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Meng J, Xu F, Yang H, Li X, Zhao P. Exploring microbiome and plankton responses and interactions in the mangrove ecosystem through eDNA and network analysis. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 930:172581. [PMID: 38641112 DOI: 10.1016/j.scitotenv.2024.172581] [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: 01/09/2024] [Revised: 04/11/2024] [Accepted: 04/17/2024] [Indexed: 04/21/2024]
Abstract
The comprehensive analysis of multiple biological communities is essential for assessing diversities within mangrove ecosystems, yet such studies are infrequent. Environmental DNA (eDNA) facilitates the simultaneous exploration of organisms across various levels within a single ecosystem. In this investigation, 16S rRNA, cytochrome C oxidase I (COI), and Mito-fish primers were employed to characterize the microbiome, eukaryotic plankton, and fish communities, along with their intricate interactions, across 24 samples from three Chinese mangrove reservoirs. The resulting dataset encompasses 3779 taxonomic groups (genus level), spanning from the microbiome to vertebrates. Diversity analysis unveiled a higher level of stability in the microbiome community compared to plankton, underscoring the superior site-specificity of plankton. The association analysis revealed that biodiversity was primarily affected by temperature, turbidity, and fluorescent dissolved organic matter (fDOM). Notably, the physicochemical factors, turbidity, and fDOM had a more pronounced impact on the microbiome than on plankton, explaining their distinct sensitivities to site-specific conditions. Network analysis constructed 15 biological interaction subnetworks representing various community connections. The most connected genera in each subnetwork, highly responsive to different environmental factors, could serve as potential indicators of distinct ecosystem states. In summary, our findings represent the first comparison of the response sensitivities of different communities and the construction of their interaction networks in mangrove environments. These results contribute valuable insights into marine ecosystem dynamics and the role of environmental factors in shaping biodiversity.
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Affiliation(s)
- Jie Meng
- Key Laboratory of Experimental Marine Biology, Institute of Oceanology, Chinese Academy of Sciences, Qingdao, China
| | - Fei Xu
- Key Laboratory of Experimental Marine Biology, Institute of Oceanology, Chinese Academy of Sciences, Qingdao, China; Key Laboratory of Breeding Biotechnology and Sustainable Aquaculture, Wuhan, China
| | - Haijie Yang
- School of Marine Science and Engineering, Hainan University, Haikou 570228, China; State Key Laboratory of Marine Resource Utilization in South China Sea, Hainan University, Haikou 570228, China
| | - Xiaoxu Li
- School of Marine Science and Engineering, Hainan University, Haikou 570228, China; State Key Laboratory of Marine Resource Utilization in South China Sea, Hainan University, Haikou 570228, China
| | - Peng Zhao
- School of Marine Science and Engineering, Hainan University, Haikou 570228, China; State Key Laboratory of Marine Resource Utilization in South China Sea, Hainan University, Haikou 570228, China.
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Weiser M, Swanson J, Ghosh N, Hong J, Harringmeyer JP, Kaiser K, Fichot CG. Improving Estimates of Dissolved Organic Carbon (DOC) Concentration from In Situ Fluorescence Measurements across Estuaries and Coastal Wetlands. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2024; 58:9213-9226. [PMID: 38748643 PMCID: PMC11138529 DOI: 10.1021/acs.est.3c10850] [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: 12/31/2023] [Revised: 05/01/2024] [Accepted: 05/02/2024] [Indexed: 05/29/2024]
Abstract
The use of optical proxies is essential to the sustained monitoring of dissolved organic carbon (DOC) in estuaries and coastal wetlands, where dynamics occur on subhour time scales. In situ dissolved organic matter (DOM) fluorescence, or FDOM, is now routinely measured along with ancillary water-quality indicators by commercial sondes. However, its reliability as an optical proxy of DOC concentration is often limited by uncertainties caused by in situ interferences and by variability in DOM composition and water matrix (ionic strength, pH) that are typical at the land-ocean interface. Although corrections for in situ interferences already exist, validated strategies to account for changes in the DOM composition and water matrix in these systems are still lacking. The transferability of methods across systems is also poorly known. Here, we used a comprehensive data set of laboratory-based excitation-emission matrix fluorescence and DOC concentration matched to in situ sonde measurements to develop and compare approaches that leverage ancillary water-quality indicators to improve estimates of DOC concentration from FDOM. Our analyses demonstrated the validity of in situ interference correction schemes, the importance of ancillary water-quality indicators to account for DOM composition and water matrix change, and the good transferability of the proposed methods.
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Affiliation(s)
- Matthew
W. Weiser
- Department
of Earth and Environment, Boston University, Boston, Massachusetts 02215, United States
| | - Jaydi Swanson
- Department
of Earth and Environment, Boston University, Boston, Massachusetts 02215, United States
| | - Nilotpal Ghosh
- Department
of Earth and Environment, Boston University, Boston, Massachusetts 02215, United States
| | - Jiyeong Hong
- Department
of Earth and Environment, Boston University, Boston, Massachusetts 02215, United States
| | - Joshua P. Harringmeyer
- Department
of Earth and Environment, Boston University, Boston, Massachusetts 02215, United States
| | - Karl Kaiser
- Department
of Marine and Coastal Environmental Science, Texas A&M University, Galveston Campus, Galveston, Texas 77553, United States
- Department
of Oceanography, Texas A&M University, College Station, Texas 77843, United States
| | - Cédric G. Fichot
- Department
of Earth and Environment, Boston University, Boston, Massachusetts 02215, United States
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Lai Y, Zhang J, Song Y, Gong Z. Retrieval and Evaluation of Chlorophyll-a Concentration in Reservoirs with Main Water Supply Function in Beijing, China, Based on Landsat Satellite Images. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2021; 18:ijerph18094419. [PMID: 33919307 PMCID: PMC8122327 DOI: 10.3390/ijerph18094419] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/24/2021] [Revised: 04/14/2021] [Accepted: 04/19/2021] [Indexed: 11/16/2022]
Abstract
Remote sensing retrieval is an important technology for studying water eutrophication. In this study, Guanting Reservoir with the main water supply function of Beijing was selected as the research object. Based on the measured data in 2016, 2017, and 2019, and Landsat-8 remote sensing images, the concentration and distribution of chlorophyll-a in the Guanting Reservoir were inversed. We analyzed the changes in chlorophyll-a concentration of the reservoir in Beijing and the reasons and effects. Although the concentration of chlorophyll-a in the Guanting Reservoir decreased gradually, it may still increase. The amount and stability of water storage, chlorophyll-a concentration of the supply water, and nitrogen and phosphorus concentration change are important factors affecting the chlorophyll-a concentration of the reservoir. We also found a strong correlation between the pixel values of adjacent reservoirs in the same image, so the chlorophyll-a estimation model can be applied to each other.
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Affiliation(s)
- Yuequn Lai
- Beijing Key Laboratory of Resource Environment and Geographic Information System, Capital Normal University, Beijing 100048, China; (Y.L.); (Y.S.)
- Key Laboratory of 3D Information Acquisition and Application of Ministry of Education, Capital Normal University, Beijing 100048, China;
- Beijing Laboratory of Water Resources Security, Beijing 100048, China
- Key Laboratory of Mechanism, Prevention and Mitigation of Land Subsidence, MOE, Beijing 100048, China
| | - Jing Zhang
- Beijing Key Laboratory of Resource Environment and Geographic Information System, Capital Normal University, Beijing 100048, China; (Y.L.); (Y.S.)
- Key Laboratory of 3D Information Acquisition and Application of Ministry of Education, Capital Normal University, Beijing 100048, China;
- Beijing Laboratory of Water Resources Security, Beijing 100048, China
- Key Laboratory of Mechanism, Prevention and Mitigation of Land Subsidence, MOE, Beijing 100048, China
- Correspondence:
| | - Yongyu Song
- Beijing Key Laboratory of Resource Environment and Geographic Information System, Capital Normal University, Beijing 100048, China; (Y.L.); (Y.S.)
- Key Laboratory of 3D Information Acquisition and Application of Ministry of Education, Capital Normal University, Beijing 100048, China;
- Beijing Laboratory of Water Resources Security, Beijing 100048, China
- Key Laboratory of Mechanism, Prevention and Mitigation of Land Subsidence, MOE, Beijing 100048, China
| | - Zhaoning Gong
- Key Laboratory of 3D Information Acquisition and Application of Ministry of Education, Capital Normal University, Beijing 100048, China;
- Beijing Laboratory of Water Resources Security, Beijing 100048, China
- Key Laboratory of Mechanism, Prevention and Mitigation of Land Subsidence, MOE, Beijing 100048, China
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Sensitivity Analysis and Optimization of a Radiative Transfer Numerical Model for Turbid Lake Water. REMOTE SENSING 2021. [DOI: 10.3390/rs13040709] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
Remote sensing can detect and map algal blooms. The HydroLight (Sequoia Scientific Inc., Bellevue, Washington, DC, USA) model generates the reflectance profiles of various water bodies. However, the influence of model parameters has rarely been investigated for inland water. Moreover, the simulation time of the HydroLight model increases as the amount of input data increases, which limits the practicality of the HydroLight model. This study developed a graphical user interface (GUI) software for the sensitivity analysis of the HydroLight model through multiple executions. The GUI software stably performed parameter sensitivity analysis and substantially reduced the simulation time by up to 92%. The GUI software results for lake water show that the backscattering ratio was the most important parameter for estimating vertical reflectance profiles. Based on the sensitivity analysis results, parameter calibration of the HydroLight model was performed. The reflectance profiles obtained using the optimized parameters agreed with observed profiles, with R2 values of over 0.98. Thus, a strong relationship between the backscattering coefficient and the observed cyanobacteria genera cells was identified.
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