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 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: Engraulis encrasicolus European anchovy 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), Čikeš Keč 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 - Trawl survey 2

4 Indirect method (you can choose more than one): - ICA - SAM Combined method: you can choose both a direct and an indirect method and the name of the combined method (please specify) 3

5 2 Stock identification and biological information Anchovy (Engraulis encrasicolus) stock is shared among the countries belonging to GSA 17 (Italy, Croatia and Slovenia) and it constitutes a unique stock. Many studies have been carried out regarding the presence of a unique stock or the presence of different sub populations living in the Adriatic Sea (GSA 17 and GSA 18). This has several implications for the management, i.e. differences in the growth features between subpopulations imply the necessity of ad hoc strategies in the management. The hypothesis of two distinct populations claims the evidence of morphometric differences between northern and southern Adriatic anchovy, such as colour and length, and some variability in their genetic structure (Bembo et al., 1996). Nevertheless, many authors warn against the use of morphological data in studies on population structure (Tudela, 1999) and, a recent study from Magoulas et al. (2006), revealed the presence of two different clades in the Mediterranean, one of those is characterized by a high frequency in the Adriatic Sea (higher than 85%) with a low nucleotide diversity (around 1%). 2.1 Stock unit 2.2 Growth and maturity Incorporate different tables if there are different maturity ogives (e.g. catch and survey). Also incorporate figures with the ogives if appropriate. Modify the table caption to identify the origin of the data (catches, survey). Incorporate names of spawning and nursery areas and maps if available. 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 April-October Maximum size observed 18 Recruitment season Size at first maturity 8 Spawning area Adriatic Sea, over continental shelf Recruitment size to the fishery 9 Nursery area Adriatic Sea 4

6 Table 2-2.2: M vector and proportion of matures by size or age (Combined) Size/Age Natural mortality Proportion of matures Table 2-3: Growth and length weight model parameters Sex Units female male Combined Years L Cm 19.4 Growth model K y t 0 Y -0.5 Data source Sinovcic, 2000 Length weight relationship a b 3.0 M (scalar) sex ratio (% females/total)

7 3 Fisheries information 3.1 Description of the fleet Identification of Operational Units exploiting this stock. Use as many rows as needed Table 3-1: 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 Engraulis encrasicolus Operational Unit 2 Italy 17 Purse seiners Sorrounding nets 35 - Herrings, sardines, anchovies Engraulis encrasicolus Operational Unit 3 Croatia 17 Purse seiners Sorrounding nets 35 - Herrings, sardines, anchovies Engraulis encrasicolus Operational Unit 4 Slovenia 17 Purse seiners Sorrounding nets 35 - Herrings, sardines, anchovies Engraulis encrasicolus Operational Unit 5 Slovenia 17 Pelagic trawlers Trawls 35 - Herrings, sardines, anchovies Engraulis encrasicolus 6

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

9 3.2 Historical trends The historical trend in landings is shown in figure After the drop from more than 50,000 tons 1980 to about 6,000 tons in 1987, the landings started to increase again, reaching the highest value of the time series with 58,600 tons in In the last five years the landings started to decrease again. The 2012 value is equal to 32,924 tons, and the average for the last three years is 37,496. Figure : Total landings (in black) and by country (Western in blue and Eastern in red) for GSA 17 from 1976 to The trend of the cohorts in the catches is shown in figure 3.2. Each plot represents the number of fish of each age born in the same year. 8

10 Figure 3.2.2: 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 A decrease of the mean individual weight has been observed for all ages. Figure 3.2.3: Mean weight at age (kg) in the catches. 3.3 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 Reference points Table 3.3-1: List of reference points and empirical reference values previously agreed (if any) Limit Reference Target Reference Indicator point/emp point/empi Value irical rical Value Comments reference value reference value B SSB Blim Bpa GFMC, 2012 (based on ICA assessment method and midyear total biomass values) F E 0.4 Patterson s value 9

11 Y CPUE Index of Biomass at sea 10

12 4 Fisheries independent information 4.1 Acoustic Surveys Fill in one section for each of the direct methods used. The name of the section should be the name of the direct method used Brief description of the chosen method and assumptions used Description of the method and assumptions used. One of several tables would have to be chosen: Egg Production Method, Acoustic survey, Trawl. Direct methods: acoustics Specify if numbers are per km 2 or raised to the area, assuming the same catchability. Specify the ageing method or the age slicing procedure applied, specify the maturity scale used. In case maturity ogive has not been estimated by year, report information for groups of years. Table 4.1-1: Acoustic cruise information. Date Cruise R/V Target species Sampling strategy Sampling season Investigated depth range (m) Echo-sounder Fish sampler Cod end mesh size as opening (mm) ESDU (i.e. 1 nautical mile) TS (Target Strength)/species Software used in the post-processing Samples (gear used) Biological data obtained Age slicing method Maturity ogive used 11

13 Table 4.1-2: Acoustic results, if available by age or length class Biomass in metric tons fish numbers Nautical Area Scattering Coefficient Indicator Indicator Spatial distribution of the resources Acoustic sampling transects and the total area covered are shown in figure Figure Acoustic transects for respectively the western survey (on the left) and the eastern survey (to the right) Historical trends Biomass estimates from the two surveys show a much higher occurrence of anchovy on the western 12

14 side of the Adriatic. In 2008 the western survey contributed to more than 85% of the total estimated biomass. The trend has been stable in the 4 years, with the estimated biomass for 2012 (540,434 tons) slightly increasing respect to 2011 (474,920 tons). Pooled total biomass from eastern and western echosurvey ( ) is shown in figure Figure 4.1.2: Total biomass (tons) estimated from the eastern and western echosurvey. Figure illustrates the proportion by year of each age class from the surveys. In 2008 a higher percentage of age 0 occurred. Age 3 and age 4 are scarcely represented in the estimation (disappearance of age 4 in 2012). Figure 4.1.3: Total proportion of age classes for the two surveys. In Figure the trend of the cohorts in the acoustic survey is shown. Each plot relates one age class to the next one. A high correlation coefficient (R 2 ) means the data follows the cohort of the population, a low R 2 means that the data do not follow the cohorts. A poor agreement has been observed for most of ages. 13

15 Figure 4.1.4: Pair-plots of the cohorts observed in the acoustic index. 14

16 5 Ecological information 5.1 Protected species potentially affected by the fisheries N/A 5.2 Environmental indexes N/A 15

17 6 Stock Assessment Integrated Catch Analysis (ICA) and Stock Assessment Model (SAM) have been performed from 1976 to 2012, using the split year assumption (Cingolani et al., 1993). Acoustic survey was used as tuning index for the assessment of anchovy in GSA 17: following the split year assumption, acoustic estimates from 2004 were used as tuning index for 2005 data, and so on. 6.1 ICA Model assumptions The final assessment of anchovy was carried out by fitting the integrated catch at age model (ICA) with a separable constraint over a ten-year period, tuned with the Acoustic survey ( ). ICA was performed using the Patterson s software (ICA, version 4.2 Patterson and Melvin, 1996). The model settings are presented in section Split year assumption - Ages 0 to 5 (since the software doesn t accept less than 6 age class) - M vector estimated using Gislason s equation (Gislason et al., 2010): Age0 Age1 Age2 Age3 Age4 Age Maturity at age: Age0 Age1 Age2 Age3 Age4 Age years for separable constraint - Reference age for separable constraint = 2 - Constant selection pattern model - S to be fixed on last age = Fbar: Catchability model = Linear - Weight for surveys: Acoustic surveys = 1 - No shrinkage Scripts N/A Input data and Parameters The data used have been in part presented in section 4. Catch at age data are shown in figure and reported in table Discard has not been included. 16

18 Figure Proportion at age for the catch data of anchovy in GSA17. Table Catch at age matrix used in the assessment of anchovy in GSA 17. Age0 Age1 Age2 Age3 Age4 Age

19 Results The fishing mortality for age 2 (presented in figure 6.1.2, top-right) shows a constant increase starting in The maximum value observed, equal to 2.2, is in The estimation for 2012 showed drop to a value of 1.0. The total biomass (figure 6.1.2, bottom-right, dark line) shows fluctuations between higher and lower value since the beginning of the time series: the average stock biomass from 1976 to 2012 is 838,888 tons and the estimation for 2012 is 652,074 tons. The SSB (figure 6.1.2, bottom-right, dashed line) estimation for 2012 is of 212,291 tons. The recruitment (age 0 figure 6.1, bottom-left) is quite stable, with fluctuations between 27,349,890 and 194,091,020 thousands individuals. The trend in 2012 is positive. The drop observed in the F value from 2011 to 2012 is strange and would need to be further investigated. Figure 6.1.2: Total landings in tons (top- left); reference F (F for age 2) with the confidence interval for the separability period (top- right); recruitment (in thousands individuals)(bottom- left); starting year biomass (full line) and mid-year SSB (dashed line) in tons (bottom- right). 18

20 Table and give respectively the fishing mortality at age by year and the stock numbers at age by year (in thousand). In table the summary of the overall results of the ICA model. Table 6.1.2: Fishing mortality at age by year. Fishing Mortality Table 6.2.3: Stock numbers at age by year (thousands) Stock Abundance (10^6)

21 Table 6.2.4: Summary table of the results obtained from the ICA model. Summary Table Recruitment Tot Bio MidYearBio SSB Fbar(1-3) The exploitation rate (F/(F+M)) is shown in figure

22 Figure 6.1.3: Exploitation rate (E = F/(F+M)) for age classes 0-3, 1-2 and 1-3 resulting from ICA analysis. The harvest rate (C/B) calculated for 2012 is equal to 19.6%, and the average from 1976 to 2012 is equal to 15.4% Robustness analysis The diagnostic graph of the index SSQ against reference age F (age 2) from ICA is plotted in figure The curves should be U-shaped, with minima fairly close to each other on x-axis (Needle, 2000). The marginal totals of residuals between the catch and the separable model shows a clear year-trend that goes from a clear underestimation of the catches from 2005 to 2009, to a strong underestimation in the last three years. No age effect was observed (see figure 6.1.5). 21

23 Figure 6.1.5: 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). High CVs (CV>20) have been estimated for the F value in 2012, and in the abundance estimation in the separable period Retrospective analysis, comparison between model runs, sensitivity analysis, etc. The robustness of the analysis has been tested against the results from the assessment presented during the GFCM working group on small pelagics in The ICA assumptions have been changed from one year to the other, due to instabilities in the model used (the model was not converging). This issue has driven changes in the general perspective on the historical series as well as some inconsistencies in the recent estimates (Figure 6.1.4). On the overall, even if the trend in biomass did not change, the minimum and maximum values observed in the time series were strongly modified: since the last year reference points have been estimated based on the empirical observation of the time series, these inconsistencies should be further investigated. 22

24 Figure 6.1.6: Comparison between past and current estimation of mid-year biomass from ICA models: this year assessment (2013, red line), last year assessment (2012, green line), short time series, last year assessment (SS2012, blue line). 6.2 SAM The stock of anchovy 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 state-space 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. Since the spawning takes place mostly in spring-summer (Zorica et al., 2013), the assessment was carried out taking into account a conventional birth date on the first of June (split-year), as in Santojanni et al. (2003). Consequently, all data were shifted by 6 months in order to have each year compounded by the time interval ranging from the first of June, up to May 31 st of the following year. All assessments are performed with version of FLSAM, together with version 2.5 of the FLR library (FLCore) Model assumptions Model settings are summarized in table Table SAM configuration settings for stock assessment of anchovy in GSA 17. 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 logn.vars catchabilities fleet

25 catchabilities catch NA NA NA NA NA NA f.vars catch obs.vars fleet obs.vars catch Scripts Available online Input data and Parameters The input data used in the assessment were the same used to run the ICA model and presented in section 3.2, and Results SAM outputs are listed in Table Table Results of the assessment of anchovy 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 24 Total biomass (tonnes) High Spawing biomass (tonnes) Mean Spawing biomass (tonnes) Low Spawing biomass (tonnes) High Landings (tonnes) Mean

26 NA NA NA NA NA NA NA Landings (tonnes) Low Landings (tonnes) High Yield / SSB (ratio) Mean Yield / SSB (ratio) Low Yield / SSB (ratio) High Mean F ages 1-2 Mean Mean F ages 1-2 Low Mean F ages 1-2 High Mean F ages 0-1 SoP (%) NA NA NA NA NA NA NA NA NA NA NA Table and give respectively the fishing mortality at age by year and the stock numbers 25

27 at age by year (in thousand). Table F at age estimated from 1976 to 2012 for anchovy in GSA 17. year age year age year age year age Table Stock numbers at age for anchovy stock in GSA 17 from 1976 to year age E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E+03 year age E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E+06 26

28 3 4.19E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E+04 year age E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E+03 year age E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E-01 The average fishing mortality for ages 1-2 (presented in figure , middle) started increasing in 1995, reaching the maximum value of in The estimate for 2012 is equal to The mid year spawning stock biomass (figure , top) fluctuated from the highest values in the late 70 th (about tons) to a first drop in the 1986 with a biomass of tons. After that the stock recovered to about tons in 1995 and then decreased again to a minimum of 105,873 tons in A third phase saw a new recovery up to tons in In 2012 the estimated SSB is around tons. The recruitment (age 0 figure , bottom) fluctuates around a minimum value of thousands specimen in 1986, to a maximum value of in A second peak was registered in 2005, with a value of thousand specimen. The CIs for all the variables in the last couple of years increase significantly. Besides, the drop in F from 2011 to 2012 is unnatural and need further investigation. 27

29 Figure Anchovy, GSA 17, Mid-year spawning stock biomass (in tons, top), Fbar (mean F 1-2, middle) and recruitment (in thousands individuals, bottom), with the 95% confidence intervals. Figure 6.2.2: Exploitation rate of different age groups (0-3; 1-2; and 1-3) compared to the Patterson reference point of 0.4. The harvest rate (C/B) calculated for 2012 is equal to 26.6%, and the average from 1976 to 2012 is equal to 17.9%. 28

30 6.2.5 Robustness analysis Catch residuals did not show any trend. On the other hand, survey data showed some patterns for most ages (figure ). a) b) 29

31 d) Figure 6.2.X: Diagnostics: Trend in residuals and fitted values for the acoustic index at age from age 0 (a) to age 4 (d) Retrospective analysis, comparison between model runs, sensitivity analysis, etc. The comparison between SAM with and without the 2012 data did not show any inconsistency. 6.3 Assessment quality The two models used for assessment of anchovy in the GSA 17 this year showed inconsistencies. Namely, ICA and SAM showed some differences in the historical part of the time series (both minimum and maximum levels). Nevertheless, from 1997 the two models give the same results, with just a small discrepancy in the last couple of year. Both the models showed some problems in the diagnostics: ICA partial residuals show a clear yearly trend, nevertheless, SAM shows strong trends in the residuals for the acoustic fitting for the ages 1 to 3 and a high CI in the last years estimations. Besides, both the models register an unusual drop in F in The harvest rate (Figure 6.3.1) was also tested with biomass values coming from both models and this seems consistent between the two. Given all the above considerations, we did not find enough scientific evidences to support the choice of one model respect to the other, therefore were both taken into account for management advises. Consequently, due to the uncertainty in the historical estimates, it was not possible to 30

32 evaluate new reference points. Nevertheless, the percentile level of the current biomass was computed respect to the overall time series: from the ICA model, current biomass is in the 12th percentile, while from SAM model is in the 19th percentile. Figure 6.3.1: Comparison between ICA estimates and SAM estimates for SSB from 1976 to Figure 6.3.2: Harvest rate (H=Catch/Biomass) of anchovy in GSA 17 from both models (ICA and SAM) 7 Stock predictions N/A 7.1 Short term predictions 7.2 Medium term predictions 7.3 Long term predictions 31

33 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 1.35 Exploitation E 0.4 E(1-3) 0.52 D IO L Stock abundance Biomass 12 th and 19 th precentile D O SSB Recruitment stable Final Diagnosis In overfishing and overfished The rationale behind the diagnosis in overfishing is based on the exploitation rate (E), which has been estimated as the average of the E derived from the two models presented above: the value of 0.52 is higher than the reference point for E of 0.4, therefore the stock is considered in overfishing. The diagnosis overexploited is due to the low biomass estimates (between 12 th and 19 th percentile for respectively ICA and SAM). Regarding the biomass reference point estimated in 2012 for Blim ( tons) and B pa ( tons), this year biomass is slightly above B lim ( tons average between mid year biomass from SAM and ICA). Nevertheless, since the two models presented show some internal inconsistencies, some differences in the historical estimates, and strong changes in the historical perspective respect to the assessment conducted in 2012 on which the reference points have been based, it is suggested to revise the entire assessment next year and to take these estimation with caution. 32

34 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 Relative low biomass: Values lower than or equal to 33 rd percentile of biomass index in the time series (O L) 33

35 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) 34

36 References Bembo, D. G., Carvalho, G. R., Cingolani, N., and Pitcher, T. J. (1996). Electrophoretic analysis of stock structure in Northern Mediterranean anchovies, Engraulis encrasicolus. ICES Journal of Marine Science, 53, Cingolani, N., Kirkwood, J., Giannetti, G., Arneri, E., and Levi, D. (1994). Note on the stock assessment of Engraulis encrasicolus and Sardina pilchardus (Walb.) of the northern and central Adriatic sea. Technical report, FAO-GFCM 3rd Technical Consultation on Stock Assessment in the Central Mediterranean, FAO Fish. Rep. 533 (suppl.): 1-5, Tunis 8-12 November. 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), Magoulas, A., Castilho, R., Caetano, S., Marcato, S., and Patarnello, T. (2006). Mitochondrial DNA reveals a mosaic pattern of phylogeographical structure in Atlantic and Mediterranean populations of anchovy (Engraulis encrasicolus). Molecular Phylogenetics and Evolution, 39, Needle, C. L. (2000). The Ins and Outs of ICA. Technical Report 04/00, Marine Laboratory, Aberdeen. Needle, C. L. (2003). Course on Fish Stock Assessment Techniques. Workshop, International Council for the Exploration of the Sea, Copenhagen. Nielsen, A. et al State-space models as an alternative to overparameterised stock assessment models. In preparation. 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. Santojanni, A., Arneri, E., Barry, C., Belardinelli, A., Cingolani, N., Giannetti, G., and Kirkwood, G. (2003). Trends of anchovy (Engraulis encrasicolus, L.) biomass in the northern and central Adriatic Sea. Scientia Marina, 67(3), Tudela, S. (1999). Morphological variability in a Mediterranean, genetically homogeneous population of the European anchovy, Engraulis encrasicolus. Fisheries Research, 42, Zorica, B., Vilibić, I., Keč, V. Č., and Šepić, J. (2013). Environmental conditions conducive to anchovy (Engraulis encrasicolus) spawning in the Adriatic Sea. Fisheries Oceanography, 22(1),