UNIT 8:

1. UNIT 8: Fisheries assessments

2. Fisheries data • Why do we need fisheries data? • FAO (2005): “Information is critical to EAF. It underpins the formulation of national policies, the development of management plans and the evaluation of management progress.” • Fisheries information can be biological, ecological, economic, social or cultural. It can be documented or oral history. • Fisheries information tells us about • Current fishery status • Fishery trends through time • Management effectiveness • All information types should be used where possible (scientific data – traditional knowledge). But remember, we will always be lacking information!

3. Data in the Pacific • Govan (2011): “To date the financial costs of scientific research and monitoring appear to have far exceeded investments in actual management of coastal areas. Using locally available information with simple approaches to community monitoring is a cost effective solution, and collaboration with government or regional technical agencies for generating highly technical and specific information such as stock assessment, is another.” • In the Pacific: • Simple data collection approaches will generally be warranted. • Need to identify approaches in consultation with stakeholders.

4. Data types • Traditional knowledge/anecdotes • simplest form of data • needs stakeholder/community consultation • collect using interviews with community members, especially elders or through community meetings • need wider community involvement • issues and management needs can be determined by consensus

5. Data types • Catch and effort data • Catch = how much is caught (weight or numbers) • Effort = how long fishing; how many fishers; how many nets; length of nets

6. Data types • Catch and effort data • Use these to calculate Catch per Unit Effort (CPUE) = a measure of relative abundance • Examples: • - number of sea cucmbers collected for every hour spent collecting them for each collector; • - weight of a target species caught per hour of line fishing for each collector and each fishing line used • For example: • Catch (C) = 36 kg; Effort (E) = 6 hours; Fishers (F) = 2 • CPUE = (C/E)/F = (36/6)/2 = 3 kg/fisher/hour

7. Data types • Size data • Measure weight and/or size of all fish caught (sub-sample) • Can be done by fishers themselves, landing sites or at markets • Calculate average size: • Average fish length = 253/7 = 36.14 cm

8. Data types • Underwater Visual Surveys (UVS) • In-water (SCUBA or snorkel) surveys of fish/invertebrate numbers and/or habitats • Can collect: • Species numbers per area (density = relative abundance) and sizes • Species diversity • Habitat types and characteristics • This approach requires training and is more resource intensive

9. UVC sample data sheet

10. Data types • Biological samples • Includes gonads and otoliths • Determine sex, maturity, • reproductive status, age & longevity • Derive: • Sex ratios • Size/age at maturity • Spawning seasonality • Age structure • Growth rates • Mortality rates • Longevity • Collecting data of this type requires resources and training. • Careful consideration of resources and management needs is required.

11. Data types • Social/economic data • Why fisheries benefit communities • Can help ensure these benefits continue • Data collected by interviews with community members • Data types include: • # of fishers, dependence on fisheries • income derived from fishing • % of total income derived from fishing • profitability • use of harvested fish • fishers’ involvement in decision-making

14. Activity • DVD: Second half of Module 1 • Activity 8.1: Identify examples of different fisheries data, how collected and how used in fisheries management?

15. Use of CPUE Russ et al (2003) Apo Island,Philippines use of CPUE data

16. Use of size data • Average fish size from local catches of grouper over an 11 year period. • A 35 cm minimum size limit was introduced in 2005 after community concerns of fewer and smaller fish.

17. Use of UVS data Russ et al (2003) Apo Island, Philippines: use of UVS data

18. Indicators • Indicators & reference points • Many data types can be used as an Indicator • An indicator will inform us about changes in the resource we are managing • It will also inform how well particular objectives are being met • Based on the objective the desirable level of the indicator should be identified. This is called the target reference level. • Also, a level below which the indicator goes is undesirable should be identified. This is called the limit reference level. • How well the indicator is perfomring against reference levels is called the performance measure

19. Indicators

20. Use of indicators • An example of the use of UVS data at SPC workshop (see Box 13, SPC, 2010):

21. Other analyses • There are many other more complex analyses that use fishery data to describe populations dynamics including: • Growth • Mortality • Yield per recruit • Biomass dynamic models • Age structured models • These methods require robust data on size, age and catch • Should be used only in data- and resource-rich situations Photo: Dave Welch

22. Unit review • Fisheries data are important to inform about: • Current fishery status • Fishery trends through time • Management effectiveness • Collection of data should be dictated by resource capability • Simple approaches are often needed • Indicators are the data we use to measure fisheries status and management perfromance • There are many different data types:

23. Unit review

24. Assessments • Activity 8.3: In two teams use simulated data to calculate some basic fisheries statistics. Report back on methods, results, and the relevance to management. • DVD: Fish and People Module 5: Fish and people: today and tomorrow • 15 minute personal review: unit review, students to review main concepts of unit in the course notes, contribute any new words (new to them) to their own personal glossary in the back of their notebook (local language equivalent terms should also be recorded where possible)

25. Homework • Answer one of the following: • Describe a method that is used to assess a fishery that you are familiar with and explain how the information is used in management. Do you think it is effective, or do you think that there is a better way to do things? • If you had an unlimited amount of money, design a plan to collect data on a fishery you are familiar with. Once you have your plan, imagine that after a few years you lost the funding to collect all but one piece of the data-what one thing would you keep collecting and why?