REGIONAL PROJECT FOR INLAND FISHERIES PLANNING, DEVELOPMENT AND MANAGEMENT IN EASTERN/CENTRAL/SOUTHERN AFRICA (I.F.I.P.)
IFIP PROJECT
RAF/87/099TD/26/91 (En) December 1991
Report on a census of fishing boats and gear in the Kenyan waters of Lake Victoria
Ethiopia Zambia Kenya Zaire Tanzania Burundi Mozambique Rwanda Zimbabwe Uganda Malawi
UNITED NATIONS DEVELOPMENT PROGRAMME
FOOD AND AGRICULTURE ORGANIZATION OF THE UNITED NATIONS
UNDP/FAO Regional Project RAF/87/099-TD/26/91 (En) for Inland Fisheries Planning Development and Management in Eastern/Central/Southern Africa
RAF/87/099-TD/26/91 (En) December 1991
Report on a census of fishing boats and gear in the Kenyan waters of Lake Victoria
by
T.M. Hoekstra1, A. Asila ?, C. Rabuor and O. Rambiri
1 APO Socio-economist, IFIP 2 Kenya Marine and Fisheries Research Institute, Kisumu 3 Department of Fisheries, Kisumu
FOOD AND AGRICULTURE ORGANIZATION OF THE UNITED NATIONS UNITED NATIONS DEVELOPMENT PROGRAMME Bujumbura, December 1991 i
The conclusions and recommendations given in this and other reportsin theIFIP projectseriesarethose considered appropriate at the time of preparation. They may be modified in the light of further knowledge gained at subsequent stages of the Project. The designations employed and the presentation of material in this publication do not imply the expression of any opinion on the part of FAO or UNDP concerning the legal status of any country, territory, city or area, or concerning the determination of its frontiers or boundaries. PREFACE
The IFIP project started in January 1989 with the main objective of promoting a more effective and rational exploitation of the fisheries resources of major water bodies of Eastern, Central and Southern Africa. The project is executed by the Food and Agriculture Organisation of the United Nations (FAO), and funded by the United Nations Development Programme (UNDP) for a duration of four years.
Thereare eleven countries and three intergovernmental organisations participating in the project: Burundi, Ethiopia, Kenya, Malawi, Mozambique, Uganda, Rwanda, Tanzania, Zambia, Zaire, Zimbabwe, The Communaut6 Economique des Pays des Grands Lacs (CEPGL), The Preferential Trade Area for Eastern and Southern African States (PTA) and the Southern African Development Coordination Conference (SADCC).
The immediate objectives of the project are: (i) to strengthen regional collaboration for the rational development and management of inland fisheries, particularly with respect to shared water bodies;(ii) to provide advisory services and assist Governments in sectoral and project planning; (iii) to strengthen technical capabilities through training; and (iv) to establish a regional information base.
PREPARATION OF THIS DOCUMENT
This document presents the results of a census of fishing units in the Kenyan waters of Lake Victoria. The census was executed by the Regional Project for Inland Fisheries Planning (IFIP) in collaboration with the Kenya Marine and Fisheries Research Institute and the Fisheries Department of Kenya. The data presented are stratified according to the 12 administrative Divisions bordering the lake. The findings should lead to a review of previously made assumptions of fishing effort and total catch and catch by gear and species. Furthermore the results should lead to a critical review of the present boat registration system.The report is structured as follows:introduction, methodology (including definitions), results and concluding comments and recommendations.
IFIP PROJECT FAO B.P 1250 BUJUMBURA BURUNDI
Telex : FOODAGRI BDI 5092 Fax : 22 77 05 Tel.: 22 43 28 iii
IFIP PUBLICATIONS
Publications of the IFIP project are issued in two series:
A series of technical documents (RAF/87/099-TD) related tomeetings, missions and research organized by the project.
A series of working papers (RAF/87/099-WP) related to more specific field and thematic investigations conducted in the framework of the project.
For both series, reference is further made to the document number (26), the year of publication (91) and the language in which the document is issued: English (En) or French (Fr).
For bibliographic purposes this document should be cited as follows:
Hoekstra,T.M., A.Asila, C. Rabuor and O. Rambiri, Report on a census of 1991 fishing boats and gear in the Kenyan waters of Lake Victoria. UNDP/FAO Regional Project for Inland Fisheries Planning (IFIP), RAF/87/099 - TD/26/91 (En): 36p. iv
Table of contents
page
INTRODUCTION 1
1.1. General 1
1.2. Study location 1 1.3. Background 2 1.4. Study objectives 3
METHODOLOGY 3
2.1. Introduction 3 2.2. Definitions 3 2.3. Data collection, verification and processing 7 2.4. Geographical stratification 8
RESULTS 8
3.1. Introduction 8 3.2. Number and location of beaches 8 3.3. Number and distribution of boats 9 3.4. Number of boats by condition 10 3.5. Number of boats by boat type 11 3.6. Number of boats by rate of registration 12 3.7. Number and distribution of gear by type 13 3.8. Number of boats by fishery type 13 3.9. Multiple gear use and gear combinations 15 3.10. Number and distribution of engines 16 3.11. Rate of inter-district boat migration 17
CONCLUDING COMMENTS AND RECOMMENDATIONS 19
FIGURES 21
Figure 1 Composition of the fleet by boat type and division 22 Figure 2 Relative distribution of gear by division 23 Figure 3 Distribution of boats by fishery type and Division Funyula, Budalangi, Bondo and Rarieda 24 Figure 4 Distribution of boats by fishery type and Division Maseno, Winam, Nyando and Nyakach 25 Figure 5 Distribution of boats by fishery type and Division Kendu, Rangwe, Mbita and Nyatike 26
ANNEXES 28
Annex 1 Map of beaches 29 Annex 2 List of beaches with number of active boats by District, Division, Location and Sub-location 31 Annex 3 The census data collection form 36
1
1. INTRODUCTION
1.1.General
Lake Victoria, the second largest fresh water lake in the world, is shared by Kenya, Uganda and Tanzania.It covers an area of 68,800 km2,the Kenyan portion being 4,100 km2 or just 6% (Vanden Bossche, 1990). It is a shallow lake with a depth ranging from 4 to 15 metres at the fringes and from 30 to 60 metres in the open lake (Ogutu,1988). The deepest part of the lake is estimated to be 84 metres (Vanden Bossche, 1990). The Lake Victoria fishery constitutes the most important fisheryin Kenya. According to official estimates, fish production in Kenya in 1989 was approximately 146,400 t of which 4,600 came from the marine sector and 138,800 t from inland fisheries and fish farming. Of the inland production, 135,400 t were reported to be from Lake Victoria. Thus Lake Victoria alone accounts for about 90% of all fish production in Kenya(FAO,1991 in press).
These production estimates are (in part) based on two assumptions with respect to fishing effort on Lake Victoria i.e. the average number of fishing days per year and the number of boats. The previous boat census in the Kenyan waters of Lake Victoria was undertaken some twenty years ago. This report presents the results of a new boat census undertaken in May 1991 and should lead to a review of previously made assumptions and an update of catch statistics of the fisheries.
The census was undertaken as a joint exercise involving the Department of Fisheries (00F), the Kenya Marine and Fisheries Research Institute (KMFRI), and the FAO Regional Project for Inland Fisheries Planning, Development and Management in Eastern/Central/Southern Africa (IFIP). Useful assistance was provided by the Lake Basin Development Authority.
1.2. Study location
The study location was the entire Kenya shoreline of Lake Victoria together with all the inhabited islands( Wayasi, Sifu, Ndeda, Oyamo, Sukru, Kibuogi, Ngodhe, Rusinga, Ringiti, Mfangano, Bemba and Kilda) located in the Kenyan waters of the lake. The zigzag shoreline with several embayments hasalength of approximately 760 km. The lake is the main resource of a highly populated area showing a population density of about 290 p/km2. There are four districts bordering the lake namely Busia, Siaya, Kisumu and South Nyanza. Ogutu (1988) described the environment as follows: "The immediate hinterland, or fishing locations fall within lake-shore savannah, characterised by low and unreliable rainfall and little arable land.This environmentaffectsagricultural activities aroundthelake, which ismainly atthe subsistence level, involving the keeping of cattle and the growing of maize, potatoes, cassava and various varieties of millet for subsistence. The main cash crop is cotton. Most areas have only one cropping season. Once the crops have been planted, weeded and harvested,the remaining months are spent looking for income generating activities; primary among which is fishing and fish trading". This pattern together with the fact that the lake accounts for about 90% of Kenya's total fish production underscores the significance of fishing as an income generating activity in the lake region as well as for Kenya a whole. 2
1.3. Background
Total landings for the lake in Kenya are estimated according to the following simple formula: (activeboats x average fishingdays/year x average catch/boat/day) + local consumption)
The only parameter derived from a sample survey is theaverage catch per boat per day. The other elements are simple assumptions: 5,000 boats are assumed to be active; boats are assumed to be active on 190 days per year; and local consumption is assumed to be 3 kg/boat/fishing day. Apart from disagreement over activity levels there has been much controversy over the number of boats operating in the Kenya waters of Lake Victoria during the past decade. Reynolds and Gréboval (1988) observed: "Available information provides a somewhat uncertain picture of fishing effort and fisher folk for the Kenya part of the lake. Fishermen may number around 21,000 up to around 31,000; they may support households totalling (at a roughly assumed rate of 7 individuals per fishermen) as few as some 147,000 individuals toas many as 217,000; and they may be operating anywhere from about 4,000 to about 8,500 canoes".
Bernacsek (1986), in a review of the fisheries statistical systems in Kenya, Uganda and Tanzania, reports over 200 landing beaches in Kenyans waters. With respect to the number of boats operating he noted: "The nominal number of boats is known because they are registered every year. However it was known that there were also many unregistered boats." A comment which should be added to Bernacsek's observation is that although the DoF registers boats that enter the fishery they do not keep record of the registered boats which disappear from the fishery.
Apart from uncertainty about the number of active boats a proper quantification of gear such as number of hooks and dimension of nets has been lacking. AsBernacsek (1986) stated: "There is an urgentneedfor a comprehensive frame survey of fishing effort. The last frame survey was done in 1971 and it is known that many changes have occurred since then due to the Nile perch explosion and other changes in ichthyofauna composition as well as general national economic development. The Department of Fisheries is in urgent need of up-to-date information on the number of fishermen, numbers of gear by type and dimension, distribution of effort by fishing area and number of fishing days per year. However the DoF's resources are insufficient and outside support is required". Since then it was not possible to execute a census given the resources available and the constraints affecting the enumerators.
It is in this context that assistance was requested from the FAO Regional Project for Inland Fisheries Planning, Development andManagement in Eastern/Central/Southern Africa (IFIP). In order to arrive at a quantification of boats and gear, it was agreed to adopt a two step approach. During the firststage census the number of boats would be assessed including an elementary indication of the gear used from each boat. During a subsequent socio-economic (sample) survey the exact dimensions of gear, crew size and number of dependents would be assessed permitting an estimation,through extrapolation, of the total quantity of gear in the lake and the total number of fishermen and fishery dependent population. Complementary information on key socio-economic indicatorswillalso be collected in this context. 3
1.4. Study objectives
The specific objectives of the 1991 fishery census are summarized below:
to assess the number and location of all the beaches; to identify types of artisanal fishery; C) to assess the number of fishing boats by fishery type and administrative region; to determine the number and distribution of engines and gear by region to investigate the rate of inter-district migration by region
2. METHODOLOGY
2.1. Introduction
The census was executed utilizing the existing administrative infrastructure of the Fisheries Department and the Kenya Marine and Fisheries Research Institute in Kisumu. Kenya employs a system of fishing boat registration since the 1960's. The boat registration system works as follows. Each year the DoF in Kisumu sends alist of(unique) numbers to the 4 District Fisheries Officers. Fishermen who have built a boat and intend to start fishing are required to apply for a registration number. The boat owner applies to the District Office to obtain "his" number. This registration number is then painted on the boat.
The DoF employed over 100 statistical enumerators (including fish scouts) while KMFRI employed 62 enumerators. Enumerators from DoF and KMFRI sometimes operate in the same beach. All enumerators are 0 level secondary school leavers whose main function is to collect catch and effort data.
For the purpose of census data collection a form (see Annex 3) was designed, each row representing a boat and each column a characteristic of the boat. A number of designated enumerators from the DoF and KMFRI were employed to fill in the forms. The registration number of the boat was entered in the first column of the form. Subsequently the characteristics (as described below) of every boat were entered. In case a boat had no (or an unreadable) registration number the enumerator would simply give the boat a number (1,2,3 etc.).
2.2. Definitions
Inorderto obtain consistencyin data collection andthe subsequent presentation of the results the following definitions were adopted.
Beach. All beaches where at least ten boats were based and regularly operated were recorded as a (separate) beach with their proper name. Boats in minor beaches with less than 10 boats were recorded on the forms of the nearest beach of 10 or more boats.
Active-nonactive: A boat was considered active if it had been operating at least one day in the past 30 days. 4
Condition of the boat: If a boat was not active because of damage the enumerator was asked if the boat, in his/her opinion, was repairable or not repairable.
Residentvisiting: A boat was considered resident if it had been operating for more than three months from the enumerated beach. A boat was regarded visiting if it normally operated elsewhere but had been operating from the enumerated beach for a period of Jess than three months.
Equipment: For each recorded boat an attempt was made to identify the gear used and whether an engine was employed. As recording the length or number of gear unitsfor every boat was,given the constraints of time and manpower, considered to be too time consuming it was decided to indicate gear type by simply writing "Yes" or "No" on the form. This information could rather easily be obtained from either the owner of the boat, the fisherman in charge, a crew member or the beach leader. 5
Boat types:
The classification by boat type is as given below.
Boat types
Boat type Description Dugout Canoe A boat carved out of a log of wood (tree trunk). It has no joints and no planks.
Karua A Karua has a flat bottom. It is made of planked wood and is mostly used in shallow(er) waters.
Sesse canoe A modified dugout canoe pointed at both ends. The bottom is V-shaped. The sides are made of planked wood.
Taruma An improved sesse canoe. The bottom is V- shaped. It is mostly used in deeper waters because of its stability. It is made of planked wood and can be modified for use of an outboard engine.
Other All boats which do not conform to any of the above boat types (e.g. boats made from corrugated iron sheets)
Fishery types:
Boats may be used to exploit several fisheries. The type of fisheries involved are determined on the basis of the major gear being used.
Fishery typesl
Fishery type Brief description of associated gear
Nile perch gillnet The gillnets for nile perch have a mesh fishery size from 152 mm to 305 mm, the most common is 178-203 mm. The gillnets are anchored on fishing grounds at a depth of 10-20 m. They are set either close to the surface during the phase of the new moon or not far from the bottom during full moon. The nets are hauled in with the catch in the morning and generally set again either immediately in the morning or in the evening.
1 For more information on gear used in the Kenya waters of Lake Victoria refer to Prado et al.(1991) on which these descriptions are based. 6
Brief description of associated gear Longline fishery A mainline with short branching lines (snoods) with hooks. Bait is attached to the hook. The longlines are anchored up to 80 m deep, either close to the surface, in midwater during the phase of the new moon or close to the bottom during full moon. Longlines can either be set in the morning or in the evening. Small boats would have some 150 hooks while large ones may operate up to 1200 to 1500 hooks. In Lake Victoria the main target species is nile perch.
Tilapia gillnet fishery The most common nets used are 102 mm and 127 mm to 178 mm, sometimes even 229 mm for the bigger fish. As far as the fishing operations are concerned, these nets are used as ordinary set gillnets or sometimes as driftnets, surrounding or drive-in nets.
Beach seine fishery Beach seines are banned but nevertheless used. Some of them are quite short, around 100 m without a bag. The longer ones, up to 150 m, have a bag in the central part with various mesh sizes in the wings ranging from a few mm (mosquito net) to 40 mm or more (most commonly observed is 28 mm).
Mosquito seine fishery The seine is made of netting with a hexagonal knotless mesh,7 mm (4 mm opening) mosquito net. The operation of mosquito seines (without the use of lights) is the same as beach seining often to catch bait for longlines.
Mosquito seine with The mesh size of the seine is as described lights fishery above. The dimensions of the mounted seine are 20 m long x 4 or 5 strips of webbing (350° meshes each) and these are hung on a line of 7 to 8 m deep. Four to six lamps (petrol "Anchor" type) are used to attract the fish. These lamps are lit in a line spaced 50 to 100 m from each other. The catching technique is based on light attraction of the fish. The method can only be used during dark lunar phases (new moon period). The target species is Rastrineobola argenta locally referred to as omens. 7
Fishery type Brief description of associated gear
Other Various other gear are used mainly for tilapia: hand lines, traps in estuaries, pole and line and set nets.
2.3. Data collection, verification and processing
Prior to data collection, training courses were conducted in a number of selected beaches. The target group were those designated to be enumerators (57 and 23 persons from DoF and KMFRI respectively).The training was conducted by two teams of two study supervisors. One team operated in the Northern and one in the Southern section of the Nyanza Gulf. At these training sessions instruction manuals were handed out and the enumerators were briefed on how to fill in the forms. After having been trained the enumerators were asked to mark the beaches in their area on a map (scale 1:250.000). The map was checked to confirm that there were no overlaps and/or gaps of the enumerators operational areas during the data collection phase of the study. Each enumerator was given a number of forms according to the number of boats he/she estimated to exist in the beaches in his/her area. The period of training and distribution of forms was four days in both the northern and southern sections of the Nyanza gulf. The enumerators were given seven days to complete data collection. After seven days the study supervisors visited the enumerators on preset dates in a number of selected beaches. At these meetings the forms were collected and verified. After these quality checks the mapping of beaches was subsequently refined. For the purpose of data input a database structure was defined. After the data were entered the database was checked so as to avoid double counting of boats. This was done by indexing the database on boat registration number and checking if there were numbers which appeared more than once.2 It was found that 412 numbers existed twice, 43 numbers existed three times and 2 numbers existed four times. At first glance this seemed to be double counting. It appeared however that when the characteristics of the boats with a same number as another boat were checked many appeared to be different. More specifically out of the 412 boat numbers that existed twice 280 boats had different characteristics than the other boat with the same number,i.e. they were unique. Out of the 43 numbers that existed three times 23 were unique and out of the 2 numbers that existed four times 4 were unique. It can thus be deduced that 154 boats (132+20+2) had the samenumber as well as the same characteristics as another boat and as such seemed to have been double counted. Consequently they should have been deleted from the database prior to analyses. However, as explained in Chapter 3.6, it was noted that fishermen regularly use one number for more than one boat. These boats may well have the same characteristics (type of boat, gear etc.). As this phenomenon reduced the justification to delete these boats from the database it was decided to include them in the analyses at the risk of a slight over enumeration of boats3.
2 The check on double counting could only be performed on the boats with registration numbers and not on the unregistered boats.
3 Maximumcare has been taken to ensure that all boats were enumerated.There may however have been a number of boats which were not recorded because, for example, they were very mobile. It is believed however 8
Afterdata inputandverification the datawereprocessed usingthe statistical package Statgraphics.
2.4. Geographical stratification
The geographical stratification used were the twelve administrative Divisions bordering the Lake.This choice was based on the observation that the fisheries in Western Kenya was regionalised4.
3. RESULTS
3.1. Introduction
This chapter presents the results of the census mainly in the form of cross tabulations. From Chapter 3.5 onwards the analysis is based on active boats only. Graphical presentations of the results are given separately in section 5.
3.2. Number and location of beaches
A total of 208 beaches (of 10 or more boats) were recorded. Some 177 beaches were enumerated on the mainland while the remainder were recorded on the 12 islands. Table 3.1 below gives the distribution per District and Division of the beaches.
that the rate of under enumeration was below 5%. The boats which have possibly been doublecounted will partlycompensate for thosewhichwerenot enumerated.
4The database permits a further breakdown of data to the level of location, sub-location and beach. 9
Table 3.1 Distribution of landing beaches by District and Division
Number of % District Division Beaches Beaches
Busia Funyula 5 2.4 Busia Budalangi 16 7.7 Siaya Bondo 29 13.9 Siaya Rarieda 17 8.2 Kisumu Maseno 9 4.3 Kisumu Winam 7 3.4 Kisumu Nyando 9 4.3 Kisumu Nyakach 7 3.4 South Nyanza Kendu 23 11.1 South Nyanza Rangwe 5 2.4 South Nyanza Mbita 62 29.8 South Nyanza Nyatike 19 9.1
TOTAL 208 100.0
The number of beaches per Division (or District) is primarily related to the length of their coastline (see Map in Annex 1). Consequently many beaches were enumerated in Mbita Division (29.8 %), Bondo (13.9 %) and Kendu (11.1 %).
3.3. Number and distribution of boats
In these 208 beaches 7279 boats were counted of which 6229 were recorded as active (see paragraph 2.2 for definition of active) and 1048 as inactive. Annex 2lists the number of active boats per beach. Table 3.2 gives the distribution of the boats per Division.
Table 3.2 Number of active and inactive boats by Division
Number of Number of % Inactive Division active boats inactive boats Unknown TOTAL boats
Funyula 111 10 0 121 8.3 Budalangi 726 110 1 837 13.1 Bondo 1013 144 0 1157 12.4 Rarieda 524 99 0 623 15.9 Maseno 156 127 0 283 44.9 Winam 224 55 0 279 19.7 Nyando 199 17 0 216 7.9 Nyakach 180 28 1 209 13.4 Kendu 447 94 0 541 17.4 Rangwe 99 33 0 132 25.0 Mbita 1637 275 0 1912 14.4 Nyatike 913 56 0 969 5.8
TOTAL 6229 1048 2 7279 14.4
Most active boats were recorded in Mbita (26.2 %) followed by Bondo (16.2 %) and Nyatike (14.7 %). For all Divisions combined the proportion of inactive boats was 14.4 %. However marked differences in the proportion of inactive boats were noted between the Divisions. The lowest proportion of inactive boats was found in Nyatike (5.8 %) and the highest in Maseno (44.9 %). Two 10 beaches in Maseno were encountered with 41 and 20 inactive boats (91.1 % and 95.2 % of the total number of boats in these beaches) respectively. Despite the fact thatthesetwo beaches contribute significantlytothe high proportion of inactive boats in this division it is noted that actually all beaches in this division displayed an activity level far below the general (entire shoreline) average. Although the local people in these beaches in the Nyanza Gulf claimed that this was due to a general lack of cash to repair the boats a complete explanation for this phenomenon is not available. As can be seen in table 3.3 the average number of active boats per beach per Division varied between 17.3 in Maseno to 48.1 boats in Nyatike with a general average of 29.9 boats for the entire coastline.
Table 3.3 Average number of boats per beach per Division
Average no. of boats Division No. of beaches No. of active boats per beach
Funyula 5 111 22.2 Budalangi 16 726 45.4 Rondo 29 1013 34.9 Rarieda 17 524 30.8 Maseno 9 156 17.3 Winam 7 224 32.0 Nyando 9 199 22.1 Nyakach 7 180 25.7 Kendu 23 447 19.4 Rangwe 5 99 19.8 Mbita 62 1637 26.4 Nyatike 19 913 48.1
TOTAL 208 6229 29.9
3.4. Number of boats by condition
If a boat was found to be inactive the enumerators were asked to indicate (if applicable) if, in their opinion, the boat was repairable. The results are given in Table 3.4 below.5
5 It should be realised that these figures reflect a rather subjective judgement of the enumerators. 1 1
Table 3.4 Number of inactive boats by reparability per Division
Not Repairable Unrepairable applicable Unknown TOTAL
Division No. % No. % No. % No. % No. %
Funyula 4 40.0 6 60.0 0 0.0 0 0.0 10 100.0 Budalangi 22 20.0 83 75.5 2 1.8 3 2.7 110 100.0
Sondo 92 63.9 40 27.8 11 7.6 1 0.7 144 100.0 Rarieda 68 68.7 26 26.3 5 5.1 0 0.0 99 100.0 Maseno 121 95.3 6 4.7 0 0.0 0 0.0 127 100.0 Winam 47 85.5 5 9.1 3 5.5 0 0.0 55 100.0 Nyando 17 100.0 0 0.0 0 0.0 0 0.0 17 100.0
Nyakach 27 96.4 1 3.6 0 0.0 0 0.0 28 100.0 Kendu 70 74.5 19 20.2 0 0.0 5 5.3 94 100.0 Rangwe 24 72.7 5 15.2 0 0.0 4 12.1 33 100.0 Mbita 205 74.5 70 25.5 0 0.0 0 0.0 275 100.0 Nyatike 25 44.6 31 55.4 0 0.0 0 0.0 56 100.0
TOTAL 722 68.9 292 27.9 21 2.0 13 1.2 1048 100.0
Many of the 21 boats indicated in the column "Not applicable" were newly built boats which did not start operating yet.
3.5 Number of boats by boat type
The fishermen on Lake Victoria utilize essentially 4 different types of boats (See paragraph 2.2 for a definition of boat types). Table 3.5
provides the distribution of active boats by boat type. Figure 1 (Section 5) gives the percentage distribution of the composition of the fleet per division.
Table 3.5 Distribution of active boats by boat type and Division
Dugout Sesse Division canoe Karua canoe Taruma Other TOTAL
Funyula 0 69 24 18 0 111 Budalangi 17 206 291 212 0 726 Sondo 0 139 763 111 0 1013
Rarieda 1 19 483 18 3 524
Maseno 0 1 136 19 0 156 Winam 10 29 79 106 0 224 Nyando 0 0 60 139 0 199 Nyakach 2 0 51 127 0 180 Kendu 13 71 207 152 4 447 Rangwe 0 2 94 3 0 99 Mbita 3 14 1413 207 0 1637 Nyatike 0 241 379 293 0 913
TOTAL 46 791 3980 1405 7 6229 Percentage 0.7 12.7 63.9 22.6 0.1 100.0 12
The majority of the boats (63.9 %) were so-called "Sesse canoes" followed by
"Tarumas" (22.6 %). Only few dugout canoes,46 , were encountered. These dugout canoes were mainly recorded in beaches located at river mouths. Differences between the Divisions can be noted with respect to relative importance of the different boattypes. The Karua canoe, for example, constitutes 62.2 % of the fleet in Funyula, while the composition of the fleet in Nyando and Nyakach shows 70 % of Taruma canoes.
3.6. Number of boats by rate of registration
As has been explained in paragraph 2.1 both registered and unregistered boats were enumerated during the census. Table 3.6 below gives the distribution of the number of registered and unregistered boats by Division.
Table 3.6 Number of registered and unregistered boats by Division
Registered boats Unregistered boats TOTAL
Division No. % No. % No. %
Funyula 94 84.7 17 15.3 111 100.0 Budalangi 451 62.1 275 37.9 726 100.0 Bondo 814 80.4 199 19.6 1013 100.0 Rarieda 477 91.0 47 9.0 524 100.0 Maseno 134 85.9 22 14.1 156 100.0 Winam 212 94.6 12 5.4 224 100.0 Nyando 166 83.4 33 16.6 199 100.0 Nyakach 146 81.1 34 18.9 180 100.0 Kendu 352 78.7 95 21.3 447 100.0 Rangwe 96 97.0 3 3.0 99 100.0 Mbita 1370 83.7 267 16.3 1637 100.0 Nyatike 689 75.5 224 24.5 913 100.0
TOTAL 5001 80.3 1228 19.7 6229 100.0
It should be noted that the table above does not give the exact rate of boat registration but rather an order of magnitude. This is explained by a few facts: if the number of a boat was unreadable and could not be obtained from the owner, the boat was (by necessity) recorded as a boat without a (registration) number; boat owners generally register their boat, but sometimes fail to paint the number on it; it was noted that boat owners frequently use one registration number for more than one boat; some boat owners paint numbers on their boats which actually do not exist in the records of the Fisheries Department, for example 33 boats were encountered with six digit numbers while the records of DoF only contain 5 digit registration numbers.
Assuming that these phenomena occur on a limited scale and that they partly compensate each other it is observed that the overall rate of boat registration was about 80 % with the highest registration ratio (97.0 %) in Rangwe Division and the lowest (62.1 %) in Budalangi Division. 13
3.7. Number and distribution of gear by type
The data collected made it possible to confirm the gear of 97 % of the active boats. Table 3.7 below provides the results. Figure 2 (Section 5) gives the relative distribution for every Division.
Table 3.7 Number of gear by type and Division
NileperchTilapia BeachMosquito Trans Division Gillnet Gillnet LonglineSeine Seine Lights Setnet Trapsport Unknown
Funyula 38 54 28 8 0 0 0 0 0 2 Budalangi 310 81 184 52 35 13 0 0 12 107 Bondo 230 202 249 126 258 178 15 0 4 45 Rarieda 89 134 107 57 157 136 0 0 0 6 Maseno 44 82 80 3 37 23 0 12 0 2 Winam 74 123 75 8 40 12 0 0 0 9 Nyando 100 114 16 7 28 0 0 15 0 2
Nyakach 33 79 38 11 19 0 0 43 0 1 Kendu 90 68 128 38 177 105 0 0 0 19 Rangwe 22 65 23 7 22 8 0 2 0 .1 Mbita 682 204 219 223 435 322 0 7 5 19 Nyatike 556 74 249 50 174 173 0 0 0 3
TOTAL9 2268 1280 1396 590 1382 970 15 79 21 216
*) Note: The (grand) total exceeds the total number of active boats since many boats operate with more than one gear.
The nileperch gillnet was, either as the only gear or in combina'cion with other types of gear, operated from 2268 (36.4 %) boats. Longlines and mosquito seines were operated from 1396 (22.4 %) and 1382 (22.2 %) boats respectively. Out of the boats operating mosquito seines 970 (70.2 %) used these seines in association with lights for night fishing. Although it is claimed that tilapia gill netting has declined rapidly in recent years the tilapia gillnet was stilloperatedfrom 1280 (20.5 %) boats. Beach seinesare officially prohibited nevertheless they were still widely used. The total number of boats using beach seine was 590 (9.2 %). Traps and set nets were only operated by a small portion of thefleet i.e. 79 (1.3 %) and 15 (0.2 %) boats respectively. The boats operating traps were largely encountered in the Nyanza Gulf, notably in Nyakach Division, while set nets were only encountered in Bondo.
3.8. Number of boats by fishery type
In table 3.7 above the number of boats, using the different types of gear, are tabulated. These gear were either the only gear used from the boat or they were combined with other gear.In order to be able to classify the boats according to fishery type the enumerators were asked to indicate the "most important" gear in case a boat carried more than one type of gear. Table 3.8 below gives the distribution of boats by fishery type or gear combination. The gear combination is given for those cases where no clear cut answer onthe most important gear (and thus fishery type) could be obtained. Fishery Type or gear Table 3.8 Number of active boats by fishery type or major gear combination 1 4 per Division combinationMAJOR GEAR DECLARED yulaFun- langiBuda- Bando Rarieda Maseno Winam Nyando kachNya- Kendu Rangwe Mbita tikeNya- TOTAL TilapiaLonglineNileperch gillnet gillnet 522617 257176 80 225184 120100 80 4236 9 465349 3213 592826 119 53 18 9 666195 113518 10481947 MosquitoBeach seine net 08 50 124160 5319 03 7 103 7 1710 513750 39 6 219202 4656 1 1016 570 SetnetTrapsMosquitox net with lightsOnly those transport boats with a fisheries registration number were recorded as they shift between fishing and transporting 0 2013 0 168 55 0 132 0 39 1028 0 2814 0 30 0 103 13 14 26 302 1110 158 0 901243 73 Transport*)Gillnet (type unknown) 0 11 0 14 52 0 1 0 0 0 0 10 0 0 0 14 2 MAJORUnknown GEAR UNDECLARED 2 108 41 5 2 9 20 01 18 0 1 17 0 03 209 18
Nileperch GN/BeachGN/Longline seine 60 8 1 0 0 0 0 1 0 0 0 0 0 08 23 1 Nileperch GN/Mosq.SeineGN/Tilapia GN 0 0 1 0 2 1 20 0 4 1 0 1 02 03 01 0 32 5 Tilapia GN/BeachGN/Longline seine 00 0 1 28 1 3 2 14 1 0 5 0 0 0 2 54 Longline/BeachTilapia GN/Mosq. seine Seine 00 0 00 03 1 0 0 1 0 0 1 0 0 0 00 3 16 MoreLongline/Mosq.TOTAL than Seine 3 gear 111 0 726 0 1013 06 524 04 156 21 9 0 224 0 199 0 180 0 447 0 99 0 1 1637 14 0 913 71 6229 1647 15
With 1947 (31.3 %) boats the nile perch gillnet fishery was by far the most widespread fishery type. Adding the 1048 (16.8 %)boats in the longline fishery to the nile perch fishery it can be concluded that a total of 2995 (48.1%) boats were primarily targeting for nileperch. The tilapia gillnet fishery was the third fishery type with 1016 (16.3 %) boats. The relative importance of various fishery types and therewith fishing effort targeting for the different fish species varied significantly according to fishingarea. Figures 3, 4 and 5 (Section 5) give theproportional distribution of fishery types per division. As can be seen from these figures marked regional differences in the composition of the fleet (according to fishery type) were noted. In Nyatike division the majority of the boats (56.7 %) operated in the nile perch fishery while in Rangwe division this fishery was far less important (9.1 %). In Nyando division more than half (51.7 %) of the boats operate in the tilapia gillnet fishery. In terms of numbers as well as relative importance Mbita division displayed an important beach seine fishery.A significant share (38.4 %) of the beach seine fishery was concentrated in this division. The mosquito seine without lights fishery constituted only a small portion (3.9 %) of the total fleet. The mosquito seines in association with lights fishery, however, was more important (14.5 %). This fishery was mainly concentrated in the adjoining divisions of Mbita and Nyatike which together account for over half (51.1 %) of the number of boats in this fishery and Bondo and Rarieda (33.3 %).
3.9 Multiple clear use and gear combinations
Tables 3.7 and 3.8 above provide the number of gear and boats by fishery type but they do not provide insight in the extend to which gear are combined and which gear are combined. Table 3.9 below gives an overview of multiple gear use by fishery type (for those cases where the major gear was declared) and the cases where the major gear was not declared.
Table 3.9 Number of boats by major gear and number of gear used
Number of boats with one and more types of gear
1 2 3 4 or 5 %1 % > 1 Major gear declared gear gear gear gear gear gear TOTAL
Nile perch gillnet 1702 221 21 3 87.4 12.6 1947 Longline 780 242 24 2 74.4 25.6 1048 Tilapia gillnet 842 163 11 0 82.9 17.1 1016 Beach seine 553 10 7 0 97.0 3.0 570 Mosquito seine 228 11 4 0 93.8 6.2 243 Mosquito seine & lights 866 33 0 2 96.1 3.9 901 Traps 69 4 0 0 94.5 5.5 73 Set net 14 0 0 0 100.0 0.0 14 Gillnet type unknown 2 0 0 0 100.0 0.0 2
SUB-TOTAL 5056 684 67 7 87.0 13.0 5814
Major gear undeclared 0 152 21 15 0.0 100.0 188 Transport n.a. n.a. n.a. n.a. n.a. n.a. 18 Unknown n.a. n.a. n.a. n.a. n.a. n.a. 209
TOTAL 5056 836 88 22 81.2 15.2 6229
Note:n. . = not applicable 16
If we confine ourselves to the upper part of the table (major gear declared) it can be seen that it is especially the long liners (25.6 %), tilapia gill netters (17.1 %) and nile perch gill netters (12.6 %) who frequently use more than one gear. The occurrence of secondary gear use is very limited in the other fishery types.
Intable3.10 the multiple useofgear is specified giving the gear combinations for those boats where two gear are combined.
Table 3.10 Associated gear of boats with two gear (major gear declared)
Nile perch Long-TilapiaBeach-Mosquito Major gear gillnet line gillnetseine seine Lights Other TOTAL
Nile perch gillnet - 132 85 3 1 0 0 221 Longline 74 - 32 4 116 0 16 242
Tilapia gillnet 111 44 - 0 1 0 7 163 Beach seine 3 0 0 - 7 0 0 10
Mosquito seine 8 1 1 0 - 0 1 11 Mosquito seine & lights 19 8 4 2 - 0 33
Traps 1 0 3 0 0 0 - 4
TOTAL 216 185 125 9 125 0 24 684
The boats having the nile perch gillnet as their major gear most frequently combine this gear with longlines. Longliners combine especially with mosquito seines. This combination is easily explained by the fact that these seines are used to catch the bait for the longlines. Tilapia gill netters use primarily the nile perch gillnet as secondary gear.
Table 3.11 gives the gear combinations of the boats operating two gear but whereby the major gear was not declared.
Table 3.11 Gear combinations of boats with two gear (major gear undeclared)
Nile perch Tilapia Beach-Mosquito gillnet Longlinegillnet seine seine Lights TOTAL
Nile perch gillnet - 22 31 1 4 0 58
Longline - 54 1 31 0 86 Tilapia gillnet - 6 2 0 8 Beach seine - - 0 0 0 Mosquito seine - - - 0 0
TOTAL 152
3.10. Number and distribution of engines
The use ofan engine enables a boat to reach distant fishing grounds. Motorization in the Lake Victoria fisheries of Kenya was still very limited. Only 212 (3.4 %) of the boats were equipped with an engine. All these engines were outboards. As can be seen in table 3.12 below the majority(93.9 %) of the boats with an outboard engine were of the Taruma type. 17
Table 3.12 Number of boats with engine by boat type and Division
Dugout Sesse Division canoe Karua canoe Taruma Other TOTAL %
Funyula 0 0 0 12 0 12 5.7 Budalangi 0 0 0 56 0 56 26.4
Sondo 0 1 0 73 0 74 34.9 Rarieda 0 0 0 4 0 4 1.9 Maseno 0 0 0 0 0 0 0.0
Winam 3 1 0 8 0 12 5.7 Nyando 0 0 0 0 0 0 0.0 Nyakach 0 0 0 0 0 0 0.0
Kendu 0 0 0 1 0 1 0.5 Rangwe 0 0 0 0 0 0 0.0 Mbita 0 0 0 17 0 17 8.0 Nyatike 0 8 0 28 0 36 17.0
TOTAL 3 10 0 199 0 212 100.0
% 1.4 4.7 0.0 93.9 0.0 100.0
Note that most motorized boats were encountered in the Northern and Southern parts of the shoreline with and only few in the Nyanza Gulf. Table 3.13 provides the number of motorized boats by fishery type.
Table 3.13 Number of motorized boats by fishery type
Fishery type Number boats with engine
Nile perch gillnet 149 70.3 Longline 11 5.2 Tilapia gillnet 11 5.2 Beach seine 2 0.9 Mosquito seine 3 1.4 Mosquito seine with lights 5 2.4 Other 6 2.9 Unknown 25 11.7
TOTAL 212 100.0
While 31.3 % of all active boats were classified in the nile perch gillnet fishery it was observed that boats with outboard engines were comparatively over represented in this fishery i.e. some 70 % of the motorized boats were involved in nile perch gill netting.
3.11. Rate of inter-district boat migration
The boat registration system enabled an assessment of the rate of inter- district migration of boats. In Kenya fishingboats6 are registered by the DoF with a number which starts with a "K" (for Kenya) and includes a character extension indicating in which district they were originally registered.
6 Transport boats are registered by Kenya Railways and start with "MK" 18
The following extensions to numbers are applied:
District Character extension Example of registration number
Busia K1 7839B Siaya SYA K57645SYA Kisumu K98535C South Nyanza S K43871S
By using theextension characters ofthe boat numbersthe numberof "outsiders" (inter-district migrants) in every Division could be determined. Table 3.14 below gives the results.
Table 3.14 Number of migrant active boats from District to Division
To To To To Busia Siaya Kisumu South Nyanza Fun- Buda- Rarie Mase- Wi- Nyan- Nya- Ken Rang- Mbi Nya- From yula langi Bondo da no nam do kach -du we -ta tikeTOTAL
Busia - 35 1 0 1 0 0 1 1 6 4 49
Siaya 0 14 - 1 5 0 0 9 0 72 4 105
Kisumu 0 11 205 143 - - - 11 0 52 27 449
South 0 3 11 57 0 1 0 1 - - 73 Nyanza
TOTAL Division 0 28 251 201 1 7 0 1 21 1 130 187 676
TOTAL 28 452 District 9 187 676
A total of 676 inter-district migrant boats were encountered. The bulk (66.4 %) of migrants originated from Kisumu district of which the majority (77.5 %) migrated to Siaya district. From the table it can be deducted that both Kisumu and Busia District experienced a net outflow of 440 and 21 (registered) boats while Siaya and South Nyanza District accommodated a net inflow of 347 and 114 boats respectively. 19
Table 3.15 below relates the number of migrant boats to the total number of boats enumerated in every Division.
Table 3.15 Number of registered boats and registered boats from outside the district per Division
No. of registered boatsNo. of registered boatsPercentage of Division encountered from outside District outsiders
Funyula 94 0 0.0 Budalangi 451 28 6.2 Bondo 814 251 30.8 Rarieda 477 201 42.1
Maseno 134 1 0.7 Winam 212 7 3.3 Nyando 166 0 0.0
Nyakach 146 1 0.7 Kendu 352 21 6.0
Rangwe 96 1 1.0 Mbita 1370 130 9.5 Nyatike 689 35 5.1
TOTAL 5001 676 13.5
From this table it is clear that Bondo and Rarieda Division in Siaya District accommodate a fairly large proportion of migrants of which 77.0 % originate from Kisumu district.
4. CONCLUDING COMMENTS AND RECOMMENDATIONS
The most widespread type of boat was the Sesse Canoe followed by the Taruma canoe. Only a very small number of dugout canoes were encountered. During the past 6 years the number of boats assumed to be active, and as such used as a raising factor in the formula employed to calculate the total catch from the Kenya part of Lake Victoria, was 5000. The total number of active boats enumerated during the 1991 census was 6229. In view of this finding current and possibly historical catch figures should be (re) calculated using a (24.6 %) higher raising factor for the number of active boats.
The prevailing fishery type was the Nile perch gillnet fishery followed by the longline fishery. Taking all active boats in these two fishery types together it is concluded that half of the active boats target primarily for nile perch.
By combining the 1991 census data on the number of active boats by fishery type and/or gear with the results of the catch and effort samples of the DoF and KMFRI a more accurate total catch per gear and species can now be derived.
Motorization of fishing boats is still very limited. The majority of boats equipped with an engine operated in the Nile perch gill net fishery.
Boat owners in Kenya are required to obtain a license for each fishing boat they own. The licensed boats carry official markings. The overall proportion of unregistered active boats, however, was found to be around 20%, ranging 20 from only 3% in Rangwe division to 37.9 % in Budalangi division. Furthermore it was found that there was multiple usage of one registration number on different boats and that artificial registration numbers existed.These phenomena combined with the factthat thesystem does notrecordthe (registered) boats which disappear from the fishery casts, at present, serious doubts on the usefulness of the boat registration system as a means to estimate the total number of active boats and therewith total catch. The system of boat registration should be strengthened and should take into account the (major) fishery type in which the boat/unit operates. This would enable a more effective monitoring of effort and eventually a better control of effort. Furthermore it would enable a more accurate estimate of total catch and of catch by gear and species. Assuming that these improvements in the system would mater alize it is still advisable to regularly execute a census of fishing boats, possibly with an interval of 3 to 5 years7 .
The assessment of the rate of migration was constrained by the fact that the origin of the boats could only be identified by district. Consequently intra- district migration, for example a boat originating in South Nyanza inside the Nyanza Gulf and migrating to the open waters (outside the Nyanza Gulf) in the same district, could not be assessed. Furthermore migration of unregistered boats could not be recorded. Having these limitations in mind it was noted that one seventh of all registered boats appeared to have migrated out of their distri.ct of origin (i.e. where they were registered). The majority of these migrant boats originated from Kisumu district. These boats from the Nyanza Gulf (which is claimed to be overexploited) appeared to mainly mig ate to the northern offshore areas.
7 Experience has shown that, when well organized, data collectlon, input and processing takes about 2 to 3 months. 2 1
5 . FIGURES 100% 75%
50%
, N 25% 0% Funyula Bondo Maseno Nyando Kendu Mbita Total Budalangi F.771Zi- Dugout canoe Rarieda Winam Karua L.J Nyakach Sesse canoe Rangwe Tarurna Nyatike 0% 1 Funyala BudalangiBeachNile perch seine GN Bondo Rarieda Maseno LA Winam MosquitoTilapia GN seine Nyando Nyakach Kendu Rangwe MosquitoLong line seine/light Mbita Nyatike Total ,11111111110001
gillnetTilepia 16%
FUNYULA BUDALANGI NI eperch gillnet 35% Longline 24% Other 5%Unknown 2% Unknown 15% Tilapis gillnet 47% Beachseine 7% Tilapia gillnet 11% Beachseine 7% Mosquito net 3% Mosquito net/lights 2% Other 3% BOND° RARIEDA LonglIne 19% Tilapla 1 gllinet 22% glilnet 23% 11111111101ilililellijerch Other 6% Unknown 4% 1111111100111111111N117:ch OtherUnknown 3% 1% t15% Beachseine 12% Mosquito net 5% Mosquito net/lights 17% Beachseine 10% Mosquito net 4% Mosquito net/lights 25% giliriat Beachseine Mosquito net/lights MAsEN0 [-orlon° WINAm Nileporch l 11111111111' Unknown 1%gillnet 6% 7aciagIllnet lila pia Other Beaoha eine 3% NyAND0 Lehone NyAKAcH Lengline gillnet 16% THapia 33% gffinet 01111100illeperch Other Unknown 1% gilinet li Beach seine 4% Mosquito h_. ut 14% Beachseine Mosquito net Tilepisgillnet 11% Longune 27% KENDU 1111Nileperch gillnet 12% TilaPla RANGWE Longline 18% Other 4% Unknown 4% gillnet 39% NiloPerch Mosquito net/lights 23% Adi111111110111111 Other gillnet6%Unknown 9% 1% Lonone 12% Mosquitolights net/ 6% Tilapia Beachseine 6% Mosquito net 14% MBITA OtherUnknown 2% 1% NilePerch gillnet 57% NYATIKE gillnet 12% Mosquitolights net/ 18% UnknownOther 2% 0% Beachseine 13% Mosquito net 1% Longline 12% TilaPis011 gillnet 6% Bo alAse',',uNv Mosquitolights net/ t17% 0% 27
6. REFERENCES
Bernacsek, G.M., Kenya, Tanzania and Uganda, evaluation of statistical 1986 services for Lake Victoria fisheries. Mission report. Accra, Ghana. FAO Regional Office for Africa, Committee for Inland Fisheries of Africa. Sub-committee for the Development and Management of the Fisheries in Lake Victoria (Second draft)
Butcher, D.A.P. and J.C.G. Colaris, A sociological survey of the fishermen 1975 population around Lake Victoria. A report prepared for the Lake Victoria Regional Fisheries Research Project, FI:DP RAF/71/242/4
Fisheries Department, Ministry of Regional Development/FAO. Review of the (in press) Fisheries of Kenya.
Gréboval, D., Management of the New Fisheries of Lake Victoria: Major 1989 socio-economic issues. UNDP/FAO Regional Project for Inland Fisheries Planning (IFIP). RAF/87/099/TD/04/89 (En)
Ogutu, E.M., Artisanal Fisheries of Lake Victoria, Kenya. Social and 1988 Economic Aspects of Production and Marketing. Paper presented at the Regional Workshop on the Fisheries of Lake Victoria, Kenya
Prado J., R.J. Beare, J. Siwc Mbuga, L.E. Oluka. A catalogue of fishing 1991 methods and gear used in Lake Victoria. UNDP/FAO Regional Project for Inland Fisheries Planning (IFIP), RAF/87/099- TD/19/91 (En): 104p
Reynolds, J.E. and D.F. Gréboval, Socioeconomic effects of the evolution of 1988 the Nile perch fisheries in Lake Victoria: A review. CIFA Technical paper (17): 148p 28
ANNEXES Map 1: Landing beaches northern section Kenya waters 76 8 SisenyeRudachoBudubusi 4321 BusembeBuyukaBwolokomaSto -port 5.0 121110 9 MulukobaMateraMarengaNanjomi beach 5 Bumbe buSIA DISTRICT 16151314 RukalaNamabusiRugungaBukoma 17201918 OsiekoBulwaniRunyuMaduwa / VictoriaPort S I AYA DISTRICT 2322 HongeMambo Yà'La",w'a mp 4243 NdedaStrong°Ltunda Isl. 272625 UsengeGoyeSiungu ; 3 363534 Ir'Anyanga OeleNyaudengeUwaria Bead. 29 28 Sik a Mageta MisoriUhanya A t,,, 38403937 SifuWariandaUtongaUgamba 6968 Nyarnaruaka 303132 UtandaMutunduMahanga Mageta Mageta _ 41 Luanda Isl. 46 UyawiOyarno Isl 6364 KadcdiKokech 70737271 As BaoKobucltoKagwelArongot 77 Ogal C) 0 494847 SOWichlum OgadaLudhiNyamnwa / 676665 RalaKokKowange ach yo 767574 0 thanyKaManga loka 31798078 Usorna/NgegePagaRari /Usare 515352 KamOsingoObenge ariga I. KISUML),IDISTRICT)-' 8382 TakoDungaKichinjio , 8584876 ObangeMirutiNyamwa 565554 MisoriKojwang B / A KISUMU 988098 ORNdicauhtruok * 57 WikwangLijando Kotien . . . . . / vi 9291 OgenyaKówiti I AS - 959493 Kombewa Ng 'ou 1 97 1 98 19 9 202201200 203204205 207206 \ \ 208 25 I 31 Annex 2 List of beaches with number of active boats by District, Division, Location and Sub-location Beach Active code Beach name boatsDistrict Division Location Sublocation 1 Sio-port 36 Rusia Funyula South Samia Bujwanga 2 Bwolokoma 30 Rusia Funyula South Samia Bujwanga 3 Buyuka 14 Busia Funyula South Samia Busembe 4 Busembe 21 Busia Funyula South Samia Busembe 5 Bumbe 10 Busia Funyula South Samia Busembe 6 Sisenye 47 Rusia Budalangi Bunyala W. Sisenye 7 Budubusi 47 Rusia Budalangi Bunyala W. Sisenye 8 Rudacho 91 Rusia Budalangi Bunyala W. Bulemia 9 Marenga 62 Rusia Budalangi Bunyala W. Bukoma 10 Nalera beach 52 Rusia Budalangi Bunyala W. Bukoma 11 Mulukoba 23 Rusia Budalangi Bunyala W. Bukoma 12 Nanjomi 16 Rusia Budalangi Bunyala S. Magombe W. 13 Rugunga 12 Rusia Budalangi Bunyala S. Lugale 14 Bukoma 74 Busia Budalangi Bunyala W. Bukoma 15 Namabusi 96 Busia Budalangi Bunyala S. Buofu 16 Rukala 51 Busia Budalangi Bunyala S. Buofu 17 Runyu 29 Rusia Budalangi Bunyala S. Buofu 18 Bulwani 24 Rusia Budalangi Bunyala S. Obaro 19 Maduwa 9 Busia Budalangi Bunyala S. Obaro 20 Osieko 38 Busia Budalangi Bunyala S. Obaro 21 Wayasi Isl. 55 Busia Budalangi Bunyala S. Obaro 22 Nambo 28 Siaya Bondo Yimbo W. Got Agulu 23 Honge 21 Siaya Rondo Yimbo W. Got Agulu 24 Siungu 13 Siaya Bondo Yimbo W. Got Agulu 25 Goye 39 Siaya Bondo Yimbo W. Usenge 26 Usenge 44 Siaya Sondo Yimbo W. Usenge 27 Uhanya 132 Siaya Rondo Yimbo W. Usenge 28 Misori A 20 Siaya Rondo Yimbo W. Usenge 29 Sika Mageta 49 Siaya Bondo Yimbo W. Mageta 30 Utanda Mageta 23 Siaya Bondo Yimbo W. Mageta 31 Mahanga Mageta 56 Siaya Rondo Yimbo W. Mageta 32 Mutundu 21 Siaya Bondo Yimbo W. Mageta 33 Anyanga 35 Siaya Bondo Yimbo W. Usenge 34 Uwaria 17 Siaya Bondo Yimbo C. Usigu 35 Nyaudenge 17 Siaya Bondo Yimbo E. Nyamonye 36 Oele Beach 36 Siaya Rondo Yimbo E. Pala 37 Ugamba 12 Siaya Rondo Yimbo E. Pala 38 Utonga 30 Siaya Rondo Sakwa W. Utonga 39 Warianda 19 Siaya Rondo Sakwa C. Nyangoma 40 Sifu Isl. 15 Siaya Rondo Sakwa C. Nyangoma 41 Luanda 18 Siaya Rondo Sakwa C. Nyangoma 42 Sirongo 65 Siaya Rondo Sakwa C. Nyangoma 43 Liunda 42 Siaya Rondo Sakwa C. Uyawi 44 Ndeda Isl. 61 Siaya Rondo Sakwa C. Uyawi 45 Oyamo Isl. 38 Siaya Rondo Sakwa C. Uyawi 46 Uyawi 25 Siaya Rondo Sakwa C. Uyawi 47 Nyamnwa 24 Siaya Rondo Sakwa S. Nyaguda 48 Ogada 13 Siaya Rondo Sakwa S. Nyaguda 32 Beach Active codeBeachname boats District Division Location Sublocation 49 Wichlum 82 Siaya Bando Sakwa S. Nyaguda 50 Ludhi 18 Siaya Bondo Sakwa S. Nyaguda 51 Kamariga 37 Siaya Rarieda Uyoma W. Kagwa 52 Obenge 18Siaya Rarieda Uyoma W. Kagwa 53 Osingo 49 Siaya Rarieda Uyoma W. Kokwiri 54Misori B 89 Siaya Rarieda Uyoma W. Nyabera 55 Kojwang 14 Siaya Rarieda Uyoma E. Naya 56Luando Kotieno 75 Siaya Rarieda Uyoma E. Naya 57 Wikwang 18 Siaya Rarieda Uyoma E. Naya 58 Madundu 25 Siaya Rarieda Uyoma E. Naya 59 Gudwa 20 Siaya Rarieda Uyoma E. Lieta 60 Kopiata 50 Siaya Rarieda Uyoma E. Katwenga 61 Kogonga 20 Siaya Rarieda Uyoma E. Ragengini 62Aram 13 Siaya Rarieda Uyoma W. Masala 63Kokech 11 Siaya Rarieda Asembo W. Mahaya 64 Kadedi 14 Siaya Rarieda Asembo W. Mahaya 65 Kowange 20 Siaya Rarieda Asembo C. Memba 66Kokach 23 Siaya Rarieda Asembo E. Omia Mwalo 67 Ralayo 28 Siaya Rarieda Asembo E. Omia Mwalo 68 Nyamaruaka 4 Kisumu Maseno Seme S.W. Kadinga W. 69 Arongo 1 Kisumu Maseno Seme S.W. Kadinga W. 70 Kagwel 35 Kisumu Maseno Seme S.W. Alungo 71 Kobudho 22 Kisumu Maseno Seme S.W. Alungo 72 Asat 35 Kisumu Maseno Seme C. Othany 73 Bao 13 Kisumu Maseno Seme C. Othany 74Othany 8 Kisumu Maseno Seme C. Othany 75 Nanga 10 Kisumu Maseno Seme E. Kajulu/Koker 76Kaloka 28 Kisumu Maseno Seme E. Kajulu/Koker 77 Ogal 25 Kisumu Winam Kisumu S.W. Osiri 78 Rari 17 Kisumu Winam Kisumu S.W. Osiri 79 Paga 29 Kisumu Winam Kisumu S.W. Kanyawegi 80Usoma/Ngege/Usare 33 Kisumu Winam Kisumu E. Kogony 81 Kichinjio 26 Kisumu Winam Kisumu E. Kogony 82Dunga 69 Kisumu Winam Kolwa W. Nyalenda B 83 Tako 25 Kisumu Winam Kolwa W. Nyalenda B 84 Nyamware 35 Kisumu Nyando Kano N.W. Nyamware S. 85 Miruti 3 Kisumu Nyando Kano N.W. Nyamware S. 86 Obange 16 Kisumu Nyando Kano S.W. Kawino 87 Nduru 15 Kisumu Nyando Kano S.W. Kadhiambo 88 Ochok 25 Kisumu Nyando Kano S.W. Kadhiambo 89 Riat 28 Kisumu Nyando Kano S.W. Kadhiambo 90 Kowiti 12 Kisumu Nyando Kano S.W. Upper Bwanda 91 Ogenya 46 Kisumu Nyando Kano S.W. Lower Bwanda 92 Singida 19 Kisumu Nyando Kano S.E. Ombaka 93 Kusa 41 Kisumu Nyakach Nyakach C. Kabodho W. 94 Ng'ou 23 Kisumu Nyakach Nyakach W. Koguta W. 95 Kombewa 16 Kisumu Nyakach Nyakach W. Koguta W. 33 Beach Active codeBeachname boats District Division Location Sublocation 96 Bala 13 Kisumu Nyakach Nyakach W. Koguta W. 97 Sango Rota 30 Kisumu Nyakach Nyakach W. Lower Kadiangla 98 Koguta 37 Kisumu Nyakach Nyakach W. Lower Kadiang'a 99 Miriu 20 Kisumu Nyakach Nyakach W. Lower Kadiang'a 100 Nyandho 24 S. Nyanza Kendu Karachuonyo E. Kobala 101 Chuowe 23 S. Nyanza Kendu Karachuonyo E. Kobala 102 Alara 15 S. Nyanza Kendu Karachuonyo E. Kobala 103 Dunga Kobala 14 S. Nyanza Kendu Karachuonyo E. Kamwala 104 Rakwaro 20 S. Nyanza Kendu Karachuonyo E. Kogweno/Rakwaro 105 Wikawere/Karabondi 11 S. Nyanza Kendu Karachuonyo E. Kajieyi/Karabondi 106 Achuodo 12 S. Nyanza Kendu Karachuonyo E. Kamser-Seka 107 Kagwa 10 S. Nyanza Kendu Karachuonyo E. Kamser-Seka 108 Kendu 24 S. Nyanza Kendu Karachuonyo N. Kakwajuok 109 Siala 12 S. Nyanza Kendu Karachuonyo C. Kogembo 110 Obaria 36 S. Nyanza Kendu Karachuonyo C. Kamser B 111 Sare 13 S. Nyanza Kendu Karachuonyo N.W. Wagwe 112 Awana 33 S. Nyanza Kendu Karachuonyo N.W. Wagwe 113 Miti Mbili 13 S. Nyanza Kendu Karachuonyo N.W. Kanj ira 114 Bala Kochoo 18 S. Nyanza Kendu Karachuonyo N.W. Kokoth B 115 Wath Remo 13 S. Nyanza Kendu Karachuonyo N.W. Kokoth B 116 Bala Rawi 22 S. Nyanza Kendu Karachuonyo W. Kanam B 117 Doho 11 S. Nyanza Kendu Karachuonyo W. Kanam B 118 Mainuga 47 S. Nyanza Kendu Karachuonyo W. Kanam B 119 Kaimbo 13 S. Nyanza Kendu Karachuonyo W. Kanam A 120 Homalime 18 S. Nyanza Kendu Karachuonyo W. Kanam A 121 Rang'ombe 22 S. Nyanza Kendu Karachuonyo W. Kanam A 122 Alum 23 S. Nyanza Kendu Karachuonyo W. Ayoo Dhimu 123 Ombogo 19 S. Nyanza Rangwe Kochia Kanam 124 Ngegu 24 S. Nyanza Rangwe Kochia Kanam 125 Lela 10 S. Nyanza Rangwe Town Kalanya 126 Koginga 20 S. Nyanza Rangwe Town Arujo 127 Kananga 26 S. Nyanza Rangwe Town Arujo 128 Sukru Isl, 32 S. Nyanza Mbita Lambe Lambwe E. 129 Ndhuru 27 S. Nyanza Mbita Lambe Lambwe E. 130 Kisaka 17 S. Nyanza Mbita Lambe Lambwe E. 131 Uwii 11 S. Nyanza Mbita Gembe Wasaki W. 132 Ondago 21 S. Nyanza Mbita Gembe Wasaki W. 133 Akuot 30 S. Nyanza Mbita Gembe Wasaki W. 134 Misori Kobar 28 S. Nyanza Mbita Gembe Wasaki W. 135 Gode Ariyo 28 S. Nyanza Mbita Gembe Wasaki W. 136 Alero 33 S. Nyanza Mbita Gembe Wasaki W. 137 Mirunda 23 S. Nyanza Mbita Gembe Wasaki W. 138 Nyaroya 9 S. Nyanza Mbita Gembe Wasaki W. 139 Lwanda Nyamasare 33 S. Nyanza Mbita Gembe Gembe E. 140 Kaugege 18 S. Nyanza Mbita Gembe Gembe E. 141 Olambwe 26 S. Nyanza Mbita Gembe Gembe E. 142 Kisui 17 S. Nyanza Mbita Gembe Gembe E. 143 Uyoga 35 S. Nyanza Mbita Gembe Gembe E. 34 Beach Active code Beachname boatsDistrict Division Location Sublocation 144 Koguna 19 S. Nyanza Mbita Gembe Gembe E. 145 Nyachebe 15 S. Nyanza Mbita Gembe Gembe E. 146 Tabla 23 S. Nyanza Mbita Gembe Gembe E. 147 Gingo 28 S. Nyanza Mbita Kaksingri Kaksingri E. 148 Sindo 36 S. Nyanza Mbita Kaksingri Kaksingri E. 149 Roo 9 S. Nyanza Mbita Kaksingri Kaksingri W. 150 Ukula 21 S. Nyanza Mbita Kaksingri Kaksingri W. 151 Nyakwara 18 S. Nyanza Mbita Kaksingri Kaksingri W. 152 Kibuogi Isl. 19 S. Nyanza Mbita Kaksingri Kaksingri W. 153 Kisenye 14 S. Nyanza Mbita Kaksingri Kaksingri W. 154 Ragwe 46 S. Nyanza Mbita Kaksingri Kaksingri W. 155 Litare 17 S. Nyanza Mbita Kaksingri Kaksingri W. 156 Nyagina 59 S. Nyanza Mbita Rusinga Isl. Waware 157 Utajo 23 S. Nyanza Mbita Rusinga Isl. Waware 158 Kogalo 25 S. Nyanza Mbita Rusinga Isl. Waware 159 Ulugi 10 S. Nyanza Mbita Rusinga Isl. Waware 160 Ngodhe Isl. 11 S. Nyanza Mbita Rusinga Isl. Wanyama Kaswanga 161 Lwanda Rombo 27 S. Nyanza Mbita Rusinga Isl. Wanyama Kaswanga 162 Kiumba 55 S. Nyanza Mbita Rusinga Isl. Wanyama Kaswanga 163 Litare Kandiege 21 S. Nyanza Mbita Rusinga Isl. Kamasengre 164 Ufira 30 S. Nyanza Mbita Rusinga Isl. Kamasengre 165 Sienga 30 S. Nyanza Mbita RusingaIsl. Kamasengre 166 Yokia 28 S. Nyanza Mbita Mfangano Isl. Waware 167 Nyakweri 35 S. Nyanza Mbita Mfangano Isl. Waware 168 Wakula 16 S. Nyanza Mbita Mfangano Isl. Wakula 169 Mulundu 50 S. Nyanza Mbita Mfangano Isl. Wakula 170 Ringiti Isl. 62 S. Nyanza Mbita Mfangano Isl. Wakula 171 Ugina 13 S. Nyanza Mbita Mfangano Isl. Wakula 172 Kasarani 17 S. Nyanza Mbita Mfangano Isl. Wakula 173 Remba Isl. 100 S. Nyanza Mbita Mfangano Isl. Wakula 174 Makira 24 S. Nyanza Mbita Mfangano Isl. Wakinga 175 Takawiri Kongata 12 S. Nyanza Mbita Mfangano Isl. Wakinga 176 Takawiri Kamarach 19 S. Nyanza Mbita Mfangano Isl. Wakinga 177 Nyagwethe 10 S. Nyanza Mbita Gwassi N. Uregi 178 Uterere 15 S. Nyanza Mbita Gwassi N. Uregi 179 Kisegi 20 S. Nyanza Mbita Gwassi N. Uregi 180 Kiwiro 15 S. Nyanza Mbita Gwassi N. Uregi 181 Osiri 25 S. Nyanza Mbita Gwassi N. Uregi 182 Kitawa 26 S. Nyanza Mbita Gwassi N. Uregi 183 Sibora 16 S. Nyanza Mbita Gwassi N. Kubia W. 184 Kiwa Isl. 33 S. Nyanza Mbita Gwassi N. Kubia W. 185 Nyandiwa 55 S. Nyanza Mbita Gwassi N. Kubia W. 186 Kinda 41 S. Nyanza Mbita Gwassi C. Nyancha 187 Kagoro 19 S. Nyanza Mbita Gwassi C. Nyancha 188 Rasira 23 S. Nyanza Mbita Gwassi E. Owich 189 Muluyu 19 S. Nyanza Mbita Gwassi E. Owich 190 Ohodi 25 S. Nyanza Nyatike Karungu W. Gunga 191 Okiro 16 S. Nyanza Nyatike Karungu W. Gunga 192 Soni 91 S. Nyanza Nyatike Karungu W. Kachien'g 193 Bongu 12 S. Nyanza Nyatike Karungu W. Raga 194 Aloma 17 S. Nyanza Nyatike Karungu E. Misiwi 35 Beach Active code Beachname boats District Division Location Sublocation 195 Nglira 38 S. Nyanza Nyatike Karungu E. Ng'ira 196 Lwanda Konyango 47 S. Nyanza Nyatike Kadem N. Kolal 197 Modi 25 S. Nyanza Nyatike Kadem C. Kanyuor 198 Kao 67 S. Nyanza Nyatike Kadem C. Kakelo Kakoth 199 Aneko 120 S. Nyanza Nyatike Kadem S. Kakoth 200 Got Kachola 57 S. Nyanza Nyatike Kadem S. Kakoth 201 Matoso 31 S. Nyanza Nyatike Kadem S. Kakoth 202 Lidha 33 S. Nyanza Nyatike Kadem S. Kakoth 203 Tagache 56 S. Nyanza Nyatike Muhuru Muhuru E. 204 Nyan'gwina 60 S. Nyanza Nyatike Muhuru Muhuru W. 205 Ng'ore 57 S. Nyanza Nyatike Muhuru Muhuru W. 206 Isumba 53 S. Nyanza Nyatike Muhuru Muhuru W. 207 Mugabo 37 S. Nyanza Nyatike Muhuru Muhuru W. 208 Kibro 71 S. Nyanza Nyatike Muhuru Muhuru W. Note: Key to abbreviations N.=North E.=East S.=South W.=West Isl.=Island 36 FISHING BOAT CENSUS FORM (FOR REGISTERED BOATS ) LAKE VICTORIA, KENYA Annex 3 The census data collection form WATERS (IFIP/FAO, KMFRI, DEP. of FISHERIES) 1 1 1 1---1 1 I 1 1 Name of enumerator:I 1 DoF1 1 IKM FRII 1 i 'Name of beach:I 1 I I i I 1 1 1 I i Code' t I Dates of data collection on beach:I i 1'District:I 'Location: ISub-location: Boat registration number Type of boat Active or If not active not active vistingResident or or Repairableobsolete or not repairable Yes/NoEngine gillnetNile perch Yes/No Tilapia gillnet Yes/No Yes/NoLongline Beach seine Yes/No Mosquito seine Yes/No Light(s) 1 Date of collection of form:I 'by: Names of researchers' 1 Yes/No Other (Specify) Gearsidentified not FISHING BOAT CENSUS FORM (FOR UN-REGISTERED BOATS) LAKE VICTORIA, KENYA WATERS 37 i 1 i I 1---1 (IFIP/FAO, KMFRI, DEP. of FISHERIES) 1 Name of enumerator:I I I DoFI IKMFRII 'Name of beach: I I I 1 I I I 1 I i I 1 C°dell IIII I I I Dates of data collection on beachd I I I'District:I I I I'Location:I I Sub-location: Date of collection of form:I Iby: Names of researchers' I Enter number for un- registered boats(1, 2, 3 etc.) Type of boat Activenot activeor Resident or If not active visting or obsolete Repairable or not repairable Engine Yes/No Nile perch gillnet Yes/No Tilapiagillnet Yes/No Yes/NoLongline.seine Beach Yes/No Yes/NoMosquitoseine Light(s) Yes/No Other (Specify) Gearsidentified not 38 LIST OF IFIP REPORTS - LISTE DES RAPPORTS PPEC I. TECHNICAL DOCUMENTS / DOCUMENTS TECHNIQUES Gréboval D., A. Bonzon, M. Giudicelli and E. Chondoma, Baseline Survey Report 1989 (1987) on inland fisheries planning, development and management in Eastern/Central/Southern Africa. UNDP/FAO Regional Project for InlandFisheries Planning (IFIP). RAF/87/099-TD/01/89 (En): 104p. Gréboval D., A. Bonzon, M. Giudicelli et E. Chondoma, Rapport de l'étude de 1989 base (1987) sur la planification, le développement et l'aménagement des pêches continentales en Afrique Orientale/ Centrale/Australe. Projet Régional PNUD/FAO pour la Planification des Péches Continentales (PPEC). RAF/87/099- TD/01/89 (Fr): 110p. Gréboval D., and B. Horemans (eds), Selected Papers presented at the SADCC/FAO 1989 Training Workshop on Fisheries Planning,Victoria Falls, Zimbabwe, 15-24 Novembre 1988. UNDP/FAO Regional Project for Inland Fisheries Planning (IFIP). RAF/87/099-TD/02/89 (En): 138p. Horemans B., et Maes M.(éds), Rapport de la Consultation technique sur les 1989 lacs Cohoha et Rweru partagés entre le Burundi et le Rwanda (Bujumbura, 13 et 14 Décembre 1989). Projet Régional PNUD/FAO pour la Planificationdes PêchesContinentales (PPEC). RAF/87/099-TD/03/89 (Fr): 94p. Gréboval D., Management of the New Fisheries of Lake Victoria: Major socio- 1989 economic issues. UNDP/FAORegional Project for Inland Fisheries Planning (IFIP), RAF/87/099-TD/04/89 (En): 25p. GrébovalD. (ed), Principles of fisheries management and legislation of 1990 relevance to the Great Lakes of East Africa: Introduction and case studies. UNDP/FAO Regional Project for Inland Fisheries Planning (IFIP), RAF/87/099-TD/05/90 (En): 41p. Report of the IFIP/SWIOP Workshop on Economic Aspects of Fisheries Development 1990 and Management. UNDP/FAO Regional Project for Inland Fisheries Planning (IFIP), RAF/87/099-TD/07/90 (En): 22p . Corsi F., Evaluation des pêcheries zaYroises des lacs Idi Amin/Edouard et 1990 Mobutu Sese Seko. Projet Régional PNUD/FAO pour la Planification des Pêches Continentales (PPEC). RAF/87/099- TD/08/90 (Fr): 64p. Corsi F., Evaluation of the Zairian Fisheries of Lakes Edward and Mobutu. 1990 UNDP/FAO RegionalProject for Inland Fisheries Planning (IFIP), RAF/87/099-TD/08/90 (En): 60p . 39 Rapport de la première réunion du Comité consultatif du projet régional pour 1990 la planification des pêches continentales. Projet Régional PNUD/FAO pour la Planification des Pèches Continentales (PPEC). RAF/87/099-TD/09/90 (Fr): 24p. Report of the First Meeting of the Advisory Committee of the Regional Project 1990 for Inland Fisheries Planning. UNDP/FAO Regional Project for Inland Fisheries Planning (IFIP), RAF/87/099-TD/09/90 (En): 22p. Report of the Symposium on Socio-economic aspects of Lake Victoria Fisheries. 1990 A Symposium organized by the IFIP Project under the framework of the CIFA Sub-comittee for Lake Victoria,24-27 April, Kisumu, Kenya, UNDP/FAO Regional Project for Inland Fisheries Planning (IFIP), RAF/87/099-TD/10/90 (En): 24p. Maes M.(ed), Report on the Technical Consultation on Lake Mweru shared by 1990 Zaire and Zambia,08-10 August,Lusaka, Zambia,UNDP/FAO Regional Project for Inland FisheriesPlanning (IFIP), RAF/87/099-TD/11/90 (En): 44p. Maes M.(éd), Rapport de la Consultation technique sur le lac Mweru partagé 1990 entre le Zaire et la Zambie,08-10 août, Lusaka,Zambie, Projet Régional PNUD/FAO pour la Planification des Pêches Continentales (PPEC). RAF/87/099-TD/11/90 (Fr): 45p. Papers presented at the IFIP/SWIOP Workshop on Economic Aspects of Fisheries 1990 Development and Management. UNDP/FAO Regional Project for Inland Fisheries Planning (IFIP), RAF/87/099-TD/12/90 (En): 122p. Case studies presented at the IFIP/SWIOP Workshop on Economic Aspects of 1990 FisheriesDevelopment andManagement UNDP/FAORegional Project for Inland Fisheries Planning (IFIP),RAF/87/099- TD/13/90 (En): 115p. Report of the Workshop on Fisheries Statistics and Information Systems for 1990 Lake Victoria,26-29 June 1990,Kampala, Uganda, UNDP/FAO Regional Project for InlandFisheriesPlanning (IFIP), RAF/87/099-TD/14/90 (En): 72p. Rapport de la consultation Technique sur l'aménagement des pêcheries des lacs 1990 Edouard et Mobutu,17-21 septembre 1990, Kampala, Ouganda, Projet Régional PNUD/FAO pour la Planification des Pêches Continentales (PPEC). RAF/87/099-TD/15/90 (Fr): 30p. Report of Technical Consultation on Management of the Fisheries of Lakes 1990 Edward and Mobutu, 17-21September 1990,Kampala, Uganda, UNDP/FAO RegionalProject for Inland FisheriesPlanning (IFIP), RAF/87/099-TD/15/90 (En): 26p. Report of the National Workshop on Fishery Statistics and Information Systems, 1990 22-26 October 1990, Addis Ababa, Ethiopia, UNDP/FAO Regional Project for Inland Fisheries Planning (IFIP), RAF/87/099- TD/16/90 (En): 33p. 40 Machena C. and V. Kanondo, A Review of the Fisheries of Lake Kariba and their 1991 Management. UNDP/FAO Regional Project for Inland Fisheries Planning (IFIP). RAF/87/099-TD/17/91 (En): 58p. Rapport de la deuxième réunion du Comité consultatif du projet régional pour 1991 la planification des pêches continentales. Projet Régional PNUD/FAO pour laPlanification des Pêches Continentales (PPEC). RAF/87/099-TD/18/91 (Fr): 25p. Report of the Second Meeting of the Advisory Committee of the Regional Project 1991 for Inland Fisheries Planning. UNDP/FAO Regional Project for Inland Fisheries Planning (IFIP). RAF/87/099-TD/18/91 (En): 23p. Prado J., Beare R.J., Siwo Mbuga J., Oluka L.E. A catalogue of fishing methods 1991 and gear used in Lake Victoria. UNDP/FAO Regional Project for Inland Fisheries Planning (IFIP). RAF/87/099-TD/19/91 (En): 104p. Biribonwoha A.R. A Review of Fisheries Inputs in Kenya, Tanzania and Uganda. 1991 UNDP/FAO RegionalProject for Inland FisheriesPlanning (IFIP). RAF/87/099-TD/20/91 (En): 65p. Rapport de la deuxième Consultation technique sur l'aménagement des pêcheries 1991 des lacsEdouardet Mobutu SeseSeko. Projet Régional PNUD/FAO pour la Planification desPêches Continentales (PPEC). RAF/87/099-TD/21/91 (Fr): 27p. Report of the Second Technical Consultation on the Management of the Fisheries 1991 of lakes Edward and Mobutu, 27-29 May 1991, Kinshasa, Zaire. UNDP/FAO RegionalProjectfor Inland FisheriesPlanning (IFIP). RAF/87/099-TD/21/91 (En): 28p. Leendertse K. and B. Horemans. Socio Economic Characteristics of the Artisanal 1991 Fishery in Kigoma region, Tanzania. UNDP/FAO Regional Project for Inland Fisheries Planning (IFIP),RAF/87/099-TD/22/91 (En): 104p. Hanek G.,K. Leendertse and B. Farhani, Socio-Economic Investigations of Lake 1991 Kivu Fisheries. UNDP/FAO Regional Project for Inland Fisheries Planning (IFIP), RAF/87/099-TD/23/91 (En): 55p. Report onthe Regional Training Course on Fish Stock Assessment, 21 January-15 1991 February 1991, Kariba, Zimbabwe. Denmark funds-in-trust FI: GCP/INT/392/DEN-Act. Rep. No 29 and UNDP/FAO Regional Project for Inland Fisheries Planning(IFIP), RAF/87/099-TD/24/91 (En): 29p. Bellemans M., Structural characteristics of the Burundi Fisheriesin 1990 and 1991 HistoricalReview. UNDP/FAO Regional Project forInland Fisheries Planning (IFIP), RAF/87/099-TD/25/91 (En): 26p. Hoekstra T.M., A. Asila, C. Rabuor, O. Rambiri. Report on a censusof 1991 fishing boats and gear in the Kenyan waters of Lake Victoria. UNDP/FAO RegionalProject for Inland FisheriesPlanning (IFIP), RAF/87/099-TD/26/91 (En): 36p. 41 II. WORKING PAPERS / DOCUMENTS DE TRAVAIL Bean C.E., Selected abstracts of basic references and current literature in 1989 fisheries economics. UNDP/FAO Regional Project for Inland Fisheries Planning (IFIP), RAF/87/099-WP/01/89 (En):51p. Ssentongo G.W.,Fish and fisheries of shared lakes of Eastern/Central/ 1990 SouthernAfrica. UNDP/FAO Regional Project for Inland Fisheries Planning (IFIP), RAF/87/099-WP/02/90 (En): 19p. Nfamara 5.D., Recent observations on the fisheries of lake Tanganyika. UNDP/ 1990 FAO Regional Project for Inland Fisheries Planning (IFIP), RAF/87/099-WP/03/90 (En):16p. Proceedings ofthe Symposium on Socio-economic aspects of Lake Victoria 1990 Fisheries. Volume 1(unedited papers 1-7). UNDP/FAO Regional Project for Inland Fisheries Planning (IFTP),RAF/87/099- WP/05/90 (En): 114p. Nfamara Improved method for smoking fish in the Kigoma region of Lake 1990 Tanganyika, Tanzania. UNDP/FAO Regional Project for Inland Fisheries Planning (IFIP), RAF/87/099-WP/06/90 (En): 23p. Proceedings ofthe Symposium on Socio-economic aspects of Lake Victoria 1991 Fisheries. Volume 2 (unedited papers 8-12). UNDP/FAO Regional Project for Inland Fisheries Planning (IFIP),RAF/87/099- WP/07/91 (En): in preparation. Gréboval D. et Diquelou J., Experimentation de la senne tournante et 1991 coulissante dans les eaux burundaises du lac Tanganyika: Etude de pre-faisabilite. Projet Regional PNUD/FAO pour la Planification des Pêches Continentales (PPEC). RAF/87/099- WP/08/91 (Fr): 20p. Maes M., Leendertse K. et Mambona Wa Bazolana, Recensement des unités de p6che 1991 zaYroise dans la partie nord du lac Tanganyika. Projet Regional PNUD/FAO pour la Planification des Pèches Continentales (PPEC). RAF/87/099-WP/09/91 (Fr): 61p.