis (RDA) the minimum variables combination-NH4+, canopy, conductivity, sub-scale cropland% and habit complexity which can significantly explain the macroinvertebrate communities were screened. The result of variance partitioning showed that NH4+was the most important variables affecting macroinvertebrate communities in the Xitiao Stream, and sub-scale cropland% was also another important factor. Under the species fit range between 50% and 100%, Cheumatopsyche sp.1 and Cheumatopsyche sp.2 were finally obtained, the abundance of Cheumatopsyche increased as the NH4+ and the sub-scale cropland% increased. The Cheumatopsyche has following advantages:widely distributed, could be easily collected, with moderately tolerance, actively drift, large body size with slower turnover rates and ecological plasticity, they exhibit to be excellent indicators for the NH4+and the sub-basin scale cropland% of disturbed sites in the Xitiao Stream.
4 Research on the river nutrients threshold based on benthic macroinvertebrate
assemblages:a case study in the upstream of the Xitiao Stream, Zhejiang, China Eutrophication has become a global problem and is one of the major environmental problems faced by China. At present, studies on the water eutrophication were mainly focused on lakes and reservoirs in China, whereas studies of river eutrophication were few. Based on the stress-response between macroinvertebrate assemblages and nutrients, we used nonparametric deviance reduction (change point analysis) to determine breakpoints in nutrient concentrations at which there was the most abrupt biotic response in the upstream watershed of the Xitiao Stream. The results indicated that the threshold was 1.409mg·L-1for TN and 0.033—0.035mg-·L-1for TP. The TN and TP concentrations of reference sites and city sewage polluted sites are lower and higher than the changepoints respectively. Nutrient concentrations higher than the thresholds may lead to the degradation of macroinvertebrates structures. We wish to set up nutrients criteria based on aquatic organisms, and give full play to the importance of biological monitoring in water management, for example, a total maximum daily load (TMDL) estimate.
引文
1. Afnor N. Essai des eaux:determination de l'indice biologique global normalize (IBGN)[S].1992
2. Allan J. D. Landscapes and riverscapes:the influence of land use on stream ecosystems[J].2004
3. Armitage P. D., Moss D., Wright J. F., et al. The performance of a new biological water quality score system based on macroin vertebrates over a wide range of unpolluted running-water sites [J]. Water research.1983,17(3):333-347
4. Barbour M. T., Gerritsen J.,Snyder B. D., et al. Rapid bioassessment protocols for use in streams and wadeable rivers:periphyton, benthic macroinvertebrates, and fish[M]. Washington, DC: Environmental Protection Agency, Office of Water,1999
5. Beck Jr W. M. Suggested method for reporting biotic data [J]. Sewage and Industrial Wastes,1955, 27(10):1193-1197
6. Benke A. C., Wallace J. B. Trophic basis of production among net-spinning caddisflies in a southern Appalachian stream [J]. Ecology,1980,61(1):108-118.
7. Black R. W., Munn M. D.,Plotnikoff R. W. Using macroinvertebrates to identify biota land cover optima at multiple scales in the Pacific Northwest, USA[J]. Journal of the North American Benthological Society,2004,23(2):340-362
8. Buck S., Denton G., Dodds W., et al. Nutrient Criteria Technical Guidance Manual:Rivers and Streams [Z]. Washington, DC:United States Environmental Protection Agency,2000
9. Butcher R. W. The biological detection of pollution [J]. Journal of the Institute of Sewage Purification,1946,2:92-97.
10. Cade B. S., Terrell J. W.,Schroeder R. L. Estimating effects of limiting factors with regression quantiles[J]. Ecology,1999,80(1):311-323
11. Camargo J. A., Alonso A.,Puente M. Eutrophication downstream from small reservoirs in mountain rivers of Central Spain[J]. Water Research,2005,39(14):3376-3384
12. Chessman B. C. New sensitivity grades for Australian river macroinvertebrates [J]. Marine and Freshwater Research,2003,54(2):95-104.
13. Chessman B. SIGNAL 2-A Scoring System for Macroinvertebrate ('Water Bugs') in Australian Rivers[J]. Monitoring River Health Initiative Technical Report.2003
14. Chutter F. M. An empirical biotic index of the quality of water in South African streams and rivers [J]. Water Research,1972,6(1):19-30
15. Clarke R. T., Wright J. F., Furse M. T. RIVPACS models for predicting the expected macroinvertebrate fauna and assessing the ecological quality of rivers [J]. Ecological Modelling, 2003,160(3):219-233
'16. Cleveland W. S. Robust locally weighted regression and smoothing scatterplots [J]. Journal of the American statistical Association,.1979,74(368):829-836
17. Cook S. Quest for an index of community structure sensitive to water pollution [J]. Environmental Pollution,1976,11(4):269-288
18. CSN. Water quality, biological analysis, determination of saprobic index [S]. Prague, Institute Czech Technical State Standard,1998
19. Davies P. River Health Bioassessment Manual, Version 1.0. National River Processes and Management Program:Monitoring River Health Initiative [M]. Environment Protection Agency: Department of Environment, Sport and Territories, Land and Water Resources Research and Development Corporation, Commonwealth,1994
20. de Pauw N., Gabriels W., Goethals P. River monitoring and assessment methods based on macroinvertebrates[M].In:Biological monitoring of rivers. Applications and Perspectives,G Ziglio, G Siligardi, M Siligardi, United Kingdom, Chichester, West Sussex:John Wiley & Sons,2006,978
21. de Pauw N., Ghetti P. F., Manzini D. P., et al. Biological assessment methods for running water [M]. River Water Quality, Ecological Assessment and Control,1992
22. Dev. Biologischokologische Gewasseruntersuchung:Bestimmung des Saprobien index (M2)[M].In: Deutsches Einheitsverfahren zur Wasser-, Abwasser-and Schlammuntersuchung,VCH: Verlagsgesell-schaft mbH, Weinheim,1992
23. Efron B., Tibshirani R. J. An introduction to the bootstrap [M]. London:Chapman & Hall,1993
24. European U. Directive 2000/60/EC of the European Parliament and of the Council of 23 October 2000 establishing a framework for Community action in the field of water policy[S].2000
25. Friedrich G. Eine revision des Saprobien systems [J]. Zietschrift Fur Wasser-Und-Abwasser-Forschung,1990,23:141-152.
26. Ghetti P. F. Manuale di applicazione:Indice Biotico Esteso (IBE). Ⅰ macroinvertebrati nel controllo della qualit?degli ambienti di acque correnti[J]. Provincia Autonoma di Trento, Agenzia provinciale per la protezione dell ambiente.1997:1-2
27. Goodnight C. J., Whitley L. S. Oligochaetes as indicators of pollution [J]. Wat. & Sewage Wks, 1960,107:311
28. Graca M., Coimbra C. N. The elaboration of indices to assess biological water quality--A case study [J]. Water Research,1998,32(2):380-392
29. Hauer F. R. Methods in stream ecology [M]. Academic Press,2006
30. Heino J., Muotka T., Mykr H., et al. Defining macroinvertebrate assemblage types of headwater streams:implications for bioassessment and conservation [J]. Ecological applications,2003,13(3): 842-852
31. Hering D., Moog O.,Sandin L., et al. Overview and application of the AQEM assessment system [J]. Hydrobiologia,2004,516(1):1-20
32. Hilsenhoff W. L. Use of arthropods to evaluate water quality of streams [J]. Technical Bulletin, 1977,100:1-15
33. Hilsenhoff W. L. Using a biotic index to evaluate water quality in streams [J]. Technical Bulletin, 1982,132:1-2
34. Hilsenhoff W. L. Rapid field assessment of organic pollution with a family-level biotic index [J]. Journal of the North American Benthological Society,1988,7(1):65-68
35. Hilty J., Merenlender A. Faunal indicator taxa selection for monitoring ecosystem health [J]. Biological Conservation,2000,92(2):185-197
36. Hynes H. I960 The biology of polluted waters [M]. Liverpool University Press,1960
37. Alba-Tercedor. J, Sanchez-Ortega A. Un metodo rapido y simple para evaluar la calidad biologica de las aguas corrientes basado en el de Helawell [J]. Limnetica,1988,4:51-56
38. Johnson R. K.,Wiederholm T. Classification and ordination of profundal macroinvertebrate communities in nutrient poor, oligo-mesohumic lakes in relation to environmental data [J]. Freshwater biology,1989,21(3):375-386
39. Johnson R. K., Wiederholm T.,Rosenberg D. M. Freshwater biomonitoring using individual organisms, populations, and species assemblages of benthic macroinvertebrates[J]. CHAPMAN AND HALL, NEW YORK(USA).1993:40-125
40. Kerans B. L., Karr J. R. A benthic index of biotic integrity (B-IBI) for rivers of the Tennessee Valley [J]. Ecological Applications,1994,4(4):768-785
41. King R. S., Richardson C. J. Integrating bioassessment and ecological risk assessment:an approach to developing numerical water-quality criteria [J]. Environmental Management,2003,31(6): 795-809
42. Kolkwitz R., Marsson M. Grundsatze fur die biologische Beurteilung des Wassers nach seiner Flora und Fauna [J]. Mitteilungen der Prufungsanstalt fur Wasserversorgung und Abwasserreinigung, 1902,1:33-72
43. Kolkwitz R., Marsson M. Okologie der pfanzlichen Saprobien. Berichte der Deutschen Botanischen Gesellschaft [J]. Berichte der Deutschen Botanischen Gesellschaft,1908,26(2):505-519
44. Lenat D. R., Crawford J. K. Effects of land use on water quality and aquatic biota of three North Carolina Piedmont streams [J]. Hydrobiologia,1994,294(3):185-199
45. Lenat D. R., Penrose D. L. History of the EPT taxa richness metric [J]. Bulletin of the North American Benthological Society,1996,13(2):305-306
46. Lep J., Milauer P. Multivariate analysis of ecological data using CANOCO [M]. Cambridge University Press,2003.
47. Merritt R. W., Cummins K. W. Trophic relations of macroinvertebrates [M].In:Methods in Stream Ecology,San Diego:Academic Press,1996,453-474.
48. Olive J. H., Dambach C. A. Benthic macroinvertebrates as indexes of water quality in Whetstone Creek, Morrow County, Ohio (Scioto River Basin)[J]. The Ohio Journal of Science,1973,73(3): 129-149
49. ONORM M. Richtlinien fur die okologische Untersuchung und Bewertung von Flieβgewassern[S]. Wien osterreichisches Normungsinstitut,1997
50. Pantle R., Buck H. Die biologische Uberwachung der Gewasser und die Darstellung der Ergebnisse [J]. Gas-und Wasserfach,1955,96(18):604-607.
51. Pauw N., Vanhooren G. Method for biological quality assessment of watercourses in Belgium [J]. Hydrobiologia,1983,100(1):153-168
52. Plafkin J., Barbour M., Porter K., et al. Rapid Bioassessment Protocols for Use in Streams and Rivers:Benthic Macroinvertebrates and Fish[S]. Washington, DC,1989
53. Qian S. S., King R. S., Richardson C. J. Two statistical methods for the detection of environmental thresholds [J]. Ecological Modelling,2003,166(2):87-97
54. Redfield A. C. The biological control of chemical factors in the environment [J]. American Scientist,1958,46(3):205-221
55. Resh V. H. Which group is best? Attributes of different biological assemblages used in freshwater biomonitoring programs [J]. Environmental monitoring and assessment,2008,138(1):131-138
56. Rolauffs P., Stubauer I.,Zahradkova S., et al. Integration of the saprobic system into the European Union Water Framework Directive:case studies in Austria, Germany and Czech Republic[J]. Hydrobiologia,2004,516(1):285-298
57. Rosenberg D. M., Davies I. J., obb D. G., et al. Protocols for measuring biodiversity:benthic macroinvertebrates in fresh waters [M]. Freshwater Institute, Department of Fisheries and Oceans, Winnipeg, Manitoba,1998
58. Ross H. H. The caddis flies, or Trichoptera, of Illinois [J]. Bull,944,111:1-326
59. Roth N. E., Allan J. D., rickson D. L. Landscape influences on stream biotic integrity assessed at multiple spatial scales J]. Landscape Ecology,996,11(3):141-156
60. Sanchez R M., endricks A. C. Life history and secondary production of Cheumatopsyche spp. in a small Appalachian stream with two different land uses on its watershed [J]. Hydrobiologia,997, 354(1):127-139.
61. Slooff W. Benthic macroinvertebrates and water quality assessment:some toxicological considerations [J]. Aquatic toxicology,1983,4(1):73-82
62. Staub R., Appling J. W., ofstetter A. M., et al. The effects of industrial wastes of Memphis and Shelby County on primary planktonic producers [J]. Bioscience,1970,20(16):905-912
63. Wallace J. B., erritt R. W. Filter-feeding ecology of aquatic insects [J]. Annual review of Entomology,1980,25(1):103-132
64. Wang L., Lyons J., Kanehl P., et al. Impacts of urbanization on stream habitat and fish across multiple spatial scales [J]. Environmental Management,2001,28(2):255-266
65. Whiles M. R.,Dodds W. K. Relationships between stream size, suspended particles, and filter-feeding macroinvertebrates in a Great Plains drainage network [J]. Journal of environmental quality,2002,31(5):1589-1600.
66. Wiggins G. B. Larvae of the North American caddisfly genera (trichoptera) [M]. Toronto: University of Toronto Press; 2nd edition,1996
67. Wilhm J. L., Dorris T. C. Biological parameters for water quality criteria [J]. Bioscience,1968, 18(6):477-481
68. Woodiwiss F. S. The biological system of stream classification used by the Trent River Board [J]. Chemistry and industry,1964,14:443-447
69. Wright S., Todd W. M. Summary of limnological investigations in western Lake Erie in 1929 and 1930 [J]. Transactions of the American Fisheries Society,1933,63(1):271-285
70. Zelinka M., Marvan P. Zur Prazisierung der biologischen Klassification der Reinheit fliessender [J]. Arch. Hydrobiol,1961,57(3):389-407
71. Zheng L., Gerritsen J.,Beckman J., et al. Land Use, Geology, Enrichment, And Stream Biota In The Eastern Ridge And Valley Ecoregion:Implications For Nutrient Criteria Development [J]. Journal of the American Water Resources Association,2008,44(6):1521-1536
72.段波,李斌峰,刘若思,等.广东横石水河流域溪流大型底栖动物漂流的昼夜节律[J].应用生态学报,2008,19(5)：1084-1091
73.龚志军,谢平,唐汇涓,等.水体富营养化对大型底栖动物群落结构及多样性的影响[J].水生生物学报,2001,25(3)：210-216
74.国家环保总局《水和废水监测分析方法》编委会. 《水和废水监测分析方法》[M].北京：中国环境科学出版社,2002.
75.郝卫民,王十达,王德铭.洪湖底栖动物群落结构及其对水质的初步评价[J].水生生物学报,1995,19(2)：124-134
76.黄玉瑶,滕德兴.利用大型底栖无脊椎动物种类多样性指数监测蓟运河污染[J].动物学集刊,1982,2：133
77.黄玉瑶,滕德兴,赵忠宪.应用大型无脊椎动物群落结构特征及其多样性指数监测蓟运河污染[J].动物学集刊,1982,2：133-146
78.姜丽红,王备新,陈爱卿.大型底栖无脊椎动物对溪流中三角枫落叶分解的影响[J].应用生态学报,2009,20(5)：1184-1189
79.蒋万祥,蔡庆华,唐涛.香溪河大型底栖无脊椎动物空间分布[J].应用生态学报,2008,19(11)：2443-2448
80.金相灿.中国湖泊环境[M].北京：海洋出版社,1995.
81.李丽娜,陈振楼,许世远,等.长江口滨岸带河蚬的时空分布特征及其指示作用[J].应用生态学报.2006,17(5)：883-886
82.李强,杨莲芳,吴璟,等.西苕溪EPT昆虫群落分布与环境因子的典范对应分析[J].生态学报,2006,26(11)：3817-3825
83.李佑文, Dudgeon D中国短脉纹石蛾属四新种——(毛翅目：纹石蛾科)[J].南京农业大学学报,1988,11(1)：41-45
84.李佑文,田立新,David D纹石蛾六新种记述[J].南京农业大学学报.1990,13(1)：37-42
85.李兆富,杨桂山,李恒鹏.西苕溪典型小流域土地利用对氮素输出的影响[J].中国环境科学,2005,25(6)：678-681
86.罗玉兰,颖徐,忠曹.秦淮河底泥及间隙水氮磷垂直分布及相关性分析[J].农业环境科学学报,2007,26(4)：1245-1249
87.秦伯强,杨柳燕,陈非洲,等.湖泊富营养化发生机制与控制技术及应用[J].科学通报,2006,51：2401-2412
88.任淑智.北京小型湖泊底栖无脊椎动物群落结构特征与营养状况的研究[J].应用生态学报,1991,2：221-225
89.苏华武,江晶,温芳妮,等.湖北清江流域叹气沟河底栖动物群落结构与水质生物学评价[J].湖泊科学,2008,20(4)：403-411
90.童晓立,胡慧建,陈思源.利用水生昆虫评价南昆山溪流的水质[J].华南农业大学学报,1995,16(3)：6-10
91.王备新.大型底栖无脊椎动物水质生物评价研究[博十学位论文].2003.
92.王备新,杨莲芳.用河流生物指数评价秦淮河上游水质的研究[J].生态学报,2003,23(10)：2082-2091
93.王备新,徐东炯,杨莲芳,等.常州地区太湖流域上游水系大型底栖无脊椎动物群落结构特征及其与环境的关系[J].生态与农村环境学报,2007,23(2)：47-51
94.王备新,杨莲芳,胡本进,等.应用底栖动物完整性指数B-IBI评价溪流健康[J].生态学报,2005,25(6)：1481-1490
95.王建国,黄恢柏,杨明旭.利用水生昆虫评价庐山自然保护区主要水体水质状况[J].江西农业大学学报.1995,16(3)：6-10
96.王霞,吕宪国,白淑英,等.松花湖富营养化发生的阈值判定和概率分析[J].生态学报,2006,26：3989-3997.
97.吴东浩,汪军涛,张咏,等.连云港主要河流大型底栖无脊椎动物水质生物评价[J].环境监测管理与技术,2010,1(22)：29-32
98.吴东浩,于海燕,吴海燕,等.基于大型底栖无脊椎动物确定河流营养盐浓度阈值——以西苕溪上游流域为例[J].应用生态学报,2010,21(2)：483-488
99.吴璟,杨莲芳,姜小三,等.浙江西苕溪土地利用变化对溪流大型底栖无脊椎动物完整性的影响[J].生态学报,2008,28(3)：1183-1191
100.吴璟,杨莲芳,李强,等.西苕溪中上游流域水生甲虫分布与环境的关系[J].应用与环境生物学报,2008,14(1)：64-68.
101.熊金林,梅兴国,胡传林.不同污染程度湖泊底栖动物群落结构及多样性比较[J].湖泊科学,2003,15：160-168
102.闫云君,李晓宇.汉江流域黑竹冲河五种优势摇蚊的周年生产量及营养基础分析[J].湖泊科学,2006,19(2)：585-591
103.颜玲,赵颖,韩翠香,等.粤北地区溪流中的树叶分解及大型底栖动物功能摄食群[J].应用生态学报,2007,18：2573-2579
104.杨莲芳,李佑文,戚道光,等.九华河水生昆虫群落结构和水质生物评价[J].生态学报,1992,12：10-17
105.杨明生,熊邦喜,杨学芬.武汉市南湖大型底栖动物的时空分布和氮磷评价[J].湖泊科学,2007,19(6)：658-663
106.袁伟,张志南,于子山.胶州湾西部海域大型底栖动物次级生产力初步研究[J].应用生态学报,2007,18(1)：145-150
107.宗良纲,王艮梅,占新华.南京秦淮河水环境质量现状评价[J].南京农业大学学报,2000,24(S1)：81-83
108.谢志才,张君倩,陈静,等.东洞庭湖保护区大型底栖动物空间分布格局及水质评价[J].湖泊科学,2007,19(3)：289-298
2. Allan J. D. Landscapes and riverscapes:the influence of land use on stream ecosystems[J].2004
3. Armitage P. D., Moss D., Wright J. F., et al. The performance of a new biological water quality score system based on macroin vertebrates over a wide range of unpolluted running-water sites [J]. Water research.1983,17(3):333-347
4. Barbour M. T., Gerritsen J.,Snyder B. D., et al. Rapid bioassessment protocols for use in streams and wadeable rivers:periphyton, benthic macroinvertebrates, and fish[M]. Washington, DC: Environmental Protection Agency, Office of Water,1999
5. Beck Jr W. M. Suggested method for reporting biotic data [J]. Sewage and Industrial Wastes,1955, 27(10):1193-1197
6. Benke A. C., Wallace J. B. Trophic basis of production among net-spinning caddisflies in a southern Appalachian stream [J]. Ecology,1980,61(1):108-118.
7. Black R. W., Munn M. D.,Plotnikoff R. W. Using macroinvertebrates to identify biota land cover optima at multiple scales in the Pacific Northwest, USA[J]. Journal of the North American Benthological Society,2004,23(2):340-362
8. Buck S., Denton G., Dodds W., et al. Nutrient Criteria Technical Guidance Manual:Rivers and Streams [Z]. Washington, DC:United States Environmental Protection Agency,2000
9. Butcher R. W. The biological detection of pollution [J]. Journal of the Institute of Sewage Purification,1946,2:92-97.
10. Cade B. S., Terrell J. W.,Schroeder R. L. Estimating effects of limiting factors with regression quantiles[J]. Ecology,1999,80(1):311-323
11. Camargo J. A., Alonso A.,Puente M. Eutrophication downstream from small reservoirs in mountain rivers of Central Spain[J]. Water Research,2005,39(14):3376-3384
12. Chessman B. C. New sensitivity grades for Australian river macroinvertebrates [J]. Marine and Freshwater Research,2003,54(2):95-104.
13. Chessman B. SIGNAL 2-A Scoring System for Macroinvertebrate ('Water Bugs') in Australian Rivers[J]. Monitoring River Health Initiative Technical Report.2003
14. Chutter F. M. An empirical biotic index of the quality of water in South African streams and rivers [J]. Water Research,1972,6(1):19-30
15. Clarke R. T., Wright J. F., Furse M. T. RIVPACS models for predicting the expected macroinvertebrate fauna and assessing the ecological quality of rivers [J]. Ecological Modelling, 2003,160(3):219-233
'16. Cleveland W. S. Robust locally weighted regression and smoothing scatterplots [J]. Journal of the American statistical Association,.1979,74(368):829-836
17. Cook S. Quest for an index of community structure sensitive to water pollution [J]. Environmental Pollution,1976,11(4):269-288
18. CSN. Water quality, biological analysis, determination of saprobic index [S]. Prague, Institute Czech Technical State Standard,1998
19. Davies P. River Health Bioassessment Manual, Version 1.0. National River Processes and Management Program:Monitoring River Health Initiative [M]. Environment Protection Agency: Department of Environment, Sport and Territories, Land and Water Resources Research and Development Corporation, Commonwealth,1994
20. de Pauw N., Gabriels W., Goethals P. River monitoring and assessment methods based on macroinvertebrates[M].In:Biological monitoring of rivers. Applications and Perspectives,G Ziglio, G Siligardi, M Siligardi, United Kingdom, Chichester, West Sussex:John Wiley & Sons,2006,978
21. de Pauw N., Ghetti P. F., Manzini D. P., et al. Biological assessment methods for running water [M]. River Water Quality, Ecological Assessment and Control,1992
22. Dev. Biologischokologische Gewasseruntersuchung:Bestimmung des Saprobien index (M2)[M].In: Deutsches Einheitsverfahren zur Wasser-, Abwasser-and Schlammuntersuchung,VCH: Verlagsgesell-schaft mbH, Weinheim,1992
23. Efron B., Tibshirani R. J. An introduction to the bootstrap [M]. London:Chapman & Hall,1993
24. European U. Directive 2000/60/EC of the European Parliament and of the Council of 23 October 2000 establishing a framework for Community action in the field of water policy[S].2000
25. Friedrich G. Eine revision des Saprobien systems [J]. Zietschrift Fur Wasser-Und-Abwasser-Forschung,1990,23:141-152.
26. Ghetti P. F. Manuale di applicazione:Indice Biotico Esteso (IBE). Ⅰ macroinvertebrati nel controllo della qualit?degli ambienti di acque correnti[J]. Provincia Autonoma di Trento, Agenzia provinciale per la protezione dell ambiente.1997:1-2
27. Goodnight C. J., Whitley L. S. Oligochaetes as indicators of pollution [J]. Wat. & Sewage Wks, 1960,107:311
28. Graca M., Coimbra C. N. The elaboration of indices to assess biological water quality--A case study [J]. Water Research,1998,32(2):380-392
29. Hauer F. R. Methods in stream ecology [M]. Academic Press,2006
30. Heino J., Muotka T., Mykr H., et al. Defining macroinvertebrate assemblage types of headwater streams:implications for bioassessment and conservation [J]. Ecological applications,2003,13(3): 842-852
31. Hering D., Moog O.,Sandin L., et al. Overview and application of the AQEM assessment system [J]. Hydrobiologia,2004,516(1):1-20
32. Hilsenhoff W. L. Use of arthropods to evaluate water quality of streams [J]. Technical Bulletin, 1977,100:1-15
33. Hilsenhoff W. L. Using a biotic index to evaluate water quality in streams [J]. Technical Bulletin, 1982,132:1-2
34. Hilsenhoff W. L. Rapid field assessment of organic pollution with a family-level biotic index [J]. Journal of the North American Benthological Society,1988,7(1):65-68
35. Hilty J., Merenlender A. Faunal indicator taxa selection for monitoring ecosystem health [J]. Biological Conservation,2000,92(2):185-197
36. Hynes H. I960 The biology of polluted waters [M]. Liverpool University Press,1960
37. Alba-Tercedor. J, Sanchez-Ortega A. Un metodo rapido y simple para evaluar la calidad biologica de las aguas corrientes basado en el de Helawell [J]. Limnetica,1988,4:51-56
38. Johnson R. K.,Wiederholm T. Classification and ordination of profundal macroinvertebrate communities in nutrient poor, oligo-mesohumic lakes in relation to environmental data [J]. Freshwater biology,1989,21(3):375-386
39. Johnson R. K., Wiederholm T.,Rosenberg D. M. Freshwater biomonitoring using individual organisms, populations, and species assemblages of benthic macroinvertebrates[J]. CHAPMAN AND HALL, NEW YORK(USA).1993:40-125
40. Kerans B. L., Karr J. R. A benthic index of biotic integrity (B-IBI) for rivers of the Tennessee Valley [J]. Ecological Applications,1994,4(4):768-785
41. King R. S., Richardson C. J. Integrating bioassessment and ecological risk assessment:an approach to developing numerical water-quality criteria [J]. Environmental Management,2003,31(6): 795-809
42. Kolkwitz R., Marsson M. Grundsatze fur die biologische Beurteilung des Wassers nach seiner Flora und Fauna [J]. Mitteilungen der Prufungsanstalt fur Wasserversorgung und Abwasserreinigung, 1902,1:33-72
43. Kolkwitz R., Marsson M. Okologie der pfanzlichen Saprobien. Berichte der Deutschen Botanischen Gesellschaft [J]. Berichte der Deutschen Botanischen Gesellschaft,1908,26(2):505-519
44. Lenat D. R., Crawford J. K. Effects of land use on water quality and aquatic biota of three North Carolina Piedmont streams [J]. Hydrobiologia,1994,294(3):185-199
45. Lenat D. R., Penrose D. L. History of the EPT taxa richness metric [J]. Bulletin of the North American Benthological Society,1996,13(2):305-306
46. Lep J., Milauer P. Multivariate analysis of ecological data using CANOCO [M]. Cambridge University Press,2003.
47. Merritt R. W., Cummins K. W. Trophic relations of macroinvertebrates [M].In:Methods in Stream Ecology,San Diego:Academic Press,1996,453-474.
48. Olive J. H., Dambach C. A. Benthic macroinvertebrates as indexes of water quality in Whetstone Creek, Morrow County, Ohio (Scioto River Basin)[J]. The Ohio Journal of Science,1973,73(3): 129-149
49. ONORM M. Richtlinien fur die okologische Untersuchung und Bewertung von Flieβgewassern[S]. Wien osterreichisches Normungsinstitut,1997
50. Pantle R., Buck H. Die biologische Uberwachung der Gewasser und die Darstellung der Ergebnisse [J]. Gas-und Wasserfach,1955,96(18):604-607.
51. Pauw N., Vanhooren G. Method for biological quality assessment of watercourses in Belgium [J]. Hydrobiologia,1983,100(1):153-168
52. Plafkin J., Barbour M., Porter K., et al. Rapid Bioassessment Protocols for Use in Streams and Rivers:Benthic Macroinvertebrates and Fish[S]. Washington, DC,1989
53. Qian S. S., King R. S., Richardson C. J. Two statistical methods for the detection of environmental thresholds [J]. Ecological Modelling,2003,166(2):87-97
54. Redfield A. C. The biological control of chemical factors in the environment [J]. American Scientist,1958,46(3):205-221
55. Resh V. H. Which group is best? Attributes of different biological assemblages used in freshwater biomonitoring programs [J]. Environmental monitoring and assessment,2008,138(1):131-138
56. Rolauffs P., Stubauer I.,Zahradkova S., et al. Integration of the saprobic system into the European Union Water Framework Directive:case studies in Austria, Germany and Czech Republic[J]. Hydrobiologia,2004,516(1):285-298
57. Rosenberg D. M., Davies I. J., obb D. G., et al. Protocols for measuring biodiversity:benthic macroinvertebrates in fresh waters [M]. Freshwater Institute, Department of Fisheries and Oceans, Winnipeg, Manitoba,1998
58. Ross H. H. The caddis flies, or Trichoptera, of Illinois [J]. Bull,944,111:1-326
59. Roth N. E., Allan J. D., rickson D. L. Landscape influences on stream biotic integrity assessed at multiple spatial scales J]. Landscape Ecology,996,11(3):141-156
60. Sanchez R M., endricks A. C. Life history and secondary production of Cheumatopsyche spp. in a small Appalachian stream with two different land uses on its watershed [J]. Hydrobiologia,997, 354(1):127-139.
61. Slooff W. Benthic macroinvertebrates and water quality assessment:some toxicological considerations [J]. Aquatic toxicology,1983,4(1):73-82
62. Staub R., Appling J. W., ofstetter A. M., et al. The effects of industrial wastes of Memphis and Shelby County on primary planktonic producers [J]. Bioscience,1970,20(16):905-912
63. Wallace J. B., erritt R. W. Filter-feeding ecology of aquatic insects [J]. Annual review of Entomology,1980,25(1):103-132
64. Wang L., Lyons J., Kanehl P., et al. Impacts of urbanization on stream habitat and fish across multiple spatial scales [J]. Environmental Management,2001,28(2):255-266
65. Whiles M. R.,Dodds W. K. Relationships between stream size, suspended particles, and filter-feeding macroinvertebrates in a Great Plains drainage network [J]. Journal of environmental quality,2002,31(5):1589-1600.
66. Wiggins G. B. Larvae of the North American caddisfly genera (trichoptera) [M]. Toronto: University of Toronto Press; 2nd edition,1996
67. Wilhm J. L., Dorris T. C. Biological parameters for water quality criteria [J]. Bioscience,1968, 18(6):477-481
68. Woodiwiss F. S. The biological system of stream classification used by the Trent River Board [J]. Chemistry and industry,1964,14:443-447
69. Wright S., Todd W. M. Summary of limnological investigations in western Lake Erie in 1929 and 1930 [J]. Transactions of the American Fisheries Society,1933,63(1):271-285
70. Zelinka M., Marvan P. Zur Prazisierung der biologischen Klassification der Reinheit fliessender [J]. Arch. Hydrobiol,1961,57(3):389-407
71. Zheng L., Gerritsen J.,Beckman J., et al. Land Use, Geology, Enrichment, And Stream Biota In The Eastern Ridge And Valley Ecoregion:Implications For Nutrient Criteria Development [J]. Journal of the American Water Resources Association,2008,44(6):1521-1536
72.段波,李斌峰,刘若思,等.广东横石水河流域溪流大型底栖动物漂流的昼夜节律[J].应用生态学报,2008,19(5)：1084-1091
73.龚志军,谢平,唐汇涓,等.水体富营养化对大型底栖动物群落结构及多样性的影响[J].水生生物学报,2001,25(3)：210-216
74.国家环保总局《水和废水监测分析方法》编委会. 《水和废水监测分析方法》[M].北京：中国环境科学出版社,2002.
75.郝卫民,王十达,王德铭.洪湖底栖动物群落结构及其对水质的初步评价[J].水生生物学报,1995,19(2)：124-134
76.黄玉瑶,滕德兴.利用大型底栖无脊椎动物种类多样性指数监测蓟运河污染[J].动物学集刊,1982,2：133
77.黄玉瑶,滕德兴,赵忠宪.应用大型无脊椎动物群落结构特征及其多样性指数监测蓟运河污染[J].动物学集刊,1982,2：133-146
78.姜丽红,王备新,陈爱卿.大型底栖无脊椎动物对溪流中三角枫落叶分解的影响[J].应用生态学报,2009,20(5)：1184-1189
79.蒋万祥,蔡庆华,唐涛.香溪河大型底栖无脊椎动物空间分布[J].应用生态学报,2008,19(11)：2443-2448
80.金相灿.中国湖泊环境[M].北京：海洋出版社,1995.
81.李丽娜,陈振楼,许世远,等.长江口滨岸带河蚬的时空分布特征及其指示作用[J].应用生态学报.2006,17(5)：883-886
82.李强,杨莲芳,吴璟,等.西苕溪EPT昆虫群落分布与环境因子的典范对应分析[J].生态学报,2006,26(11)：3817-3825
83.李佑文, Dudgeon D中国短脉纹石蛾属四新种——(毛翅目：纹石蛾科)[J].南京农业大学学报,1988,11(1)：41-45
84.李佑文,田立新,David D纹石蛾六新种记述[J].南京农业大学学报.1990,13(1)：37-42
85.李兆富,杨桂山,李恒鹏.西苕溪典型小流域土地利用对氮素输出的影响[J].中国环境科学,2005,25(6)：678-681
86.罗玉兰,颖徐,忠曹.秦淮河底泥及间隙水氮磷垂直分布及相关性分析[J].农业环境科学学报,2007,26(4)：1245-1249
87.秦伯强,杨柳燕,陈非洲,等.湖泊富营养化发生机制与控制技术及应用[J].科学通报,2006,51：2401-2412
88.任淑智.北京小型湖泊底栖无脊椎动物群落结构特征与营养状况的研究[J].应用生态学报,1991,2：221-225
89.苏华武,江晶,温芳妮,等.湖北清江流域叹气沟河底栖动物群落结构与水质生物学评价[J].湖泊科学,2008,20(4)：403-411
90.童晓立,胡慧建,陈思源.利用水生昆虫评价南昆山溪流的水质[J].华南农业大学学报,1995,16(3)：6-10
91.王备新.大型底栖无脊椎动物水质生物评价研究[博十学位论文].2003.
92.王备新,杨莲芳.用河流生物指数评价秦淮河上游水质的研究[J].生态学报,2003,23(10)：2082-2091
93.王备新,徐东炯,杨莲芳,等.常州地区太湖流域上游水系大型底栖无脊椎动物群落结构特征及其与环境的关系[J].生态与农村环境学报,2007,23(2)：47-51
94.王备新,杨莲芳,胡本进,等.应用底栖动物完整性指数B-IBI评价溪流健康[J].生态学报,2005,25(6)：1481-1490
95.王建国,黄恢柏,杨明旭.利用水生昆虫评价庐山自然保护区主要水体水质状况[J].江西农业大学学报.1995,16(3)：6-10
96.王霞,吕宪国,白淑英,等.松花湖富营养化发生的阈值判定和概率分析[J].生态学报,2006,26：3989-3997.
97.吴东浩,汪军涛,张咏,等.连云港主要河流大型底栖无脊椎动物水质生物评价[J].环境监测管理与技术,2010,1(22)：29-32
98.吴东浩,于海燕,吴海燕,等.基于大型底栖无脊椎动物确定河流营养盐浓度阈值——以西苕溪上游流域为例[J].应用生态学报,2010,21(2)：483-488
99.吴璟,杨莲芳,姜小三,等.浙江西苕溪土地利用变化对溪流大型底栖无脊椎动物完整性的影响[J].生态学报,2008,28(3)：1183-1191
100.吴璟,杨莲芳,李强,等.西苕溪中上游流域水生甲虫分布与环境的关系[J].应用与环境生物学报,2008,14(1)：64-68.
101.熊金林,梅兴国,胡传林.不同污染程度湖泊底栖动物群落结构及多样性比较[J].湖泊科学,2003,15：160-168
102.闫云君,李晓宇.汉江流域黑竹冲河五种优势摇蚊的周年生产量及营养基础分析[J].湖泊科学,2006,19(2)：585-591
103.颜玲,赵颖,韩翠香,等.粤北地区溪流中的树叶分解及大型底栖动物功能摄食群[J].应用生态学报,2007,18：2573-2579
104.杨莲芳,李佑文,戚道光,等.九华河水生昆虫群落结构和水质生物评价[J].生态学报,1992,12：10-17
105.杨明生,熊邦喜,杨学芬.武汉市南湖大型底栖动物的时空分布和氮磷评价[J].湖泊科学,2007,19(6)：658-663
106.袁伟,张志南,于子山.胶州湾西部海域大型底栖动物次级生产力初步研究[J].应用生态学报,2007,18(1)：145-150
107.宗良纲,王艮梅,占新华.南京秦淮河水环境质量现状评价[J].南京农业大学学报,2000,24(S1)：81-83
108.谢志才,张君倩,陈静,等.东洞庭湖保护区大型底栖动物空间分布格局及水质评价[J].湖泊科学,2007,19(3)：289-298