GeoCrust 2.0 a Geographical Information System for Monitoring the Portuguese Crustacean Trawl Fishery using VMS, Landings and Logbooks Data

Transcription

1 FAO - Marine Resources Department (FIRM) GeoCrust 2.0 a Geographical Information System for Monitoring the Portuguese Crustacean Trawl Fishery using VMS, Landings and Logbooks Data Manuel Afonso-Dias and Carlos Pinto with Joana Simões University of Algarve Faro, Portugal GeoPesca project: MARE (March 2004 February 2007) Supported by the European Union Co-financed by ERDF 1

2 PRESENTATION OUTLINE 1. Background crustacean fishery 2. GeoCrust 2.0 software description 3. Present and future developments + Software live demonstration 2

3 Background 3

4 1. Background FISHERY - LOCATION Portugal Lisbon Spain Morocco SeaWiFS Project, NASA/Goddard Space Flight Center and ORBIMAGE 4

5 1. Background FISHERY - TARGET SPECIES C.J. Chapmam Parapenaeus longirostris Deepwater rose shrimp Nephrops norvegicus Norway lobster Aristeus antennatus Blue and red shrimp 3 target secies: [ 2005 > Parapenaeus: 100 t; Nephrops: 423 t; Aristeus: 8 t ] Different depth range distribution ( m) Large degree of overlapping Dependence on mud sediments 5

6 1. Background FISHERY FLEET Crustacean trawlers at the fishing port of Olhão M.Afonso-Dias 9 33 fishing trawl licenses - 55 mm mesh size 9 Average characteristics: 25 m LL 124 TAB 563 HP 6

7 1. Background MONICAP Portuguese Vessel Monitoring System Land Station Inmarsat C Satellites Fisheries Inspection Control Center GPS Satellites Blue Box Mobile Unit Modificado de: VMS (MONICAP) fully working since mid 1990 s GPS positions and vessel speed in 10 minutes intervals send in packages (8/8 hours) 7

8 1. Background PRESENT SITUATION Monitoring and stock assessment: IPIMAR + ICES WG Fisheries data collected by DGPA VMS for fisheries surveillance and law enforcement Landings reported without any spatial reference (all area) Logbooks considered highly unreliable => Spatial distributions of catch and fishing effort unknown! 8

9 GeoCrust 2.0 Description 9

10 MAIN GOAL To make use of the VMS data of the Portuguese crustacean trawl fleet to obtain, map and analyse geo-referenced fishing effort and catch rates data (crossing effort with landings and logbook data) GeoCrust 2.0 was extended in order to analyse the Portuguese finfish fishery 10

11 PROGRAMMING LANGUAGE & DATABASE Application: developed with MapObjects and Visual Basic Database: MySql (in a Linux server) INPUT DATA (for each vessel) Landings: sales notes by species Landings declarations: catch report produced by the captain Log-books: daily data on catch and nº fishing operations VMS: date&time, lat / long and speed (10 interval) 11

12 DIGITAL MAPS Produced from Fishing Charts of the Portuguese Hydrographic Institute Maps extended now to the entire Portuguese continental coast 12

13 MODULES Module 1 Preliminary Analysis Module 2 Fishing Trips Definition Module 3 Trawl Hauls Definition Module 4 Mapping Fishing Effort and Catch Rates + Two complementary modules 13

14 Module 1 Preliminary Analysis Application for the preliminary analysis of the VMS data that includes: To analyse vessel speed frequency distributions To map the spatial distribution of each vessel fishing activity and produce preliminary maps of fishing effort To detect and correct errors 14

15 PRELIMINARY ANALYSIS Speed frequency distribution 15

16 PRELIMINARY ANALYSIS Spatial distribution - Raw data Navigation and fishing trawl activity 2003 data 16

17 PRELIMINARY ANALYSIS Spatial distribution Speed filtered data Fishing trawl activity 2003 data 17

18 PRELIMINARY ANALYSIS Fishing effort - Speed filtering & density grid Grid squares =0.03 x 0.03 nm 2003 data 18

19 Module 2 Fishing Trips Definition Application to identify fishing trip limits (beginning and end) All fishing trips end-up with a landing (sale in fish market) Beginning and End: definition based on the departure and return from and to port with one reported landing - Semi-automatic or automatic procedures Information produced in each fishing trip stored in the database 19

20 FISHING TRIPS DEFINITION Catch data Log-book Landing declaration Sales note Fishing trip Beginning End 20

21 Module 3 Trawl Hauls Definition Application to identify trawl haul limits (beginning and end) within a fishing trip (previously identified) Beginning and End: definition based on the analysis of the variation of vessel speed with time and change of direction automatic and semi-automatic procedures The information produced on each trawl haul is stored in the database 21

22 TRAWL HAULS DEFINITION Machine learning techniques = algorithms to guess trawl hauls ( Bayesian networks and Classification trees) 22

23 Fishing trips OUTPUT DATA (for each vessel with VMS data) Valid / Partially valid Fishing ports (departure and arrival) Duration and distance travelled Related landing and log-books data Trawl hauls (within each valid fishing trip) Duration and distance Depth strata and Fishing grounds 23

24 Module 4 Mapping Application to map the spatial distribution of trawl hauls and catch rates FISHING EFFORT Spatial display of trawl hauls for one or more vessels for a selected period of time and an area (Total Area, Region or Fishing ground) Two types of spatial representation 24

25 FISHING EFFORT - MAPPING Linear representation 2003 data 25

26 FISHING EFFORT - MAPPING Grid density representation Grid squares =0.03 x 0.03 nm 2003 data 26

27 2. Descrição da Aplicação GeoCrust 2.0 Jornadas INIP-Angola, Novembro 2006 FISHING EFFORT DATA ANALYSIS n = Fishing Hours by Fishing ground & Quarter A B C D E F G % st Quarter 2nd Quarter 3rd Quarter 4th Quarter 0 A B C D E F G Out Fishing ground / Quarter 2003 data 27

28 Module 4 Mapping CATCH RATES (LPUE) Fishing effort crossed with landings to calculate LPUE for one or more vessels, for a selected period of time and area (Total Area, Region or Fishing ground) Only data from fishing trips performed exclusively within a Region or Fishing Ground were used to calculate LPUE - Exclusive fishing trips 28

29 CATCH RATES - MAPPING Pie chart representation Norway lobster Rose shrimp Blue and red shrimp Other crustacea Molluscs Fishes 2003 data 29

30 kg/h Rose shrimp CATCH RATES DATA ANALYSIS LPUE by Quarter and Fishing Ground 1st Quarter 2nd Quarter 3rd Quarter 4th Quarter A B n = 3804 C D E F G 0 A B C D E F G Fishing Ground / Quarter kg/h Norway lobster A B C D E F G Fishing Ground / Quarter kg/h A B C D E F G Fishing Ground / Quarter Blue and red shrimp 2003 data 30

31 Complementary Modules: Statistics To extract and analyse data from the database: landings, effort and LPUE, in a spatio-temporal basis, for one or more vessels Fishing activity visualization To visualize the activity of the fishing vessels of one or more vessels, for a selected period of time 31

32 2.5 FISHING REGIME Fishing Trip Duration (days) Average values n = 1283 Days F M A M J J A S O N D Month Nº Haul / fishing trip Haul duration (hours) Nº Hours 4 F M A M J J A S O N D Month data 32

33 Present and future developments 33

34 3. Present and Future Developments PRESENT AND FUTURE DEVELOPMENTS System Implementation in Portugal For crustacean and finfish trawl fisheries The GeoPescas website project 34

35 3. Present and Future Developments PRESENT AND FUTURE DEVELOPMENTS The GeoPescas website project output examples 35

36 3. Present and Future Developments PRESENT AND FUTURE DEVELOPMENTS System Implementation in Portugal Stock assessment based on catch and effort data by fishing ground Other studies, e.g., closed area impact Sines Box > 2003 data 36

37 3. Present and Future Developments PRESENT AND FUTURE DEVELOPMENTS System adaptation to other trawl fisheries To develop projects to adapt the system to trawl fisheries in other countries Generalization of the application To develop a web application (Java) for the analysis of VMS and fisheries data from vessels operating with any type of gears (e.g., longline fisheries) Sesimbra black scabbard fish fishery 37

38 E Project Team Scientific Coordinator Manuel Afonso-Dias (Fisheries biologist) Computer porgrammers Carlos Pinto (Computing programmer) Joana Simões (GIS programmer) Collaborators André Pires and P. Fernandes (Data processing) Carla Vaz (digital maps) Daniel Gomes (website design) Isabel Afonso-Dias (website contents) data 38