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Catch Per Unit Effort (CPUE) RESEARCH FOR THE MANAGEMENT OF THE FISHERIES ON LAKE GCP/RAF/271/FIN-TD/80 (En) TANGANYIKA GCP/RAF/271/FIN-TD/80 (En) January 1998 CATCH PER UNIT OF EFFORT (CPUE) STUDY FOR DIFFERENT AREAS AND FISHING GEARS OF LAKE TANGANYIKA by COENEN E.C., PAFFEN P. & E. NIKOMEZE FINNISH INTERNATIONAL DEVELOPMENT AGENCY FOOD AND AGRICULTURAL ORGANIZATION OF THE UNITED NATIONS Bujumbura, January 1998 The conclusions and recommendations given in this and other reports in the Research for the Management of the Fisheries on the Lake Tanganyika Project series are those 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 FINNIDA concerning the legal status of any country, territory, city or area, or concerning the determination of its frontiers or boundaries. PREFACE The Research for the Management of the Fisheries on Lake Tanganyika project (LTR) became fully operational in January 1992. It is executed by the Food and Agriculture Organization of the United Nations (FAO) and funded by the Finnish International Development Agency (FINNIDA) and the Arab Gulf Program for the United Nations Development Organization (AGFUND). LTR's objective is the determination of the biological basis for fish production on Lake Tanganyika, in order to permit the formulation of a coherent lake-wide fisheries management policy for the four riparian States (Burundi, Tanzania, Zaire and Zambia). Particular attention is given to the reinforcement of the skills and physical facilities of the fisheries research units in all four beneficiary countries as well as to the build-up of effective coordination mechanisms to ensure full collaboration between the Governments concerned. Prof. O.V. LINDQVIST Dr. George HANEK LTR Scientific Coordinator LTR Coordinator LAKE TANGANYIKA RESEARCH (LTR) FAO B.P. 1250 BUJUMBURA BURUNDI Telex: FOODAGRI BDI 5092 Tel: (257) 229760 Fax: (257) 229761 email: [email protected] GCP/RAF/271/FIN-TD/80 (En) iii GCP/RAF/271/FIN PUBLICATIONS Publications of the project are issued in two series: * a series of technical documents (GCP/RAF/271/FIN-TD) related to meetings, missions and research organized by the project; * a series of manuals and field guides (GCP/RAF/271/FIN-FM) related to training and field work activities conducted in the framework of the project. For both series, reference is further made to the document number (01), and the language in which the document is issued: English (En) and/or French (Fr). F or b ibliographic p urpose s t his d ocument s hould b e c ited a s f ollows : Coenen E.J1., Paffen P.2 & E. Nikomeze3, Catch per Unit of 1998 Effort (CPUE) study for different areas and fishing gears of Lake Tanganyika. FAO/FINNIDA Research for the Management of the Fisheries on Lake Tanganyika. GCP/RAF/271/FIN-TD/80 (En): 86 p. 1 Mr. E.J. Coenen is a Fisheries Biologist and worked as a biostatistician at LTR/Bujumbura, Burundi. 2 Ms. P. Paffen is an APO Fisheries Biologist at LTR/Mpulungu, Zambia. 3 Mr. E. Nikomeze is a Fisheries Officer at the Department of Fisheries in Bujumbura, Burundi. GCP/RAF/271/FIN-TD/80 (En) iv TABLE OF CONTENTS 1. Introduction 1 2. Frame Surveys (FS) 2.1. Frame Survey history 3 2.2. Simultaneous FS (1995) results 3 3. Catch Assessment Surveys (CAS) 3.1. CAS in Burundi 6 3.2. CAS in Tanzania 8 3.3. CAS in Zambia 9 3.4. CAS in Congo 11 4. Fisheries statistics recorded during fish biology sampling 4.1. Liftnets 13 4.2. Beach seines (without lights) 18 4.3. Beach seines (with lights) 19 4.4. Chiromila seines 20 4.5. Purse seines 20 5. Spawning, recruitment, relative abundance, environmental conditions, etc. in clupeids 5.1. Single and multiple spawning 22 5.2. Higher survival through larger number of smaller eggs/larvae 23 5.3. Relation between food supply and level of spawning activity and fish fecundity 23 5.4. Relation between level of recruitment and post-hatching survival and egg production 23 5.5. Relation between temperature and spawning success. 23 5.6. Other factors influencing recruitment success 23 5.7. Influence of wind and upwelling on the spawning success 24 5.8. Spatial distribution of clupeids 24 5.9. Migrations 25 5.10. Environmental fluctuations 25 5.11. Factors affecting fishing operations targeted at clupeids 25 6. Summary and conclusions 6.1. FS, CAS and CPUE results 25 6.2. CPUE: a measure of abundance? 27 6.3. The influence of environmental conditions on CPUE 27 6.4. Future monitoring of catch/effort fishery statistics 28 Acknowledgements 30 References 31 Figures and Tables 35 GCP/RAF/271/FIN-TD/80 (En) v 1. Introduction Basic landing statistics constitute one type of fishery-dependent information to evaluate the status of exploited fishery resources. Effort and catch data can be combined into indices of stock abundance, based on the Catch per Unit of Effort (CPUE). CPUE (or C/f), also called fishing success, is defined as "the catch of fish, in numbers or weight, taken by a defined unit of fishing effort". And the fishing effort is defined as "the total fishing gear in use for a specified period of time" (Ricker, 1975). Some authors also include the human effort (number of fishermen) into the total fishing effort. When different kinds of fishing are conducted on the same stock, the effort and catch taken by each is tabulated separately. When one gear is predominant over the others in a fishery, the effort of all other gears may be scaled to terms of the dominant gear by dividing their gross catch by the catch/effort of the dominant gear. When a single homogeneous population is being fished, and when effort is proportional to the instantaneous rate of fishing mortality (F), it is well established that CPUE is proportional to the mean stock present during the time fishing takes place. However, for many kinds of fishing, the stock in different subareas is not homogeneous (not equally vulnerable to fishing) and will tend to vary approximately as stock density or fish present per unit area. An overall CPUE proportional to stock size can then be obtained by adding the CPUE values for individual subareas, weighting each as the size of its subarea (Ricker, 1975). Moreover, active gears and light attraction tend to concentrate (certain) fish to make them more vulnerable to be caught by the fishing gear in question. Comparison of CPUEs for different areas, even for an identical fishing gear, must therefore be handled with caution. The CPUE of passive sampling gears (e.g. gill nets) should theoretically be directly proportional to the stock abundance, but many other variables also influence fishing efficiency (e.g. physical and chemical variables like season, water temperature, dissolved oxygen, turbidity, currents, habitat type, etc.). The most important ones are water T° and turbidity: generally, as water T° declines or turbidity increases, the CPUE declines. As fishing efficiency with passive gears is a function of fish movement, changes in fish behaviour result in a great degree of variability in CPUE among species and even among intra-species year classes (Hubert, 1983). Absolute comparison of CPUEs for different areas might thus lead to wrong conclusions about relative stock abundance, as fish stocks for different areas are not homogenous. Moreover, in Lake Tanganyika, the two real pelagic fish species demonstrate migratory behaviour (schooling species) and live in an apparent prey-predator relationship. The clupeid fishery is also very dependent on the incoming age group (new recruits) each year, which are not yet caught with the pelagic gears in use. Relative abundance of the species in question is also variable and subject to quick changes. GCP/RAF/271/FIN-TD/80 (En) 1 Given the above limitations of CPUE analysis (fishery-dependent information), the need for fishery-independent information through vessel sampling programs is obvious. LTR is therefore executing absolute fish population estimates through direct stock assessment (instantaneous or snapshot picture of the stock compared to periodical averages in CPUE analysis) of the fish stocks of Lake Tanganyika. This is done through regular (during different seasons) hydroacoustic cruises with the R/V Tanganyika Explorer. The most recent one was executed in November 1997 and the last one is scheduled in February 1998. Hydroacoustics has a number of advantages over other assessment techniques, as well as several limitations (Thorne, 1983). Advantages include independence from fishery catch statistics (allows application to unexploited or poorly exploited stocks, no long lag times), favourable time scale (can be applied prior to harvest), relatively low operational costs, low variance and potential for absolute population estimation. Disadvantages include poor species discrimination, little or no sampling capability near bottom and surface, relatively high complexity, high initial investment, potential bias associated with target strength and calibration (use of a split beam sonar can solve this problem) and lack of biological samples (unless complementary sampling is done). During acoustic cruises with the R/V Tanganyika Explorer simultaneous biological sampling is indeed carried out. Different authors however recently suggested that trawl sampling may not accurately reflect the distribution and abundance of many species (Fox & Starr, 1996). In the next chapters, the reports deals with: Þ frame surveys (FS), especially the simultaneous lake-wide FS of 1995, mainly encompassing a determination of the fishing effort or the number, distribution and types of fishing vessels and fishing methods per (stratified) Lake area, Þ catch assessment surveys (CAS) or estimates of catch per area and per time interval for the different types of fishing, Þ catch per unit of effort (CPUE) analyses, based on calculations of the available effort and catch estimates (originating from FS, CAS and fish biology sampling) per fishing type, fishing area and time interval, Þ an overview of world-wide behaviour patterns of clupeids and other factors (e.g.
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