A subfossil chironomid-total phosphorus inference model for lakes in the middle and lower reaches of the Yangtze River

E. Zhang, A. Bedford, R. Janes, J. Shen

Research output: Contribution to journalArticle

23 Citations (Scopus)

Abstract

The results of an investigation into the relationship between surface sediment subfossil chironomid distribution and water quality are presented. Data from 30 lakes in the middle and lower reaches of the Yangtze River indicate that the nutrient gradient was the major factor affecting the distribution of chironomids across these sites. Canonical correspondence analysis (CCA) revealed that of 12 summer water environmental variables, total Phosphorus was most important, accounting for 20.1% of the variance in the chironomid data. This was significant enough to allow the development of quantitative inference models. A TP inference model was developed using weighted averaging (WA), partial least squares (PLS) and weighted averaging partial least squares (WA-PLS). An optimal two-component WA-PLS model provided a high jack-knifed coefficient of prediction for conductivity r 2 jack = 0.76, with a low root mean squared error of prediction (RMSEPjack = 0.13). Using this model it is possible to produce long-term quantitative records of past water quality for lacustrine sites across the middle and lower reaches of the Yangtze River, which has important implications for future lake management and ecological restoration.
Original languageEnglish
Pages (from-to)2125-2132
JournalChinese Science Bulletin (csb)
Volume51
Issue number17
DOIs
Publication statusPublished - 2006

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subfossil
phosphorus
lake
river
water quality
prediction
correspondence analysis
conductivity
nutrient
summer
sediment
water
distribution

Cite this

@article{a8f1e9c89218479bbe99e682c3ecc675,
title = "A subfossil chironomid-total phosphorus inference model for lakes in the middle and lower reaches of the Yangtze River",
abstract = "The results of an investigation into the relationship between surface sediment subfossil chironomid distribution and water quality are presented. Data from 30 lakes in the middle and lower reaches of the Yangtze River indicate that the nutrient gradient was the major factor affecting the distribution of chironomids across these sites. Canonical correspondence analysis (CCA) revealed that of 12 summer water environmental variables, total Phosphorus was most important, accounting for 20.1{\%} of the variance in the chironomid data. This was significant enough to allow the development of quantitative inference models. A TP inference model was developed using weighted averaging (WA), partial least squares (PLS) and weighted averaging partial least squares (WA-PLS). An optimal two-component WA-PLS model provided a high jack-knifed coefficient of prediction for conductivity r 2 jack = 0.76, with a low root mean squared error of prediction (RMSEPjack = 0.13). Using this model it is possible to produce long-term quantitative records of past water quality for lacustrine sites across the middle and lower reaches of the Yangtze River, which has important implications for future lake management and ecological restoration.",
author = "E. Zhang and A. Bedford and R. Janes and J. Shen",
year = "2006",
doi = "10.1007/s11434-006-2062-8",
language = "English",
volume = "51",
pages = "2125--2132",
journal = "Chinese Science Bulletin",
issn = "1001-6538",
publisher = "World Scientific Publishing",
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}

A subfossil chironomid-total phosphorus inference model for lakes in the middle and lower reaches of the Yangtze River. / Zhang, E.; Bedford, A.; Janes, R.; Shen, J.

In: Chinese Science Bulletin (csb), Vol. 51, No. 17, 2006, p. 2125-2132.

Research output: Contribution to journalArticle

TY - JOUR

T1 - A subfossil chironomid-total phosphorus inference model for lakes in the middle and lower reaches of the Yangtze River

AU - Zhang, E.

AU - Bedford, A.

AU - Janes, R.

AU - Shen, J.

PY - 2006

Y1 - 2006

N2 - The results of an investigation into the relationship between surface sediment subfossil chironomid distribution and water quality are presented. Data from 30 lakes in the middle and lower reaches of the Yangtze River indicate that the nutrient gradient was the major factor affecting the distribution of chironomids across these sites. Canonical correspondence analysis (CCA) revealed that of 12 summer water environmental variables, total Phosphorus was most important, accounting for 20.1% of the variance in the chironomid data. This was significant enough to allow the development of quantitative inference models. A TP inference model was developed using weighted averaging (WA), partial least squares (PLS) and weighted averaging partial least squares (WA-PLS). An optimal two-component WA-PLS model provided a high jack-knifed coefficient of prediction for conductivity r 2 jack = 0.76, with a low root mean squared error of prediction (RMSEPjack = 0.13). Using this model it is possible to produce long-term quantitative records of past water quality for lacustrine sites across the middle and lower reaches of the Yangtze River, which has important implications for future lake management and ecological restoration.

AB - The results of an investigation into the relationship between surface sediment subfossil chironomid distribution and water quality are presented. Data from 30 lakes in the middle and lower reaches of the Yangtze River indicate that the nutrient gradient was the major factor affecting the distribution of chironomids across these sites. Canonical correspondence analysis (CCA) revealed that of 12 summer water environmental variables, total Phosphorus was most important, accounting for 20.1% of the variance in the chironomid data. This was significant enough to allow the development of quantitative inference models. A TP inference model was developed using weighted averaging (WA), partial least squares (PLS) and weighted averaging partial least squares (WA-PLS). An optimal two-component WA-PLS model provided a high jack-knifed coefficient of prediction for conductivity r 2 jack = 0.76, with a low root mean squared error of prediction (RMSEPjack = 0.13). Using this model it is possible to produce long-term quantitative records of past water quality for lacustrine sites across the middle and lower reaches of the Yangtze River, which has important implications for future lake management and ecological restoration.

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JO - Chinese Science Bulletin

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