THE SOUTH WEST INDIAN OCEAN FISHERIES PROJECT SWIOFP

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THE SOUTH WEST INDIAN OCEAN FISHERIES PROJECT (SWIOFP) By HARRISON ONG’ANDA KENYA MARINE AND

THE SOUTH WEST INDIAN OCEAN FISHERIES PROJECT (SWIOFP) By HARRISON ONG’ANDA KENYA MARINE AND FISHERIES RESEARCH INSTITUTE P. O. BOX 81651 MOMBASA, KENYA PREPARED FOR PRESENTATION AT: 1 st Pan-Africa Structured Learning Workshop, 30 Oct – 2 Nov 2006, Nairobi

The SWIOFP has three specific objectives: n n n To identify and study exploitable

The SWIOFP has three specific objectives: n n n To identify and study exploitable offshore fish stocks within the SWIO and to understand the relationship between environmental and anthropogenic impacts, To develop the region’s institutional and human capacity in fisheries and marine science through training and career building, To implement a regional fisheries management programme and associated harmonized legislation in collaboration with the FAO- South West Indian Ocean Fisheries Commission.

SWIOFP Focal Area Countries taking part: Kenya, Tanzania, Mozambique, Republic of South Africa, Seychelles,

SWIOFP Focal Area Countries taking part: Kenya, Tanzania, Mozambique, Republic of South Africa, Seychelles, Mauritius, Comoros, Madagascar, (France)

Key Performance Indicators: Success of the Project will be measured by the following performance

Key Performance Indicators: Success of the Project will be measured by the following performance indicators: n Production and adoption of joint fisheries TDA and SAP by all eight countries participating in project n Formal agreement by all countries on policy, institutional and legal framework governing ecosystem-based management of specific transboundary fisheries n Adoption by all SWIOFP countries of environmental status and stress reduction indicators that define ecosystem health within the framework of a regional management institution legally mandated to undertake this function n Adoption of at least one national or multinational management plan for a specific demersal, pelagic or crustacean fishery by each country participating in the project n Establishment of a regional fisheries databased on new and historic data including repatriated data

Development of themes Theme Country Output Secretariat Mozambique Development; administration Project Appraisal Document Science

Development of themes Theme Country Output Secretariat Mozambique Development; administration Project Appraisal Document Science plan South Africa Integrating the science plan Overall sampling and capacity plan, ship programme Data management Kenya IT, data management systems, 9 point data roadmap, policy, data sharing Procurement Tanzania Procedures for project funding and acquisition, accountability Project management Madagascar Project implementation structures Legal issues France MOU- protocols, agreements

SWIOFP Components 1. Data Atlas and gap analysis (3) 2. Crustacean assessment (2) 3.

SWIOFP Components 1. Data Atlas and gap analysis (3) 2. Crustacean assessment (2) 3. Demersal fishes assessment (2) 4. Assessment of pelagic fishes (3) 5. Monitoring of effort and catchvalue (2) 6. Impacts on non-target resources (3) 7. Strengthening RMU/NM - SWIOFC (2)

SWIOFP Management structures n STRUCTURES q q n PLENARY (Permanent Secretary/Director General) SECRETARIAT (RMU

SWIOFP Management structures n STRUCTURES q q n PLENARY (Permanent Secretary/Director General) SECRETARIAT (RMU – KENYA) NATIONAL FOCAL POINTS THEMES Trio of projects – LME approach q SWIOFP, ASCLME; WIOLa. B

SWIOFP Funding n n PDF- World Bank: US$ 700 k COST= US$ 28. 6

SWIOFP Funding n n PDF- World Bank: US$ 700 k COST= US$ 28. 6 m direct cost q GEF – US$ 12 m q Finance gap= US$ 9. 3 m q Country contributions ~ US$ 100 m in-kind

Project Agreements n n Grant Agreement : q World Bank and Government of Kenya

Project Agreements n n Grant Agreement : q World Bank and Government of Kenya q World Bank and Participating countries Memorandum of Understanding (Mo. U) among the member countries spelling out project management and operations

Time Frame n 2007 q n 2008. . 2011 q q n Data Gap

Time Frame n 2007 q n 2008. . 2011 q q n Data Gap Analysis Science plan strengthening management – eg SWIOFC 2011 ……. q TDA; SAP; Investment

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