Abstract: In this paper, the items related to fishing capacity in the Chinese marine fisheries' statistical data are described. The key items used for monitoring and controlling fishing capacity include total number of fishing vessels, total engine power and total tonnage. The methods used by Chinese fisheries scientists for standardizing fishing effort when determining fishing capacity are described. The gray system theory is proposed as an appropriate method for standardization across different size vessels and across fisheries.
China has been one of the world's top fish producing countries since 1989. In 1998, total fisheries output amounted to 39.06 million tonnes, of which the output from marine fishing was 14.98 million tonnes, 38.3 percent of the total. China's fisheries have a long history, and consist of various fishing methods in coastal waters, including trawl, purse seine, set net, longline, gill-net, etc. Furthermore, in trawling, large mid-water trawl, pair trawl, outrigger prawn trawl and beam trawl are used. Fishing enterprises consist of national and collective fishery companies, as well as joint-venture companies and private fishing units owned by individual fishermen, all of which use various types of vessels and fishing gears.
The diversity of fishing methods, numerous producers and the collapse of marine resources create difficulties in the measurement, quantification and control of fishing capacity in Chinese coastal waters. Since the late 1970s, the resources of some major economic species, such as long hair-tail fish, large yellow croaker, small yellow croaker and cutter fish, in Chinese coastal waters have fallen or collapsed. As a consequence, species with relatively low value or a low position in the food chain currently comprise the greatest proportion of total output. Given this, it is necessary to control and reduce number of fishing vessels and fishing capacity urgently. Therefore, research into the measurement and control of fishing capacity seems to be of significant in Chinese coastal waters.
In China, there are three statistic indexes currently used to indicate fishing capacity. These are the number of fishing vessel, the gross tonnage of fishing vessel and engine power. These three indexes basically represent the capacity of the Chinese coastal fishery to a certain extent and have played a role in fishery management. In addition, the number of fishing vessel and the engine power are regarded as control indexes for fishing capacity. For example, Chinese government has conducted a policy of controlling and limiting the amount of engine power since 1987.
The development of the number of fishing vessels and engine power in Chinese coastal waters from 1951 to 1997 is shown in Figures 1 and 2[149]. In 1997, China also started a 'double control' programme, aimed at controlling both the total number of fishing vessel and the amount of engine power. Furthermore, in early 1999, the Chinese government decided not to increase, but reduce the total number of fishing vessels and engine power in coastal waters.
Figure 1. Total engine power, 1951 - 1997
Figure 2. Total number of fishing vessels, 1951 - 1997
'Fishing capacity', which is a new concept in fishery management, has not had a standard definition and appropriate measuring method up until fairly recently. Holland and Sutinen (1998) considered that fishing capacity is usually thought of in terms of the ability to produce fishing effort per period. In FAO (1998), fishing capacity is defined as "[t]he ability of stock of inputs (capital) to produce output (measured as either effort or catch). Fishing capacity is the ability of a vessel or a fleet of vessels to catch fish." However, the concept of fishing capacity originates from traditional industrial economic theory, and is based on the reasonable utilization of the fishing resources under consideration given existing ecological, economic and social aspects, and given that the various inputs (including the fishery resources) are utilized in their best combination. It should be noted that the concept of fishing capacity is different from fishing effort. It is well known that fishing effort is measured as the natural characteristics of fishing vessel (such as gross tonnage and engineer power) or fishing operation (for example, fishing days and number of hauls). However, fishing capacity should be considered as a comprehensive index, presenting or indicating all factors affecting the catches or fishing effort. Fishing capacity is also a dynamic concept that will vary with different fishing gear and method, skill, fishing area, and fishery management.
The main factors affecting fishing capacity are fishing time, fishing technology and its equipment, the biomass of the fish resources, and other inputs.
Fishing time consists of maximum (potential) fishing time, optimal fishing time and actual fishing time. For the purposes of macro-management, it is suitable to adopt maximum fishing time, because maximum fishing time is a relative fixed value after the period of closed fishing season and other factors affecting fishing time under a given fishery management are deducted. Optimal fishing time is the fishing time necessary to achieve the aim of fishery management, which will change as the aims of management and fish resources change. Actual fishing time may accurately reflect the pressure on fishery resources and vary with fishing vessels and marine environment. For example, a fishing vessel that stops its fishing activity may be considered as non-fishing capacity. In China, actual fishing time is usually used in the measurement of fishing capacity.
Fishing time includes productive time and non-productive time. Productive fishing time is related to detecting fish, looking for fishing ground and harvesting fish. The allocation of fishing time depends on the fishing gears and methods used. Taking whaling as an example, the time of harvesting a whale is short, but productive fishing time is mainly involved in searching for the whale. However, in the demersal trawl fishery, most of productive fishing time is spent on trawling once main fishing grounds have been found. This is also the case for longline and squid jigging. However, the harvesting time varies greatly in purse-seine fishery,
During longlining, gillnetting, trawling and squid jigging, fishing time has a positive relationship with catch. The methods for calculating fishing time should reflect the fishing feature. For example, in a trawl fishery, the catch may closely relate to the actual fishing time (e.g. per fishing hour or per haul). If the fishing time per haul is a fixed length, the number of haul may become an index of fishing capacity. However, there are many ways to measure fishing time, such as fishing hour, number of haul, fishing days, days-at-sea and number of trip, etc. Because all of these are closely related, the most suitable index needs to be selected for measuring fishing capacity.
By analyzing the distribution of fishing time to obtain a more appropriate index representing fishing effort, it is suggested that the best way to calculate the actual fishing time in the fishing ground would be by means of a unit based on either fishing days or fishing hours. For this purpose, fishing time should be recorded on the log book or catch table in detail. For instance, this would involve specifying the time spent on searching for fish and looking for fishing grounds, the time for preparing or maintaining the fishing gear, actual fishing time and clearing up the catch, etc.
It is well known that science and technology will greatly influence fishing capacity, particularly for active fishing methods, such as trawling and purse seining. For these activities, fishing capacity varied with the improvement and progress of fishing vessel and fishing gear. As well as the increase in the industry in terms of boat numbers, gross tonnage and engine power of fishing vessel are increasing, the size of fishing gear is also expanding, and more advanced instruments are used. As a result of these changes, fishing efficiency improves and fishing capacity increases. For purse seining, the adoption of high speed fishing vessels and advanced detecting equipment, such as sonar, expands the detecting range and improves the efficiency of searching for fishing ground and thereby results in increased catch. In squid jigging, deep-sea temperature and salinity analyzer (e.g. VTS-300) and special designed sounder for squid are likely to strengthen the ability to find high yielding fishing grounds. Under-water lights (e.g. SWSY) made fishing not only feasible during the night, but also can be used in day time, resulting in higher catches. In contrast, in the passive fishing activities such as trap and longline fisheries, fishing capacity may mainly depend on the number of traps or lines, and their unit of capacity may be relatively stable.
Since fish in the fishing ground are distributed unevenly, the distribution of fishing vessels is unequal also. If the fish resources are abundant, the main factors affecting actual fishing capacity may be a function of fishing vessel, fishing gear and fishing technology. In contrast, if the resource is at a low level, the major factor may be the biomass of resources. Therefore, in a fixed period, the level of resources is one of the important factors affecting total catch. However, we should note that fishermen would transform their fishing capacity from one fishing area to another. Thus the total biomass decreased in an area, the catch of a fishing vessel would still maintain a certain level.
The variable inputs include oil, labour, ice and feed. Even if fishing time is kept constant, the level of variable inputs employed and their combination with fixed inputs may change. In a fixed fishing period, it is possible to increase catch by increasing certain variable inputs. For example, in the Chinese squid jigging fishery, in which the output from handed-jigger occupy more than 60 percent of the total catch, the number of fishermen directly influence the catch per day. In addition, some fixed capital such as refrigerator and size of storehouse also affect fishing capacity. Those fishing vessel with strong freezing and large storage facilities can support longer fishing time at sea, which can greatly affect output during the high yield period. It should be noted that while some factors come under certain restrictions, fishermen can (and do) adjust various inputs and their combination, increasing unlimited inputs. This will result in an increase in fishing capacity.
The skill of the skippers reflects the level of fishing technology, the ability to identify the best fishing ground and the level of management. These will directly or indirectly influence the catch (output) and fishing capacity.
Sea conditions in the fishing area may directly affect the available fishing time. In different fishing area, the level of biomass and management regulations are also different. However, fishing vessels move between fishing areas often, which makes fishing capacity fully utilized.
Methods of measuring capacity may be considered either 'input-based' or 'output-based'. 'Input-based' measurement, which is the traditional method, is estimated in many ways. A common practice is to select a factor positively related with fishing efficiency for the unit of fishing capacity such as labour, number of fishing vessel, quantity of fishing gear used, days-at-sea or gross engine power. But as there are so many factors, one factor could not properly reflect fishing capacity. For example, the number of fishing gear used may not be considered as a unit of measurement alone because of variations in fishing vessels, fishing gear and size. Therefore, a composite index is required. For example, in pair-trawl fisheries, an index of fishing time multiplied by engine power may be an appropriate unit for measuring fishing capacity. In gillnetting, the number of nets set per day may be used as a unit of capacity. In squid jigging fisheries, the number of sets of jigging machines and number of fishermen doing hand jigging could be considered as appropriate measurement units.
However, often several different fishing gears and fishing methods are utilized on the one fishing ground. For instance, long hairtail fish distributed over the whole East China Sea are caught by trawl, purse seine, and set nets. Consequently, the multispecies nature of the fisheries and varied factor inputs create more difficulty in measuring fishing capacity.
In the Chinese coastal fishery, the measurement of fishing capacity has not been carried out on a single fishing vessel, a single fleet or a single fishery because many factors are complicate and not easily quantified. In practice, the method adopted is based on a reference frame, using one representative fishing vessel or one fishing fleet as the standard unit of capacity. The capacity of the other fishing vessels or fleets is estimated based on a comparison with the standard vessel/fleet.
Fishing capacity is the ability of a fishing vessel to catch fish, which depends on the size, gross tonnage and engine power, and the fishing gear used. To a certain degree, fishing capacity is positively correlated with catch per unit fishing time or catch per unit effort (CPUE), so fishing capacity may be estimated by the adoption of CPUE. For a given fishing ground, resources density and fishing time, a conversion coefficient (K) can be estimated as the ratio of the CPUE of one fishing vessel to that of the standard CPUE, given by:
|
K = CPUE of a fishing vessel/Standard CPUE |
(1) |
Suppose there are three types of vessels fishing in the same fishing ground, with vessel type A being regarded as the standard fishing vessel. The conversion coefficients for type A, B and C are KA(=1), KB and KC respectively. The total fishing capacity (F) in this fishing area is:
|
F = FA + FBKB + FCKC |
(2) |
Where F is the total fishing capacity; FA, FB, and FC are nominal measure of fishing capacity (e.g. days) of type A, B and C respectively.
If various fishing methods catch the same stock in one fishing ground, it is very difficulty for us to adopt the same unit for measuring fishing capacity and calculate total capacity. We selected a representative fishing method regarding as a standard one, for instance type A, the total capacity is:
|
Total fishing capacity = fishing capacity of type A × total catch/catch of type A |
(3) |
The important step is the selection of a representative fishing method to represent the unit of capacity. If more than two fishing fleets using different fishing gears and methods catch the same stock in one fishing ground, CPUE of each fishing fleet need to be calculated first, and the differences in CPUE between the fishing fleets analyzed. If the CPUE of the two fleets are similar, either CPUE can be selected as the standard unit for measuring fishing capacity. If the CPUE of the fleets varied, there is no one fishing fleet that can be selected as the standard unit.
For example, the herring fishery in the Yellow Sea has several fishing methods, including trawling, purse seining and various set-nets. The catch from trawling dominates and makes up 50 percent of the total catch. The trawling operation covers most of area in Yellow Sea. The number of trawl nets used is quite stable and the size of trawls are identical. Ye and Huang (1980) chose 100 hauls of trawling as a unit of measuring capacity in each type of vessels, and standardized fishing capacity in the herring fishery based on the above method. In 1972, the total output of herring in the Yellow Sea reached 175 000 tonnes, and the catch from trawling per 100 hauls during January and March was 323.6 tonnes so the total fishing capacity in 1972 amount to 540 units of capacity (175 000/323.6). It should be mentioned that the total output, 175 000 tonnes, was caught by trawlers, seiners, and other types of fishing vessels.
As fishing vessel, fishing gear, fishing time and skill have influence on fishing capacity, Gu and You (1987) proposed a correcting method for bottom trawling in the East China Sea and Yellow Sea. The method takes into account the:
(a) influence of fishing vessel and fishing gear. The engine power increased from 100-250 horse power in 1960 to 250-600 hp in 1987, the fishing gear also enlarged from 560 mesh × 11.43 cm or 756 mesh × 11.43 cm up to 844 mesh × 11.43 cm or 1 200 mesh × 11.43 cm. Since 1978, the large mesh (20×40 cm) has been adopted.
(b) changing in target species and non-target species;
(c) progress in technology and skill; and
(d) length of fishing time per haul. For example, in 1960, a pair trawling vessel made 2.59 hauls per day with each trawl towed for 2.5 hours per haul on average. In 1985, the hauls per day had fallen to 1.44, but towing time per haul increased to 4.5 hours.
Gu and You (1987) derived three correcting parameters: F1 (corrected coefficient of fishing power and fishing vessel), F2 (corrected coefficient of trawling time) and F3 (corrected coefficient of fishing gear improvement), with the total corrected coefficient, F, being given by:
|
F = F1 × F2 × F3 |
(4) |
Gu and You (1987) calculated the corrected coefficient based on the data from 1960 to 1985 and estimated fishing capacity (see Figure 3), the corrected capacity is more appropriate to actual fishery.
Figure 3. Comparison of nominal and corrected capacity for bottom trawlers in the East China Sea and Yellow Sea, 1960-1984
From the above, there are many factors affecting fishing capacity which vary by fishing methods, so an aggregative weighted index of fishing capacity needs to be constructed. To establish such an index requires determining the main factors in each fishing methods and deriving appropriate weights to reflect their influence. Different weighted rates will be given to each main factor and an aggregative weighted index for fishing capacity can be derived. The paper intends to analyze and compare these factors through Grey theory, and build an aggregated weighted index of capacity.
The formula for Grey correlation coefficient L0 i (k) between maternal series and sub-series that have been standardized is:
|
|
(5) |
where 
is
the absolute value of difference between maternal series and sub-series at time
k; Dmax is the maximum
value of all differences between maternal series and sub-series; Dmin is the minimum value of all
differences between maternal series and sub-series; and l is the resolving rate, with a range of (0, 1). A value
of l = 0.5 is assumed in this paper.
The Grey correlation degree is given by:
|
|
(6) |
where R0 i is the correlation coefficient between the maternal series and sub-series; and N is the number of compared series.
For example, the data from the Shanghai fishery company during 1981 and 1985 includes the number of hauls, fishing day and catch landing of 600 hp trawler. After analyzing these data, two factors - hauls and fishing days - are identified as the main factors affecting fishing capacity. The estimated correlation coefficients R01 (correlation between fishing day and catch) and R02 (correlation between number of hauls and catch) were 0.5162 and 0.5757 respectively, which indicates that the number of hauls is more suitable for the measurement of fishing capacity.
Based on the above data, an aggregative weighted index for capacity has been established by means of Factor Analysis. The formula for the aggregative weighted index (Z) is given by:
|
Z = 0.3454 X1 + 0.50284 X2 |
(7) |
where X1 is the fishing time (days) and X2 is the number of hauls.
The measures of fishing capacity for both single and multiple fishing methods shown above can be used as a reference index for the purposes of fisheries management. However, this measure is not perfect, as it is only based on the number of fishing vessels and their natural characteristics. There is a limitation to quantifying fishing capacity because the capacity of standard fishing vessels and fishing gear themselves vary with time. In addition, if some factors which affect fishing capacity are restricted by the fisheries regulations due to conservation of fisheries, such as set limitations on the number of fishing vessels, engine power and gross tonnage, these might result in the increased use of other inputs. Therefore, it is very important for estimation and control of fishing capacity to monitor the total catch of fleets and fully analyze and understand the function of the combination of various inputs.
The level of fish resources is the most important element in the factors. The actual fishing capacity varies based on different levels of stock. For example, one large squid jigging vessel with 50 sets of jigging machines may catch about ten tonnes squids per day only during peak fishing season in the Northern Pacific. However, the same fishing vessel may have daily catch more than 90 tonnes squid in Northwest Atlantic because of abundant squid stock. In this case, the main factors affecting the real fishing capacity may be the ability to fast-freeze and process. Similarly, the trawling duration of pair trawling for file fish in the 1950s in Chinese water was about a half hour and the catch was eight to 16 tonnes. However, in the 1990s, because of the fish resources decline, it was only about two tonnes with much longer trawling time even though more advanced facilities were used, which meant greater fishing capacity.
Among the various fishing methods, measuring capacity of trawler is the most difficult because of many factors affecting the level of output. Moreover, the total capacity of a fleet may be not equal to, and often more than the simple sum of individual capacity of fishing vessels. Since modern communication technology developed, the exchange of fishery information has become much easier than before, which has improved fishing ability. The supply of fuel, freshwater and food to the fishing vessels at sea has also lengthened the available fishing time.
It is also possible that variable inputs could become the main factors determining fishing capacity. For example, adjusting the use of fuel and labour will increase the real catching power or raise fishing efficiency. The optimal levels and combination of variable inputs depends on biological, economic and regulatory conditions in the fishery. Therefore, the levels of uncontrolled inputs will change if some inputs are regulated. Thus, both the potential and the optimal capacity of fleets may change even though the size and number of vessels do not change.
Clearly, fishing capacity is a dynamic concept, which is affected by many factors. Obviously, fishing capacity need to be corrected periodically to reflect the actual ability of the fleet.
To sum up, the aims of quantification and measurement of fishing capacity are to control and reduce the pressure on fishery resources, to achieve sustainable utilization and raise economic benefit. Therefore, from a macro-management point of view, fishing capacity of fleets is estimated on the basis of the average level rather than only on the actual capacity of one vessel. To simplify the calculation, one or several main indexes should be determined from the many factors that affect output. On the other hand, in order to correctly control and limit the increase of fishing capacity, the level of stock, sea condition and other factor have to be taken into account. Furthermore, the standardized units for measuring the fishing capacity will vary between countries, with the development of harvesting technology and with changes in stock levels. Consequently, it is suggested that capacity should be measured based on the country, fishing area or region.
In order to promote the study on the fishing capacity around the world and to carry out the international action plan of fishery management, the comparative study across countries, area and regions should be organized, and corresponding fishery data and information system should be built up with the assistance of international research groups.
FAO. 1998. Report of the Technical Working Group on the Management of Fishing Capacity. La Jolla, United States, 15-18 April 1998. FAO Fisheries Report No. 586. Rome, FAO.
Holland, D. & Sutinen, J.G. 1998. Draft guidelines on fishing capacity. The technical working group on the management of fishing capacity. La Jolla, California, United States, 15-18 April 1998.
Gu, H. & You. H. 1987. An approach to adjusting the fishing effort on the trawl fishery in east China sea and Yellow sea. Marine Science, 4: pp.43-46.
Ye, C. & Huang, B. 1980. Biological mathematics of fisheries - Assessment of resources and management. Agricultural press.
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[148] Shanghai Fisheries
University, China. [149] Data for these figures were taken from the Yearbook of Chinese fishery statistics. |
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