1
|
Li J, Zhou Q, Dao Y, Song D, Yu Z, Chang J, Jeppesen E. Periodically asymmetric responses of deep chlorophyll maximum to light and thermocline in a clear monomictic lake: Insights from monthly and diel scale observations. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 955:177000. [PMID: 39427899 DOI: 10.1016/j.scitotenv.2024.177000] [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: 06/17/2024] [Revised: 10/14/2024] [Accepted: 10/15/2024] [Indexed: 10/22/2024]
Abstract
Deep chlorophyll maximum (DCM), a chlorophyll peak in the water column, has important implications for biogeochemical cycles, energy flow and water surface algal blooms in deep lakes. However, how an observed periodically asymmetric DCM response to environmental variables remains unclear, limiting our in-depth understanding and effective eco-environmental management of deep lakes. Based on both monthly field investigations in 2021 and diel continuous observations in 2021-2023 in clear, monomictic Lake Fuxian, Southwest China, the temporal dynamics and drivers of DCM were examined and periodic features of DCM were found, with a formation period (FP, February-July) and a weakening period (WP, August-December). On the monthly scale, although DCM dynamics were partly attributed to thermocline structures, the role of light penetration depths varied with period. In the FP, the influence of light on DCM was direct, i.e., increased depth and thickness but decreased magnitude. Differently, the influence of light mainly occurred by affecting thermocline structures in the WP, where water quality was another important driver. On the diel scale, light was a major reason for a thicker and lower (magnitude) DCM during day than at night, and the response of DCM to environmental factors between the FP and WP differed also more during day. This periodically asymmetric response of daytime DCM not only being caused by light but possibly also related to other physical factors such as lake surface water temperature, wind speed and precipitation. Bayesian network modelling suggested that water darkening and stratification intensification may promote a shallower, thinner and larger (magnitude) DCM in both FP and WP, but achieving such changes in DCM requires different light and thermocline thresholds. Our findings provide new information valuable for modelling DCM and for predicting the related surface algal blooms in deep lakes under climate change and eutrophication.
Collapse
Affiliation(s)
- Jingyi Li
- Yunnan Key Laboratory of Ecological Protection and Resource Utilization of River-lake Networks, Institute for Ecological Research and Pollution Control of Plateau Lakes, School of Ecology and Environmental Sciences, Yunnan University, Kunming 650500, China
| | - Qichao Zhou
- Yunnan Key Laboratory of Ecological Protection and Resource Utilization of River-lake Networks, Institute for Ecological Research and Pollution Control of Plateau Lakes, School of Ecology and Environmental Sciences, Yunnan University, Kunming 650500, China.
| | - Yue Dao
- Yunnan Key Laboratory of Ecological Protection and Resource Utilization of River-lake Networks, Institute for Ecological Research and Pollution Control of Plateau Lakes, School of Ecology and Environmental Sciences, Yunnan University, Kunming 650500, China
| | - Di Song
- Yunnan Key Laboratory of Pollution Process and Management of Plateau Lake-watershed, Yunnan Research Academy of Eco-environmental Sciences, Kunming 650034, China
| | - Zhirong Yu
- Yunnan Key Laboratory of Ecological Protection and Resource Utilization of River-lake Networks, Institute for Ecological Research and Pollution Control of Plateau Lakes, School of Ecology and Environmental Sciences, Yunnan University, Kunming 650500, China
| | - Junjun Chang
- Yunnan Key Laboratory of Ecological Protection and Resource Utilization of River-lake Networks, Institute for Ecological Research and Pollution Control of Plateau Lakes, School of Ecology and Environmental Sciences, Yunnan University, Kunming 650500, China.
| | - Erik Jeppesen
- Yunnan Key Laboratory of Ecological Protection and Resource Utilization of River-lake Networks, Institute for Ecological Research and Pollution Control of Plateau Lakes, School of Ecology and Environmental Sciences, Yunnan University, Kunming 650500, China; Department of Ecoscience, Aarhus University, Aarhus 8000, Denmark; Department of Biology, Limnology Laboratory, Üniversiteler Mahallesi, Middle East Technical University, Çankaya, Ankara 06800, Turkey; Sino-Danish Centre for Education and Research (SDC), Beijing 100049, China
| |
Collapse
|
2
|
Liu H, Liu J, Wang H, Liu Z, Li X, Zhang P, Liu W, Xiao S. Variations and driving factors for concentrations and carbon isotopes of dissolved CO 2 in lake water across different Chinese lakes. ENVIRONMENTAL RESEARCH 2024; 262:119826. [PMID: 39173819 DOI: 10.1016/j.envres.2024.119826] [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: 05/15/2024] [Revised: 08/07/2024] [Accepted: 08/20/2024] [Indexed: 08/24/2024]
Abstract
Carbon dioxide (CO2) stands as the primary driver of Earth's greenhouse effect, and it's suggested that the global contribution of CO2 emissions from lakes cannot be ignored. Despite the numerous estimations of CO2 fluxes from lakes, limited focus has been directed towards the carbon isotopes (δ13C) of dissolved CO2 in lake water. Particularly, the potential use of δ13C values in tracing the CO2 concentrations in lake water remains as an understudied area, warranting further exploration and investigation. In this study, we conducted an analysis of the concentrations and δ13C values of dissolved CO2 in 33 lakes located at the Tibetan Plateau, Chinese Loess Plateau, and Yangtze Plain (among which high-resolution spatial investigations were performed in 6 lakes through in-situ continuous monitoring). Our findings revealed spatial variations in both the CO2 concentrations and δ13C values in lakes. Additionally, notable differences are observed among lakes in different regions of China, with lakes in the Yangtze Plain exhibiting considerably higher CO2 concentrations, and the overall CO2 δ13C values in lakes on the Tibetan Plateau tend to be more positive, while those in lakes on the Chinese Loess Plateau tend to be more negative. The pH values, dissolved oxygen, and dissolved organic carbon are likely crucial factors influencing the CO2 concentrations and δ13C values in the lakes. Furthermore, lake water CO2 concentrations are negatively correlated with δ13C values of CO2 and dissolved inorganic carbon (DIC) both within a single lake with high spatial resolutions or in lake groups across different regions. These results highlight that the CO2/DIC δ13C values can be applied to trace the concentration variations of dissolved CO2 in lakes.
Collapse
Affiliation(s)
- Hu Liu
- State Key Laboratory of Loess and Quaternary Geology, Institute of Earth Environment, Center for Excellence in Quaternary Science and Global Change, Chinese Academy of Sciences, Xi'an, 710061, China; Xi'an Institute for Innovative Earth Environment Research, Xi'an, 710061, China.
| | - Jia Liu
- Hubei Field Observation and Scientific Research Stations for Water Ecosystem in Three Gorges Reservoir, China Three Gorges University, Yichang, 443002, China
| | - Huanye Wang
- State Key Laboratory of Loess and Quaternary Geology, Institute of Earth Environment, Center for Excellence in Quaternary Science and Global Change, Chinese Academy of Sciences, Xi'an, 710061, China
| | - Zhonghui Liu
- Department of Earth Sciences, The University of Hong Kong, Hong Kong, China; Institute for Climate and Carbon Neutrality, The University of Hong Kong, Hong Kong, China
| | - Xiangzhong Li
- Yunnan Key Laboratory of Earth System Science, Yunnan University, Kunming, 650500, China
| | - Ping Zhang
- Yunnan Key Laboratory of Earth System Science, Yunnan University, Kunming, 650500, China
| | - Weiguo Liu
- State Key Laboratory of Loess and Quaternary Geology, Institute of Earth Environment, Center for Excellence in Quaternary Science and Global Change, Chinese Academy of Sciences, Xi'an, 710061, China; University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Shangbin Xiao
- Hubei Field Observation and Scientific Research Stations for Water Ecosystem in Three Gorges Reservoir, China Three Gorges University, Yichang, 443002, China.
| |
Collapse
|
3
|
Xun F, Feng M, Zhao C, Luo W, Han X, Ci Z, Yin Y, Wang R, Wu QL, Grossart HP, Xing P. Epilimnetic oligotrophication increases contribution of oxic methane production to atmospheric methane flux from stratified lakes. WATER RESEARCH 2024; 268:122602. [PMID: 39454273 DOI: 10.1016/j.watres.2024.122602] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/12/2024] [Revised: 10/03/2024] [Accepted: 10/08/2024] [Indexed: 10/28/2024]
Abstract
Although considerable attention has been paid to the effects of eutrophication on aquatic methane (CH4) emissions to the atmosphere, the ecosystem-level effects of oligotrophication/re-oligotrophication on aquatic CH4 production and subsequent ecological responses remain to be elucidated. It has been hypothesized that dissolved inorganic phosphorus (DIP)-deficient conditions drive the ecosystem to utilize poorly bioavailable organic phosphorus for biomass formation, thereby generating CH4 as a by-product. To test this hypothesis, a mass balance approach was used to estimate in situ oxic methane production (OMP) in an oligotrophic, deep Lake Fuxian. The isotopic signature of dissolved 13C-CH4, the potential substrates for OMP, and the phnJ/phnD genes associated with microbial demethylation of organic phosphorus compounds were analyzed. Our results indicate that CH4 accumulation was maximal in the surface mixed layer (SML, i.e., Epilimnion) during lake stratification, and ∼ 86 % of the total CH4 flux to the atmosphere was due to OMP. Decomposition of methylphosphonate (MPn) by Alphaproteobacteria (genera Sphingomonas and Mesorhizobium) contributed significantly to OMP. Furthermore, water temperature (Temp), chlorophyll a (Chla), and DIP were the most critical predictors of water OMP potential. Meta-analysis of currently available global data showed that OMP had a negative exponential distribution with DIP (OMP = 2.0 e-0.71DIP, R2 = 0.57, p < 0.05). DIP concentrations below a threshold of 3.40 ∼ 9.35 μg P L-1 triggered OMP processes and increased the atmospheric CH4 emissions. Under future warming scenarios, stratification and catchment management induced oligotrophication or re-oligotrophication may systematically affect the biogeochemical cycling of phosphorus and the OMP contribution to CH4 emission in stratified lakes.
Collapse
Affiliation(s)
- Fan Xun
- Key Laboratory of Lake and Watershed Science for Water Security, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing 210008, China; State Key Laboratory of Lake Science and Environment, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing 210008, China; College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Muhua Feng
- Key Laboratory of Lake and Watershed Science for Water Security, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing 210008, China; State Key Laboratory of Lake Science and Environment, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing 210008, China
| | - Cheng Zhao
- Key Laboratory of Lake and Watershed Science for Water Security, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing 210008, China; State Key Laboratory of Lake Science and Environment, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing 210008, China; College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Wenlei Luo
- Key Laboratory of Lake and Watershed Science for Water Security, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing 210008, China; State Key Laboratory of Lake Science and Environment, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing 210008, China; The Fuxianhu Station of Deep Lake Research, Chinese Academy of Sciences, Chengjiang 652500, China
| | - Xiaotong Han
- Key Laboratory of Lake and Watershed Science for Water Security, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing 210008, China; State Key Laboratory of Lake Science and Environment, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing 210008, China
| | - Zhen Ci
- Key Laboratory of Lake and Watershed Science for Water Security, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing 210008, China; State Key Laboratory of Lake Science and Environment, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing 210008, China; College of Hydrology and Water Resources, Hohai University, Nanjing 210008, China
| | - Yifan Yin
- Key Laboratory of Lake and Watershed Science for Water Security, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing 210008, China; State Key Laboratory of Lake Science and Environment, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing 210008, China; College of Hydrology and Water Resources, Hohai University, Nanjing 210008, China
| | - Rong Wang
- Key Laboratory of Lake and Watershed Science for Water Security, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing 210008, China; State Key Laboratory of Lake Science and Environment, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing 210008, China; The Fuxianhu Station of Deep Lake Research, Chinese Academy of Sciences, Chengjiang 652500, China
| | - Qinglong L Wu
- Key Laboratory of Lake and Watershed Science for Water Security, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing 210008, China; State Key Laboratory of Lake Science and Environment, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing 210008, China; The Fuxianhu Station of Deep Lake Research, Chinese Academy of Sciences, Chengjiang 652500, China; Center for Evolution and Conservation Biology, Southern Marine Science and Engineering Guangdong Laboratory (Guangzhou), Guangzhou 511458, China; Sino-Danish Center for Education and Research, University of Chinese Academy of Sciences, Beijing 100039, China
| | - Hans-Peter Grossart
- Department of Plankton and Microbial Ecology, Leibniz- Institute of Freshwater Ecology and Inland Fisheries (IGB), Stechlin 16775, Germany; Institute of Biochemistry and Biology, University of Potsdam, Potsdam 14476, Germany
| | - Peng Xing
- Key Laboratory of Lake and Watershed Science for Water Security, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing 210008, China; State Key Laboratory of Lake Science and Environment, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing 210008, China; The Fuxianhu Station of Deep Lake Research, Chinese Academy of Sciences, Chengjiang 652500, China.
| |
Collapse
|
4
|
Yang X, Zhou Y, Yu Z, Li J, Yang H, Huang C, Jeppesen E, Zhou Q. Influence of hydrological features on CO 2 and CH 4 concentrations in the surface water of lakes, Southwest China: A seasonal and mixing regime analysis. WATER RESEARCH 2024; 251:121131. [PMID: 38246081 DOI: 10.1016/j.watres.2024.121131] [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: 11/11/2023] [Revised: 01/03/2024] [Accepted: 01/10/2024] [Indexed: 01/23/2024]
Abstract
Due to the large spatiotemporal variability in the processes controlling carbon emissions from lakes, estimates of global lake carbon emission remain uncertain. Identifying the most reliable predictors of CO2 and CH4 concentrations across different hydrological features can enhance the accuracy of carbon emission estimates locally and globally. Here, we used data from 71 lakes in Southwest China varying in surface area (0.01‒702.4 km2), mean depth (< 1‒89.6 m), and climate to analyze differences in CO2 and CH4 concentrations and their driving mechanisms between the dry and rainy seasons and between different mixing regimes. The results showed that the average concentrations of CO2 and CH4 in the rainy season were 23.9 ± 18.8 μmol L-1 and 2.5 ± 4.9 μmol L-1, respectively, which were significantly higher than in the dry season (10.5 ± 10.3 μmol L-1 and 1.8 ± 4.2 μmol L-1, respectively). The average concentrations of CO2 and CH4 at the vertically mixed sites were 24.1 ± 21.8 μmol L-1 and 2.6 ± 5.4 μmol L-1, being higher than those at the stratified sites (14.8 ± 13.4 μmol L-1 and 1.7 ± 3.5 μmol L-1, respectively). Moreover, the environmental factors were divided into four categories, i.e., system productivity (represented by the contents of total nitrogen, total phosphorus, chlorophyll a and dissolved organic matter), physicochemical factors (water temperature, Secchi disk depth, dissolved oxygen and pH value), lake morphology (lake area, water depth and drainage ratio), and geoclimatic factors (altitude, wind speed, precipitation and land-use intensity). In addition to the regression and variance partitioning analyses between the concentrations of CO2 and CH4 and environmental factors, the cascading effects of environmental factors on CO2 and CH4 concentrations were further elucidated under four distinct hydrological scenarios, indicating the different driving mechanisms between the scenarios. Lake morphology and geoclimatic factors were the main direct drivers of the carbon concentrations during the rainy season, while they indirectly affected the carbon concentrations via influencing physicochemical factors and further system productivity during the dry season; although lake morphology and geoclimatic factors directly contributed to the carbon concentrations at the vertically mixed and stratified sites, the direct effect of system productivity was only observed at the stratified sites. Our results emphasize that, when estimating carbon emissions from lakes at broad spatial scales, it is essential to consider the influence of precipitation-related seasons and lake mixing regimes.
Collapse
Affiliation(s)
- Xiaoying Yang
- Institute for Ecological Research and Pollution Control of Plateau Lakes, School of Ecology and Environmental Sciences, Yunnan University, Kunming 650500, China; Institute of International Rivers and Eco-Security, Yunnan University, Kunming 650500, China
| | - Yongqiang Zhou
- Taihu Laboratory for Lake Ecosystem Research, State Key Laboratory of Lake Science and Environment, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing 210008, China
| | - Zhirong Yu
- Institute for Ecological Research and Pollution Control of Plateau Lakes, School of Ecology and Environmental Sciences, Yunnan University, Kunming 650500, China
| | - Jingyi Li
- Institute for Ecological Research and Pollution Control of Plateau Lakes, School of Ecology and Environmental Sciences, Yunnan University, Kunming 650500, China
| | - Hong Yang
- Department of Geography and Environmental Science, University of Reading, Whiteknights, Reading RG6 6AB, United Kingdom
| | - Changchun Huang
- School of Geography, Nanjing Normal University, Nanjing 210023, China; Key Laboratory of Virtual Geographic Environment (Nanjing Normal University), Ministry of Education, Nanjing 210023, China
| | - Erik Jeppesen
- Institute for Ecological Research and Pollution Control of Plateau Lakes, School of Ecology and Environmental Sciences, Yunnan University, Kunming 650500, China; Department of Ecoscience, Aarhus University, Aarhus 8000, Denmark
| | - Qichao Zhou
- Institute for Ecological Research and Pollution Control of Plateau Lakes, School of Ecology and Environmental Sciences, Yunnan University, Kunming 650500, China; Yunnan Key Laboratory of Pollution Process and Management of Plateau Lake-Watershed, Yunnan Research Academy of Eco-environmental Sciences, Kunming 650034, China.
| |
Collapse
|
5
|
Ge Y, Gu X, Zeng Q, Mao Z, Chen H, Yang H. Development and testing of a planktonic index of biotic integrity (P-IBI) for Lake Fuxian, China. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2023; 30:105873-105884. [PMID: 37723388 DOI: 10.1007/s11356-023-29818-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/17/2023] [Accepted: 09/06/2023] [Indexed: 09/20/2023]
Abstract
Lake Fuxian has the largest reserves of high-quality water resources in China, and understanding its ecological health status is the basis of its environmental protection. Based on a seasonal field investigation of the plankton community, we established a planktonic index of biotic integrity (P-IBI) evaluation system to assess the lake's ecosystem health. The biological integrity of Lake Fuxian was relatively good during winter and spring, but gradually deteriorated from summer to autumn. Areas with poor biological integrity were mainly distributed near tourist attractions along the lake's west coast. Redundancy analysis (RDA) was performed to explore the relationships between the P-IBI, its selected indicators, and the environmental variables. Water temperature (WT), pH, ammonia nitrogen (NH3-N), and dissolved oxygen (DO) significantly influenced the P-IBI and its selected indicators. NH3-N and DO were significantly positively correlated with the P-IBI, indicating that it could be used as a water quality indicator to indirectly reflect lake biological integrity. We demonstrated that the P-IBI can effectively reflect temporal and spatial variations of biological integrity and could be used as a potential tool to evaluate Lake Fuxian ecosystem health.
Collapse
Affiliation(s)
- You Ge
- State Key Laboratory of Lake Science and Environment, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing, 210008, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Xiaohong Gu
- State Key Laboratory of Lake Science and Environment, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing, 210008, China.
| | - Qingfei Zeng
- State Key Laboratory of Lake Science and Environment, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing, 210008, China
| | - Zhigang Mao
- State Key Laboratory of Lake Science and Environment, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing, 210008, China
| | - Huihui Chen
- State Key Laboratory of Lake Science and Environment, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing, 210008, China
| | - Huiting Yang
- State Key Laboratory of Lake Science and Environment, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing, 210008, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| |
Collapse
|