SAC GFCM Sub-Committee on Stock Assessment

Transcription

1 SAC GFCM Sub-Committee on Stock Assessment 1 DAY MONTH YEAR Date* 28 September 21 Code* MUT61Fer Authors* Fernández, A. M. Affiliation* I. E. O. Centro Oceanográfico de Murcia GFCM Priority S 1 Mullus barbatus - MUT MUT Species Scientific name* Source: GFCM Priority Species 2 Source: - 3 Source: - Geographical area* Western Mediterranean Geographical Sub-Area (GSA)* Combination of GSAs Northern Spain

2 Sheet # Assessment form Basic data on the assessment 1 Date* 28 Sep 21 Authors* Fernández, A. M. Code: MUT61Fer Species Scientific name* Mullus barbatus - MUT Data Source GSA* Mullus barbatus - MUT 6 - Northern Spain Species common name* Red mullet Period of time* Description of the analysis Type of data* Method of assessment* Size composition of commercial catches, official landings and CPUE Tuned VPA (XSA) Y/R analysis (pseudocohort) IEO, Fishermen Associations, Regional Data source* Autonomous Governments Lowestoft (Darby and Flatman, 1994) VIT Software used* (Lleonart & Salat, 1997) Sheets filled out B P1 P2a P2b G A1 A2 A3 Y Other D Z C Comments, bibliography, etc. 114 Abella, A., Caddy, J.F., Serena, F. (1997). Do natural mortality and availability decline with age? An alternative yield paradigm for juvenile fisheries, illustrated by the hake Merluccius merluccius fishery in the Mediterranean. Aquat. Liv. Res., 1: Caddy, J.F. (1991). Death rates and time intervals: is there an alternative to the constant natural mortality axiom? Rev. Fish. Biol. Fish., 2: Carbonell, A. (1997) Discards of the western Mediterranean trawl fleets. Final Report Contract DGXIV-MED/94/27, 142 pp. Darby, C.D. and Flatman, S., (1994). Virtual Population Análisis: version 3.1 (Windows/DOS) user guide. Info. Tech. Ser., MAFF Direct. Fish. Res., Lowestoft, nº 1, 85 pp. Demestre M., M. Sbrana, F. Álvarez and P. Sánchez (1997) Analysis of the interactions of fishing gear in Mullus barbatus fisheries of the Western Mediterranean. J. Appl. Ichthyol., 13: Lleonart J. and J. Salat (1997) VIT: Software for fishery analysis. User s manual. FAO Computerized Information Series (Fisheries). Nº 11. Rome, FAO, 15 pp. García-Rodriguez M. and Fernández A.M.25. Influencia de la geometría de la malla del copo en las captura,selectividad y rendimientos de algunas especies de peces comerciales en el Golfo de Alicante (SE de la península Ibérica). Inf.Tec.Ins.Esp.Oceanogr. 185.

3 Sheet # (page 2) Comments, bibliography, etc Lombarte A., L. Recasens, M. González and L. Gil de Sola (2) Spatial segregation of two species of Mullidae (Mullus surmuletus and M. barbatus) in relation to habitat. Mar. Ecol. Prog. Ser., 26: Martín P., P. Sartor and M. García-Rodríguez (1999) Exploitation patterns of the European hake Merluccius merluccius, red mullet Mullus barbatus and striped red mullet Mullus surmuletus in the western Mediterranean. J. Appl. Ichthyol., 15:

4 Sheet B Biology of the species Code: MUT61Fer Biology Somatic magnitude measured (LH, LC, etc)* Total length Units* Sex Fem Mal Both Unsexed Maximum size observed Size at first maturity Recruitment size 28.5 (1) 12.2 (2) 7.8 (3) Reproduction season Reproduction areas Nursery areas cm May-July Continental shelf (4) Coastal areas Parameters used (state units and information sources) Growth model Length weight relationship L K t Data source a b M sex ratio (mal/fem) Sex Units female male both unsexed 34.5 (5) (6) Comments 1467 (1) Size composition of trawl catches in GSA6. (2) From the Spanish DCR National Programme (3) García-Rodriguez, M. and Fernández, A.M.25. (4) Lombarte, A.; L. Recasens; M. González and L. Gil de Sola (2) (5) Growth parameters adopted in the SGMED-8-3 meeting. (6) Vector of M by size class calculated from Caddy (1991) equation using the PROBIOM Excel spreadsheet (Abella et al., 1997) and transformed to a M at age vector by VIT program: Age M Mean.4

5 Comments 3691 Alternative analysis was also done using the following parameters: Linf = 26.; K =.41; t = -.4 (SGMED-8-3 slow growth) Sheet B (page 2) Age M From PROBIOM (M. barbatus assessment GSA7 29, IFREMER-IEO) Mean.25

6 Sheet P1 General information about the fishery Code: MUT61Fer Data source* Size composition of trawl catches from IEO and Span Year (s)* Data aggregation (by year, average by year for XSA analysis and average for Y/R analysis figures between years, etc.)* Fleet and catches (please state units) Country GSA Fleet Segment Fishing Gear Class Group of Target Species Species Operational Unit 1* Operational Unit 2 Operational Unit 3 Operational Unit 4 Operational Unit 5 ESP 6 E - Trawl (12-24 metres) 3 - Trawls 33 - Demersal shelf species MUT Operational Units* ESP 6 E MUT Fleet (n of boats)* Kilos or Tons Catch (species assessed) Other species caught Discards (species assessed) Discards (other species caught) Effort units 723 Tons 1146 See sheet P2b No days fishing Legal minimum size Total cm total length 1146 Comments

7 Sheet P1 (page 2) Comments tons Mullus barbatus. Trawl landings in GSA6 (red dot: estimated figure for 29) Landings of M. barbatus increased continuously from the earliest 197's reaching 1669 tons in From this year until now a general decreasing trend with some fluctuations is observed. For the southern area of the GSA 6 complete landing data are available for all ports. Because complete data are not yet available for the northern area, data for 29 are provisional.

8 Sheet P2a Fishery by Operational Unit Code: MUT61Fer Page 1 / 1 Data source* OpUnit 1* ESP 6 E MUT Time series Year* Catch Minimum size Average size Lc Maximum size Fleet Year Catch Minimum size Average size Lc Maximum size Fleet Selectivity L L5 7.8 L Selection factor 1.95 Remarks Selectivity parameters for 4 mm diamond mesh in the cod-end (García-Rodriguez and Fernández, 25). 2 Structure by size or age Number (thousands) Total length (cm) Average size distribution ( )

9 Sheet P2a (Page 1 / 1-2 sheet) Structure by size or age

10 Sheet G Indirect methods. Global model Code: MUT61Fer Analysis #* Page 2 / Data source* Gear* Model characteristic Type of model* Software Fitting criterion Bibliographical source Data Year Catch Effort CPUE Year Catch Effort CPUE Adjustment RMS Results Carryng capacity Growth rate Catchability MSY EMSY E.1 Ecurrent a b TACMSY TAC.1 Comments

11 Comments Sheet G (Page 2 / - 2 sheet)

12 Sheet G Indirect methods. Global model Code: MUT61Fer Analysis #* Page 3 / Data source* Gear* Model characteristic Type of model* Software Fitting criterion Bibliographical source Data Year Catch Effort CPUE Year Catch Effort CPUE Adjustment RMS Results Carryng capacity Growth rate Catchability MSY EMSY E.1 Ecurrent a b TACMSY TAC.1 Comments

13 Comments Sheet G (Page 3 / - 2 sheet)

14 Sheet G Indirect methods. Global model Code: MUT61Fer Analysis #* Page 4 / Data source* Gear* Model characteristic Type of model* Software Fitting criterion Bibliographical source Data Year Catch Effort CPUE Year Catch Effort CPUE Adjustment RMS Results Carryng capacity Growth rate Catchability MSY EMSY E.1 Ecurrent a b TACMSY TAC.1 Comments

15 Comments Sheet G (Page 4 / - 2 sheet)

16 Sheet A1 Indirect methods: VPA, LCA Code: MUT61Fer Sex* both Page 1 / 2 Time series Analysis # * 1 Data (mark with X) Size Age X Model (mark with X) Cohorts X Pseudocohorts Equation used # of gears F terminal Catch equation Tunig method Software XSA Lowestoft VPA suite (Darby & Flatman, 1994) Population results (please state units) Minimum Average Maximum Critical Sizes Ages Recruitment Average population Virgin population Turnover Amount (2) x 1** 6 Biomass 397 (2) SSB (2) 73 in tons Average mortality Total F F 2.19 Z (F1 and F2 represent different possible calculations. Please state them) Gear Comments 1339 (1) F terminal from previous separable VPA (2) average F1 is the average Fbar -2 ( ) F2 is the mean F at age ( ) Z=.4+F1

17 Sheet A1 Indirect methods: VPA, LCA Code: MUT61Fer Sex* Both Page 2 / 2 Time series Analysis # * 2 Data (mark with X) Size X Age Model (mark with X) Cohorts Pseudocohorts X Equation used # of gears Catch equation 1 Tunig method Software VIT (Lleonart & Salat, 1997) F terminal 1.3 Population results (please state units) Minimum Average Maximum Critical Sizes Ages 1.25 Recruitment Average population Virgin population Turnover Amount 97.6 Biomass 115 x 1**6 tons Average mortality Total F Gear F 2 Z (F1 and F2 represent different possible calculations. Please state them) Comments 1416 F1 is is the arithmetic mean of F calculated along the different size classes Z=F1+.4

18 Sheet A1 Indirect methods: VPA, LCA Code: MUT61Fer Sex* Page 3 / 2 Time series Analysis # * Data (mark with X) Size Age Model (mark with X) Cohorts Pseudocohorts Equation used # of gears Tunig method Software F terminal Population results (please state units) Minimum Average Maximum Critical Sizes Ages Recruitment Average population Virgin population Turnover Amount Biomass Average mortality Total Gear F 1 F 2 Z (F1 and F2 represent different possible calculations. Please state them) Comments 15

19 Sheet A1 Indirect methods: VPA, LCA Code: MUT61Fer Sex* Page 4 / 2 Time series Analysis # * Data (mark with X) Size Age Model (mark with X) Cohorts Pseudocohorts Equation used # of gears Tunig method Software F terminal Population results (please state units) Minimum Average Maximum Critical Sizes Ages Recruitment Average population Virgin population Turnover Amount Biomass Average mortality Total Gear F 1 F 2 Z (F1 and F2 represent different possible calculations. Please state them) Comments 15

20 Sheet A2 Indirect methods: data Code: MUT61Fer Sex* Both Gear* Trawl Analysis # * 1 Data Data Catch in number by age (x 1 3 ) 1 2 +gp CPUE index for tunned VPA CPUE S. Pola MEDITS

21 Sheet A3 Indirect methods: VPA results Sex* Both Gear* Code: MUT61Fer Page 1 / 1 Trawl Analysis #* 1 Population in figures Stock number at age(start of the year) (x 1 3 ) 1 2 +gp Population in biomass Stock biomass at age (start of the year) 1 2 +gp Fishing mortality rates FBAR FBAR -2 (fast) FBAR -4 (slow)

22 Sheet A3 Indirect methods: VPA results Sex* Gear* Analysis #* Code: MUT61Fer Page 2 / 1 1 Population in figures SSB 1 5 Recruitment Fast Fast Slow Population in biomass Total biomass Fast Slow CPUE age (nº indiv/day) Fishing mortality rates AGE gp BAR

23 Sheet A3 Indirect methods: VPA results Sex* Gear* Log catchability residuals Analysis #* Code: MUT61Fer Page 3 / 1 Population in figures FLEET Population in biomass MEDITS Fishing mortality rates

24 Sheet A3 Indirect methods: VPA results Sex* Gear* RETROSPECTIVE ANALYSIS Analysis #* Code: MUT61Fer Page 4 / 1 Population in figures MEAN F F Population in biomass Tonnes 1 SSB Fishing mortality rates Thousands 2 RECRUITS

25 Sheet Y Indirect methods: Y/R Sex Both Code: MUT61Fer Analysis # 2 # of gears 1 Software VIT (Lleonart & Salat, 1997) Parameters used Vector F Vector M Vector N From a previous separable VPA (see comments in sheet A1) Vector of M at age shown in sheet B Pseudocohort Model characteristics See Lleonart & Salat (1997) page 94. Results Total Gear Current YR Maximum Y/R Y/R F max.25 F.1.17 Current B/R 7.8 Maximum B/R B/R.1 46 Comments Fast Slow SSB tons R mill Turnove B virgen tons F max F F global Comparative resullts for the two sets of growth parameters

26 Sheet Y (page 2) Comments Fast growth Y/R Slow growth Y/R 1 2

27 Sheet D Diagnosis Indicators and reference points Code: MUT61Fer Criterion B SSB F Y CPUE Current value Units 2956 tons 854 tons tons kg/day Reference Point Trend Comments Bmean as reference point (Blow=215) SSBmean as reference point (SSBlow=475 ) Mean Fbar -2 as a reference point (Flow=.515 ) Ymean as reference point (Ylow= 985) Total trawl fishery data. CPUElow= 17.8 Stock Status* Use one (or both) of the following two systems for the stock assessment status description Unidimensional FALSE FALSE FALSE FALSE TRUE FALSE? - (or blank) Not known or uncertain. Not much information is available to make a judgment; U - Underexploited, undeveloped or new fishery. Believed to have a significant potential for expansion in total production; M - Moderately exploited, exploited with a low level of fishing effort. Believed to have some limited potential for expansion in total production; F - Fully exploited. The fishery is operating at or close to an optimal yield level, with no expected room for further expansion; O - Overexploited. The fishery is being exploited at above a level which is believed to be sustainable in the long term, with no potential room for further expansion and a higher risk of stock depletion/collapse; D - Depleted. Catches are well below historical levels, irrespective of the amount of fishing effort exerted; FALSE R - Recovering. Catches are again increasing after having been depleted or a collapse from a previous; Bidimensional FALSE FALSE FALSE FALSE TRUE FALSE Exploitation rate No or low fishing Moderate fishing High fishing mortality Uncertain / Not assessed FALSE TRUE Stock abundance Virgin or high abundance Intermediate abundance Low abundance FALSE Depleted Uncertain / Not assessed

28 Sheet D (page 2) Comments 3324 h Cath in in number of individuals are based on younger ages ( and 1). Average fishing mortality for ages -2 show a general decreasing trend over the studied period. Althought some fluctuations are observed, recruitment has remained more or less constant between Nevertheless recruitment is under the mean for the period in the last two years. SSB has recovered after the minimum observed in 24; in the last four years is above the average for the whole period. Total biomass show wide fluctuations but any trend is observed. Trends in recruitment, Fbar, stocks biomass and SSB are similar for both set of parameters used (fast and slow from SGMED-8-3).

29 Sheet Z Objectives and recommendations Code: MUT61Fer Management advice and recommendations* (1) To reduce the fishing effort 7% (2) More effective control in shelf areas above 5 m depth should reduce the catch of small individuals under the minimum legal size. (3) According to transition analysis (MUT68Fer) the compulsory use of the 4 mm square mesh in the cod-end from 21 onwards should improve trawl exploitation pattern and Y/R by 24%, but a close supervision of the observance of this measure is needed.

30 Advice for scientific research* - To improve biological and growth parameters - Besides on board sampling, sampling at port is also needed 3893

31 Abstract for SCSA reporting Authors Fernández, A. M. Year 21 1 Species Scientific name Mullus barbatus - MUT Source: GFCM Priority Species Source: - Source: - Geographical Sub-Area 6 - Northern Spain Fisheries (brief description of the fishery)* 337 Both species of red mullet, Mullus surmuletus and M. barbatus, are exploited by trawl and artisanal fisheries fleets in GSA 6, althought small gears (trammel nets and gillnets) account only for 5% of the total landings of these species (Demestre et al., 1997). Trawl fisheries developed along the continental shelf and upper slope are multi-specific. Small vessels operate almost exclusively on the continental shelf targeting on red mullets, octopus, cuttlefish and sea breams. Medium and large vessels usually operates on the slope areas targeting on hake and decapod crustaceans, but some of these units can also operate on the continental shelf depending on the season (e.g. red mullet is more intensively exploited from September to November; Martín et al., 1999), the weather conditions or market prices. Landings of M. barbatus increased continuously from the earliest 197's until From this year until now a general decreasing trend with fluctuations is observed. An important fraction (28% of individuals) of M. barbatus are under the minimun legal size. The total number of boats (trawl fleet) in the GSA6 has been reduced 3% from 1998.

32 Source of management advice* (brief description of material -data- and methods used for the assessment) 35 The stock of Mullus barbatus of the GFCM-GSA6 has been assessed using data from the trawl fishery on a time series covering the period The assessment has been carried out applying tuned VPA (Extended Survivor Analysis, XSA) and Y/R analysis on the pseudo-cohort These approaches were performed using monthly size composition of catches, official landings and the growth parameters accorded in the SGMED-8-3 meeting. Length-weight relationships and oogive of maturity were obtained within the framework of the Spanish Data Collection Programme. The vector of natural mortality-at age was obtained from Caddy s (1991) formula using the PROBIOM Excel spreadsheet (Abella et al., 1997).The VPA was tuned with CPUE data from MEDITS surveys and standardised fleet CPUE (by aplying GLM models). Several XSA runs were carried out using different values for the terminal fishing mortality, retaining for the final analysis the value that minimised the SSQ. Software used were the Lowestoft VPA program for the XSA (Darby and Flatman, 1994) and the VIT program (Lleonart and Salat, 1997) for the Y/R analysis from a mean pseudo-cohort. Stock Status* O - Overexploited. The fishery is being exploited at above a level which is believed to be sustainable in the long term, with no potential room for further expansion and a higher risk of stock depletion/collapse; Exploitation rate High fishing mortality Comments Stock abundance Low abundance Cath in number of individuals are based on younger ages ( and 1). Average fishing mortality for ages -2 show a general decreasing trend over the studied period. Althought some fluctuations are observed, recruitment has remained more or less constant between Nevertheless recruitment is under the mean for the period in the last two years. SSB has recovered after the minimum observed in 24; in the last four years is above the average for the whole period. Total biomass show wide fluctuations but any trend is observed. Trends in recruitment, Fbar, stocks biomass and SSB are similar for both set of parameters used (fast and slow from SGMED-8-3).

33 Management advice and recommendations* 1 (1) To reduce the fishing effort 7%. (2) More effective control in shelf areas above 5 m depth should reduce the catch of small individuals under the minimum legal size. (3) According to transition analysis (MUT68Fer) the compulsory use of the 4 mm square mesh in the cod-end from 21 onwards should improve trawl exploitation pattern and Y/R by 24%, but a close supervision of the observance of this measure is needed.

34 Advice for scientific research* 1 - To improve biological and growth parameters - Besides on board sampling, sampling at port is also needed