Prediction of fishing intensity and trends across South China Sea biogeographic zones
文献类型：期刊论文
| 作者 | He, Bin1,5,6; Yan, Fengqin1,2,5; Su, Fenzhen1,2,5,6; Lyne, Vincent1,3; Tang, Jiasheng1,4 |
| 刊名 | SCIENCE OF THE TOTAL ENVIRONMENT
 |
| 出版日期 | 2023-11-15 |
| 卷号 | 899页码:12 |
| ISSN号 | 0048-9697 |
| 关键词 | Automatic identification system (AIS) Fishing effort GAM prediction South China Sea Spatio-temporal analysis VIIRS DNB |
| DOI | 10.1016/j.scitotenv.2023.165691 |
| 通讯作者 | Yan, Fengqin(yanfq@lreis.ac.cn) ; Su, Fenzhen(sufz@lreis.ac.cn) |
| 英文摘要 | The volume of industrial fishing in the South China Sea ranks among the top global sustainable fisheries concerns of the Food and Agriculture Organization (FAO). To better understand the scale of management challenges, biogeographic zones of the SCS were characterized, and within each a multivariate GAM (General Additive Model) was fitted to predict and map the complete fishing activities from 2017 to 2020. Model variables, some incomplete or with gaps, included: VIIRS DNB night-time light imagery; Global Fisheries Watch (GFW) data; satellite Ocean Colour; Sea Surface Temperature; and bathymetry data. Four biogeographic zones with differing fishing patterns and trends were identified. We used cross-validation and the GAM model's own tuning method for model prediction accuracy determination, which performed well in four biogeographic zones (R2 respectively: 0.62, 0.68, 0.74 and 0.71). High-intensity fishing grounds are mainly distributed in offshore continental shelf areas. From 2017 to 2019, high-intensity fishing grounds were located near the Beibu Gulf of Vietnam, south Vietnam, part of the Gulf of Thailand and the central Java Sea, where fishing effort greater than 50 h exceeded average annual SCS fishing intensity for several years. By season, intensity and extent of fishing in Spring were largest. In 2020, due to the impact of COVID-19, except for Spring, fishing volume generally decreased. Our experimental results provide new insights and an adaptable biogeographic modelling methodology to map the scale and intensity of regional fishing activities more accurately and completely. This more comprehensive database, that takes account of intrinsic biogeographic fishery context, will help improve and strengthen the regulation of fishing activities around the world. |
| WOS关键词 | GENERALIZED ADDITIVE-MODELS ; VIIRS DAY/NIGHT BAND ; SPATIAL-DISTRIBUTION ; SHIP TRACKING ; FISHERIES ; DISTRIBUTIONS ; FRAMEWORK ; LIGHTS ; AREAS ; NIGHT |
| 资助项目 | National key Ramp;D plan[2022YFB3903604] ; Youth Project of Innovation LREIS[YPI001] |
| WOS研究方向 | Environmental Sciences & Ecology |
| 语种 | 英语 |
| 出版者 | ELSEVIER |
| WOS记录号 | WOS:001050827300001 |
| 资助机构 | National key Ramp;D plan ; Youth Project of Innovation LREIS |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/196312]  |
| 专题 | 中国科学院地理科学与资源研究所 |
| 通讯作者 | Yan, Fengqin; Su, Fenzhen |
| 作者单位 | 1.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, State Key Lab Resources & Environm Informat Syst, Beijing 100101, Peoples R China 2.Univ Chinese Acad Sci, Coll Resources & Environm, Beijing 100049, Peoples R China 3.Univ Tasmania, IMAS Hobart, Hobart, Tas 7004, Australia 4.Lanzhou Jiaotong Univ, Fac Geomat, Lanzhou, Peoples R China 5.Nanjing Univ, Collaborat Innovat Ctr South China Sea Studies, Nanjing 210023, Peoples R China 6.Nanjing Univ, Sch Geog & Ocean Sci, Nanjing 210023, Peoples R China |
| 推荐引用方式 GB/T 7714 | He, Bin,Yan, Fengqin,Su, Fenzhen,et al. Prediction of fishing intensity and trends across South China Sea biogeographic zones[J]. SCIENCE OF THE TOTAL ENVIRONMENT,2023,899:12. |
| APA | He, Bin,Yan, Fengqin,Su, Fenzhen,Lyne, Vincent,&Tang, Jiasheng.(2023).Prediction of fishing intensity and trends across South China Sea biogeographic zones.SCIENCE OF THE TOTAL ENVIRONMENT,899,12. |
| MLA | He, Bin,et al."Prediction of fishing intensity and trends across South China Sea biogeographic zones".SCIENCE OF THE TOTAL ENVIRONMENT 899(2023):12. |
入库方式： OAI收割
来源：地理科学与资源研究所
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