Czerwinski, I.A. (Ivone Alejandra)

García-Isarch, E. (Eva)

Quinzán, M. (Marta)

English

Repositorio Institucional Digital del IEO

The Spanish shrimp trawlers is one of the most important fleets operating in Mauritania. They target 3 species: -Penaeus notialis (at 20-80 m depth) -Parapenaeus longirostris (at 100-350 m depth) -Aristeus varidens (at 400-800 m depth) in 3 types of fishing operations that can be carried out during the same day.  A critical challenge is to define suitable metrics of effective fishing effort since logbooks only provide information of catches by day. Accurate CPUE obtained from these vessels could be considered good abundance indices of its target stocks, which is of paramount importance for assessment purposes. The objective of this analysis was to use Vessel Monitoring System (VMS) information to robustly infer fleet activity as well as estimate units of effort directed to each of the three target species of the Spanish trawlers operating within the EEZ of Mauritania. The methodology comprised:  1) discrimination between non-fishing and fishing points in VMS data;  2) computation of effort to each target species with respect to depth;  3) comparison with fisheries-dependent as observers’ data for its validation.  As instantaneous speed is known to be uninformative, averaged speed was calculated from the Euclidian distance and time interval between consecutive VMS records. Fishing activity (no fishing, fishing and steaming) was identified by applying a segmented regression to the cumulative frequency distribution of speeds based in the package VMStools. Speed boundaries were then used to select those records where the vessels were identified to be fishing. VMS positions were linked to GEBCO bathymetry to determine each of the three target species according to depth-ranges. We focus on estimating effort as the time spent fishing based on a point summation method. Effort was estimated for each VMS record as the interval since the previous record and validated by checking the results against observers on-board datasets.  ●  Link with logbook data to obtain CPUE (kg/h) by target species ●  Input for stock assessment as abundance indicator Towards effort quantification  through VMS and observers’ data:  the case of shrimp trawlers in Mauritanian waters METHODOLOGY RESULTS NEXT  MOTIVATION Figure 1. Speed distribution calculated given the Euclidian distance and time interval between successive VMS pings of the Spanish shrimp trawlers operating within EEZ Mauritania in 2016 and 2018, where colors represent the speed categories identified by the segmented regression.  Figure 2. The spatial distribution in 2016 and 2018 of raw VMS positions and “fishing” positions after having applied the speed segmented regression rule and assigned to target species according to depth-ranges. ARV: A. varidens (green), DPS: P. longirostris (blue), PEN: P. notialis (red). trip  initial date  final date hauls total pings fishing pings % fishing pings to total pings correct fishing pings %correct fishing pings to total fishing pings 0116 21/03/2016 29/03/2016 46 407 216 53.1 192 88.9 0216 03/04/2016 24/05/2016 274 2327 1317 56.6 1157 87.9 0316 27/05/2016 27/07/2016 321 2733 1470 53.8 1316 89.5 0416 19/08/2016 20/09/2016 217 771 328 42.5 287 87.5 0516 20/11/2016 20/12/2016 182 739 328 44.4 219 66.8 0118 10/01/2018 13/03/2018 292 4806 2901 60.4 2677 92.3 0218 07/05/2018 14/07/2018 357 1629 961 59.0 825 85.8 0318 26/09/2018 12/11/2018 218 1134 509 44.9 462 90.8 0418 19/12/2018 31/12/2018 63 310 151 48.7 134 88.7 The segmented regression indicated that the use of a 2.2-3.3 knots speed filter could provide an effective means of distinguishing the fishing activity for trawling. Using the speed range 2.2-3.3 knots to signify fishing, 49% of records were classified as fishing in each of the years analyzed. Quinzan, M.; Czerwinski, I.A.; García-Isarch, E. Instituto Español de Oceanografía (IEO, CSIC)     m a r t a . q u i n z a n @ i e o . e s  Figure 3. An example of VMS and observer data for one trip (0116, hauls 25 to 36), each point representing one VMS record. The blue boxes represent the fishing activity recorded by the observer (hauls). Calculated vessel speeds between 2.2 and 3.3 knots were assumed to correspond to fishing. False-positive results are VMS records that fall within the speed criteria for fishing, but for which no fishing activity was recorded. False-negative results are VMS records that fall outside the speed criteria for fishing, but which took place during fishing operations. Figure 4. Monthly time series of estimated (from VMS) and observed (registered by observers on-board) effort (hours) in 2016 and 2018 by target species. PEN: P. notialis, DPS: P. longirostris, ARV: A. varidens.   Table 1. Observers’ trips used for detailed comparison and validation of VMS analysis.   In CONCLUSION: •The speed criteria (i.e. 2.2-3.3 knots) provides a simple method for identifying trawling activity of the shrimpers in Mauritanian waters •The estimates of trawling effort by target species obtained from VMS data show consistency in both values and temporal trends with those registered by observers on-board •The adoption of a consistent method for analysing VMS data will help to ensure that calculations of trawling effort are repeatable and comparable among studies ARV DPS PEN ARV DPS PEN 

Towards effort quantification through VMS and observers’ data: the case of shrimp trawlers in Mauritanian waters

http://www.repositorio.ieo.es/e-ieo/bitstream/10508/11908/1/Quinzanetal_TowardsEff_draft5_final.pdf

Towards effort quantification through VMS and observers’ data: the case of shrimp trawlers in Mauritanian waters

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