Livelihood Options and Livelihood Security Among Tribal in South Western Plateau and Highland Region in West Bengal

Abstract

Livelihood resources are varying from one region to another due to natural and human factors. There are no such studies that consider a broad geographical region and tribal livelihood options and livelihood security. So the present study can fulfil such a literature gap. The present study makes an attempt to analyse livelihood options and livelihood security among the tribals. The study was carried out along the south western plateau and highland region in West Bengal. Secondary data and the primary data have been used. Purposive stratified random sampling technique was used to collect the primary data. Sustainable livelihood framework (SLF) has been used for the selection of factors and indicators. The core outcome of the research is that small landholding size and traditional technology are no longer to meet the rising demands of tribal population. Forest resources are also very rapidly declining due to the huge industrial demands and ever-increasing household needs. Now tribal people are travelling long distances to collect forest products than ever before. The better education opportunities to the younger generation could open up new occupational opportunities and economic diversification and that definitely leads to the good economic status of the tribal people.

Keywords

Tribal livelihood tribal population sustainable development livelihood capital livelihood security

Introduction

Livelihood perspective starts with how different people in different places live. Livelihoods perspective has been central to rural development thinking and practice in the past few decades. Livelihood is a very flexible term. For example, it can be related to location (rural and urban livelihoods), occupations (farming, pastoral or fishing livelihoods), the social difference (gendered, age-defined livelihoods), directions (livelihood pathways, trajectories), dynamic patterns (sustainable, resilient livelihoods) and many more. A variety of definitions of livelihood are given in the literature, including, for example, ‘the means of gaining a living’ (Chambers, 1995) or ‘a combination of the resources used and the activities are undertaken in order to live’. The Department for International Development (DFID) defined that ‘livelihood comprises capabilities, assets, and required for a means of living’(Solesbury, 2003). People combine different activities of a portfolio of activities to make a living. The natural environment surrounding the people provides several goods, services and amenities, and other environmental resources that make the livelihood of the tribes (Kumar, Gupta, & Radhakrishnan, 2016).

Tribal people of West Bengal are facing a large scale economic and livelihood insecurity due to the lack of employment opportunities in villages. There are numerous issues of sustainable livelihood among the scheduled tribe population in this region. Ongoing pressure on forest resources is leading to a decline in their traditional occupation. Government control and the exchange of forest land are weakening valuable tribal land.(Mallik, 2013) There have been less number of the institutional opportunities given by the government to upgrade their income opportunities. Forest degradation also causes poverty. In this way, livelihood options are declining quickly. Institutional disappointments, absence of government strategies and frail direction prompts expanding poverty. Many villages of this region are cut off from many social services (health care, education, employment, etc.) provided by the government and non-government organisations due to poor infrastructural development. Poor communication and inadequate policy lead to a low level of industrial development which directly affects people’s livelihoods. For vote bank politics, the political leader uses this region according to their benefit; as a result, long-term deprivation takes place. So, there are needs for livelihood diversification, which can adapt to and recuperate from stresses and shocks, which would reduce poverty. So, from the above discussion it can be said that livelihood options and opportunities are very less for sustaining a meaningful living. The region has a vast potentiality of becoming a vibrant economy. If vast mining resources and forest resources are rationally used then this region will change rapidly and also contribute to our national economy. That is why the above-mentioned topic and region are selected for the study. There are numerous studies on tribal livelihood. But there is no such study that considers a broad geographical region and emphasises tribal livelihood options and livelihood security. So, the present study can fulfil such a literature gap. That is why this study is very important.

Review of Literature

Almost two-thirds of the world’s population living in poverty lives in the rural villages of low-income countries, mainly depending on subsistence farming and other natural resources for their livelihood. The major issue in rural regions of China is the security and quality of the lives of farmers. With an increase in natural capital, farmers tend to engage in agricultural production and make farming or animal husbandry the primary source of household livelihood. The abundance of natural capital tends to make farming a more profitable enterprise overall. Farmers with access to more financial capital tend to engage in secondary and tertiary industries to gain more revenue that is redirected into technology, equipment or infrastructure to be cycled back into production (Su & Shang, 2012).

The incidence of poverty is higher in the mountains than in the plains as a result of the poor accessibility, fragile ecological environment and tense relationship between people and the land, as well as low social-economic development. Poverty in China is mainly found in rural areas, and in the mountains is particularly prevalent, especially in the southwest mountain area. After the economic reforms in the 1980s, China has gradually entered a stage of rapid urbanisation and industrialisation, and now a large number of rural migrant workers leave their villages every year for industries in the cities. Simultaneously, farmers’ livelihood strategies are diversifying. For example, the share of agriculture in household net income is decreasing, while the share of off-farm income is increasing (Xu et al., 2015).

Most of East African coastal and marine ecosystem services are severely undervalued, causing less investment for their protection and conservation. As a result, marine and coastal ecosystems have been degraded, losing economic opportunities for the local inhabitants. The majority of coastal communities are categorised as living at or below the national poverty line. Rural coastal livelihoods in many areas are complex, diversified, and undergoing change continuously. Coastal communities change their livelihood activities at different time periods, which makes their income uncertain. Sixty-one per cent of the population are living without basic livelihood needs (Jayaweera, 2008/09).

Eighty per cent of the total population are located in rural villages where the majority of them depend on subsistence cultivation for their livelihood. However, fairly small irrigated landholding (average of 0.9 hectares), high dependence on agriculture, declining farm productivity and limited access to non-farm income have triggered severe poverty in the rural areas of the mountains and hills in Nepal. The low productivity in farming and limited accessibility to non-farm income sources has been increasing the vulnerability of rural people who are often deprived of a minimum standard of life. Livelihood strategies have consistently found a positive relationship between livelihood diversification to the non-farm sector and poverty reduction. There is also an increasing evidence of rural non-farm sector and commercial farming help declining rural poverty (Khatiwada et al., 2017).

The condition of agriculture-dependent livelihood in Indian villages is very depressing till now. The proportion of income derived from agricultural activity decreased and there was a growing tendency of migration and non-farm activity. This resulted largely from disproportionately low price increases for agriculture crops, and many a times faulty irrigation system and drought produces lower yields which also badly affects the agriculture livelihood (Deb et al., 2002).

Research Gap

Several scholars have studied household livelihood strategies through different approaches: large scale study on sustainable livelihood, livelihood strategy and livelihood security. But there is still a lack of effort to grasp the micro-level and household level picture of livelihood options, livelihood capital and livelihood security among the tribal population. There is a lack of study considering the geographical region with the livelihood aspects. What proportion of the area is provided with good livelihood assets or good livelihood options? And how secure is the tribal household’s livelihood? This study has been designed to answer some of these questions.

Objectives of the Study

To investigate the available livelihood options among the tribal households.

To measure the status of livelihood security among tribal households.

Map 1.

Source: The authors.

Study Area

Physically the south western plateau and highland region in West Bengal comprises an eroded remnant of the adjoining Chotanagpur plateau. This region looks like a triangle, stretching from Bihar and Murshidabad district in the north to Orissa and Purba Medinipur district in the south, and from Jharkhand in the west to Nadia and Hooghly districts in the east (see Map 1). The region has a total area of 34,055 square kilometres.

Data Sources

The database of the study is based on primary and secondary sources. Secondary sources of data are from the flowing sources:

Districts statistical handbook, 2003 and 2013, from Bureau of Applied Economics and Statistics, Department of Statistics and Programme Implementation, Government of West Bengal.

Report from the department of higher education, Government of West Bengal, 2010–2011

Primary census abstract, 2001 and 2011, District Census handbook 2011

Website of Earth Explorer-USGS

Primary data is collected through a well-structured questionnaire. The questions were formed to understand:

The household general information

Demographic, educational and occupational profile of the household

Occupational diversification.

Livelihood options of the household.

The status of livelihood security.

Stratified purposive random sampling technique is used to meet the goals and objectives of the study. One hundred and fifty households were selected from four sub-regions from the study area.

Methodology

Before going to primary survey, the whole study region was divided into four sub-regions: (a) High livelihood resource region (HLRR), (b) Medium livelihood resource region (MLRR), (c) Low livelihood resource region (LLRR) and (d) Very low livelihood resource region (VLRR) on the basis of Livelihood assets index (LAI) based on the available secondary data. Selection of respondents has been done from four subregions, see Table 1 for more details.

Table 1.

Selection of Respondents

Region	Resource Region	Size of Land Holding in acres	Type of Farmers	No of Respondents
South eastern plateau and high land region in West Bengal	High livelihood resource region	(< 0.80)	Large	6
		(< 0.40–0.80)	Medium	11
		(< 0–0.40)	Small	13
	Medium livelihood resource region	(< 1.60)	Large	10
		(< 0.80–1.60)	Medium	13
		(> = 0.80)	Small	17
	Low livelihood resource region	(< 1.20)	Large	10
		(< = 0.80–1.20)	Medium	15
		(> 0.80)	Small	15
	Very low livelihood resource region	(< 2.00)	Large	10
		(< 1.20–2.00)	Medium	14
		(> = 1.20)	Small	16
Total				150

Source: The authors.

Table 2.

Livelihood Asset Index and their Variables

Index	Indicators	Variables
Livelihood asset index (based on secondary data)	Human capital	(a) Schedule tribe literacy rate, (b) the percentage of total workers, (c) percentage of rural people served by the educational facility, (d) the percentage of rural people served by the medical facility
	Natural capital	(a) Forest land in hectares, (b) the percentage of cultivable area to the total area, (c) percentage of irrigated area to total cultivable area, (d) pisciculture area in hectares, (e) percentage number of livestock to total region
	Physical capital	(a) Percentage of the area to the total area of a particular CD block, (b) Elevation in metre of each CD block
	Financial capital	(a) Percentage of rural people served by banking facility, (b) the total number of banks per one lakh population, (c) net collection from small savings in rupees
	Social capital	(a) Number of cooperative societies per 100 thousand population, (b) the percentage of rural people served by agricultural credit societies

Source: The authors.

Table 3.

Human Capability Index, Economic Activity Index, and Livelihood Options Index and Their variables

Index	Variables
Human capability index (based on secondary data)	(a) ST literacy rate, (b) the percentage of main workers, (c) percentage of marginal workers, (d) the percentage of non-workers to total workers, (e) pupil-teacher ratio, (f) no of deaths up to five years/100 thousand population
Economic activity index (based on secondary data)	(a) percentage of cultivators, (b) the percentage of agricultural labours, (c) percentage of household industry workers, (d) percentage of other workers, (e) net area available for effective pisciculture, (f) percentage of livestock to the total region and (g) percentage of rural people served by bank facility.
Livelihood options index (based on secondary data)	(a) Human capability index, (b) livelihood asset index and (c) Economic activity index

Source: The authors.

Table 4.

Livelihood Security Index and Their Variables

Index

Variables

Livelihood security index (based on primary data)

(a) Per household average agriculture land in acres, (b) Percentage of livestock to total region, (c) Dependency ratio, (d) Percentage of the household having secure livelihood (e). Percentage of the household having an insecure livelihood, (f) Percentage of the household having better livelihood compared to five years ago, (g) Percentage of the household having better livelihood option, (h) Percentage of household under self-help group, (i) Percentage of workers who have working days between 180–200, (j) Percentage of the migrant to total migrant of each region has been considered, (k) Household’s satisfaction scores from housing facilities, (l). Satisfaction scores from health care facilities, (m) Satisfaction scores from educational facilities and (n) Satisfaction scores from employment facilities.

Source: The authors.

From Table 2 the data of physical capital—percentage of area to the total area of a particular CD block and elevation in metre of each CD block—were derived out from the analysis of recent satellite images with the help of ArcMap 10.1. Satellite images are collected from the following website of Earth Explorer-USGS. All other variables are collected from the above-mentioned secondary sources.

The interaction among the following three attributes: possession of human capabilities, access to other tangible and intangible assets, and the existence of economic activities defines what livelihood option an individual household pursues. Human capability, livelihood assets and the existence of economic activity are three important elements of livelihood options (Krantz, 2001). That is why the present study used these three important indicators (human capability, livelihood asset and economic activity) for creating livelihood options index. What are the major variables used for Livelihood asset index, Human capability index, Economic activity index and Livelihood options index calculation has been discussed in Table 2 and Table 3. Livelihood security index has been calculated from primary survey data. See Table 4 for what are variables used for index calculation.

After collecting secondary data, the data has been arranged in a suitable tabular format. Then, the data has been converted into standardising variables by the following formula:

Standardisation =1 - (\frac{Max value - observed value}{Max value - \min v a l u e})

Where Max = Maximum, Min = Minimum

The maximum and the minimum values will depend upon the nature of a particular indicator. In the case of a positive indicator, the maximum value will be treated as the BEST value and the minimum will be considered as the WORST value. Similarly, if the indicator is NEGATIVE in nature, then the LOWEST value will be considered as the maximum value and the HIGHEST, the minimum value (EDI, 2009).

Principal Component Analysis

Once the normalised values are obtained for all the indicators across the CD Block, the next step is to assign factor loadings and weights. Principal component analysis (PCA) is used to compute the factor loading and weights of these indicators. The present study followed the step by step process from Educational development index: A suggestive framework for computation published by the Department of Educational Management Information System, National University of Educational Planning and Administration, New Delhi. All the indices used in this research have been derived from the composite index and calculated from IBM SPSS Statistics 20 software.

The following formula is used to determine the index (same formula has been used for all index calculation).

I = \frac{\sum_{i = 1}^{n} x_{i} (\sum_{j = 1}^{n} |L_{ij}| \cdot E_{j})}{\sum_{i = 1}^{n} (\sum_{J = 1}^{n} |L_{ij}| \cdot E_{i})}

Where I is the index, X_i is the ith Indicator; L_ij is the factor loading value of the ith variable on the jth factor; E_j is the eigenvalue of the jth factor.

Livelihood resource region map (Map 2) has been prepared through ArcMap 10.1 and the Livelihood assets index data was used for the map preparation.

The formula of Livelihood options index:

{(Human Capability Index+Livelihood Asset Index+Economic Activity Index)/3)}

All the index values presented in Table 5 and Table 6 are average values calculated in the following way:

For example, Natural capital index of HLRR = = 0.43 (see Table 5).

The same method have been followed for all other index value calculations in Table 5 and Table 6.

Four point Likert scale has been used to measure the level of satisfaction scores for some livelihood sustaining facilities and services. Where 1 means very poor satisfaction and 4 means very good satisfaction. Dependency ratio and sex ratio has been calculated from the primary data. The formula of Sex ratio = Number of females per 1000 males. Formula of Dependency ratio = {(% of dependent member/% of earning member)*100}

Table 5.

Livelihood Resource regions within South Western Plateau and Highland Region in West Bengal

Livelihood Resource Region	No of Blocks	The area in SQ KM	% of the Area to Total Region	Name of the Blocks
HLRR	26	6906.58	20.28	Sabang, Pingla, Daspur 2, Ghatal, Kotulpur, Raina 2, Jamalpur, Raina 1, Khandaghosh, Galsi 2, Burdwan 1, Burdwan 2, Memari 1, Kalna 2, Memari 2, Kalna 1, Purbasthali 1, Bhatar, Manteswar, Purbasthali 2, Mangalkoat, Ausgram 2, Katwa 1, Ketugram 2, Ketugram 1, Nalhati 2
MLRR	30	5162.90	15.16	Mohanpur, Datan 2, Narayangarh, Debra, Daspur 1, Chandrakona 2, Chandrakona 1, Garbeta 2, Joypur, Indus, Bankura 1, Patrasayer, Ausgram 1, Galsi 1, Faridpur-Durgapur, Asansol, Katwa 2, Bolpur, Nanoor, Labhpur, Suri 2, Suri 1. Sainthia, Mayureswar 2, Mayureswar 1, Rampurhat 2, Rampurhat 1, Nalhati 1, Murarai 2, Hura
LLRR	29	10703.84	31.43	Datan 1, Kesiari, Sankrail, Kharagpur, Midnapur, Keshpur, Garbeta 3, Garbeta 1, Raipur, Ranibandh, Simlapal, Taldangra, Onda, Bishnupur, Bankura 2, Sonamukhi, Gangajalghati, Kanksa, Jamuria, Barabani, Kulti, Illambazar, Dubrajpur, Murarai 1, Puncha, Purulia 2, Purilia 1, Para, Raghunathpur 2
VLLRR36		11279.39	33.12	Nayagram, Gopiballavpur, Jhargram, Jambani, Salbani, Binpur 1, Binpur 2, Sarenga, Khatra, Hirbandh, Indpur, Chhatna, Saltora, Mejhia, Barjora, Ondal, Ranijang, Pandabeswar, Salanpur, Bandoyan, Manbazar 2, Manbazar 1, Barabazar, Balarampur, Baghmundi, Arsha, Jhalda 1, Jhalda 2, Kashipur, Jaipur, Raghunathpur 1, Santuri, Nituria, Khoyrasol, Rajnagar, Mahammad Bazar

Source: The authors.

Notes: HLRR = high livelihood resource region, MLRR = medium livelihood resource region, LLRR = low livelihood resource region, VLLRR = very low livelihood resource region and TR = total region.

Table 6.

Distribution of Five Livelihood Capital

Resource Region	Five Livelihood Capital
Resource Region	Natural Capital Index	Human Capital Index	Physical Capital Index	Financial Capital Index	Social Capital Index
HLRR	0.43	0.68	0.82	0.55	0.45
MLRR	0.40	0.62	0.79	0.48	0.35
LLRR	0.33	0.59	0.70	0.44	0.20
VLLRR	0.26	0.58	0.65	0.41	0.11
TR	0.35	0.61	0.74	0.46	0.27

Source: District census handbook, 2011 and District statistical handbook, 2003 & 2013 of BOAES Government of West Bengal.

Results and Discussion

Available Livelihood Options

The south western plateau and highland region in itself is a natural region because it has a homogeneity in terms of the physical environment, climatic conditions and overall human characteristics. For depth analysis and inquiry, of the livelihood options and the opportunities among the tribals, the whole region is divided into four sub-regions (see Map 2) by considering natural and human elements. Five types of capital or resources are incorporated to represent natural and human elements. These five types of capital are as follows: (a) natural capital, (b) human capital, (c) physical capital, (d) financial capital and (e) social capital.

From the livelihood resource map (Map 2), it is clearly observed that the whole region is subdivided into four parts. Each part represents itself as a single resource region. It is also found that livelihood resource is unevenly distributed throughout the region. The major reasons behind the uneven distribution of livelihood resources are the differential distribution of livelihood capital. Though some resources like forest and mining are in very rich distribution in LLRR and VLLRR, most of the resources like human capital, physical capital, financial capital and social capital are richer in HLRR and MLRR than the other regions. For analysing which block falls under which category, Table 5 is produced below.

Map 2.

Source: The authors.

Livelihood capital, assets or resources are bases for human development in any region. Table 6 indicates that five livelihood capitals are distributed unevenly throughout the region. The differences of the index values from HLRR to VLLRR is as follows: Natural capital (0.43 – 0.26) = 0.17, Human capital (0.68 – 0.58) = 0.10, Physical capital (0.82 – 0.65) = 0.17, Financial capital (0.55 – 0.41) = 0.14 and Social capital (0.45 – 0.11) = 0.34. So, it can be concluded that social capital has the largest inequality within the region, followed by natural capital, physical capital, financial capital and human capital. The concentration of cooperative societies per 100 thousand population and the percentage of rural people served by agricultural credit societies is much higher in HLRR than in VLLRR. That is why such social capital has given the highest inequality results. We need to develop more cooperative societies and agriculture credit societies in VLLRR and LLRR. Five important livelihood capital index values are graphically presented in a Bar diagram, From the Figure 1 it is found that Physical capital index has the highest values among all livelihood capital values all through the region. Social capital has the lowest index values all through the region.

Table 6 and Figure 2 clearly indicated that livelihood options increase from VLLRR to HLRR. The highest (0.06) amount of index value increases from LLRR to MLRR, while the lowest (0.03) amount of livelihood options index value increases from VLLRR to LLRR. Difference between the highest and the lowest livelihood options index value is (0.62 – 0.48) 0.14. This clearly shows the cross-sectional inequality of livelihood options from east to west within the study region. Major causes of livelihood options decline are as follows: Human capability decline from HLRR to VLLRR is (0.68 – 0.53) 0.15, Livelihood capital decline from HLRR to VLLRR is (0.58 – 0.38) 0.20 and the decline of economic activity from HLRR to VLLRR is (0.60 – 0.51) = 0.09. Below Figure 2 indicates the sharp reduction of livelihood options from HLRR to VLLRR. Distribution of index values of Human capability, Livelihood assets, Economic activity and Livelihood options index are presented below Table 7. It shows an immense inequality from HLRR to VLLRR.

Figure 1.

Source: The authors.

Table 7.

Livelihood Options Index and Their Related Variables

Resource Region	Variables used for Livelihood Options Index			Livelihood Options Index
Resource Region	Human capability index	Livelihood assets index	Economy activity index
HLRR	0.68	0.58	0.60	0.62
MLRR	0.60	0.52	0.59	0.57
LLRR	0.57	0.44	0.53	0.51
VLLRR	0.53	0.38	0.51	0.48
TR	0.59	0.47	0.55	0.54

Source: Census of India 2011 and Districts Statistical Handbooks 2003 and 2013 of the five districts of West Bengal.

Notes: All the index values are average index values of each respective region. For example, in HLRR there are 26 CD Block. Human capability index of HLRR = (summation of 26 CD Block index value/26) = 0.68. In the same way, all other index value has been calculated except livelihood options index. HLRR = high livelihood resource region, MLRR = medium livelihood resource region, LLRR = low livelihood resource region, VLLRR = very low livelihood resource region and TR = total region.

Figure 2.

Source: The authors.

A recent picture of livelihood insecurity among the tribals was found from a Government of West Bengal’s report. A survey was conducted on 21–22 November 2018 in Jhargram, Bankura, and Purulia under Cultural Research Institute, Government of West Bengal. The report mentioned that almost none of the Sabar tribal people have job cards under MGNREGA, a Sabar does not usually work as agricultural labourer, they are habitually hunters and depend on forest product to earn their livelihood. Electricity supply to the houses of the Sabars surveyed had been disconnected because of non-payment of bills. The literacy rate is very low among the Sabar, child labour is also prevalent and the Sabar covered under the study were addicted to locally produced liquor, which might have a huge impact on their health (TheTelegraph, 2018). As a result, they have fewer livelihood options leading them towards a very critical livelihood insecurity condition and sometimes death.

Study Villages and Demographic Features

Tribal people are the children of nature. Their lifestyle is shaped by the natural ecosystem. Due to environmental degradation, they are facing many problems like scarcity of drinking water, adequate food, traditional medicinal plants and other facilities(Ramya, Satyagopal, Prasad, & Raja, 2017). As a result even today they are the most marginalised section of the society. In the recent few decades, their livelihood system has changed rapidly with the help of access to education, government facility and awareness among the people. Now their livelihood is more secure than the earlier times, though a large number of people are illiterate, unskilled, unemployed and alcoholic, which leads to insecure livelihood. A long duration of insecure livelihood leads to chronic poverty. After that, they automatically fall into the poverty trap (cycle of poverty). That is why research and policy intervention is the need of the hour.

Table 8.

List of Sample Villages and Their Location

Districts Name	C.D. Block Name	Villages Name	No of Household Surveyed
Bankura	Kotulpur	Palashban	3
		Tildanga	4
		Chaknayan	3
	Joypur	Murabari	14
	Ranibandh	Barikul	4
	Ranibandh	Kankrijharna	9
	Taldangra	Maheshpur	5
	Bhihnupur	Aadhkata	7
	Bhihnupur	Bamunbandh	6
	Khatra	Kharidungri	4
	Khatra	Ruparhir	1
Barddhaman	Khandaghosh	Kantapukur	4
	Khandaghosh	Enatigore	1
	Burdwan 2	Talit	6
	Burdwan 1	Sholun	1
	Burdwan 1	Kantapukur	3
Birbhum	Nalhati 2	Khandakar	5
Birbhum	Nalhati 1	Paikpara-Adibasipara	9
Paschim Medinipur	Garbeta 2	Sirishbani	9
Paschim Medinipur	Garbeta 3	Vangadanga	9
Puruliya	Hura	Bahukata	3
	Hura	Ledhodi	5
	Manbazar 1	Patharkata	9
	Kashipur	Parasol	11
	Kashipur	Jihurbana	6
	Bundwan	Jashpur	6
		Sursinga	2
		Churku	1
Total	17	28	150

Source: Field survey 15 January–16 February 2018.

Figure 3.

Source: Field survey 15 January–16 February 2018 .

Sample villages are located within the four sub-resource region. Nine villages are located in HLRR while five, six and eight villages are located consecutively in MLRR, LLRR and VLLRR. The field survey touched seventeen CD blocks and twenty-eight villages. One hundred and fifty sample households were surveyed. It is clearly observed in the present study first the districts were selected then CD blocks, after that villages and finally the households. How household selection has been done from Districts to CD Block and CD block to Village and Village to Household has been presented in the Table 8.

Table 9.

Some Demographic and Economic Features of Study Villages

ResourceRegion	Type of Farmer	Total population & no of HH	Pre-Young Population	Young Population	Pre-Old Population	Old age pop	Sex Ratio	AverageLandholding in Acres/HH	Dependency Ratio	% To Total Migrants
HLRR	Large	32(6)	25.00	46.88	18.75	9.38	1133	1.20	88.24	20.00
	Medium	52(11)	32.69	51.92	15.38	0.00	1000	0.71	100.00	32.73
	Small	60(13)	31.67	46.67	18.33	3.33	1143	0.35	122.22	47.27
MLRR	Large	54(10)	16.67	61.11	9.26	12.96	862	4.01	80.00	26.23
	Medium	59(13)	32.20	44.07	16.95	6.78	1185	1.28	103.45	29.51
	Small	73(17)	31.51	45.21	15.07	8.22	780	0.53	121.21	44.26
LLRR	Large	69(10)	24.64	53.62	15.94	5.80	1029	2.20	97.14	20.00
	Medium	74(15)	32.43	51.35	10.81	5.41	1000	1.11	131.25	30.91
	Small	65(15)	33.85	49.23	12.31	4.62	912	0.37	85.71	49.09
VLLRR	Large	59(10)	16.95	49.15	22.03	11.86	903	4.69	110.71	26.15
	Medium	58(14)	17.24	58.62	20.69	3.45	758	1.89	70.59	33.85
	Small	82(16)	29.27	50.00	13.41	7.32	1050	0.97	115.79	40.00
TR		737(150)	27.41	50.61	15.47	6.51	965	1.45	102.47

Source: Field survey 15 January–16 February 2018 .

Notes: Value within the brackets are the number of households, age structure showing in percentage number of population; Pre young = > 18 years, young = 18–45 years, pre old = 46–60 years, old = < 60 years; HLRR = high livelihood resource region, MLRR = medium livelihood resource region, LLRR = low livelihood resource region, VLLRR = very low livelihood resource region; HH mean Household.

From Table 9 it is seen that tribal population distribution within the study area is uneven. In HLRR per household, the population is 4.80, whereas in VLLRR per household population is 4.97; population concentration is more where livelihood resource is less. Age structure has been classified into four categories: a). Pre young (> 18 years), b). Young (18–45 years), c). Pre old (46–60 years) and d). old (< 60 years). The young population in the total region is 50.61 per cent which is much higher than the other age groups. Following that were the population of pre young (27.41 per cent), pre old (15.47 per cent) and old age (6.51 per cent) with respect to the total region. This is a clear indication of a tribal household’s dependency on the young age group population for their livelihood support. If we are able to channelise this young age group population by skill development and training programme, they can help our state and nation in economic development. The sex ratio is also higher in HLRR and MLRR than LLRR and MLRR. Where livelihood is secure, sex ratio is also high. Land ownership is one of the greatest reasons for disparity on the planet today. The land is the best asset for creating wealth. Out of 150 households, 36 households (24.00 per cent) have large landholding sizes, 53 households (35.53 per cent) have medium landholding size and 61 households (40.67 per cent) have small landholding size. Though per household average landholding is very high (4.69 acres/household) in large landholding size class in VLLRR, the economic return from this land is very low. Because of one time cropping pattern prevailing there, people are almost entirely dependent on monsoon rainfall and the productivity of the land, among other factors. Lowest per household average landholding is found in small landholding size class in HLRR. The cropping pattern in HLRR is of three-times. That is why value and economic returns per unit area are very high. Here household earning members can diversify their income by engaging themselves as agricultural labour or construction labour in the nearby locality. Here work opportunity is much higher than in VLLRR. The overall declining trend of dependency ratio is also following from large farmer to small farmer. The highest dependency ratio was found in LLRR within a medium farmer’s household. The percentage of total migrants is also increasing with decreasing landholding size. The small farmer tries to secure their livelihood through more number of seasonal migration labours. So, from Table 9, it can be said that small farmers have less opportunity to secure their livelihood than the medium and large farmers.

From Figure 3 it is observed that the highest average schooling year per literate person of 10.17 years is found in large farmer’s households in LLRR, following the large farmer’s household in MLRR. In both the cases here, landholding plays an important role in educational attainment. With an increment of landholding size, the average schooling year/literate person also increases. But the exception is in VLLRR where landholding size does not affect education attainments. It was seen that with decreasing landholding size average year on schooling increases. Here most of the parents with small landholding depend on seasonal migration and forest resource collection. They always feel insecure about their livelihood. That is why they send their children to school to secure their future livelihood.

Status of Livelihood Security

Secure livelihood for all citizens should indeed be a strategy need for all governments. In India, particularly in the tribal belt, this objective is far off as a financial, social and political goal (Gokarn, 2014). Food and Agriculture Organisation (FAO) defines household livelihood security as adequate and sustainable access to income and resources to meet basic needs, which include adequate access to food, potable water, health facilities, educational opportunities, housing, time for community participation and social integration. Most of the tribal people within the study region directly or indirectly depend on agriculture for their livelihood. There is always a huge risk and uncertainty in agriculture because agriculture very much depends on monsoonal rainfall. The tribal population does not have sufficient land for agriculture. As a result, they always face livelihood insecurity. To understand the three important sector of economic activities among tribal within study region Figure 4 has been presented. To understand the status of livelihood security among tribal household Figure 5 has been drawn.

Figure 4.

Source: Field survey 15 January–16 February 2018.

Figure 5.

Source: The authors.

Figure 4 indicates that the three sectors of economic activity (primary, secondary and tertiary sector) have been classified into nine major categories. Agriculture is the major activity along all the four sub-regions. Percentage of people engaged in agricultural activity vary from one region to another due to the availability of agricultural land. Tribal people from VLLRR engage themselves as migrant labour. The second and third highest activity is hunting, collecting and gathering, and manufacturing activity. Forest-based tribal villages hunt animals like rabit, mouse, pig, etc., and collect fruits, roots, honey, mushroom, Sal leaves, Kendu leaves, and so on, for sustaining their livelihood. They make plate from Sal leaves and sell Kendu leaves for bidi making. The tribal population of VLLRR also take part in processing activities like rope making from Babui grass. This special grass does not require much water. If someone planted this grass it will remain for four to five years. One person can earn Rs.90 to Rs.100 per day from such activity. Construction activity is also found in all regions but very little. Transport activity is highest in HLRR. In the transport activity, they work as a labour in the lorry or some people work as a driver. Service sector activity is only 2.83 per cent with respect to the total region. So, from Figure 4 it is found that higher livelihood options in terms of economic returns exist in HLRR, and gradually declines towards VLLRR.

From Figure 5, it is indicated that livelihood security index values are declining from HLRR to LLRR and also from large farmers to the small farmers. But there is an exception in HLRR, where small farmers have much more livelihood security than the medium farmer. The major reasons is a very little attachment to land due to small landholding leading towards diversification of activity. Here employment opportunity is high; demand for daily wage employment is high all through the year. That is why people can earn more money and secure their livelihoods in a better way than the medium size farmers.

Conclusion and Recommendation

Livelihoods in south western plateau and highland region in West Bengal continue to be based primarily on subsistence agriculture, animal husbandry and the extraction of natural resources. Seasonal migration among young men and women is a frequent phenomenon in the western part of the region. Insufficient output result found in VLLRR leads to non-fulfilment of basic livelihood needs. LLRR falls under partial fulfilment of needs. It was found that landless and marginal people between the age group 30 and 45 years migrated to places like Burdwan, Hooghly and Purba Medinipur. The migration usually take place during the monsoonal season and rabi crop season. The main reason for seasonal migration is inadequate irrigation facility, lack of fertile land, degradation of forest, erratic rainfall and soil degradation. Livelihood capital distribution within the study region itself indicates inequality. Such inequality plays a major role in labour migration, financial exclusion and social exclusion, and ultimately strives to livelihood insecurity. Livelihood options index decreases from HLRR to VLLRR.

The government ought to take after the accompanying methodology for better livelihood. The most fitting policy ought to include wage employment generation by means of government wage labour scheme and through generating interest for wage work in addition to rural development in the area. Another imperative methodology is to focus on the tribal population living in poverty by helping them access potential jobs and profitable employment. Then the village level will grow. In this setting, the government ought to set up some Regional resource centres (RRC) to encourage migration. Land redistribution is a genuinely necessary arrangement in regions with river, pond and canal irrigated areas. The issues of infrastructure development, authoritative obligations and basic leadership require reorientation to make participatory forest management a more grass route level applicable. The minimum support for NTFPs ought to be accordingly fixed. Data framework for NTFPs should be built up and observed regularly. The government should give long time access and control rights over the forest land assets to the tribal forest dwellers. Capacity building, aptitude building and preparing programmes for the diffusion of information on forest land assets are of utmost need. Simplifying forest land laws, acts, strategies, and fortifying participatory methods in forest land management for improving more noteworthy sustenance security. The government should set up primary collection centres at Gram panchayat levels for the accumulation of NTPFs for the tribal people.

To maintain livelihood security among the tribals is a multidimensional task. Most of the tribal households do not have an electricity connection. BPL electricity connection is cut off due to non-payment of electric bills. As a result, most of the students from families living in poverty are suffering. The health sector, especially for women and children, are the most vulnerable section among the tribal population. The government should deploy health activists for raising awareness levels among women and children.

Footnotes

Declaration of Conflicting Interests

The authors declared no potential conflicts of interest with respect to the research, authorship and/or publication of this article.

Funding

The authors received no financial support for the research, authorship and/or publication of this article.

References

Chambers

(1995). Poverty and livelihoods: Whose reality counts? Environment and Urbanization , 7(1), 173–204.

Deb

U. K.

Rao

G. N.

Rao

Y. M.

Slater

(2002). Diversification and livelihood options: A study of two villages in Andhra Pradesh, India 1975–2001 [Working paper no. 178]. Overseas Development Institute.

EDI (2009). Educational development index: A suggestive framework for computation . National University of Educational Planning and Administration.

Gokarn

(2014, 3 November). The three components of livelihood security: Jobs, skills and safety nets [Report]. ASSOCHAM Livelihoods Security Summit.

Jayaweera

(2008/2009). Livelihood diversification in rural coastal communities: Dependence on ecosystems services and possibilities for sustainable snterprising in Zanzibar , Tanzania [Master’s thesis]. Stockholm University.

Khatiwada

S. P.

Deng

Paudel

Khatiwada

J. R.

Zhang

(2017). Household livelihood strategies and implication for poverty reduction in rural areas of Central Nepal. Sustainability , 9(4), 1–20.

Krantz

(2001). The Sustainable Livelihood Approach to Poverty Reduction: An Introduction . Swedish International Development Cooperation Agency.

Kumar

Gupta

Radhakrishnan

(2016). Sustainability of diairy based livelihoods of the tribes in Ranchi and Dhanbad districts of Jharkhand. Indian Journal of Dairy Sciences , 220–225.

Mallik

R. M.

(2013). Tribal livelihood, food security and poverty in India . SSDN Publishers & Distributors.

10.

Ramya

H. R.

Satyagopal

P. V.

Prasad

S. V.

Raja

(2017). Characteristics determining the livelihood security of the tribal farmers. International Journal of Current Microbiology and Applied Sciences , 6(7), 4461–4470.

11.

The Telegraph. (2018). Study shows what ails savars . Kolkata: The Telegraph ePaper. https://epaper.telegraphindia.com//printteXtviews.php?id=237240&boxid=155330168&type=img

12.

Solesbury

(2003). Sustainable livelihoods: A case study of the evolution of the DFID policy [working paper no. 217, 1–28]. Overseas Development Institute.

13.

Shang

(2012). Relationship analysis between livelihood assets and livelihood strategies: A Heihe river basin example. Sciences in Cold and Arid Regions , 4(3), 265–274.

14.

Zhang

Rasul

Liu

Xie

Cao

Liu

(2015). Household livelihood strategies and dependence on agriculture in the mountainous settlements in the Three Gorges Reservoir area, China. Sustainability , 7(5), 4850–4869.