Stock Assessment Form Small Pelagics Reference Year: 2012 Reporting Year: 2014

Transcription

1 Stock Assessment Form Small Pelagics Reference Year: 2012 Reporting Year: 2014 [A brief abstract may be added here]

2 Stock Assessment Form version 1.0 (January 2014) Uploader: Please include your name Stock assessment form 1 Basic Identification Data Stock identification and biological information Stock unit Growth and maturity Fisheries information Description of the fleet Historical trends Management regulations Reference points Fisheries independent information {NAME OF THE DIRECT METHOD}... Error! Bookmark not defined Brief description of the chosen method and assumptions used Spatial distribution of the resources Historical trends... Error! Bookmark not defined. 5 Ecological information Protected species potentially affected by the fisheries Environmental indexes Stock Assessment {Name of the Model} Model assumptions Scripts Input data and Parameters Tuning data... Error! Bookmark not defined Results Robustness analysis Retrospective analysis, comparison between model runs, sensitivity analysis, etc Assessment quality... Error! Bookmark not defined. 7 Stock predictions Short term predictions Medium term predictions Long term predictions Draft scientific advice Explanation of codes

3 1 Basic Identification Data Scientific name: Common name: ISCAAP Group: Sardina pilchardus European sardine 35 - Herrings, sardines, anchovies 1 st Geographical sub-area: 2 nd Geographical sub-area: 3 rd Geographical sub-area: [GSA 17] 4 th Geographical sub-area: 5 th Geographical sub-area: 6 th Geographical sub-area: 1 st Country 2 nd Country 3 rd Country Italy Croatia Slovenia 4 th Country 5 th Country 6 th Country Stock assessment method: (direct, indirect, combined, none) Combined Authors: Carpi P. (1), (in alphabetical order) Angelini S. (1), Belardinelli A. (1), Biagiotti I. (1), Campanella F. (1), Canduci G. (1), Cingolani N. (1), Èikeš Keè V.(2), Colella S. (1), Croci C. (1), De Felice A. (1), Donato F.(1), Leonori I. (1), Martinelli M. (1), Malavolti S. (1), Modic T. (3), Panfili M. (1), Pengal P. (3), Santojanni A. (1), Ticina V. (2), Vasapollo C. (1), Zorica B. (2), Arneri E (4). Affiliation: (1) CNR-ISMAR (Ancona, Italy), (2) Institute of Oceanography and Fisheries (Split, Croatia), (3) Fisheries Research Institute of Slovenia (Ljubjana, Slovenia), (4) FAO-Adriamed (Rome, Italy) The ISSCAAP code is assigned according to the FAO 'International Standard Statistical Classification for Aquatic Animals and Plants' (ISSCAAP) which divides commercial species into 50 groups on the basis of their taxonomic, ecological and economic characteristics. This can be provided by the GFCM secretariat if needed. A list of groups can be found here: Direct methods (you can choose more than one): - Acoustics survey Indirect method (you can choose more than one): 2

4 - ICA - SAM 3

5 2 Stock identification and biological information Sardine (Sardina pilchardus) stock is shared among the countries belonging to GSA 17 (Italy, Croatia and Slovenia, Figure ) and it constitutes a unique stock. Although there is some evidence of differences on a series of morphometric, meristic, serological and ecological characteristics, the lack of genetic heterogeneity in the Adriatic stock has been demonstrated through allozymic and mitochondrial DNA (mtdna) surveys (Carvalho et al., 1994) and through sequence variation analysis of a 307-bp cytochrome b gene (Tinti et al., 2002). The results of the genetic analyses imply that the different trophic and environmental conditions found in the northern and central Adriatic, may cause differences in growth rates. 2.1 Stock unit 2.2 Growth and maturity Table 2.2-1: Maximum size, size at first maturity and size at recruitment. Somatic magnitude measured LT Units cm (LT, LC, etc) Sex Fem Mal Combined Reproduction season October - April Maximum size observed 22.5 Recruitment season Size at first maturity 8 Spawning area Whole Adriatic - over the continental shelf Recruitment size to the fishery 13 Nursery area Mainly along eastern Adriatic coast, over almost whole continental shelf but mostly in area of Kvarner and Kvarneriæ, and around middle Dalmatian islands. On the western Adriatic: River Po Delta and Manfredonia Gulf 4

6 Table 2.2-2: M vector and proportion of matures by size or age (Combined) Size/Age Natural mortality Proportion of Table 2.2-3: Growth and length weight model parameters Sex Units female male Combined Years L Cm 20.5 Growth model K y t 0 Y -0.5 Data source Sinovcic, 1986 Length weight relationship a b M (scalar) sex ratio (% females/total) 5

7 3 Fisheries information 3.1 Description of the fleet Table 3.1-1: Description of operational units exploiting the stock Country GSA Fleet Segment Fishing Gear Class Group of Target Species Species Operational Unit 1* Italy 17 Pelagic trawlers Trawls 35 - Herrings, sardines, anchovies Sardina pilchardus Operational Unit 2 Italy 17 Purse seiners Sorrounding nets 35 - Herrings, sardines, anchovies Sardina pilchardus Operational Unit 3 Croatia 17 Purse seiners Sorrounding nets 35 - Herrings, sardines, anchovies Sardina pilchardus Operational Unit 4 Slovenia 17 Purse seiners Sorrounding nets 35 - Herrings, sardines, anchovies Sardina pilchardus Operational Unit 5 Slovenia 17 Pelagic trawlers Trawls 35 - Herrings, sardines, anchovies Sardina pilchardus 6

8 Table 3.1-2: Catch, bycatch, discards and effort by operational unit in the reference year Operational Units* Total Fleet (n of boats)* Catch (T or kg of the species assessed) Other species caught (names and weight ) Discards (species assessed) Discards (other species caught) Effort (units) 7

9 3.2 Historical trends In figure and in table the trend in landings from 1975 to 2012 for Italy and Croatia are shown. Slovenian catches are included as well, but are not shown here since the quantities are really low (around 18 tons in 2012). The landings of sardine in GSA17 started decreasing in the late eighties reaching a minimum in 2005 with tons. In the last 7 years the Croatian catches grew high, reaching the maximum of the entire time series in 2011 with about tons (almost 90% of the overall catches). In 2012 the total landings slightly decreased respect to the previous year, with an overall value of The average of the last three years ( ) is equal to tons. Figure Total landings (Black line) and by country (western in blu, eastern in red) for GSA 17 from 1975 to 2012 Table Total landings (in tons) for GSA 17 from 1975 to 2012 Year Landings Year Landings Year Landings Catch at age data (in numbers, 10 3 ) are shown in table 3.2-2; the proportion at age is shown in figure Table Catch at age matrix used in the assessment of sardine in GSA 17. 8

10 Catch at age data (numbers, 10 3 ) Age0 Age1 Age2 Age3 Age4 Age5 Age

11 Figure Proportion at age for the catch data of sardine in GSA17. The trend of the cohorts in the catches is shown in figure Each plot represents the number of fish of each age born in the same year. Age 2 can be identified as the first fully recruited age in most of the years. 10

12 Fig Log numbers at age (thousands) of the catch at age used in the assessment. The mean weight at age (in kg) as obtained by sampling of commercial catches is given in figure Throughout the investigated years, mean weight at age for all observed ages varied in similar manner, except in last few years when a slight decrease and increase in mean weight for ages 1-3 and 4-6 was noticed, respectively. 11

13 Fig Mean individual weight at age used in the assessment from 1975 to Management regulations A multi annual management plan for small pelagic fisheries in the Adriatic Sea has been established by the General Fisheries Commission for the Mediterranean (GFCM) in Besides, Italy has been enforcing for years a general regulation concerning the fishing gears and since 1988 a suspension (about one month) of fishing activity of pelagic trawlers in summer. A closure period is observed from 15th December to 15th January from the Croatian purse seiners. In 2011 and 2012 a closure period of 60 days (August and September) was endorsed by the Italian fleet. 3.4 Reference points Biomass reference points, based on the mid-year total biomass estimated with analytical model, were established in 2012 (Tab ). Nevertheless, the WG felt the need to revise the value of Bpa, which has been considered too close to Blim, therefore less conservative. The adopted Blim is still the minimum mid-year biomass value of the assessed time series, which resulted to be consistent among the models used in 2012 and the models applied during this year WG. On the other hand, Bpa is defined as the point at which the probability to be below Blim is lower than 5%. In order to estimate it, a lognormal distribution of Blim is assumed, with a coefficient of variation of 40%. This approximately results in Bpa = 2 * Blim. The new precautionary reference point resulted 15% higher than the 2012 Bpa. The Patterson s reference point of E=0.4 has been adopted as fishing mortality reference point. Table 3.4-1: List of reference points and empirical reference values previously agreed (if any) Indicator Limit Reference point/empiri cal reference value Value Precautionary Reference point/empiric al reference value Value Comments Blim Bpa During the GFCM (2014) new biomass reference points were estimated; Blim=62505, Bpa= B Current biomass: SSB F E 0.4 Current E:

14 Y CPUE Index of Biomass at sea 4 Fisheries independent information 4.1 MEDIAS ECHOSURVEY (Acoustic survey) Brief description of the chosen method and assumptions used Echosurveys were carried out from 2004 to 2012 for the entire GSA 17. In the western part the acoustic survey was carried out since 1976 in the Northern Adriatic (2/3 of the area) and since 1987 also in the Mid Adriatic (1/3 of the area), and it is in the MEDIAS framework since The eastern part was covered by Croatian national pelagic monitoring program PELMON. The data from both the surveys have been combined to provide an overall estimate of numbers-at-age. The survey methods for MEDIAS are given in the MEDIAS handbook (MEDIAS, March 2012). Western Echosurvey: - Length frequencies distribution available from 2004 onward (no LFD for Mid Adriatic in 2004, so the biomass at length in 2004 was assumed equal to the proportion of biomass at length in the 2005 Mid Adriatic survey). - ALKs available for ; - Numbers at age for 2004 to 2008 were obtained applying the sum of the ALKs to the numbers at length. Eastern Echosurvey: - Length frequencies distribution available from No ALKs available. - Numbers at length from 2004 to 2008 were obtained applying the length frequency distribution from the 2009 survey to the total biomass. - Numbers at age were obtained applying commercial ALK from the eastern catches to the eastern echosurvey length distribution and 2012 surveys covered only the Northern part of the area (about 52% of the total area), so the estimated biomass was raised to the total using an average percentage from previous years ( ). 13

15 4.1.2 Historical trends Biomass estimates from the two surveys show a general higher occurrence of sardine on the eastern side of the Adriatic. In 2011 and in 2012, however, the western survey contributed to respectively 83% and 64% of the total estimated biomass. It should be taken into account that in these years the eastern coverage was only half of what it used to be: therefore, an analysis of the spatial variability of sardine stock through the years should be considered to improve the eastern estimates. Pooled total biomass in tons from eastern and western echosurvey ( ) is given in table and it is shown in figure Table : Biomass estimates from the eastern-western acoustic survey from 2004 to 2012 Biomass in metric tons fish numbers Nautical Area Scattering Coefficient Indicator Indicator 14

16 Fig Total biomass (tons) estimated from the eastern and western echosurvey. Figure illustrates the proportion by year of each age class from the surveys. In 2009, 2011 and 2012 a higher percentage of age 0 has occurred. Age 5 and age 6 are scarcely represented. Figure Total proportion of age classes from the acoustic surveys from 2004 to Internal consistency plot (Fig ) was used to explore the survey data and age classes within survey. Each plot relates one age class to the next one. A high correlation coefficient (R2) means the data follows the cohort in the population, while a low R2 means that the data do not follow the cohorts. A poor agreement has been observed for most of ages. 15

17 Figure Internal consistency plot of the echo-survey data used to tune assessment for sardine in GSA Spatial distribution of the resources Acoustic sampling transects and the total area covered are shown in figure Fig Acoustic transects for the western echosurvey (on the left) and the eastern echosurvey (on the right). 16

18 5 Ecological information N/A 5.1 Protected species potentially affected by the fisheries N/A 5.2 Environmental indexes N/A 17

19 6 Stock Assessment Integrated Catch Analysis (ICA) and State-Space Assessment Program (SAM) have been performed to assess the stock status of sardine in GSA17 from 1975 to Acoustic survey data were available and were used as tuning index. Age 0 was not included in the model: the high natural mortality, in fact, drives the biomass to really high and quite unrealistic- values. Since age 0 is not largely represented in the catches, the WG decided not to include it in the assessment. All the input data can be found in section and of the present stock assessment form. 6.1 ICA Integrated Catch-at-age Analysis (ICA) is an age-structured model that bases its algorithm on a separability assumption, in which the estimation of F derives from a multiplicative combination of a year effect (Fy) and an age effect (Sa) (Needle, 2003; Patterson and Melvin, 1996). The years before the separable period are modelled by a conventional VPA using the first year of the separable model as starting point. ICA was performed using the Patterson s software (ICA, version 4.2 Patterson and Melvin, 1996). The model settings are presented in section Model assumptions - Split year assumption - Ages 0 to 6 (since the software doesn t accept less than 6 age class) - M vector estimated using Gislason s equation (Gislason et al., 2010): Age1 Age2 Age3 Age4 Age5 Age Maturity at age: Age1 Age2 Age3 Age4 Age5 Age years for separable constraint - Reference age for separable constraint = 3 - Constant selection pattern model - S to be fixed on last age = Fbar: Catchability model = Linear - Weight for surveys: Acoustic surveys = 1. - No shrinkage 18

20 6.1.2 Scripts N/A Input data and Parameters The data used have been presented in section 4. Discard has not been included in the analysis Results The fishing mortality for age 3 (presented in figure top-right) shows a steep increase starting in 1998 (RefF = 0.40) up to 2012 (RefF = 1.26). In 2012 the Fbar(1-4) is equal to After a strong collapse from tons in 1984 to in 1999, the SSB (figure , bottom-right, dashed line) is constantly increasing up to a value of tons. The 2012 estimation of SSB is equal to The recruitment (age 1 figure , bottom-left) is increasing from the historical minimum in 1998 of thousands to the highest value of the last ten years in The 2012 estimate remains high, with a value of thousands specimen. Fig Total landings in tons (top-left); reference F (F for age 3) with the confidence interval for the separability period (top-right); recruitment (as thousands individuals)(bottom-left); mid year stock biomass and SSB in tons (bottom-right). Table Fishing mortality at age by year for sardine in GSA

21 Fishing Mortality ,0158 0,0303 0,0368 0,0198 0,0169 0,0137 0,0655 0,0415 0,0414 0,0283 0,0288 0,0139 0, ,0402 0,0664 0,073 0,049 0,0472 0,0486 0,1106 0,1079 0,0735 0,0848 0,0504 0,058 0, ,0932 0,1244 0,1665 0,1368 0,1171 0,1347 0,209 0,1717 0,1595 0,1034 0,1037 0,0865 0, ,2109 0,2679 0,2537 0,2609 0,2035 0,2667 0,4004 0,3055 0,2577 0,2611 0,1337 0,2635 0, ,1466 0,2024 0,2188 0,1885 0,1591 0,1894 0,3214 0,2714 0,2182 0,2092 0,1321 0,1793 0, ,1466 0,2024 0,2188 0,1885 0,1591 0,1894 0,3214 0,2714 0,2182 0,2092 0,1321 0,1793 0, ,0118 0,0121 0,0086 0,0033 0,0035 0,0121 0,0175 0,0071 0,0292 0,0589 0,1136 0,1135 0, ,0857 0,1245 0,0898 0,0648 0,0509 0,0435 0,0636 0,0585 0,0734 0,1351 0,2694 0,2909 0, ,1018 0,137 0,1506 0,1301 0,1298 0,1232 0,1051 0,1372 0,1859 0,2373 0,4061 0,632 0, ,2488 0,1826 0,192 0,2041 0,1422 0,1798 0,152 0,1532 0,2875 0,3825 0,4929 0,8453 0, ,205 0,2299 0,2064 0,1802 0,1452 0,1494 0,1513 0,1589 0,2384 0,3479 0,5726 0,8013 1, ,205 0,2299 0,2064 0,1802 0,1452 0,1494 0,1513 0,1589 0,2384 0,3479 0,5726 0,8013 1, ,084 0,0526 0,0521 0,0294 0,024 0,0214 0,0224 0,0325 0,0533 0,0483 0,0582 0, ,6934 0,6633 0,3864 0,2184 0,1783 0,1587 0,1666 0,241 0,3956 0,3586 0,4322 0, ,9929 1,5536 0,9672 0,5468 0,4464 0,3974 0,4169 0,6032 0,9902 0,8976 1,0819 1, ,8456 1,2059 0,991 0,5603 0,4574 0,4071 0,4272 0,618 1,0146 0,9197 1,1085 1, ,3031 1,61 1,0639 0,6015 0,4911 0,4371 0,4586 0,6635 1,0893 0,9874 1,1901 1, ,3031 1,61 1,0639 0,6015 0,4911 0,4371 0,4586 0,6635 1,0893 0,9874 1,1901 1,3861 Table Stock numbers at age (thousands) by year as obtained from ICA model. Stock Abundance (10^6)

22 Table Summary table of the results obtained from the ICA model. Summary Table Recruitment Tot Bio SSB Fbar(1-3) , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , ,

23 6.1.5 Robustness analysis The diagnostic graph of the index SSQ against reference age F (age 3) from ICA is plotted in figure The curves should be U-shaped, with minima fairly close to each other on x-axis (Needle, 2000). Figure Diagnostic graph of the index SSQ against reference age F (age 3) from ICA for sardine in GSA 17. The marginal totals of residuals between the catch and the separable model (Figure ) are overall small as well as trend-free in the separable period ( ). 22

24 Figure Diagnostics: log-residual contour plot (top-left); fitted selection pattern (top-right); year residuals for the catches (bottom-left); age residuals for the catches (bottom-right) Retrospective analysis, comparison between model runs, sensitivity analysis, etc. The model run performed in 2012 using the same time series and a shorter one starting in 2000, give the same trend with no inconsistencies in either the historical perspective or the more recent years (Figure ). 23

25 Figure Estimated biomass from the ICA model with and without 2012 data and using a shorter time series ( ). 6.2 SAM The stock of sardine was asssessed using the State-space Assessment Model (SAM) (Nielsen et al., 2012) in FLR environment with data from 1976 to The SAM environment is encapsulated into the Fisheries Library in R (FLR) (Kell et al., 2007) in the form of the package FLSAM. The statespace assessment model (SAM) is an assessment model which is used for several assessments within ICES. The model allows selectivity to evolve gradually over time. It has fewer model parameters than full parametric statistical assessment models, with quantities such as recruitment and fishing mortality modelled as random effects. One tuning index (acoustic survey covering the entire GSA 17) from 2004 to 2012 was used in the assessment. All assessments are performed with version of FLSAM, together with version 2.5 of the FLR library (FLCore) Model assumptions name Final Assessment range min max plusgroup minyear maxyear minfbar maxfbar fleets Acoustic Survey for the entire GSA 17 from 2004 to 2012 plus.group TRUE age logn.vars catchabilities fleet f.vars catch obs.vars fleet obs.vars catch

26 6.2.2 Scripts Available online Input data and Parameters The input data used in the assessment were the same used to run the ICA model Results SAM outputs are listed in table Tables and Results of the assessment of sardine in GSA 17 obtained from the SAM model. Year Recruits Age 0 (Thousands) Mean Recruits Age 0 (Thousands) Low Recruits Age 0 (Thousands) High Total biomass (tonnes) Mean Total biomass (tonnes) Low 25 Total biomass (tonnes) High Spawing biomass (tonnes) Mean Spawing biomass (tonnes) Low Spawing biomass (tonnes) High Landings (tonnes) Mean

27 Table Results of the assessment of sardine in GSA 17 obtained from the SAM model. Year Landings Landings Yield / Yield / Yield / Mean F Mean F Mean F Mean F SoP (%) Table and give respectively the fishing mortality at age by year and the stock numbers at age by year (in thousand). 26

28 Table F at age estimated from 1975 to 2012 for sardine in GSA 17. year age year age year age year age Table Stock numbers at age for sardine stock in GSA 17 from 1975 to year age year age year 27

29 age year age The average fishing mortality for ages 2-5 (presented in figure , middle panel) starts increasing in 1995, reaching the maximum value of in The estimate for 2012 is equal to The mid year spawning stock biomass (figure , top panel) fluctuates from the highest values in 1984 (about tons) to a minimum in 1999 of tons. After that the stock is constantly increasing: in 2012 reach the highest value registered in the last decade ( tons). The recruitment (age 1, figure , bottom panel) fluctuates around a minimum value of thousands specimen in 1999, to a maximum value of in From 1999 the estimated recruitment is constantly increasing: the value for 2012 is equal to thousands specimen. Figure Mid-year spawning stock biomass (in tons, top), Fbar (mean F 2-5, middle) and recruitment (in thousands individuals, bottom), with the 95% confidence intervals. 28

30 The exploitation rate (F/(F+M)) is shown in figure Figure Exploitation rate (E = F/(F+M)) for age classes 1-3 and 1-4 compared to the Patterson reference point of Robustness analysis Catch residuals did not show any trend. On the other hand, survey data showed some patterns for the most ages (figure ). 29

31 a) b) 30

32 c) Figure Diagnostics: Trend in residuals and fitted values for the acoustic index at age from age 2 (a) to age 4 (c). 6.3 Assessment quality The two models used for the assessment of sardine in GSA17 showed some inconsistencies in the historical perspective, nevertheless the estimation from 1997 onward is coherent between the two models (Figure 6.3-1). Before 1998, ICA showed rather higher estimations in the historical part of the time series (maximum level) respect to SAM estimation, reaching value of approximately tons; SAM, on the other hand, remains at lower values ( tons) that seem more realistic from an ecological point of view. Fig Comparison between the SSB estimate from the ICA and the SAM model from 1975 to

33 The diagnostics of both the models did not shown any problems: only acoustic residuals for ages 2 and 4 in SAM display some trends. Harvest rate (Figure 6.3-2) was also tested with biomass values coming from ICA and SAM models. Due to the high biomass value estimated from ICA, the H derived resulted in really low values until Due to all the considerations mentioned above, and considering that in ICA the goodness of fit is estimated only for the separability period, therefore not allowing an objective evaluation of the goodness of fit for the oldest part of the time series, and recognizing as well that the recent perspective is identical between the two models, SAM was chosen as final model and the advices were based on it. Figure Harvest rate (H=Catch/Biomass) of sardine in GSA 17 from both models (ICA and SAM). 7 Stock predictions N/A 7.1 Short term predictions N/A 7.2 Medium term predictions 7.3 Long term predictions 32

34 8 Draft scientific advice Based on Indicator Analytic al reference point (name and value) Current value from the analysis (name and value) Empirical reference value (name and value) Trend (time period) Status Fishing mortality Fishing mortality Fishing effort Catch F(1-4) 0.66 Exploitation 0.4 E(1-4) 0.42 Stock abundance Biomass Blim=62505 Bpa= Bcurr= I SSB I Recruitment I Final Diagnosis In high risk of overexploitation The estimated biomass is above both Blim (78000 tons) and Bpa ( tons) estimated in 2012, and Blim (62505 tons) and Bpa ( tons) based on the results of the assessment presented above. Since the exploitation rate E(1-4) is slightly higher than the empirical reference point of 0.4, the stock is to be considered in high risk of overexploitation. 33

35 8.1 Explanation of codes Trend categories 1) N - No trend 2) I - Increasing 3) D Decreasing 4) C - Cyclic Stock Status Based on Fishing mortality related indicators 1) N - Not known or uncertain Not much information is available to make a judgment; 2) U - undeveloped or new fishery - Believed to have a significant potential for expansion in total production; 3) S - Sustainable exploitation- fishing mortality or effort below an agreed fishing mortality or effort based Reference Point; 4) IO In Overfishing status fishing mortality or effort above the value of the agreed fishing mortality or effort based Reference Point. An agreed range of overfishing levels is provided; Range of Overfishing levels based on fishery reference points In order to assess the level of overfishing status when F0.1 from a Y/R model is used as LRP, the following operational approach is proposed: If Fc*/F 0.1 is below or equal to 1.33 the stock is in (O L): Low overfishing If the Fc/F 0.1 is between 1.33 and 1.66 the stock is in (O I): Intermediate overfishing If the Fc/F 0.1 is equal or above to 1.66 the stock is in (O H): High overfishing *Fc is current level of F 5) C- Collapsed- no or very few catches; Based on Stock related indicators 1) N - Not known or uncertain: Not much information is available to make a judgment 2) S - Sustainably exploited: Standing stock above an agreed biomass based Reference Point; 3) O - Overexploited: Standing stock below the value of the agreed biomass based Reference Point. An agreed range of overexploited status is provided; Empirical Reference framework for the relative level of stock biomass index 34

36 Relative low biomass: Values lower than or equal to 33 rd percentile of biomass index in the time series (O L) Relative intermediate biomass: Values falling within this limit and 66 th percentile (O I) Relative high biomass: Values higher than the 66 th percentile (O H) 4) D Depleted: Standing stock is at lowest historical levels, irrespective of the amount of fishing effort exerted; 5) R Recovering: Biomass are increasing after having been depleted from a previous period; Agreed definitions as per SAC Glossary Overfished (or overexploited) - A stock is considered to be overfished when its abundance is below an agreed biomass based reference target point, like B0.1 or BMSY. To apply this denomination, it should be assumed that the current state of the stock (in biomass) arises from the application of excessive fishing pressure in previous years. This classification is independent of the current level of fishing mortality. Stock subjected to overfishing (or overexploitation) - A stock is subjected to overfishing if the fishing mortality applied to it exceeds the one it can sustainably stand, for a longer period. In other words, the current fishing mortality exceeds the fishing mortality that, if applied during a long period, under stable conditions, would lead the stock abundance to the reference point of the target abundance (either in terms of biomass or numbers) 35

37 References Azzali, M., Felice, A. De, Luna, M., Cosimi, G., & Parmiggiani, F. (2002). The state of the Adriatic Sea centered on the small pelagic fish populations. Marine Ecology, 23(1), Carvalho G.R., Bembo D.G., Carone A., Giesbrecht G., Cingolani N., and Pitcher T.J. (1994). Stock discrimination in relation to the assessment of Adriatic anchovy and sardine fisheries. Final Project Report to the Commission of the European Communities, EC XIV-1/MED/91001/A. Fiorentino, F., Patti, B., Colloca, F., Bonanno, A., Basilone, G., Gancitano, V., Mazzola, S. (2013). A comparison between acoustic and bottom trawl estimates to reconstruct the biomass trends of sardine and anchovy in the Strait of Sicily (Central Mediterranean). Fisheries Research, 147, Gislason, H., Daan, N., Rice, J. C., and Pope, J. G. (2010). Size, growth, temperature and the natural mortality of marine fish. Fish and Fisheries, 11(2), Kell, L. T., Mosqueira, I., Grosjean, P., Fromentin, J.-M., Garcia, D., Hillary, R. and Scott, R. D. (2007). FLR: an open-source framework for the evaluation and development of management strategies. ICES Journal of Marine Science, 64(4), Needle, C. L. (2003). Course on Fish Stock Assessment Techniques. Workshop, International Council for the Exploration of the Sea, Copenhagen. Needle, C. L. (2000). The Ins and Outs of ICA. Technical Report 04/00, Marine Laboratory, Aberdeen. Patterson, K. R. and Melvin, G. D. (1996). Integrated Catch at Age Analysis - Version 1.2. Technical Report 58, The Scottish Office - Agriculture, Environment and Fisheries Department. Sbrana, M., Ranieri, S. De, Ligas, A., Reale, B., Rossetti, I., & Sartor, P. (2010). Comparison of trawl survey and commercial data on small pelagics from the FAO geographic Sub-Area 9 (Western Mediterranean). Rapp. Comm. Int. Mer Mèditerr., 39, 658. Tinti F., Di Nunno C., Guarniero I., Talenti M., Tommasini S., Fabbri E. and Piccinetti C. (2002). Mitochondrial DNA sequence variation suggests the lack of genetic heterogeneity in the Adriatic and Ionian stocks of Sardina pilchardus. Mar. Biotech. 4: