Sibananda Senapati (Research Scholar, NITIE Mumbai Faculty, Chandragupt Institute of Management, Patna) & Prof. Vijaya Gupta (NITIE, Mumbai)

Transcription

1 Assessment of Socio-Economic Vulnerability due to Climate Change among Fish Dependent Community from Mumbai, India Sibananda Senapati (Research Scholar, NITIE Mumbai Faculty, Chandragupt Institute of Management, Patna) & Prof. Vijaya Gupta (NITIE, Mumbai) 11/5/2013 1

2 A new approach to vulnerability: Sustainable Livelihood Approach (SLA) A livelihood comprises the capabilities, assets and activities required for a means of living. A livelihood is sustainable when it can cope with and recover from stresses and shocks. (Chambers and Conway, 1991) The SLA approach deals with both the quantitative and qualitative elements (Scoones, 1998). SLA addresses the issues of sensitivity and adaptive capacity to climate change, it brings together the critical factors, assets and activities that affect the vulnerability or strength of household strategies (Allison and Ellis, 2001). The SLA approach considers five types of assets (human, natural, financial, social and physical) and uses multiple indicators to assess exposure to natural disasters and climate variability, social and economic characteristics of households that affect their adaptive capacity, and current health, food, and water resource characteristics that determine their sensitivity to climate change impacts. 11/5/2013 2

3 Coastal Fisheries Community Fish is an important source of food as well as employment, income and foreign exchange for India. The high dependence on natural resources makes fishing communities vulnerable to climate change. The livelihood of fishing communities is vulnerable both economically and socially to climatic changes (seal level rise, flood, heavy rainfall, increases temperature, cyclones, storms) Past studies on climate variability, change and fisheries have mostly focused on deriving trends and fluctuations in fish stocks and distribution. (Badjeck et al. 2010; CMFRI, 2011). 11/5/2013 3

4 Coastal fishing communities (Koli) of Mumbai: A case study Flooding is a very common problem in Mumbai when heavy rainfall coincides with high tides or storm surges. It has been observed that till 1989 the average rainfall of Mumbai was 2129 mm. However, in the average annual rainfall was found to be of 3214 mm (Kumar et al. 2008). Mumbai is the most vulnerable district in terms of loss in area (19.9% or km2) and population affected to 1-metre sea level rise as estimated by TERI (1996). A substantial number of population in the city are fishing communities, popularly known as Kolis. There are 30 fishing villages and 5 fishing Taluks in Mumbai (MFC, 2010). The total Koli population o inmumbai close coseto 41 thousand residing in more oe than 10 thousand families. 11/5/2013 4

5 Other issues Over fishing: Increase in mechanized boats, Increase in export, demand, Government subsidy Ecological degradation and pollution: Pollution of the coastal waters and the creeks from domestic and industrial wastes is another major problem for coastal fishers in Mumbai. Financial and Social Burdens :The entry of middle man and migrants in to the fishing business put lot of financial pressure on fisherman especially on Koli woman. 11/5/2013 5

6 Objectives To study the socio-economic factors and climate change stimulated vulnerability in coastal regions of India in general and coastal communities in Mumbai in particular. To derive indicators of vulnerability at household level To analyze the impacts of climate change on household h productivity and the factors affecting productivity. To identify and analyze the potential climate change adaptation strategies for coastal communities. 11/5/2013 6

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8 Data and Methodology 200 Households surveyed during August 2011-February The survey questionnaire i consisted of ten sections that broadly reflect the five types of assets considered by SLA. These sections are (i) Households demographic information, (ii) Occupation, migration and other characteristics, (iii) Households physical assets, (iv) Family income and expenditure, (v) Borrowings and Savings, (vi) Climate change perceptions, (vii) Marketing issues, (viii) Health issues, (ix) Other social issues, (x) Adaptation measures. With Mahesh K Baria from VersovaVillage 11/5/2013 8

9 Methodology used for the Study The study uses primary data obtained through household surveys for various empirical analyses like; (i) the perception analysis based on descriptive statistics (ii) and for deriving vulnerability indicators (iii) an efficiency analysis using stochastic frontier. Versova Fish landing centre 11/5/2013 9

10 Results and Discussion 1. Perceptions Analysis Table 1: Fishermen Observation on climate change Very high High Moderate Low Very Low Total Rise in temperature 67 (36.8%) 82 (45.1%) 21 (11.5%) 12 (6.6%) 6%) (100%) Rise in rainfall 44 (24.2%) 57 (31.3%) 54 (29.7%) 27 (14.8%) 0 182(100%) Change in rainfall pattern 89 (48.9%) 68 (37.4%) 24 (13.2%) 1(5%) (.5%) 0 182(100%) Rise in sea level 22 (12.1%) 78 (42.9%) 52 (28.6%) 28 (15.4%) 2 (1.1%) 182 (100%) Rise in storm heights and frequency 32 (17.6%) 78 (42.9%) 53 (19.1%) 19 (10.4%) (100%) 11/5/

11 Table 2: Fishermen observation on Impact of climate change on fishing Very Very high High Moderate Low Low Total Less availability of fish (55.5%) (36.8%) 14 (7.7%) (100%) Availability of fish in a different and longer distance 69 (37.9%) (44.5%) (17.6%) (100%) Less availability of a particular fish 62 (34.1%) Loss of fish habitat 32 (17.6%) Loss of coaral reefs 11 (6.0%) 83 (45.6%) 72 (39.6%) 73 (40.1%) 34 (18.7%) 3 (1.6%) 0 182(100%) (30.2%) (11.5%) 2 (1.1%) 182 (100%) (31.9%) (19.2%) 5 (2.7%) 182 (100%) 11/5/

12 2. Indicators of Vulnerability Vulnerability Sensitivity/ Exposure Adaptive Capacity Livlihood Perceived changes and variability Human Physical Financial i Social Govt t&p Policy Resources Resources Resources Resources Resources Percent. of HH Incomes from fishing less availability of fish Age Type of House Total Income Member ship of community Training Type of occupation less availability of a particular fish Education Type of boat Savings Type of family Climate Information Other Sources of Income Rise in storm level Adults in hh Access to elec. gadgets Loans community hall Insurance Occup. female in fishing activities Change in rainfall pattern Health Distance of hospital Total exp. towards fishing send children to school Sale fish to a Rise in middle man temparature subsidy Sea level rise 11/5/

13 Village Vulnerability scores Sensitivity Scores Adaptive capacity scores Khardand Madh Mahim Versova Worli /5/

14 Indicator scores for Physical resources Worli Khardanda Madh Type of House Type of boat Access to elect. Gadgets Distance of hospital Versova Mahim 11/5/

15 Exp-1 Exp-2 Exp-3 Livlihhod condition Perceived change and variability 11/5/

16 3. Efficiency Analysis Nagothu et al., (2012) in their study explained the differences in efficiencies using socio-economic i and climatic i variables from shrimp farming in Andhra Pradesh, India. They have used a stochastic frontier function and a Cob- Douglas production function to study the technical and economic efficiencies of the farmers. Battese and Coelli, (1995) simultaneously estimate the stochastic frontier production and the inefficiency model in one step using the program FRONTIER 4.1 (Coelli, 1996). We have used the following Cobb-Douglas production function. The technical inefficiency model specify as follows. 11/5/

17 Where, yi = Total revenue earned per trip (in Rs) xi = Value of boat (in Rs) Value of net (in Rs) Fuel per trip (in Rs) Ice per trip (in Rs) Labour per trip (in Rs) People go for fishing (in Numbers) Category of boat (1 if mechanized, 0 otherwise Category of boat (1 if motorized, 0 otherwise) Number of trip p( (1 if once in a week, 0 otherwise) Number of trip (1 if daily, 0 otherwise) Where, Zi = Age (in years) Education (1; illiterate, 2; ;primary, 3; high school level, 4; higher secondary, 5; graduate and above) Training g( (1, if taken training, 0 otherwise) Types of electronic gadget used (1; GPS, 2; Satellite, 3; Fish finder, 4; Mobile, 5; other) Observation on increase in temperature (1; very high, 2; high, 3; moderate, 4; low, 5; very low) Observation on rainfall pattern change (1; very high, 2; high, 3; moderate, 4; low, 5; very low) Observation on sea level rise (1; very high, 2; high, 3; moderate, 4; low, 5; very low) Observation on availability of fish in longer distances (1; very high, 2; high, 3; moderate, 4; low, 5; very low) Damaged to boat (1, if boat is damaged, 0 otherwise) 11/5/

18 coefficients Standard -error t-statistics β * β1 (Value of boats) β2 (Value of nets) β3 (Fuel ) * β4 (Ice) β5 (Labour) *** β6 (No. of people) D1 (Category of boat1) * D2 (Category of boat2) * D3 (Number of trip1) D4 (Number of trip2) * Inefficiency model δ δ1 (Age) δ2 (Education) *** δ3 (Training ) δ4 (Types of gadgets) * δ5 (Obs on temp) *** δ6 (Obs on rainfall) δ7 (Obs on SLR) δ8 (Obs on fish availability) δ9 (Damaged to boat) Variance Parameters *= 1% level of significance, Sigma squared (σ2= σu2+ σv2) * Gamma [γ=(σ2/(σ2+ σv2)] ** Log Liklihood **= 5 % level significance, ***= 10% level of 11/5/2013 significance 18

19 Distribution of Technical Efficiency Technical Frequency of Percentage of efficiency (%) Obs. Obs. Mean Efficiency (%) less than Above Mean Efficiency of the 164 households is /5/

20 Conclusion The descriptive analysis shows fishermen are facing the climate change problems like rise in temperature, change in rainfall pattern which continuously affect their fish catch. Urbanization and pollution are also severely affecting the small scale fisherman. Fishermen are not fully aware regarding climate change. The support of government towards fishing communities are not adequate. The study found Worli village is more vulnerable having high sensitivity and low adaptive capacity among the fishing villages selected for study. Though the distribution of efficiencies varies among households, the mean efficiency shows most of the households having a very low level of efficiency. The Efficiency scores among mechanized boat owner and other motorized and country boats owner varies significantly. These derived vulnerability scores can be very useful for considering various policy measures in fishing villages and the indicators can be considered for assessing vulnerability for other regions. 11/5/

21 References Stern, N., (2007) The Economics of Climate Change, The Stern Review, Cambridge University Press, Cambridge, UK Senapati, S. and V. Gupta, Economics of climate change mitigation and adaptation: moving from impact assessment to vulnerability, Interdisciplinary Environmental Review, Vol. 13, Nos. 2/3, Senapati, S. and V. Gupta, The need and scope of adaptation policy beyond as an alternative to mitigation approach, National Seminar on Ecological Economics: An approach towards Socioeconomic and Environmental Sustainability, at Institute for Social and Economic Change (ISEC), Bangalore, India. 30 th September -1 st October, 2009 Senapati, S. and V. Gupta (2011) Vulnerability to Climate Change: A Multidimensional Approach, (Edt.) M. Reddy and T. Vijaya Lakshmi, Climate Change: Vulnerability and Adaptation, Volume -1, pg Chambers, R. and G.R. Conway Sustainable Rural Livelihoods: Practical Concepts for the 21st Century. Institute of Development Studies DP 296, University of Sussex: Brighton. Scoones, I Sustainable Rural Livelihoods: A framework for analysis. Institute of Development Studies Working Paper 72, University of Sussex: Brighton. Senapati, S. and V. Gupta, Climate change vulnerability and livelihood lih sustainability among fish dependent d communities i of coastal regions in India. National Conference on Environment, Natural Resources and Indian Economy, organized by the Analytical and Applied Economics Department, Utkal University, Bhubaneswar, Odisha, India at Utkal University during 18 th -19 th January, 2013 Allison, E. H. and Ellis, F (2001) The Livelihoods Approach and Management of Small-scale Fisheries, Marine Policy, 25, pp Badjeck, M. C. Allison, E. H. Halls, A. S. and Dulvy, N. K. (2010) Impacts of Climate Variability and Change on Fishery-based Livelihoods, Marine Policy, 34, pp Nagothu, U,.S., Muralidhar, M., Kumaran, M., Muniyandi, B., Umesh, N. R., Krishna Prasad, K. S. and Sena De Silva (2012) Climate Change and Shrimp Farming in Andhra Pradesh, India: Socio-economics and Vulnerability, Energy and Environment Research, Vol. 2, No. 2, pp /5/

22 Thank You.. gmail.com s. 11/5/