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
Estimating technical reference points (2/3)
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
Estimating technical reference points (3/3)
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
Intermediate parameters
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
Intermediate parameters
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
Intermediate parameters
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….