风场数据在西北太平洋秋刀鱼栖息地预报中的应用适宜性分析

刘瑜; 徐莹; 郑全安

风场数据在西北太平洋秋刀鱼栖息地预报中的应用适宜性分析

刘瑜^{1, 2,},
徐莹^{3, 4, ,},
郑全安⁵

1.
桂林理工大学测绘地理信息学院，广西桂林 541004
2.
上海海洋大学海洋科学学院，上海 201306
3.
国家卫星海洋应用中心，北京 100081
4.
自然资源部空间海洋遥感与应用重点实验室，北京 100081
5.
广东海洋大学海洋与气象学院，广东湛江 524088

基金项目: 国家重点研发计划（2023YFD2401302）；国家自然科学基金（42176184）；桂林理工大学博士后启动基金（RD2400002498）。

详细信息

作者简介:
刘瑜（1985—），女，工程师，研究方向为渔业遥感。 E-mail：liuy@shou.edu.cn

通讯作者:
徐莹（1980—），男，研究员，研究方向为海洋遥感。E-mail：xuying@mail.nsoas.org.cn

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出版历程
- 网络出版日期: 2024-08-19

Suitability analysis of wind data for habitat forecasting of the Pacific saury fishery in northwestern Pacific Ocean

LIU Yu^{1, 2
,},
XU Ying^{3, 4
, ,},
ZHENG Quan-an⁵

1.
College of Geomatics and Geoinformation, Guilin University of Technology, Guilin 541004, China
2.
College of Marine Sciences, Shanghai Ocean University, Shanghai 201306, China
3.
National Satellite Ocean Application Service, Beijing 100081, China
4.
Key Laboratory of Space Ocean Remote Sensing and Application, Ministry of Natural Resources, Beijing 100081, China
5.
College of Ocean and Meteorology, Guangdong Ocean University, Zhanjiang 524088, China

摘要

摘要: 为探讨风场数据在西北太平洋秋刀鱼栖息地预报中的应用适宜性，本文基于中国2019−2020年的6−11月在西北太平洋公海的秋刀鱼生产数据、中法海洋卫星（CFOSAT）共4种风场数据及海洋环境数据，利用广义可加模型构建夏、秋季秋刀鱼栖息地适宜性指数(Habitat Suitability Index, HSI)模型。结果显示：（1）环境变量对单位捕捞渔获量的影响权重表现出明显季节特征，夏、秋季影响最高权重值分别为叶绿素浓度和海表面温度，风速的权重值分别为最低和第二位，风速大小与权重值高低成正比；（2）四组卫星数据夏、秋季的检验精度平均值分别为68.37%和76.65%，最高为秋季CFOSAT达80.94%；（3）HSI高值区域与秋刀鱼实际渔场的空间分布移动方向基本一致，散射计卫星在台风多发的秋季HSI高值区更为突出和集中。应用风速的预报模型在秋季速报中具有优势，能够反映瞬时环境变量的变化对秋刀鱼鱼群洄游和集聚的影响。
- 秋刀鱼渔场 /
- GAM /
- 栖息地预报 /
- CFOSAT /
- 西北太平洋
Abstract: To analysis the suitability of using wind field data for forecasting Pacific saury habitat in the northwest Pacific, this paper use the generalized additive model to fit the habitat suitability index (HSI) for Pacific saury in summer and autumn, based on the Chinese fishery data, environmental data and four types of wind field data included the China-France oceanography satellite (CFOSAT) during June to November in 2019−2020.Result indicates that, (1) Weighted analysis shows distinct seasonal variation of environmental variables on catch per unit effort, with chlorophyll concentration and sea surface temperature having the highest weights in summer and autumn, respectively, while wind speed had the lowest weight and directly proportional to the weight. (2) The average accuracy of the four data in summer and autumn is 68.37% and 76.65%, respectively, and CFOSAT reaching the highest accuracy of 80.94% in autumn. (3) The high-HSI areas are consistent with the fishing grounds of Pacific saury, while the high-value regions of scatter meter in autumn show clear and focus. The advantages of using wind speed on the forecast model in autumn, which can explain the influence of transient variation factors on the migration and aggregation of Pacific saury.
- pacific saury fishing ground /
- GAM /
- Habitat forecast /
- CFOSAT /
- Northwestern Pacific Ocean

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图 1 不同HSI值下的产量比重和平均CPUE（夏季）

Fig. 1 Mean CPUE and percentages of yield under different HSI values (summer)

下载: 全尺寸图片幻灯片

图 2 不同HSI值下的产量比重和平均CPUE（秋季）

Fig. 2 Mean CPUE and percentages of yield under different HSI values (autumn)

下载: 全尺寸图片幻灯片

图 3 夏季秋刀鱼HSI和作业位置(红色圆圈)分布

Fig. 3 The distribution of HSI and CPUE in the fishing ground (red circle) of Pacific saury during summe

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图 4 秋季秋刀鱼HSI和作业位置(红色圆圈)分布

Fig. 4 The distribution of HSI and CPUE in the fishing ground (red circle) of Pacific saury during autumn

下载: 全尺寸图片幻灯片

表 1 $ {\mathrm{S}\mathrm{I}}_{m} $拟合结果

Tab. 1 Result of fitted $ {\mathrm{S}\mathrm{I}}_{m} $

	autumn						summer
parameter	CFOSAT			ASCATB			CFOSAT			ASCATB
parameter	R²	step interval	weight/%	R²	step interval	weight/%	R²	step interval	weight/%	R²	step interval	weight/%
SST	0.97	0.39	29.05	0.95	0.39	32.75	0.75	0.42	16.13	0.73	0.095	12.77
CHLA	0.91	0.037	15.05	0.9	0.035	12.14	0.76	0.0125	31.59	0.74	0.01	39.14
MLD	0.9	3.8	18.3	0.97	3.8	17.38	0.9	2.9	21.13	0.94	2.9	17.96
SLA	0.92	0.0275	15.58	0.92	0.0275	17.63	0.96	0.02	18.45	0.93	0.018	16.61
WIND	0.86	0.5	22.02	0.93	0.45	20.1	0.95	1	12.71	0.97	1	13.51
parameter	CCMP			FUSION			CCMP			FUSION
parameter	R²	step interval	weight/%	R²	step interval	weight/%	R²	step interval	weight/%	R²	step interval	weight/%
SST	0.91	0.45	34.61	0.91	0.45	34.41	0.75	0.095	12.97	0.73	0.095	12.83
CHLA	0.87	0.022	14	0.87	0.022	14.12	0.87	0.025	36.54	0.89	0.025	38.18
MLD	0.98	4	19.13	0.98	4	18.86	0.9	3.5	19.4	0.9	3.5	18.44
SLA	0.92	0.025	15.89	0.92	0.025	15.84	0.96	0.018	18.21	0.96	0.018	18.1
WIND	0.93	0.5	16.37	0.85	0.39	16.77	0.91	0.7	12.87	0.96	0.5	12.75
Note：SST（°C），SLA（m），CHLA（mg/m3），MLD（m），WIND（m/s）

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