Table 25. Frequency of occurrence of fish in gillnet sets. Figures represent number of stations where a species was caught during the sampling rounds. Total number of samples = 20
Rounds | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | Total % |
Frequency of species in samples | |||||||||
Mormyridae | |||||||||
Mormyrus rume | - | 1 | - | - | - | - | - | - | .4 |
Mormyrus macrophthalmus | - | - | - | 2 | - | 2 | - | - | 1.6 |
Mormyrops deliciosus | - | - | - | - | - | - | 1 | - | .4 |
Pollimyrus isidori | 2 | - | - | - | - | - | - | - | .8 |
Hyperopisus bebe | 2 | 2 | 1 | 2 | - | 1 | 2 | - | 4.17 |
Petrocephalus bovie | 13 | 11 | 13 | 10 | 8 | 7 | 6 | 5 | 30.4 |
Petrocephalus simus | - | 1 | - | - | - | - | - | - | 0.4 |
Gnathonemus herringtoni | 3 | - | - | - | - | 3 | 1 | 1 | 3.3 |
Gnathonemus pictus | - | 1 | 1 | 1 | - | 1 | 3 | 4 | 4.6 |
Gnathonemus senegalensis | - | - | 1 | 2 | - | - | - | - | 1.2 |
Clupidae | |||||||||
Cynothrissa mento | 23 | 13 | 19 | 17 | 17 | 25 | 15 | 10 | 57.9 |
Pellonula afzeliusi | 38 | 28 | 29 | 28 | 23 | 23 | 28 | 30 | 93.1 |
Characidae | |||||||||
Hydrocynus brevis | - | 5 | 1 | 1 | 4 | 3 | 1 | - | 6.2 |
Hydrocynus lineatus | 1 | 3 | - | 2 | 2 | 2 | 2 | - | 5.0 |
Hydrocynus forskali | - | - | 3 | 4 | 5 | 2 | - | - | 5.8 |
Alestes imberi | 2 | - | - | 1 | - | - | - | - | 1.2 |
Alestes leuciscus | 24 | 17 | 22 | 14 | 16 | 24 | 19 | 18 | 64.2 |
Alestes macrolepidotus | 15 | 14 | 15 | 10 | 13 | 15 | 13 | 11 | 44.2 |
Alestes nurse | 17 | 14 | 11 | 12 | 20 | 17 | 11 | 5 | 44.6 |
Alestes baremose | 20 | 20 | 20 | 20 | 17 | 16 | 16 | 20 | 62.1 |
Alestes dentex | 6 | 10 | 4 | 6 | 4 | 5 | 1 | 4 | 16.7 |
Citharinidae | |||||||||
Citharinus citharus | 3 | 4 | - | 1 | 1 | - | 2 | - | 4.6 |
Citharinus latus | - | - | 1 | 1 | - | - | 1 | - | 1.2 |
Paradistichodus dimidiatus | 3 | 8 | 15 | 8 | 10 | 17 | 15 | 11 | 36.2 |
Distichodus brevipinnis | 1 | - | - | - | - | - | - | - | 0.4 |
Distichodus engycephalus | 3 | 1 | - | - | 1 | 4 | 1 | 1 | 4.6 |
Distichodus rostratus | 9 | 17 | 14 | 15 | 14 | 10 | 12 | 8 | 41.2 |
Cyprinidae | |||||||||
Barbus macrops | 1 | 2 | 8 | 1 | 1 | 3 | 1 | 1 | 7.5 |
Labeo branchypoma | - | 1 | - | 1 | - | - | - | - | 0.8 |
Labeo coubie | 8 | 8 | 5 | 3 | 3 | 2 | 5 | 4 | 15.8 |
Labeo senegalensis | 3 | 3 | 2 | - | - | 3 | 1 | 1 | 5.4 |
Labeo pseudocoubie | - | - | - | - | 5 | 2 | 6 | 4 | 7.1 |
Bagridae | |||||||||
Chrysichthys auratus | 7 | - | 3 | 1 | 3 | 6 | 1 | 6 | 11.2 |
Chrysichthys walkeri | 3 | 3 | 2 | 4 | 3 | 4 | 5 | 3 | 11.2 |
Chrysichthys velifer | - | 2 | 1 | 1 | 1 | 5 | 2 | 3 | 6.2 |
Chrysichthys nigridigitatus | 7 | 5 | 2 | - | - | - | - | - | 5.8 |
Chrysichthys furcatus | - | 1 | 3 | - | 2 | 9 | 1 | 1 | 7.1 |
Auchenoglanis occidentalis | 1 | 1 | - | - | 1 | - | 2 | 2 | 2.9 |
Schilbeidae | |||||||||
Eutropius niloticus | 17 | 22 | 24 | 22 | 24 | 22 | 19 | 19 | 70.4 |
Physailia pellucida | 16 | 24 | 26 | 22 | 17 | 19 | 21 | 16 | 67.1 |
Schilbe mystus | 4 | 6 | 3 | 11 | 8 | 4 | 1 | 2 | 16.2 |
Siluranodon auritus | 1 | 1 | 1 | 2 | 1 | 2 | 4 | - | 5.0 |
Mochocidae | |||||||||
Synodontis filamentosus | - | - | 1 | - | - | - | - | - | 0.4 |
Synodontis gambiensis | 3 | 5 | 2 | 4 | 3 | 3 | 5 | 3 | 11.7 |
Synodontis courteti | - | - | - | - | 1 | - | - | - | 0.4 |
Synodontis membranaceous | 1 | 1 | 1 | 4 | 4 | - | 2 | - | 5.4 |
Synodontis schall | - | - | - | - | - | 1 | 2 | 2 | 2.1 |
Synodontis nigrita | 2 | - | - | 1 | 1 | - | - | - | 1.7 |
Synodontis sorex | 1 | 1 | 1 | 1 | - | 1 | - | 1 | 2.5 |
Polypteridae | |||||||||
Polypterus senegalensis | 1 | 1 | - | - | - | - | - | - | 0.8 |
Cichlidae | |||||||||
Chromidotilapia guntheri | - | 1 | - | - | - | 1 | 2 | - | 1.7 |
Hemichromis bimaculatus | - | - | 1 | 1 | - | 2 | 1 | 1 | 2.5 |
Hemichromis fasciatus | 1 | 2 | - | 3 | 2 | 2 | 2 | 2 | 5.8 |
Tilapia zilli | 1 | - | - | 1 | - | 1 | 1 | 3 | 2.9 |
Sarotherodon galileus | 4 | 5 | 2 | 2 | 2 | 2 | 4 | 9 | 12.5 |
Gymnarchidae | |||||||||
Gymnarchus niloticus | - | 1 | - | - | - | 1 | - | - | 0.8 |
Malapteruridae | |||||||||
Malaptarus electricus | - | - | - | - | - | - | - | 1 | 0.4 |
Centropomidae | |||||||||
Lates niloticus | 10 | 14 | 10 | 10 | 11 | 15 | 14 | 8 | 38.3 |
Tetraodontidae | |||||||||
Tetraodon fahaka | 1 | - | - | 1 | 1 | - | - | 1 | 1.7 |
Hepsetidae | |||||||||
Hepsetus odoe | - | - | 1 | - | - | - | - | - | 0.4 |
Table 26. Frequency of occurrence of individual species in experimental gillnet catches
(a) | Regularly occurring: These are those species which were present in 70 percent or more of the sets. They are: | ||
Pellonula afzeliusi | (93.3%) | ||
Eutropius niloticus | (70.4%) | ||
(b) | Frequently occurring: These are those which were present in 35 to 69 percent of the sets. They are: | ||
Physailia pellucida | (67.1%) | ||
Alestes leuciscus | (64.2%) | ||
Cynothrissa mento | (57.9%) | ||
Alestes nurse | (44.6%) | ||
A. macrolepidotus | (44.2%) | ||
Distichodus rostratus | (41.2%) | ||
Lates niloticus | (38.3%) | ||
Paradistichodus dimidiatus | (36.2%) | ||
(c) | Occasionally occurring: These are those species which were present in 10 to 34 percent of the sets. These are: | ||
Petrocephalus bovei | (30.4%) | ||
Alestes dentex | (16.7%) | ||
Schilbe mystus | (16.2%) | ||
Labeo coubie | (15.8%) | ||
Sarotherodon galilaeus | (12.5%) | ||
Synodontis gambiensis | (11.7%) | ||
Chrysichthys auratus | (11.2%) | ||
C. walkeri | (11.2%) | ||
(d) | Rarely occurring: These are species which appeared in less than 10 percent of the sets. Since these are in the majority and are very many, only a few which are the more abundant of them have been listed below. | ||
Barbus macrops | ( 7.5%) | ||
Chrysichthys furcatus | ( 7.1%) | ||
Labeo pseudocoubie | ( 7.1%) | ||
Hydrocynus brevis | ( 6.2%) | ||
H. forskali | ( 5.8%) | ||
Chrysichthys nigrofasciatus | ( 5.8%) | ||
Hemichromis fasciatus | ( 5.8%) | ||
Labeo senegalensis | ( 5.4%) | ||
Synodontis membranaceous | ( 5.4%) |
Table 27. Research and development history of Volta Lake
Applied Fishery Research Activities | ||||||||||
Research Discipline | Major Findings | Recommendations | Follow-up | Remarks | ||||||
1. | Fish Stock Assessment | 1. | Fish stocks were not being overfished | 1. | The fishery could be expanded | 1. | Introduction of a more efficient net (monofilament gillnet) | 1. | Readily accepted | |
2. | Offshore stocks were being underutilized | 2. | Expand the fishery to offshore areas | 2. | Suitable boat designed to withstand offshore choppy waters | 2. | Lack of imported inputs has been hampering progress | |||
3. | Tiny clupeid comprises 23% by weight of gillnet catches. Hardly exploited | 3. | Could use 13 mm mesh to harvest until means of concentrating them (e.g. attraction to light) is deviced to permit mass harvest | 3. | None | 3. | Method time-consuming hence does not appeal to fishermen | |||
2. | Fish Catch Survey | 1. | Defines the magnitude of inputs and outputs of the fishing industry | - | - | 1. | Data used for overall development of the fishing industry | |||
3. | Socio-economic Studies | 1. | Define the socio-economic structure of the industry | 1. | Fishery should remain artisanal to extend benefit to maximum number of people | |||||
4. | Processing and Marketing | 1. | Quality of the processed processed fish leaves much to be desired. Better product developed | 1. | Design more efficient oven | 1. | Moderate effort made to extend use of the new oven | 1. | Has not made impact on the industry yet | |
2. | Fish distribution inefficient | 2. | Construct fishery complexes to serve as landing marketing centres | 2. | Construction of Kpandu-Torkor Fishery Complex | 2. | Has been operating successfully | |||
5. | Boat Construction Unit | 1. | Traditional craft fishery | 1. | Better craft should be designed | 1. | Better crafts for | 1. | Lack of imported inputs have been hampering progress | |
(a) | fishing and | |||||||||
(b) | passenger/good traffic constructed | |||||||||
2. | Carpenters trained in construction of crafts | |||||||||
6. | Fishery Development Planning | 1. | Major fishing villages need landing facilities | 1. | Construct floating jetties | 1. | Floating jetties constructed | 1. | Dismantled by squally winds | |
2. | Need central points for fish processing | 2. | Construct fish processing centres | 2. | Pilot processing centre constructed | 2. | Has been shut down because of operational problems | |||
7. | Fishing Gear Technology | 1. | Found catching ability of monofilament nylon net twice that of multifilament nylon net | 1. | Introduce new net to fishery to increase catching rate | 1. | None | 1. | No active expansion programme was undertaken but industry readily accepted new net | |
8. | Agronomy | 1. | Know-how for cultivation of drawdown and upland areas absent | 1. | Introduce techniques for farming drawdown and upland areas through operation of pilot projects | 1. | Operation of pilot projects | 1. | Perhaps the most successful extension programme | |
9. | Limnology | 1. | 79% of the total water mass suitable for fish life | 1. | May extend fishery to deeper waters | - | 1. | Problem: snagging of nets on trees in deeper waters |
Table 28. Periods during which FAO experts in fisheries, hydrology and related fields worked on the Volta Lake Research Project
FAO Experts | Starting date | Concluding date | ||||
Project Manager | June | 1967 | December | 1973 | ||
Fishing Gear Technologist | October | 1967 | February | 1971 | ||
Sociologist | October | 1967 | November | 1970 | ||
Fishery Biologist | March | 1968 | December | 1971 | ||
Fishery Limnologist | April | 1968 | October | 1970 | ||
Agronomist | June | 1968 | December | 1977 | ||
Fishery Technologist | May | 1968 | May | 1970 | ||
Masterfisherman | December | 1968 | December | 1970 | ||
Economist | March | 1969 | 1970 | |||
Wildlife Officer | December | 1969 | June | 1970 | ||
Resource Economist | September | 1970 | December | 1970 | ||
Development Officer | September | 1970 | August | 1971 | ||
Processing & Marketing Officer | July | 1971 | June | 1973 | ||
Boat Builder | October | 1971 | March | 1973 | ||
FAO Consultants | ||||||
Catch Assessment | (several times 1st assignm. 1969) | |||||
Boat Builder | 25 | November | 1970 | 30 | November | 1970 |
Boat Designer | 17 | October | 1976 | 4 | November | 1976 |
Table 29. Proposed research activities rearranged in priority order
PRE-IMPOUNDMENT PHASE
Discipline | Major objectives | ||
1. | Socio-economics | (a) | Define socio-economic structure of the population in the area to be flooded |
(b) | Make recommendations for resettlement of population | ||
2. | Epidemiology | (a) | Recommend measures needed to deal with important health hazards |
3. | Resource Economics (System Analysis) | (a) | Outline economic framework for overall development of resources |
4. | Fishery Biology (Stock Assessment) | (a) | Define status of abundance of fish populations |
(b) | Predict nutrient trend in future reservoir | ||
5. | Fishery Limnology | (a) | Determine nutrient status of river |
(b) | Predict nutrient trend in future reservoir | ||
6. | Statistical Survey (Catch Assessment) | (a) | Define input into and output from fishery |
7. | Aquatic Weeds | (a) | Identify noxious weeds |
(b) | Predict extent of weeds problem for future reservoir | ||
POST-IMPOUNDMENT PHASE | |||
1. | Fishery Biology | (a) | Define status of abundance of the stock under exploitation on continuing basis |
(b) | Make recommendations for rational harvest | ||
2. | Statistical Survey | (a) | Same as for pre-impoundment but on continuing basis |
3. | Fishery Limnologist | (a) | Complement efforts of Fishery Biologist in predicting future yields |
4. | Epidemiology | (a) | Monitor extent of spread of water borne diseases |
(b) | Implement measures for combating outbreak of disease | ||
5. | Socio-economics | (a) | Carry out socio-economic surveys in connection with implementation of various research results |
6. | Development Planning | (a) | Formulate overall development plan for lake area |
7. | Fishing Gear Technologist | (a) | Devise suitable gear for rational harvest of the stocks |
8. | Boat Designer | (a) | Design suitable boat for fishery and transportation |
9. | Boat Builder | (a) | Build suitable boat for fishery and transportation |
10. | Processing and Marketing | (a) | Devise methods for processing of better quality products |
11. | Aquatic Weeds | (a) | Mount surveillence on rate of appearance of noxious weeds |
(b) | Recommend measures for combating spreading of noxious weeds |
Table 30. Cost of equipping a fishing unit
Improved | Local | ||
1 | Canoe | ¢ 7 000.00 | ¢ 3 400.00 |
1 | 5–10 HP outboard motor | ¢ 3 000.00 | 2 paddles ¢ 100.00 |
5 | bundles fishing nets (yearly requirement) | ¢ 10 000.00 | ¢10 000.00 |
Hardlaid chord | |||
Floats | |||
Lead | |||
Twine |
Table 31. Development activities on Volta Lake
Activity | Cost (¢) | Duration of Activity | |||||
1. | Kpandu-Torkor Fishery Complex | 1. | Construction cost: | 936 457.50 | 1. | On-going since commissioning in 1976 | |
2. | Fish Processing Demonstration Programme | 2. | Annual Budget: | 10 000.00 | 2. | 1973 to date | |
3. | Kpandu-Torkor Complex Fishing School | 3. | Not Available (N.A.) | 3. | 1977 to date | ||
4. | Mobile Fishery School | 4. | Annual Budget: | 10 000.00 | 4. | N.A. | |
5. | Floating Jetties Programme | 5. | Construction cost of 4 jetties: | 27 981.00 | 5. | 1973–1977 | |
6. | Yeji Fishing Complex | 6. | Annual budget for site studies: | 100 000.00 | 6. | Yet to take off | |
7. | Net Revolving Programme | 7. | Cost of total nets ordered: | 1 020 405.04 | 7. | 1975 to date | |
8. | Boat Revolving Programme | 8. | (a) | Outboard Motors ordered: | 453 085.33 | 8. | 1975/75 to date |
(b) | Cost of construction of 58 canoes: | 184 262.64 | " " | ||||
9. | Fishery Extension Service | 9. | N.A. | 9. | 1975 to date | ||
10. | Lakeside Fishermen Cooperative Development Programme | 10. | N.A. | 10. | N.A. |
N.A. = Not available at the moment of writing
U.S.$ = ¢ 2.75
Table 32. Crop yields, irrigated versus rainfed
(V.L.R. and D.P. Report, 1979)
Crop | Irrigated kg/ha (av.) | Rainfed kg/ha (max) |
Maize (Composite IV) | 6 000 | 2 000 |
Tomatoes (Wosoinoso) | 20 000 | 1 200 |
Groundnuts (Florispan) | 2 400 | 1 600 |
Cowpeas | 1 100 | 600 |
Tobacco | 2 700 | 1 700 |
Figure 1. Volta Lake's sampling sites
Figure 2. Commercial fish catch in Volta Lake 1964–1965
Figure 3. Species composition change from 1969 to 1971. Catches with large meshed (102–203 mm) experimental gillnets (Vanderpuye, 1972) | Figure 4. Species composition change from 1969 to 1970. Catches by commercial gillnets |
Figure 5. Relative catch of the various ecogryps during the periods 1969 to 1973 in Volta Lake
by
Daniel Pauly
International Center for Living Aquatic Resources Management
MCC P.O.Box 1501
Makati, Metro Manila, Philippines
ABSTRACT |
Recently developed fish stock assessment methods are briefly presented which could be used for the management of the fish stocks of African reservoirs. These methods include length-structured versions of Virtual Population Analysis which seem particularly suited to reservoirs because (a) they do not include any equilibrium assumption; and (b) they can be used in conjunction with such highly selective gears as gillnets. |
RESUME |
On trouvera résumé ci-après des méthodes d'évaluation des stocks de poisson qui viennent d'être élaborées et qui pourraient être utilisées pour aménager les stocks dans les réservoirs africains. Ces méthodes comportent divers types d'analyses de populations virtuelles, basées sur la longueur, qui semblent particulièrement adaptées aux réservoirs, car a) elles ne présupposent aucun équilibre; et b) elles peuvent être utilisées en même temps que des engins hautement sélectifs, par exemple les filets maillants. |
Reservoirs differ in a number of features from those water bodies (lakes, marine waters) where conventional methods for the assessment of fish stocks have been commonly applied. Among these features, the lack of stability of the various fish communities following impoundment has generally prevented the meaningful application of methods built around steady-state assumptions (e.g., surplus-yield models, yield per recruit models), while the presence of flooded tree stumps in most reservoirs has generally prevented the use of sampling gears other than the ubiquitous, but highly selective gillnets. While these constraints cannot be ignored, it is apparent that advances in the assessment and management of reservoir stocks will be made only if serious attempts are made to adapt to reservoir conditions at least a part of the stock assessment methodology that is presently in use in other aquatic systems. In the following, a brief review is given of methods used for the assessment of the fish stocks of African reservoirs, emphasis is given to methods recently developed which extract a maximum of reliable information from a minimum of data.
The identification of annual rings on the scales or otoliths of African fishes has generally been achieved where it has been attempted (Matthes, 1973). In fishes with short life spans (e.g., in the clupeids Stolothrissa and Limnothrissa), the study of daily growth rings seems particularly indicated. The concept and methods are given in Panella (1971, 1974); Brothers (1980) gives an exhaustive bibliography.
Growth studies based on length-frequency data can be quite reliable when using the ELEFAN method of Pauly and David (1981); however, access to a microcomputer (at least) is required. The method allows, given length-frequency data, for the rapid estimation of the von Bertalanffy Growth Function (VBGF) L∞ and K (and their standard errors) and of terms expressing the seasonality of growth occuring in African reservoirs, where marked summer-winter differences in temperature are common.
Tagging studies also are suitable for the estimation of L∞ and K in reservoir fishes (besides allowing for the estimation of mortalities and biomass, see below); new methods for the estimation of growth parameters from length at tagging and length at recovery are given in Pauly and Ingles (1981) and Munro (1982).
Mortalities are defined in fishery biology as M (natural mortality), F (fishing mortality) and Z (total mortality) and Z = M + F. Gulland (1969) and Ricker (1975) give mathematical definitions of these parameters.
A variety of methods are available for estimating Z in fish stocks, such as:
equation relating Z and mean length of the catch,
length-converted catch curves, i.e., relationships linking the relative numbers of large (old) fish to those of the small (young) fish in the catch or in scientific samples;
methods for analysis of mark and recapture data.
Detailed description of the methods in (i) and (ii) are given in Pauly (1980); for use in reservoirs, it is important to use data from time periods during which the assumption of equilibrium condition is at least approximately met. Some of the methods also have to be adapted when the sampling gears are gillnets, i.e., the establishment of selection curves and the subsequent debiasing of data are imperative. Gulland (1969) gives methods to deal with this and also with estimation of Z using the methods in (iii). Another approach is to estimate Z from the maximum age (tmax) in years in the catch (Hoenig, 1982; Hoenig and Lawing, 1982) which can be done, e.g., using the relationship
Loge Z = 1.44 - 0.984 loge tmax | (1) |
Separating Z into its constituent parts M and F is generally quite difficult and the use of the following expression is suggested for obtaining first estimates of M from the growth parameters and mean environmental temperature of a stock:
log10M = 0.0066 - 0.279 log10 L∞ + 0.6543 log10K + 0,4634 log10T | (2) |
where T is the annual mean water temperature (in °C) of that part of the reservoir inhabited by the stock in question, K is expressed on a yearly basis and L∞ is the total length in cm (Pauly, 1980a).
Estimating the standing stock of fish in reservoirs by species or groups of species of the same ecotype is extremely useful, both to manage the stocks in practice and to reach an understanding of the working of a given ecosystem.
In reservoirs, standing stocks can be estimated from mark-recapture studies, through Virtual Population Analysis (VPA, see below), sampling, and the DeLury method. Catch in weight (Y), fishing mortality (F) and biomass (B) are related by
Y = F.B | (3) |
which offers the possibility, if F can be estimated by subtraction, using equation (1) and (2) above, to estimate biomass through
B = Y/F | (4) |
Thus, there are situations where it is possible to estimate biomass (at least roughly) without sampling more than the catch of a fishery (as is also possible using VPA, see below).
An interesting aspect of biomass estimates is that they can be used in conjunction with equations, such as (3) and (4), to construct ecosystem (trophic) models by linking the biomasses of given taxa (or group of them) through arrows expressing food consumed (Q) by a predatory species and quantified, in analogy to (3) by
Q = M.B | (5) |
where M and B apply to a prey species. Trophic models of this type (which are discussed in detail in Pauly, 1982) are relatively easy to construct, and offer a concise way of summarizing what is known of a given fishery and of the ecosystem that supports it. Moreover, such trophic models have built-in checks, for example, the amount consumed daily by the animals of a given taxon should be in the vicinity of 3–5 percent of their own weight, or that their gross food conversion efficiency (Z.B)/food consumed) should be somewhere between 0 and 20 percent (Jones, 1982). It is thus possible to infer, if such a trophic model does not balance, that either important groups have not been accounted for or that the values of some of the parameters are incorrect.
Virtual Population Analysis (VPA) and its related methods (cohort analysis, length cohort analysis; see Jones, 1981) seem not to have been applied to any reservoir stocks, and certainly not to any African stock. The principle of the method is that, in an exploited stock, the population of fish that must have been in the water to generate, over time, a given succession of catches can be reconstructed, using only the catches themselves and an estimate of M. The important features of VPA-based methods in connection with their potential use in reservoir fisheries are:
VPA does not require unselective gears, nor debiasing of catch samples for the effect of selection. Thus, catch data even from a fishery using strongly selective gears can be used;
No estimates of effort are needed;
No assumptions of equilibrium are involved.
As commonly used (e.g., in Northern Europe), VPA requires data on catch-at-age; however, various modifications have been proposed which require only catch-at-length data, along with estimates of L∞ and K of the VBGF (Jones, 1981). Recently, a version of VPA has been developed which, while still being based on catch-at-length data, performs an analysis similar to an age-based VPA, with the result that estimates of F, standing stock and recruitment can be obtained in real time, e.g., on a monthly basis (Pope et al., MS).
This method, which was developed for application of stocks of short-lived fishes, e.g., Peruvian anchoveta, could very profitably be applied in an African reservoir context, especially to the stocks of pelagic clupeids which have dynamics similar to those of the Peruvian anchovy-with quantity of river inflow replacing upwelling intensity (Marshall et al., 1982).
The author will be glad, within the framework of ICLARM's Network of Tropical Fisheries Scientists (Munro and Pauly, 1982), to assist any reader in the implementation of the methodology outlined above, as well as to provide copies of the papers (with the exception of Ricker's and Gulland's books).
Brothers, E.B., 1980 Age and growth studies on tropical fishes. In Stock assessment for tropical small-scale fisheries, edited by S.B. Saila and P.M. Roedel. Proceedings of an International Workshop held in September 19–21, 1979 at the University of Rhode Island. Kingstone, R.I., International Center for Marine Resources Development, University of Rhode Island, pp.119–36
Gulland, J.A., 1969 Manual of methods for fish stock assessment, Part 1. Fish population analysis. FAO Man.Fish.Sci., (4):154 p. Issued also in French and Spanish
Hoenig, J.M., 1982 Estimating mortality rate from the maximum observed age. ICES C.M. 1982/D:5:8 p. (mimeo)
Hoenig, J.M. and W.D. Lawing, 1982 Estimating the total mortality rate using the maximum order statistic for age. ICES C.M. 1982/D:7:13 p. (mimeo)
Jones, R., 1981 The use of length composition data in fish stock assessment (with notes on VPA and cohort analysis). FAO Fish.Circ., (734):55 p. Issued also in Spanish
Jones, R., 1982 Ecosystem, food chains and fish yields. ICLARM Conf.Proc., (9):195–230
Marshall, B.E., F.J.R. Junor and J.D. Langerman, 1982 Fisheries and fish production on the Zimbabwean side of Lake Kariba. Kariba Stud., (10):175–231
Matthes, H.H., 1973 A bibliography of African freshwater fish. Rome, FAO, 299 p.
Munro, J.L., 1982 Estimation of the parameters of the von Bertalanffy growth equation from recapture data at variable time intervals. J.Cons.CIEM, 40:199–200
Munro, J.L. and D. Pauly, 1982 The ICLARM network of tropical fishery scientists. ICLARM Neswl., 5(4):5
Panella, G., 1971 Fish otoliths: daily growth layers and periodical patterns. Science, Wash., 1137(4002): 1124–7
Panella, G., 1974 Otolith growth patterns: an aid in age determination in temperate and tropical fishes. In The ageing of fish, edited by T.B. Bagenal. Old Woking, Surrey, Unwin Brothers, Ltd., pp.28–39
Pauly, D., 1980 A selection of simple methods for the assessment of tropical fish stocks. FAO Fish.Circ., (729):54 p. Issued also in French
Pauly, D., 1980a On the interrelationships between natural mortality, growth parameters and mean environmental temperature in 175 fish stocks. J.Cons.CIEM, 39(2):175–92
Pauly, D., 1982 Notes on tropical multispecies fisheries, with a short bibliography on the food and feeding habits of tropical fish. In Report of the regional training course on fisheries stock assessment, Samutprakarn, Thailand, 1 Sept.–9 Oct. 1981. Part 2. Vol.1. Manila, South China Sea Fisheries Development and Coordinating Programme, SCS/GEN/82/41: 30–5,92–8
Pauly, D. and N. David, ELEFAN I, 1981 a BASIC program for the objective extraction of growth parameters from length-frequency data. Meeresforschung/Rep.Mar.Res., 28(4):205–11
Pauly, D. and J. Ingles, 1981 Aspects of the growth and mortality of exploited coral reef fishes. Proceedings of the Fourth International Coral Reef Symposium, Manila, edited by E. Gomez et al., vol.1:81–98
Pope, J.G., D. Pauly and N. David, ELEFAN III, n.d. a BASIC program for the detailed analysis of catch-at-length data using Virtual Population Analysis. MS
Ricker, W.E., 1975 Computation and interpretation of biological statistics of fish populations. Bull.Fish. Res.Board Can., (191):382 p.