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Ren W, Yao Y, Gao X, Wang H, Wen Z, Ni L, Zhang X, Cao T, Chou Q. Water depth affects submersed macrophyte more than herbivorous snail in mesotrophic lakes. FRONTIERS IN PLANT SCIENCE 2024; 15:1375898. [PMID: 38828221 PMCID: PMC11140150 DOI: 10.3389/fpls.2024.1375898] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 01/24/2024] [Accepted: 04/22/2024] [Indexed: 06/05/2024]
Abstract
Introduction Water depth (WD) and snail abundance (SA) are two key factors affecting the growth of submersed aquatic plants in freshwater lake ecosystems. Changes in WD and SA drive changes in nutrients and other primary producers that may have direct or indirect effects on submersed plant growth, but which factor dominates the impact of both on aquatic plants has not been fully studied. Methods To investigate the dominant factors that influence aquatic plant growth in plateau lakes, a one-year field study was conducted to study the growth of three dominant submersed macrophyte (i.e., Vallisneria natans, Potamogeton maackianus, and Potamogeton lucens) in Erhai Lake. Results The results show that, the biomass of the three dominant plants, P.maackianus, is the highest, followed by P.lucens, and V.natans is the lowest. Meanwhile, periphyton and snails attached to P.maackianus are also the highest. Furthermore, WD had a positive effect on the biomass of two submersed macrophyte species of canopy-type P.maackianus and P.lucens, while it had a negative effect on rosette-type V.natans. Snail directly inhibited periphyton attached on V.natans and thereby increasing the biomass of aquatic plants, but the effect of snails on the biomass of the other two aquatic plants is not through inhibition of periphyton attached to their plants. Discussion The dominant factors affecting the biomass of submersed macrophyte in Erhai Lake were determined, as well as the direct and indirect mechanisms of WD and snails on the biomass of dominant submersed macrophyte. Understanding the mechanisms that dominate aquatic plant change will have implications for lake management and restoration.
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Affiliation(s)
- Wenjing Ren
- State Key Laboratory of Marine Resource Utilization in South China Sea, Hainan University, Haikou, China
| | - Yiqian Yao
- State Key Laboratory of Freshwater Ecology and Biotechnology, Institute of Hydrobiology, Chinese Academy of Sciences, Wuhan, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Xiaoyu Gao
- State Key Laboratory of Freshwater Ecology and Biotechnology, Institute of Hydrobiology, Chinese Academy of Sciences, Wuhan, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Hao Wang
- State Key Laboratory of Freshwater Ecology and Biotechnology, Institute of Hydrobiology, Chinese Academy of Sciences, Wuhan, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Zihao Wen
- State Key Laboratory of Freshwater Ecology and Biotechnology, Institute of Hydrobiology, Chinese Academy of Sciences, Wuhan, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Leyi Ni
- State Key Laboratory of Freshwater Ecology and Biotechnology, Institute of Hydrobiology, Chinese Academy of Sciences, Wuhan, China
| | - Xiaolin Zhang
- State Key Laboratory of Freshwater Ecology and Biotechnology, Institute of Hydrobiology, Chinese Academy of Sciences, Wuhan, China
| | - Te Cao
- State Key Laboratory of Freshwater Ecology and Biotechnology, Institute of Hydrobiology, Chinese Academy of Sciences, Wuhan, China
| | - Qingchuan Chou
- State Key Laboratory of Freshwater Ecology and Biotechnology, Institute of Hydrobiology, Chinese Academy of Sciences, Wuhan, China
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Wang Y, Li Y, Cheng Y, Wang Y, Zhu Y, Li R, Acharya K, Ibrahim M. Thermal stratification and mixing processes response to meteorological factors in a monomictic reservoir. JOURNAL OF ENVIRONMENTAL MANAGEMENT 2024; 354:120205. [PMID: 38359623 DOI: 10.1016/j.jenvman.2024.120205] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/03/2023] [Revised: 01/02/2024] [Accepted: 01/20/2024] [Indexed: 02/17/2024]
Abstract
Formation and extinction of thermal stratifications impact the reservoir ecosystems and have been closely influenced by meteorological and hydrological factors. However, quantifying the relative importance of these crucial environmental factors and mechanisms in reservoir regions characterized by various depths remain comparatively uninvestigated. Tianbao Reservoir is a typical monomictic warm and drinking water source reservoir in Southwest China. This study supplemented field observations with a three-dimensional numerical simulation model to quantitatively analyze mixing and turnover events. Air temperature and wind were two important meteorological factors resulting in hydrodynamics during stratification and mixing processes. Air temperature led to variations in stratification strength and wind-induced fluctuations of thermocline depth. A 10% rise in air temperature increased stratification strength by 18%, and a 3 m/s rise in wind speed induced the deepening of the thermocline by 2.09 m. Two hydrodynamics involved penetrative convection caused by temperature plummets and wind-induced mixing during winter turnover events were identified. Penetrative convection was the main driving force, and wind shear mixed the upper 21% of the mixed layer, which was contributed by convection. Response of water temperature to air temperature in shallow regions was faster (58 d), and the mixing depth caused by the wind was smaller than that in deep regions. Research on physical processes during stratification and mixing processes can provide support for further study on water quality deterioration distributions.
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Affiliation(s)
- Yaning Wang
- Key Laboratory of Integrated Regulation and Resource Development on Shallow Lake of Ministry of Education, College of Environment, Hohai University, Nanjing, 210098, China
| | - Yiping Li
- Key Laboratory of Integrated Regulation and Resource Development on Shallow Lake of Ministry of Education, College of Environment, Hohai University, Nanjing, 210098, China.
| | - Yue Cheng
- Key Laboratory of Integrated Regulation and Resource Development on Shallow Lake of Ministry of Education, College of Environment, Hohai University, Nanjing, 210098, China
| | - Yu Wang
- Key Laboratory of Integrated Regulation and Resource Development on Shallow Lake of Ministry of Education, College of Environment, Hohai University, Nanjing, 210098, China
| | - Ya Zhu
- Key Laboratory of Integrated Regulation and Resource Development on Shallow Lake of Ministry of Education, College of Environment, Hohai University, Nanjing, 210098, China
| | - Ronghui Li
- Key Laboratory of Disaster Prevention and Structural Safety, Ministry of Education, College of Civil Engineering and Architecture, Guangxi University, Nanning, 530000, China
| | - Kumud Acharya
- Desert Research Institute, Las Vegas, NV, 89119, USA
| | - Muhammad Ibrahim
- Key Laboratory of Integrated Regulation and Resource Development on Shallow Lake of Ministry of Education, College of Environment, Hohai University, Nanjing, 210098, China; Department of Environmental Management and Toxicology, Federal University Dutse, Dutse, 720101, Nigeria
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Meng Z, Yu X, Xia S, Zhang Q, Ma X, Yu D. Effects of water depth on the biomass of two dominant submerged macrophyte species in floodplain lakes during flood and dry seasons. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 877:162690. [PMID: 36894075 DOI: 10.1016/j.scitotenv.2023.162690] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/03/2022] [Revised: 02/12/2023] [Accepted: 03/03/2023] [Indexed: 05/06/2023]
Abstract
Floodplain lakes share characteristics of both deep and shallow lakes throughout any given year. Seasonal fluctuations in their water depth drive changes in nutrients and total primary productivity, which directly and indirectly affect submerged macrophyte biomass. To investigate how water depth and environmental variables affect submerged macrophyte biomass, we surveyed six sub-lakes in the Poyang Lake floodplain, China, during the flood and dry seasons of 2021. Dominant submerged macrophytes include Vallisneria spinulosa and Hydrilla verticillata. The effect of water depth on the biomass of these macrophytes varied between the flood and dry seasons. In the flood season, there was a direct effect of water depth on biomass, while in the dry season only an indirect effect was observed. During the flood season, the direct effect of water depth on the biomass of V. spinulosa was less than the indirect effect, with water depth primarily affecting the total nitrogen, total phosphorus and water column transparency. Water depth directly, positively affected H. verticillata biomass, with this effect being greater than the indirect effect by affecting the carbon, nitrogen and phosphorus content in the water column and sediment. During the dry season, water depth affected H. verticillata biomass indirectly through sediment carbon and nitrogen content, while for V. spinulosa, the effect on biomass was indirect through carbon content of the sediment and water column. The main environmental variables affecting submerged macrophyte biomass in the Poyang Lake floodplain during the flood and dry seasons, and the mechanisms through which water depth affects dominant submerged macrophyte biomass, are identified. An understanding of these variables and mechanisms will enable improved management and restoration of wetland.
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Affiliation(s)
- Zhujian Meng
- Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences (CAS), Beijing 100101, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Xiubo Yu
- Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences (CAS), Beijing 100101, China; University of Chinese Academy of Sciences, Beijing 100049, China.
| | - Shaoxia Xia
- Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences (CAS), Beijing 100101, China; University of Chinese Academy of Sciences, Beijing 100049, China.
| | - Quanjun Zhang
- CMA Meteorological Observation Centre (MOC), Beijing 100081, China
| | - Xu Ma
- State Key Laboratory of Simulation and Regulation of Water Cycle in River Basin, Beijing 100038, China; China Institute of Water Resources and Hydropower Research, Beijing 100038, China
| | - Dingkun Yu
- Jiangxi Poyang Lake National Nature Reserve Authority, Nanchang 330038, China
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Ren Y, Xia J, Zeng S, Song J, Tang X, Yang L, Lv P, Fan D. Identifying critical regions for nitrogen and phosphorus loss management in a large-scale complex basin: The Jialing River. ENVIRONMENTAL RESEARCH 2023:116359. [PMID: 37295585 DOI: 10.1016/j.envres.2023.116359] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/12/2023] [Revised: 05/30/2023] [Accepted: 06/07/2023] [Indexed: 06/12/2023]
Abstract
The determination of critical management areas for nitrogen (N) and phosphorus (P) losses in large-scale basins is critical to reduce costs and improve efficiency. In this study, the spatial and temporal characteristics of the N and P losses in the Jialing River from 2000 to 2019 were calculated based on the Soil and Water Assessment Tool (SWAT) model. The trends were analyzed using the Theil-Sen median analysis and Mann-Kendall test. The Getis-Ord Gi* was used to determine significant coldspot and hotspot regions to identify critical regions and priorities for regional management. The ranges of the annual average unit load losses for N and P in the Jialing River were 1.21-54.53 kg ha-1 and 0.05-1.35 kg ha-1, respectively. The interannual variations in both N and P losses showed decreasing trends, with change rates of 0.327 and 0.003 kg ha-1·a-1 and change magnitudes of 50.96% and 41.05%, respectively. N and P losses were highest in the summer and lowest in the winter. The coldspot regions for N loss were clustered northwest of the upstream Jialing River and north of Fujiang River. The coldspot regions for P loss were clustered in the central, western, and northern areas of the upstream Jialing River. The above regions were found to be not critical for management. The hotspot regions for N loss were clustered in the south of the upstream Jialing River, the central-western and southern areas of the Fujiang River, and the central area of the Qujiang River. The hotspot regions for P loss were clustered in the south-central area of the upstream Jialing River, the southern and northern areas of the middle and downstream Jialing River, the western and southern areas of the Fujiang River, and the southern area of the Qujiang River. The above regions were found to be critical for management. There was a significant difference between the high load area for N and the hotspot regions, while the high load region for P was consistent with the hotspot regions. The coldspot and hotspot regions for N would change locally in spring and winter, and the coldspot and hotspot regions for P would change locally in summer and winter, respectively. Therefore, managers should make specific adjustments in critical regions for different pollutants according to seasonal characteristics when developing management programs.
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Affiliation(s)
- Yuanxin Ren
- Shaanxi Key Laboratory of Earth Surface System and Environmental Carrying Capacity, College of Urban and Environmental Sciences, Northwest University, Xi'an, 710127, China; Chongqing Institute of Green and Intelligent Technology, Chinese Academy of Sciences, Chongqing, 400714, China; Chongqing School, University of Chinese Academy of Sciences, Chongqing, 400714, China
| | - Jun Xia
- Shaanxi Key Laboratory of Earth Surface System and Environmental Carrying Capacity, College of Urban and Environmental Sciences, Northwest University, Xi'an, 710127, China; Chongqing Institute of Green and Intelligent Technology, Chinese Academy of Sciences, Chongqing, 400714, China; Chongqing School, University of Chinese Academy of Sciences, Chongqing, 400714, China; State Key Laboratory of Water Resources and Hydropower Engineering Science, Wuhan University, Wuhan, 430072, China
| | - Sidong Zeng
- Chongqing Institute of Green and Intelligent Technology, Chinese Academy of Sciences, Chongqing, 400714, China; Chongqing School, University of Chinese Academy of Sciences, Chongqing, 400714, China.
| | - Jinxi Song
- Shaanxi Key Laboratory of Earth Surface System and Environmental Carrying Capacity, College of Urban and Environmental Sciences, Northwest University, Xi'an, 710127, China
| | - Xiaoya Tang
- Chongqing Institute of Green and Intelligent Technology, Chinese Academy of Sciences, Chongqing, 400714, China; Chongqing School, University of Chinese Academy of Sciences, Chongqing, 400714, China
| | - Linhan Yang
- Chongqing Institute of Green and Intelligent Technology, Chinese Academy of Sciences, Chongqing, 400714, China; Chongqing School, University of Chinese Academy of Sciences, Chongqing, 400714, China
| | - Pingyu Lv
- Water-Environment Monitoring Center for the Upper Reach of Changjiang, Changjiang Water Resource Commission, Chongqing, 40021, China
| | - Di Fan
- Chongqing Institute of Green and Intelligent Technology, Chinese Academy of Sciences, Chongqing, 400714, China; Chongqing School, University of Chinese Academy of Sciences, Chongqing, 400714, China
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