Operational modelling of bigeye tuna (Thunnus obesus) spatial dynamics in the Indonesian region

被引：14

作者：

Lehodey, P. ^{[1
]}

Senina, I ^{[1
]}

Wibawa, T. A. ^{[1
,2
]}

Titaud, O. ^{[1
]}

Calmettes, B. ^{[1
]}

Conchon, A. ^{[1
]}

Tranchant, B. ^{[1
]}

Gaspar, P. ^{[1
]}

机构：

[1] CLS, Marine Ecosyst Dept, Space Oceanog Div, 8-10 Rue Hermes, F-31520 Ramonville St Agne, France

[2] IMRO, Jembrana 82218, Bali, Indonesia

来源：

MARINE POLLUTION BULLETIN | 2018年 / 131卷

关键词：

Bigeye tuna; Ecosystem modelling; Maximum Likelihood Estimation; Operational oceanography; SEAPODYM; Tuna fisheries; INDIAN-OCEAN; CLIMATE-CHANGE; SKIPJACK TUNA; ECOSYSTEM; PACIFIC; POPULATION; FISHERIES; CONFIGURATION; VARIABILITY; IMPACT;

D O I：

10.1016/j.marpolbul.2017.08.020

中图分类号：

X [环境科学、安全科学];

学科分类号：

08 ; 0830 ;

摘要：

With INDESO, Indonesia has implemented a system for the monitoring and management of its tuna resources. Despite increasing catch, very few is known about the dynamics and real abundance of tuna species in the Indonesian waters and adjacent oceanic regions. The SEAPODYM model was implemented in an operational chain of production for the Indonesian region to simulate tuna spatial dynamics in real-time. This challenging objective imposed developing a global scale model at coarse resolution to provide initial and boundaries conditions of the regional model. A parameter optimization approach was used to provide the best solution fitting several hundreds of thousand catch observations, over a long historical simulation at coarse resolution. Then downscaling method and regional modelling at high resolution (1/12 degrees'x day) were validated to produce realtime and forecast on a weekly basis. The architecture of this application, the approach for its parameterization and some key results are presented and discussed.

引用

页码：19 / 32

页数：14

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