# Effect of production quotas on economic and environmental values of growth rate and feed efficiency in sea cage fish farming

Mathieu Besson, I.J.M. de Boer, Marc Vandeputte, J.A.M. van Arendonk, Edwige Quillet, H. Komen, Joël Aubin

► To cite this version:

Mathieu Besson, I.J.M. de Boer, Marc Vandeputte, J.A.M. van Arendonk, Edwige Quillet, et al.  
Effect of production quotas on economic and environmental values of growth rate and feed efficiency  
in sea cage fish farming. PLoS ONE, 2017, 12 (3), pp.1-15. 10.1371/journal.pone.0173131. hal-  
01606037

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Submitted on 26 May 2020

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benthos may cause eutrophication, which affects the natural ecosystem [1, 2]. In all European countries, therefore, producing fish in sea cages has to comply with regulatory measures to limit the environmental impact. These measures require an environmental impact study of biotic and abiotic change3s due to the farming process [3, 4]. The aim of this environment impact study is to explore how much fish can be produced based on the carrying capacity of the natural ecosystem. The estimations can be supported by modeling tools. In Norway, for example, the Modelling—On growing fish farms—Monitoring (MOM) [5-7] is legally required by the Directorate of Fisheries for site selection [8]. The environmental impact study determines the delivery of the farming authorization accompanied by prescriptions that set a specific quota to the farm. The nature of the quota varies across European countries. In France, Greece or Spain, quotas constrain the annual production of fish or the annual feed distributed per farm [9, 10], whereas in Denmark, the quota is based on annual emission of nitrogen [4]. In Ireland, the production is constrained by the density of fish [4]. In Norway, the production of salmon is limited by the standing biomass per license and per site [11]. The main goal of these quotas is to limit the environmental impact of the farm to an acceptable level.

Nevertheless, fish farming is growing due to an increasing demand for fish products; the challenge, therefore, is to reach the demand while constraining or reducing environmental impacts. So far, the reduction of environmental impacts have been achieved through improving farming technologies and practices. For instance, Ytrestøyl et al. [12] showed that salmon is now a net contributor of marine ingredients due to a lower inclusion of fish meal and dish oil in the feed. Genetic improvement could also be a tool to decrease environmental impacts as it acts at the source of emission by generating cumulative changes in animal performances [13, 14]. The economic (EV) and environmental value (ENV) of genetic improvement of traits included in the breeding goal can be estimated using bio-economic models. These values represent the economic or environmental impacts of a change in one trait keeping the other traits constant [15]. Environmental values were first calculated in dairy systems using the principles of life cycle assessment (LCA) [14, 16, 17]. In fish farming, we combined a bioeconomic model with an LCA to estimate the economic and environmental values of thermal growth coefficient (TGC) and feed conversion ratio (FCR) of African catfish (*Clarias gariepinus*) produced in a recirculating aquaculture system, RAS [18]. The results showed that in dairy as well as in fish farming, genetic change of a trait can simultaneously reduce environmental impacts per unit of products and increase economic farm profit by improving production efficiency or production level. An improved production efficiency decreases the amount of resources needed per unit of product. A higher production level dilutes fixed environmental impacts over more production. However, as we showed in previous studies [18, 19], the economic and environmental values depended on the factors limiting production, which in the case of RAS are fish rearing density and nitrogen treatment capacity. In sea cages, the limiting factor is, most of the time, the production quota. The variety of quotas applied in sea cage farming suggests that genetic improvement might lead to a variety of economic and environmental responses, depending on which quota is being applied.

This study aims to investigate how different types of quota affect the economic and environmental impacts of genetic improvement in sea cage system. Using our bioeconomic / LCA model, we calculated the economic and environmental values of TGC and FCR in a sea cage system producing sea bass. First, we express ENV as a change of environmental impacts per ton of fish produced. This functional unit emphasizes the change in environmental efficiency of producing fish after genetic improvement. However, in the context of quotas such a functional unit cannot describe the dynamics of environmental impacts at farm level. Therefore, we also calculate ENV at farm level.
The system was defined from cradle-to-farm-gate and included five distinct sub-systems: (1) production of purchased feed, including production of ingredients, processing, and transportation; (2) production of energy expended at farm level (electricity, gas and petrol); (3) production of farming facilities and equipment; (4) Chemical used, including the production and the use of anti-fouling for nets; (5) farming operation, including nutrient based pollutants emission from biological transformation of feed.

The functional units in which environmental impacts were expressed was (a) per ton of fish produced on a basis of one year of routine production (impact_fish) and (b) per farm on a basis of one year of routine production (impactFarm). impact_fish and impactFarm were used to calculate environmental values.

**Life cycle inventory.**

1. Production of purchased feed—Crop-derived ingredients originated from Brazil and France (e.g. soybean meal from Brazil and wheat from France), whereas fish-derived ingredients originated from the Peruvian fish milling industry (Biomar, pers com, 2014). The chemical composition of the diet and the origin of the ingredients are given in S2 Table. The exact composition is not given to respect confidentiality. Economic allocation was used to calculate the environmental impacts of processes yielding multiple products in the feed production industry [28]. Ingredients were transported to the feed manufacture in France (Aquitaine) by transoceanic ship and by lorry (>32t), whereas the transport of feed from feed mill to the fish farm in southern France was by lorry (>32t). Transport distances and other data required to compute the environmental impact of feed ingredients were based on Boissy et al. [29] and Pelletier and Tyedmers [30], presented in detail in S2 and S3 Tables.

2. Production of energy expended on farm—The energy consumed by the farm was considered fixed. The energy consumption was set at 25,000 l of diesel per year, 55,000 l of petrol per year and 110,000 kWh of electricity per year. The electricity used by the farm was coming from the French energy mix proposed by EcoInvent v3 database. Contribution analysis is available in S4 Table.

3. Production of farming facilities and equipment used—We considered the construction of a building of 650 m² with a life span of 30 years. The equipment includes cages (64 in total), vehicles (2 boats and 6 barges, 2 trucks, 1 car), two ice making machines and other small equipment (i.e. plastic buckets). The use of building and equipment was considering fixed per year at farm level. The background processes stem from EcoInvent v3. Contribution analysis is available in S5 Table.

4. Chemical used—This sub-system includes the emission from the production and the use of anti-fouling for nets. We considered that the nets were treated every nine months with water-based anti-fouling with copper dioxide at 24%.

5. Farm operation—The farm operation sub-system includes the emission of pollutants from biological transformation of the feed distributed to the fish. The amount of nitrogen (N), phosphorus (P) and chemical oxygen demand (COD) of the dissolved organic matter excreted by the fish directly into the sea were calculated through the bioeconomic model. Contribution analysis is available in S6 Table.

**Life cycle impact assessment.** Each flow observed in the system was assigned to different impact categories relatively to its potential environmental effects. We chose to investigate eutrophication, acidification and climate change [27], because fish farming contributes most
to these environmental impact categories [31, 32]. The characterization factors from CML2 Baseline 2000 version 2.04 were used for eutrophication and climate change. The impact categories were calculated using Simapro 7.0 software.

## Economic and environmental values

Economic (EV) and environmental values (ENV) represent the change in profit and environmental impacts due to genetic improvement in a trait, while keeping other traits in the breeding goal constant. We calculated EV and ENV for two important traits representing production performance of a farm: TGC and the FCR. EV and ENV were calculated for each quota scenario. The genetic improvement implemented was one genetic standard deviation (σg) from the mean (μ). μTGC = 2.25, σg-TGC = 0.23 [33] and μFCR = 2.0, σg-FCR = 0.38. The genetic standard deviation of FCR was calculated according to Sutherland [34] using data from Kause et al. [35]. EVs were calculated as the difference between the annual profits of the farm after genetic change minus before genetic change. We calculated EVs at farm scale because the aim of selecting breeding is to increase farmer's income. Then, the EVs were rescaled per ton of fish for better visualization. This rescaling is done before genetic gain to account for the economic gain of an increase of production after genetic change [36]. The EV was expressed in euro per ton of fish produced:

$$EV = \frac{Profit_{\mu+\sigma_g} - Profit_{\mu}}{Production_{\mu}} \quad (1)$$

Environmental values were first calculated per ton of fish produced; ENV(fish). ENV(fish) were calculated as environmental impacts (category level) per ton of fish produced before genetic improvement minus environmental impacts per ton of fish produced after genetic improvement:

$$ENV(\text{fish}) = \text{Impact\_fish}_{\mu+\sigma_g} - \text{Impact\_fish}_{\mu} \quad (2)$$

ENV(fish) express, therefore, the capacity of a trait to improve environmental efficiency of fish production. However, the aim of the quota is mainly to limit the impact of the farming process on the local environment. Hence, we also calculated environmental values at farm level; ENV(farm). ENV(farm) estimate the capacity of a trait to affect environmental impacts of a specific farming site. They were calculated similarly as economic values i.e. difference between the impacts at farm level after genetic change minus the impacts at farm level before genetic change divided by annual production before genetic change. It means that the ENV (farm) were rescaled to impacts per farm per ton of fish to be able to compare with ENV(fish).

$$ENV(\text{farm}) = \frac{\text{Impact\_farm}_{\mu+\sigma_g} - \text{Impact\_farm}_{\mu}}{\text{Production}_{\mu}} \quad (3)$$

Each trait has an ENV(fish) and an ENV(farm) for each of the three impact categories investigated. ENV(fish) and ENV(farm) were also expressed in percentage of change.

$$ENV(\text{fish}\%) = \frac{ENV(\text{fish}) \times 100}{\text{Impact\_fish}_{\mu}} \quad (4)$$

$$ENV(\text{farm}\%) = \frac{ENV(\text{farm}) \times 100}{\text{Impact\_farm}_{\mu}} \quad (5)$$
<table><caption>**Table 1.** Summary of the consequences of genetic improvement in TGC (thermal growth coefficient) and FCR (feed conversion ratio) on technical performances of a sea cage farm constrained by different quota. Qprod is the quota on annual production, Qannual\_feed is on annual feed distributed, Qstock is on the daily biomass present on site and Qdaily\_feed is on daily feed distributed.</caption><thead><tr><td>Quota type</td><td>Improving TGC</td><td>Improving FCR</td></tr></thead><tbody><tr><td>Qprod</td><td>none</td><td>Production efficiency</td></tr><tr><td>Qannual\_feed</td><td>none</td><td>Production + Production efficiency</td></tr><tr><td>Qstock</td><td>Production</td><td>Production efficiency</td></tr><tr><td>Qdaily\_feed</td><td>Production</td><td>Production + production efficiency</td></tr></tbody></table>

doi:10.1371/journal.pone.0173131.t001

## Results

Genetic improvement can affect the production level (i.e. tonnes of fish produced per year) and/or the production efficiency of the farm (i.e. quantity of input used per unit of fish produced) (Table 1). These changes affect the economic and environmental values of thermal growth coefficient (TGC) and feed conversion ratio (FCR).

## Economic values, EV (Tables 1 and 2)

**EV of TGC.** Improving TGC decreased the time to reach harvest size and increased daily feed intake. In consequence, production should increase as more batches can be produced (increasing batch rotation). When the quota was on annual production (Qprod), higher batch rotation was balanced by lower stocking density to comply with the quota. This situation was similar with a quota on annual feed distributed (Qannual\_feed). Thus, the economic value of TGC was null in Qprod and Qannual\_feed. Conversely, when the quota was on daily standing stock (Qstock) or daily feed distributed (Qdaily\_feed), increasing TGC led to more batches, but without a proportional decrease in stocking density. The resulting annual production was higher. Therefore, the economic value of TGC was positive: 0.12 €/kg of fish for Qstock and 0.08 €/kg of fish for Qdaily\_feed.

**EV of FCR.** Improving FCR decreased the amount of feed required per unit of fish produced. When the quota was on feed distributed (Qannual\_feed or Qdaily\_feed) better FCR increased, therefore, production efficiency but production could also be increased until the feed quota was reached. Consequently, the economic value of FCR was 1.14 €/kg for Qannual\_feed and 0.95 €/kg for Qdaily\_feed. When Qprod or Qstock were the quotas, improving FCR improved only production efficiency. Thus, less feed was consumed at farm level and the economic value of FCR was 0.50 €/kg.

## Environmental value at fish level, ENV(fish)

More details about the results of the life cycle assessment are given in S7, S8 and S9 Tables.

**ENV(fish) of TGC (Tables 3 and 4).** ENV(fish) of TGC were null for all impact categories when the quota was Qprod or Qannual\_feed because in this situation TGC did not increase production or production efficiency. However, when the quota was Qstock or Qdaily\_feed, improving TGC increased production. When production increased, the fixed environmental impacts are diluted over more fish produced. The fixed environmental impacts are the production of energy, the use of chemical and the production of equipment and infrastructure. These impacts represent 16.4% of acidification and 6.7% of climate change. Consequently, the environmental impact per ton of fish produced decreased and the ENV(fish) of TGC were positive for acidification and climate change categories. However, fixed environmental impacts represent less than 1% of eutrophication. The 99% remaining are caused by feed production and
<table><caption>Table 2. Effect of different values of Thermal Growth Coefficient (TGC) and Feed Conversion Ratio (FCR) on fish production parameters in different quota scenarios. Qprod is the quota on annual production, Qannual\_feed is on annual feed distributed, Qstock is on the daily biomass present on site and Qdaily\_feed is on daily feed distributed.</caption><thead><tr><th>Quota</th><th>TGC</th><th>FCR</th><th>Days to reach harvest weight (d)</th><th>Number of batch produced (#)</th><th>Production per batch (t)</th><th>Production at farm (t)</th><th>Feed consumption per farm (t)</th><th>Incomes (€ x 1000)</th><th>Feed cost (€ x 1000)</th><th>Juveniles cost (€ x 1000)</th><th>Fixed cost (€ x 1000)</th><th>Profit (€)</th><th>EV TGC (€/kg)</th><th>EV FCR (€/kg)</th></tr></thead><tbody><tr><td rowspan="3">Qprod</td><td>2.25</td><td>2.02</td><td>573</td><td>30.87</td><td>32.4</td><td>1000</td><td>2047</td><td>5598</td><td>2662</td><td>692</td><td>2245</td><td>-0.03</td><td>0</td><td>0.5</td></tr><tr><td>2.48</td><td>2.02</td><td>528</td><td>35.64</td><td>28.1</td><td>1000</td><td>2047</td><td>5598</td><td>2662</td><td>692</td><td>2245</td><td>-521.88</td><td>0</td><td>1.14</td></tr><tr><td>2.25</td><td>1.64</td><td>573</td><td>30.87</td><td>32.4</td><td>1000</td><td>1660</td><td>5598</td><td>2159</td><td>692</td><td>2245</td><td>503048.8</td><td>0</td><td>1.14</td></tr><tr><td rowspan="3">Qannual\_feed</td><td>2.25</td><td>2.02</td><td>573</td><td>31.22</td><td>32.0</td><td>1000</td><td>2047</td><td>5597</td><td>2661</td><td>692</td><td>2245</td><td>0.56</td><td>0</td><td>0.5</td></tr><tr><td>2.48</td><td>2.02</td><td>528</td><td>36.43</td><td>27.4</td><td>1000</td><td>2047</td><td>5597</td><td>2661</td><td>692</td><td>2245</td><td>-521.19</td><td>0.12</td><td>0.95</td></tr><tr><td>2.25</td><td>1.64</td><td>573</td><td>28.97</td><td>42.5</td><td>1232</td><td>2047</td><td>6900</td><td>2661</td><td>853</td><td>2245</td><td>1141326</td><td>0.08</td><td>0.95</td></tr><tr><td rowspan="3">Qstock</td><td>2.25</td><td>2.02</td><td>573</td><td>32.02</td><td>31.2</td><td>1000</td><td>2046</td><td>5596</td><td>2659</td><td>692</td><td>2245</td><td>0.46</td><td>0.5</td><td>0.95</td></tr><tr><td>2.48</td><td>2.02</td><td>528</td><td>34.49</td><td>30.6</td><td>1055</td><td>2160</td><td>5904</td><td>2809</td><td>730</td><td>2245</td><td>120354.6</td><td>0.59</td><td>0.95</td></tr><tr><td>2.25</td><td>1.64</td><td>573</td><td>32.02</td><td>31.2</td><td>1000</td><td>1657</td><td>5596</td><td>2155</td><td>692</td><td>2245</td><td>504751.8</td><td>0.59</td><td>0.95</td></tr><tr><td rowspan="3">Qdaily\_feed</td><td>2.25</td><td>2.02</td><td>573</td><td>31.12</td><td>32.1</td><td>1000</td><td>2046</td><td>5597</td><td>2660</td><td>692</td><td>2245</td><td>0.59</td><td>0.08</td><td>0.95</td></tr><tr><td>2.48</td><td>2.02</td><td>528</td><td>35.06</td><td>29.5</td><td>1035</td><td>2118</td><td>5792</td><td>2753</td><td>716</td><td>2245</td><td>77713.2</td><td>0.08</td><td>0.95</td></tr><tr><td>2.25</td><td>1.64</td><td>573</td><td>29.34</td><td>39.6</td><td>1162</td><td>1929</td><td>6506</td><td>2508</td><td>804</td><td>2245</td><td>949212.7</td><td>0.08</td><td>0.95</td></tr></tbody></table>

doi:10.1371/journal.pone.0173131.t002
<table><caption>**Table 3.** Effect of different values of Thermal Growth Coefficient (TGC) and Feed Conversion Ratio (FCR) on annual emission of pollutants and environmental impacts in different quota scenarios. Qprod is the quota on annual production, Qannual\_feed is on annual feed distributed, Qstock is on the daily biomass present on site and Qdaily\_feed is on daily feed distributed.</caption><thead><tr><th>Quota</th><th>TGC</th><th>FCR</th><th>Production per farm (t)</th><th>Nitrogen emission (t)</th><th>COD emission (t)</th><th>Phosphorus emission (t)</th><th>Climate change (kg CO<sub>2</sub>-eq / ton of fish)</th><th>Eutrophication (kg PO<sub>4</sub>-eq / ton of fish)</th><th>Acidification (kg SO<sub>2</sub>-eq / ton of fish)</th></tr></thead><tbody><tr><td rowspan="3">Qprod</td><td>2.25</td><td>2.02</td><td>1000</td><td>114.92</td><td>2614.15</td><td>16.44</td><td>3636.53</td><td>168.62</td><td>21.77</td></tr><tr><td>2.48</td><td>2.02</td><td>1000</td><td>114.98</td><td>2616.06</td><td>16.45</td><td>3636.53</td><td>168.73</td><td>21.77</td></tr><tr><td>2.25</td><td>1.64</td><td>1000</td><td>88.29</td><td>1959.10</td><td>12.18</td><td>2995.38</td><td>127.90</td><td>18.33</td></tr><tr><td rowspan="3">Qannual\_feed</td><td>2.25</td><td>2.02</td><td>1000</td><td>114.87</td><td>2613.11</td><td>16.43</td><td>3636.02</td><td>168.59</td><td>21.76</td></tr><tr><td>2.48</td><td>2.02</td><td>1000</td><td>114.93</td><td>2615.01</td><td>16.45</td><td>3636.02</td><td>168.69</td><td>21.76</td></tr><tr><td>2.25</td><td>1.64</td><td>1232</td><td>108.84</td><td>2414.94</td><td>15.02</td><td>2949.75</td><td>127.66</td><td>17.66</td></tr><tr><td rowspan="3">Qstock</td><td>2.25</td><td>2.02</td><td>1000</td><td>114.79</td><td>2611.13</td><td>16.42</td><td>3635.28</td><td>168.51</td><td>21.76</td></tr><tr><td>2.48</td><td>2.02</td><td>1055</td><td>121.20</td><td>2757.49</td><td>17.34</td><td>3622.52</td><td>168.57</td><td>21.57</td></tr><tr><td>2.25</td><td>1.64</td><td>1000</td><td>88.11</td><td>1954.71</td><td>12.16</td><td>2991.65</td><td>127.68</td><td>18.31</td></tr><tr><td rowspan="3">Qdaily\_feed</td><td>2.25</td><td>2.02</td><td>1000</td><td>114.86</td><td>2612.80</td><td>16.43</td><td>3635.76</td><td>168.58</td><td>21.76</td></tr><tr><td>2.48</td><td>2.02</td><td>1035</td><td>118.94</td><td>2706.36</td><td>17.02</td><td>3627.54</td><td>168.67</td><td>21.64</td></tr><tr><td>2.25</td><td>1.64</td><td>1162</td><td>102.59</td><td>2276.24</td><td>14.16</td><td>2960.63</td><td>127.67</td><td>17.83</td></tr></tbody></table>

doi:10.1371/journal.pone.0173131.t003

fish excretion which increased with higher production in Qstock and Qdaily\_feed. Therefore, ENV(fish) of TGC for eutrophication is close to zero in Qstock and Qdaily\_feed.

**ENV(fish) of FCR (Tables 3 and 5).** The ENV(fish) of FCR in all quotas is positive, i.e. improving FCR decreases environmental impacts, because improving FCR decreased the amount of inputs need to produce one tonne of fish. The decrease was higher for eutrophication because eutrophication also includes the reduction in pollutants emission from the fish.

## Environmental values at farm level, ENV(farm)

**ENV(fish) of TGC (Tables 3 and 4).** ENV(farm) of TGC was null or close to null for all impact categories when quota was Qprod or Qannual\_feed because TGC did not increase production or production efficiency. When the quota was Qstock or Qdaily\_feed, production increased as well as feed consumption and emission of pollutants, which are the main

<table><caption>**Table 4.** Environmental Value (ENV) of TGC (thermal growth coefficient) at fish and farm level in different quota. Qprod is the quota on annual production, Qannual\_feed is on annual feed distributed, Qstock is on the daily biomass present on site and Qdaily\_feed is on daily feed distributed. Between brackets is the percentage a change in environmental impacts. A negative sign means that the environmental impact considered increased after genetic change.</caption><thead><tr><th rowspan="2">Quota</th><th rowspan="2">TGC</th><th rowspan="2">FCR</th><th colspan="3">ENV at farm level</th><th colspan="3">ENV at fish level</th></tr><tr><th>Climate Change<br>(kg CO<sub>2</sub>-eq)</th><th>Eutrophication<br>(kg PO<sub>4</sub>-eq)</th><th>Acidification<br>(kg SO<sub>2</sub>-eq)</th><th>Climate Change<br>(kg CO<sub>2</sub>-eq)</th><th>Eutrophication<br>(kg PO<sub>4</sub>-eq)</th><th>Acidification<br>(kg SO<sub>2</sub>-eq)</th></tr></thead><tbody><tr><td rowspan="2">Qprod</td><td>2.25</td><td>2.02</td><td>0</td><td>-0.11</td><td>0</td><td>0</td><td>-0.11</td><td>0</td></tr><tr><td>2.48</td><td>2.03</td><td>(0%)</td><td>(-0.06%)</td><td>(0%)</td><td>(0%)</td><td>(0%)</td><td>(0%)</td></tr><tr><td rowspan="2">Qannual\_feed</td><td>2.25</td><td>2.02</td><td>0</td><td>-0.11</td><td>0</td><td>0</td><td>-0.11</td><td>0</td></tr><tr><td>2.48</td><td>2.03</td><td>(0%)</td><td>(-0.06%)</td><td>(0%)</td><td>(0%)</td><td>(-0.06%)</td><td>(0%)</td></tr><tr><td rowspan="2">Qstock</td><td>2.25</td><td>2.02</td><td>-186.84</td><td>-9.35</td><td>-1</td><td>12.76</td><td>-0.06</td><td>0.19</td></tr><tr><td>2.48</td><td>2.03</td><td>(-5.14%)</td><td>(-5.55%)</td><td>(-4.61%)</td><td>(0.35%)</td><td>(-0.04%)</td><td>(0.86%)</td></tr><tr><td rowspan="2">Qdaily\_feed</td><td>2.25</td><td>2.02</td><td>-118.74</td><td>-5.97</td><td>-0.63</td><td>8.22</td><td>-0.09</td><td>0.12</td></tr><tr><td>2.48</td><td>2.03</td><td>(-3.25%)</td><td>(3.54%)</td><td>(-2.91%)</td><td>(0.23%)</td><td>(-0.05%)</td><td>(0.55%)</td></tr></tbody></table>

doi:10.1371/journal.pone.0173131.t004
<table><caption>**Table 5. Environmental Value (ENV) of FCR (feed conversion ratio) at fish and farm level in different quota.** Qprod is the quota on annual production, Qannual\_feed is on annual feed distributed, Qstock is on the daily biomass present on site and Qdaily\_feed is on daily feed distributed. Between brackets is the percentage a change in environmental impacts. A positive value means that the environmental impact considered decreased after genetic change.</caption><thead><tr><th rowspan="3">Quota</th><th rowspan="3">TGC</th><th rowspan="3">FCR</th><th colspan="3">ENV at farm level</th><th colspan="3">ENV at fish level</th></tr><tr><th>Climate Change</th><th>Eutrophication</th><th>Acidification</th><th>Climate Change</th><th>Eutrophication</th><th>Acidification</th></tr><tr><th>(kg CO<sub>2</sub>-eq)</th><th>(kg PO<sub>4</sub>-eq)</th><th>(kg SO<sub>2</sub>-eq)</th><th>(kg CO<sub>2</sub>-eq)</th><th>(kg PO<sub>4</sub>-eq)</th><th>(kg SO<sub>2</sub>-eq)</th></tr></thead><tbody><tr><td rowspan="2">Qprod</td><td>2.25</td><td>2.02</td><td>641.15</td><td>40.72</td><td>3.44</td><td>641.15</td><td>40.72</td><td>3.44</td></tr><tr><td>2.48</td><td>2.03</td><td>(17.63%)</td><td>(24.15%)</td><td>(15.80%)</td><td>(17.63%)</td><td>(24.15%)</td><td>(15.80%)</td></tr><tr><td rowspan="2">Qannual\_feed</td><td>2.25</td><td>2.02</td><td>0</td><td>11.23</td><td>0</td><td>686.27</td><td>40.93</td><td>4.11</td></tr><tr><td>2.48</td><td>2.03</td><td>(0%)</td><td>(6.66%)</td><td>(0%)</td><td>(18.87%)</td><td>(24.28%)</td><td>(18.87%)</td></tr><tr><td rowspan="2">Qstock</td><td>2.25</td><td>2.02</td><td>643.63</td><td>40.83</td><td>3.45</td><td>643.63</td><td>40.83</td><td>3.45</td></tr><tr><td>2.48</td><td>2.03</td><td>(17.71%)</td><td>(24.23%)</td><td>(15.86%)</td><td>(17.71%)</td><td>(24.23%)</td><td>(15.86%)</td></tr><tr><td rowspan="2">Qdaily\_feed</td><td>2.25</td><td>2.02</td><td>194.12</td><td>20.16</td><td>1.04</td><td>675.13</td><td>40.91</td><td>3.94</td></tr><tr><td>2.48</td><td>2.03</td><td>(5.34%)</td><td>(11.96%)</td><td>(4.79%)</td><td>(18.57%)</td><td>(24.27%)</td><td>(18.09%)</td></tr></tbody></table>

doi:10.1371/journal.pone.0173131.t005

contributors to environmental impacts. Consequently, the ENV(farm) of TGC was negative for all impact categories, meaning that increasing TGC increased environmental impacts at farm level. The increase of environmental impacts was higher in Qstock quota than in Qdaily\_feed.

**ENV(fish) of FCR (Tables 3 and 5).** When the quota was Qprod or Qstock, improving FCR improved production efficiency. Therefore, less feed was consumed at farm level and the ENV(farm) of FCR were positive for all impacts categories, meaning that environmental impacts decreased. When the quota was Qannual\_feed, improving FCR increased production efficiency and production, which kept annual consumption of feed constant. Consequently the ENV(farm) of FCR for climate change and acidification was null. However, with better FCR, less nutrient based pollutants were emitted. It resulted in a decrease in eutrophication by 6.66% because the nutrients-based pollutants emitted to water were considered to remain in water and thus they were contributing to eutrophication only. Thus, for Qannual\_feed, the ENV(farm) of FCR for eutrophication was positive. When the quota was Qdaily\_feed, improving FCR increased at the same time production efficiency and production but less feed was consumed at farm level. It resulted in a positive ENV(farm) for FCR. The ENV(farm) of FCR was also higher for eutrophication than other impact categories because improving FCR reduces the amount of pollutants emitted.

Discussion

In sea cage farming, quotas are implemented to limit the environmental impacts of farm operations, such as the deposition of organic matter under the cages and the emission of dissolved nutrients in water, leading to eutrophication. In the present study, we investigated the effect of these quotas on economic and environmental responses to genetic improvement of sea bass. This is the first time the effect of quotas on genetic improvement of fish is tested. Economic values are used to maximize the economic response in the breeding goal. These values weigh the traits of a breeding goal according to their impacts on farm profit. They are specific to production systems according to the quota applied [37] or the environmental conditions [38]. When EVs differ from one production system to another, a single breeding program may not be enough to maximize economic response in all production systems [38]. It is important to remember that EVs and ENVs represent the economic and environmental change due to an improvement in one trait while keeping the other traits of the breeding goal constant. Therefore, EVs and ENVs are informative about the economic and environmental importance of a
eutrophication to be 168.57 kg of PO₄-eq per t of fish produced, the eutrophication at European scale would increase from 26,373 to 29,933 t of PO₄-eq. Keeping eutrophication constant with the same increase in production would require a 11.9% improvement of FCR over 3 years (1 generation), which could be achieved by a 20% selection pressure (i = 1.4) on FCR if its heritability is 0.17 as suggested in Kause et al. [35].

In addition, the increase in production could also increase environmental impacts of farming site and the role of quota system is to prevent this increase. Thus, we chose to calculate ENV(farm) to estimate the capacity of a trait to affect environmental impacts of a specific farming site in compliance with the aim of quota system. At farm level, mitigation does not exist anymore and an increase in production increases feed distribution and hence nitrogen emission. Therefore, the ENV(farm) of TGC are negative in Qstock and Qdaily feed. It means that, in Qstock and Qdaily feed, the environmental response to selection on TGC can be interpreted differently whether we look at farm level or at fish level. This has been shown in dairy where genetic improvement in milk yield would increase emission of CO₂-eq. at herd level but reduce emission per kilogram of milk produced [17]. Regarding FCR, genetic improvement would always decrease environmental impacts at farm level in every quota scenario. However, the ENV(farm) of FCR in Qannual feed and Qdaily feed are lower than in Qprod and Qstock because improving FCR in Qannual feed and Qdaily feed increases production level together with production efficiency. The variation of ENV(farm) of TGC and FCR suggests that a single breeding program including ENV(farm) would not minimize environmental response in all quotas. It also suggests that breeding objectives using ENV(farm) and ENV(fish) would not lead to the same response. Therefore, the choice between ENV(farm) and ENV(fish) depends on the objectives of the breeding program.

In our model, the only limiting factor was one of the four production quota, which implied a constant stocking density through the time. This stocking density was calculated to reach the quota limitation without overtaking it. In the reference scenario (without genetic improvement) we considered that the oxygen availability was not limiting the number of fish stocked. However, in the scenario with genetic improvement, increasing TGC increases individual oxygen consumption due to higher feed intake and increasing FCR decreases individual oxygen consumption due to lower feed intake. Therefore, if you considered oxygen limitation, changing TGC and FCR could impact the number of fish stocked in cages to avoid hypoxia. In Besson et al. [21], we showed that the economic value of TGC, when oxygen was the limiting factor, was null when the average temperature was 18°C and increased with higher average temperatures. These results suggest that the ENV(fish) of TGC would also increase with higher temperature when oxygen is the limiting factor. However, ENV(farm) would decrease with higher temperature. Regarding FCR, both the EV and ENV(fish) would be positive because better FCR decreases feed intake and oxygen consumption which would increase production and increase production efficiency. However, ENV(farm) would also be positive because only due to better production efficiency.

The economic and environmental sustainability of fish farming is already a main target of fish breeders. Since the 70's and the development of the first breeding program for salmon, new traits have been included in breeding goals such as disease resistance or filet yield beside growth rate [42]. Nevertheless, the lack of knowledge on the potential economic and environmental impacts of these traits could generate economic shortfall for farmers and increase their environmental impacts. The advantages of using EV or ENV to weigh the traits in a breeding program is that they maximize the economic gain or the environmental gain of a breeding program. However, it is not possible to combine EV and ENV in a common breeding objective as they are not expressed with the same unit. EV is in euros while ENV is, for instance, in CO₂-eq. Consequently, the economic breeding objective may have adverse effects on the
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