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Journal of Resources and Ecology >

2022 , Vol. 13 >Issue 5: 888 - 896

DOI: https://doi.org/10.5814/j.issn.1674-764x.2022.05.013

Assessing Impact of Restoration on Livelihood

The Impacts of Relocation on the Livelihoods among Different Agro-pastoralist Groups in an Immigrated Village in Tibet

  • ZHU Jin , 1, 2 ,
  • PAN Ying , 1, * ,
  • ZHAO Zhongxu 1, 2 ,
  • LI Zhennan 1, 2 ,
  • WU Junxi 1
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  • 1. Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
  • 2. University of Chinese Academy of Sciences, Beijing 100049, China
*PAN Ying, E-mail:

ZHU Jin, E-mail:

Received date: 2021-10-30

  Accepted date: 2022-04-13

  Online published: 2022-07-15

Supported by

The National Natural Science Foundation of China(31971560)

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Abstract

China has achieved a comprehensive victory in poverty eradication. Relocation has been the major measure of the poverty alleviation strategy, and 10 million poor people have successfully been relocated in the ‘Thirteenth Five-Year’ period (from 2016 to 2020). This paper established an integrated evaluation index system for the livelihoods of relocated groups and the sustainability of the village, based on the framework of United Nation 2030 Sustainable Development Goals and using the data from questionnaire surveys in Bailang Village, Tibet. The indicator system quantitatively analyzed the changes in the livelihoods of different agro-pastoralist groups before and after relocation from the three aspects of living standards, livelihood assets, and livelihood strategies. The results showed that relocation led to the improvement of the livelihoods of immigrated households. As the duration after relocation increases, the living standards rise steadily, especially in poverty eradication (SDG1), which increased nearly 100%. Relocation affects the livelihood strategies of the relocated groups, in that the original pure farmers chose more diverse livelihood strategies and the non-farm employment ratio (SDG8) of the village increased. The total SDG score increased from the perspective of the sustainable development of the village. The data also showed that relocation had limited impacts on the livelihoods of the aborigines. The results implied that the relocation policy for poverty alleviation has been implemented successfully in this area. This research could support policy optimization for improving the sustainability of the village and the livelihoods of the immigrants.

Key words： poverty alleviation; relocation; livelihoods; immigrated village; UN-SDGs

Cite this article

ZHU Jin , PAN Ying , ZHAO Zhongxu , LI Zhennan , WU Junxi . The Impacts of Relocation on the Livelihoods among Different Agro-pastoralist Groups in an Immigrated Village in Tibet[J]. Journal of Resources and Ecology, 2022 , 13(5) : 888 -896 . DOI: 10.5814/j.issn.1674-764x.2022.05.013

1 Introduction

In order to resolutely win the battle against poverty, the Chinese government has applied a policy of relocating poor people as one of the major poverty alleviation measures of the country. Poor households were registered and analyzed by the governments regarding their status and the reasons for their poverty. It is widely accepted that ecosystem degradation and poverty are linked together (Cao et al., 2009). Poverty is thought to be reflected from three dimensions: social, economic and environmental (Liu et al., 2014), and environmental deterioration not only erodes the possibilities for maintaining progress but also further aggravates the poverty level, which is known as the “poverty trap” (Cao et al., 2021; Wackernagel et al., 2021). Studies have shown that the reality of ‘one side of the water and soil does not support its own inhabitants’ has led to the migratory behavior of the poor (RGWUFSRPA, 2020). When poor peasants make a living in a vulnerable environment, it is difficult to maintain a sustainable livelihood (Cheng and Gao, 2009). Ultimately, the government decided to relocate 10 million people for poverty alleviation. Among them, 6.44 million people were originally located in the western region, accounting for 64.4% of the total (https://www.ndrc.gov.cn/).
The relocation policy for poverty alleviation is an extremely complex systematic project, which will have impacts not only on the livelihoods of the relocated families, but also on the natural resources of the relocation area (Li et al., 2018; Liu et al., 2019; Wang et al., 2019), and the living environment has a direct impact on the livelihood assets of poor peasants. Farmers are highly dependent on natural resources, while increasing household wealth can reduce that dependence (Duan et al., 2015). Finding the breakthrough for the construction of poor peasants’ livelihood needs to focus on livelihood assets and the choices of livelihood strategy (He et al., 2017). By analyzing a large amount of panel data, Wang et al. (2020) concluded that the poverty alleviation relocation effort has effectively improved the livelihood capital and livelihood strategy of rural households and eliminated the poverty traps. Using the Heckman two-stage model the results showed that relocation will help people optimize their livelihood structure and promote the transition of their livelihood strategy to non-agricultural options (Li et al., 2013). However, there is still a lack of in-depth investigation and research on tracking the variations of livelihoods of the relocated groups and the ecological environment of the destination at a certain period after relocation.
At the United Nations Development Summit in 2015, the UN adopted the 2030 Agenda for Sustainable Development, which contains 17 Sustainable Development Goals (SDGs) and 169 specific goals (https://www.un.org/sustainabledevelopment/). Conducting regional sustainable development evaluation based on UN-SDGs enhances the comparability of research results (Ma and Ai, 2019; Cheng et al., 2020; Xu et al., 2020). This evaluation system can be used to evaluate large-scale projects or local policies in a more comprehensive way (Bryan et al., 2018). Due to certain synergy and trade-off relationships between the 17 sustainable development goals (Zhao et al., 2020), priority is given to assessing and achieving some goals under the special policy background and limited resources (Pradhan et al., 2017). In addition, the UN-SDGs indicators are mainly for national-scale evaluations (Bali and Yang-Wallentin, 2020), which might not always be feasible for regional studies, due to the data availability and regional differences. As a result, more comparable and specific indicators have been added or adjusted based on the 17 goals in UN-SDGs, in full consideration of the specific study areas and research topics of various studies (Lv et al., 2018; Wei et al., 2018; Gao et al., 2019; Zhang, 2019).
Tibet was the only province in the country’s 14 contiguous poverty-stricken areas. The local government has ambitiously relocated 263000 poor people who were originally located in the villages with poor ecological conditions, fragile ecological environments and frequent natural disasters, to the villages within Tibet where the environmental conditions were relatively more suitable for living (https://drc.xizang.gov.cn/) (Tibet Autonomous Region Development and Reform Commission, 2018). This relocation project involves a lot of land use changes and the immigration of the population, so figuring out how to improve immigrated groups’ livelihood and make the whole area sustainable is a question obviously worth considering. Therefore, linking the impact of the poverty alleviation relocation policy on the livelihoods of relocated groups and the sustainable development of the village is of great significance for guiding the follow-up support policy for relocation and the improvement of the policy’s implementation goals.
This study established a group of indicators to study the impacts of relocation on the household livelihood and the sustainability of the immigrated village, based on the UN-SDGs frameworks. Based on the survey data of rural households, this paper first evaluated the impacts of relocation on the household livelihood level and strategy, in consideration of the different immigration years. Then the variations of the SDG scores due to the relocation were also evaluated among different livelihood strategy groups and the whole village.

2 Method

2.1 Study region

The study region of Bailang Village is located in the Lhasa River valley in the southwest of Linzhou County, Lhasa City, Tibet. Bailang is a semi-agricultural and semi-herding village, with an altitude ranging from 3800 to 5500 m and a total area of about 123 km2. The specific geographical range of the village is between 91°01′E-91°10′E, 29°46′-29°55′N. Grassland covers approximately 95% of the total area, at 114.59 km2. Bailang is a climatically favorable area in Lhasa, with an average annual temperature of 7.5 ℃, an average annual rainfall of 440 mm, simultaneous rain and heat in summer, and sufficient light resources throughout the year. Consequently, there are many choices for residents to have a good living, like farming, grazing and working in urban areas.
Bailang administrative village consists of the five natural settlements of Bailang, Kui, Dangguo, Gabu and “Kazi new village”. The “Kazi new village” was used to resettle other villagers from Kazi Township, Linzhou County. From 2016 to 2018, a total of 100 households with 445 people were immigrated in, of which 23 households were residents of Bailang Village and 77 households were from other villages. After 2019, the eradication of poverty has entered a critical stage. The “Sanyan” area was built to resettle poor households from the Qamdo region of Tibet. The Sanyan area received 85 and 125 households in 2019 and 2020, respectively, most of which came from Mangkang County and Gongjue County in Qamdo. As of June 2021, there were 425 households with 2278 people in Bailang Village.

2.2 Data sources

In order to study the impacts of the duration after relocation on the household livelihood changes, the residents in Bailang Village were divided into three groups, which were the aboriginals, the residents who immigrated in after 2016 (from 2016 to 2018), and those who immigrated in after 2019. Data were gathered from questionnaire surveys of farming and herding households in Bailang Village which were completed in 2018, 2019 and 2021. In 2018, the survey was mainly conducted on the indigenous residents in the natural settlements of Bailang, and 10 valid questionnaires were collected. In 2019, the questionnaire survey was conducted for the relocated households and the aboriginals separately in the natural settlements including “Kui”, “Dangguo” and “Kazi new village”. The survey in 2021 was basically the same as the one in 2019, but a site of questionnaire surveys was added for relocation and resettlement in the “Sanyan” area which was newly built after 2019. All surveyed households were selected by the random sampling method. In the end, 33 valid questionnaires were collected, including eight indigenous households and 25 relocated households. Among the relocated households, seven households moved there after 2019, and the duration after relocation was less than 2 years; 18 households moved to Bailang Village in 2016, and the duration after relocation was close to 5 years.
Considering the need for professional knowledge and translation of the language, each survey was conducted by at least two researchers with professional knowledge and a member of the village committee. The questionnaire was designed to obtain the following information for each household in the present time and before the relocation activities (i.e., before their personal immigration for the immigrated households and before any relocation happened in the village for the indigenous residents). The information gathered included the name of the head of the household, the composition of the family population, income, land use, food production and consumption, acquisition and consumption of different types of energy (yak dung, fuelwood, etc.), the convenience and sufficiency of available water resources for livelihood and cultivation, the housing condition including the living area and building construction, and other additional subjective perceptions of the impacts of relocation. The data acquired for before the relocation activities were mainly based on the memories of the head of the household and relevant textual evidence.

2.3 Quantification of household livelihoods based on UN-SDGs

An integrated system of indicators based on the UN-SDGs was established for quantifying both the household livelihoods and the sustainable development of the village, since the impacts of relocation on the livelihoods of the residents of different groups would simultaneously affect the sustainability of the whole village. Considering the impacts of relocation policies for poverty alleviation and relocation, the indicators of household livelihoods were linked with the village-level indicator system of SDGs. The indicators were consistent with the global targets of UN-SDGs, and fully considered the background of the poverty alleviation relocation policy and the spatial scale of villages, to ensure the pertinence and measurability of the indicators.
The quantification of the livelihoods of different groups of residents was mainly carried out on three aspects: living standards, livelihood assets and livelihood strategies (Su et al., 2009). Living standard reflected the family’s income or economical consumption level. Livelihood assets reflected the consumable level of the natural and human resources and other resources that the family possesses during labor activities. Livelihood strategies refer to the labor modes selected by the family member. In fact, these three aspects could help poor households to establish sustainable livelihoods. By analyzing the living standard and livelihood assets, the causes of poverty and the constraints or short-term factors of livelihood development can be identified. Then, through the support of relevant policy implementation, choosing livelihood strategies that can adapt to various external environments results in more sustainable livelihood output (He et al., 2017), and the households can finally achieve the improvement of self-development capacity and stable poverty alleviation.
Therefore, based on the specific targets in the UN-SDGs for poverty eradication (SDG1) and sustainable water management (SDG6), the proportions of farmers and herdsmen whose incomes and water use convenience ratios were higher than the national poverty standards were selected as the village-scale indicators for measuring the living standards. The construction of resettlement areas during the relocation process will lead to the large-scale development and consolidation of the village’s land resources, affecting the village’s ecosystem structure and process, and the migration of population, and thus further affecting the supply and demand of the village’s ecosystem services. Based on this consideration, corresponding to the UN-SDGs of sustainable energy (SDG7) and terrestrial ecosystem protection (SDG15) and their specific targets, the consumption of dry yak dung and net primary productivity were selected as village-scale indicators for measuring the livelihood assets of famers and herdsmen households. The annual food production and proportion of non-farm employment were selected to reflect hunger eradication (SDG2) and decent work (SDG8) for measuring the livelihood strategy (Table 1).
Table 1 Sustainable development evaluation index system for different groups based on UN-SDGs
Goals Indicators Index calculation Aspects of livelihood
SDG1 Poverty relieve rate Hp/Ht Living standard
SDG2 Annual food production for each household M/Ht Livelihood strategy
SDG6 Water accessibility for each household Hw/Ht Living standard
SDG7 Energy supply services C/H Livelihood assets
SDG8 Non-farm employment ratio Pm/Pt Livelihood strategy
SDG15 Net primary productivity in the village NPP/Pt Livelihood assets

Note: Hp: Number of surveyed households with annual net income per capita more than 2300 yuan①(① The poverty line standard is referring to the national poverty alleviation standard promulgated in the 2011 National Poverty Alleviation Work Conference.); Hw: Number of surveyed households with high convenience of water accessibility; M: Annual food production (including wheat and highland barley); C: Consumption of dry yak dung for energy every year in Bailang Village; Ht : Total number of households surveyed; Pm: Number of migrant workers; Pt : Total number of residents in Bailang Village.

2.4 Village SDG calculation

According to the survey data obtained, the village-scale sustainable development indicators were divided into three time periods of ‘before the relocation’, ‘the duration after relocation of less than two years’, and ‘the duration after relocation was within 2-5 years’. At the same time, residents with different livelihood strategies were divided into four types: farmers, herdsmen, semi-agricultural and semi- herdsmen, and pure-working households. The sustainable development indicators of each group were calculated separately.
(1) Methodology for standardization of SDG indicators
${{X}_{i}}=\frac{{{x}_{i}}-{{x}_{i,\text{min}}}}{{{x}_{i,\text{max}}}-{{x}_{i,\text{min}}}}$
where Xi represents the score that SDGi could have after the calculation, xi represents an average value of the SDGi index in survey data from all villagers, xi,max represents the maximum value of the SDGi index in survey data from all villagers, and xi,min represents the minimum value of the SDGi index in survey data from all villagers.
(2) Village Sustainability Development Index
Village SDGs after the standardization treatment were then used to calculate the Village Sustainability Development Index:
$\begin{matrix} VSD=\underset{i=1}{\overset{n}{\mathop \sum }}\,{{X}_{i}} \\ \end{matrix}$
where VSD is Village Sustainability Development Index, Xi represents the standardized value of the SDGi index, and n includes the goals in Table 1 (n=6).

3 Results

3.1 Livelihood changes with different durations after relocation

In general, with an increase in the duration after relocation, SDG1 and SDG6 showed a similar increasing trend in both of the two groups with different relocation years and the aboriginal group. However, SDG2 and SDG8 varied differently in the three groups. SDG7 remained stable during the investigation periods. SDG15 of the per capita NPP of the village, which reflects the per capita possession of ecological resources in the village, declined with the increase in the duration after relocation (Fig. 1).
Fig. 1 Changes in the individual SDG scores for migrants and natives before and after relocation
Specifically, the SDG1 increased by nearly 100% in two years, from 0.429 to 0.857, among the relocated residents who immigrated after 2019. The SDG6 of the three groups all eventually increased to 1, and the growth rate of SDG6 was as high as 257% among the villagers who immigrated after 2019. The SDG2 decreased by 68% for the residents who immigrated after 2016, compared with the situation while they lived in their original locations. The SDG2 of the indigenous people were not negatively affected by the relocation, in contrast, they increased by 32% over the five years while the new residents continuously immigrated in. SDG7 also varied over time and differently among the indigenous people and the relocated groups. The SDG7 of the aboriginal people remained unchanged at the lowest level of 0.2, while SDG7 slightly increased by 0.02 for the residents who immigrated after 2019. For the residents who immigrated after 2016, SDG7 increased in the first two years and then decreased slightly thereafter, with a total increase from 0.39 to 0.49. SDG8 of the resident groups that immigrated after 2016 or after 2019 both increased, by 0.25 and 0.28, respectively. However, SDG8 of the aboriginal people has generally declined by 0.17 since 2016.
These results show that the impacts of relocation on residents’ livelihoods changed over time, and there were trade-offs in some of the SDGs. Under the direct influence of the relocation policy, in the first two years after the relocation, the SDGs shows an initial increasing trend. However, as the duration after relocation increased to five years, the related variations of SDGs show diverse directions. For example, as the duration after relocation increased, SDG2 showed trade-offs with SDG8. This trade-off situation occurred due to the livelihood strategy changes. As the proportion of migrant workers in the adult labor force (SDG8) increases, it leads to the shortage of human resources in the family, which then leads to a decrease in the grain planting area, and the corresponding decrease in the agricultural livelihood capital of farmers (SDG2).

3.2 Changes in livelihood strategy for the immigrated households

The poverty alleviation of relocated people is one of the core motivations for the implementation of a relocation policy. Livelihood strategy is the main factor that affects the livelihood level of a household. An increase in livelihood assets makes the livelihood strategies more diversified for achieving poverty alleviation.
There are four livelihood strategies of pure agriculture, semi-agricultural and semi-herding, pure pastoral and migrant workers in the village. Twelve households changed their livelihood strategies after relocation, accounting for 48% of the total. Specifically, before the relocation, there were six pure farmers and 19 semi-agricultural and semi-herding households, accounting for 24% and 76%, respectively. After the relocation, there were two pure agriculture households, four pure pastoral households, 11 semi-agricultural and semi-herding households, and two households of migrant workers, accounting for 16%, 20%, 64% and 8%, respectively (Fig. 2).
Fig. 2 Changes in the household livelihood strategies before and after relocation
Among the original pure farmers, they changed their livelihood strategy to develop pastoral components and became semi-agricultural and semi-pastoral livelihood households. The semi-agricultural and semi-herding households mostly maintained their original livelihood strategy. In summary, the relocation group chooses their livelihood strategies through a combination of multiple livelihood assets, and the number of households who used only one livelihood asset for their livelihood strategies decreased.

3.3 Comparisons of SDG scores among different livelihood strategies

The realization of livelihood strategies depends on the use of livelihood capital. Farmers with different livelihood strategies have different emphases on their livelihood assets. In order to compare the impacts of relocation policies on groups with different livelihood strategies, the SDG scores before and after relocation were calculated.
After the relocation, SDG1, SDG6, SDG7, and SDG8 of the three livelihood strategies were higher than before the relocation, indicating that the changes of residence can directly improve living standards and increase livelihood assets. SDG1 was positively affected by the relocation to the greatest degree, and increased from 0.52 to 0.92, for a growth rate close to 80%. SDG 6, 7 and 8 also increased by more than 50% after relocation, while SDG2 decreased by 46% after relocation. There were two potential factors leading to the decrease of SDG2. One factor was the increase in the village population and the reduction in cultivation land per capita. The other factor was the change in livelihood strategies, that is, the increase in the number of migrant workers may lead to land abandonment (Fig. 3).
Fig. 3 Comparisons of the SDG scores for different livelihood strategies before and after relocation. (a) Average levels of all living strategies; (b) Living strategies of semi-agricultural and semi-herding; (c) Living strategies of pure farmers.
Relocation negatively affected the SDG2 and SDG8 of pure farmers, which decreased by 0.185 and 0.142, respectively. In contrast, relocation had a positive impact on the SDG2 and SDG8 of the semi-agricultural and semi-pastoral households, where SDG2 increased by 0.082 and SDG8 increased from 0.184 to 0.625, for a growth rate of 239%.

3.4 The trend of SDGs in the whole village

The total SDG score of Bailang Village mainly reflects the overall impact of the poverty alleviation relocation policy on the sustainability of the whole village, including all the residents and the ecosystem. In terms of the overall trend, the SDG score of Bailang Village increased in recent years, while the relocation policy was being implemented (Fig. 4). The largest contributions to the increase of the total SDG score are the increases in SDG1 (poverty eradication) and SDG7 (energy consumption), and the sum of their contribution rates is 84%. SDG2 (hunger eradication) was the only factor that was reduced, leading to the decrease of the village SDG score by 0.261. During the period from before relocation to 2019, both SDG6 and SDG8 showed a temporary decrease of 0.2 and 0.09, then both increased during 2019 and 2021.
Fig. 4 Changes in the VSD Index scores before and after relocation

4 Discussion

Relocation has positive impacts on the improvement of household livelihoods, and the positive impacts improved as the duration after relocation increased. Comparing those households relocated in 2016 and 2019, the poverty alleviation rate and living conditions of residents who relocated earlier were improved to a greater degree. However, the ecological environment of residential areas, such as rural arable land (SDG2) and per capita possession of ecological resources (SDG15), gradually decreased with an increase of the number of migrants (Li et al., 2013). The main reason is that an increase in the village population leads to an insufficient supply of natural resources in the short term. Therefore, to optimize the relocation policy, the number of immigrants should be estimated and restricted based on the ecological and environmental capacity of the immigration village (Ning et al., 2018).
Relocation affects the livelihood strategy choices of the immigrants. As Bailang Village is close to Lhasa City (the capital city and economic center of Tibet), more job positions were available for the immigrants after the relocation, which led to the diversification of their livelihood strategies (Wu, 2016). The livelihood strategies chosen by the immigrated households tended to change from single to multiple types, leading to a decrease of the number of households adopting a single type of livelihood strategy. Besides, relocation influenced the household livelihood strategies in both direct and indirect ways. The direct impact is that the relocation led to the spatial aggregation of the population with more convenient employment and market activities, facilitating the changes in the livelihood strategies. The indirect impact included the limited natural resources and environmental capacity, such as poor soil fertility and reduced per capita arable land area (Wang et al., 2019). At the same time, there was a shift towards non-agricultural options among the relocated groups, which is consistent with the research of Wang et al. (2020).
The relocation policy has little impact on the aborigines, and the overall village SDGs showed an upward trend. However, the changes in SDG2, SDG7, and SDG8 are still unsustainable. A simple prediction can be made for the future trend of village SDG. Firstly, SDG1 and SDG15 reflect the overall social and ecological resources of the village, and they will show no significant change in the short term. In addition, water availability (SDG6) has peaked with infrastructure improvements and will no longer contribute to the improvements of SDG. However, because Bailang Village has relocated and settled groups in different time periods, SDG2, SDG7, and SDG8 are closely related to the households’ own individual factors in addition to external factors. It is uncertain whether they are already in a stable state and what the future trend of change will be. Thus, the future sustainability of the village is still unknown. However, it is known that ‘building a settlement’ is only the first step, so how to eliminate the phenomenon of “returning to poverty” (Bai, 2018), how to continue to improve the livelihood of villagers, and how to enhance the sustainability of the whole village are still issues worthy of more attention.
Nevertheless, there are still some limitations of this study. In terms of sample size, the number of surveyed households accounted less than one-tenth of the total. However, they covered all types of households, not only in relocation duration but also in terms of livelihood strategies, which could make the results more representative. Furthermore, this survey failed to collect the information on the supplies and consumptions of public services such as village medical and educational conditions (SDG3, 4) although they are significant in supporting household livelihood in the social aspect and are also among the important factors for the sustainability of the village. Efforts should be taken for further investigations on the public services and expanding the sample size in Bailang Village. Such a study is expected to obtain more interesting results in the future.

5 Conclusions

This paper demonstrated the impacts of relocation on the livelihoods of residents in an immigrated village, by establishing an integrated indicator system based on UN-SDGs. The results showed that SDG1 has increased nearly 100% since the poor immigrated in. In surveyed households, half of them changed their livelihood strategies after relocation. In all kinds of livelihood strategies, SDG1, SDG6, SDG7, and SDG8 are higher than they were before relocation. The most important finding is that relocation positively affected the household livelihood, and the improvement increased with the increasing duration after relocation. The coexistence of multiple livelihood strategies became the main choice of the relocated households. This implied that relocation has redistributed family labor and increased the non- agricultural labor population. The total SDG score showed that the relocation is a favorable condition for the overall sustainable development of the village. In summary, the initial progress of the relocation of Bailang Village was greatly successful, which is closely related to the support of government policies.

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