SHARED MANAGEMENT OF FISHERY RESOURCES IN TANZANIA Presented at International Institute of Fisheries, Economics and Trade conference, 12-15 July 2016; AECC, Aberdeen, Scotland, UK. Fatma Sobo, Assistant Director of Fisheries, Ministry of Agriculture, Livestock and Fisheries, Tanzania. fsoboster@gmail.com
PRESENTATION OUTLINE Introduction; History of Data collection and its challenges; Sampling protocol; Data dependent program; Cost comparison; Implication of fisheries management; and Conclusion.
INTRODUCTION Well endowed with water resources; Sharing three of the largest and most important inland lakes in Africa; Lake Victoria Lake Tanganyika Lake Nyassa; Diverse river system; Numerous wetlands; and Coastline of 1424 km long A SIGNIFICANT FISHERY SECTOR
Fisheries Potential (Small scale) S/N Water body Total Area Tanzania share Coverage (%) Estimated Fisheries Resources 1. Lake Victoria 68,800 35,088 51 1,550,211 2. Lake Tanganyika 32,900 13,489 41 295,000 3. Lake Nyasa 30,800 5,760 20 168,000 4. Marine (Territorial sea) 64,000 64,000 100 100,000 5. Other inland water bodies 5,000 5,000 100 30,000
Fisheries categories Artisanal small scale operating in shallow waters using small sized vessels and gears non mechanized but employs less technology The artisanal fishery is the most important fisheries as it support majority of the fishing communities. Industrial Distant Water Fishing Nations EEZ - Tuna and tuna like species including Yellowfin, Bigeye, Marlins, Sword fish and, Sharks Deep Sea Fishing Authority was established with the aim of overseeing all matters pertaining to deep sea fishing in the United Republic of Tanzania. The fishery is operating under license agreement and catches are landed to their (DWFN) destinations
History of Data Collection in TZ Data were collected since 1960 few landing sites; 1986 1996 TANFIS sampling; 1997 2001 Dormant period Change of Admin system (Centralised Decentralised) 2002 2007 SADC-RFIS introduction of CAS 2006 2007 UNU-FTP project Update ( CAS) and IOTC (OFCF) 2009 FAO UNU-FTP Project 2010 RECOMAP - Update CAS Database 2014 Web based Database
Why modifies the system of fisheries data collection and processing The main problems/challenges in the fisheries monitoring system are: Lack of human and financial resources; Lack of capacity/knowledge in fisheries monitoring at local level; Lack of appropriate, cost effective data collection systems; Lack of reliable, adequate and accurate information; and Gaps in data collection, processing and analysis
Tanzania sampling protocol Stratification - All administrative districts strata In each strata 2 to 3 LS have been sampled (Random selection) Boat/Gear combination were used to collect data Data were collected for 16 sampling days per month; (FAO sample based survey) Sampling -selecting a few measurements to estimate the total weight of the target population. A minimum of 31 records per gear type strata of any given LS per unit sample is needed for 95% confidence level in the lowest level analysis
Current System: Fishery - dependent data monitoring 5 Costal District were used as pilot area; The districts were used as a strata; In each strata 2 landing sites were randomly selected; (Total 10 LS for 5 strata); In each landing sites 2 BMU member from Statistical committee were trained (20 data enumerators); The sampling days were reduced from 16 to 10 days; The data collection form were translated to Kiswahili; Fish species were identified up to local names;
Data Quality (mean value at 95% CL) Gear_Type Trips Fishing Time Gears fishermen Gear*hours Mean SE Mean SE Mean SE Mean SE Dema Traps 5,099 22.8 0.08 10.9 0.62 1.9 0.31 248.0 14.18 Gill Net 2" 1,748 6.2 0.10 9.3 1.30 2.1 0.04 52.8 6.71 Gill Net 2.5" 4,633 6.2 0.06 11.0 0.22 4.1 0.07 69.3 1.60 Hand Held 202 7.4 0.27 4.8 2.47 2.0 0.04 28.0 13.33 Nets Hand Line 11,064 7.0 0.04 3.0 0.04 1.7 0.02 20.8 0.37 Ring Net 828 7.3 0.13 1.0 0.06 19.5 0.52 7.7 0.42 Long Line 1,480 9.2 0.26 31.1 2.75 1.9 0.13 372.0 37.65 Shark Nets 1,551 22.0 0.21 13.4 0.25 4.7 0.06 295.8 6.17 Stick/Spear 3,129 5.8 0.08 5.1 1.12 3.3 0.14 31.1 6.04 All gears 29,734 10.3 0.08 8.1 0.24 3.0 0.07 101.8 3.44
Costs incured to have fishery dependent-data through Beach Management Units (BMU) 32 Sampled landing sites but we compare with 5 LS; 16 sampling days; Enumerators were Govt. Employee The cost of paying them was 300,000/-per month (150 US $) 10 Data enumerators will be paid 1,500 US $ per month; 5 Pilot sampled landing sites 10 sampling days Enumerators are BMU s who are working on voluntary bases but they are given 65,000/- (32.5 US $) each as a pocket money; 10 data enumerators will be paid 325 S $ per month; There is a significance difference of 1,275 US $ per person per month Fishery independent data Fisheries Staff Fishery dependent data Community data enumerators
Trend of Fish Catches for marine waters from 1985-2013 70,000.00 60,000.00 50,000.00 Wt in m. Tons 40,000.00 30,000.00 20,000.00 10,000.00? 0.00 Years
60,000.00 50,000.00 40,000.00 Wt in mtons 30,000.00 20,000.00? 10,000.00 0.00 1998 2000 2002 2004 Years 2006 2008 2010 2012 2014
Conclusion Stakeholders involvement in data collection should be encouraged among fishery management institutions with very close monitoring; BMU s members do not collects data only, but also enforces fishery regulations, in their respective landing sites and fishing grounds too i.e. management!!! They also involved in making policy recommendations and can make judgments about the policy and fishery management plans prepared by the district authorities; For many fishermen these multiple responsibilities create a sense of ownership to the fishery resources and they feel themselves as part of the decision makers.
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Lake Victoria Country Area owned km 2 Shorelin e (km long) Tanzania 35,088 (51%) 1,150 33 Uganda 29,584 (43%) 1,750 51 Kenya 4,128 (6%) 550 16 Shoreline Percentage % Total 68,800 (100%) 3,450 100
Lake Tanganyika Country Area owned km 2 Shoreline (km) Tanzania 13,489 669 41 Burundi 2,632 215 8 Zambia 1,974 159 6 DRC(Zaire) 14,805 807 45 Total 32,900 1,850 100 Percentag e %
Effect of Decentralization Centralised System DFSO were employed by Central Govt They are answerable to Director of Fisheries (Central Govt) They collect data and submit to Central Gvt There was reported information (Annual Statistics report) Decentralise System DFSO are being employed by Local Govt They are answerable to District Executive Director (Local Govt) Do not collect data as they are working on revenue collection etc No annual statistics until introduction of BMU s
Catch Assessment Survey (CAS)- Data Collected Under CAS Fishing effort CPUE Total catch (Calculated) Species composition Total Catch = Fishing Effort x CPUE Fishing Effort = F * BAC * A