Long-term and inter-monthly dynamics of aquatic vegetation and its relation with environmental factors in Taihu Lake, China

Wang, Shuangshuang; Gao, Yanfang; Qin, Liqiang; Gao, Junfeng; Zhai, Shikui; Zhou, Yiming; Cheng, Yuanhua

doi:10.1016/j.scitotenv.2018.09.216

Cited by 61 publications

(34 citation statements)

References 28 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Furthermore, aquatic plants also react to water regimes differently compared to completely closed lakes such as Tai Lake (located in east China) and Qinghai Lake (located in west China) (Chen, Du, Yuan, & Wang, 2014; Wang et al, 2019). Water levels in such lakes are very stable throughout the year.…”

Section: Discussionmentioning

confidence: 99%

“…Water levels in such lakes are very stable throughout the year. Nutrients and salts in the lake water rather than in the water regimes determine the occurrences of aquatic plants in completely closed lakes (Chen et al, 2014; Wang et al, 2019). It can be concluded that due to different topographic features of lakes, water regimes exert various degrees of influence on aquatic vegetation.…”

Section: Discussionmentioning

confidence: 99%

See 1 more Smart Citation

Aquatic vegetation dynamics in two pit lakes related to interannual water level fluctuation

Zheng

Zhan

et al. 2020

Hydrological Processes

View full text Add to dashboard Cite

Water regime characteristics have been recognized as critical factors for aquatic vegetation. In this study, we examined changes in aquatic vegetation coverage area in two shallow sub-lakes of Poyang Lake (Bang Lake and Cuoji Lake) during the dry season from 1987 to 2017. The relationships between eight water regime components (annual average water level, annual maximum water level, annual minimum water level, and flooded days at five water levels [11, 13, 15, 17, and 19 m]) and aquatic vegetation coverage area were determined. The most critical water regimes were identified and results demonstrated that aquatic vegetation coverage area in Bang Lake and Cuoji Lake peaked in drier years (2005 and 2009, respectively) with no obvious up or down trend. Water regimes indicating high flow events such as annual maximum water level, flooded days at water level 19 m, and annual average water level were found to be more important for predicting aquatic vegetation.High-flow events appear to be essential for understanding aquatic vegetation dynamics in pit lakes, yet overall the influences of water level fluctuation on aquatic vegetation varied among wetland units of Poyang Lake. This study helps to understand the hydroecological dynamics in connected lakes further and provide a reference for the lake management and protection.

show abstract

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Aquatic vegetation dynamics in two pit lakes related to interannual water level fluctuation

Zheng

Zhan

et al. 2020

Hydrological Processes

View full text Add to dashboard Cite

show abstract

“…Previous studies have pointed out that the macrophyte-dominated zone also have received large amount of nutrient inputs (Liang et al 2017). For instance, enclosure culture in East Taihu Bay (the region Site 5 located) reached its peak from 1998 to 2008 (Wang et al 2019). Although suffered a mass of anthropogenic organic matter inputs, the water quality of East Taihu Bay was better than that of algae-dominated zone (Kong et al 2018).…”

Section: Discussionmentioning

confidence: 99%

Spatial heterogeneity of food web structure in a large shallow eutrophic lake (Lake Taihu, China): implications for eutrophication process and management

Wang

Liu

et al. 2019

Journal of Freshwater Ecology

View full text Add to dashboard Cite

The knowledge of food web spatial heterogeneity is important for ecologists and lake managers to understand ecosystem complexity and lake management. Lake Taihu, a large shallow eutrophic lake in China, has two distinct zones: algae-and macrophytedominated. In this study, we assessed the spatial heterogeneity of food webs in the two lake zones using stable isotope analysis and isotope mixing model. The basal sources and consumers showed significant differences in d 13 C and d 15 N ratios between the two lake zones, except for the filter-feeding fishes. Overall, more d 13 C-depleted and d 15 N-enriched ratios were found in the algae-than the macrophyte-dominated zones for basal sources and consumers. Although the consumers in the algae-dominant zone had higher average d 15 N values, the food web of the macrophyte-dominated zone had longer food chain length and more diverse trophic linkages. These spatial differences may have resulted from resource availability and environmental stress of Lake Taihu ecosystem. Factors associated with spatial trophic heterogeneity should be considered for the management and restoration of this shallow eutrophic lake.

show abstract

“…), and biological (e.g., phytoplankton [20], aquatic fish [21] and aquatic plant [22] etc.) parameters, as well as the influences of land use [23] and eutrophication [24]. In this research, we focus on water quality parameters of Beihai Lake.…”

Section: Introductionmentioning

confidence: 99%

Application of a Hybrid Optimized BP Network Model to Estimate Water Quality Parameters of Beihai Lake in Beijing

Yan

et al. 2019

Applied Sciences

View full text Add to dashboard Cite

Nowadays, freshwater resources are facing numerous crises and pressures, resulting from both artificial and natural process, so it is crucial to predict the water quality for the department of water environment protection. This paper proposes a hybrid optimized algorithm involving a particle swarm optimization (PSO) and genetic algorithm (GA) combined BP neural network that can predict the water quality in time series and has good performance in Beihai Lake in Beijing. The data sets consist of six water quality parameters which include Hydrogen Ion Concentration (pH), Chlorophyll-a (CHLA), Hydrogenated Amine (NH4H), Dissolved Oxygen (DO), Biochemical Oxygen Demand (BOD), and electrical conductivity (EC). The performance of the model was assessed through the absolute percentage error ( A P E m a x ), the mean absolute percentage error (MAPE), the root mean square error (RMSE), and the coefficient of determination ( R 2 ). Study results show that the model based on PSO and GA to optimize the BP neural network is able to predict the water quality parameters with reasonable accuracy, suggesting that the model is a valuable tool for lake water quality estimation. The results show that the hybrid optimized BP model has a higher prediction capacity and better robustness of water quality parameters compared with the traditional BP neural network, the PSO-optimized BP neural network, and the GA-optimized BP neural network.

show abstract

Long-term and inter-monthly dynamics of aquatic vegetation and its relation with environmental factors in Taihu Lake, China

Cited by 61 publications

References 28 publications

Aquatic vegetation dynamics in two pit lakes related to interannual water level fluctuation

Aquatic vegetation dynamics in two pit lakes related to interannual water level fluctuation

Spatial heterogeneity of food web structure in a large shallow eutrophic lake (Lake Taihu, China): implications for eutrophication process and management

Application of a Hybrid Optimized BP Network Model to Estimate Water Quality Parameters of Beihai Lake in Beijing

Contact Info

Product

Resources

About