Workshop on bioeconomic assessment of management measures for small pelagics in GSA17-18

1. “Workshop on bioeconomic
assessment of management
measures”
for small pelagics in GSA17-18
1-3 February 2016
GFCM Headquarters, Rome

2. MANAGEMENT STRATEGY EVALUATION:
METHODOLOGIES USED
​
2. BEMTOOL model:
Integrated Bio-Economic Modelling TOOLs
Maria Teresa Spedicato1, Maria Teresa Facchini1, Paolo
Accadia2 Isabella Bitetto1 and Giuseppe Lembo1​
1COISPA Tecnologia & Ricerca, ​Stazione Sperimentale per lo Studio delle
Risorse del Mare, Bari, Italy
2NISEA, Salerno, Italy

3. Definition Description
Reference points FMSY, Blim, Bpa,
Timeframe to reach
Reference points
2020
Species and fleets
Species for which stock assessments are available
and fleets according to fishing technique/LOA
(fleet segment strata)
Strategy to reach the RPs
or to implement the HCR
1) linear reduction
2) adaptive strategy.

4. Definition Description
Mixed fisheries
Taking into account the nature of mixed fisheries,
evaluate interactions
Amount of reduction Defined on the basis of the results from the
assessments and diagnosis
MSY approach
FMSY range approach (i.e. Fupper and Flower)
Translate reduction of
fishing mortality into
effort reduction
Scenarios of reduction of activity and/or capacity
designed taking into account considerations of
social/management components based on
existing management decisions and feedback
from stakeholders

5. Definition Description
Uncertainty
Applying error estimates on recruitment for the
forecasts.
Multiplicative log-normal error
with mean 0 and standard
deviation 0.3 (the process error.)
Propagated to all the model
indicators.

6. EVALUATION OF SCENARIOS USING MCDA
Utility per group of indicators in BEMTOOL
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7. Stock assessment of small pelagic species at GFCM WGSASP 2015 -
November.
Economic data from DCF complemented by information from National
Authorities
The case study of small pelagics
in GSA 17-GSA18 - inputs to BEMTOOL model

8. The basic information needed for each stock included in the case study:
• Growth parameters (von Bertalanffy, length-weight relationship and life
span);
• Maturity information (maturity ogive by length and maturity range);
• Annual recruitment (numbers by year from stock assessment and
recruitment season);
• Sex ratio at initial stage;
• Natural mortality (from the same assumptions as from stock assessment)
BIOLOGICAL DATA FOR MODELLING

9. The basic information needed:
a. Fishing mortality by age and year (from stock assessment);
b. Catches by fleet segment (from DCF and/or National Authorities);
c. Annual effort by fleet segment (number of vessels, days at sea, GT and
KW) (from DCF and/or National Authorities);
Other inputs for improving the ability of the model to simulate observed
data:
a. Monthly effort (to take into account monthly changes in effort, e.g.
fishing bans)
Information needed for each stock and fleet segment of the case study.
FISHERY DATA FOR MODELLING
Discarding dynamics not considered in this case study

10. 1. Total number of vessels (No
vessels)
2. Vessel tonnage (GT)
3. Engine power (KW)
4. Days at sea (No days)
5. Landings . Target species
6. Total landings (KG)
7. Revenues.Target species 1(€)
8. Total revenues (€)
9. Fuel (energy) costs (€)
10. Energy consumption (Litres)
11. Commercial costs (€)
12. repair and maintenance costs (€)
13. other fixed costs (€)
14. labour costs (crew wage ) (€)
15. depreciation costs (€) and
opportunity (interest) costs (€)
16. other income (e.g. direct
subsidies) (€)
17. No of employees
18. Fixed tangible asset value
(Depreciated replacement) (€)
The information needed to run the economic and social module:
ECONOMIC DATA FOR MODELLING (1)
(from DCF and/or National Authorities)

11. Other inputs that could improve the ability of the model to simulate
observations:
•Working days established by regulations (No days)
•Type of working contract (e.g. income sharing system )
•Minimum national wage
•Volume of imported Target species
•Value of imported Target species
•Landings. Target species by commercial category (e.g length class )
•Revenues. Target species by commercial category
•In-year investments (€)
Information should be provided for each fleet segment of the case study
and at least for five years
ECONOMIC DATA FOR MODELLING (2)
(from DCF and/or National Authorities)

12. Biological Pressure Economic Social
SSB Anchovy Catch Anchovy Revenues Employment
SSB Sardine Catch Sardine
Current Revenues/Break
Even Revenues
Salary
(Wage)
Selection of Indicators for evaluation
In this exercise we can consider the following basic
indicators at whole fleet level and by fleet segment
(depending from the indicator)...

13. Scenario
code
Description
Scenario 1 Status quo - Projecting the current population using recruitment models
and keeping freezed F (e.g. average of the last three years if F is stable)
and f, do not take any additional management action
Scenario 2 If F current is higher than Fmsy (whatever the level of SSB), reduce the
fishing mortality to reach Fmsy (upper) of the more exploited species by
reducing fishing days at fleet segment level, apply a linear reduction to
2020. If current biomass is very low and the difference between F current
and Fmsy low, Biomass is the driving reference point.
Scenario 3 If F current is higher than Fmsy (whatever the level of SSB), reduce the
fishing mortality to reach Fmsy (upper) of the more exploited species by
reducing fishing days and vessels at fleet segment level, apply a linear
reduction to 2020. If current biomass is very low and the difference
between F current and Fmsy low, Biomass is the driving reference point.

14. Scenario
code
Description
Scenario 4 If F current is higher than Fmsy (whatever the level of SSB),
reduce the fishing mortality to reach Fmsy (upper) of the more
exploited species by reducing fishing days at fleet segment level,
apply a non-linear reduction to 2020. If current biomass is very
low and the difference between F current and Fmsy low, SSB is the
driving reference point.
Scenario 5 If F current is higher than Fmsy (whatever the level of SSB),
reduce the fishing mortality to reach Fmsy (upper) of the more
exploited species by reducing fishing days and vessels at fleet
segment level, apply a non-linear reduction to 2020. If current
biomass is very low and the difference between F current and
Fmsy low, SSB is the driving reference point.

15. Scenario
code
Description
Scenario 6 If F current is lower or equal to Fmsy and Bcurrent is lower than
Bpa and in the middle between Bpa and Blim apply the HCR as it
is in the GFCM reccommendation (reduce fishing immediately
50%) for the stock with lower biomass compared to ref SSB
Scenario 7 If F current is lower or equal to Fmsy and Bcurrent is lower than
Bpa (but higher than in the middle between Bpa and Blim) apply
the HCR in the GFCM reccommendation for the stock with lower
biomass compared to ref SSB, using a gradual (linear) reduction
to bring the current SSB at Bpa level (to 2020)

16. ANCHOVY
Reference Point
Value %red. or ratio
between the
current status and
RP
SARDINE
Reference Point
Value %red. or ratio
between the current
status and RP
F current (2014) 0.99 F current (2014) 1.1
Fmsy 0.554 44 Fmsy 0.715 34
B current (2014) 89501 0.97 B current (2014) 208604 0.83
Blim (Blow) 45936 Blim (Blow) 125318
Bpa 91872 Bpa 250636
The management objectives are to reach Fmsy for both stocks, keeping the
biomass at safe levels (≥Bpa).

17. A sensitivity analysis performed using the geometric mean of the
recruitment: 1) the last 3 or 2) the last 10 years of the time series
The geometric mean of the last three years has been retained in the end.
However, as such mean can be affected by the trend in the recruitment in the
last years, if in the near future the recruitment will tend to change from one
year to the next, this should be interpreted as a trigger for a quick management
reaction, i.e. decreasing effort in case recruitment is decreasing.

18. A multiplicative log-normal error with mean 0 and standard deviation 0.3
applied to the geometric mean of recruitment of the last three years .

19. Constraint to achieve Fmsy to 2020, monitoring the level of SSB as a result of
the management action.
In 2015 the management initiatives put in place at National levels were taken
into account, given that what has been done to 2014 (including this year) is
incorporated in the resulting F from the assessment and thus considered as
status quo.
The management initiatives put in place at National levels, as received by
National Authorities were implemented.
Allocation of effort reduction to the fleet segments according to Fmsy target
was thus set from 2016 to 2021, accounting for the above initiatives in 2015
A full compliance of the above initiatives for 2015 was assumed.
Other features of the designed scenarios

20. The current situation of the two stocks (Fmsy and Bpa) was also observed
in the status quo scenarios to 2021

21. 0.5
0.7
0.9
1.1
1.3
1.5
1.7
1.9
2014 2015 2016 2017 2018 2019 2020 2021
Anchovy F/FMSY
Scenario 1-StatusQuo
Scenario 2-LinearRed45onDays
Scenario 3-LinearRed45onVessDays
Scenario 4-NonLinearRed45onDays
Scenario 5-
NonLinearRed45onVessDays
0.5
0.7
0.9
1.1
1.3
1.5
1.7
1.9
2014 2015 2016 2017 2018 2019 2020 2021
Sardine F/FMSY
Scenario 1-StatusQuo
Scenario 2-LinearRed45onDays
Scenario 3-LinearRed45onVessDays
Scenario 4-NonLinearRed45onDays
Scenario 5-NonLinearRed45onVessDays
Results of the modelled reductions of F to the ratio F/FMSY

22. 0.500
0.600
0.700
0.800
0.900
1.000
1.100
1.200
2014 2015 2016 2017 2018 2019 2020 2021
Anchovy SSB/Bpa
Scenario 1-StatusQuo
Scenario 2-LinearRed45onDays
Scenario 3-LinearRed45onVessDays
Scenario 4-NonLinearRed45onDays
Scenario 5-NonLinearRed45onVessDays
0.500
0.600
0.700
0.800
0.900
1.000
1.100
1.200
2014 2015 2016 2017 2018 2019 2020 2021
Sardine SSB/Bpa
Scenario 1-StatusQuo
Scenario 2-LinearRed45onDays
Scenario 3-LinearRed45onVessDays
Scenario 4-NonLinearRed45onDays
Scenario 5-NonLinearRed45onVessDays
Results of the modelled reductions of F to achieve BPA

23. Forecast (status quo to 2021) of SSB
landings and revenues for anchovy
and sardine stocks) in GSAs 17-18

24. Forecast of SSB of anchovy and
sardine in GSA 17 and 18:
comparison among the
management scenarios.
Bpa
Blim

25. Forecast of landings of anchovy and sardine in GSA 17 and 18: comparison among
the management scenarios.

26. Scenario, year
2021
ALL fleets
Salary CR.BER Rev. Emp.
Catch
Anchovy
Catch Sardine
SSB
Anchovy
SSB
Sardine
Status quo (values) 10796 0.92 84697745 2183 31651 82790 90035 213028
Scenario 2 (%) 6.1 6.2 -12.4 0.0 -14.5 -13.5 12.9 15.1
Scenario 3 (%) 17.5 20.9 -11.2 -9.7 -12.2 -13.1 13.1 12.7
Scenario 4 (%) 8.0 8.8 -11.3 0.0 -13.0 -13.1 13.6 16.5
Scenario 5 (%) 21.4 25.8 -9.0 -9.7 -10.2 -10.0 14.6 13.7
MCDA results: evaluation of the overall
utility associated to each management
scenario

27. Oucomes of the BEMTOOL forecasts
 Under status quo scenarios BEMTOOL predicts that stocks
continue to be outside biological safe limits.
 Under the different management scenarios tested, there is
overall an improvement of the status of the stocks (both on SSB
and on F, in relation to agreed reference points), while a
reduction of revenues is observed.
 Under all management scenarios (except status quo), after
5 years there is an improvement on the profitability of the
fisheries nearly for all fleet segments (revenues – costs are
positive)
Conclusions and Recommendations