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Potential distribution of seagrass meadows based on the MaxEnt model in Chinese coastal waters
Wang, M.; Wang, Y.; Liu, G.; Chen, Y.; Yu, N. (2022). Potential distribution of seagrass meadows based on the MaxEnt model in Chinese coastal waters. Journal of Ocean University of China 21(5): 1351-1361. https://dx.doi.org/10.1007/s11802-022-5006-2
In: Journal of Ocean University of China. Springer: Qingdao. ISSN 1672-5182; e-ISSN 1993-5021
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| Auteurs | | Top |
- Wang, M.
- Wang, Y.
- Liu, G.
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| Abstract |
Seagrass meadows are generally diverse in China and have become important ecosystem with essential functions. However, the seagrass distribution across the seawaters of China has not been evaluated, and the magnitude and direction of changes in seagrass meadows remain unclear. This study aimed to provide a nationwide seagrass distribution map and explore the dynamic changes in seagrass population under global climate change. Simulation studies were performed using the modeling software MaxEnt with 58961 occurrence records and 27 marine environmental variables to predict the potential distribution of seagrasses and calculate the area. Seven environmental variables were excluded from the modeling processes based on a correlation analysis to ensure predicted suitability. The predicted area was 790.09 km2, which is much larger than the known seagrass distribution in China (87.65 km2). By 2100, the suitable habitat of seagrass will shift northwest and increase to 923.62 km2. Models of the sum of the individual family under-predicted the national distribution of seagrasses and consistently showed a downward trend in the future. Out of all environmental variables, physical parameters (e.g., depth, land distance, and sea surface temperature) contributed the most in predicting seagrass distributions, and nutrients (e.g., nitrate, phosphate) ranked among the key influential predictors for habitat suitability in our study area. This study is the first effort to fill a gap in understanding the distribution of seagrasses in China. Further studies using modeling and biological/ecological approaches are warranted. |
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