Sustainable Management of Fisheries in Tamil Nadu  

J.S. Amarnath , A. Mouna
Department of Agricultural Economics, Tamil Nadu Agricultural University, Agricultural College and Research Institute, Madurai, India
Author    Correspondence author
International Journal of Marine Science, 2015, Vol. 5, No. 28   doi: 10.5376/ijms.2015.05.0028
Received: 15 Feb., 2015    Accepted: 28 Mar., 2015    Published: 04 May, 2015
© 2015 BioPublisher Publishing Platform
This is an open access article published under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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Amarnath and Mouna, 2015, Sustainable management of Fisheries in Tamil Nadu, International Journal of Marine Science, Vol.5, No.28 1-8 (doi: 10.5376/ijms.2015.05.0028)

Abstract

The study on sustainable management of fisheries was taken up in the Cuddalore district of Tamil Nadu with varying levels of pollution by SIPCOT industries. The cost of fish production was highest for low affected category due to less pollution intensity and the consequent high fish production in that category. The gross income and net income was highest for low affected fishermen with Rs. 468816 and Rs. 151237 respectively which showed that they were more profitable than other two categories. Fish catch was varied with pollution intensity.
 

Resource use efficiency of fish production with Cobb-Douglas production function revealed that variables of fuel cost, number of fishermen and maintenance cost were positive and significant for all categories of fishermen. The technical efficiency of affected fishermen with Data Envelopment Analysis revealed that mean technical efficiency and scale efficiency of the three categories of serious affected, medium affected and low affected fishermen was similar and was around 99 per cent. The Contingent Valuation revealed that the WTP amount was also highest for serious affected category with annual amount of Rs. 5850 and higher over medium affected category by 163.59 per cent and over low affected category by 491.18 per cent. Sustainable Rural Livelihood framework analyses showed that low affected fishermen was more sustainable followed by medium and low affected fishermen.

Keywords
Management of fisheries; Resource use efficiency; Cobb-Douglas production function; Technical efficiency; Data envelopment analysis; Contingent evaluation and Sustainable; Rural Livelihood framework

Tamil Nadu ranked fourth in marine production in India. Tamil Nadu with its 1076 km of coastline, 1.90 lakh sq.km of Exclusive Economic Zone (EEZ) and a continental shelf of about 41412 Sq km is one of the leading producers of both marine and inland fish and fish products. The marine fish potential in Tamil Nadu estimated at 7 lakh metric tonnes. The fishing population in the state is 9.15 lakh fishermen and of which, 2.60 lakh are actively engaged in fishing.
In Cuddalore district, the chemical industries are located in the SIPCOT industrial complex. There are 12 major industries covering an area of 516 acres are very close to the sea coast. These industries polluted the ground and surface water and also impacted the availability of fishes. Also, modern shrimp farms have replaced the coconut gardens and mango orchards and also affected fish production. Further, the coastal ecosystem is turned into hotspot for real estate activities with the development of farm houses like Happy Bay, Sea Breeze and Vishwamudra. In this juncture, the sustainable approach to fisheries management requires at the foremost the analyses of production efficiency and technical efficiency of fisheries production. It requires then the conservation of fisheries resources, which one would realize through the valuation of fisheries damage using market and non-market valuation methodologies. It finally requires the estimation of sustainability through approaches like Sustainable Rural Livelihood approach (SRL).
1 Methodology
In Cuddalore district, among the fishing villages affected by SIPCOT industries, six fishing villages were selected purposively to study the negative externalities. Based on the intensity of pollution, they were categorized into seriously affected, medium affected and low affected. A sample of 20 fishermen in each village was selected randomly and the sample size was 120. Production efficiency analyses were done through Cobb-Douglas production function analyses. Technical efficiency analysis was done by Data Envelopment analysis. Willingness To Pay (WTP) and Willingness To Accept Compensation (WTAC) was estimated through Contingent Valuation methodology. Sustainability evaluation was done through SRL approach (Venkatesh Salgramma, 2006).
2 Results and Discussion
2.1 Cost of fish production

The cost of fish production is furnished in Table 1. The variable cost included was fuel cost, cost of human labour and interest on working capital. It could be seen from the Table that the total variable cost was highest for low affected fishermen with Rs. 187250 and it was higher over medium affected fishermen by 102.94 per cent and over serious affected fishermen by 141.13 per cent. The variable cost of fish production was highest for low affected category which was due to the less pollution intensity and the consequent high fish production in that category. Among the components of variable cost, fuel cost accounted for a major proportion and it was 64.02 per cent for low affected fishermen; 64.01 per cent for medium affected fishermen; 57.69 per cent for serious affected fishermen. Cost of human labour formed the next category and interest on working capital formed the last category of variable cost.

 


Table 1 Cost of fish production

 


The total fixed cost also was highest for low affected fishermen with Rs. 130239 and it was higher over medium affected fishermen by 137.38 per cent and over serious affected fishermen by 167.52 per cent. The fixed cost included the depreciation and maintenance cost, insurance and interest on fixed capital. The depreciation and maintenance cost was highest for medium and low affected fishermen and it was 60.88 per cent and 59.52 per cent respectively to total of that categories. This cost was highest for these two categories because fish catch was relatively higher in them and consequent usage of boat. Insurance cost was higher in serious affected category with a proportion of 74.40 per cent because of the fear of loss in fish production due to the more presence of negative externalities in that category. Interest on fixed capital was similar in all categories and it was around 11 per cent. The total cost was also higher for low affected category with Rs. 317579 and it was higher over medium affected category by 114.77 per cent and over serious affected category by 150.92 per cent.

2.2 Gross and Net Income
The detail of gross and net income of sample fishermen is presented in Table 2. It could be seen from the Table that the gross income of low affected category was highest with Rs. 468816 and it was higher over medium affected category by 142.30 per cent and over serious affected category by 202.49 per cent. The net income also revealed the same pattern like gross income and it was highest for low affected fishermen with Rs. 151237. It was higher over medium affected fishermen by 286.67 per cent and also higher over serious affected fishermen by 716.80 per cent. Thus the gross and net income was coincided with the pollution intensity.


Table 2 Gross and Net Income of sample fishermen

2.3 Production efficiency of fish production
Cobb-Douglas production function was employed to study the relationship between the fish catch and the inputs used in the fish production for the three categories of serious, medium and low affected fishermen and the results are furnished in Table 3.


Table 3 Production function for total fish production

2.4 Serious affected fishermen
For serious affected fishermen, the catch responded significantly to the inputs such as depreciation cost, fuel cost, number of fishermen per trip and the maintenance cost. The fish catch and depreciation cost had a negative relationship with coefficient value of -0.52 which showed the seriousness of pollution that as the boat usage increased (consequent increased depreciation), it resulted in decreased fish catch. The coefficients of fuel cost, numbers of fishermen and maintenance cost were positive and significant at one per cent level with coefficient values of 0.26, 0.11 and 0.85 respectively. This was in line with the findings of Najmudeen and Sathiadhas (2007) who have shown that fish catch was positively responded to fuel cost and maintenance and repair cost along the Kerala coast by employing Cobb-Douglas production function. Also another study conducted in lower Amazon by Almedia et.al. (1997) by employing Cobb-Douglas production function showed that gross revenue per catch was positively influenced by number of fishermen, depreciation and fuel inputs. In their study, the depreciation had a positive influence because it was fishing in good water.
The ratio between MVP and MIC was also worked out for this category and the results are given in the Table 4. The input is used efficiently if the ratio between MVP and MIC was one. A ratio of more than one and less than one would indicate underutilization and over utilization respectively .It could be seen from the Table that this ratio between MVP and MIC of depreciation cost of boat, fuel cost and human labour was less than one. It indicated that the above resources were over utilized and there exists a possibility for enhancing the fish catch quantity by decreasing the respective inputs from the existing level. The ratio of MVP and MIC of maintenance cost was more than one and it indicates underutilized.


Table 4 Economic efficiency of resource use of serious affected fishermen (MVP/MIC ratio)

2.5 Medium affected fishermen
For medium affected fishermen, the catch responded significantly to the inputs. The coefficient of depreciation cost of boat, fuel cost, number of fishermen and maintenance cost were positive and significant at one percent level with coefficient values 0.10, 0.06, 0.16 and 0.87 respectively. In this category, the depreciation had a positive influence over the fish catch since it was affected by less pollution as compared to seriously affected category. The ratio between MVP and MIC of depreciation, fuel cost and human labour was less than one. It indicated that the above inputs were over utilized as like seriously affected fishermen. The ratio of MVP and MIC of maintenance cost was more than one which indicated that the input was underutilized.
2.6 Low affected fishermen
The catch responded significantly to the inputs and the coefficient of fuel cost, number of fishermen and maintenance cost were positive and significant at one per cent level with coefficient values 0.15 and 0.15 and 0.66 respectively. The ratio between MVP and MIC of depreciation cost of boat, fuel cost and human labour were less than one and it indicated that the above inputs are over used. as like other two categories of affected fishermen. The ratio of MVP and MIC of maintenance cost was more than one and indicates that it was underutilized. Thus the preceding analyses confirmed that efforts should be dovetailed for arresting the excessive usage of fuel, human labour, boat and the consequent depreciation and at the same time better attention towards boat maintenance for the attainment of sustainable management of fisheries production.
2.7 Technical efficiency of fish production
Data envelopment analysis was attempted to measure the technical efficiency of serious, medium and low affected fish production. The data envelopment analysis (DEA) is a non - parametric mathematical programming methodology based on the works of Farrell (1957) and Fraser and Cordina (1999). The results of DEA with constant return to scale technical efficiency (CRSTE), variable return to scale technical efficiency (VRTSTE) and scale efficiency (SE) for serious, medium and low affected fish production are given in Table 5. It could be observed from the Table that the level of technical efficiency for serious affected fishermen category was ranged from 94.60 to 100.00 with mean efficiency of 98.00 percent in constant return to scale. The technical efficiency as calculated by using variable return to scale indicated that efficiency was ranged from 95.80 to 100.00 with mean efficiency of 98.00 per cent. Scale efficiency was ranged from 98.10 to 100.00 with mean efficiency of 99.00 percent.


Table 5 Technical Efficiency and Scale Efficiency of total fish production

The level of technical efficiency for medium affected fishermen category was ranged from 93.10 to 100.00 with mean efficiency of 98.60 percent in constant return to scale. The technical efficiency as calculated by using variable return to scale indicated that the efficiency was ranged from 98.20 to 100.00 with mean efficiency of 99.60percent and scale efficiency was ranged from 93.10 to 100.00 with mean efficiency of 99.00 percent.
The level of technical efficiency for low affected fishermen category was ranged from 96.40 to 100.00 with mean efficiency of 99.20 percent in constant return to scale. The technical efficiency as calculated by using variable return to scale indicated that efficiency ranged from 97.40 to 100.00 with mean efficiency of 99.60percent and scale efficiency ranged from 96.40 to 100.00 with mean efficiency of 99.60 percent. It could be concluded from the above results the mean technical efficiency and scale efficiency of all the three categories of serious, medium and low affected fishermen was similar and was around 99 per cent.
2.8 Valuation of fish production damage
The valuation of the fish production damage was attempted in this section with production change technique and direct valuation methodology of contingent valuation.
2.9 Production change technique
In the present study, negative externalities and the consequent decline in fish production were analyzed for serious, medium and low affected fishermen. Since the production decline was measurable, the production change technique was employed for the year 2012-2013 and presented in Table 6. It could be seen from the Table that fish production was varied with pollution intensity for both Sardinella longiceps and Rastrelliger kanagurta. In particular, the fish production for Sardinella longiceps was highest for low affected category with the annual fish production of 22593 Kilograms and it was higher over medium affected category by 151.16 per cent and over serious affected category by 210.54 per cent. Likewise, the annual fish production was also highest for low affected category in case of Rastrelliger kanagurta with 22899 Kilograms and it was higher over medium affected category by 159.21 per cent and over serious affected category by 207.87 per cent.


Table 6 Annual Fish Production in the study area

3 Contingent valuation
3.1 Willingness to Pay for affected fishermen
Willingness To Pay (WTP) is direct valuation methodology and is based on interviewing the respondents, who reveal their preferences based on their income and other considerations.
The details of WTP are presented in Table 7. It could be seen from the Table that number of WTP was increased with pollution intensity and it was highest for with serious affected category with 50.00 response followed by medium affected category with 37.50 per cent response and lastly by low affected category with 20.00 per cent response. The WTP amount was also highest for serious affected category with annual amount of Rs. 5850 and it was higher over medium affected category by 163.59 per cent and over low affected category by 491.18 per cent. The preferred mode of payment was monthly payment and was highest among all categories as compared to annual payment. Farmers preferred monthly payment since they felt that fish production was encountered with seasonal fluctuations and also had rest period, it is better to make monthly payment.


Table 7 Willingness to pay of affected fishermen

3.2 Willingness to Accept the Compensation and No Payment
The case of Willingness To Accept Compensation (WTAC) and no payment is presented in Table 8. The willingness to accept compensation and no payment was lowest for seriously affected fishermen with a proportion of 30.00 per cent and 20.00 per cent respectively. It was highest for low affected fishermen with a proportion of 37.50 per cent and 42.50 per cent respectively. The proportion of compensation was lowest for serious affected fishermen since the fishermen in this category felt that the compensation principle would not be practical and time consuming. They wanted immediate solution since they were affected seriously. On the other hand, for moderately and low affected fishermen due to less pollution intensity, the proportion of compensation and no payment was higher. For all categories of fishermen, there was no limit in accepting compensation.


Table 8 WTAC and No payment of affected fishermen

Among reasons for no payment, 75 per cent of the seriously affected fishermen and 25.00 per cent of the moderately affected fishermen cited limited income as the reason for no payment. On the other hand, cent per cent of low affected fishermen, fifty per cent of moderately affected fishermen and 12.50 per cent of seriously affected fishermen felt that the government should pay for starting of any scheme to counter fisheries production damage especially SIPCOT industrial pollution since they felt that it was only the government that had encouraged the establishment of the industry in the coastal ecosystem which eventually led to higher pollution. Thus it could be concluded from the preceding analyses that WTP was varied with pollution intensity and it was highest for seriously affected category. WTAC was highest for medium and low affected categories.
3.3 Sustainability Evaluation with Sustainable Rural Livelihood framework Analysis
The Sustainability evaluationwithSustainable Rural Livelihood Framework (SRL) analysis of fisheries production was attempted by assessing the natural capital, financial capital, physical capital, human capital and social capital and the results are furnished in Table 9.


Table 9 Sustainable Rural Livelihood Index for affected Fishermen

3.4 Natural assets
Natural assets were assessedin term of fish catch, seasonality of catch and habitat destruction. The fish catch and seasonality of fish catch was both coincided with pollution intensity. The fish catch for low affected fishermen was highest with 233 Kg per catch and it was higher over medium affected fishermen by 120.73 per cent and over serious affected fishermen by 159.59 per cent. The seasonality of fish catch was assessed by examining the fish catch in peak and lean season. The peak season fish catch was highest for low affected fishermen with 250 Kg and it was higher over medium affected fishermen by 121.36 per cent and over serious affected fishermen by 150.60 per cent. The lean season fish catch was also highest for low affected fishermen with 200 Kg and it was higher over medium affected category by 163.93 per cent and over serious affected category by 166.67 per cent. The habitat destruction by the operation of industries was highest in seriously affected category with seven industries followed by medium affected category with five industries and low affected category with two industries.
3.5 Physical assets
The physical assets of fishermen were examined by means of value and quality of housing, sanitation, accessibility to schools and hospitals and value of boat and all these varied with pollution intensity. Housing value was highest for low affected fishermen with Rs. 4.95 lakhs and all are pucca cement houses. For medium affected fishermen, even though the proportion of pucca houses was of 97.50 per cent, the value was only 2.64 lakhs. For low affected fishermen, the proportion of pucca houses was 87.50 per cent with the value of 2.19 lakhs. Sanitation was also varied with pollution intensity and the proportion of houses with toilets was highest for low affected category with 75.00 per cent. It was comparatively low for medium and serious affected category with the proportion of 32.50 per cent and 25.00 per cent respectively. Accessibility to schools and hospitals was increased with pollution intensity. Value of boat was highest in low affected category with 3.03 lakhs and it was higher over medium affected category by 248.36 per cent and higher over serious affected category by 270.54 per cent.
3.6 Human assets
The human assets of fishermen were assessed in terms of gender ratio, migration, food security, health, education and occupation. With regard to gender ratio, there was no much disparity among the three categories as it being a demographic factor and it was around 890. Migration to cities was present only in serious affected category with 10.00 per cent due to high pollution and consequent drop in fish income in that category. Food expenditure and health expenditure was highest for serious affected category with 86.16 and 24.10 thousands of rupees respectively. There was no much difference among literacy rate between the three categories and it was around 70-75 per cent. Occupational analyses indicated that other occupations like bus driving, casual labour and shop keeping apart from fisheries dominated the scene in low affected fishermen with 30.00 per cent; 25.00 per cent for medium affected fishermen and 12.50 per cent for low affected fishermen.
3.7 Social assets
Social assets were assessed in terms of family size, participation in village meeting and exposure to mass media. Family size was almost similar between categories and it was around 4-5 members. Participation in village meeting and exposure to mass media was varied with pollution intensity and it was highest for serious affected category with seven and five respectively
3.8 Financial assets
Financial asset was examined by the saving and credit position of the three categories of affected fishermen. With regard to saving, it was highest for low affected fishermen with Rs. 382350 and it was higher over medium affected fishermen by 154.86 per cent and was higher
over serious affected fishermen by 178.96 per cent. Thus the savings varied with pollution intensity. Among different sources of saving, the investment on land occupied the highest among all categories. Jewels formed the next source and savings by cash formed the last source which showed that savings by sample fishermen are less liquid.
The formal credit borrowed by serious affected fishermen was 10.00 per cent with an average amount of  13000 and there was no formal credit borrowing in medium and low affected categories. The informal credit borrowing was ranged with pollution intensity and it was highest for serious affected category with a proportion of 57.50 per cent with an average amount of 161 thousands of rupees.
4 Conclusions
The variable cost, fixed cost, total cost, gross income and net income was varied with pollution intensity. The resource use efficiency analyses revealed that fish catch was positively influenced by the inputs of fish production namely fuel cost, human labour and maintenance cost for all the three categories of affected fishermen. The mean technical efficiency and scale efficiency of total fish production of all the three categories of serious, medium and low affected fishermen was similar and was around 99 per cent. Contingent valuation exercise revealed that WTP was varied with pollution intensity and it was highest for seriously affected category with Rs. 5850 per annum. Assessment of sustainability through sustainable rural livelihood framework under five capital assets revealed that low affected fishermen was more sustainable followed by medium and low affected fishermen as the fisheries level efficiency were transformed into different assets creation.
Policy implications
Ø The production function analyses revealed that fuel cost and human labour positively and significantly influenced the fish catch and hence the State Government should supply the fuel at free of cost to the fishermen. The Government should also initiate schemes like National Rural Employment Guarantee scheme to enhance the human resource potential in fish production.
Ø The technical efficiency of Sardinella longiceps was lowerand Rastriller kanagurta was much lower and hence the extension efforts by the Fisheries Department to popularise the frontier technologies to achieve the highest technical efficiency is the need of the hour.
Ø The contingent valuation technique employed in the study revealed the damage of the seriously affected fishermenwas at Rs.5850 per annum, Rs.3576 per annum for moderately affected fishermen and Rs.1191 per annum for low affected fishermen. The Government should collect this amount from the polluters and pay to the victims depending on the intensity of pollution.
Ø The sustainability analyses revealed that serious affected and moderate affected fishermen were less sustainable due to less investment on natural, human, physical, social and financial assets and hence the financial institutions should facilitate fishermen with cheap credit to have investment on these assets so as to have capital formation in fisheries production
Ø Finally sincere efforts should be undertaken by fishermen for arresting the excessive usage of fuel, human labour, boat and the consequent depreciation and at the same time better attention towards boat maintenance for achieving sustainable management of fisheries production.
References
Almedia et.al.,1997, Production analysis of commercial fishing in the lower Amazon, Report of Research Institute for the Amazon
Battese and Coelli,1995, A model for Technical Inefficiency effects in a Stochastic Frontier Production Function for panel data. Empirical Economics,20: 325-352
Coelli T.J., 1992, A Computer program for Frontier Production Function estimation, Frontier Version 2.0., Economic Letters, 39: 29-32
http://dx.doi.org/10.1016/0165-1765(92)90096-H
Najmudeen T.N.and R.Sathiadas,2007, Economic efficiency of input utilization of mechanized trawlers along the Kerela Coast, Journal of Marine Biological Association of India, 49(2):113-117
 

Venkatesh Salagramma, 2006, Trends in poverty and livelihood in Coastal fishing communities of Orissa State, India, FAO fisheries technical report, Food and Agricultural Organization, Rome

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