Stock assessment for fishery management - using the FMSP Tools FMSP Stock Assessment Tools Training Workshop Bangladesh 19 th - 25 th September 2005

Stock assessment for fishery management - using the FMSP Tools

FMSP Stock Assessment Tools

Training Workshop

Bangladesh

19th - 25th September 2005

Purpose of talk

To show where the FMSP Tools may be used in the process of fishery management

Complements Chapters 3-5 of FAO Fish. Tech. Pap. 487

Chapters 3-5

Content

The stock assessment processData collection for stock assessmentEstimating intermediate parametersEstimating indicatorsEstimating technical reference points Risks of alternative reference pointsProviding stock assessment advice to managers ----------The FMSP Stock assessment toolsWhat do they estimate?What can they provide advice on?How do you select the best tool for the job?

The stock assessment process

Collecting fishery data

( Estimating intermediary parameters )

Estimating the current status of the fishery (indicators)

Estimating technical reference points

Providing management advice

Monitoring and feedback

Chapter 3

The Stock Assessment

Process

Data / Inputs Catch, effort and abundance data Size compositions (catch at age and length frequency data) Biological data (sex, size at maturity, etc) Other data: Social, economic, indigenous knowledge, etc

Assessmenttools

FMSP software

LFDA

Yield

CEDA

ParFish

Other FMSPtools/

guidelines

Age based methods

B&H invariant methods

Multi-species guidelines

Bayesian approaches

Empirical approaches

Other tools

FiSAT

VPA

BEAM4, etc

Intermediate parameters

Used in models to estimate indicators and reference points, e.g.: Individual fish growth rates (K, L∞) Population growth rate and carrying capacity (K) Natural mortality (M), maturity and reproduction (Lm50) Gear selectivity (e.g. Lc50), Catchability (q) Stock recruitment relationship

Fishery Indicators Catch, effort (Cnow, fnow) CPUE, Stock size (Bnow) Fishing mortality rate (Fnow) Others (social, economic,

ecological, governance etc)

Reference Points MSY-based (FMSY, BMSY) Proxies for MSY (e.g. F0.1) For maintaining reproductive

capacity (e.g. F%SSB, F%SPR) Risk-defined (e.g. Ftransient) Multispecies and eco-

system based Economic and social

Management advice Comparison of fishery indicators and reference points to provide

management advice allowing for uncertainty and risk Feedback for control rule management Management projections (short-term and long-term advice) Recognising multiple objectives and management options Figure 1.2

Data collection for stock assessment

1. Catch, effort and abundance (CPUE or survey-based)

2. Catch compositions (length and/or age frequencies -> F)

3. Other biological data (maturity, fecundity etc)

Section 3.2 focuses data needs for stock assessment (as above). See also below from FAO

FAO. 1998. Guidelines for the routine collection of capture fishery data. Prepared at the FAO/DANIDA Expert Consultation. Bangkok, Thailand, 18-30 May 1998. FAO Fish. Tech. Pap. 382. Rome, FAO. 113pp.

Stamatopoulos, C. 2002. Sample based fishery surveys. A technical handbook. FAO Fish. Tech. Pap. 425. Rome, FAO. 132pp.

Section 3.2

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

Catchability (e.g. by CEDA)

Maturity and reproduction

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

Estimating indicators

Catch (Grainger and Garcia method)-------------------------------------------------------------------------------CPUE (approximate indicator of stock size)-------------------------------------------------------------------------------Stock size (overall biomass by CEDA …

or stock size at age by VPA …or relative abundance index by swept area survey)

-------------------------------------------------------------------------------Fishing mortality rate (F at age & year by VPA…

or equilibrium F by catch curves)-------------------------------------------------------------------------------Other performance indicators

(e.g. % of mature fish in catch, others re objectives)

Section 3.4

Estimating technical reference points (1/3)

MSY reference points (LRPs or TRPs)• FMSY, BMSY or the MSY catch (Yield, CEDA or PFSA)

Proxies for MSY reference points• e.g. Fmax, F0.1, where no SR data (from Yield or Gulland eqn)

Reference points for reproductive capacity (use as LRPs)• From a stock-recruitment plot: MBAL, BLOSS, Fmed etc

• From a stock-recr. relationship: B50%R, Fcrash etc

• From biomass per recruit: F20%SPR, F30%SPR (Yield)

• From size limits based on size at maturity

Section 3.5


Risk defined reference points

• Risk is inherently determined by:

1. selection of reference points (e.g. Fcrash is clearly a riskier reference point than FMSY), and

2. distance between Flim and Fpa (percentile point selected) (see next slide)

• Set risk more explicitly using Yield’s Ftransient point:

F giving a specified probability (e.g. 10%) that the %SSB will fall below a specified level (e.g. 20% of unexploited level) during a forward projection (e.g. of 20 years)

Section 3.5

Risks of alternative reference points

Size ofCatch

Amount of Fishing

Maximum Catch - FMSY

Fcrash riskier

Point at which species

becomes extinct

Setting risk-based reference points

Blim

(BMSY)

Bpa

(%ileBMSY)

Low risk Bpa at ~90th percentile of Blim distribution

Setting risk-based reference points

Blim

(BMSY)

Bpa

(%ileBMSY)

Higher risk Bpa at ~75th percentile of Blim distribution


Multi-species and ecosystem-based reference points• Focus on technical interactions and avoidance of bycatch and

discarding problems etc• In CCAMLR, target fisheries may be closed if a bycatch limit is

reached for a bycatch species

Economic and social reference points• E.g. MEY, indices of employment; income or profitability

(resource rent); distribution of benefits (e.g. the percentage of the catch allocated to industrial and artisanal fisheries)

• emphasises tradeoffs in objectives, e.g. between the catch rate and the total catch, and between the economic efficiency and employment.

Section 3.5

Providing management advice

Annual feedback for ‘control rule’ management (where a full decision control system already in place and agreed)

Long-term decision analyses (every few years?)• Making projections: short-term and medium-term advice

(emphasising the current state of the stock, and the likely time it will take to recover – see Yield and CEDA presentations)

• Recognising multiple objectives and management options

present as graphs or decision tables• Providing advice on uncertainty and risk

– using sensitivity tests, – or by estimating risk-based reference points

Section 3.6

A simple decision table formatManagement

Strategy 1(No change to

F)

ManagementStrategy 2

e.g. F up 20%

ManagementStrategy 3e.g. F down

20%

Biological Indicatorse.g. B/BMSY

%SPR

Ecosystem Indicatorse.g. B of bycatch species

Economic Indicatorse.g. Annual catch (% of MSY)

Annual income per fisherVariability in incomes

Means andconfidence

intervals

Social Indicatorse.g. Change in number of fishers

Repeat table for each uncertainty or alternative ‘state of nature’

Indicators

Flow of information between managers and stock assessment advisors in developing and implementing a management plan

See also checklist of SA needs in new document

Information that FisheriesManagers need to provideto Fisheries Scientists

Ph-ase

Stage Information required by Managers fromFisheries Scientists

Decision on what fishery theplan is for

1 Define The unit stock for the target fishery based onthe distribution of fish stocks and fishingactivities

Stakeholders to beconsulted

2 StakeholderAnalysis

Information on the distribution of the fishers etcengaged in the fishery

3 SituationAnalysis

Historical data on fishing effort and fish catch,showing fishery trends.

Approach to precaution anduncertainty

I

4 ManagementApproach

Pros and cons of alternative approaches todecision making, allowing for uncertainty.

5 Purpose6 Goals7 Objectives

Objectives for each goal

II

8 ManagementStandards

Suggest what indicators and reference pointscould be used as targets or limits to measureprogress towards each objective – noting thefeasibility and cost implications of any SAinvolved with each.

Which ManagementMeasures are seen associally politically andtechnically feasible for thisfishery

9 ManagementMeasures

Strategic advice on the expected impact on theindicators of alternative possible managementmeasures, and suggest alternative levels forcontrol measures

Approach to uncertainty anddegree of risk tolerance

10 Control Rules Estimates of uncertainty in the indicators andreference points, and suggested precautionaryadjustments to reference points to allow forrisk and uncertainty.

Resources available formonitoring

III

11 Resources

12 Implement13 Monitoring. Tactical advice updating the estimate of the

selected indicators – this is usually done eachyear – for comparison with the referencepoints and guiding management actions asagreed in the control rules

IV

14 Reviewing Up-dated Stock Assessment advice allowingfor the latest data from the fishery and anychanges in the goals and situation.

Options for alternative SA approaches

Following slides summarise Section 3.1 of FAO Document…

Deterministic or stochastic?

Deterministic models always give the same answer

Stochastic models allow for uncertainty in the inputs and estimate the uncertainty in the outputs….

CEDA, Yield and PFSA software all give stochastic outputs

Section 3.1.2

Biomass dynamic or analytical?

Biomass dynamic models like Schaefer surplus production model used in CEDA and PFSA• 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

Equilibrium or dynamic?

Modern biomass dynamic fitting methods all use non-equilibrium dynamic approaches

Older methods (e.g. plotting CPUE vs f) would always enable some model to be fitted, due to correlation in variables, but often WRONG

Non-equilibrium methods will sometimes fail to find any reasonable solution, e.g. due to lack of contrast in data

Better to recognise limitations of data rather than use an incorrect equilibrium model

Section 3.1.4

Age-based or length-based?

ELEFAN, FiSAT II etc largely promoted length-based methods for tropical fisheries. FMSP LFDA software also length-based

Four FMSP projects, however, have confirmed the benefits of age-based approaches, wherever fish can be aged (e.g. using otolith readings) – more accurate etcAge-based methods now used for deep slope snapper fisheries in FMSP study sites in Seychelles

Length-based methods better where fish really can not be aged (e.g. crustacea), or where ageing is v. expensive

Section 3.1.5, Chapter 10

‘per recruit’ or with recruitment?

Including recruitment in analytical models completely changes results

But stock-recruit relationship expensive to get

So, if using per-recruit models, give first priority to LRPs for biomass per recruit

Section 3.2

0 0.5 1 1.5 2

Fishing mortality rate (F)

Yield-per-R

Yield

SSB-per-R

SSB

The FMSP Stock Assessment Tools

Following FMSP outputs covered in FAO FTP 487

• LFDA software - estimating growth and mortality rates• Reference points from minimal population parameters• Yield software - estimating reference points for YPR etc• Management of multi-species fisheries• CEDA software - biomass dynamic / surplus production models• ParFish software - for data-limited situations & co-management• Empirical methods• Special approaches for inland fisheries

Chapter 4 and Parts 2/3

The analytical

stock assessment

approach using LFDA

and Yield

LFDA


L∞, K, t0 (growth)

Z ( - M ) Fnow(Eq)

Biological data, management controls (size limits, closed seasons etc)

Compare to make management advice on F

e.g. if Fnow > FMSY, reduce F by management controls

if Fnow < FMSY, OK

Yield

Per recruit

Fmax F0.1 F%SPR

With SRR

FMSY Ftransient

Data / inputs

Assessment tools

Indicators

Reference points

Management advice

Length frequency data

Figure 4.1

The CEDA stock

assessment approach

(DRP / biomass dynamic

model)

Figure 4.5 Section 4.5

CEDA


r, K, q

Bnow

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

BMSY fMSY MSY

fnow Cnow

The ParFish stock

assessment approach

Figure 4.10 Section 4.6

ParFish


r, K, q

Current catch / effort data

Data / inputs

Assessment tools

Indicators

Reference points

Catch / effort time series

fnow Cnow

Stock assess’t interview data or other priors

Preference interview data

ParFish

flim Clim

Management advice on effort or catch controls, in terms of limit and target levels. Targets (fopt,Copt) incorporate the preferences of resource users. Limits are based on the risk that B will be reduced below a specified % of K.

fopt Copt

Management advice

Bnow

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

Parameters estimated Available FMSP toolsType Parameters

LF

DA

Yie

ld

CE

DA

Pa

rFis

h

Em

pir

ica

lm

eth

od

s

Be

ve

rto

na

nd

Ho

ltin

va

ria

nts

r, K, q (production model) x xK, L8 , t0 (von Bertalanffy growth) xM (natural mortality rate 1) x x

Intermediate

Z (total mortality rate) xYPR / BPR (yield / biomass per recruit) xYield / biomass (absolute, equilibrium 3) xBt (biomass in year t) x 2 x xNt (numbers in year t) x 2 xFeq (fishing mortality rate, Z-M) x

Indicators

CPUA (catch per unit area) xMSY, fMSY, BMSY, FMSY x x xFmax, F0.1, F0.x, F%SPR (per recruit)FMSY, F%SSB, Fcrash (absolute 3)Ftransient (risk-based)

xxx

flim, Clim (risk-based, biological limits)fopt, Copt (adjusted for ‘preferences’)

xx

Referencepoints

Fmax (max yield per recruit)FMSY (max absolute yield 3)

xx

Which tools can be used to provide advice for different management measures

(Table 6 of new guide)

Management measures

Bio

log

ical

st

ud

ies

Yie

ld

CE

DA

Par

Fis

h

Em

pir

ical

m

eth

od

s

Bev

ert

on

an

d H

olt

in

vari

ants

Fishing effort (‘input’) controls, e.g. limited vessel licensing x1 x x x2 x1 Catch (‘output’) controls, e.g. quotas or ‘TACs’ x3 x x x2 x3 Closed seasons x x x Changing size at first capture (e.g. with minimum legal mesh size or fish size regulations)

x x x

Closed areas x x x 1 In combination with LFDA or some other method of estimating current fishing mortality rate. 2 Per unit area. 3 If biomass also known.

See also Section 2.5.5 in FTP 487

How to select the best tool for the job?

Step 1. Decide the goals, objectives and standards first.

What tools could provide advice about the management controls and standards (indicators and reference points) selected for the fishery?

See Tables 5 and 6 of new SA guide

Note that several tools might be suitable, so...

Step 2. Of the tools and approaches available, what is the most appropriate to the local situation?

See ‘pros and cons’ tables to help decide

See also Box 13 and Table 9 of new guide for process….

Documents

Stock assessment for fishery management - using the FMSP Tools FMSP Stock Assessment Tools Training Workshop Bangladesh 19 th - 25 th September 2005