The European Union Common Fisheries Policy has established a discard ban, which states that fish below a reference size cannot be sold directly for human consumption. In a fishing effort-regulated fishery, the discard ban can result in extra handling, storing and landing costs. In an output-regulated fishery, this policy might also limit the effort levels as all the catches count against the quota. In both cases, this regulation can reduce the economic performance of the companies, even in single-species fisheries. A possible solution is to increase the mesh size, thus retaining fewer small individuals. To study this option, a bioeconomic simulation of a change in the gear selectivity from 100- to 120-mm minimum mesh size (MMS) was performed. The results show that the private perspective (profits) does not change. Furthermore, due to the lower retention of 120 mm MMS, the efficiency of a fishing day was reduced by 5% and 2.5%, from the point of view of capital and labour productivity, respectively. In contrast, gross revenues increased by 1.5% and crew compensation by 2%. Given a societal benefit of this change in the mesh size, this gain could be re-distributed to provide an incentive for selectivity improvements.
La Política Pesquera Común de la Unión Europa ha introducido la prohibición de descartar, estableciendo que todo pescado por debajo de una talla de referencia no puede ser vendido para consumo humano directo. En una pesquería regulada a través de limitaciones del esfuerzo de pesca, la prohibición de descartar puede generar sobrecostes de manipulación, almacenamiento y desembarque adicionales. En una pesquería regulada a través de límites en las capturas, esta política podría incluso limitar los niveles de esfuerzo ya que todas las capturas deben ser deducidas de la cuota. En ambos casos, esta regulación puede reducir el resultado económico de las empresas, incluso en el caso de una pesquería mono-específica. Una posible solución sería aumentar el tamaño mínimo de la malla, y así reducir la retención de los individuos más pequeños. Con el fin de estudiar esta opción, se ha realizado una simulación bioeconómica de un cambio en el tamaño mínimo de la malla de 100 a 120-mm. Los resultados muestran cómo la perspectiva económica privada (beneficios) no varía. Más aun, debido a la menor retención de la malla de 120 mm, la eficiencia de un día de pesca se ve reducida en un 5% y en un 2.5%, desde el punto de vista de la productividad del capital y del trabajo, respectivamente. Por el contrario, los beneficios brutos aumentan un 1.5% y la remuneración al trabajo en un 2%. Debido a la existencia de un beneficio social, la ganancia podría ser redistribuida para así ofrecer un incentivo a esta mejora de la selectividad.
Discards are defined as the proportion of the total organic material of animal origin in the catch that is thrown away or dumped at sea, for whatever reason (
The MCRS has been established as the means of controlling fish mortality by age group. The length of the fish can be used as an indirect indicator of age (
The LO is likely to have some effect on the fishing activity. One of its consequences is the choke species effect (
Reducing the choke effect in a single-species fishery implies reducing the caches of individuals below the MCRS. The first objective of this study was to explore, in consultation with the skippers, the measures that could reduce this choke effect. Governance is key in fishery management, especially when a complex measure such as the LO is implemented. The effects of this measure, its implementation and its legitimacy affect compliance with and attainment of objectives (
The MCRS choke effect is not the only cost that can be anticipated as a result of the LO. The obligation to retain all the catches means that the storing capacity of the vessel(s) must be considered. If its limit is reached within one trip, more trips might be required to land the appropriate amount of fish. Additional crew effort, handling and landing costs (the landings not destined for human consumption have to be treated in a different manner) must also be considered. However, part of these costs can be recovered by selling the catch as non-human consumption products, such as fishmeal.
An impact assessment, the core of the rationale of the LO regulation, was the second objective of this study. The LO should, ideally, create economic incentives to use the new or already available technology to maximize the catches that can be used for human consumption. This should be done by considering the sustainability prescription provided by the Maximum Sustainable Yield (MSY) objective (Article 2.2 of the CFP [
Only a few studies analyse the cost-benefit of a selectivity change (
In an impact assessment, the different dimensions of the system (economic, biological and social) cannot be treated in isolation. Any biological effects on, for example, the productivity of the stock (
To perform a biological and economic impact assessment of changing the mesh size, we used a bioeconomic stochastic simulation model of a hake fishery in the Bay of Biscay. The simulation was based on an age-structured model for hake and focused on a single fleet targeting hake (
The Bay of Biscay (
Many extended and diverse communities of commercial species can be found in the Bay of Biscay and surrounding waters (
Hake is important due to its abundance and economic value. It can live for as long as 20 years and reach a length of 140 cm and a weight of 15 kg. It reaches its sexual maturity at around three to four years of age. It is usually found at a depth of between 75 and 400 m. It tends to stay close to the seabed in daytime, leaving it to swim up the water column only at night.
There are two (management) stocks of hake in Atlantic EU waters. The northern stock (the stock targeted by the fleet analysed) is found in the North Sea, Skagerrak, on the Atlantic coast of the UK and Ireland, and in the Bay of Biscay.
The management of hake in the Bay of Biscay is based on a TAC and quota system. An MCRS of 27 cm is in place for the Atlantic waters (30 cm for in Kattegat and Skagerrak the MCRS is of 30 cm and in the Mediterranean of 20). Hake is normally a part of a mixed fishery with other demersal species such as anglerfish and megrim and pelagic species such as mackerel and horse mackerel.
The Spanish bottom pair trawlers operating in the Bay of Biscay are an exception to this multispecies characteristic. In the years 2011-2013, this fleet consisted of 10 vessels (5 fishing units, each consisting of two paired vessels) operating exclusively in the Bay of Biscay, with an average length of 38 m. Their average freezer storage capacity was 8600 (4300 per vessel) 12-kg boxes (the characteristic box type used by this fleet). On average, their fishing effort was distributed among 50 trips (per fishing unit and year). They captured approximately 8% of the total northern stock and 25% of hake catches in the Bay of Biscay.
The vessels in this group use a very high vertical-opening bottom net (MMS of 100 mm) and target mainly hake. This species accounts for 90% of the landings and approximately the same proportion of income (
Before assessing the impact of a change in the MMS, the extent of the size change must be chosen. The five skippers who took part in the survey requested that the MMS be increased from 100 to 120 mm.
It should also be noted that this selectivity level is specific for hake, and the changes do not affect the catches of other species. This might be a problematic assumption in the multispecies fisheries, but the fleet analysed here targets only hake, so; this assumption should not significantly affect the results.
To simulate the selectivity change, it was considered that the catchability (q) can be decomposed into a product of the selectivity of the gear used and a parameter that incorporates the vulnerability, accessibility and availability of the fish, as described in the paper of
qa,ms=Sa,ms ra , | (1) |
where Sa,m,s stands for the selectivity of fish of age a related to the MMS; ms and ra stand for the factors affecting catchability and are not related to the MMS. If the catchability and selectivity at age a for a given MMS are known, ra can be calculated by applying Equation 1. It can be used afterwards to estimate the hypothetical catchability for the MMS, for which age selectivity is known.
Selectivity of the fish length for pair trawlers with 100-mm MMS has been estimated by The Spanish Oceanography Institute (
r(L)=exp(a+bL)/ (1+ exp(a+bL)) , | (2) |
where a and b are the parameters to be estimated. The results of the estimation were a=–6.53 and b=0.2. This curve has the property that the length for 50% retention r(L50) is such that r(L50)=0.5 and therefore L50 =–a/b.
However, there are no studies providing the length selectivity for hake for pair trawlers with 120-mm MMS. Furthermore, several factors affect the size selection of the towed fishing gears for a given mesh size. These are the spatial and seasonal variations (
To overcome these difficulties, the percentage change in L50 between 80- and 100-mm MMS was calculated. It was used as a proxy of the L50, keeping the shape of the curve (parameter b of Eq. 2) constant.
The results showed that the L50 was 22.6 cm with an 80-mm MMS 34.6 cm with a 100-mm MMS. Consequently, it could be inferred that the L50 for a 120-mm MMS was 40.8 cm. This last value was within the range of the expected L50 (from 22 to 43 cm, according to
To fit the results into the age-structured dynamics of the simulation model, the selectivity-at-length curves were transformed to age using the Von Bertalanffy growth model (the Stock Synthesis III assessment model; Methot and Wetzel 2013) employed by the ICES assessment working group for hake (
A model coupled in all its dimensions (economic, biological and social) is required to perform the impact assessment of the change in the MMS. Economic results are related to the stock productivity, which can change depending on the retention pattern. Moreover, the stock productivity is also related to fishing effort. For example, if one fleet stops fishing, the overall productivity of the stock will change, simply because of the average selectivity changes.
The model used was FLBEIA (
Pair trawlers were economically conditioned using AZTI data sources obtained through the Data Collection Framework of the EU (
Variable | Pair trawlers | Units | Variable | Pair trawlers | Units |
---|---|---|---|---|---|
Fuel Cost | 1240 | €/days | Capital Cost | 64438 | €/vessel/year |
Crew Cost | 33% | % of the fishing income | Depreciation | 20952 | €/vessel/year |
Variable Cost | 875 | €/days | Max. days | 150 | days |
Fixed Cost | 15449 | €/vessel/year | Employment (full-time equivalent) | 11 | per vessel |
Several types of costs were defined: those changing with the effort (variable and fuel costs), those changing with the value of landings (crew costs); and those changing with the number of vessels (fixed, capital and depreciation costs). There are also other costs associated with the LO. Under this regulation, each trip retains more fish than without LO. Therefore, more storage boxes might be required, and the refrigeration facilities of the vessels must be suitable for storing them.
The storage requirements per trip were calculated for boxes of 12 kg. If the maximum number of boxes that can be stored in a fishing unit is higher than the needs, the additional costs will be zero. If not, the additional trips must be evaluated at a variable cost (changing with the effort, if more trips can be made to catch the same amount) or at the market price if the catch is smaller (more trips cannot be made due to a physical limit).
All fleets that cause hake fishing mortality were included in the model. For the projection, the fleet fishing effort was kept constant, except for the Spanish pair trawlers operating in the Bay of Biscay, as explained below.
The relationship between the hake population and the catch was analysed in biomass. The catch and effort relationship was based on a Schaefer production model (
ha=qaEXa | (3) |
Equation 3 describes the catch of hake (h) at age (a) as a function of its catchability coefficient (q), which was also calculated at the age level, the biomass of hake (X) at the age level and the effort exercised by the fleet on fishing days (E). Throughout the projection, the pair-trawler effort was limited by the TAC share of hake. This share was calculated (based on the average for 2011-2013) as approximately 8%, as mentioned previously. It was assumed that the remaining hake was caught by the “other” fleets, according to their catch share.
Hake ex-vessel prices were obtained from the sale sheets of the fleet using averages from 2009 to 2013 (
Code | Common name | Scientific name | Stock | Age | Average price |
---|---|---|---|---|---|
HKE | Hake | VI, VII, VIIIabd | <3 | €2.27 | |
HKE | Hake | VI, VII, VIIIabd | 3 | €2.16 | |
HKE | Hake | VI, VII, VIIIabd | 4 | €2.07 | |
HKE | Hake | VI, VII, VIIIabd | >4 | €2.89 | |
OTH | Others | Others | - | all | €1.96 |
The simulation used age-structured dynamics, and the data necessary to condition the model were taken from the ICES assessment working group report and from the results of the assessment modelling conducted by this group (
Stochasticity was only introduced in the S/R of hake. A lognormal multiplicative error around the S/R curve (with a median equal to one and a coefficient of variation equal to the one observed in the historical period) was used. Two hundred and fifty iterations were run. No more uncertainties were considered.
The reference point for hake was FMSY, which in the case of hake is 0.27 (
The “other” stock accounts for the catches of species different from hake. These catches were considered proportional to the effort deployed (using Eq. 3) by the fleet, assuming an arbitrary “large” added biomass. This assumption was expected to have a low impact on the results, given that hake constitutes 90% of the catch of this fleet.
Perfect implementation of the management advice was assumed. In the projection the LO started in the year 2016, and no exemptions to this LO were introduced.
Selectivity changes are likely to alter the productivity of the stock. Even if the removal quantities are similar, their different age compositions could change the age distribution in the stock. In particular, young individuals tend to have higher growth rates (
Though the evolution of SSB and fishing mortality did not change during the simulation (
In this fleet, the necessary effort to catch its share of hake (i.e. the quota) was not constrained by the capacity. As a result of the obligation to retain all the catches, extra storage was required (10% increase in the number of boxes). During an average trip, these fishing units catch approximately 30 t of fish (2500 boxes), with a maximum of 59 t (4900 boxes). The refrigeration capacity of one vessel is around 50 t (4000 boxes); the fishing unit has a refrigeration capacity of 100 t. This shows that the refrigeration storage capacity (meeting the safety requirements) does not limit the fishing effort within one trip.
Thus, the number of trips required to catch the TAC share were the same for 100- and 120-mm MMS. It also meant that the overall catches of hake were the same for these two mesh sizes (
However, fishing with 120-mm MMS nets required an increased level of effort (
Figure 5A shows that the catches of hake are the same for the two MMSs. The landings of hake destined for human consumption are higher for 120- than for 100-mm MMS (
The simulations showed that GVA was larger for 120-mm MMS than for 100-mm MMS. This causes an increase in the gross revenue, which is higher for 120-mm MMS net use (
The other component of GVA is the capital compensation, which can be illustrated using profit as an indicator. Profit does not change when the 120-mm MMS is used (
The productivity of fishing effort should also be considered. Capital productivity, measured in terms of the gross profit per fishing day, was 5% lower for 120-mm MMS than for 100-mm MMS (
In summary, the results show that increasing the MMS from 100 to 120 mm does not change the stock biotic potential, at least when this increase is implemented in the fleet studied. However, the productivity of the effort is reduced, in terms of both catches per unit of effort and the GVA and profit per unit of effort. The total capital compensation was unchanged, so there were no private economic incentives to implement the MMS change. The MMS increase produced more hake landings above MCRS and higher average ex-vessel prices of hake, which created an increase in revenues and GVA.
As pointed out by
Before an economic impact assessment, an evaluation of the effects of a change in selectivity on the biotic potential of the stock should be conducted. This evaluation should be integrated and coupled with the economic analysis. The result of the simulation presented here shows that, from the fishery community point of view, there would be no evolutionary change due to the new selection pattern. The study of Hilborn and Minte-Vera (
The simulation did not deal with the impact on the ecosystem. Gear-related conservation measures assume that the escaping fish survive and support the relevant population. However, there are no reliable estimates of post-capture survival of hake (
In the analysed fleet, an increase in MMS reduced the efficiency of the system (in terms of catch per unit of effort). The desired effect of the regulation is to change the size distribution by reducing the catches of individuals under MCRS. This change should also increase the average price. This was, indeed, the case in our simulation, although this result was the consequence of the change in the MMS and not its cause (
In the simulation presented here, a rise in selectivity implies a lower retention of individuals below the MCRS of hake. The overall effect is that more of the landings are destined for human consumption but at the cost of increased fishing effort. When more effort is exerted, two possible limits have to be considered. The first limit is a capacity ceiling (no more fishing days are available, or no more vessels can be made). We did not observe this problem in the current simulation. The second potential limit is associated with the species caught, of which some might be constrained by the LO. In the case analysed, the fleet is “almost” a single-species fleet, so such situation is unlikely. The results show that the fleet using an increased-MMS gear needs more effort to catch their hake quota. No onboard storage limits were observed. However, the storage problems might occur in different fleets, and an increase in the number of trips might be necessary to land the same amount of fish for human consumption.
The observed 2% increase in gross revenues clearly differs from the predicted general 10% to 15% reduction (
Finally, the results showed that the GVA and human consumption hake supply increased after the enlargement of the gear MMS. This means that society has the potential capacity to compensate the productivity loss of the owners of the labour and the capital.
Here, we performed a bioeconomic impact assessment of an MMS increase for a case study in the Atlantic Area. It should be noted, however, that the MCRS regulations will have a more global effect in other EU areas such as the Mediterranean, where the TAC is not used as a general fishery management instrument, and the MCRS is the main component of the LO. The simulation showed no private incentives for increasing the MMS. However, this conclusion cannot necessarily be extrapolated to other areas or to other fleets. Other case-specific studies must be conducted to reach a detailed understanding of the subject. The lack of private incentives should not discourage society from supporting the increase in the selective fishing activities. From the social perspective, there is room for incentives that increase the selectivity of the gear, at least in the fleet analysed here. These incentives can be created by penalizing the lower selectivity of the 100-mm MMS or rewarding (for example, with a higher quota or effort possibilities) the use of a more selective gear. One such example is the bonus provided to some vessels in the fully documented fishery trials of Danish fisheries (
This work was partially financed by the EU H2020 project Discardless (Grant Agreement No 633680), the REdDisc project and the Basque Government–funded project MULTIPLAN. I.C. has also benefited from a grant from the Training of Technologists Programme of the Department of Economic Development and Competitiveness of the Basque Government. This publication reflects the views of the authors only and none of the funding parties can be held responsible for any use which may be made of the information contained therein. This is contribution 815 from the Marine Research Division (AZTI-Tecnalia).