<p>SUPPLEMENTARY MATERIALS</p><p>Table S1 - Linear mixed model analyses (using the lme4 R package) for explaining the gain in GAV (compared to the baseline situation, see section 2.4) from individual vessel features such as the gear in use (OtterBTrawl otter bottom trawl, OtterTrawl, PairTrawl, Seine, BeamTrawl, OtterTTrawl, otter twin trawl), the target assemblage (CRU crustaceans, DEF demersal fish, MCD mixed crustaceans demersal fish and SPF small pelagic fish), the vessel nationality (DEU, DEN and SWE), the categories of vessel length in m, the fuel consumption rate in litre per hour, storage capacity in kg, the fuel tank capacity in litres, and the trip duration in days. The model is:</p><p>Where i indexes the scenario and j the vessels, the betas are the model-class variables, the gammas are the two random intercepts for the vessels and the scenarios, respectively, and finally the epsilon error follow a normal law.</p><p>Random effects Groups Variance Std.Dev. Vessels 0.05100 0.2258 Scenarios 0.01098 0.1048 Residual 0.04822 0.2196 </p><p>Fixed effects Estimate Std.Error t value Signif. (Intercept) 0,152 0,254 0,596 gearStatic 0,042 0,090 0,473 gearOtterMTrawl 0,047 0,151 0,314 gearPairTrawl 0,000 0,078 0.000 gearSeine 0,073 0,098 0,748 gearBeamTrawl -0,058 0,082 -0,708 gearOtterTTrawl -0,026 0,089 -0,295 targetDEF -0,214 0,087 -2.454 *** targetMCD -0,170 0,101 -1.679 *** targetSPF -0,296 0,131 -2.258 *** ctryDNK 0,122 0,061 1.994 *** ctrySWE 0,152 0,120 1.266 ** vessel_size(12,18] -0,312 0,125 -2.488 ***</p><p>1 vessel_size(18,24] -0,252 0,156 -1.623 *** vessel_size(>24) -0,349 0,190 -1.838 *** vessel_speed(10,15] 0,027 0,144 0,186 vessel_speed(>15) 0,000 0,150 -0,003 fuelcons_rate(60,120] -0,042 0,059 -0,715 * fuelcons_rate(120,240] 0,013 0,111 0,115 * fuelcons_rate(240,480] -0,019 0,324 -0,058 fuelcons_rate(>480) -0,024 0,256 -0,095 storage_capacity(10000,40000] 0,066 0,082 0,804 storage_capacity(>40000) 0,090 0,134 0,672 fuel_tank_capacity(2000,8000) -0,006 0,134 -0,041 fuel_tank_capacity(8000,16000 ) -0,083 0,194 -0,426 fuel_tank_capacity(>16000) 0,048 0,267 0,179 average_trip_duration(10,20] 0,034 0,088 0,384 average_trip_duration(>20) 0,127 0,092 1.377 ** Signif. Codes: ‘***’ 0; ‘**’ 0.01; ‘*’ 0.05</p><p>Table S2 - same as Table S1 but for the gain in VPUF i.e. The model is: </p><p>Random effects Groups Variance Std.Dev. Vessels 0.013497 0.11618 Scenarios 0.007316 0.08553 Residual 0.022386 0.14962</p><p>Fixed effects Estimate Std.Error t value Signif. (Intercept) 0,043 0,139 0,307 gearStatic -0,050 0,048 -1.040 gearOtterMTrawl 0,099 0,081 1.225 * gearPairTrawl 0,006 0,042 0,14 gearSeine 0,103 0,053 1.955 *** gearBeamTrawl 0,039 0,044 0,894 gearOtterTTrawl -0,044 0,048 -0,928 targetDEF -0,058 0,047 -1.246 * targetMCD -0,077 0,054 -1.423 ** targetSPF -0,194 0,070 -2.754 *** ctryDNK 0,049 0,033 1.477 **</p><p>2 ctrySWE 0,101 0,064 1.563 ** vessel_size(12,18] -0,149 0,067 -2.223 *** vessel_size(18,24] -0,212 0,084 -2.536 *** vessel_size(>24) -0,190 0,102 -1.864 *** vessel_speed(10,15] 0,044 0,077 0,573 vessel_speed(>15) 0,101 0,081 1.258 * fuelcons_rate(60,120] 0,043 0,032 1.357 * fuelcons_rate(120,240] -0,024 0,060 -0,397 fuelcons_rate(240,480] 0,085 0,174 0,49 fuelcons_rate(>480) 0,128 0,137 0,934 storage_capacity(10000,40000] 0,031 0,044 0,695 storage_capacity(>40000) -0,020 0,072 -0,279 fuel_tank_capacity(2000,8000) -0,045 0,072 -0,625 fuel_tank_capacity(8000,16000 ) -0,060 0,104 -0,579 fuel_tank_capacity(>16000) -0,047 0,143 -0,332 average_trip_duration(10,20] -0,021 0,047 -0,44 average_trip_duration(>20) 0,033 0,050 0,665 Signif. Codes: ‘***’ 0; ‘**’ 0.01; ‘*’ 0.05</p><p>Table S3 - Linear mixed model analyses (using the lme4 R package) for explaining the gain in GAV from random effects (individual vessels and scenarios) and fixed effects (gain relative to the baseline in terms of total effort, steaming effort, total cod, sprat and herring landings, total other landings, catch per unit of fishing effort CPUE for herring, sprat and cod respectively, CPUE from other stocks, average trip duration, and average number of trips). P-values are obtained by likelihood ratio tests of the full model with the effect in question against the model without the effect in question.</p><p>Random effects Groups Variance Std.Dev. Vessels 0.045665 0.21369 Scenarios 0.001639 0.04048 Residual 0.040424 0.20106</p><p>Fixed effects Estimate Std.Error t value Signif. (Intercept) -0,043 0,023 -1.878</p><p>3 gain_effort 0,195 0,148 1.317 gain_seffort -0,076 0,088 -0,861 gain_totland_others 0,398 0,060 6.659 *** gain_totland_HER_SPR_CO D 0,320 0,032 10.027 *** gain_fcpue_HER 0,107 0,022 4.900 *** gain_fcpue_SPR -0,007 0,020 -0,341 gain_fcpue_COD 0,071 0,032 2.247 gain_fcpue_others -0,206 0,044 -4.719 *** gain_av_trip_duration -0,153 0,104 -1.468 gain_av_nbtrips 0,567 0,108 5.235 *** Signif. Codes: ‘***’ 0; ‘**’ 0.01; ‘*’ 0.05</p><p>Table S4 - Linear mixed model analyses (using the lme4 R package) for explaining the gain in VPUF with the same specifications as described for Table S3.</p><p>Random effects Groups Variance Std.Dev. Vessels 0.008774 0.09367 Scenarios 0.001068 0.03268 Residual 0.014204 0.11918</p><p>Fixed effects Estimate Std.Error t value (Intercept) -0,024 0,015 -1.663 * gain_effort 0,060 0,085 0.700 gain_seffort -0,622 0,050 -12.553 *** gain_totland_others 0,107 0,034 3.149 *** gain_totland_HER_SPR_COD 0,219 0,018 11.962 *** gain_fcpue_HER 0,126 0,012 10.114 *** gain_fcpue_SPR -0,013 0,012 -1.082 *** gain_fcpue_COD 0,057 0,018 3.130 *** gain_fcpue_others 0,121 0,025 4.826 *** gain_av_trip_duration 0,011 0,060 0,187 gain_av_nbtrips 0,084 0,061 1.365 </p><p>4 Signif. Codes: ‘***’ 0; ‘**’ 0.01; ‘*’ 0.05</p><p>Supplementary Material Figure S1 - Underlying spatial stock distribution (resource availability, longitude East and latitude North in decimal degrees) from the analysis of the ICES BITS research survey data for the herring, sprat and cod stocks in the first semester (a) and in the second semester (b) of the period 2008-2012. The main bulk of the spatial distribution is obtained after applying a kernel density (with sigma=0.3 and 4 levels) on the spatial pattern of the stock specific nodes weighted by the proportion of the stock available on each node calculated for each period. Note that the white areas do not mean a 0 abundance since only the main bulks are depicted.</p><p>5 Supplementary Material Figure S2 - Percentage of vessels per value per unit of fuel (VPUF) stress levels at the horizon time of each scenario (a green bar represents a gain compared to the baseline situation while a red bar represents a loss). </p><p>6 Supplementary Material Figure S3 - Percentage of vessels per total landings stress levels at the horizon time of each scenario (a green bar represents a gain compared to the baseline situation while a red bar represents a loss).</p><p>7 Supplementary Material Figure S4 - Same as for the figure xx but by further categorizing the vessel by vessel length classes (bars with discrete colors and category values in meters). </p><p>8 Supplementary Material Figure S5 - Same as for the figure xx but by further categorizing the vessel by fishing gear classes in the bars (Dredge, static gears, otter bottom trawl, otter mid- water trawl, pair trawl, seine, beam trawl and otter twin trawl) where each vessel is assigned the most used type of gear in terms of deployed effort in 2012. </p><p>9 Supplementary Material Figure S6 - Same as for the figure xx but by further categorizing the vessel by nationality classes (in bars with discrete colors for DEU ( German), DEN (Danish), and</p><p>SWE (Swedish) vessels).</p><p>10 Supplementary Material Figure S 7 - Benthic marine habitats (landscapes) as extracted from the </p><p>BALANCE Interim report No24. (from Al-Hamdani et al. 2007; reproduced with the author permission). </p><p>11</p>