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A method of monitoring fishery status
Fisheries Research, 11 ( 1991 ) 171-175
171
Elsevier Science Publishers B.V., Amsterdam
A method of monitoring fishery status Moses O. Okpanefe Nigerian Institute for Oceanographyand Marine Research, P.M.B. 12729, Lagos, Nigeria (Accepted for publication 19 September 1990)
ABSTRACT Okpanefe, M.O., 1991. A method of monitoring fishery status. Fish. Res., 11: 171-175. Basic common problems encountered in the management of a fishery in developing countries are lack of expertise and of adequate data. Useful advice on the management of a given fishery is often stated in such complex scientific language that the fishery manager, who is usually not a scientist, finds it difficult to understand and adopt. This paper develops a simple method for better understanding of fishery status and introduces a simple device which signals to the manager the effect of exploitation on the fish resource. The concept is demonstrated by application to the Nigeria croaker (Pseu-
dotolithus spp. ) fishery. The findings confirm the concern in official circles that possibly the fishery was over exploited, and indicate that there should be no further increase in effort if the fishery is to be saved from collapse.
INTRODUCTION
The tremendous increase in demand for fish and fishery products throughout the world has brought the desire for greater fishing effort. Consequently, fishery managers are increasingly faced with problems of managing national fisheries resources. These problems arise from lack of expertise and equipment and also because scientific results often are expressed in language difficult to understand. Traditionally fish stock assessments are made by the application of complex, multivariable models based on biological considerations, such as those of Beverton and Holt ( 1975 ), Schaefer ( 1954, 1957 ), Gulland (1969), Chikuni (1976), Pauly (1980) and Sparre (1985). Other models based on economic considerations include those of Crutchfield and Zellner (1963) and Christy and Scott ( 1965 ). Some very simple variables, which tend to be ignored, may be more useful than they are generally thought to be. One such parameter is average fish size. A simple statistical approach to the problem of fishery management based on the average size of fish landed, as distinct from both biological and economic considerations, is presented here. 0165-7836/91/$03.50
© 1991 - - Elsevier Science Publishers B.V.
172
M.O. OKPANEFE
MODEL CONCEPT
The hypothesis on which the concept is developed is that in any fishery, the size of fish landed is dependent on the mesh size of the gear used and the amount of effort applied. If the stock is fished with gear of the same mesh size, then variations in the size of fish landed are explained by changes in effort. Thus in a virgin fish stock where little effort is applied, large fish will tend to be landed. As the fishing effort increases, not only will the stock be depleted, but smaller and smaller fish will begin to dominate the landings, i.e. the average size of fish will decrease as the stock changes from an under-exploited to a fully and eventually an over-exploited one. This should signal to the fishery manager the necessity to initiate policies aimed at saving the fishery from early collapse. METHODOLOGY
The implementation of the model requires that a baseline population mean together with upper and lower limits be established from length-frequency data of several years. The limits represent 5% confidence levels attached to the mean. A control chart plotting the mean and limits against time is then set up. Sample means computed from annual data are then plotted and the trend observed. Provided the fishery is not concentrated on juveniles, the status of the fishery can be monitored at any time by comparing sample means with baseline population mean.
Interpretation of chart ( 1 ) It is expected that not more than 5 out of 100 sample means should lie outside the limits. Where this condition fails, further investigation is essential. (2) Where all sample means lie within the limits, a continuous downward trend indicates a depleting resource whereas an upward trend suggests recovery of the fishery. ( 3 ) A fluctuating trend within the limits represents a case of random variation, or a situation of relative equilibrium in a stable stock. The advantage of this approach to understanding and monitoring the fishery over approaches invoking the biological concept of maximum sustainable yield is that there is no need to determine the so-called maximum yield. In any case there is no assurance that a maximum yield may occur, or when it will occur in a given fishery. In a similar manner, the economic considerations of effort and value of catch suffer from the effect of fluctuating prices of fish. This approach is simple and of practical application. Neither expertise nor
FISHERY MONITORING
173
sophisticated equipment is essential to both understanding and utilizing the data. The Nigerian trawl fishery is here used to demonstrate the application of this model. NIGERIAN FISHERY
The Nigerian fishery consists of artisanal, industrial and fish-farming sectors. The artisanal sector involves numerous local fishermen fishing in freshwater rivers and lakes as well as in brackish water. The industrial fishery, on the other hand, involves trawling for a variety of species in coastal waters. Fish culture is conducted on a small scale in earth ponds. Okpanefe ( 1982 ) estimated the contribution of the various sectors to total fish production as 95% artisanal, 4% industrial and 1% fish farming. The two dominant fish species of the industrial fishery, the croakers Pseudotolithus senegalensis and Pseudotolithus typus, contributed over 40% of the trawl landing in the same year. P. senegalensis, the more important of the croakers, is used in this presentation. In the years 1971-1979, big croakers were c o m m o n in the fish markets. By 1980, the situation had started changing with the appearance of small croakers. In 1981, a statistical sampling scheme was initiated as part of monitoring the industrial fishery and this has continued to date. From the 1971-1979 length-frequency data (Statistics and Economics Division of the Institute ( N I O M R ) ) , population mean and standard deviation for P. senegalensis were measured as 30.20 cm and 7.42 cm respectively. The upper and lower limits based on 5% level of significance and sample size of four boxes of fish were 33.88 cm and 26.52 cm respectively. With this information, the control chart (Fig. 1 ) was set up. For the monitoring exercise, annual mean lengths were calculated, and the results plotted in the chart were revealing. From the years before 1981 and just before 1983, the trawlers were landing fish of above the average population size. This was the period of big croakers in the market. But from 1983 to 1986, the reverse condition occurred and the mean size of fish in the catch persistently fell below the population mean baseline. The fishery thus became a recruitment fishery with the catching of many small croakers below the population average size. The question to be addressed was whether the result obtained was due to increased fishing effort or to changes in mesh size of the gear used. The total catch per unit effort was computed (Table 1 ) and indicated a depleting fish resource. However, the multi-species, multi-gear nature of the fishery rendered the use of these data almost valueless. Mesh size was investigated. The 1971 Sea Fisheries Decree (official gazette No. 39, Vol. 59, 24 August 1972) established 44 m m cod-end as the minim u m mesh size for shrimping and 76 m m cod-end for fishing. From the beginning the fishermen did not comply with the 76 m m regulation; rather, cod-
174
M.O.OKPANEFE
35
Upper l i m i t , 33.88cm
30-u
I•1
Population, i
I
I
I
mean
30.20cm
e@ ._J @ c~ 0
Lower l i m i t , 26.52cm
25-
Fig. 1. Mean statistical quality control chart for monitoring fish size (croaker, Pseudotolithus senegalensis) in Nigerian industrial fishery. X, annual mean length of fish landed (cm). Population mean and 5% confidence limits are calculated from 197 l-1979 records. TABLE 1 Trends in Nigerian trawl fisheries data Year
Annual landing, all species (tonnes)
No. of vessels
Annual catch per vessel (tonnes)
1981 1982 1983 1984 1985 1986
12435.00 15051.71 12145.34 14850.10 15723.14 20507.72
45 52 81 94 109 132
276.33 289.46 149.94 157.98 144.25 155.36
FISHERYMONITORING
175
ends of 4 0 - 4 6 m m were used and this practice has continued to date. The declining size of croakers over the years therefore could not be attributed to changes in mesh size. On the contrary, the analysis showed that increased effort has resulted not only in a declining catch per unit effort but also in a decreasing size of fish caught. It was therefore recommended that considerable restraint be exercised in further increasing effort, if the trawl fishery was not to collapse in the very near future. Apparently this earlier advice was not heeded and so by 1989 the Trawler Owners Association of Nigeria called on the Federal Government to ban trawling for a period of time to allow the fishery to recover.
REFERENCES Beverton, R.J.H. and Holt, S.J., 1957. On the Dynamics of Exploited Fish Populations. Fish. Invest. Minist. Agric. Fish. (GB) Ser. II Salmon Freshwater Fish., 19:533 pp. Chikuni, S., 1976. Problems in monitoring abundance in the multi-species and multi-gear ground fish fisheries in the Bering Sea. FAO Fish. Techn. Pap., No. 155, 23-36. Christy, F. and Scott, A.D., 1965. The Commonwealth of Ocean Fisheries. Johns Hopkins University, Baltimore, MD. Crutchfield, J.A. and Zellner, A., 1963. Economic aspects of the Pacific halibut fishery. Fish. Ind. Res., 1( 1). Gulland, J.A., 1969. Manual of Methods for Fish Stock Assessment. FAO Man. Fish. Sci. No. 4:154 pp. Okpanefe, M.O., 1982. Length/frequency composition of major Nigerian marine fishes by number. Niger. Inst. Oceanogr. Mar. Res. Ann. Rep. 1982, 36. Pauly, D., 1980. A selection of simple methods for the assessment of tropical fish stock. FAO Fish. Circ. No. 72 (FIRM/C729): 54 pp. Schaefer, M.B., 1954. Some aspects of the dynamics of populations important to the management of commercial marine fisheries. Bull. Inter-Am. Trop. Tuna Commn., 1(2): 27-56. Schaefer, M.B., 1957. A study of the dynamics of the fishery for yellow fin tuna in the eastern tropical Pacific Ocean. Bull. Inter.-Am. Trop. Tuna Commn, 2(6): 274-285. Sparre, P., 1985. Introduction to tropical fish stock assessment. FAO/DANIDA PROJECT GCP/ INT392/DEN., 338 pp. o
171
Elsevier Science Publishers B.V., Amsterdam
A method of monitoring fishery status Moses O. Okpanefe Nigerian Institute for Oceanographyand Marine Research, P.M.B. 12729, Lagos, Nigeria (Accepted for publication 19 September 1990)
ABSTRACT Okpanefe, M.O., 1991. A method of monitoring fishery status. Fish. Res., 11: 171-175. Basic common problems encountered in the management of a fishery in developing countries are lack of expertise and of adequate data. Useful advice on the management of a given fishery is often stated in such complex scientific language that the fishery manager, who is usually not a scientist, finds it difficult to understand and adopt. This paper develops a simple method for better understanding of fishery status and introduces a simple device which signals to the manager the effect of exploitation on the fish resource. The concept is demonstrated by application to the Nigeria croaker (Pseu-
dotolithus spp. ) fishery. The findings confirm the concern in official circles that possibly the fishery was over exploited, and indicate that there should be no further increase in effort if the fishery is to be saved from collapse.
INTRODUCTION
The tremendous increase in demand for fish and fishery products throughout the world has brought the desire for greater fishing effort. Consequently, fishery managers are increasingly faced with problems of managing national fisheries resources. These problems arise from lack of expertise and equipment and also because scientific results often are expressed in language difficult to understand. Traditionally fish stock assessments are made by the application of complex, multivariable models based on biological considerations, such as those of Beverton and Holt ( 1975 ), Schaefer ( 1954, 1957 ), Gulland (1969), Chikuni (1976), Pauly (1980) and Sparre (1985). Other models based on economic considerations include those of Crutchfield and Zellner (1963) and Christy and Scott ( 1965 ). Some very simple variables, which tend to be ignored, may be more useful than they are generally thought to be. One such parameter is average fish size. A simple statistical approach to the problem of fishery management based on the average size of fish landed, as distinct from both biological and economic considerations, is presented here. 0165-7836/91/$03.50
© 1991 - - Elsevier Science Publishers B.V.
172
M.O. OKPANEFE
MODEL CONCEPT
The hypothesis on which the concept is developed is that in any fishery, the size of fish landed is dependent on the mesh size of the gear used and the amount of effort applied. If the stock is fished with gear of the same mesh size, then variations in the size of fish landed are explained by changes in effort. Thus in a virgin fish stock where little effort is applied, large fish will tend to be landed. As the fishing effort increases, not only will the stock be depleted, but smaller and smaller fish will begin to dominate the landings, i.e. the average size of fish will decrease as the stock changes from an under-exploited to a fully and eventually an over-exploited one. This should signal to the fishery manager the necessity to initiate policies aimed at saving the fishery from early collapse. METHODOLOGY
The implementation of the model requires that a baseline population mean together with upper and lower limits be established from length-frequency data of several years. The limits represent 5% confidence levels attached to the mean. A control chart plotting the mean and limits against time is then set up. Sample means computed from annual data are then plotted and the trend observed. Provided the fishery is not concentrated on juveniles, the status of the fishery can be monitored at any time by comparing sample means with baseline population mean.
Interpretation of chart ( 1 ) It is expected that not more than 5 out of 100 sample means should lie outside the limits. Where this condition fails, further investigation is essential. (2) Where all sample means lie within the limits, a continuous downward trend indicates a depleting resource whereas an upward trend suggests recovery of the fishery. ( 3 ) A fluctuating trend within the limits represents a case of random variation, or a situation of relative equilibrium in a stable stock. The advantage of this approach to understanding and monitoring the fishery over approaches invoking the biological concept of maximum sustainable yield is that there is no need to determine the so-called maximum yield. In any case there is no assurance that a maximum yield may occur, or when it will occur in a given fishery. In a similar manner, the economic considerations of effort and value of catch suffer from the effect of fluctuating prices of fish. This approach is simple and of practical application. Neither expertise nor
FISHERY MONITORING
173
sophisticated equipment is essential to both understanding and utilizing the data. The Nigerian trawl fishery is here used to demonstrate the application of this model. NIGERIAN FISHERY
The Nigerian fishery consists of artisanal, industrial and fish-farming sectors. The artisanal sector involves numerous local fishermen fishing in freshwater rivers and lakes as well as in brackish water. The industrial fishery, on the other hand, involves trawling for a variety of species in coastal waters. Fish culture is conducted on a small scale in earth ponds. Okpanefe ( 1982 ) estimated the contribution of the various sectors to total fish production as 95% artisanal, 4% industrial and 1% fish farming. The two dominant fish species of the industrial fishery, the croakers Pseudotolithus senegalensis and Pseudotolithus typus, contributed over 40% of the trawl landing in the same year. P. senegalensis, the more important of the croakers, is used in this presentation. In the years 1971-1979, big croakers were c o m m o n in the fish markets. By 1980, the situation had started changing with the appearance of small croakers. In 1981, a statistical sampling scheme was initiated as part of monitoring the industrial fishery and this has continued to date. From the 1971-1979 length-frequency data (Statistics and Economics Division of the Institute ( N I O M R ) ) , population mean and standard deviation for P. senegalensis were measured as 30.20 cm and 7.42 cm respectively. The upper and lower limits based on 5% level of significance and sample size of four boxes of fish were 33.88 cm and 26.52 cm respectively. With this information, the control chart (Fig. 1 ) was set up. For the monitoring exercise, annual mean lengths were calculated, and the results plotted in the chart were revealing. From the years before 1981 and just before 1983, the trawlers were landing fish of above the average population size. This was the period of big croakers in the market. But from 1983 to 1986, the reverse condition occurred and the mean size of fish in the catch persistently fell below the population mean baseline. The fishery thus became a recruitment fishery with the catching of many small croakers below the population average size. The question to be addressed was whether the result obtained was due to increased fishing effort or to changes in mesh size of the gear used. The total catch per unit effort was computed (Table 1 ) and indicated a depleting fish resource. However, the multi-species, multi-gear nature of the fishery rendered the use of these data almost valueless. Mesh size was investigated. The 1971 Sea Fisheries Decree (official gazette No. 39, Vol. 59, 24 August 1972) established 44 m m cod-end as the minim u m mesh size for shrimping and 76 m m cod-end for fishing. From the beginning the fishermen did not comply with the 76 m m regulation; rather, cod-
174
M.O.OKPANEFE
35
Upper l i m i t , 33.88cm
30-u
I•1
Population, i
I
I
I
mean
30.20cm
e@ ._J @ c~ 0
Lower l i m i t , 26.52cm
25-
Fig. 1. Mean statistical quality control chart for monitoring fish size (croaker, Pseudotolithus senegalensis) in Nigerian industrial fishery. X, annual mean length of fish landed (cm). Population mean and 5% confidence limits are calculated from 197 l-1979 records. TABLE 1 Trends in Nigerian trawl fisheries data Year
Annual landing, all species (tonnes)
No. of vessels
Annual catch per vessel (tonnes)
1981 1982 1983 1984 1985 1986
12435.00 15051.71 12145.34 14850.10 15723.14 20507.72
45 52 81 94 109 132
276.33 289.46 149.94 157.98 144.25 155.36
FISHERYMONITORING
175
ends of 4 0 - 4 6 m m were used and this practice has continued to date. The declining size of croakers over the years therefore could not be attributed to changes in mesh size. On the contrary, the analysis showed that increased effort has resulted not only in a declining catch per unit effort but also in a decreasing size of fish caught. It was therefore recommended that considerable restraint be exercised in further increasing effort, if the trawl fishery was not to collapse in the very near future. Apparently this earlier advice was not heeded and so by 1989 the Trawler Owners Association of Nigeria called on the Federal Government to ban trawling for a period of time to allow the fishery to recover.
REFERENCES Beverton, R.J.H. and Holt, S.J., 1957. On the Dynamics of Exploited Fish Populations. Fish. Invest. Minist. Agric. Fish. (GB) Ser. II Salmon Freshwater Fish., 19:533 pp. Chikuni, S., 1976. Problems in monitoring abundance in the multi-species and multi-gear ground fish fisheries in the Bering Sea. FAO Fish. Techn. Pap., No. 155, 23-36. Christy, F. and Scott, A.D., 1965. The Commonwealth of Ocean Fisheries. Johns Hopkins University, Baltimore, MD. Crutchfield, J.A. and Zellner, A., 1963. Economic aspects of the Pacific halibut fishery. Fish. Ind. Res., 1( 1). Gulland, J.A., 1969. Manual of Methods for Fish Stock Assessment. FAO Man. Fish. Sci. No. 4:154 pp. Okpanefe, M.O., 1982. Length/frequency composition of major Nigerian marine fishes by number. Niger. Inst. Oceanogr. Mar. Res. Ann. Rep. 1982, 36. Pauly, D., 1980. A selection of simple methods for the assessment of tropical fish stock. FAO Fish. Circ. No. 72 (FIRM/C729): 54 pp. Schaefer, M.B., 1954. Some aspects of the dynamics of populations important to the management of commercial marine fisheries. Bull. Inter-Am. Trop. Tuna Commn., 1(2): 27-56. Schaefer, M.B., 1957. A study of the dynamics of the fishery for yellow fin tuna in the eastern tropical Pacific Ocean. Bull. Inter.-Am. Trop. Tuna Commn, 2(6): 274-285. Sparre, P., 1985. Introduction to tropical fish stock assessment. FAO/DANIDA PROJECT GCP/ INT392/DEN., 338 pp. o