A Macroinvertebrate Multimetric Index for the Bioassessment of Wet-lands Adjacent to Agriculture Fields in the Sanjiang Plain, China

WU Haitao; LU Kangle; LYU Xianguo; XUE Zhenshan

doi:10.1007/s11769-019-1083-6

Volume 29 Issue 6

Dec. 2019

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Article Navigation > Chinese Geographical Science > 2019 > 29(6): 974-984

WU Haitao, LU Kangle, LYU Xianguo, XUE Zhenshan. A Macroinvertebrate Multimetric Index for the Bioassessment of Wet-lands Adjacent to Agriculture Fields in the Sanjiang Plain, China[J]. Chinese Geographical Science, 2019, 29(6): 974-984. doi: 10.1007/s11769-019-1083-6

Citation:

WU Haitao, LU Kangle, LYU Xianguo, XUE Zhenshan. A Macroinvertebrate Multimetric Index for the Bioassessment of Wet-lands Adjacent to Agriculture Fields in the Sanjiang Plain, China[J]. Chinese Geographical Science, 2019, 29(6): 974-984. doi: 10.1007/s11769-019-1083-6

A Macroinvertebrate Multimetric Index for the Bioassessment of Wet-lands Adjacent to Agriculture Fields in the Sanjiang Plain, China

doi: 10.1007/s11769-019-1083-6

1. Key Laboratory of Wetland Ecology and Environment, Northeast Institute of Geography and Agroecology, Chinese Academy of Sci-ences, Changchun 130102, China;
2. University of Chinese Academy of Sciences, Beijing 100049, China

Funds:

Under the auspices of National Key Research and Development Project of China (No. 2016YFC0500408), National Natural Science Foundation of China (No. 41871099, 41671260), Science and Technology Development Program of Jilin Province (No. 20180101080JC)

Received Date: 2018-12-06
Publish Date: 2019-12-01

Abstract

Adjacent intensive agriculture disturbs the natural condition of wetlands. However, to assess the effect of this agriculture on wetlands, few studies have used indices based on aquatic invertebrates. Multi-metric indices (MMIs) have been successfully used to assess freshwater ecosystems worldwide and are an important management tool, but little is known about their applicability in the Sanjiang Plain, Northeast China. In this study, we developed a MMIs for aquatic invertebrates to assess freshwater wetlands in this region. The aquatic invertebrate assemblages were sampled in 27 wetlands in the Sanjiang Plain that included those in natural reserves and those affected by adjacent, intensive agriculture. Twenty-four candidate metrics were initially reviewed and screened before four core metrics were selected:total number of taxa, number of Hemiptera taxa, proportion of Gastropoda, and proportion of predators. Mann-Whitney U tests, Box and Whisker plots, correlation analyses, and redundant metric tests were used to assess the ability of metrics to distinguish among reference and impaired wetlands. Four ordinal rating categories for wetland were defined:poor, fair, good, and excellent. Of the impaired freshwater wetlands, 76.2% were in poor or fair categories. The MMIs was robust in discriminating reference wetlands from impaired wetlands and therefore have potential as a biomonitoring tool to assess the condition and to guide the restoration efforts of freshwater wetlands in Northeast China.
- bio-assessment,
- Hemiptera,
- Mollusca,
- multi-metric indices (MIS),
- bioassessment of wetland,
- the Sanjiang Plain

References

[1]	Baptista D F, Buss D F, Egler M et al., 2007. A multimetric index based on benthic macroinvertebrates for evaluation of Atlantic Forest streams at Rio de Janeiro State, Brazil. Hydrobiologia, 575(1):83-94. doi: 10.1007/s10750-006-0286-x
[2]	Barbour M T, Stribling J B, Karr J R, 1995. The multimetric ap-proach for establishing biocriteria and measuring biological condition. In:Davis W S, Simon T P (eds). Biological Assess-ment and Criteria:Tools for Water Resource Planning and Decision Making. Boca Raton, London:Lewis Publishers, 63-76.
[3]	Barbour M T, Gerritsen J, Griffith G E et al., 1996. A framework for biological criteria for Florida streams using benthic ma-croinvertebrates. Journal of the North American Benthological Society, 15(2):185-211. doi: 10.2307/1467948
[4]	Batzer D P, Shurtleff A S, Rader R B, 2001. Sampling inverte-brates in wetlands. In:Rader R B, Batzer D P, Wissinger S A (eds). Bioassessment and Management of North American Freshwater Wetlands. New York:John Wiley and Sons, 339-354.
[5]	Bonada N, Prat N, Resh V H et al., 2006. Developments in aquatic insect biomonitoring:a comparative analysis of recent ap-proaches. Annual Review of Entomology, 51(1):495-523. doi: 10.1146/annurev.ento.51.110104.151124
[6]	Bullock A, Acreman M, 2003. The role of wetlands in the hydro-logical cycle. Hydrology and Earth System Sciences, 7(3):358-389. doi: 10.5194/hess-7-358-2003
[7]	Clifford H F, 1991. Aquatic Invertebrates of Alberta. Alberta:The University of Alberta Press.
[8]	Couceiro S R M, Hamada N, Forsberg B R et al., 2012. A ma-croinvertebrate multimetric index to evaluate the biological condition of streams in the Central Amazon region of Brazil. Ecological Indicators, 18:118-125. doi:10.1016/j.ecolind. 2011.11.001
[9]	De Bikuña B G, López E, Leonardo J M et al., 2015. Development of a multimetric benthic macroinvertebrate index for assessing the ecological condition of Basque streams (North of Spain). Fundamental and Applied Limnology, 187(1):21-32. doi: 10.1127/fal/2015/0741
[10]	Ferreira W R, Paiva L T, Callisto M, 2011. Development of a benthic multimetric index for biomonitoring of a neotropical watershed. Brazilian Journal of Biology, 71(1):15-25. doi: 10.1590/S1519-69842011000100005
[11]	Fierro P, Arismendi I, Hughes R M et al., 2018. A benthic ma-croinvertebrate multimetric index for Chilean Mediterranean streams. Ecological Indicators, 91:13-23. doi: 10.1016/j.ecolind.2018.03.074
[12]	Fu Bojie, Liu Guohua, Chen Liding et al., 2001. Scheme of eco-logical regionalization in China. Acta Ecologica Sinica, 21(1):1-6. (in Chinese)
[13]	Hawkins C P, Norris R H, Gerritsen J et al., 2000. Evaluation of the use of landscape classifications for the prediction of freshwater biota:synthesis and recommendations. Journal of the North American Benthological Society, 19(3):541-556. doi: 10.2307/1468113
[14]	Hering D, Feld C K, Moog O et al., 2006. Cook book for the de-velopment of a multimetric index for biological condition of aquatic ecosystems:experiences from the European AQEM and STAR projects and related initiatives. Hydrobiologia, 566(1):311-324. doi: 10.1007/s10750-006-0087-2
[15]	Huang Q, Gao J F, Cai Y J et al., 2015. Development and applica-tion of benthic macroinvertebrate-based multimetric indices for the assessment of streams and rivers in the taihu basin, China. Ecological Indicators, 48:649-659. doi: 10.1016/j.ecolind.2014.09.014
[16]	Hughes R M, 1995. Defining acceptable biological status by comparing with reference conditions. In:Davis W S, Simon T P (eds). Biological Assessment and Criteria:Tools for Water Resource Planning and Decision Making. Boca Raton, FL:Lewis Publishers, 31-47.
[17]	Hughes R M, Howlin S, Kaufmann P R, 2004. A biointegrity index (IBI) for coldwater streams of Western Oregon and Washington. Transactions of the American Fisheries Society, 133(6):1497-1515. doi: 10.1577/T03-146.1
[18]	Kerans B L, Karr J R, 1994. A benthic index of biotic integrity (B-IBI) for rivers of the tennessee valley. Ecological Applica-tions, 4(4):768-785. doi: 10.2307/1942007
[19]	Leung A S L, Dudgeon D, 2011. Scales of spatiotemporal varia-bility in macroinvertebrate abundance and diversity in mon-soonal streams:detecting environmental change. Freshwater Biological, 56(6):1193-1208. doi: 10.1111/j.1365-2427.2010.02556.x
[20]	Ligeiro R, Hughes R M, Kaufmann P R et al., 2013. Defining quantitative stream disturbance gradients and the additive role of habitat variation to explain macroinvertebrate taxa richness. Ecological Indicators, 25:45-57. doi:10.1016/j.ecolind. 2012.09.004
[21]	Liu Xingtu, Ma Xuehui, 2002. Natural Environmental Changes and Ecological Protection in the Sanjiang Plain. Beijing:Sci-ence Press. (in Chinese)
[22]	Lu K L, Wu H T, Xue Z S et al., 2019. Development of a mul-ti-metric index based on aquatic invertebrates to assess flood-plain wetland condition. Hydrobiologia, 827(1):141-153. doi: 10.1007/s10750-018-3761-2
[23]	Mereta S T, Boets P, De Meester L et al., 2013. Development of a multimetric index based on benthic macroinvertebrates for the assessment of natural wetlands in Southwest Ethiopia. Eco-logical Indicators, 29:510-521. doi: 10.1016/j.ecolind.2013.01.026
[24]	Milošević D, Čerba D, Szekeres J et al., 2016. Artificial neural networks as an indicator search engine:the visualization of natural and man-caused taxa variability. Ecological Indicators, 61:777-789. doi: 10.1016/j.ecolind.2015.10.029
[25]	Mitsch W J, Gosselink J G, 2007. Wetlands. 4th ed. New York:John Wiley and Sons, Inc.
[26]	Morse J C, Yang L F, Tian L X, 1994. Aquatic Insects of China Useful for Monitoring Water Quality. Nanjing:HoHai Univer-sity Press.
[27]	Ntislidou C, Lazaridou M, Tsiaoussi V et al., 2018. A new multi-metric macroinvertebrate index for the ecological assessment of Mediterranean lakes. Ecological Indicators, 93:1020-1033. doi: 10.1016/j.ecolind.2018.05.071
[28]	O'Brien A, Townsend K, Hale R et al., 2016. How is ecosystem health defined and measured? A critical review of freshwater and estuarine studies. Ecological Indicators, 69:722-729. doi: 10.1016/j.ecolind.2016.05.004
[29]	Odountan O H, De Bisthoven L J, Abou Y et al., 2019. Biomoni-toring of lakes using macroinvertebrates:recommended indices and metrics for use in West Africa and developing countries. Hydrobiologia, 826(1):1-23. doi: 10.1007/s10750-018-3745-2
[30]	Omernik J M, 1995. Ecoregions:a spatial framework for envi-ronmental management. In:Davis W S, Simon T P (eds). Bio-logical Assessment and Criteria:Tools for Water Resource Planning and Decision Making. Boca Raton, FL:Lewis Pub-lishers, 49-62.
[31]	Riato L, Leira M, Della Bella V et al., 2018. Development of a diatom-based multimetric index for acid mine drainage impacted depressional wetlands. Science of the Total Environment, 612:214-222. doi: 10.1016/j.scitotenv.2017.08.181
[32]	Rydin H, Jeglum J K, 2013. The Biology of Peatlands. 2nd ed. Oxford:Oxford University Press.
[33]	Shi X, Liu J L, You X G et al., 2017. Evaluation of river habitat integrity based on benthic macroinvertebrate-based multi-metric model. Ecological Modelling, 353:63-76. doi: 10.1016/j.ecolmodel.2016.07.001
[34]	Šidagytė E, Višinskienė G, Arbačiauskas K, 2013. Macroinverte-brate metrics and their integration for assessing the ecological status and biocontamination of Lithuanian lakes. Limnologica, 43(4):308-318. doi: 10.1016/j.limno.2013.01.003
[35]	Song K S, Wang Z M, Du J et al., 2014. Wetland degradation:its driving forces and environmental impacts in the Sanjiang Plain, China. Environmental Management, 54(2):255-271. doi: 10.1007/s00267-014-0278-y
[36]	Stoddard J L, Larsen D P, Hawkins C P et al., 2006. Setting ex-pectations for the ecological condition of streams:the concept of reference condition. Ecological Applications, 16(4):1267-1276. doi:10.1890/1051-0761(2006)016[1267:SEFTEC]2.0. CO;2
[37]	Stoddard J L, Herlihy A T, Peck D V et al., 2008. A process for creating multimetric indices for large-scale aquatic surveys. Journal of the North American Benthological Society, 27(4):878-891. doi: 10.1899/08-053.1
[38]	Vander Laan J J, 2012. Environmental Assessment of Streams:Linking Land Use, Instream Stressors, and Biological Indices to Infer Likely Causes of Ecological Impairment. Logan, Utah:Utah State University.
[39]	Verhoeven J T A, Arheimer B, Yin C Q et al., 2006. Regional and global concerns over wetlands and water quality. Trends in Ecology & Evolution, 21(2):96-103. doi: 10.1016/j.tree.2005.11.015
[40]	Wang Li, Song Changchun, Hu Jinming et al., 2010. Response of regeneration diversity of Carex Lasiocarpa community to dif-ferent water levels in Sanjiang Plain, China. Chinese Geo-graphical Science, 20(1):37-42. doi: 10.1007/s11769-010-0037-9
[41]	Wang Z M, Song K S, Ma W H et al., 2011. Loss and fragmenta-tion of marshes in the Sanjiang plain, Northeast China, 1954-2005. Wetlands, 31(5):945-954. doi: 10.1007/s13157-011-0209-0
[42]	Weilhoefer C L, 2011. A review of indicators of estuarine tidal wetland condition. Ecological Indicators, 11(2):514-525. doi: 10.1016/j.ecolind.2010.07.007
[43]	Whittier T R, Stoddard J L, Larsen D P et al., 2007. Selecting reference sites for stream biological assessments:best profes-sional judgment or objective criteria. Journal of the North American Benthological Society, 26(2):349-360. doi: 10.1899/0887-3593(2007)26[349:SRSFSB]2.0.CO;2
[44]	Williams M R, Filoso S, Longstaff B J et al., 2010. Long-term trends of water quality and biotic metrics in Chesapeake Bay:1986-2008. Estuaries and Coasts, 33(6):1279-1299. doi: 10.1007/s12237-010-9333-y
[45]	Wu Haitao, Lu Xianguo, Jiang Ming et al., 2009. Impacts of soil fauna on litter decomposition at different succession stages of wetland in Sanjiang Plain, China. Chinese Geographical Sci-ence, 19(3):258-264. doi: 10.1007/s11769-009-0258-y
[46]	Wu H T, Lu X G, Wu D H et al., 2010. Biogenic structures of two ant species Formica sanguinea and Lasius flavus altered soil C, N and P distribution in a meadow wetland of the Sanjiang Plain, China. Applied Soil Ecology, 46(3):321-328. doi: 10.1016/j.apsoil.2010.10.011
[47]	Wu H T, Guan Q, Lu X G et al., 2017. Snail (Mollusca:Gastrop-oda) assemblages as indicators of ecological condition in freshwater wetlands of Northeastern China. Ecological Indi-cators, 75:203-209. doi: 10.1016/j.ecolind.2016.12.042

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A Macroinvertebrate Multimetric Index for the Bioassessment of Wet-lands Adjacent to Agriculture Fields in the Sanjiang Plain, China

1. Key Laboratory of Wetland Ecology and Environment, Northeast Institute of Geography and Agroecology, Chinese Academy of Sci-ences, Changchun 130102, China;

2. University of Chinese Academy of Sciences, Beijing 100049, China

Funds:

Received Date: 2018-12-06

Publish Date: 2019-12-01

Key words:

Abstract: Adjacent intensive agriculture disturbs the natural condition of wetlands. However, to assess the effect of this agriculture on wetlands, few studies have used indices based on aquatic invertebrates. Multi-metric indices (MMIs) have been successfully used to assess freshwater ecosystems worldwide and are an important management tool, but little is known about their applicability in the Sanjiang Plain, Northeast China. In this study, we developed a MMIs for aquatic invertebrates to assess freshwater wetlands in this region. The aquatic invertebrate assemblages were sampled in 27 wetlands in the Sanjiang Plain that included those in natural reserves and those affected by adjacent, intensive agriculture. Twenty-four candidate metrics were initially reviewed and screened before four core metrics were selected:total number of taxa, number of Hemiptera taxa, proportion of Gastropoda, and proportion of predators. Mann-Whitney U tests, Box and Whisker plots, correlation analyses, and redundant metric tests were used to assess the ability of metrics to distinguish among reference and impaired wetlands. Four ordinal rating categories for wetland were defined:poor, fair, good, and excellent. Of the impaired freshwater wetlands, 76.2% were in poor or fair categories. The MMIs was robust in discriminating reference wetlands from impaired wetlands and therefore have potential as a biomonitoring tool to assess the condition and to guide the restoration efforts of freshwater wetlands in Northeast China.

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Reference (47)

[1]	Baptista D F, Buss D F, Egler M et al., 2007. A multimetric index based on benthic macroinvertebrates for evaluation of Atlantic Forest streams at Rio de Janeiro State, Brazil. Hydrobiologia, 575(1):83-94. doi:10.1007/s10750-006-0286-x
[2]	Barbour M T, Stribling J B, Karr J R, 1995. The multimetric ap-proach for establishing biocriteria and measuring biological condition. In:Davis W S, Simon T P (eds). Biological Assess-ment and Criteria:Tools for Water Resource Planning and Decision Making. Boca Raton, London:Lewis Publishers, 63-76.
[3]	Barbour M T, Gerritsen J, Griffith G E et al., 1996. A framework for biological criteria for Florida streams using benthic ma-croinvertebrates. Journal of the North American Benthological Society, 15(2):185-211. doi:10.2307/1467948
[4]	Batzer D P, Shurtleff A S, Rader R B, 2001. Sampling inverte-brates in wetlands. In:Rader R B, Batzer D P, Wissinger S A (eds). Bioassessment and Management of North American Freshwater Wetlands. New York:John Wiley and Sons, 339-354.
[5]	Bonada N, Prat N, Resh V H et al., 2006. Developments in aquatic insect biomonitoring:a comparative analysis of recent ap-proaches. Annual Review of Entomology, 51(1):495-523. doi:10.1146/annurev.ento.51.110104.151124
[6]	Bullock A, Acreman M, 2003. The role of wetlands in the hydro-logical cycle. Hydrology and Earth System Sciences, 7(3):358-389. doi:10.5194/hess-7-358-2003
[7]	Clifford H F, 1991. Aquatic Invertebrates of Alberta. Alberta:The University of Alberta Press.
[8]	Couceiro S R M, Hamada N, Forsberg B R et al., 2012. A ma-croinvertebrate multimetric index to evaluate the biological condition of streams in the Central Amazon region of Brazil. Ecological Indicators, 18:118-125. doi:10.1016/j.ecolind. 2011.11.001
[9]	De Bikuña B G, López E, Leonardo J M et al., 2015. Development of a multimetric benthic macroinvertebrate index for assessing the ecological condition of Basque streams (North of Spain). Fundamental and Applied Limnology, 187(1):21-32. doi:10.1127/fal/2015/0741
[10]	Ferreira W R, Paiva L T, Callisto M, 2011. Development of a benthic multimetric index for biomonitoring of a neotropical watershed. Brazilian Journal of Biology, 71(1):15-25. doi:10.1590/S1519-69842011000100005
[11]	Fierro P, Arismendi I, Hughes R M et al., 2018. A benthic ma-croinvertebrate multimetric index for Chilean Mediterranean streams. Ecological Indicators, 91:13-23. doi:10.1016/j.ecolind.2018.03.074
[12]	Fu Bojie, Liu Guohua, Chen Liding et al., 2001. Scheme of eco-logical regionalization in China. Acta Ecologica Sinica, 21(1):1-6. (in Chinese)
[13]	Hawkins C P, Norris R H, Gerritsen J et al., 2000. Evaluation of the use of landscape classifications for the prediction of freshwater biota:synthesis and recommendations. Journal of the North American Benthological Society, 19(3):541-556. doi:10.2307/1468113
[14]	Hering D, Feld C K, Moog O et al., 2006. Cook book for the de-velopment of a multimetric index for biological condition of aquatic ecosystems:experiences from the European AQEM and STAR projects and related initiatives. Hydrobiologia, 566(1):311-324. doi:10.1007/s10750-006-0087-2
[15]	Huang Q, Gao J F, Cai Y J et al., 2015. Development and applica-tion of benthic macroinvertebrate-based multimetric indices for the assessment of streams and rivers in the taihu basin, China. Ecological Indicators, 48:649-659. doi:10.1016/j.ecolind.2014.09.014
[16]	Hughes R M, 1995. Defining acceptable biological status by comparing with reference conditions. In:Davis W S, Simon T P (eds). Biological Assessment and Criteria:Tools for Water Resource Planning and Decision Making. Boca Raton, FL:Lewis Publishers, 31-47.
[17]	Hughes R M, Howlin S, Kaufmann P R, 2004. A biointegrity index (IBI) for coldwater streams of Western Oregon and Washington. Transactions of the American Fisheries Society, 133(6):1497-1515. doi:10.1577/T03-146.1
[18]	Kerans B L, Karr J R, 1994. A benthic index of biotic integrity (B-IBI) for rivers of the tennessee valley. Ecological Applica-tions, 4(4):768-785. doi:10.2307/1942007
[19]	Leung A S L, Dudgeon D, 2011. Scales of spatiotemporal varia-bility in macroinvertebrate abundance and diversity in mon-soonal streams:detecting environmental change. Freshwater Biological, 56(6):1193-1208. doi:10.1111/j.1365-2427.2010.02556.x
[20]	Ligeiro R, Hughes R M, Kaufmann P R et al., 2013. Defining quantitative stream disturbance gradients and the additive role of habitat variation to explain macroinvertebrate taxa richness. Ecological Indicators, 25:45-57. doi:10.1016/j.ecolind. 2012.09.004
[21]	Liu Xingtu, Ma Xuehui, 2002. Natural Environmental Changes and Ecological Protection in the Sanjiang Plain. Beijing:Sci-ence Press. (in Chinese)
[22]	Lu K L, Wu H T, Xue Z S et al., 2019. Development of a mul-ti-metric index based on aquatic invertebrates to assess flood-plain wetland condition. Hydrobiologia, 827(1):141-153. doi:10.1007/s10750-018-3761-2
[23]	Mereta S T, Boets P, De Meester L et al., 2013. Development of a multimetric index based on benthic macroinvertebrates for the assessment of natural wetlands in Southwest Ethiopia. Eco-logical Indicators, 29:510-521. doi:10.1016/j.ecolind.2013.01.026
[24]	Milošević D, Čerba D, Szekeres J et al., 2016. Artificial neural networks as an indicator search engine:the visualization of natural and man-caused taxa variability. Ecological Indicators, 61:777-789. doi:10.1016/j.ecolind.2015.10.029
[25]	Mitsch W J, Gosselink J G, 2007. Wetlands. 4th ed. New York:John Wiley and Sons, Inc.
[26]	Morse J C, Yang L F, Tian L X, 1994. Aquatic Insects of China Useful for Monitoring Water Quality. Nanjing:HoHai Univer-sity Press.
[27]	Ntislidou C, Lazaridou M, Tsiaoussi V et al., 2018. A new multi-metric macroinvertebrate index for the ecological assessment of Mediterranean lakes. Ecological Indicators, 93:1020-1033. doi:10.1016/j.ecolind.2018.05.071
[28]	O'Brien A, Townsend K, Hale R et al., 2016. How is ecosystem health defined and measured? A critical review of freshwater and estuarine studies. Ecological Indicators, 69:722-729. doi:10.1016/j.ecolind.2016.05.004
[29]	Odountan O H, De Bisthoven L J, Abou Y et al., 2019. Biomoni-toring of lakes using macroinvertebrates:recommended indices and metrics for use in West Africa and developing countries. Hydrobiologia, 826(1):1-23. doi:10.1007/s10750-018-3745-2
[30]	Omernik J M, 1995. Ecoregions:a spatial framework for envi-ronmental management. In:Davis W S, Simon T P (eds). Bio-logical Assessment and Criteria:Tools for Water Resource Planning and Decision Making. Boca Raton, FL:Lewis Pub-lishers, 49-62.
[31]	Riato L, Leira M, Della Bella V et al., 2018. Development of a diatom-based multimetric index for acid mine drainage impacted depressional wetlands. Science of the Total Environment, 612:214-222. doi:10.1016/j.scitotenv.2017.08.181
[32]	Rydin H, Jeglum J K, 2013. The Biology of Peatlands. 2nd ed. Oxford:Oxford University Press.
[33]	Shi X, Liu J L, You X G et al., 2017. Evaluation of river habitat integrity based on benthic macroinvertebrate-based multi-metric model. Ecological Modelling, 353:63-76. doi:10.1016/j.ecolmodel.2016.07.001
[34]	Šidagytė E, Višinskienė G, Arbačiauskas K, 2013. Macroinverte-brate metrics and their integration for assessing the ecological status and biocontamination of Lithuanian lakes. Limnologica, 43(4):308-318. doi:10.1016/j.limno.2013.01.003
[35]	Song K S, Wang Z M, Du J et al., 2014. Wetland degradation:its driving forces and environmental impacts in the Sanjiang Plain, China. Environmental Management, 54(2):255-271. doi:10.1007/s00267-014-0278-y
[36]	Stoddard J L, Larsen D P, Hawkins C P et al., 2006. Setting ex-pectations for the ecological condition of streams:the concept of reference condition. Ecological Applications, 16(4):1267-1276. doi:10.1890/1051-0761(2006)016[1267:SEFTEC]2.0. CO;2
[37]	Stoddard J L, Herlihy A T, Peck D V et al., 2008. A process for creating multimetric indices for large-scale aquatic surveys. Journal of the North American Benthological Society, 27(4):878-891. doi:10.1899/08-053.1
[38]	Vander Laan J J, 2012. Environmental Assessment of Streams:Linking Land Use, Instream Stressors, and Biological Indices to Infer Likely Causes of Ecological Impairment. Logan, Utah:Utah State University.
[39]	Verhoeven J T A, Arheimer B, Yin C Q et al., 2006. Regional and global concerns over wetlands and water quality. Trends in Ecology & Evolution, 21(2):96-103. doi:10.1016/j.tree.2005.11.015
[40]	Wang Li, Song Changchun, Hu Jinming et al., 2010. Response of regeneration diversity of Carex Lasiocarpa community to dif-ferent water levels in Sanjiang Plain, China. Chinese Geo-graphical Science, 20(1):37-42. doi:10.1007/s11769-010-0037-9
[41]	Wang Z M, Song K S, Ma W H et al., 2011. Loss and fragmenta-tion of marshes in the Sanjiang plain, Northeast China, 1954-2005. Wetlands, 31(5):945-954. doi:10.1007/s13157-011-0209-0
[42]	Weilhoefer C L, 2011. A review of indicators of estuarine tidal wetland condition. Ecological Indicators, 11(2):514-525. doi:10.1016/j.ecolind.2010.07.007
[43]	Whittier T R, Stoddard J L, Larsen D P et al., 2007. Selecting reference sites for stream biological assessments:best profes-sional judgment or objective criteria. Journal of the North American Benthological Society, 26(2):349-360. doi:10.1899/0887-3593(2007)26[349:SRSFSB]2.0.CO;2
[44]	Williams M R, Filoso S, Longstaff B J et al., 2010. Long-term trends of water quality and biotic metrics in Chesapeake Bay:1986-2008. Estuaries and Coasts, 33(6):1279-1299. doi:10.1007/s12237-010-9333-y
[45]	Wu Haitao, Lu Xianguo, Jiang Ming et al., 2009. Impacts of soil fauna on litter decomposition at different succession stages of wetland in Sanjiang Plain, China. Chinese Geographical Sci-ence, 19(3):258-264. doi:10.1007/s11769-009-0258-y
[46]	Wu H T, Lu X G, Wu D H et al., 2010. Biogenic structures of two ant species Formica sanguinea and Lasius flavus altered soil C, N and P distribution in a meadow wetland of the Sanjiang Plain, China. Applied Soil Ecology, 46(3):321-328. doi:10.1016/j.apsoil.2010.10.011
[47]	Wu H T, Guan Q, Lu X G et al., 2017. Snail (Mollusca:Gastrop-oda) assemblages as indicators of ecological condition in freshwater wetlands of Northeastern China. Ecological Indi-cators, 75:203-209. doi:10.1016/j.ecolind.2016.12.042

A Macroinvertebrate Multimetric Index for the Bioassessment of Wet-lands Adjacent to Agriculture Fields in the Sanjiang Plain, China

doi: 10.1007/s11769-019-1083-6

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通讯作者: 陈斌, bchen63@163.com

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