Monitoring the Dynamics of Aquatic Vegetation in a Typical Shallow Lake Using the Water Bloom Index Algorithm—A Case Study in Bao’ an Lake in the Middle Reaches of the Yangtze River
Understanding changes in the distribution and coverage of aquatic vegetation (AV) is of great significance for the restoration of lake ecosystems. In this study, the vegetation and bloom indices (VBI) algorithm were used to interpret submerged aquatic vegetation (SAV), floating/emergent aquatic vege...
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MDPI AG
2024-11-01
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| author | Shixing Song Xiaodong Wu Jianjun Hou Shuang Peng Xiaowen Lin Xuguang Ge Dongming Yan Guiying Lin |
| author_facet | Shixing Song Xiaodong Wu Jianjun Hou Shuang Peng Xiaowen Lin Xuguang Ge Dongming Yan Guiying Lin |
| author_sort | Shixing Song |
| collection | DOAJ |
| description | Understanding changes in the distribution and coverage of aquatic vegetation (AV) is of great significance for the restoration of lake ecosystems. In this study, the vegetation and bloom indices (VBI) algorithm were used to interpret submerged aquatic vegetation (SAV), floating/emergent aquatic vegetation (FEAV), and algal bloom (AB). The dynamics of AV and their influencing factors in Bao’ an Lake, in the middle reaches of the Yangtze River in China, were studied from 2000 to 2023. The results showed that (1) the VBI algorithm can accurately distinguish AV and AB of different life forms with an overall accuracy of 93% and a kappa coefficient of 0.86. (2) Macrophyte coverage decreases. AV grew vigorously in spring, and SAV was the dominant type within it, whereas AV coverage was low in summer, and SAV had no summer species for a long time. In 2000, the coverage of AV was the highest, reaching 64.5%, but a gradual decrease that followed in the coming years finally led to a coverage percentage of less than 5% by 2023. (3) The correlation between SAV coverage and total phosphorus (<i>p</i> < 0.01), total nitrogen (<i>p</i> < 0.05), and water depth/transparency (<i>p</i> < 0.05) in Bao’ an Lake were 0.23, 0.28, and 0.32, respectively. (4) The SAV species experienced three stages: richness (before 2003), monotonicity (2004–2020), and final disappearance (2021–present). This study shows that the coverage of AV in Bao’ an Lake is too low and the number of SAV species is one (2010–now). Therefore, it is necessary to implement measures to improve vegetation coverage and diversity. |
| format | Article |
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| institution | Kabale University |
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| language | English |
| publishDate | 2024-11-01 |
| publisher | MDPI AG |
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| series | Plants |
| spelling | doaj-art-b9b5846f756847d3a5f3166e9cc6a3d92024-11-08T14:39:36ZengMDPI AGPlants2223-77472024-11-011321309010.3390/plants13213090Monitoring the Dynamics of Aquatic Vegetation in a Typical Shallow Lake Using the Water Bloom Index Algorithm—A Case Study in Bao’ an Lake in the Middle Reaches of the Yangtze RiverShixing Song0Xiaodong Wu1Jianjun Hou2Shuang Peng3Xiaowen Lin4Xuguang Ge5Dongming Yan6Guiying Lin7College of Urban and Environmental Sciences, Hubei Normal University, Huangshi 435002, ChinaCollege of Urban and Environmental Sciences, Hubei Normal University, Huangshi 435002, ChinaCollege of Life Sciences, Hubei Normal University, Huangshi 435002, ChinaCollege of Urban and Environmental Sciences, Hubei Normal University, Huangshi 435002, ChinaCollege of Urban and Environmental Sciences, Hubei Normal University, Huangshi 435002, ChinaCollege of Urban and Environmental Sciences, Hubei Normal University, Huangshi 435002, ChinaCollege of Geography and Planning, Chengdu University of Technology, Chengdu 610059, ChinaCollege of Urban and Environmental Sciences, Hubei Normal University, Huangshi 435002, ChinaUnderstanding changes in the distribution and coverage of aquatic vegetation (AV) is of great significance for the restoration of lake ecosystems. In this study, the vegetation and bloom indices (VBI) algorithm were used to interpret submerged aquatic vegetation (SAV), floating/emergent aquatic vegetation (FEAV), and algal bloom (AB). The dynamics of AV and their influencing factors in Bao’ an Lake, in the middle reaches of the Yangtze River in China, were studied from 2000 to 2023. The results showed that (1) the VBI algorithm can accurately distinguish AV and AB of different life forms with an overall accuracy of 93% and a kappa coefficient of 0.86. (2) Macrophyte coverage decreases. AV grew vigorously in spring, and SAV was the dominant type within it, whereas AV coverage was low in summer, and SAV had no summer species for a long time. In 2000, the coverage of AV was the highest, reaching 64.5%, but a gradual decrease that followed in the coming years finally led to a coverage percentage of less than 5% by 2023. (3) The correlation between SAV coverage and total phosphorus (<i>p</i> < 0.01), total nitrogen (<i>p</i> < 0.05), and water depth/transparency (<i>p</i> < 0.05) in Bao’ an Lake were 0.23, 0.28, and 0.32, respectively. (4) The SAV species experienced three stages: richness (before 2003), monotonicity (2004–2020), and final disappearance (2021–present). This study shows that the coverage of AV in Bao’ an Lake is too low and the number of SAV species is one (2010–now). Therefore, it is necessary to implement measures to improve vegetation coverage and diversity.https://www.mdpi.com/2223-7747/13/21/3090VBI algorithmBao’ an Lakeaquatic vegetationcoverageremote sensing |
| spellingShingle | Shixing Song Xiaodong Wu Jianjun Hou Shuang Peng Xiaowen Lin Xuguang Ge Dongming Yan Guiying Lin Monitoring the Dynamics of Aquatic Vegetation in a Typical Shallow Lake Using the Water Bloom Index Algorithm—A Case Study in Bao’ an Lake in the Middle Reaches of the Yangtze River Plants VBI algorithm Bao’ an Lake aquatic vegetation coverage remote sensing |
| title | Monitoring the Dynamics of Aquatic Vegetation in a Typical Shallow Lake Using the Water Bloom Index Algorithm—A Case Study in Bao’ an Lake in the Middle Reaches of the Yangtze River |
| title_full | Monitoring the Dynamics of Aquatic Vegetation in a Typical Shallow Lake Using the Water Bloom Index Algorithm—A Case Study in Bao’ an Lake in the Middle Reaches of the Yangtze River |
| title_fullStr | Monitoring the Dynamics of Aquatic Vegetation in a Typical Shallow Lake Using the Water Bloom Index Algorithm—A Case Study in Bao’ an Lake in the Middle Reaches of the Yangtze River |
| title_full_unstemmed | Monitoring the Dynamics of Aquatic Vegetation in a Typical Shallow Lake Using the Water Bloom Index Algorithm—A Case Study in Bao’ an Lake in the Middle Reaches of the Yangtze River |
| title_short | Monitoring the Dynamics of Aquatic Vegetation in a Typical Shallow Lake Using the Water Bloom Index Algorithm—A Case Study in Bao’ an Lake in the Middle Reaches of the Yangtze River |
| title_sort | monitoring the dynamics of aquatic vegetation in a typical shallow lake using the water bloom index algorithm a case study in bao an lake in the middle reaches of the yangtze river |
| topic | VBI algorithm Bao’ an Lake aquatic vegetation coverage remote sensing |
| url | https://www.mdpi.com/2223-7747/13/21/3090 |
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