Integrating the flow regime and water quality effects into a niche-based metacommunity dynamics model for river ecosystems

Journal Article (2023)
Authors

Yibo Wang (Wuhan University)

Pan Liu (Wuhan University)

D. P. Solomatine (TU Delft - Water Resources, IHE Delft Institute for Water Education)

Liping Li (Changjiang Water Resources Commission)

Chen Wu (Wuhan University)

Dongyang Han (Wuhan University)

Xiaojing Zhang (Wuhan University)

Zhikai Yang (Wuhan University)

Sheng Yang (China Energy Science and Technology Research Institute Co.,Ltd)

Research Group
Water Resources
Copyright
© 2023 Yibo Wang, Pan Liu, D.P. Solomatine, Liping Li, Chen Wu, Dongyang Han, Xiaojing Zhang, Zhikai Yang, Sheng Yang
To reference this document use:
https://doi.org/10.1016/j.jenvman.2023.117562
More Info
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Publication Year
2023
Language
English
Copyright
© 2023 Yibo Wang, Pan Liu, D.P. Solomatine, Liping Li, Chen Wu, Dongyang Han, Xiaojing Zhang, Zhikai Yang, Sheng Yang
Research Group
Water Resources
Volume number
336
DOI:
https://doi.org/10.1016/j.jenvman.2023.117562
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Abstract

Aquatic community dynamics are closely dominated by flow regime and water quality conditions, which are increasingly threatened by dam regulation, water diversion, and nutrition pollution. However, further understanding of the ecological impacts of flow regime and water quality conditions on aquatic multi-population dynamics has rarely been integrated into existing ecological models. To address this issue, a new niche-based metacommunity dynamics model (MDM) is proposed. The MDM aims to simulate the coevolution processes of multiple populations under changing abiotic environments, pioneeringly applied to the mid-lower Han River, China. The quantile regression method was used for the first time to derive ecological niches and competition coefficients of the MDM, which are demonstrated to be reasonable by comparing them with the empirical evidence. Simulation results show that the Nash efficiency coefficients for fish, zooplankton, zoobenthos, and macrophytes are more than 0.64, while the Pearson correlation coefficients for them are no less than 0.71. Overall, the MDM performs effectively in simulating metacommunity dynamics. For all river stations, the average contributions of biological interaction, flow regime effects, and water quality effects to multi-population dynamics are 64%, 21%, and 15%, respectively, suggesting that the population dynamics are dominated by biological interaction. For upstream stations, the fish population is 8%–22% more responsive to flow regime alteration than other populations, while other populations are 9%–26% more responsive to changes in water quality conditions than fish. For downstream stations, flow regime effects on each population account for less than 1% due to more stable hydrological conditions. The innovative contribution of this study lies in proposing a multi-population model to quantify the effects of flow regime and water quality on aquatic community dynamics by incorporating multiple indicators of water quantity, water quality, and biomass. This work has potential for the ecological restoration of rivers at the ecosystem level. This study also highlights the importance of considering threshold and tipping point issues when analyzing the “water quantity-water quality-aquatic ecology” nexus in future works.

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