Many factors have been suggested as influencing the development of aquaculture in a positive or negative way. This section will describe a system for examining five major factors, including 15 sub-factors, in an attempt to identify those most closely related to the development of aquaculture. If successful, certain factors or sub-factors might be used as indicators of the probability that aquaculture production would increase in various countries. This might then be used as a guide in the selection of appropriate development programmes on a global, regional or country basis.
1. Environment
The factor environment, and its three sub-factors: (1) physical, (2) institutional and (3) social, obviously are important since they concern the suitability of geographical areas for aquaculture developments.
The physical environment determines whether a selected species can be grown successfully in a certain area without providing a controlled habitat to meet its environmental requirements. This sub-factor includes temperature, rainfall, insolation, water quality and quantity, and similar characteristics.
A second portion of the environmental factor is termed institutional. Under this heading are included governmental policy, planning, programmes such as training, extension services and financial assistance, and controls, any of which can have a positive or negative impact on the development of aquaculture. Political and economic stability at the national level can markedly affect investment decisions and the successes of aquaculture ventures.
A third kind of environment can be termed social. This includes traditions, customs, religious beliefs which affect fish consumption and the social acceptability of aquaculture as an individual, group or community activity. The major question here is whether individuals will perceive aquaculture as an acceptable activity with enough potential to cause them to change from some other activity to fish farming.
Another aspect of the social environment is the stage of social and political development of local communities. The availability of supplies, services, housing and amenities and the status of transportation and communication facilities, which are generally included in the term infrastructure, are also included under this heading.
2. Space
A second major factor is the availability of suitable space on land or in lakes, rivers, estuaries or protected coastal bays for aquatic farming. Land or water space must be obtainable at an acceptable cost and, for private farming, must permit private control similar to that needed for agriculture. This factor and the sub-factors (1) land and (2) water include the problems of competition among user groups for attractive areas such as residential or recreational waterfront and established agricultural lands.
3. Technology
Technology and its sub-factors: (1) culture technology and (2) product technology include the state-of-the-art for growing selected species, preparing or preserving the resulting products and delivering them to the consumers in good condition.
This factor also includes the local availability of adequate information concerning culture and product technology. Information dissemination, training and extension service activities are usually needed to provide a sound technological basis for the development of aquaculture.
4. Production
This factor which concerns the application of technology and its four sub-factors: (1) planning and management, (2) inputs, (3) operations and (4) costs, cover all of the activities directly related to growing the selected species. The sub-factor planning and management includes development of the initial concept, species and site selection, capital formation, design and construction of the farm and business management of the operation. This sub-factor includes the availability of personnel with technical and business management skills or training needs in this area.
The second sub-factor, inputs includes the availability of seed, feed, water, energy and various materials and supplies at acceptable costs. This also includes the logistics of providing the needed inputs for the farm.
The third sub-factor, operations, includes all of the day to day activities needed to grow fish, molluscs, crustaceans or aquatic plants and to harvest the products and to prepare them for delivery to processors or distributors. Trained personnel is the most important requirement for a successful farm. This must include individuals with technical skills in aquaculture, foremen, in the case of large projects, and trained labourers.
The final sub-factor, costs, is considered separately to emphasize the importance of production costs in the development of aquaculture. Fish farms which incur high costs because of location, culture systems or operational inefficiency will be uneconomical.
5. Marketing
The factor marketing including its four sub-factors: (1) planning and management, (2) demand, (3) operations and (4) revenues covers processing, preservation, and packaging of aquacultural products, transportation to population centres and sale to distributors, wholesalers, retailers or consumers.
The first sub-category, planning and management, includes the selection of product form, processing or preservation methods and marketing strategy. It also covers the business management of the processing/marketing functions including scheduling the harvesting of fish farms to provide continuity of supply and minimizing seasonal overproduction. Individuals with skills in product technology, marketing, and business management are required for this activity.
Demand, income and price considerations are the major incentives for selecting certain species for production. Both are affected by the availability of the same or similar products from capture fisheries. As the cost of commercial fishing increases and wild stocks become fully utilized, aquaculture generally becomes more competitive.
The third sub-factor operations includes all of the day to day activities needed to process, preserve and package the fish, molluscs, crustaceans or marine plants produced in aquatic farms and to transport them to selected levels of the marketing chain. Personnel trained in product technology are needed to operate processing plants following procedures which will maintain the inherently high quality of farmed products. In the case of molluscs grown in contaminated water, operation of a depuration plant or a system of holding the live molluscs for a short period in clean water will be needed to protect consumers of raw or partially cooked products.
This sub-factor also may include transportation of the raw products from the farms to processing plants and delivery and sale of the finished product to various buyers using procedures which will prevent deterioration of the product. Individuals trained in quality control and marketing are required for this activity.
The final sub-factor revenue together with production costs determine the profitability of the fish farm. Logical marketing strategies and market development can increase revenues. High perceived revenues will encourage expansion of aquaculture.
All of the sub-factors except physical environment represent conditions which could be modified to a greater or lesser degree by man's activities. Even the physical environment would technically prohibit aquaculture only in extremely unfavourable areas. However, even moderately unfavourable physical environments could make aquaculture uneconomical since expensive controlled habitats might be needed to provide the environmental conditions suitable for growing the selected species.
The factors and sub-factors selected for this study are listed in Table 6.1.
Several individuals with direct knowledge of the status of aquaculture in certain countries were asked to rate the 15 sub-factors described above in relation to the way in which these factors may affect the development of aquaculture in those countries. The rating scale ranged from +5 to -5 with positive numbers indicating conditions favourable or encouraging to aquaculture development and negative numbers indicating unfavourable or discouraging conditions. A rating of zero indicated a neutral condition; ratings of +5 and -5 indicated very favourable and very unfavourable conditions respectively. These ratings for various countries are shown in Table 6.2. (The country's identity is “coded” in these tables to emphasize the preliminary nature of this analysis.)
Where information was available, separate ratings were made for the effect of each sub-factor on the development of aquaculture of various species or commodity groups in a country. However, such information was available only for a few species in a few countries therefore this level of detail was excluded from Table 6.2. An example of analysis by species is presented below. (Table 6.5)
Ratings for sub-factors in Table 6.2 were averaged by columns to provide mean regional ratings. Sub-factor ratings were also averaged by rows to provide mean country ratings and these were averaged to provide mean regional ratings. Variances were computed for sub-factor ratings as a guide for selection of sub-factors for further analysis.
Next, the regional ratings were listed in Table 6.3 and means and variance were computed. This table also includes regional means for the three measures of aquaculture development (annual increase in production in percent and grams per capita). Correlation factors were then computed to examine the relation between the three measures of aquaculture development and the various sub- factors on a global basis.
It was not possible during this study to obtain expert ratings of sub-factors for each country but an example of such an analysis, including ten Asian countries is shown in Table 6.4.
Similarly, an example of analysis of the rate of development of one selected species, oysters, in various “coded” countries and ratings for sub-factors is shown in Table 6.5.
1. Analysis of sub-factors on a global basis
Analysis of the global values for the ratings of sub-factors in Table 6.3 indicated considerable range of values among regions and among sub-factors. Mean world values ranged from 1.74 for production cost to 2.99 for physical environment.
Likewise variances of world values were higher for some sub-factors indicating greater variability among the regional ratings. Higher values were found for the sub-factors: Institutional Environment, Social Environment, Culture Technology, Product Technology, Production Management and Marketing Management. These are the productive sub-factors for further analysis.
| FACTOR | SUB-FACTOR | COMMENTS |
|---|---|---|
| ENVIRONMENT | PHYSICAL | Suitability of land and water (including quality and quantity) in relation to require- ments of aquaculture species |
INSTITUTIONAL | Government policy, planning, programmes (such as training, extension services and financial assistance) and controls, legal requirements, political/economical stability | |
SOCIAL | Infrastructure, stage of political develop- ment, traditions, life style, education of level | |
| SPACE | LAND | Availability of space for aquaculture at acceptable cost |
WATER | Availability of space in lakes, bays, coastal zone for aquaculture at acceptable cost | |
| TECHNOLOGY | CULTURE METHODOLOGY | State-of-the-art for growing selected species and local availability of methodo- logy |
PRODUCT TECHNOLOGY | State-of-the-art of handling, preservation, processing, packaging, storage, distribution and local availability of methodology | |
| PRODUCTION | PLANNING/MANAGEMENT | Business decisions re site selection, plant design, culture system, operations, capital formation and business management |
INPUTS | Availability of seed, feedwater, utilities and materials at acceptable costs | |
OPERATIONS | Management, labour, and farm operations needed to grow selected species to marketable size | |
COSTS | Fixed and operational costs in relation to revenues | |
| MARKETING | PLANNING/MANAGEMENT | Decisions re product form, processing methods, marketing strategy and business management |
DEMAND | Domestic and export demand and prices | |
OPERATIONS | Processing, preserving and packaging the products, distribution and quality control | |
REVENUE | Market development, sale price in relation to production and marketing costs |
| ENVIR PHY | ENVIR INST | ENVIR SOC | SPACE LAND | SPACE WATER | TECH CULT | TECH PROD | PROD MANG | PROD INPUT | PROD OPER | PROD COST | MARK MANG | MARK DEMAND | MARK OPER | MARK REV | MEAN | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| AFRICAN | ||||||||||||||||
| COUNTRY: | ||||||||||||||||
| AFA | 3 | 1 | 3 | 3 | 3 | 3 | 1 | 3 | 1 | 3 | 1 | 3 | 1 | 3 | 2.29 | |
| AFB | 3 | 1 | 3 | 3 | 3 | 1 | -1 | 3 | -1 | 3 | 3 | 3 | 3 | 3 | 2.14 | |
| AFC | 1 | 1 | -1 | 3 | 3 | 1 | 1 | 3 | 4 | 3 | 3 | 3 | 1 | 3 | 2.07 | |
| AFD | 3 | 2 | 3 | 2 | 4 | 1 | 2 | 2 | 1 | 0 | 2 | 2 | 2 | 2 | 2 | 2.00 |
| AFE | 4 | 3 | 4 | 4 | 3 | 1 | 2 | 3 | 1 | -4 | 3 | -1 | 3 | -1 | 1 | 1.73 |
| AFF | 1 | 1 | 1 | -1 | 3 | 3 | 1 | 3 | 1 | 3 | 1 | 2 | 1 | 2 | 1.57 | |
| AFG | 3 | 1 | -3 | 1 | 1 | 1 | 1 | 2 | 1 | 2 | 3 | 3 | 1 | 3 | 1.43 | |
| AFH | 3 | 1 | -1 | 1 | 3 | 1 | -1 | 2 | -1 | 2 | 3 | 2 | 3 | 2 | 1.43 | |
| AFI | 2 | -1 | 0 | 3 | 4 | 0 | 0 | -2 | -1 | 1 | 2 | 2 | 4 | 2 | 4 | 1.33 |
| AFJ | 1 | -3 | 3 | -1 | 3 | 3 | 1 | 2 | 1 | 2 | 1 | 2 | 1 | 1 | 1.21 | |
| AFK | 3 | -1 | -1 | 1 | 1 | 1 | -1 | 2 | -1 | 2 | 3 | 2 | 3 | 2 | 1.14 | |
| AFL | 1 | -1 | 1 | 1 | 1 | 1 | 1 | 2 | 1 | 2 | 1 | 2 | 1 | 2 | 1.14 | |
| AFM | 1 | -3 | 1 | -1 | 1 | 1 | 1 | 2 | 1 | 2 | 1 | 3 | 1 | 3 | 1.00 | |
| AFN | 1 | 0 | -3 | 3 | -1 | 1 | -1 | 3 | -1 | 3 | 1 | 3 | 1 | 3 | 0.93 | |
| AFO | 1 | -2 | -3 | 2 | -1 | 1 | 1 | 2 | 1 | 2 | 1 | 2 | 1 | 2 | 0.71 | |
| AFP | 3 | -3 | -3 | 3 | -3 | 1 | 1 | 2 | 1 | 2 | 1 | 2 | 1 | 2 | 0.71 | |
| AFQ | 3 | -1 | -1 | 3 | 1 | 1 | -3 | -1 | -3 | -1 | 2 | 3 | 2 | 3 | 0.57 | |
| AFR | -1 | -3 | 1 | -3 | -3 | -1 | 1 | 2 | 1 | 2 | 2 | 3 | 2 | 3 | 0.43 | |
| AFS | 1 | -3 | -3 | 1 | -3 | 1 | 1 | 2 | 1 | 2 | 1 | 2 | 1 | 2 | 0.43 | |
| AFT | 0 | -2 | -1 | -1 | -1 | -1 | 2 | 0 | 2 | 0 | 2 | 0 | 2 | 2 | 2 | 0.40 |
| AFU | -1 | -1 | -3 | -1 | 1 | 1 | -1 | 3 | -1 | 3 | -1 | 3 | 1 | 2 | 0.36 | |
| AFV | 1 | -3 | -1 | 3 | -1 | 1 | -1 | -1 | -3 | 1 | 1 | 3 | 1 | 3 | 0.29 | |
| AFW | -3 | -3 | 1 | -1 | -1 | 1 | 1 | 2 | 1 | 2 | -1 | 2 | -1 | 2 | 0.14 | |
| AFX | -3 | -3 | 1 | -3 | -3 | 1 | 1 | 2 | 1 | 2 | 1 | 2 | 1 | 2 | 0.14 | |
| AFY | -1 | -3 | 1 | -1 | -1 | 1 | -3 | 2 | -3 | 2 | 1 | 2 | 1 | 2 | 0.00 | |
| AFZ | -1 | -3 | -3 | 3 | 1 | 1 | -3 | -1 | -3 | -1 | -1 | 3 | 1 | 3 | -0.29 | |
| AFRICA M. | 1.12 | -1.08 | -0.15 | 1.29 | 1.00 | 0.35 | 1.23 | 0.04 | 1.69 | -0.15 | 2.00 | 1.19 | 2.54 | 1.27 | 2.38 | 0.98 |
| VARIANCE | 1.87 | 1.88 | 2.21 | 1.88 | 2.77 | 1.98 | 0.85 | 1.56 | 1.26 | 1.81 | 1.00 | 1.24 | 0.57 | 0.94 | 0.68 | |
| ENVIR PHY | ENVIR INST | ENVIR SOC | SPACE LAND | SPACE WATER | TECH CULT | TECH PROD | PROD MANG | PROD INPUT | PROD OPER | PROD COST | MARK MANG | MARK DEMAD | MARK OPER | MARK REV | MEAN | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| ASIA & OCEANA COUNTRIES: | ||||||||||||||||
| AOA | 5 | 5 | 5 | 4 | 4 | 5 | 5 | 5 | 4 | 5 | 4 | 5 | 5 | 5 | 5 | 4.73 |
| AOB | 5 | 4 | 5 | 4 | 5 | 4 | 4 | 4 | 4 | 5 | 4 | 4 | 4 | 4 | 4.29 | |
| AOC | 3 | 4 | 5 | 2 | 4 | 5 | 4 | 4 | 3 | 4 | 2 | 4 | 5 | 4 | 3 | 3.73 |
| AOD | 4 | 3 | 4 | 4 | 4 | 4 | 3 | 3 | 3 | 4 | 3 | 3 | 4 | 3 | 4 | 3.53 |
| AOE | 4 | 4 | 5 | 4 | 4 | 3 | 2 | 3 | 2 | 2 | 2 | 3 | 4 | 2 | 4 | 3.20 |
| AOF | 5 | 3 | 4 | 3 | 3 | 3 | 1 | 3 | 3 | 2 | 2 | 3 | 4 | 2 | 4 | 3.00 |
| AOG | 4 | 4 | 4 | 3 | 2 | 4 | 4 | 2 | 0 | 2 | 3 | 3 | 2 | 2 | 3 | 2.80 |
| AOH | 5 | 2 | 4 | 3 | 3 | 2 | 1 | 1 | 2 | 1 | 2 | 2 | 4 | 1 | 4 | 2.47 |
| AOI | 2 | 4 | 0 | 2 | 2 | 2 | 3 | 2 | 2 | 1 | -2 | 2 | 4 | 2 | 0 | 1.73 |
| AOJ | 2 | 2 | 4 | 0 | 2 | 2 | 2 | -2 | -3 | 2 | 2 | 2 | 3 | 1 | 3 | 1.47 |
| AOK | -2 | 0 | 1 | -4 | -4 | 4 | 4 | 5 | 2 | 4 | 0 | 4 | 1 | 3 | 1 | 1.27 |
| AOL | 1 | 2 | 4 | 0 | 4 | -2 | 3 | -2 | -4 | -3 | -1 | 2 | 2 | 0 | -1 | 0.33 |
| MEAN | 3.17 | 3.08 | 3.75 | 1.91 | 2.67 | 3.08 | 3.00 | 2.33 | 1.50 | 2.33 | 1.83 | 3.08 | 3.50 | 2.42 | 2.83 | 2.70 |
| VARIANCE | 2.03 | 1.32 | 1.53 | 2.31 | 2.17 | 1.89 | 1.22 | 2.25 | 2.47 | 2.05 | 1.91 | 0.95 | 1.19 | 1.38 | 1.77 | |
| EUROPEAN COUNTRIES: | ||||||||||||||||
| EUA | 4 | 4 | 5 | 3 | 4 | 5 | 5 | 4 | 3 | 4 | 3 | 5 | 5 | 5 | 5 | 4.27 |
| EUB | 5 | 4 | 5 | 3 | 3 | 5 | 5 | 4 | 2 | 4 | 3 | 5 | 4 | 4 | 4 | 4.00 |
| EUC | 4 | 4 | 5 | 4 | 4 | 5 | 5 | 4 | 3 | 4 | 1 | 4 | 4 | 5 | 4 | 4.00 |
| EUD | 3 | 3 | 5 | 2 | 3 | 5 | 5 | 4 | 3 | 4 | 2 | 4 | 4 | 4 | 4 | 3.67 |
| EUE | 2 | 2 | 4 | 2 | 2 | 4 | 4 | 4 | 2 | 3 | 2 | 4 | 2 | 4 | 2 | 2.87 |
| EUF | 2 | 4 | 4 | 2 | 3 | 2 | 4 | 4 | 1 | 2 | 0 | 4 | 4 | 4 | 2 | 2.80 |
| EUG | 3 | 2 | 4 | 2 | 2 | 1 | 4 | 2 | 1 | 2 | 1 | 4 | 3 | 4 | 3 | 2.53 |
| EUH | 4 | -4 | 4 | 4 | 4 | 2 | 4 | 3 | 1 | -4 | 2 | 3 | 3 | 4 | 2 | 2.13 |
| MEAN | 3.38 | 2.38 | 4.50 | 2.75 | 3.13 | 3.63 | 4.50 | 3.63 | 2.00 | 2.38 | 1.75 | 4.13 | 3.63 | 4.25 | 3.25 | 3.28 |
| VARIANCE | 0.99 | 2.53 | 0.50 | 0.83 | 0.78 | 1.58 | 0.50 | 0.70 | 0.93 | 2.55 | 0.97 | 0.60 | 0.86 | 0.43 | 1.09 | |
| ENVIR PHY | ENVIR INST | ENVIR SOC | SPACE LAND | SPACE WATER | TECH CULT | TECH PROD | PROD MANG | PROD INPUT | PROD OPER | PROD COST | MARK MANG | MARK DEMAD | MARK OPER | MARK REV | MEAN | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| L.AMERICAN COUNTRIES: | ||||||||||||||||
| LAA | 5 | 4 | 4 | 4 | 3 | 4 | 4 | 4 | 4 | 4 | 3 | 3 | 4 | 3 | 4 | 3.80 |
| LAB | 5 | 4 | 4 | 4 | 4 | 4 | 4 | 4 | 4 | 4 | 2 | 3 | 4 | 3 | 4 | 3.80 |
| LAC | 4 | 2 | 3 | 4 | 2 | 4 | 5 | 3 | 2 | 4 | 3 | 3 | 4 | 3 | 3 | 3.27 |
| LAD | 4 | 4 | 4 | 4 | 2 | 4 | 3 | 4 | 3 | 2 | 2 | 1 | 2 | 3 | 3 | 3.00 |
| LAE | 5 | 3 | 1 | 4 | 2 | -1 | 2 | 0 | 3 | 0 | 2 | 0 | 3 | 3 | 3 | 2.00 |
| LAF | 4 | -2 | 2 | 4 | 4 | 0 | 1 | -2 | 0 | -3 | 1 | -1 | 2 | -1 | 1 | 0.67 |
| LAG | 2 | -3 | -2 | 2 | 1 | -2 | 4 | -4 | 1 | -4 | -1 | 2 | 0 | 0 | 2 | -0.13 |
| LAH | 2 | -4 | -1 | 3 | 2 | 2 | 0 | 4 | 2 | -1 | -3 | -4 | -1 | -4 | -2 | -0.33 |
| L.AMER.M. | 3.88 | 1.00 | 1.88 | 3.63 | 2.50 | 1.88 | 2.88 | 1.63 | 2.38 | 0.75 | 1.13 | 0.88 | 2.25 | 1.25 | 2.25 | 2.01 |
| VARIANCE | 1.17 | 3.20 | 2.21 | 0.70 | 1.00 | 2.37 | 1.62 | 3.00 | 1.32 | 3.03 | 1.96 | 2.32 | 1.79 | 2.49 | 1.85 | |
| N.AMERICAN COUNTRIES: | ||||||||||||||||
| NAA | 3 | 4 | 4 | 3 | 4 | 4 | 5 | 4 | 1 | 4 | 2 | 4 | 2 | 4 | 2 | 3.33 |
| NAB | 3 | 4 | 4 | 3 | 2 | 4 | 5 | 3 | 2 | 3 | 2 | 3 | 3 | 2 | 4 | 3.13 |
| N.AMER.M. | 3.00 | 4.00 | 4.00 | 3.00 | 3.00 | 4.00 | 5.00 | 3.50 | 1.50 | 3.50 | 2.00 | 3.50 | 2.50 | 3.00 | 3.00 | 3.23 |
| VARIANCE | 0.00 | 0.00 | 0.00 | 0.00 | 1.00 | 0.00 | 0.00 | 0.50 | 0.50 | 0.50 | 0.00 | 0.50 | 0.50 | 1.00 | 1.00 | |
| Regional Ratings of Sub-Factors | Rate of Development | ||||||||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Region | Envir Phy | Envir Inst | Envir Soc | Space Land | Space Water | Tech Cult | Tech Prod | Prod Mang | Prod Input | Prod Oper | Prod Cost | Mark Mang | Mark Dem | Mark Oper | Mark Rev | Mean | Annual Growth % | t/yr Growth | g/cap/yr |
| Africa | 1.12 | -1.08 | 0.15 | 1.29 | 1.00 | 0.35 | 1.23 | 0.04 | 1.69 | -0.15 | 2.00 | 1.19 | 2.54 | 1.27 | 2.38 | 0.98 | -12.97 | -2 356 | -5.01 |
| Asia | 3.17 | 3.08 | 3.75 | 1.91 | 2.67 | 3.08 | 3.00 | 2.33 | 1.50 | 2.33 | 1.83 | 3.08 | 3.50 | 2.42 | 2.83 | 2.70 | 7.64 | 319 333 | 122.77 |
| Europe | 3.38 | 2.38 | 4.50 | 2.75 | 3.13 | 3.63 | 4.50 | 3.63 | 2.00 | 2.38 | 1.75 | 4.13 | 3.63 | 4.25 | 3.25 | 3.28 | 6.85 | 64 272 | 85.73 |
| L. America | 3.88 | 1.00 | 1.88 | 3.63 | 2.50 | 1.88 | 2.88 | 1.63 | 2.38 | 0.75 | 1.13 | 0.88 | 2.25 | 1.25 | 2.25 | 2.01 | 0.60 | 395 | 1.09 |
| N. America | 3.00 | 4.00 | 4.00 | 3.00 | 3.00 | 4.00 | 5.00 | 3.50 | 1.50 | 3.50 | 2.00 | 3.50 | 2.50 | 3.00 | 3.00 | 3.23 | 7.50 | 11 439 | 45.46 |
| Mean | 2.91 | 1.88 | 2.80 | 2.52 | 2.46 | 2.59 | 3.32 | 2.23 | 1.81 | 1.76 | 1.74 | 2.56 | 2.88 | 2.44 | 2.74 | 2.44 | |||
| Variance | 0.94 | 1.77 | 1.72 | 0.82 | 0.76 | 1.33 | 1.33 | 1.32 | 0.34 | 1.30 | 0.32 | 1.28 | 0.57 | 1.13 | 0.38 | 0.86 | |||
| Correlation Factors | |||||||||||||||||||
| %/yr | 0.80 | 0.95 | 0.92 | 0.53 | 0.97 | 0.95 | 0.86 | 0.92 | -0.12 | 0.89 | -0.08 | 0.76 | 0.19 | 0.69 | 0.71 | 0.95 | |||
| Significance | 90% | 99% | 95% | - | 99% | 99% | 90% | 95% | - | 95% | - | 80% | - | 80% | 80% | 99% | |||
| t/yr | 0.20 | 0.41 | 0.41 | -0.34 | 0.26 | 0.30 | 0.01 | 0.17 | -0.44 | 0.31 | 0.16 | 0.36 | 0.69 | 0.17 | 0.28 | 0.28 | |||
| Significance | - | - | - | - | - | - | - | - | - | - | - | - | 80% | - | - | - | |||
| g/cap/yr | 0.37 | 0.39 | 0.79 | -0.56 | 0.61 | 0.69 | 0.45 | 0.62 | -0.43 | 0.66 | 0.27 | 0.64 | 0.89 | 0.66 | 0.73 | 0.69 | |||
| Significance | - | - | 90% | - | - | 80% | - | - | - | - | - | - | 95% | - | 80% | 80% | |||
| Country | Annual Growth | Factor Ratings | Analysis | |||||||
|---|---|---|---|---|---|---|---|---|---|---|
| % | tons | g/cap | Env | Space | Tech | Prod | Mark | Mean | Var | |
Bangladesh | -3.20 | -2 297 | -26 | 3.67 | 3.00 | 1.50 | 1.50 | 2.75 | 2.48 | 0.86 |
China | 8.99 | 179 806 | 1831 | 4.00 | 3.00 | 4.50 | 3.25 | 4.00 | 3.75 | 0.55 |
Cyprus | 2.38 | 1 | 2 | 2.00 | 2.00 | 2.50 | 0.75 | 2.00 | 1.85 | 0.58 |
India | 3.79 | 28.807 | 42 | 4.67 | 4.00 | 2.50 | 2.25 | 3.25 | 3.33 | 0.91 |
Indonesia | 2.12 | 3 647 | 9 | 2.67 | 1.00 | 2.00 | -0.25 | 2.25 | 1.53 | 1.05 |
Israel | -2.40 | -302 | -78 | -0.33 | -4.00 | 4.00 | 2.75 | 2.00 | 0.89 | 2.82 |
Japan | 4.45 | 21 501 | 2 7781 | 5.00 | 4.00 | 5.00 | 4.50 | 5.00 | 4.70 | 0.41 |
Nepal | 5.39 | 240 | 17 | 4.00 | 3.00 | 2.00 | 2.50 | 3.25 | 2.95 | 0.68 |
Philippines | 4.05 | 5 503 | 112 | 4.00 | 2.50 | 4.00 | 1.75 | 2.50 | 2.95 | 0.90 |
Thailand | 8.65 | 10 933 | 2321 | 3.67 | 4.00 | 3.50 | 3.25 | 3.50 | 3.58 | 0.25 |
| Mean | 3.30 | 2.25 | 3.15 | 2.22 | 3.05 | 2.80 | ||||
| Variance | 1.55 | 2.27 | 1.14 | 1.29 | 0.91 | 1.08 | ||||
| 2Correlation Factor (%) | 0.51D | 0.59C | 0.40 | 0.41 | 0.58C | 0.68B | ||||
| Correlation Factor (t) | 0.25 | 0.20 | 0.45D | 0.35 | -0.15 | 0.41 | ||||
| Correlation Factor (g/cap) | 0.43 | 0.32 | 0.58C | 0.78A | 0.77A | 0.65B | ||||
1 Biased by statistics which include shell weight of molluscs
2 Level of certainty: A = 99%; B = 95%; C = 90%; D = 80%
(Scale: -5 = very unfavourable; O = neutral; +5 = very favourable)
| Country | Env Phys | Env Inst | Env Soc | Space Water | Space Cult | Tech Prod | Tech Mang | Prod Input | Prod Oper | Prod Cost | Prod Mang | Mark Dem | Mark Oper | Mark Rev | Mark | Mean | Estimated Growth1 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| AAA | 1 | 4 | 4 | 3 | 5 | 5 | 2 | 2 | 1 | 1 | 1 | 2 | 1 | 1 | 2.36 | 1.49 | -1 |
| BBB | 5 | 4 | 4 | 4 | 4 | 4 | 4 | 4 | 4 | 2 | 3 | 4 | 3 | 4 | 3.79 | 0.67 | 4 |
| CCC | 5 | 4 | 4 | 4 | 5 | 5 | 5 | 2 | 3 | 2 | 5 | 3 | 5 | 3 | 3.93 | 1.10 | 5 |
| DDD | 3 | 3 | 3 | 4 | 3 | 1 | 2 | 3 | 1 | 4 | 1 | 2 | 1 | 2 | 2.36 | 1.04 | 1 |
| EEE | -3 | -3 | 1 | -3 | -3 | 1 | 1 | 2 | 1 | 2 | 1 | 2 | 1 | 2 | 0.57 | 2.69 | 1 |
| FFF | 1 | 1 | 1 | -1 | 3 | 3 | -1 | 3 | 1 | 3 | 1 | 2 | 1 | 2 | 1.57 | 1.12 | 0 |
| GGG | 4 | 3 | 3 | 3 | 3 | 4 | 4 | 4 | 4 | 2 | 2 | 4 | 2 | 4 | 3.29 | 0.80 | 4 |
| HHH | -1 | 3 | 4 | 0 | 5 | 5 | 2 | 2 | 1 | 2 | 3 | 4 | 3 | 3 | 2.57 | 1.68 | -3 |
| III | 4 | 4 | 3 | 2 | 5 | 5 | 4 | 3 | 4 | 3 | 1 | 2 | 1 | 2 | 3.07 | 1.28 | 1 |
| JJJ | 3 | -5 | 2 | 2 | 2 | -1 | -5 | 3 | 1 | -3 | -5 | -4 | -4 | -4 | -1.29 | 3.17 | -1 |
| Mean | 2.20 | 1.80 | 2.90 | 1.80 | 3.20 | 3.20 | 2.30 | 2.80 | 2.10 | 1.80 | 1.30 | 2.10 | 1.40 | 1.9 | |||
| Variance | 2.52 | 3.06 | 1.14 | 2.27 | 2.32 | 2.04 | 2.83 | 0.75 | 1.37 | 1.34 | 2.45 | 2.21 | 2.20 | 2.17 | |||
| Correlation with estimated growth | 0.65 | 0.33 | 0.18 | 0.48 | 0.01 | 0.20 | 0.60 | 0.45 | 0.75 | 0.26 | 0.48 | 0.39 | 0.50 | 0.50 | 0.54 | ||
| Significance | 95% | 80% | 90% | 80% | 95% | 80% | 80% | 80% | 90% |
1 Scale for estimated growth: -5 = large decrease; 0 = none; +5 = large increase
The correlation factors shown in Table 6.3 explored the relation between observed rate of growth in various regions and the regional ratings of various sub-factors. An examination of the annual increase in production expressed as percent and the sub-factor ratings indicated significant or highly significant correlation for the mean of regional sub-factor ratings and for the following sub- factors: Physical Environment, Institution Environment, Social Environment, Water Space, Culture Technology, Production Management and Production Operations. Correlations for five other sub-factors were at the 80–90 percent level of certainty.
Similar analysis based on the annual increase in production expressed in tons showed correlation for only one sub-factor, Market Demand and that was at the 80 percent level. Annual production increases which varied from 319 333 t in Asia to -2 356 t in Africa, provide a biased picture of growth largely because mollusc production is reported as whole weight including shells. This measure will have little use as an indicator of growth until correction factors are applied to reduce mollusc statistics to meat weight.
Finally, correlation factors were computed for the annual increase in production expressed as grams per capita and the ratings for each sub-factor. This analysis indicated a significant level of correlation only for the sub-factor Demand and, at the 80–90 percent level of certainty for mean regional ratings and for Social Environment, Culture Technology and Revenue.
This growth indicator which varied from 123 g per capita in Asia to -5 g in Africa has the same inherent inaccuracies as the measure, tons, since it is based on statistics which include the weight of mollusc shells which may be 75–90 percent of the total weight. Although this measure will be of limited use in its present form, it could be very useful in the future if the basis for reporting mollusc statistics is changed to weight of meats.
2. Analysis of sub-factors on a regional basis
Analysis of the mean regional values for ratings of sub-factors in Table 6.2 indicates considerable range. Mean values for the African countries ranged from -1.08 for Institutional Environment to 2.54 for Demand.
Values for Asia, including Oceania, ranged from 1.50 for Production Inputs to 3.75 for Social Environment.
Values for Europe ranged from 1.75 for Production Costs to 4.50 for Social Environment.
Values for Latin America, including the Caribbean, ranged from 0.75 for Production Operations to 3.88 for Physical Environment.
Values for North America ranged from 1.50 for Production Inputs to 5.00 for Production Technology.
Variances were higher for some sub-factors suggesting further analysis of these sub-factors. Higher variances were found for the sub-factors Institutional Environment in four regions and Social Environment in three. Sub-factors with higher variances in two regions included Physical Environment, Culture Technology, Marketing Operations, Land Space and Water Space.
1. Analytical procedure
The analysis of aquaculture development within a region in relation to ratings for various factors is described in this section. For this example mean factor ratings for ten Asian countries (Table 6.4) are compared with the annual rate of growth of aquaculture in terms of percent, tons and grams per capita.
2. Results
The correlation factors shown in Table 6.4 indicate a strong relation between the annual growth in percent and several factors. The correlation is significant for the mean of all factors and at the 80–90 percent level of certainty for Environment, Space and Marketing.
The correlation between annual increase in tons and factors was at the 80 percent level of certainty for Technology but not for the other four factors. As discussed in Section 6.3, this measure of growth suffers from inclusion of shell weight of molluscs.
On the basis of annual increase in per capita food supply, the correlation was significant for the means of factor ratings and for Production, Marketing and Technology. This measure of growth also is influenced by inclusion of shell weight of molluscs although the effects on this analysis are less drastic than for analyses using tons as a measure of annual growth.
The analysis presented in this example suffers from the lack of reliable production records and the inherent inaccuracy of summary growth indicators for countries in which production varies among species and commodity groups. Obviously application of this technique would require analysis by species or at least by commodity groups with weighting to arrive at reliable summary growth indicators. Likewise the reliability of factor and sub-factor ratings could be improved by including evaluations by several individuals with personal knowledge of each country.
Nevertheless, the high correlation between annual growth in percent and three of five factors and the mean factor rating for each country indicates the usefulness of this method. Complete analysis, based on sound statistics and ratings by several experts, will be needed for its application in the FAO planning process.
1. Analytical procedures
The analysis of aquaculture development on a regional or global level can also be based on the rate of growth in the production of various species (e.g., Tilapia nilotica, species groups (e.g., tilapias) or commodity groups (e.g., finfish). This section presents an example of an analysis by species group based on oyster production in ten countries (Table 6.5).
It was not possible during this study to obtain accurate statistics for oyster production to permit computation of the rate of growth in various countries. Therefore, the rate of increases in each country was based on a descriptive rating of -5 = large decrease; 0 = none; 5 = large increase.
Sub-factor ratings were based on an evaluation of their effect on the development of oyster farming in each country. These, of course, would differ from the country ratings shown in other tables.
2. Results
Examination of mean sub-factor ratings for the ten countries listed in Table 6.5 indicates a range from 1.30 for Marketing Management to 3.20 for Culture and Product Technology.
Examination of variances indicates the productive sub-factors for further analysis include Institutional Environment, Physical Environment and Production and Marketing Management.
Correlation factors in Table 6.5 were at the 95 percent level of certainty for Physical Environment and Production Operations and at the 80–90 percent level for six other sub-factors and for the mean country ratings.
Table 6.5 is presented only as an example of methodology, therefore, no inferences of validity should be drawn from the correlation factors. Nevertheless, application of this method could provide a better basis for understanding the factors influencing the development of aquaculture of various species and this could lead to improved forecasts.
As is apparent from the preceding discussion, difficulties arise in considering the partial effect of one factor, holding all other factors constant. Many factors tend to move together and obscure the influence on growth of an individual factor. We propose two approaches, principal component analysis and stepwise regression, which might be useful in narrowing the number of potential explanations for aquacultural growth. One cannot be assured that either approach will reduce the potential factors into a manageable set, but these approaches are the next logical step in the analysis.
Principal component analysis assists in determining whether there are common characteristics among sets of factors which might allow elimination of certain factors. For example, there are four individual factors (i.e., planning, inputs, operations, costs) under the heading “Production” in Table 6.2. Using principal component analysis, it might happen that one factor (say costs) explained 90 percent of the variation in all four factors. If this were the case, it might be useful to drop the other three factors and use only expert opinion on costs as a factor explaining growth. The analysis is readily used and available in most statistical software packages (e.g., SPSS, SAS). We recommend as a first step trying principal component analysis to reduce the potential factors in major headings in Table 6.2. If this is successful, then one might proceed to use the remaining factors to predict growth in a multiple regression framework.
Another potentially useful approach is stepwise regression analysis (or other forms of pre-test regression analysis). In this approach, aquacultural production or growth would be related to the various factors in a sequential fashion, with the sequence being directly related to the explanatory power of the factor. The procedure allows one to observe the partial effect of a factor while at the same time considering only those factors for which the data suggests a relationship. It is conceivable that after considering four or five of the factors with large explanatory power, the remaining factors do not add much to the explanation of production or growth. Again, stepwise regression is available in most statistical software packages. (See Marriott, 1974 and Harman, 1967.)
The methodology explored in this section was to dissect the total effects of man and nature into small components for microscopic analysis. Starting with the hypothesis that some components are more important than others, an attempt was made to identify those with significant effects on a country, regional or global basis.
The factors and sub-factors examined in this study indeed appeared to be related, to a greater or lesser extent with aquaculture development. The relation was clearest at the global level where the sum of country and regional observations were considered. However, at regional, country and even at species level the same factors appeared to be correlated with the success of aquaculture.
All of the five factors used in this study, Environment, Space, Technology, Production and Marketing Management and Marketing were related to the development of aquaculture. The following sub-factors were most closely related on the basis of correlation factors:
| Physical Environment | |
| Institutional Environment | |
| Social Environment | |
| Water Space | |
| Culture Technology | |
| Production Management | |
| Production Operations |
The application of this method in the project planning process would include the following steps:
