基于MaxEnt模型和ArcGIS预测多肋藻在中国海域的适生分布特征
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李国梁(1995–),男,硕士研究生,研究方向为藻类资源与利用.E-mail:898587535@qq.com

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S932

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国家重点研发计划“蓝色粮仓科技创新”《重要养殖藻类种质创制与高效扩繁》项目《重要养殖藻类生态适应性与安全性评价》(2018YFD0901504); 中国水产科学研究院基本科研业务费“创新团队”项目(2020TD27).


Potential geographic distribution of Costaria costata in China based on the MaxEnt Model and ArcGIS
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    摘要:

    基于大型经济海藻的经济和生态价值, 开发具有潜力的新栽培物种是海藻栽培产业健康多样化发展的保障。 多肋藻(Costaria costata)是一种具有很高营养价值及经济价值的大型褐藻, 但并非我国本土物种。本研究采用 MaxEnt 模型预测多肋藻在我国的适生情况, 并探究不同因子对多肋藻孢子体生长的影响, 旨在为开展多肋藻栽培提供支撑。结果表明, 当正则化参数为 1, 训练集与测试集比值为 70 : 30 时, 模型预测性能最佳。基于环境因子的相关性和对模型的贡献率, 筛选出 8 项用于多肋藻适生预测模型的构建, 其中温度与光强对多肋藻自然分布的影响最大, 在光强不低于 4 μmol/(m2 ·s), 月均温度不低于 7 ℃, 多肋藻的适生概率较高。模型显示, 多肋藻在我国的适生区主要分布于黄渤海, 约占该海域面积的 11.32%, 其中 8.08%为边缘适生区和低适生区, 中适生区和高适生区分别占 1.33%和 1.91%, 主要位于辽东湾。表明辽东湾、大连沿海以及山东半岛沿海是多肋藻引种栽培的适宜海域。但辽东湾部分区域的高适生性也预示高入侵风险性, 若开展人工栽培, 应加强生态安全性方面的评估。

    Abstract:

    Based on the economic and ecological value of macroalgae, the recruitment of new cultivated species with potential is necessary for the healthy development of the seaweed cultivation industry. Costaria costata is a brown alga with high nutritional and economic value. This natural seaweed resource is not found in China. In this study, the MaxEnt model and ArcGIS were used to predict the suitability and potential invasion risk of C. costata in China and explore the influence of different factors on the growth of sporophyte, to support the cultivation of C. costata. The prediction model of C. costata distribution was constructed based on correlation analysis between environmental factors, a selection of the global natural distribution points of C. costata, screening of the regulation parameter, and the ratio of the training set to test set on the prediction performance of the model. Results showed that the model performed the best when the regularization parameter was 1 and the ratio of training set to testing set was 70 : 30. The prediction model for C. costata distribution was constructed by eight environmental factors based on the correlation of environmental factors and model contribution rate. Among them, the temperature and light intensity had the most significant influence on the natural distribution. When the light intensity was not less than 4 μmol/(m2 ·s), the annual variation was 52 μmol/(m2 ·s), the monthly mean temperature was not less than 7 ℃, and the annual variation was 27 ℃, indicating the high suitable distribution probability of C. costata. The model showed that the suitable areas of C. costata in China were primarily distributed in the Yellow Sea and Bohai Sea, accounting for 11.32% of the total sea area; among which the marginal biogenic areas of C. costata in Yellow and Bohai Sea are primarily distributed in the coastal areas of Liaodong Bay, the northern coastal areas of Bohai Bay, and the coastal areas from Qingdao to Lianyungang, accounting for 2.99% of the total sea area. The low adaptable areas are primarily distributed in the coastal area of Liaodong Bay, the coastal area of Dalian, and the coastal area of Shandong Peninsula, accounting for 5.09% of the total sea area. The middle adaptable areas are primarily distributed in the southwest coastal area of Liaodong Bay, accounting for 1.33% of the total sea area. The high suitability areas are primarily distributed in the northern and southern coastal area of Liaodong Bay, accounting for 1.91% of the total sea area. The single-factor growth experiment results showed that, when the temperature was 10 ℃, the light intensity was 60 μmol/(m2 ·s), the salinity was 36, the nitrate was 1 mg/L, and the phosphate was 0.1 mg/L, indicating the highly relative growth rate of C. costata sporophyte. Combined with the field investigation, C. costata was found on the floating shelf in Changdao Island in Yantai and Longwangtong Bay in Dalian, consistent with the predicted results. This study showed that the coastal areas of Liaodong Bay, Dalian, and Shandong Peninsula are suitable areas for the introduction and cultivation of C. costata. However, attention should be paid to the risk of high invasion in the northern and southern coastal areas of Liaodong Bay. If artificial cultivation is performed, ecological safety assessment should be strengthened.

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李国梁,汪文俊,李宝贤,姚海芹,孙昕,梁洲瑞,鲁晓萍,刘福利,张朋艳.基于MaxEnt模型和ArcGIS预测多肋藻在中国海域的适生分布特征[J].中国水产科学,2021,28(12):1588-1601
LI Guoliang, WANG Wenjun, LI Baoxian, YAO Haiqin, SUN Xin, LIANG Zhourui, LU Xiaoping, LIU Fuli, ZHANG Pengyan. Potential geographic distribution of Costaria costata in China based on the MaxEnt Model and ArcGIS[J]. Journal of Fishery Sciences of China,2021,28(12):1588-1601

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  • 在线发布日期: 2021-12-27
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