范江涛, 陈国宝, 陈作志. 基于栖息地指数的南海北部枪乌贼渔情预报模型构建[J]. 南方水产科学, 2017, 13(4): 11-16. DOI: 10.3969/j.issn.2095-0780.2017.04.002
引用本文: 范江涛, 陈国宝, 陈作志. 基于栖息地指数的南海北部枪乌贼渔情预报模型构建[J]. 南方水产科学, 2017, 13(4): 11-16. DOI: 10.3969/j.issn.2095-0780.2017.04.002
FAN Jiangtao, CHEN Guobao, CHEN Zuozhi. Forecasting fishing ground of calamary in the northern South China Sea according to habitat suitability index[J]. South China Fisheries Science, 2017, 13(4): 11-16. DOI: 10.3969/j.issn.2095-0780.2017.04.002
Citation: FAN Jiangtao, CHEN Guobao, CHEN Zuozhi. Forecasting fishing ground of calamary in the northern South China Sea according to habitat suitability index[J]. South China Fisheries Science, 2017, 13(4): 11-16. DOI: 10.3969/j.issn.2095-0780.2017.04.002

基于栖息地指数的南海北部枪乌贼渔情预报模型构建

Forecasting fishing ground of calamary in the northern South China Sea according to habitat suitability index

  • 摘要: 根据2009年~2014年南海捕捞信息网络获取的南海北部200 m等深线以内近海底拖网渔业数据,结合环境遥感数据,构建南海北部枪乌贼类(Uroteuthis sp.)栖息地指数(habitat suitability index, HSI)模型。选取海表水温(sea surface temperature, SST)、海面高度(sea surface height, SSH)和叶绿素a浓度(chlorophyll-a concentration, CHL)等环境因子,采用一元非线性回归建模,并分月份采用最小二乘法确定各环境因子的权重系数,从而建立南海北部枪乌贼类的栖息地指数综合模型。构建的模型能够有效解释渔场分布与环境要素之间的关系, 并可从模型中推断各环境因子的最适范围和变化趋势;单位捕捞努力量渔获量(catch per unite effect, CPUE)高的渔场主要分布于HSI大于0.5的海域,其他HSI高的海域可能为潜在渔场。对不同因子权重系数的研究发现,叶绿素a浓度是影响渔场分布的重要因素。对模型的验证结果表明,其准确率达到75%以上。该研究表明,基于不同权重系数的HSI模型能够较好地预测南海北部枪乌贼渔场。

     

    Abstract: Based on the data of bottom trawl fishery within shelf area at depth of less than 200 m by a fishery information network from 2009 to 2014, and environmental data obtained from remote sensing, we established the habitat suitability index (HSI) models for calamary (Uroteuthis sp.) in the northern South China Sea. The sea surface temperature, sea surface height and concentration of chlorophyll-a were determined by nonlinear regression modeling. The integrated HSI models for each month, which were established using least square method for assigning weight coefficients to the environmental factors, could explain the relationship between distribution of fishing grounds and environmental factors effectively, and deduce the most suitable range and variation tendency of the environmental factors. High catches per unite effect (CPUE) values of the trawl fishery were mainly in the areas where the HSIs were higher than 0.5, and the other high HSI areas might be potential fishing grounds. Weight coefficients for the environmental factors in the integrated HSI models suggest that chlorophyll-a concentration is the most important factor influencing the distribution of fishing grounds. Verification of the HSI models shows an accuracy of over 75%. The study indicates that the integrated HSI models based on different weight coefficients for environmental factors can better predict fishing grounds of calamary in the northern South China Sea.

     

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