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Fishing effort alternatives for the management of
demersal fisheries in the western Mediterranean
Paloma Martín, Francesc Maynou, Mariona Garriga-Panisello, John Ramírez, Laura Recasens
Institut de Ciències del Mar, CSIC, Pg. Marítim de la Barceloneta, 37-39. 08003 Barcelona, Spain.
(PM) (Corresponding author) E-mail: paloma@icm.csic.es. ORCID iD: https://orcid.org/0000-0002-5665-2695
(FM) E-mail: maynouf@icm.csic.es. ORCID iD https://orcid.org/0000-0001-7200-6485
(MG) E-mail: mariona.garripa@gmail.com. ORCID iD https://orcid.org/0000-0002-1869-3074
(JR) E-mail: j.gabriel@icm.csic.es. ORCID iD https://orcid.org/0000-0002-0262-8200
(LR) E-mail: laura@icm.csic.es. ORCID iD https://orcid.org/0000-0002-2821-1796
Summary: Management alternatives based on fishing effort for the demersal fisheries in the western Mediterranean were
tested, with the novelty of examining management alternatives at temporal scales smaller than one year. Nine scenarios were
considered on the basis of input control: decrease in the number of fishing days, which may correspond to cessation of activ-
ity of vessels or lower activity of the fleet; and implementation of seasonal closures of one-, two- and three-month duration in
winter, spring, summer and autumn. The approach is based on a multispecies and multigear bioeconomic model. We selected
a total of ten species (Merluccius merluccius, Nephrops norvegicus, Mullus barbatus, Mullus surmuletus, Parapenaeus
longirostris, Lophius piscatorius, Lophius budegassa, Aristeus antennatus, Phycis blennoides and Lepidorhombus boscii)
and seven fleets, defined as a combination of fishing gear (bottom trawl, entangling nets and longline) and fleet segment. A
similar decrease in F is achieved with a 20% reduction of fishing effort (days) or with two- to three-month closures. Maxi-
mum Sustainable Yield (MSY) for all stocks would be achieved only with such a drastic reduction of fishing effort (>80% of
fishing days by the end of the five years of simulation) that, in practice, its application can be considered unrealistic, since it
would represent a very low activity of all fishing fleets over the year.
Keywords: demersal fisheries; fisheries management; fishing effort; western Mediterranean.
Alternativas de esfuerzo de pesca para la gestión de las pesquerías demersales en el Mediterráneo occidental
Resumen: Se investigaron alternativas de gestión, basadas en el esfuerzo de pesca, para las pesquerías demersales del Me-
diterráneo occidental, con la novedad de analizar alternativas de gestión a escalas temporales inferiores a 1 año. Se conside-
raron nueve escenarios basados en control de entrada: disminución en el número de días de pesca, que puede corresponder
a cese de actividad de las embarcaciones o a una menor actividad de la flota; y aplicación de vedas temporales de 1,2 y 3
meses de duración, en invierno, primavera, verano y otoño. Se ha trabajado con un modelo bioeconómico, multi-especies
y multi-arte. Se seleccionó un total de 10 especies (Merluccius merluccius, Nephrops norvegicus, Mullus barbatus, Mullus
surmuletus, Parapenaeus longirostris, Lophius piscatorius, Lophius budegassa, Aristeus antennatus, Phycis blennoides,
Lepidorhombus boscii) y 7 flotas, definidas como una combinación de arte de pesca (arrastre de fondo, redes de enmalle y
palangre) y segmento de flota. Se consigue un mismo descenso en F con una reducción del 20% del esfuerzo de pesca (días
de pesca) o con vedas de 2-3 meses de duración. MSY para todos los stocks se alcanzaría con una reducción tan drástica del
esfuerzo de pesca (>80% de los días de pesca al final de los cinco años de simulación) que, en la práctica, puede considerarse
su aplicación no realista, ya que representaría una actividad muy baja de las flotas durante el año.
Palabras clave: pesquerías demersales; gestión de pesquerías; esfuerzo de pesca; Mediterráneo occidental.
Citation/Como citar este artículo: Martín P., Maynou F., Garriga-Panisello M., Ramírez J., Recasens L. 2019. Fishing ef-
fort alternatives for the management of demersal fisheries in the western Mediterranean. Sci. Mar. 83(4): 293-304. https://
doi.org/10.3989/scimar.04937.29B
Editor: E. Massutí.
Received: April 10, 2019. Accepted: October 24, 2019. Published: November 12, 2019.
Copyright: © 2019 CSIC. This is an open-access article distributed under the terms of the Creative Commons Attribution
4.0 International (CC BY 4.0) License.
Scientia Marina 83(4)
December 2019, 293-304, Barcelona (Spain)
ISSN-L: 0214-8358
https://doi.org/10.3989/scimar.04937.29B
Featured article
294 • P. Martín et al.
SCI. MAR. 83(4), December 2019, 293-304. ISSN-L 0214-8358 https://doi.org/10.3989/scimar.04937.29B
INTRODUCTION
Demersal fisheries in the Mediterranean are typi-
cally multigear and multispecies. These fisheries are
currently managed through national management
plans, although the 2013 reform of the Common Fish-
eries Policy (EU 2013) foresees the application of
multiannual fisheries management plans, coordinated
at supranational level. The European Commission
launched in 2018 a Proposal for a Regulation of the
European Parliament and of the Council establishing
a multiannual plan for fisheries exploiting demersal
stocks in the western Mediterranean (EC 2018), in-
cluding Spanish, French and Italian waters. For FAO
geographical sub-area 6 (GSA 6), which is the area
considered in this study (Fig. 1, northern Spain), this
regulation applies to the main demersal species in the
commercial fishery, viz. to blue and red shrimp Aris-
teus antennatus, deep-water rose shrimp Parapenaeus
longirostris, European hake Merluccius merluccius,
Norway lobster Nephrops norvegicus and red mullet
Mullus barbatus.
Like other Mediterranean fisheries, GSA 6 de-
mersal fisheries are managed by effort limitation and
technical restrictions (e.g. seasonal and spatial clo-
sures; bottom trawl forbidden at <50 m depth; char-
acteristics of the fishing gear: 40-mm square mesh
trawl cod-end) and minimum conservation reference
sizes established for EU Member States (Annex III
of Council Regulation 1967/2006, the Mediterranean
Regulation) and also set at national level (Spain) and
by autonomous governments. These last two include
additional minimum landing sizes, for species not
considered in the EC Mediterranean Regulation (e.g.
anglerfish, Lophius budegassa and Lophius piscato-
rius, four-spot megrim, Lepidorhombus bosci). To
date, no total allowable catch (TAC) is implemented
in demersal fisheries in the Mediterranean. Locally,
additional fishing effort limitation is applied in cer-
tain areas (e.g. in some Aristeus antennatus fishing
grounds and spatial closure in hake recruitment fish-
ing grounds in the northern GSA 6).
The multigear and multispecies character of the
demersal fisheries in the Mediterranean may result in
the exploitation of a given species by different fishing
gears. This is the case in our study area of European
hake exploited by bottom trawl, gillnet and longline,
and of striped red mullet (Mullus surmuletus) exploited
by bottom trawl and trammel net. Moreover, bottom
trawl strongly affects not only the main target species
but also others that are highly vulnerable to bottom
trawling (e.g. the greater forkbeard Phycis blennoides,
by-catch of the red shrimp fishery).
According to standard stock assessments carried
out by expert working groups of the Scientific, Techni-
cal and Economic Committee for Fisheries (STECF)
and the General Fisheries Commission for the Medi-
terranean (GFCM), the current situation in the western
Mediterranean is that some of the main demersal fish-
ing targets are highly overexploited, with, for example,
F/FMSY≥5 in the case of Merluccius merluccius and
Mullus barbatus (GFCM 2017a,b, STECF 2018) and
F/FMSY≥2 in the case of Parapenaeus longirostris,
Aristeus antennatus and Nephrops norvegicus (GFCM
2016, STECF 2017, 2018).
In the decision-making process, it is useful to work
with different management alternatives to examine
how successful they could be in the achievement of
the management targets. To this aim, the Mediterra-
nean Fisheries Simulation Tool (MEFISTO, Lleonart
et al. 2003, Nielsen et al. 2018), a bioeconomic model
specifically developed for Mediterranean fisheries,
was chosen. MEFISTO simulates alternative manage-
ment strategies (i.e. it is not an optimization model).
It includes a population dynamics submodel, which
simulates the dynamics of the stock, and an economic
submodel. It is a useful simulation tool in the context
of mixed fisheries because it shows the response of the
stocks to different management measures. It produces
F and F/FMSY for each simulation scenario (i.e. for the
various management measures that will be simulated),
which can be compared against the stock assessment
results. MEFISTO has been applied preferentially in
Mediterranean demersal fisheries, but also in pelagic
fisheries, e.g. a bottom trawl fishery in the Balearic
Islands (Merino et al. 2015); small-scale and bottom
trawl fisheries in the northern Aegean Sea (Maravelias
et al. 2014); a small-scale lagoon fishery in the west-
ern Mediterranean (Maynou et al. 2014); and a small
pelagic fishery in the northern Adriatic Sea (Silvestri
and Maynou 2009). MEFISTO is an age-based model
that is multispecies and multigear. It can be an advisory
tool, as it allows different management options to be
tested, including those typically used in Mediterranean
fisheries management. For characteristics of the model
and a detailed documentation of MEFISTO, see Lleon-
art et al. (2003), Merino et al. (2015) and Nielsen et al.
(2018).
The aim of this study was to test different manage-
ment alternatives for the demersal fisheries in the west-
ern Mediterranean on the basis of fishing effort, with
the novelty of examining management alternatives at
temporal scales smaller than one year. The approach is
multispecies and multigear. The scenarios considered
include seasonal closures of different durations and a
decrease in the fishing effort of the fleets targeting de-
mersal resources at different levels (bottom trawl and
small-scale fleets). The study area is FAO geographical
sub-area 6, northern Spain (GSA 6, Fig. 1).
MATERIALS AND METHODS
Input data
The fishing activity is carried out near the port base,
five days a week, and the catch is marketed fresh daily
upon arrival of the vessels at the port. The catch of the
demersal fisheries (bottom trawl, entangling nets and
longline) in the study area has steadily decreased in the
last few years, from a peak of around 29000 tonnes in
2006 to 24000 tonnes in 2015, that is, a decrease of
17% according to Data Collection Framework (DCF).
At the same time, the fishing fleet has decreased by
30%, from 698 trawlers, 886 entangling nets (mainly
Demersal fisheries management in the W Mediterranean • 295
SCI. MAR. 83(4), December 2019, 293-304. ISSN-L 0214-8358 https://doi.org/10.3989/scimar.04937.29B
trammel net and also gillnet) and 82 longliners in 2006,
to 457, 649 and 71, respectively, in 2016 (EC Fleet
Register).
A total of 10 species were selected, including the
main target species of the demersal fisheries in GSA
6, as well as the most vulnerable species. The selec-
tion of the species was made taking into account (i)
the five stocks that define the demersal fisheries, ac-
cording to the EC proposal establishing a multiannual
plan for the fisheries exploiting demersal stocks in the
western Mediterranean Sea, GSA 6; (ii) species with a
minimum landing size; (iii) the importance of the spe-
cies in terms of landings and income; and (iv) the spe-
cies’ vulnerability to bottom trawl, based on the results
of a productivity and susceptibility analysis (Patrick
et al. 2009) performed for this purpose (DRuMFISH
2018), which showed the most vulnerable species to
be greater forkbeard, anglerfish, black-bellied angler,
four-spot megrim and European hake.
The species are the following: European hake
Merluccius merluccius, Norway lobster Nephrops
norvegicus, red mullet Mullus barbatus, striped red
mullet Mullus surmuletus, deep-water rose shrimp
Parapenaeus longirostris, anglerfish Lophius pisca-
torius, black-bellied angler Lophius budegassa, blue
and red shrimp Aristeus antennatus, greater forkbeard
Phycis blennoides and four-spot megrim Lepidorhom-
bus boscii. Most of these species are fished exclusively
by bottom trawl, but in some cases the species catch
comes from different gears, each one targeting a given
size (or age) range (e.g. Merluccius merluccius, Mul-
lus barbatus, Mullus surmuletus, Lophius piscatorius
and Lophius budegassa). Bottom trawl catches are in
all cases much higher and sizes (or ages) smaller than
those of the small-scale gears with which the resource
is shared. The selected species represent around 26% of
the demersal fisheries catch in GSA 6 and around 57%
of income from sale at auction in 2015 (DCF). Their
relative importance in the demersal fisheries in GSA 6
is shown in Table 1. The data used in this study come
from the EC Data Collection Framework (DCF 2016)
and stock assessment results. The data taken from the
DCF include landings, discards, length-frequency dis-
tributions and fishing fleet characteristics. MEFISTO
start-up requires the establishment of an initial stock
situation. The model carries out forward projections
starting from the current situation of the stocks and
fleets under different conditions, i.e. the management
options that will be analysed. The input data required
regarding the stock status correspond to the mean value
of the last three years assessed in the reports indicated
in Table 1. Stock assessment results were taken from
the assessments performed by STECF and GFCM
Stock Assessment Working Groups. In some cases, i.e.
when the information in the reports did not allow the
calculation of this three-year mean value or when the
Fig. 1. – Study area: GSA 6, northern Spain. Geographical subareas as established by the General Fisheries Commission for the Mediterranean
(GFCM).
Table 1. – Selected species: landings and income in GSA 6 in 2015 (DCF) and length-weight relationship and growth parameters (VBGC)
used to run MEFISTO, taken from referenced assessments. Lepidorhombus boscii (LDB) had not been assessed previously (ANK, Lophius
budegassa; ARA, Aristeus antennatus; DPS, Parapenaeus longirostris; GFB, Phycis blennoides; HKE, Merluccius merluccius; LDB, Lepi-
dorhombus boscii; MON, Lophius piscatorius; MUR, Mullus surmuletus; MUT, Mullus barbatus; NEP, Nephrops novegicus).
Stockname (t) Landings (%) (k€) Income (%) a b Linf K t0Reference
ANK 858.0 3.5 303.0 0.3 0.0232 2.85 102.0 0.15 –0.05 STECF (2015b)
ARA 689.7 2.8 22052.3 20.9 0.0020 2.51 77.0 0.38 –0.07 STECF (2015a)
DPS 177.4 0.7 2963.5 2.8 0.0031 2.49 45.0 0.39 0.00 STECF (2013a)
GFB 399.3 1.6 1143.8 1.1 0.0034 3.25 49.3 0.31 –0.09 STECF (2013b) (GSA09)
HKE 1778.2 7.3 12404.7 11.8 0.0068 3.04 110.0 0.18 0.00 STECF (2015a)
LDB 84.3 0.3 29.8 0.0 0.0643 2.27 45.6 0.15 –0.59 Landa et al. 2016
MON 179.3 0.7 3999.5 3.8 0.0182 2.93 140.0 0.11 –0.70 STECF (2017)
MUR 226.0 0.9 1309.0 1.2 0.0084 3.12 40.1 0.16 –1.88 GFCM (2015) (GSA05)
MUT 1569.3 6.5 6285.4 6.0 0.0062 3.16 34.5 0.34 –0.14 GFCM (2015)
NEP 361.6 1.5 8957.4 8.5 0.0010 3.08 74.1 0.17 0.00 STECF (2017)
296 • P. Martín et al.
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species had not been previously assessed, these were
generated with pseudo-cohort analysis (VIT; Lleonart
and Salat 1997). Growth parameters (length-weight
relationship and VBGC parameters) were the same as
those used in the assessments (Table 1).
Within a gear, the catch of a species obtained by
each fleet segment is different. The fleet segments as
defined in the DCF are based on the length overall and
are the following: VL0612 (6-12 m), VL1218 (12-18
m), VL1824 (18-24 m) and VL2440 (24-40 m). The
EC Fleet Register specifies the characteristics of each
vessel (http://ec.europa.eu/fisheries/fleet/index.cfm).
According to the overall vessel length, each vessel was
assigned to its corresponding fleet segment. Fleet as
used here corresponds to the combination of gear and
fleet segment. A total of seven fleets were considered,
three bottom otter trawl, two longline and two gillnet
and trammel net. Fishing mortality by species and fleet
was calculated from the total fishing mortality, F, taken
from the stock assessment and the corresponding land-
ings by species and fleet. The DCF economic transver-
sal data were used for this calculation (https://stecf.jrc.
ec.europa.eu/web/stecf/reports/economic).
Recruitment timing by species and month, ex-
pressed in percentage, is shown in Table 2. Landings
in GSA 6 display a marked seasonality, as elsewhere in
the Mediterranean, and the landings peak corresponds
to the recruitment timing. The definition of the recruit-
ment timing for each stock was based on the landings
trend during the year. Fbar used in MEFISTO is the same
as that used in the assessments (Table 3). Fishing mor-
tality at age by fleet for each stock is presented in Table
4, which shows the relative importance of each gear
and fleet segment in the exploitation of each study spe-
cies. Stock numbers of individuals at age (thousands)
resulting from the latest assessments (mean values of
the last three years) are given in Table 5.
Management scenarios and reference points
We considered nine simulation scenarios based on
input control that took into account the following man-
agement measures: a decrease in the number of fishing
days, which may correspond to cessation of activity
of vessels or to lower activity of the fleet, and imple-
mentation of seasonal closures of one-, two- and three-
month duration in winter, spring, summer and autumn
(Table 6). Gear selectivity remained unchanged.
Scenarios 1 and 2 simulate a 20% reduction in
the number of fishing days by the end of five years
of application of the management measure to all fleets
(scenario 1) or to bottom trawl (scenario 2). Scenarios
3 and 4 apply annually to all fleets a 10% and 20% re-
duction, respectively, of the number of fishing days for
five years. In scenario 5 30% reduction of fishing days
is applied annually for five years, and in scenario 6 the
30% reduction will be achieved by the end of the five
years of implementation of the measure. Scenarios 7,
8, and 9 apply seasonal closures of three, two and one
months, respectively (Table 6). When the fleets return
to their activity after the temporal cessation, the num-
ber of fishing days is the same as before the closure.
Scenario 1 corresponds to the Spanish management
plan for the conservation of fishing resources in the
Mediterranean for the period 2013-2017 (BOE 2012),
aimed at reducing at least 20% of the total fishing ef-
fort, measured as number of vessels, horsepower or
tonnage, by the end of the implementation of the plan.
Our scenario 3 is in line with the recently approved
multiannual plan for demersal fisheries in the western
Mediterranean, which calls for a reduction of 40% ef-
fort during the 2019-2024 period. The reduction in the
number of fishing days resulting from the five-year im-
plementation of the scenarios is given in Table 6. TAC
or quota were not considered as possible management
tools because Mediterranean fisheries are traditionally
managed with input measures (effort limitations, tech-
nological restrictions). Table 7 shows the FMSY values
that are used as a reference for calculating the ratio F/
FMSY resulting from the MEFISTO scenarios. F0.1 re-
sulting from yield per recruit analysis was taken as a
proxy for FMSY.
The duration of the simulations was 15 years and
the model initialization, i.e. the time required to rebuild
the spawning stock biomass (SSB), was set to 15 years.
The management scenarios were applied during five
consecutive years after the model initialization. Re-
Table 2. – Recruitment timing, by species and month, expressed in percentage. Species codes as in Table 1.
Month ANK ARA DPS GFB HKE LDB MON MUR MUT NEP
10.24 0.00 0.22 0.00 0.01 0.00 0.23 0.00 0.00 0.00
20.23 0.00 0.28 0.00 0.01 0.00 0.27 0.00 0.00 0.00
30.15 0.00 0.28 0.00 0.01 0.00 0.27 0.00 0.00 0.00
40.00 0.15 0.22 0.00 0.01 0.00 0.23 0.00 0.00 0.00
50.00 0.23 0.00 0.22 0.01 0.23 0.00 0.00 0.00 0.23
60.00 0.24 0.00 0.28 0.01 0.27 0.00 0.00 0.00 0.27
70.00 0.23 0.00 0.28 0.22 0.27 0.00 0.00 0.00 0.27
80.00 0.15 0.00 0.22 0.24 0.23 0.00 0.00 0.00 0.23
90.00 0.00 0.00 0.00 0.24 0.00 0.00 0.30 0.30 0.00
10 0.00 0.00 0.00 0.00 0.22 0.00 0.00 0.40 0.40 0.00
11 0.15 0.00 0.00 0.00 0.01 0.00 0.00 0.30 0.30 0.00
12 0.23 0.00 0.00 0.00 0.01 0.00 0.00 0.00 0.00 0.00
Table 3. – Fbar used in the simulations. Species codes as in Table 1.
Species Age range References
ANK 1 4 STECF (2015b)
ARA 1 3 STECF (2015a)
DPS 2 4 STECF (2013a)
GFB 1 3 STECF (2013b)
HKE 1 3 STECF (2015a)
LDB 1 6 This study
MON 1 4 STECF (2017)
MUR 0 2 GFCM (2015)
MUT 1 2 GFCM (2015)
NEP 2 6 STECF (2017)
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cruitment was assumed constant during the simulation
period. In the Mediterranean fisheries it has not been
possible to establish convincing SSB per recruit rela-
tionships for the main stocks. The economic module
of MEFISTO was disabled because we were interested
in the biological response of the stocks to the manage-
ment scenarios.
The MEFISTO software, which includes full docu-
mentation on the model and a user guide, can be down-
loaded at http://mefisto2017.wordpress.com/
Table 4. – Fishing mortality. F at age by fleet for each stock. Fleet code indicates gear and vessel length (OTB, bottom otter trawl; LLS,
longline; DFN, entangling nets). Species codes as in Table 1.
stock age OTBVL1218 OTBVL1824 OTBVL2440 LLSVL0612 LLSVL1218 DFNVL0612 DFNVL1218
ANK 0 0.004 0.004 0.005 0.000 0.000 0.000 0.000
ANK 1 0.068 0.073 0.086 0.002 0.000 0.006 0.000
ANK 2 0.431 0.465 0.543 0.010 0.000 0.036 0.000
ANK 3 0.384 0.414 0.484 0.009 0.000 0.032 0.000
ANK 4 0.187 0.201 0.235 0.004 0.000 0.016 0.000
ANK 5 0.318 0.344 0.401 0.007 0.000 0.027 0.000
ANK 6 1.314 1.418 1.655 0.030 0.000 0.110 0.000
ANK 7 0.618 0.667 0.779 0.014 0.000 0.052 0.000
ANK 8 0.618 0.667 0.779 0.014 0.000 0.052 0.000
ARA 0 0.000 0.001 0.001 0.000 0.000 0.000 0.000
ARA 1 0.012 0.283 0.476 0.000 0.000 0.000 0.000
ARA 2 0.014 0.315 0.530 0.000 0.000 0.000 0.000
ARA 3 0.011 0.259 0.437 0.000 0.000 0.000 0.000
ARA 4 0.011 0.247 0.415 0.000 0.000 0.000 0.000
DPS 0 0.000 0.000 0.000 0.000 0.000 0.000 0.000
DPS 1 0.007 0.045 0.041 0.000 0.000 0.000 0.000
DPS 2 0.080 0.512 0.465 0.000 0.000 0.000 0.000
DPS 3 0.124 0.791 0.718 0.000 0.000 0.000 0.000
DPS 4 0.151 0.965 0.876 0.000 0.000 0.000 0.000
DPS 5 0.119 0.760 0.690 0.000 0.000 0.000 0.000
DPS 6 0.119 0.760 0.690 0.000 0.000 0.000 0.000
GFB 0 0.002 0.021 0.024 0.000 0.000 0.000 0.000
GFB 1 0.030 0.277 0.306 0.005 0.001 0.000 0.000
GFB 2 0.028 0.254 0.281 0.004 0.001 0.000 0.000
GFB 3 0.005 0.044 0.049 0.001 0.000 0.000 0.000
HKE 0 0.010 0.061 0.064 0.004 0.004 0.002 0.003
HKE 1 0.103 0.655 0.693 0.043 0.047 0.018 0.032
HKE 2 0.123 0.778 0.824 0.051 0.056 0.022 0.039
HKE 3 0.111 0.708 0.749 0.046 0.051 0.020 0.035
HKE 4 0.066 0.422 0.446 0.028 0.030 0.012 0.021
HKE 5 0.066 0.422 0.446 0.028 0.030 0.012 0.021
LDB 0 0.001 0.001 0.000 0.000 0.000 0.000 0.000
LDB 1 0.092 0.091 0.013 0.000 0.000 0.002 0.000
LDB 2 0.205 0.203 0.029 0.000 0.000 0.005 0.000
LDB 3 0.250 0.248 0.036 0.000 0.000 0.006 0.000
LDB 4 0.231 0.229 0.033 0.000 0.000 0.005 0.000
LDB 5 0.171 0.170 0.025 0.000 0.000 0.004 0.000
LDB 6 0.046 0.045 0.007 0.000 0.000 0.001 0.000
MON 0 0.006 0.025 0.017 0.000 0.000 0.001 0.001
MON 1 0.052 0.218 0.146 0.002 0.003 0.006 0.007
MON 2 0.043 0.181 0.121 0.002 0.002 0.005 0.006
MON 3 0.026 0.107 0.072 0.001 0.001 0.003 0.004
MON 4 0.017 0.071 0.048 0.001 0.001 0.002 0.002
MON 5 0.014 0.059 0.039 0.000 0.001 0.002 0.002
MON 6 0.016 0.065 0.043 0.001 0.001 0.002 0.002
MON 7 0.028 0.116 0.077 0.001 0.001 0.003 0.004
MON 8 0.036 0.151 0.101 0.001 0.002 0.004 0.005
MON 9 0.016 0.068 0.045 0.001 0.001 0.002 0.002
MON 10 0.235 0.984 0.658 0.008 0.011 0.027 0.033
MUR 0 0.008 0.019 0.007 0.000 0.000 0.017 0.019
MUR 1 0.053 0.119 0.044 0.001 0.001 0.107 0.121
MUR 2 0.080 0.178 0.066 0.001 0.001 0.161 0.181
MUR 3 0.099 0.220 0.082 0.002 0.001 0.200 0.224
MUR 4 0.069 0.154 0.058 0.001 0.001 0.140 0.157
MUR 5 0.060 0.135 0.050 0.001 0.001 0.122 0.137
MUR 6 0.012 0.026 0.010 0.000 0.000 0.024 0.027
MUT 0 0.004 0.007 0.006 0.000 0.000 0.000 0.000
MUT 1 0.209 0.440 0.331 0.000 0.000 0.022 0.022
MUT 2 0.449 0.943 0.709 0.000 0.000 0.047 0.046
MUT 3 0.280 0.588 0.442 0.000 0.000 0.029 0.029
MUT 4 0.020 0.042 0.032 0.000 0.000 0.002 0.002
NEP 0 0.002 0.010 0.006 0.000 0.000 0.000 0.000
NEP 1 0.053 0.325 0.211 0.000 0.000 0.000 0.000
NEP 2 0.139 0.855 0.556 0.000 0.000 0.000 0.000
NEP 3 0.125 0.766 0.498 0.000 0.000 0.000 0.000
NEP 4 0.118 0.723 0.470 0.000 0.000 0.000 0.000
NEP 5 0.116 0.713 0.463 0.000 0.000 0.000 0.000
NEP 6 0.116 0.713 0.463 0.000 0.000 0.000 0.000
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RESULTS
We simulated the dynamics of the stocks under
nine management strategies; scenario 0 corresponds
to the status quo, the initial situation of the stocks.
The results in terms of Fbar and Fbar/FMSY are shown
in Tables 8 and 9, respectively. As is to be expected,
because all scenarios represent a substantial fishing
effort reduction, Fbar at the end of the simulation is
smaller than at the beginning (status quo). The change
in Fbar is similar in scenarios 1 and 2 (20% reduction
in fishing days for the five-year period of implemen-
tation applied to all fleets or only to bottom otter trawl
fleets), indicating that most of the fishing mortality
applied corresponds to bottom otter trawl. The excep-
tion is striped red mullet, one of the main targets of
small-scale fishing, namely, entangling nets. A simi-
lar decrease in F results from a 20% reduction in the
number of fishing days (scenarios 1 and 2) and from
the implementation of temporal closures of three or
two months (scenarios 7 and 8). The temporal cessa-
tion of activity for one month (scenario 9) leads to a
very slight decrease in fishing mortality.
Since the biological characteristics and the initial
stock status are different, the management target of
Fbar≤FMSY is reached under different scenarios, depend-
ing on the stock. The initial status was of overexploita-
tion in most of the stocks at the start of the simulation
(Table 9, scenario 0). For some of the main bottom
trawl targets, the status is of very high overexploitation.
This is the case of, for example, of Norway lobster, Eu-
ropean hake, black-bellied angler and deep-water rose
shrimp. These stocks would achieve or would be close
to Fbar≤FMSY only under a very drastic effort reduction
of more than 80% of fishing days (scenario 5).
MEFISTO simulation results are shown for sce-
narios 1, 5 and 7 (Fig. 2). These scenarios correspond
to the management measures in the 2013-2017 Span-
ish management plan for the conservation of fishing
Table 5. – Stock numbers at age (thousands) resulting from the latest
assessments (mean values of the last three years). Species codes as
in Table 1.
ages 0 1 2 3 4 5 6 7 8 9 10
ANK 12073 4430 2490 304 56 29 12 1 2 - -
ARA 203197 56406 4690 866 269 - - - - - -
DPS 110227 27784 11712 2867 411 45 - - - - -
GFB 25045 7981 2597 1003 - - - - - - -
HKE 102767 26775 2792 226 34 6 - - - - -
LDB 5154 3518 1973 862 345 142 68 - - - -
MON 905 308 125 65 39 25 17 11 7 4 1
MUR 25885 8954 3376 1250 426 179 85 - - - -
MUT 116359 42682 10042 666 39 - - - - - -
NEP 53856 33138 16596 4459 1445 558 249 - - - -
Table 6. – Simulation scenarios. The total fishing days reduction corresponding to each scenario by the end of the five-year simulation period
is given in the right column.
Scenario Description days reduction
0 Status quo
1 20% reduction of fishing days by the end of 5 years of simulation applied to all fleets. 20%
2 20% reduction of fishing days by the end of 5 years of simulation applied to OTB fleets. 20%
3 10% annual reduction of fishing days during 5 years of simulation applied to all fleets. 41%
4 20% annual reduction of fishing days during 5 years of simulation applied to all fleets. 67%
5 30% annual reduction of fishing days during 5 years of simulation, applied to all fleets 83%
6 30% reduction of fishing days during 5 years of simulation, applied to all fleets. 30%
7 3-month closure applied to OTB.
8 2-month closure applied to OTB
9 1-month closure applied to OTB
Table 7. – FMSY estimated in the assessments. These FMSY values are used as a reference for calculating the F/FMSY ratio resulting from the
MEFISTO scenarios. Species codes as in Table 1.
Species Code Scientific name FMSY(F0.1 YperR) Assessment Method References
ANK Lophius budegasa 0.140 XSA STECF (2015b)
ARA Aristeus antennatus 0.360 XSA STECF (2015a)
DPS Parapenaeus longirostris 0.269 XSA STECF (2013a)
GFB Phycis blennoides 0.780 VIT This study
HKE Merluccius merluccius 0.260 XSA STECF (2015a)
LDB Lepidorhombus boscii 0.903 VIT This study
MON Lophius piscatorius 0.467 VIT This study
MUR Mullus surmuletus 0.663 VIT This study
MUT Mullus barbatus 0.449 XSA GFCM (2015)
NEP Nephrops norvegicus 0.175 XSA STECF (2017)
Table 8. – Fbar by stock under the nine scenarios considered after five consecutive years of implementation of the measures of fishing effort
reduction. Definition of the scenarios in Table 6 and species codes as in Table 1.
Scenarios 0123456789
ANK 0.921 0.737 0.742 0.544 0.302 0.155 0.645 0.698 0.772 0.847
ARA 0.779 0.623 0.623 0.460 0.255 0.131 0.545 0.584 0.649 0.714
DPS 1.561 1.249 1.249 0.922 0.511 0.262 1.093 1.171 1.301 1.431
GFB 0.429 0.343 0.344 0.253 0.140 0.072 0.300 0.323 0.358 0.393
HKE 1.734 1.387 1.418 1.024 0.568 0.291 1.214 1.339 1.470 1.602
LDB 0.494 0.395 0.396 0.291 0.162 0.083 0.346 0.371 0.412 0.453
MON 0.287 0.230 0.232 0.169 0.094 0.048 0.201 0.218 0.241 0.264
MUR 0.395 0.316 0.356 0.233 0.129 0.066 0.276 0.347 0.363 0.379
MUT 1.609 1.287 1.301 0.950 0.527 0.270 1.126 1.224 1.352 1.480
NEP 1.366 1.093 1.093 0.807 0.448 0.230 0.957 1.025 1.139 1.253
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resources (scenario 1), the scenario under which the
status of all the stocks would be Fbar≤ FMSY (scenario
5), and the results from a seasonal closure of three
months (scenario 7, winter). Exploitation is based
on the younger ages, 0 to 2. Since most species are
heavily exploited, the reaction to a decrease in fishing
effort is rapid, despite the different biological charac-
teristics of each species. Scenario 1 shows the gradual
decrease imposed on the fishing days, to reach a 20%
reduction in relation to the starting value at the end of
the five-year period of implementation of the meas-
ure. This reduction runs simultaneously to increasing
catches, biomass and SSB, which remain higher after
the five-year implementation than at the beginning
of the simulation. Scenario 5 shows—along with the
marked decrease in F resulting from the very dras-
tic decrease in the fishing activity—the increase in
catches, biomass and SSB. In scenario 7, the effect of
the implementation of the seasonal closure is evident
during the five years when this measure is imple-
mented, but afterwards, since the fishing effort is the
same as at the beginning, catches, biomass and SSB
gradually decrease to the initial values, and the effect
of the closure is lost in the years following the ces-
sation of the measure. During the implementation of
the management measures, F decreases and SSB in-
creases at a different rate depending on the scenario.
The F and SSB trend during the five years when the
effort reduction is applied is shown in Figure 3 for
scenarios 1 and 5.
Table 9. – Fbar/FMSY under the nine management scenarios considered after five consecutive years of implementation of the measures of fishing
effort reduction. FMSY value is given in Table 7. Definition of the scenarios in Table 6 and species codes as in Table 1.
Scenarios 0123456789
ANK 6.58 5.26 5.30 3.88 2.16 1.11 4.60 4.98 5.52 6.05
ARA 2.16 1.73 1.73 1.28 0.71 0.36 1.51 1.62 1.80 1.98
DPS 5.80 4.64 4.64 3.43 1.90 0.98 4.06 4.35 4.84 5.32
GFB 0.55 0.44 0.44 0.32 0.18 0.09 0.38 0.41 0.46 0.50
HKE 6.67 5.34 5.45 3.94 2.19 1.12 4.67 5.15 5.66 6.16
LDB 0.55 0.44 0.44 0.32 0.18 0.09 0.38 0.41 0.46 0.50
MON 0.61 0.49 0.50 0.36 0.20 0.10 0.43 0.47 0.52 0.57
MUR 0.60 0.48 0.54 0.35 0.20 0.10 0.42 0.52 0.55 0.57
MUT 3.58 2.87 2.90 2.12 1.17 0.60 2.51 2.73 3.01 3.30
NEP 7.81 6.25 6.25 4.61 2.56 1.31 5.47 5.86 6.51 7.16
Fig. 2. – Catches, Fbar, biomass and spawning stock biomass (SSB) trend over 15 years of simulation under the implementation of scenarios
1 (20% reduction of fishing days by the end of five years of simulation applied to all fleets), 5 (30% annual reduction of fishing days during
five years of simulation applied to all fleets) and 7 (three-month closure applied to otter bottom trawl, winter).
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Fig 3. – Fishing mortality (Fbar) and SSB trend during five consecutive years of implementation of scenarios 1 and 5 and in year 6 after the
implementation period of the fishing effort restrictions. Empty circle corresponds to status quo. Trends go from right to left (decreasing F)
and upwards (increasing SSB).
Fig. 4. – Catches by gear and fleet segment (left column, otter bottom trawl; right column, small-scale fishing) after five consecutive years of
implementation of otter bottom trawl seasonal closures of three, two and one months. Note that small-scale fishing gears benefit from these
closures.
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Temporal cessation of fishing activity is a very
widely implemented management measure in the
Mediterranean. In GSA 6 the duration is between one
and two months, depending on the zone, and it is im-
plemented at different times of the year. We examined
the effects of a seasonal closure of bottom otter trawl
for one, two and three months on bottom otter trawl
and small-scale overall catches of the selected stocks
and the influence of the time of the year when the clo-
sure was implemented (Fig. 4). It is worth noting that
the longer the closure, the higher the landings are and,
interestingly, the small-scale fleets clearly benefit
from bottom otter trawl closures. Within bottom otter
trawl, the higher increase corresponds to VL1824 and
VL2440, while in the case of longline and gillnet and
trammel net all segments respond similarly. As for
the most appropriate timing for the seasonal closure,
results of SSB trend, which depend on the recruitment
timing of each stock, suggest that it is in autumn that
the highest SSB is achieved for most of the selected
species (Fig. 5). The species with recruitment to the
fishery that takes place in autumn, or partially in au-
tumn, are those that would take more advantage of
the closure in this season, such as as hake, Norway
lobster, red mullet, striped red mullet and blue and
red shrimp. Autumn would also be an appropriate
period for the closure for the vulnerable species iden-
tified, greater forkbeard and four-spot megrim. SSB
returns to the initial values since the fishing activity
was the same before and after the implementation of
the closure. The effect of the closure was apparent in
the following two, three or even more years, depend-
ing on the species, after the cessation of the five-year
implementation of the measure.
Fig. 5. – SSB trend over 15 years of simulation under the implementation of a three-month closure for the otter bottom trawl fleets in winter,
spring, summer and autumn.
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DISCUSSION
This study is interesting in that it reveals the re-
sponse of the stocks to different management measures
while addressing features characteristic of Mediter-
ranean demersal fisheries, such as the interaction
between fishing gears and competition for common
resources. This is why a management measure applied
to a fishing fleet may affect other fleets not concerned
by the measure. Indeed, the results highlight benefits
for small-scale fishing expressed as increased catches
when bottom trawl effort decreased.
Generally, all species will benefit from a seasonal
reduction of fishing effort. Depending on their biol-
ogy, closures affect the stocks differently. Particular
attention was given to seasonal closures, since this is
a management measure widely applied in the Mediter-
ranean, with differences in duration and in the fleets
concerned. Temporal cessation of the fishing activity
for bottom trawl has been implemented for many years
in GSA 6. These closures have changed over time in
duration, time of year and zone. At present, 2019,
the duration of these closures is one or two months,
depending on the harbour or district within GSA 6,
and they are implemented at different times of year,
mainly in late spring and summer but also in winter
(BOE 2018a, b, c, d). Therefore, seasonal closures
are not applied in autumn, the time of the year most
favourable for SSB recovery for most of the stocks
considered in this study, as the results suggest. As for
the duration, the closure effect on decreasing F would
be limited when the duration is one month. It is worth
noting that a similar decrease in F is achieved with a
20% reduction of fishing effort and with two- to three-
month closures (Table 8, scenarios 1-2 and 7-8). This
observation is a useful tool for managers because it
highlights that different alternatives aimed at reducing
fishing mortality may provide similar results regarding
the conservation of the stocks. With these reductions
in fishing effort, however, several of the studied spe-
cies would be far from achieving the target maximum
sustained yield (MSY). In general, complying with in-
ternational agreements imposing fishing at MSY will
require strong fishing mortality reductions over a short
time-frame (Maynou 2014).
The most recent assessments of demersal stocks
in the western Mediterranean, by GSAs and combi-
nations of GSAs, refer to hake, red mullet, Norway
lobster, deep-water rose shrimp, blue and red shrimp
and giant red shrimp (STECF 2018). They coincide
with the previous stocks assessments used here in that
the Mediterranean assessed stocks are in overexploita-
tion, with the exception of red mullet in the southern
and central Thyrrenian (GSA 10) and deep-water rose
shrimp in the Ligurian and northern Thyrrenian seas
(GSA 9). The European Parliament recently stressed
the lack of consistency between the plans for western
Mediterranean demersal fisheries adopted by France,
Italy and Spain and stated that these plans have proven
ineffective for meeting the objectives set in the Com-
mon Fisheries Policy (European Parliament 2019). Our
results are in line with this observation.
Simulation results of scenario 1, which corresponds
to the fishing effort reduction provided for in the 2013-
2017 Spanish management plan for the conservation
of fishing resources, indicate that the 20% reduction of
fishing effort over the five years leads to an increase in
catches, biomass and SSB and a decrease in F during
the five years, and that afterwards, catches, biomass
and SSB stabilize at a higher level than the initial one
and F remains at a lower level than the initial one. Nev-
ertheless, the implementation of scenario 1 would not
lead to the target Fbar/FMSY=1, although this plan would
represent a major reduction of the fleet, additional to
that implemented in the previous management plan. It
is impossible to achieve MSY simultaneously across
all species. This target would be jointly achieved by the
stocks considered only with such a drastic reduction of
fishing effort (83% of fishing days by the end of the
simulation; scenario 5) that, in practice, its application
seems unrealistic because it would mean a very low
activity throughout the year. This reduction in fishing
effort to achieve MSY is greater than those proposed
for other fisheries. Merino et al. (2015) proposed 71%
reductions for the bottom trawl fishery in the Balearic
Islands (GSA 5), an area where the most important
demersal resources are in a better state than in GSA
6, but still overexploited. Such drastic reductions in
fishing effort might be unnecessary to achieve FMSY if
Mediterranean fisheries are oriented towards selective
fishing practices (Maynou 2014).
Although most of the fishing mortality is exerted
by bottom otter trawl, fishing mortality by small-scale
fisheries, basically trammel net and longline, is not to
be considered negligible. For instance, a 53% reduc-
tion in the fishing effort of the small-scale fisheries in
the Balearic Islands was proposed to keep the stocks
exploited in shallower waters than the bottom trawl
fisheries below their MSY (Quetglas et al. 2016). The
small-scale fisheries change the target species during
the year and usually operate during key life-history
periods, such as when spawners concentrate. This is,
for example, the case the hake fishery in the Gulf of
Lions (GSA 7), where the species was exploited in a
more diversified way than in other areas, the whole
population becoming accessible to fishing. By the
late 1980s, hake was exploited by trawl (196 units),
gillnet (20 units) and longline (13 units). In 1988 the
total annual hake landings in that area amounted to
5882 t (Aldebert and Recasens 1993). Three decades
later, in 2016, the presence in the catch of >40 cm TL
individuals had drastically decreased and the annual
landings amounted to 1029.3 t. The fleet consisted of
75 trawlers, 122 gillnetters and entangling netters and
6 longliners (GFCM 2017a).
The greater forkbeard and four-spot megrim, vul-
nerable species included in the study according to
their stock status (Tables 8 and 9), would not be over-
exploited. Their corresponding fishing mortality was
much lower than that of the main fishing targets (e.g.
hake, red mullet, Norway lobster and deep-water rose
shrimp). They are by-catch species of bottom trawl,
the catch of the small-scale fisheries being negligible.
Four-spot megrim landings are low, although the spe-
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SCI. MAR. 83(4), December 2019, 293-304. ISSN-L 0214-8358 https://doi.org/10.3989/scimar.04937.29B
cies, unlike the greater forkbeard, is well accepted by
consumers. Nevertheless, results show that any meas-
ure aimed at reducing bottom trawl fishing effort based
on the status of the main target stocks would be benefi-
cial for both four-spot megrim and greater forkbeard.
Cook and Heath (2018) propose that the assessments
of target species give a broad indication of the likely
exploitation and biomass trends in by-catch species,
although there will be differences depending on the
species and fisheries concerned.
Two aspects that are important for sound manage-
ment of fishing effort, the spatial distribution of fishing
effort and its re-allocation, have not been dealt with in
this study. This information is currently available for
bottom trawl. However, in order to implement meas-
ures related to the spatial distribution of effort, we also
need to obtain precise knowledge of the target spe-
cies’ distribution throughout their life cycle (e.g. areas
where spawners or recruits concentrate) and to identify
the most intensively exploited fishing grounds for the
implementation of spatial closures or rotation of areas,
for example. Furthermore, it is not generally possible
to assign the specific fishing effort to each species, but
information is available, so in the near future this is
expected to be feasible.
Some issues of the management of fishing effort
are not dealt with in MEFISTO. The model does not
consider the spatial dimension of fisheries, nor can
account for effort distribution within fleet segments
endogenously. To date, very few bioeconomic models
are fully spatially oriented (see review in Nielsen et
al. 2018), but Russo et al. (2014) provides an applica-
tion of the SMART model to demersal fisheries in the
Sicily Strait, which, although highly data-demanding,
is a first step towards an operative model that allows
spatial management of fishing effort to be included as
a tool for the management of fisheries.
TAC or quota were not considered as possible
management tools because demersal fisheries in the
Mediterranean have been, and are, managed with input
measures (effort limitations, technological restrictions).
At present, the implementation of the western Mediter-
ranean multiannual plan for the demersal fisheries pro-
posed by the European Commission (2018) has been
adopted. The European Parliament rejected manage-
ment measures based on TACs because they are not ap-
propriate for the Mediterranean, given the difficulty in
applying this measure in multi-specific fisheries where
stocks are shared with non-EU countries. It would be
preferable to apply technical measures to improve the
state of the stock by reducing the fishing mortality of
the target species where appropriate (European Parlia-
ment 2019).
In conclusion, this study provides relevant input for
the management of demersal resources. For the effect
of temporal closures to persist beyond the five years of
implementation, their duration should be longer than
one month. Autumn would be the most appropriate
season, taking into account the species’ behaviour in
the area. The limitation of the bottom trawl activity
aimed at reducing fishing mortality would also benefit
the small-scale fishing.
ACKNOWLEDGEMENTS
This study was partially funded by the pro-
ject DRuMFISH (EASME/EMFF/2014/1.3.2.4/
SI2.721116). We thank the EC Directorate-General for
Maritime Affairs and Fisheries (Directorate MARE)
for providing the Data Collection Framework data for
GSA 6.
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