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Identifying the main drivers of change of phytoplankton community structure and gross primary productivity in a river-lake system

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Identifying the main drivers of change of phytoplankton community structure and gross primary productivity in a river-lake system. / Jia, Junjie; Gao, Yang; Zhou, Feng; Shi, Kun; Johnes, Penny J; Dungait, Jennifer A. J.; Ma, Mingzhen; Lu, Yao.

In: Journal of Hydrology, Vol. 583, 124633, 01.04.2020.

Research output: Contribution to journalArticle (Academic Journal)

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Jia, Junjie ; Gao, Yang ; Zhou, Feng ; Shi, Kun ; Johnes, Penny J ; Dungait, Jennifer A. J. ; Ma, Mingzhen ; Lu, Yao. / Identifying the main drivers of change of phytoplankton community structure and gross primary productivity in a river-lake system. In: Journal of Hydrology. 2020 ; Vol. 583.

Bibtex

@article{4105d8fbab5f42658efb481e9783df14,
title = "Identifying the main drivers of change of phytoplankton community structure and gross primary productivity in a river-lake system",
abstract = "The management of river-lake systems is hindered by limitations in the applicability of existing models that describe the relationship between environmental factors and phytoplankton community characteristics but rarely include common and indirect effects on algae dynamics. In this study, we assumed that the interaction of light, water, temperature, pH, and nutrients, including direct and indirect effects, are the potential factors affecting phytoplankton dynamics. We determined which of these are the main drivers of phytoplankton community structure and production in a river-lake system by using three different models based on the partial least squares structural equation modeling method. Our results indicated that the models achieved more than 60% of the overall explanatory power of various environmental factors on phytoplankton characteristics, including indirect and direct effects. In particular, light, pH, and nutrient content and ratios commonly control phytoplankton dynamic characteristics rather than a single nutrient, but light is the main driving force of phytoplankton community characteristics. Controlling the underwater light conditions, and nitrogen and phosphorus pollution load could effectively regulate algal blooms, increase productivity, promote ecological balance, and reduce water pollution. Our findings provide a scientific and theoretical basis for water resource management and pollution control.",
keywords = "phytoplankton community, gross primary productivity, biodiversity, environmental factor, Poyang Lake",
author = "Junjie Jia and Yang Gao and Feng Zhou and Kun Shi and Johnes, {Penny J} and Dungait, {Jennifer A. J.} and Mingzhen Ma and Yao Lu",
year = "2020",
month = apr,
day = "1",
doi = "10.1016/j.jhydrol.2020.124633",
language = "English",
volume = "583",
journal = "Journal of Hydrology",
issn = "0022-1694",
publisher = "Elsevier",

}

RIS - suitable for import to EndNote

TY - JOUR

T1 - Identifying the main drivers of change of phytoplankton community structure and gross primary productivity in a river-lake system

AU - Jia, Junjie

AU - Gao, Yang

AU - Zhou, Feng

AU - Shi, Kun

AU - Johnes, Penny J

AU - Dungait, Jennifer A. J.

AU - Ma, Mingzhen

AU - Lu, Yao

PY - 2020/4/1

Y1 - 2020/4/1

N2 - The management of river-lake systems is hindered by limitations in the applicability of existing models that describe the relationship between environmental factors and phytoplankton community characteristics but rarely include common and indirect effects on algae dynamics. In this study, we assumed that the interaction of light, water, temperature, pH, and nutrients, including direct and indirect effects, are the potential factors affecting phytoplankton dynamics. We determined which of these are the main drivers of phytoplankton community structure and production in a river-lake system by using three different models based on the partial least squares structural equation modeling method. Our results indicated that the models achieved more than 60% of the overall explanatory power of various environmental factors on phytoplankton characteristics, including indirect and direct effects. In particular, light, pH, and nutrient content and ratios commonly control phytoplankton dynamic characteristics rather than a single nutrient, but light is the main driving force of phytoplankton community characteristics. Controlling the underwater light conditions, and nitrogen and phosphorus pollution load could effectively regulate algal blooms, increase productivity, promote ecological balance, and reduce water pollution. Our findings provide a scientific and theoretical basis for water resource management and pollution control.

AB - The management of river-lake systems is hindered by limitations in the applicability of existing models that describe the relationship between environmental factors and phytoplankton community characteristics but rarely include common and indirect effects on algae dynamics. In this study, we assumed that the interaction of light, water, temperature, pH, and nutrients, including direct and indirect effects, are the potential factors affecting phytoplankton dynamics. We determined which of these are the main drivers of phytoplankton community structure and production in a river-lake system by using three different models based on the partial least squares structural equation modeling method. Our results indicated that the models achieved more than 60% of the overall explanatory power of various environmental factors on phytoplankton characteristics, including indirect and direct effects. In particular, light, pH, and nutrient content and ratios commonly control phytoplankton dynamic characteristics rather than a single nutrient, but light is the main driving force of phytoplankton community characteristics. Controlling the underwater light conditions, and nitrogen and phosphorus pollution load could effectively regulate algal blooms, increase productivity, promote ecological balance, and reduce water pollution. Our findings provide a scientific and theoretical basis for water resource management and pollution control.

KW - phytoplankton community

KW - gross primary productivity

KW - biodiversity

KW - environmental factor

KW - Poyang Lake

U2 - 10.1016/j.jhydrol.2020.124633

DO - 10.1016/j.jhydrol.2020.124633

M3 - Article (Academic Journal)

VL - 583

JO - Journal of Hydrology

JF - Journal of Hydrology

SN - 0022-1694

M1 - 124633

ER -