1. Stock assessment, fishery management systems, and the FMSP Tools -- Summary -- FMSP Stock Assessment Tools Training Workshop Bangladesh 19th - 25th September 2005

2. The management context The legal regime Domestic laws International agreements Management approach to uncertainty Precautionary or adaptive management? Or both? Management scope Single or multi-species? Ecosystem approach? Property rights Use rights? Control rights? Stakeholder roles in management State or community control? Co-management? Fishery scale Industrial or artisanal? Economically important? Management capacity Technical skills, staff, funds? Sections 1.1 and 2.1 – 2.4 Fishery Policy Define management intentions Policy goals and operational objectives (biological, ecological, economic, social, other sectors) Section 2.5.1 Stock assessment process Data/Inputs Intermediate parameters Indicators Reference points Management advice in terms of risk, allowing for uncertainty Chapters 3 and 4 and Parts 2 and 3 Management process Fishery Management Plan Define management standards For each operational objective: Conceptual reference points (target, limit, precautionary) Indicators Technical reference points Set management measures Decision control rules defined by reference points and harvesting strategy Management strategy, comprising one or more control measures (inputs; outputs; technical, ecological etc) Monitoring Control and Surveillance Sections 2.5.2 – 2.5.5 Figure 1.1 A framework for fishery management (FTP 487)

3. The new international legal regime 1992 Convention on Biological Diversity Chapter 17 of UNCED’s Agenda 21 1995 UN ‘Fish Stocks Agreement’ 1995 FAO Code of Conduct for Responsible Fisheries 2002 Johannesburg World Summit on Sustainable Development (WSSD) Section 1.1

4. Examples of goals and op. objectives (3/3) Section 2.3.1 GoalsOperational Objectives BiologicalTo maintain the target species at or above the levels necessary to ensure their continued productivity To maintain the stock at all times above 50% of its mean unexploited level EcologicalTo minimise the impacts of fishing on the physical environment and on non-target (bycatch), associated and dependent species To maintain all non-target, associated and dependent species above 50% of their mean biomass levels in the absence of fishing activities EconomicTo maximise the net incomes of the participating fishers To stabilise net income per fisher at a level above the national minimum desired income SocialTo maximise employment opportunities for those dependent on the fishery for their livelihoods To include as many of the existing participants in the fishery as is possible given the biological, ecological and economic objectives listed above

5. Indicators and reference points Set indicators and reference points for each operational objective An indicator is a specific state, or variable, which can be monitored in a system such as a fishery to give a measure of the state of the system at any given time (Cochrane, 2002) A reference point is an estimated value derived from an agreed scientific procedure and/or an agreed model which corresponds to a state of the resource and/or of the fishery and can be used as a guide for fisheries management Indicators and ‘RP’s should be used in combination to express the operational objectives in ways that can be measured in quantitative fisheries assessments. Section 2.5.2

6. Catch Fishing effort Stock size (biomass) Catch Fishing effort Catch per unit effort (CPUE) or Stock size (biomass) Long term (equilibrium) relationships between Catch, Effort and Stock size Indicators (not directly related!)

7. Risk of alternative reference points Size of Catch Amount of Fishing Maximum Catch - F MSY F crash riskier Point at which species becomes extinct

8. Target or limit reference points? (defining the objectives and control rules) Target RP - aim here, slightly above or below both OK Indicator X Limit RP - avoid danger zone below here Indicator X E.g. Catch rate E.g. spawning stock size

9. B MSY Stock size this year F MSY If B now < B MSY, no fishing allowed next year (danger zone) Fishing mortality rate to be allowed next year If B now > B MSY, fishing allowed at rate of F MSY next year Decision control rules – a simple example Section 2.3.3

10. Precautionary reference points Such points were adopted in response to the UN Fish Stocks Agreement (see point 5 of Annex II), to help make sure that the LRPs are avoided. Define the point at which managers should take action, to avoid the LRPs being reached. The distance by which the precautionary point is removed from the LRP is usually set according to: the uncertainty in the data and the risk tolerance of the manager. Section 2.3.4

11. And ‘precautionary’ reference points... Limit RP Indicator X Take action at the Precautionary RP to avoid the risk of getting to the Limit RP Precautionary RP

12. Setting reference points allowing for uncertainty and risk B lim (B MSY ) B pa (%ileB MSY ) Low risk B pa at ~90 th percentile of B lim distribution

13. B lim (B MSY ) B pa (%ileB MSY ) Higher risk B pa at ~75 th percentile of B lim distribution Setting reference points allowing for uncertainty and risk

14. Management measures 1.Input controls (fishing effort restrictions) 2.Output controls (catch limits) 3.Technical measures (size limits, closed seasons, closed areas etc) 4.Ecological and integrated management Input and output controls often vary between years, depending on harvesting strategy and state of stock Technical measures usually fixed, or updated every few years based on long-term assessments Sections 2.3.5 and 5.4

15. Phase I Where are you now? Phase II Where do you want to be? Phase III How are you going to get there? Time Phase IV How will you know you are there? Plan Do Review New plan Do Review New plan etc Process for developing a management plan See new guidebooks from FMSP project R8468

16. Summary of the management plan PurposeGoalsObjectivesManagement Standards Management Measures IndicatorReference Point Management Measures Decision Control Rules Biological Ecological Social Economic How to quantify the goals and objectives How to achieve the goals and objectives Phase II Where do you want to be? Phase III How are you going to get there?

17. Part 2 - The stock assessment process Collecting fishery data ( Estimating intermediate parameters ) Estimating the current status of the fishery (performance indicators) Estimating technical reference points Providing management advice Monitoring and feedback Chapter 3

18. Stock assessment – collecting fishery data 1.Catch, effort and abundance (CPUE or survey-based or fishing experiments) 2.Catch compositions (length and/or age frequencies to estimate indicator F) 3.Other biological data (maturity, fecundity etc) Section 3.2

19. Estimating intermediate parameters Individual growth rates of fish (e.g. by LFDA) Population growth rate and carrying capacity (e.g. CEDA) Natural mortality rate (e.g. by Pauly equation) Exploitation pattern / gear selectivity (from LF data) Catchability (e.g. by CEDA) Maturity and reproduction (from biological samples) Stock and recruitment (usually from VPA) Not of direct value, but used as inputs to fishery assessments Not constants, may vary over time (e.g. q, K etc) Values will usually be uncertain, so use sensitivity tests Section 3.3

20. Biomass dynamic or analytical? Biomass dynamic models like Schaefer surplus production model used in CEDA and ParFish relate fishery outputs (catch) directly to inputs (effort) Useful where fish are hard to age – used to set quotas and effort Analytical models used in ‘Yield’ and other ‘per recruit’ and dynamic pool approaches include intermediary processes, both biological and fishery (e.g. from LFDA) may be length-based or age-based Needed for management advice on size limits, seasons etc Neither approach is more right or wrong than the other – they are just based on different models and assumptions Section 3.1.3

21. The analytical stock assessment approach using LFDA and Yield LFDA Intermediate parameters L ∞, K, t 0 (growth) Z ( - M ) F now(Eq) Biological data, management controls (size limits, closed seasons etc) Compare to make management advice on F e.g. if F now > F MSY, reduce F by management controls if F now < F MSY, OK Yield Per recruit F max F 0.1 F %SPR With SRR F MSY F transient Data / inputs Assessment tools Indicators Reference points Management advice Length frequency data Figure 4.1

22. The CEDA stock assessment approach (DRP / biomass dynamic model) Figure 4.5 Section 4.5 CEDA Intermediate parameters r, K, q B now Current catch / effort data Compare to make management advice on effort or catches Data / inputs Assessment tools Indicators Reference points Management advice Catch / effort time series B MSY f MSY MSY f now C now

23. The ParFish stock assessment approach Figure 4.10 Section 4.6 ParFish Intermediate parameters r, K, q Current catch / effort data Data / inputs Assessment tools Indicators Reference points Catch / effort time series f now C now Stock assess’t interview data or other priors Preference interview data ParFish f lim C lim Management advice on effort or catch controls, in terms of limit and target levels. Targets (f opt,C opt ) incorporate the preferences of resource users. Limits are based on the risk that B will be reduced below a specified % of K. f opt C opt Management advice B now

24. What do the different FMSP stock assessment tools estimate? (Table 5 of new guide)

25. Which tools can be used to provide advice for different management measures (Table 6 of new guide) See also Section 2.5.5 in FTP 487

26. Data collection training Why collect data? Useful references on data collection ------------------------------------------------------------------------------------ Data commonly used in stock assessments (e.g. using FMSP tools) Data needs of the different SA approaches and FMSP tools ------------------------------------------------------------------------------------ Data collection methods (C/E, LF, biological, ParFish) System design Sampling design Data forms Database systems

27. Data needs of the different approaches / tools Analytical approach (LFDA / Yield) (See FTP 487, Tables 4.1 & 4.3) Catch composition data (either from length frequency data – LF, or ageing studies) Biological data (e.g. size at maturity) Management advice can be produced from just one seasons’ sampling (e.g. from a short time-series sample of LF and biological data) But note some reference points also need long-term Stock-Recruit relationship Biomass dynamic approach and depletion modelling (CEDA) Multi-year time series of catch and effort data, or catch data with a secondary index of abundance (e.g. from a survey) Short-term time series of C & E for depletion modelling of N 0 and q ParFish approach Uses C/E and/or abundance data as with the other biomass dynamic models Due to Bayesian formulation, can also add other sources of information to improve the analysis, e.g. where few or no C/E data are available, and to ‘tune’ the outputs to local users preferences

28. Data collection - Discussion questions What data do you have already that could be used for stock assessment? In FRSS or in local management units? How are catch and effort estimated? How reliable are the data? What effort measures are used for different gear types? Would they provide useful, unbiased indicators of abundance? Do you have any routine survey data that could provide abundance estimates (time series) Do you collect length frequency or age frequency data? How often? For what species, what sample sizes? Do you have biological data needed for analytical methods? How could national (e.g. FRSS) and local management data collection systems be integrated, especially in inland fisheries? Are any data collected in both? What other data should be collected, besides C/E, LF, biological?

29. The management context The legal regime Domestic laws International agreements Management approach to uncertainty Precautionary or adaptive management? Or both? Management scope Single or multi-species? Ecosystem approach? Property rights Use rights? Control rights? Stakeholder roles in management State or community control? Co-management? Fishery scale Industrial or artisanal? Economically important? Management capacity Technical skills, staff, funds? Sections 1.1 and 2.1 – 2.4 Fishery Policy Define management intentions Policy goals and operational objectives (biological, ecological, economic, social, other sectors) Section 2.5.1 Stock assessment process Data/Inputs Intermediate parameters Indicators Reference points Management advice in terms of risk, allowing for uncertainty Chapters 3 and 4 and Parts 2 and 3 Management process Fishery Management Plan Define management standards For each operational objective: Conceptual reference points (target, limit, precautionary) Indicators Technical reference points Set management measures Decision control rules defined by reference points and harvesting strategy Management strategy, comprising one or more control measures (inputs; outputs; technical, ecological etc) Monitoring Control and Surveillance Sections 2.5.2 – 2.5.5 Figure 1.1 A framework for fishery management (FTP 487)