1. Unit 4 Data needs for fisheries management Peter Manning FAO Coastal Fisheries Policy and Planning Course, 28/01/08 – 8/02/08, Apia, Samoa Secretariat of the Pacific Community

2. Informed public to support management Development of fisheries management plans Better management decision-making Tracking performance of management plans Why is fisheries data and analysis important … Fishery data & information Assessment of fishery policy Sound policy development

3. Typical Problems of Fishery Information  Poor quality of information  Limited/non use of information  Limited support for data collection  Shortage of trained personnel and finance

4. Lack of support for data collection Problem self perpetuating... Non-use of information Poor quality of information “Self-reinforcing” cycle of problems

5. What exacerbates data collection problems?  Dispersed, diversified small-scale activities for subsistence purpose – difficult to monitor  Archipelagic nature of small island countries – challenge logistics capacity  Weak linkage between policy/ management objectives and information generated

6. what exacerbates problems...(cont)  Production oriented data collection that give little attention to socio-economic aspects (e.g. income, consumption, employment /participation, gender roles)  Adoption of inappropriate methods of data collection – a valid system in a bigger country in temperate water may not be …

7. We need a data collection system that  Requires less money and people to run  Employs new approaches to meet specific requirements of small-scale multispecies fisheries  Generates relevant and sufficiently accurate data and information a challenge!

8. what do we do? three basic questions:  WHY do we need the information?  For what purposes do you use the information ?  WHAT data need to be collected?  what are the data needed to meet the objectives of information users  We do not need the data that no one uses  HOW best can the required data be collected?

9. fulfills Fishery data & information collection system define Information requirements determine Fishery policy & management objectives Other users’ needs why

10. Some important elements in defining information requirements  Effective consultation mechanism among various stakeholders  Periodical review of information requirements

11. WHAT: A simple exercise to clarify information requirements ?  Step 1: list important policy and management objectives, necessary actions to achieve objectives  Step 2: List data and information required for each objective  Step 3: Compare “the data needed” with “the data currently collected”  Step 4: Identify gaps and irrelevancies

12. An example of simple exercise to clarify information requirements Step 1a: List important policy/management objectives Support sustainable management of coastal fisheries resources Increase export income from the fisheries sector Alleviate poverty in fishing communities etc. Step 1b: List necessary actions Delegate management authorities to communities Zoning of coastal waters Introduction of fishing rights Establishment of marine protected areas Promote value addition to fishery products Access rights to foreign fleet etc.

13. Data/information needed Data items currently collected Types of fish caught Types gears used Production trend of indicator species (e.g. Rabbitfish) No of people harvest resources Occurrence of illegal activities (e.g. poison fishing) Locations of critical habitats (mangroves, sea grass beds, coral reefs) Volume of fish sold at fish markets Sales of fish by grade (Grade A, B and C) No. of registered fishing boats Step 2 & 3: List the data required for each objective and compare them with the data items currently collected Objective 1: Sustainable management of coastal resources

14.  Identify the data gaps  Identify “ irrelevant ” data When operational resources are scarce, can not spare precious resources on “ nice to know ” data while not collecting “ need to know ” data Steps 4: Simple Gap Analysis

15. THANK YOU NEXT A STRATEGY FOR COLLECTING DATA IN DATA- POOR, BUDGET AND MANPOWER LIMITED SITUATIONS