State Key Laboratory of Water Resources and Hydropower Engineering Science, Wuhan University, Wuhan, 430072, PR China; Hubei Provincial Key Lab of Water System Science for Sponge City Construction, Wuhan University, Wuhan, 430072, PR China; Research Institute for Water Security (RIWS), Wuhan University, Wuhan, 430072, PR China.
State Key Laboratory of Water Resources and Hydropower Engineering Science, Wuhan University, Wuhan, 430072, PR China; Hubei Provincial Key Lab of Water System Science for Sponge City Construction, Wuhan University, Wuhan, 430072, PR China; Research Institute for Water Security (RIWS), Wuhan University, Wuhan, 430072, PR China.
J Environ Manage. 2023 Jun 15;336:117562. doi: 10.1016/j.jenvman.2023.117562. Epub 2023 Mar 11.
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.
水生群落动态受流态和水质条件的紧密支配,这些条件正日益受到大坝调节、引水和营养物污染的威胁。然而,对于流态和水质条件对水生多种群动态的生态影响的进一步理解,很少被整合到现有的生态模型中。为了解决这个问题,提出了一种新的基于生态位的集合种群动态模型(MDM)。MDM 的目的是模拟在不断变化的非生物环境中多个种群的共同进化过程,开创性地应用于中国中下游的汉江水系。首次使用分位数回归方法来推导出 MDM 的生态位和竞争系数,并通过与经验证据进行比较,证明它们是合理的。模拟结果表明,鱼类、浮游动物、底栖动物和大型水生植物的纳什效率系数均大于 0.64,皮尔逊相关系数均不小于 0.71。总体而言,MDM 在模拟集合种群动态方面表现出色。对于所有河流站点,生物相互作用、流态效应和水质效应对多种群动态的平均贡献分别为 64%、21%和 15%,这表明种群动态主要由生物相互作用决定。对于上游站点,鱼类种群对流态变化的响应比其他种群更为敏感,增加了 8%-22%,而其他种群对流态变化的响应比鱼类更为敏感,增加了 9%-26%。对于下游站点,由于水文条件更为稳定,流态效应对每个种群的影响小于 1%。本研究的创新之处在于提出了一种多种群模型,通过整合水量、水质和生物量的多个指标,量化流态和水质对水生群落动态的影响。这项工作有可能在生态系统层面上实现河流的生态恢复。本研究还强调了在未来的工作中分析“水量-水质-水生生态”关系时考虑阈值和 tipping point 问题的重要性。