Data Collection & Database Program
The Data Collection and Database Program is responsible for the following main duties:
- Obtaining statistical records of the tuna fishery directly from the fishing fleet and processing plants.
- Processing of the data specified in 1, preparation of the corresponding reports, as well as the provision of data in response to requests from CPCs.
- Providing the data necessary for assessing the effects of fishing on the abundance of the stocks to the Stock Assessment Program, as well as for other research activities under other programs at IATTC.
- Activities related to the IATTC Regional Register of Vessels and its maintenance, including the lists and categories established in different resolutions.
Organigram
Staff
Projects
- 1
8 Project(s)
A.1.a | Regular activities of the Bycatch and IDCP Program | Ongoing | |
A.3.a | Conversion of all remaining Visual Basic 6 (VB6) computer programs to Visual Basic Net (VB.net) | Oct 2014-Dec 2021 | |
A.3.b | Develop databases of biological and fisheries parameters to support Ecological Risk Assessment and ecosystem models | Jan 2018-Dec 2023 | |
A.3.c | Series of workshops on improvements in data collection and provision to provide recommendations for updating the data provision Resolution C-03-05 | Jan 2022-Jun 2026 | |
B.1.a | Improving smart species identification tools | Jan 2022-Dec 2023 | |
D.2.a | Pilot study of electronic monitoring (EM) of the activities and catches of purse-seine vessels | Completed | Jan 2018-Mar 2021 |
M.5.b | Reducing losses, and fostering recovery of FADs in the purse-seine fishery in the EPO | May 2021-May 2023 | |
P.1.a | Fulfil requests for development of database and data processing applications for entities outside the IATTC | Ongoing |
Courses
- 1
2 Course(s)
Bibliography
- 1
- Maunder, M.N., Hinton, M.G., Bigelow, K.A., Langley, A.D. 2006. Developing indices of abundance using habitat data in a statistical framework. Bulletin of Marine Science
- Maunder, M.N. and Hinton, M.G. 2006. Estimating relative abundance from catch and effort data, using neural networks. IATTC Special Report