Stock Assessment Form Demersal species Reference year: Reporting year:

Transcription

1 Stock Assessment Form Demersal species Reference year: Reporting year: [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 {TYPE OF SURVEY}... Error! Marcador no definido Brief description of the direct method used Spatial distribution of the resources Historical trends Ecological information Protected species potentially affected by the fisheries Environmental indexes Stock Assessment {Name of the Model}... Error! Marcador no definido Model assumptions Scripts Input data and Parameters Tuning data 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: Merluccius merluccius - HKE European hake 32 1 st Geographical sub-area: 2 nd Geographical sub-area: 3 rd Geographical sub-area: 07 Gulf of Lions 4 th Geographical sub-area: 5 th Geographical sub-area: 6 th Geographical sub-area: 1 st Country 2 nd Country 3 rd Country France Spain [Country_3] 4 th Country 5 th Country 6 th Country Stock assessment method: (direct, indirect, combined, none) XSA (tuning with MEDITS indices) and Y/R Authors: Angélique Jadaud*, Beatriz Guijarro**, Tristan Rouyer*, Enric Massutí* Affiliation: * IFREMER, 1 rue Jean Monnet, BP 171, Sète (France); **IEO- Centre Oceanogràfic de les Balears; Moll de Ponent s/n; Palma de Mallorca (Spain) 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: Indirect method (you can choose more than one): - XSA - Yield per Recruit analysis 2

4 2 Stock identification and biological information Specify whether the assessment is considered to cover a complete stock unit. If the stock unit limits are more or less known, but for technical reasons the assessment only covers part of the stock (e.g. a GSA area but stock spreads to other GSAs), explain the state of the art of the stock unit knowledge. If there are doubts about the stock unit, state them here. If there is knowledge on migration rates between different stock units that affect the stock state them here. 2.1 Stock unit The Gulf of Lions (GSA07) has been pointed as an individualized area for assessment and management purposes in the western Mediterranean. 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 Total length Units centimeters (LT, LC, etc) Sex Fem Mal Combined Reproduction season All year (winter) Maximum size observed Recruitment season All year (spring) Size at first maturity 29* Spawning area Shelf & upper slope Recruitment size to the fishery 5 Nursery area Shelf 3

5 Table 2-2.2: M vector and proportion of matures by size or age (both sexes) Size/Age Natural mortality(***) from PRODBIOM (Abella et al., 1997) : Mean 0.36 Proportion of matures(*) Table 2-3: Growth and length weight model parameters Sex Units female male Combined Years L cm 100,7 72,8 Growth model K years ** 0.233** t Data source Tagging experiments** Length weight relationship a * b 2.97* M (scalar) 0.36*** sex ratio (% females/total) * Comments 4

6 (*) from new biological parameters estimated from data collected in the GSA 7 ( ) by IFREMER for the DCF. These parameters were length-weight relationship, sex-ratio and maturity ogive and were computed using inbio (R scripts developed by IEO). (**) growth parameters, especially the estimations of K, come from tagging experiments developed by IFREMER Sète in the Gulf of Lions ( Mellon-Duval et al., 2010) and considering Linf from Aldebert & Recasens (1996). (***) from PRODBIOM (Abella et al., 1997) 3 Fisheries information 3.1 Description of the fleet Hake (Merluccius merluccius) is one of the most important demersal target species for the commercial fisheries in the Gulf of Lions (GFCM-GSA07). In this area, hake is exploited by French trawlers, French gillnetters, Spanish trawlers and Spanish long-liners. Around 240 boats are involved in this fishery and, according to official statistics, the total annual landings for the period have oscillated around an average value of 2030 tons (1123 tons in 2012). In 2009, because of the large decline of small pelagic fish species in the area, the trawlers fishing small pelagic have diverted their effort on demersal species. Since 2011, the fishing capacity of French trawlers in GSA 07 has decreased by nearly 30%. The French trawler fleet is the largest in number of boats and catch (42 and 72%, respectively). The length of hake in the trawler catches ranges between 3 and 92 cm total length (TL), with an average size of 21 cm TL. The second largest fleet is the French gillnetters (~41 and 14% respectively, range cm TL and average size 39 cm TL), followed by the Spanish trawlers (~11 and 8%, respectively, range 5-88 cm TL, and average size 24 cm TL), and the Spanish long-liners (~6 and 6%, respectively, range cm TL and average size 52 cm TL). 11% FLEET (number of boats) 6% French trawl 8% 6% LANDINGS (tons) French trawl 42% French gillnet Spanish trawl 14% French gillnet Spanish trawl 41% Spanish longline 72% Spanish longline The hake trawlers exploits a highly diversified species assemblage: Striped mullet (Mullus surmuletus), Red mullet (Mullus barbatus), Anglerfish (Lophius piscatorius), Black-bellied anglerfish (Lophius budegassa), European conger (Conger conger), Poor-cod (Trisopterus minutus capelanus), Fourspotted megrim 5

7 Number of fish Number of fish Number of fish Number of fish (Lepidorhombus boscii), Soles (Solea spp.), horned octopus (Eledone cirrhosa), squids (Illex coindetii), Gilthead seabream (Sparus aurata), European seabass (Dicentrarchus labrax), Seabreams (Pagellus spp.), Blue whiting (Micromesistius poutassou) and Tub gurnard (Chelidonichtys lucerna) French trawlers (average ) Total length (cm) French gillnetters (average ) Total length (cm) Spanish trawlers (average ) Total length (cm) Spanish longliners (average ) Total length (cm) 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* FRA 07 E - Trawl (12-24 metres) 03 - Trawls 33 - Demersal shelf species HKE Operational Unit 2 FRA 07 C - Minor gear with engine (6-18 metres) 07 - Gillnets and Entangling Nets 33 - Demersal shelf species HKE 6

8 Operational Unit 3 ESP 07 E - Trawl (12-24 metres) 03 - Trawls 33 - Demersal shelf species HKE Operational Unit 4 ESP 07 I - Long line (12-24 metres) 09 - Hooks and Lines 34 - Demersal slope species HKE 7

9 Table 3.1-2: Catch, bycatch, discards and effort by operational unit in the reference year Operational Units* 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) FRA 07 E HKE 80 Tons 1088 S. pilchardus, E. encrasicolus, Mullus spp., Solea spp., Lophius spp., S. aurata, D. labrax, Pagellus spp., M. poutassou, T. m. capelanus and Eledone spp. included unknown FRA 07 C HKE 120 Tons 224 S. scombrus, T. lucerna, T. m. capelanus, Lepidorhombus spp. and S. canicula not discarded unknown ESP 07 E HKE 27 Tons 144 Solea spp., Mullus spp., Lophius spp., Pagellus spp., M. poutassou, T. m. capelanus and E. cirrhosa included unknown ESP 07 I HKE 11 Tons 33 L. caudatus, H. dactylopterus, C. conger, P. bogaraveo and P. blennoides not discarded unknown Total

10 Catches (tons) Numbers HKE GSA Total length (cm) 3.2 Historical trends Time series analysis with tables and figures showing the observed trends in catches, landings, fishing capacity or effort Hake catches ( ) Years TOTAL without spanish data ( & ) French trawlers 9

11 Catches in tons Catches 2500 CATCH Hake GSA French trawl Spanish trawl French gillnet Spanish longline Landings COUNTRY French trawlers Spanish trawlers French gillnetters Spanish longliners Discards COUNTRY French

12 trawlers Spanish trawlers Management regulations List current and past (recent) management regulations that affect the different operational fleets and/or the whole fishery. French Trawlers: - Fishing license: fully observed - Engine power limited to 316 KW or 500 CV: Not full compliance - Cod-end mesh size (bottom trawl: square 40 mm or 50 mm diamond -by derogation-): not fully observed - Fishing forbidden within 3 miles (France): not fully observed - Time at sea: fully observed French gillnetters: - Fishing license: fully observed - Maximum length of net: not fully observed Spanish trawlers: - Fishing license: fully observed - Engine power limited to 316 KW or 500 CV: not observed - Mesh size in the codend (before Jun 1st 2010: 40 mm diamond: after Jun 1st 2010: 40 mm square or 50 mm diamond -by derogation-): fully observed - Fishing forbidden <50 m depth: fully observed - Time at sea: fully observed 11

13 Spanish longliners: - Fishing license: fully observed - Number of hook per boat: not fully observed In 2009, GFCM proposed the creation of a High Sea Fishery Restricted Area (FRA, GFCM/33/2009/1) in which the fishing effort for demersal stocks of vessels using towed nets, bottom and mid-water longlines, bottom-set nets shall not exceed the level of fishing effort applied in 2008 in the fisheries restricted area of the eastern Gulf of Lions as bounded by lines joining the following geographic coordinates: 42 40'N, 4 20' E; 42 40'N, 5 00' E; 43 00'N, 4 20' E; 43 00'N, 5 00' E. In the article 4 from the EU Regulation No. 1343/2011 of the European Parliament and of the Council of 13 December 2011, this fisheries restricted area was established and in 2012 both French (Arrêté du 28 décembre 2012, NOR: TRAM A) and Spanish (Orden AAA/1857/2012 de 22 de agosto) governments published their own laws regulating this FRA. 3.4 Reference points Table 3.3-1: List of reference points and empirical reference values previously agreed (if any) B Indicator SSB F Y CPUE Index of Biomass at sea Limit Reference point/emp irical reference value Value Target Reference point/empi rical reference value Value Comments 12

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15 4 Fisheries independent information 4.1 MEDITS Fill in one section for each of the direct methods used. The name of the section should be the name of the TYPE OF SURVEY. Brief description of the direct method used Description of the survey and method applied. One of several tables would have to be chosen: Egg Production Method, Acoustic survey, Trawl. Fishery independent information regarding the state of the red mullet in GSA 07 was derived from the international survey MEDITS. MEDITS surveys have been carried out from late spring to middle summer, between 1994 and 2012, following random depthstratified sampling design. Five depth strata were considered: m, m, m, m and m. The gear used was a GOC 73, an experimental bottom trawl gear, with a cod-end mesh size of 20 mm. Sampling duration depended on the depth of the sampling station: 30 minutes for the samples on the shelf ( m) and 60 minutes for those in the slope ( m). See Bertrand et al. (2002) for further details. The data was assigned to strata based upon the shooting position and average depth (between shooting and hauling depth). Catches by haul were standardized to 60 minutes hauling duration. The abundance and biomass indices by GSA were calculated through stratified means (Cochran, 1953; Saville, 1977). This involves weighting the average values of the individual standardized catches and the variation of each stratum by the respective stratum areas in each GSA: Yst = Σ (Yi*Ai) / A V(Yst) = Σ (Ai² * si ² / ni) / A² Where: A=total survey area Ai=area of the i-th stratum si=standard deviation of the i-th stratum ni=number of valid hauls of the i-th stratum n=number of hauls in the GSA Yi=mean of the i-th stratum Yst=stratified mean abundance V(Yst)=variance of the stratified mean The variation of the stratified mean is then expressed as the 95 % confidence interval: Confidence interval = Yst ± t(student distribution) * V(Yst) / n Length distributions were obtained by the sum of all standardized length frequencies (subsamples raised to standardized haul abundance per hour) over the stations of each stratum. Aggregated length frequencies were then raised to stratum abundance * 100 (because of low numbers in most strata) and finally aggregated (sum) over the GSA strata Spatial distribution of the resources 14

16 Numbers Mean catch (n/h) Mean catch (Kg/h) Include maps with distribution of total abundance, spawners and recruits (if available) Historical trends Time series analysis (if available) and graph of the observed trends in abundance, abundance by age class, etc. for each of the directed methods used. Abundance and biomass upper 95% conf. int. GSA07 lower 95% conf. int upper 95% conf. int. GSA07 lower 95% conf. int MEDITS indices (lengths in numbers/hour) MEDITS indices nb/h Ages

17 5 Ecological information 5.1 Protected species potentially affected by the fisheries A list of protected species that can be potentially affected by the fishery should be incorporated here. This should also be completed with the potential effect and if available an associated value (e.g. bycatch of these species in T) 5.2 Environmental indexes If any environmental index is used as i) a proxy for recruitment strength, ii) a proxy for carrying capacity, or any other index that is incorporated in the assessment, then it should be included here. Other environmental indexes that are considered important for the fishery (e.g. Chl a or other that may affect catchability, etc.) can be reported here. 16

18 6 Stock Assessment An Extended Survivor Analysis (XSA) tuned with MEDITS survey data was carried out over the period , considering age classes from 0 to Extended survivor analysis Model assumptions Three sensitivity analyses were conducted before performing the assessment, in order to assess the effect of different XSA settings on the outcome of the method. First, 5 different shrinkage assumptions (i.e. fse) were tested: 0.5, 1, 1.5, 2 and 2.5 (Figure ). The results showed some differences between the runs only considering the Fbar. The second sensitivity analysis was conducted to assess the effect of the age after which catchability is no longer estimated (i.e. qage assigning values ranging from 0 to 6 (Figure ). The results were found to be robust to this parameter as the runs showed very similar results. The parameters finally retained for the final run are in Table Fig Sensitivity analysis on shrinkage. The shrinkage parameter (fse) was set from 0.5 to 2.5. The resulting time series of spawning stock biomass (left panel, SSB) and fishing mortality (right panel, F bar) were plotted. 17

19 Fig Sensitivity analysis on catchability. The age after which catchability is no longer estimated (qage) was set from 0 to 6. The resulting time series of spawning stock biomass (left panel, SSB) and fishing mortality (right panel, F bar ) were plotted. Fig Sensitivity analysis on shrinkage on the last ages. The shrinkage on last ages was testing using from 1 to 5 last ages. The resulting time series of spawning stock biomass (left panel, SSB) and fishing mortality (right panel, F bar ) were plotted. Table Final parameters used to perform the SSB Fse shk.yrs shk.ages rage qage

20 6.1.2 Scripts If a script is available which incorporates the stock assessment run (e.g. if using FLR in R) it should be provided here in order to create a library of scripts Input data and Parameters Catch-at-age (Numbers in thousands) : landings, discards Age class Total Tuning data Catch-at-age (thousands) MEDITS index ages in numbers/hour ( ) Age class If it is the case add a table per gear (i.e. VIT) Add a table with input parameters and model settings Results Tables and graphs of Total biomass, SSB, Recruitment, F or other outcomes of the stock assessment model with comments on trends in stock size, recruitment and exploitation. 19

21 The SSB shows a decreasing trend over the analyzed period. The highest recruitment values observed over the period are in 1998, and Since 2007, the recruitment follows a decreasing trend and is currently at the lowest level observed Robustness analysis Retrospective analysis, comparison between model runs, sensitivity analysis, etc. A retrospective analysis was carried out for the mean F, recruitment and SSB for the last 5 years. 20

22 Because of the large decline of small pelagic species in the area, trawlers fishing those species have diverted their effort on demersal species in This can explain the divergence of the mean F trajectories obtained from the retrospective analysis after Furthermore, the very high recruitment in 2007 and 2008 can explain the overestimation of the recruitment 2007 and then of the SSB in 2009 (age 2, 0.67% of matures) Assessment quality Stability of the assessment, evaluation of quality of the data and reliability of model assumptions. No trend was detected for the residuals for MEDITS survey, with values between -2 and 2. 21

23 7 Stock predictions When an analytical assessment exists, predictions should be attempted. All scenarios tested (recruitment and/or fishing mortality) should be reported. The source of information/model used to predict recruitment should be documented. 7.1 Short term predictions Short term predictions were implemented in R ( using FLR routines and based on the results of the Extended Survivor Analyses (XSA. Darby and Flatman. 1994) A short term projection table (Table 7.1.1) assuming a status-quo F of Fstq= 1.83 in 2013 and a recruitment of thousands individuals shows that: - Fishing at Fstq from 2012 to 2014 would produce a decrease in catches of 10.74% and an increase in SSB of 12.49% between 2014 and Fishing at F0.1 (0.11) from 2012 to 2014 would generate a decrease of 89.82% of the catches and an increase in SSB of % between 2014 and Table Short term forecast for different F scenarios computed for Merluccius merluccius in GSA 7. Basis: F(2013) =1.83; R( ): (thousands); SSB(2012)= 543 t; Catch (2012)= 1123 t. Change Change Rationale F F Catch Catch SSB SSB catch scenario factor (%) (%) zero catch High long-term yield (F0.1) Status quo Different scenarios

24 Medium term predictions Because no stock-recruitment relationship could be reliably fitted to the dataset (Fig ), no medium term predictions were made. Figure Scatter plot of the SSB/Recruitment. and fit of Hockey stick relationship 7.3 Long term predictions Yield per recruit analysis was used to calculate the reference point F0.1 and the estimated reference fishing mortality (Fref). Reference F was estimated using an R script, using as weights by age the means of the last 3 years and future recruitment as the geometric mean of the last 3 years. The reference point F0.1 was 0.11 and the estimated reference fishing mortality (Fref) was The figure below shows the yield per recruit analysis. 23

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26 8 Draft scientific advice (Examples in blue) 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) Stock Status Fishing mortality Fishing mortality (F 0.1, = 0.11, F current = 1.83) N IO H Fishing effort Catch Stock abundance Biomass 33 th percentile O L SSB Recruitment Final Diagnosis Example: In intermediate level of overfishing and overexploited with low level of biomass D State the rationale behind that diagnoses, explaining if it is based on analytical or on empirical references 25

27 7.4 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 F 0.1 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 ) 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 ) 26

28 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) 27