Human Activities and Ecosystem

Policy Assessment and Recommendations for Forestry-based Ecological Poverty Alleviation: An Empirical Study from the Prefectures of Nujiang and Aba, Southwestern China

  • WANG Yaming , 1 ,
  • QIN Fanding 2 ,
  • ZHAO Guangshuai 1 ,
  • FENG Qinliang 2 ,
  • WU Qiong 1 ,
  • LI Yang 1 ,
  • YI Xutong , 1, *
  • 1. Economics and Development Research Center of National Forestry-Grassland Administration, Beijing 100714, China
  • 2. Guangxi University of Finance and Economics, Nanning 530003, China
*YI Xutong, E-mail:

WANG Yaming, E-mail:

Received date: 2020-08-21

  Accepted date: 2020-09-22

  Online published: 2021-03-30

Supported by

Economic Development Research Center of National Forestry and Grassland Administration Research Project(JYC2018-101)


China has adopted a long-term campaign against poverty. In recent decades, there is an increasing understanding that ecological poverty alleviation can meet the dual goals of environmental protection and rural poverty reduction. China is pivoting towards forestry-based poverty reduction in the severely poverty-stricken areas. However, several key factors remain elusive, including the extent to which the poor people benefit from forestry programs, whether they are satisfied with the policies and whether the policies are effective for poverty alleviation. Based on data collected through a questionnaire survey of 79 households in the prefectures of Nujiang and Aba, southwestern China, the analytic hierarchy process (AHP) approach was used to examine the effectiveness of the forestry-based poverty alleviation policy. The results showed that four poverty alleviation pathways, including industry, employment, micro-finance and pairing assistance in villages, had obviously increased the incomes of the filing poor households and solved the problem of “Two Worries-free and Three Guarantees”. The poor were satisfied with the forestry-based ecological poverty alleviation policies and these policies had good effects in fighting against poverty. However, there are still some shortcomings, such as a lack of active participation, imperfect targeted identification, lack of funds and limited sources of funds during the policy implementation. Our results highlight the importance of the forestry industry and the public welfare position in the alleviation of poverty in the poverty-stricken areas. Synergies between ecological protection and poverty reduction are possible through sound forestry-based policies. This article recommends five policies to simultaneously realize the potential of poverty alleviation and environment protection through forestry development.

Cite this article

WANG Yaming , QIN Fanding , ZHAO Guangshuai , FENG Qinliang , WU Qiong , LI Yang , YI Xutong . Policy Assessment and Recommendations for Forestry-based Ecological Poverty Alleviation: An Empirical Study from the Prefectures of Nujiang and Aba, Southwestern China[J]. Journal of Resources and Ecology, 2021 , 12(1) : 110 -123 . DOI: 10.5814/j.issn.1674-764x.2021.01.011

1 Introduction

Poverty is a public concern in the developing countries. It is not only a social crisis, but also a great challenge to socio- economic development. By the end of 2018, there were still 16.6 million rural poor people in China, with a poverty incidence rate of 1.7%. Winning the battle of poverty alleviation is not only a pivotal task for building a moderately prosperous society in all respects, but also a critical step toward realizing “Two Centenary” goals( The “Two Centenary” goals means by the time the Communist Party of China celebrates its centenary in 2021, a moderately prosperous society in all respects will be built; and also by the time the People's Republic of China celebrates its centenary in 2049, China will develop into a great modern socialist country that is prosperous, strong, democratic, culturally advanced, harmonious and beautiful.) and building a solid foundation for the Chinese dream of national rejuvenation(② The Chinese dream of national rejuvenation was mentioned by President Xi Jinping at the closing session of the 12th National People’s Congress. The definition of the “Chinese Dream” is, as the greatest ideal for the Chinese people in modern times, the dream to realize national prosperity, national rejuvenation and the happiness of the people.). The Chinese government has proclaimed various action plans, including forest-based pro-poor programs, and has been implementing long-standing strategies and policies to combat poverty.
Forests provide goods and services, and thus support the livelihoods of rural people. Forest related businesses (or so-called forestry industries) contribute to supporting the livelihoods of approximately 90% of the world’s poorest people (Sunderlin et al., 2005). In southeastern Asia, traditional community forestry has grown rapidly to meet the demand of poverty alleviation (Sunderlin, 2006). Evidence has also shown that forestry provides a pathway out of poverty by providing regular cash income in South Africa (Shackleton et al., 2007, Dokken and Angelsen, 2015). Therefore, it is generally acknowledged that forestry can potentially play a central role in the poverty reduction efforts across the developing world (Rasmussen et al., 2017).
The Chinese government began its anti-poverty action many decades ago, although at that time the concept of forestry-based poverty alleviation had not been brought up. In 1994, “National Eight Seven Poverty Alleviation Plan (National Eight Seven Poverty Alleviation Plan” was issued by the The State Council in March 1994. “Eight Seven” means the problem of lacking food and clothes faced by 80 million poor people in rural areas was basically solved in seven years (from 1994 to 2000). With the promulgation and implementation of this plan, China’s poverty alleviation work had entered a critical stage.) pointed out that the unbalanced development of ecology is a common situation in poor areas, so improving the eco-environment should be part of the anti-poverty action, and this marked the start of poverty alleviation in the ecological sector. In June 2001, “China’s Rural Poverty Alleviation and Development Outline (2001-2010)” put forth the idea that poverty alleviation and development must be combined with resource conservation and ecological construction to achieve a virtuous circle of resources, population and environment, in order to enhance the sustainable development capacity of poverty-stricken areas. In November of that same year, White Papers, “New Progress in China’s Rural Poverty Alleviation and Development” stressed that poverty alleviation and sustainable development strategies should be combined together, especially in soil and water conservation, environmental protection and the ecological construction sector. In December 2011, “China’s Rural Poverty Alleviation and Development Outline (2011-2020)” emphasized the importance of continuing to implement key ecological restoration projects, establishing an ecological compensation mechanism, increasing the amount of compensation in ecological functional areas, and focusing on biodiversity conservation in poverty-stricken areas. In November 2015, the Central Committee of Communist Party of China (CPC) and the State Council enacted “Decision on Winning the Battle Against Poverty”. One of its basic principles was to protect the environment and achieve green development. Top priority must be given to ecological protection, and new ways to lift the poor out of poverty must be explored so that they can benefit from ecological improvement and restoration. In November 2016, the State Council released “Poverty Alleviation Plan for the 13th Five-Year Plan Period (2016-2020)”.
According to the above documents and national plans, forestry-based poverty alleviation has been elevated to the level of a national policy goal of the poverty reduction programs in China. Forestry is regarded as a key player in rural poverty alleviation. The Chinese government has formulated policies that prioritize forestry-based ecological programs to improve farmers’ livelihoods. Forestry-based programs play an extremely important role in helping poor areas to not only improve the environment and infrastructure, but also to generate economic and social benefits. Ecological compensation, i.e. payment for ecosystem services (PES), is a win-win policy for poverty alleviation, so that the poor people can achieve ecological employment, which not only strengthens ecological conservation and construction, but also increases the income of the poor. It is considered as a potentially effective way to eliminate poverty and generate wealth by vigorously developing forest tourism, forest health care, desert tourism, and sand area sports in most of the poverty-stricken areas of China with fragile environments. In order to strengthen the policy of forestry-based ecological poverty alleviation, the Chinese government has stressed that a new way of ecological poverty alleviation can be explored in combination with ecological conservation and management in areas with poor living conditions, but also that important ecosystems need to be protected and restored.
Making up for developmental shortcomings is the key strategy to overcome poverty. In 2017, the State Council issued the Implementation Opinions on Supporting Poverty Alleviation in Severely Poverty-stricken Areas, and was determined to increase not only investments, but also new programs and measures for ecological poverty alleviation with a focus on supporting the “Three Regions and Three Prefectures”. In January 2018, six ministries of the central government, including the National Forestry-Grassland Administration, formulated the Ecological Poverty Alleviation Work Plan in order to increase the labor remuneration of the poor by allowing them to participate in ecological engineering and construction, to gain stable wage income from ecological public welfare posts, to increase business income and property income from ecological industry development, and to receive transfer income through compen-sation policies for ecological protection.
The poor normally derive environmental income from forests. A global comparative study showed that forest income accounted for 22% (natural forestry 21%, plantation forestry 1%) of total household income on average, but with a large variation (Angelsen et al., 2014). However, evidence for the role of forest income as a pathway out of poverty is limited and even more contested (Dokken and Angelsen, 2015). Angelsen and Wunder (2003) summarized the actual and potential roles of forests in poverty alleviation from a global perspective, and divided the benefits into three types: non-timber, timber and environmental services, but many problems and uncertainties remain to be verified. Shyamsundar et al. (2018) developed a conceptual framework to identify five potential areas of investment in forest landscapes that could increase the contribution of forests to poverty reduction. The practical utility of that framework was tested through a portfolio review of forestry lending by the World Bank Group. However, this framework still needs to be more fully tested to identify additional issues that are not being captured and theories of change related to poverty reduction pathways in varied contexts.
Thus far, debate still exists over the effectiveness of forestry in achieving the win-win goals of conservation and poverty reduction (Wunder, 2001; Pagiola et al., 2005). China has carried out large-scale poverty alleviation since the 1980s. Especially in recent decades, many innovative forestry pro-poor models have been practiced in the poverty-stricken areas. Although a considerable number of case studies on the effects of poverty reduction have been conducted, there have been few studies up to now on the modes of targeted forestry-based poverty alleviation in China, focusing on the modes of forestry program and economic development. For this reason, we conducted surveys of poor households in two severely poverty-stricken areas. The aim is to examine the effectiveness of household-level forestry-based poverty alleviation modes and assess whether the poor respondents are satisfied with the forestry-related pro-poor policies.

2 Methodology

2.1 Study areas

The 13th Five-Year Plan for Poverty Alleviation issued in 2016 points out that the most severely poverty-stricken areas are Tibet Autonomous Region, other Tibetan regions in four provinces, four prefectures in southern Xinjiang Autonomous Region, Liangshan Prefecture in Sichuan Province, Nujiang Prefecture in Yunnan Province and Linxia Prefecture in Gansu Province (hereinafter referred to as “Three Regions and Three Prefectures”), as well as poverty-stricken counties and towns with poverty incidences of more than 18% and 20%, respectively. They are characterized by fragile geographical conditions, incomplete infrastructure and large poverty-stricken areas, which are the main difficulties in the fight against poverty. Hence, we chose two severely poor prefectures, i.e. the Nujiang and Aba in southwestern China, to represent the typical areas of the “Three Regions and Three Prefectures”.
Nujiang Lisu Autonomous Prefecture (98°39°-99°39°E, 25°33°-28°23°N) is located in the hinterland of Nujiang River Grand Canyon, in the northwest of Yunnan Province, with most of its territory distributed in the high mountains and dissected valleys. About 61% of the land area belongs to protected areas. The environment is fragile, which intertwines the ecological and poverty problems. In 2018, there were 142900 poverty-stricken people, for a poverty incidence rate of 32.52%, which is among the highest rate in China. Yunnan Province has invested 981 million Chinese yuan (100 Chinese yuan = 15 USD) since 2018 to implement a series of ecological programs such as natural forest protection, sloping land conservation, and ecological benefit compensation. The main measures are as follows: 1) setting up professional cooperatives to participate in afforestation and management and obtain wage income through labor services; 2) building up innovative eco-compensation mechanisms of ecological programs which provide ecological public welfare jobs to the filing poor households( ④ According to the targeted poverty alleviation policy of Chinese government, every poor household should be registered by government with a file card to record their basic information such as family income, poverty causes, support policies or measures, etc. The registered family was called “the filing poor household”.); 3) allowing the poor people participating in forestry-based ecological industries to receive business income from programs such as Nujiang flower valley, Nujiang green spice park and high-quality walnut production; and 4) carrying out pairing assistance(⑤ The Chinese government has mobilized all forces to help poverty-stricken area, one of the measures is called “pairing assistance”, every government department (from central t to loca government) was paired with at least one county or one village to help this county or village lift out of poverty in all aspects. Usually, the send staff or specialists working in the poor area for certain periods.) to help the poor in villages.
Aba Tibetan and Qiang Autonomous Prefecture (100°00°-104°07°E, 30°05°-34°09°N) is located in the western Sichuan plateau with altitudes ranging from 3500 m to 4000 m. There are 13 severely impoverished counties with 103600 poor people. Different programs for ecological protection and restoration, as well as poverty alleviation, have been implemented through transfer payment funds, joint subsidies and award funds. The major programs include Natural Forest Protection Program phase II, prohibition of logging, fire prevention, disaster monitoring and early warning, grassland protection, control of rodents and pests, constructed wetland parks, desertification control and forestry-based eco-tourism.

2.2 Questionnaire design and survey

The questionnaire survey was conducted twice in March and July, 2019 with the assistance of the Forestry-Grassland Bureau of Nujiang Prefecture and the Forestry Bureau of Aba Prefecture. The survey covered 181 households in 12 townships of six counties. In total, four different questionnaires were designed for 1) the poor households; 2) the households which used to be poor but have crossed over the poverty line; 3) the households which have never have been in a poor condition and 4) the households which were lifted out of poverty but became poor again. Since this study is primarily interested in the long-term mechanism of forestry-based ecological poverty alleviation, more focus is concentrated on the survey of poor households. A total of 82 poor households were selected for follow-up analysis, but only 79 (Table 1) valid questionnaires were produced, for an effective rate of 96.34%.
Table 1 Sources of samples in the studied prefectures of Nujiang and Aba
Prefectures Counties Townships Numbers of samples Percent (%) Numbers of poor households samples Percent (%)
Nujiang Prefecture Lanping County Zhongpai Town 19 10.5 5 6.33
Lajing Town 7 3.87 6 7.59
Shideng Town 13 7.18 5 6.33
Tu’e Town 20 11.05 8 10.13
Fugong County Jiakedi Town 12 6.63 6 7.59
Pihe Town 18 9.94 5 6.33
Shangpa Town 19 10.5 4 5.06
Lushui County Pianma Town 11 6.08 4 5.06
Gudeng Town 18 9.94 8 10.13
Aba Prefecture Aba County Kuasha Town 12 6.63 12 15.19
Hongyuan County Hongyuan County 16 8.84 16 20.25
Li County Li County 16 8.84 0 0.00
Total 181 100 79 100
The poor household is the basic survey unit for assessing whether the level of poor farmers’ income has been improved with the help of the poverty alleviation measures and whether the poor are satisfied with the related policies. The minimal criteria are the so called “Two Worries-free and Three Guarantees”, meaning that rural poor people are free from worries over food and clothing, and that they are guaranteed to have access to compulsory education, basic medical services and safe housing (Table 2). For this purpose, we designed a series of questionnaires to survey poor households and quantitatively examine the effect of policy implementation on income improvement and farmers’ feedback on the poverty alleviation modes (Table 2) in the prefectures of Nujiang and Aba (Fig. 1).
Table 2 Questionnaire design on the living conditions and forestry-based modes of poverty reduction
Survey category Sub-categories Main surveyed questions

Two Worries-free and
Three Guarantees

Two worries-free
No worries of food and clothing. Questions include:
$\bullet$ Do you have enough food? percentage of total income expended on food
$\bullet$ Source of drinking water and whether water supply is safe or not
$\bullet$ If you have seasonal clothes, quilts and shoes at home

Three guarantees
Including basic and serious illness medical insurance, compulsory education and safe housing:
$\bullet$ Have you benefited from the renovation policy of dangerous houses since 2014 and has your old house been renovated?
$\bullet$ Is the individual payment part of medical insurance subsidized by government finances?
$\bullet$ Are the medical expenses reduced compared with before?
Forestry-based modes of poverty reduction

Forestry-based small industry $\bullet$ Have you had financial or material support to develop your own industry?
$\bullet$ Can the developed industries bring long-term stable income for poor households?
$\bullet$ Has your business cooperated or linked with enterprises, cooperatives and large households?
$\bullet$ Are you a member or shareholder of a cooperative?
$\bullet$ How is the operation of the cooperative?
$\bullet$ If the cooperative pays dividends, does it participate in the production and operation of the cooperative?
$\bullet$ Is it helpful to increase the family’s income after receiving the industrial poverty alleviation and assistance measures?
$\bullet$ How many family members have taken part in forestry employment training after filing as a poor household?
$\bullet$ Is the training helpful for your finding jobs or increasing employment income?
$\bullet$ How many people in your family have gone out to work or work locally through the government organization after filing?
$\bullet$ Among them, how many family members participated in public welfare jobs?
$\bullet$ Is it helpful to increase family income after obtaining employment assistance measures?
Micro-finance $\bullet$ Do you know about microfinance for poverty alleviation?
$\bullet$ Has your family ever lent a small loan? If yes, how much and what is the loan interest? Did the bank require a mortgage and guarantee?
$\bullet$ What is the main purpose of the loan? Does it help your family to increase income? Yes or no, and why?
$\bullet$ Is there a village pairing assistance team in the village?
$\bullet$ What are the main tasks of the village team? Are you satisfied with its work?
$\bullet$ Does your family have a responsible person in charge of helping? What did he do to help your family and is it helpful for your family?
Fig. 1 Questionaire and interview conductions in Nujiang Prefecture
The main contents of the questionnaire are: 1) general information on the poor households, including family composition and sources of income; 2) forestry-based poverty alleviation policies for forestry industry, employment, micro-finance and pairing assistance in the villages, and 3) farmers’ satisfaction with the above policies. For assessing the effectiveness of the policies, we set up 14 criteria (second level), and 79 evaluation indicators (three levels) in the policy evaluation questionnaire (Table 3). Five levels of satisfaction, including very dissatisfied, dissatisfied, general, satisfied and very satisfied, were established to solicit farmers’ attitudes to 14 aspects of the programs. Those aspects included the publicity of the assistance policy, precise identification of the poor households, identification standards, identification methods, transparency of the identification process, accuracy of identification results, government efforts, assistance policies, assistance personnel, assistance projects, assistance progress, assistance funds, effectiveness of the assistance policies, present living condition, and forestry (or grassland) policies for enhancing social poverty alleviation. Consultation with experts was used to assign importance and evaluate the weights of the different indicators. In this study, 21 experts from 17 universities or research centers, such as Qingdao Agriculture University, Institute of Geographic Sciences and Natural Resources Research, CAS, Nanjing Forestry University, etc., were involved. Most of the experts are from agriculture or forestry universities, and more than 57% of them are professors or vice professors. At the same time, the index system for forestry-based ecological poverty alleviation policy was evaluated in order to identify the problems and put forward feasible solutions to the corresponding problems after comprehensive analysis.
Table 3 Hierarchical structure of forestry-based poverty alleviation policy assessment
First level (A) Second level (B) Third level (C)

A1 Policy making

B1 Precise policy
objectives 0.900(0.249)
C1 Income increase 1.00(0.199)
C2 Living condition improvement 1.00(0.201)
C3 Environment improvement 1.00(0.200)
C4 Management institution of forestry development 1.00(0.200)
C5 Improving social stability in poor areas 0.50(0.200)
B2 Scientific policy options 1.000(0.251) C6 Orientation of policy making 1.000(0.250)
C7Adaptability of policy making 1.000(0.200)
C8 Innovation of policy making 1.000(0.200)
C9 Flexibility of Policy making 0.500(0.200)
B3 Rational policy
measurement 0.900(0.250)
C10 Poverty alleviation in agro-forestry industry 1.000(0.143)
C11 Ecological transfer payment for poverty alleviation 1.000(0.143)
C12 Forestry vocational training 1.000(0.143)
C13 Ecological compensation for poverty alleviation 1.000(0.143)
C14 Social poverty alleviation 1.000(0.143)
C15 Forestry finance poverty alleviation 1.000(0.142)
C16 Forestry relocation 1.000(0.143)
B4 Complete decision making process 0.900(0.249) C17 Public awareness of policy decision making 1.000(0.199)
C18 Public participation in policy decision making 0.500(0.201)
C19 Scientific policy decision making method 1.000(0.200)
C20 Legal procedures for policy decision making 1.000(0.200)
C21 Transparency of policy decision making 1.000(0.200)

A2 Policy
B5 Precise identification of the poor population 0.685(0.331) C22 Identification system for poor population 1.000(0.199)
C23 Information system of the poor population 1.000(0.201)
C24 Complete account of the poor population 1.000(0.200)
C25 Underreporting rate of poor people 0.185(0.200)
C26 Misreporting rate of poor people 0.105(0.200)
B6 Implementation of
poverty alleviation 0.750(0.335)
C27 Reasonable poverty alleviation program 0.500(0.166)
C28 Appropriate measures for poverty alleviation 0.500(0.167)
C29 Intervention means of poverty alleviation 1.000(0.167)
C30 Scientific cause analysis of poverty 1.000(0.166)
C31 Improving measures of poverty alleviation 1.000(0.167)
C32 Family visit records 0.500(0.167)
B7 Village staff of poverty alleviation 0.810(0.334) C33 Cognitive level of poverty alleviation 1.000(0.143)
C34 Willingness and attitudes towards poverty alleviation 1.000(0.143)
C35 Production technology level 1.000(0.143)
C36 Marketing skills of forestry products 0.500(0.143)
C37 Communicative competence and level 0.500(0.143)
C38 Mediation ability of forest right disputes 1.000(0.143)
C39 Number of staff 0.667(0.142)

A3 Policy guarantee
B8 Policy guarantee 1.000(0.333) C40 Policy completeness 1.000(0.498)
C41 Policy feasibility 1.000(0.502)
B9 Human resource
guarantee 0.786(0.333)
C42 Personnel management system 0.500(0.143)
C43 Implementation of main responsibility 1.000(0.143)
C44 Five level working mechanism 0.500(0.143)
C45 Organization construction 0.500(0.143)
C46 Service evaluation 1.000(0.143)
C47 Stationing of personnel 1.000(0.143)
C48 Connection of helper and the poor 1.000(0.142)
First level (A) Second level (B) Third level (C)
B10 Investment guarantee 0.750(0.334) C49 Total investment 1.000(0.200) 1.000(0.498)
C50 Diversity of funding sources 1.000(0.502)

A4 Policy effectiveness
B11 Economic performance 0.857(0.249) C51 Increase of forestry income level 1.000(0.143)
C52 Upgrading of rural forestry industry 0.500(0.143)
C53 Improvement of rural infrastructure 0.500(0.142)
C54 Growth of household income 1.000(0.143)
C55 Growth of household wealth stock 1.000(0.143)
C56 Improvement of farmers’ living conditions 1.000(0.0.143)
C57 Improvement of farmers’ drinking water conditions 1.00(0.143)
B12 Social performance 0.831(0.251) C58 Reduction rate of file-recorded poor people 1.000(0.111)
C59 The exit rate of poor towns 0.367(0.111)
C60 The exit rate of poor villages 0.667(0.111)
C61 The exit rate of the poor population 0.600(0.111)
C62 Coverage rate of rural endowment insurance 0.846(0.111)
C63 Coverage rate of rural cooperative medical system / serious illness medical treatment 1.000(0.112)
C64 Coverage rate of rural compulsory education 1.000(0.111)
C65 Social stability of forest area 1.000(0.111)
C66 Promotion of ecological awareness 1.000(0.111)
B13 Ecological
performance 0.752(0.251)
C67 Forest coverage 1.000(0.111)
C68 Green coverage rate of villages 0.667(0.111)
C69 Improvement of forest structure 1.000(0.111)
C70 Transformation of low quality forests 1.000(0.111)
C71 Prevention and control of forest diseases and insects 0.70(0.11)
C72 Growth rate of woodland area 0.300(0.111)
C73 Harmless treatment rate of feces 0.500(0.111)
C74 Effective sewage treatment rate 1.000(0.111)
C75 Effective garbage treatment rate 0.600(0.111)
B14 Subjective satisfaction 0.750(0.249) C76 Satisfaction with policy making 1.000(0.249)
C77 Satisfaction of policy implementation 0.500(0.251)
C78 Satisfaction of policy guarantee 1.000(0.250)
C79 Satisfaction of policy effect 1.000(0.250)

Note: Data are the policy score and weight (in the parenthesis), respectively, at the different levels; B1-B4 belong to A1, B5-B7 belong to A2, B8-B10 belong to A3, B11-B14 belong to A4.

2.3 Analytic hierarchy process analysis

The quality of a forestry-based ecological poverty alleviation policy directly determines its effectiveness for fighting against poverty. Based on the framework of public policy theory, an index system was constructed for assessing poverty alleviation policies in terms of four objectives: policy formulation, policy implementation, policy guarantee and policy effects. The analytic hierarchy process (AHP) proposed by American operations researcher Thomas Saaty in the 1980s is a combination of qualitative and quantitative decision-making analysis methods (Saaty, 2001). It is widely applicable to the decision analysis of various types of problems (Wu, 2004; Vaidya and Kumar, 2006; Guo, 2008). Specifically, in forestry decision-making evaluation, as long as a reasonable scale is introduced for some unmeasurable factors, this method could be used to measure the relative importance of each factor, so as to provide a basis for decision making (Ananda, 2007; Díaz-Balteiro and Romero, 2001). According to the AHP method, the weight of each sub-evaluation index was confirmed, and then the evaluation index of forestry ecological poverty alleviation policy was constructed to comprehensively evaluate it.
2.3.1 Building a hierarchical model for assessment of forest-based poverty alleviation policies
AHP is a multi-criteria decision-making approach which is widely used for weight determination of factors and policy assessments. The framework for implementing an AHP has three levels of functional hierarchy consisting of objectives, criteria and factors. From the perspective of farmers’ subjective satisfaction, combined with the actual investigation in six counties of Nujiang and Aba Prefecture, the objective is to assess the policies of forestry-based poverty alleviation.
2.3.2 The relative importance of indicators and data normalization
The second step was to assign the relative importance of the indicators by creating a pairwise comparison matrix. The judgments in the pairwise comparison matrix were determined by obtaining the opinions of experts. The assessment of the effectiveness of forestry-based ecological poverty alleviation policy is a multi-indicator evaluation, including both quantitative and qualitative indicators. Therefore, before the comprehensive evaluation, it is necessary to normalize the data to the dimensionless range of [0, 1]. Normalization is a method to eliminate the influence of original index dimensions through mathematical transformation. The evaluation index system for the implementation effect of poverty alleviation policy can be divided into positive and negative directions. A positive evaluation means that the larger the index value, the better the effect; and, on the contrary, the less the negative value, the better the effect. These are the two attributes of the evaluation index for the implementation effect of forestry ecological poverty alleviation policy.
The factors used in this study are classified into two types, positive and reverse. Xi and Si are the actual and standard values of the ith factor, respectively. P(Xi) is an index with a poor effect, and P´(Xi) is an index with a good effect. The specific determination process is as follows:
(1) For the positive factors (i.e., the larger value the better the effect):
If a “good effect” is taken as the standard value:
If XiSi, then P(Xi) = 0
If Xi < Si, then P(Xi) = 1-Xi / Si;
If a “bad effect” is taken as the standard value:
If XiSi, then P(Xi) = 1
If Xi > Si, then P(Xi) = Si / Xi
(2) For the negative factors (i.e. the smaller the value, the better the effect):
If a “good effect” is taken as the standard value:
If Xi Si, then P(Xi) = 0
If Xi > Si, then P(Xi) = 1-Si / Xi;
If a “bad effect” is taken as the standard value:
If XiSi, then P(Xi) = 1
If Xi < Si, then P(Xi) = Xi / Si
(3) Transforming the index with a bad effect into the index with a good effect:
2.3.3 Consistency check of judgment matrices
The consistencies of the comparison matrices are verified during paired comparisons by calculating the consistency index and consistency ratio (Saaty, 1980). The consistency index (CI) = (λmax-n)/(n-1), where n is the number of criteria evaluated and λmax is the main eigenvalue. The consistency ratio (CR) = CI/IR, where IR is the random effect or random index, the values of which vary according to the size of the AHP matrix and can be verified (Saaty, 2008). The level of consistency is considered reasonably acceptable if the CR is less than the upper limit of 0.1 or 10%.
2.3.4 Determination of indicator weights by AHP
This study adopts subjective weighting evaluation of AHP to determine the weight of each factor. First, the decision- making objectives to be carried out are placed in a large system with many factors which influence each other, then the objectives are hierarchically arranged, and finally a multi-layer analysis structure model is formed. After that, the mathematical method and qualitative analysis are combined to assist in the decision-making by sorting the layers and finally calculating the weight of each factor. Based on the pairwise comparison matrix, the weight of the contribution of each factor toward policy assessment can be obtained. First, construct the relevant judgment matrix, invite experts to fill in the judgment matrix, and then fill in the judgment matrix after comparing the relative importance of each specific indicator. Second, calculate the importance ranking, and according to the judgment matrix, fill in the judgment matrix, and the feature vector corresponding to the largest eigenvalue is obtained. Finally, the consistency test is carried out to verify whether the data are valid or not. For each indicator, the higher the weight, the more preferable the indicator (Table 3).
2.3.5 Calculation of the comprehensive policy index
In this paper, for the index evaluation method, the most important step is to synthesize the composite index. A single index and its weight can only reflect one aspect of the forestry ecological poverty alleviation policy. To understand the overall situation of the forestry ecological poverty alleviation policy, it is necessary to combine the individual index values. In this paper, the index sum method is used to synthesize the situations of different aspects of the forestry ecological poverty alleviation policy:
${P}'\left( o \right)=\underset{i=1}{\overset{n}{\mathop \sum }}\,{{W}_{ci}}\times {P}'\left( Ci \right)~$
in which P°(o) represents the composite index of policy indicators, Wci is the weight of each single indicator and P¢(Ci) is the index of a single indicator.
On the basis of previous studies and expert consultation, the levels of implementation effectiveness for the forestry-based poverty alleviation policy in the prefectures of Nujiang and Aba were divided into four grades: excellent (P¢(o) >0.9), good (0.8 <P¢(o)≤0.9), medium (0.6 <P¢(o)≤ 0.8) and poor (P¢(o)≤0.6).

3 Results and discussion

3.1 Basic information of the poor households surveyed

In the surveyed households, Lisu and Han are the main ethnic groups, followed by Tibetan and Bai. The general education level of the poor households surveyed is very low, with 63.3% of the interviewees having not finished primary school. Among the other factors, 41.8% of filing households had four to five poor people, 44.3% of the poor families had two working labors, and most of the poor people work locally (Table 4).
Table 4 Basic characteristics of the respondents among the surveyed households
Variable Characteristics Percent (%) Variable Characteristics Percent (%)
Gender Male 83.54 File-recorded poor population 0 7.60
Female 16.46 1-3 32.91
Nationality Lisu 36.71 4-5 41.77
Han 21.52 6-8 17.72
Tibet 18.99 Number of members in the work force 0 6.33
Bai 15.19 1 18.99
Nu 7.59 2 44.30
Age <30 7.60 3 16.45
31-40 26.58 4 10.13
41-50 26.58 5 3.80
51-60 25.32 Number of migrant workers 0 74.68
> 60 13.92 1 17.72
Education level < Primary school 63.29 2 6.33
Secondary school or higher education 36.71 3 1.27

3.2 Sources of household income and its structure

The main source of the poor household income is agriculture. Descriptive statistics showed that 64.56% and 20.25% of those surveyed obtained income from farming and animal husbandry, respectively, while 20.3% of poor families benefited from the poverty alleviation funds from the government. About 37.97% of the surveyed filing poor households got help from the Minimum Living Standard Guarantee provided by the government. Incomes from working and businesses were limited. About 22.9% and 29.11% of the surveyed families had experiences of migrant working in other provinces and locally, respectively. Business income, at only 1.27%, can be considered as negligible (Table 5).
Table 5 Sources of income for the poor households (N=79)
Sources of income Proportion (%)
Yes No
Poverty alleviation funds provided by the government 20.25 79.75
Minimum living standard guarantee
provided by the government
37.97 60.03
Income from working in other provinces 27.85 72.15
Income from migrant working in the province of residence 8.86 91.14
Income from local working 29.11 70.89
Income from doing business 1.27 98.73
Income from animal husbandry 20.25 79.75
Income from farming 64.56 35.44
Regarding household income structure, nearly half of the surveyed poor families obtained family production income, including farm income and off farm income of less than 5000 yuan, from farming, animal husbandry, and other business activities; while 46% of the families obtained working salary income of 5000-10000 yuan, with only 26% over 10000 yuan. Only eight households had property income of less 5000 yuan from land expropriation, land rent, financial and credit fund dividends and other financial income. The poor households who received transfer income from government subsidies and money from relatives and friends showed a dispersed distribution, with 34.7% of households having income below 5000 yuan and 28.57% having more than 15000 yuan (Table 6).
Table 6 The structure of household annual net income
Source of income (yuan) ≤5000 5001-10000 10001-15000 >15000
Family production income, including farm income and off farm income (N=52) 48.08 21.15 7.69 23.08
Salary income(N=50) 28.00 46.00 12.00 14.00
Property income(N=8) 100.00 0.00 0.00 0.00
Transfer income(N=49) 34.68 26.53 10.20 28.57

3.3 Household forestry and forestry-based income

Most (90.6%) of the interviewed filing poor households had family forest land. About 46.43% of the poor households had a forest land area of less than 10 mu (15 mu = 1 ha), while 21.43% had 10-20 mu, and 32.14% had more than 20 mu of forest land. Among the family forests, 62.07% of the filing poor households had public welfare forest, but nearly half had forest land area of less than 10 mu. Only 14.5% of them used public welfare forest to develop under-forest economy, but with a forest area of less than 5 mu. About one-fourth (25.86%) of the filing poor households had commercial forest, with an average forest land area of 13.37 mu, but only 9.40% of them had submature forest.
About 76.92% of the surveyed filing poor households had forestry income. Further statistical analysis of the households with forestry income showed that 65.06% of the poor households had annual income over 8000 yuan, and 20.48% had a profit of more than 12000 yuan. Only 15.66% of the households obtained annual forestry income less than 2000 yuan.
The filing poor households participated in three forestry-based ecological protection and restoration programs. First, 54.7% of the poor households obtained the eco- compensation from the Protection of Public Welfare Forests, of which nearly 49.05% obtained annual eco-compensation below 400 yuan, while 24.53% received eco-compensation more than 1000 yuan. Second, 61.54% of the respondents received income through participating in the Conversion of Cropland to Forestry Program (CCFP), of which 59.68% of the respondents obtained an annual CCFP subsidy of 2500 yuan and 11.29% received the CCFP subsidy of over 8500 yuan. Third, only 24.79% of filing poor households earned eco-compensation through participating in the Program of Natural Forest Protection, of which most of them received a benefit of less than 10000 yuan per year (Table 7).
Table 7 Household forestry income from public welfare forest and forest programs
Eco-compensation income from
public welfare forests (N=53)
Income from Conversion of Cropland to
Forestry Program (N=60)
Income from Natural Forest Protection Program (N=20)
Income range (yuan) Proportion (%) Income range (yuan) Proportion (%) Income range (yuan) Proportion (%)
≤ 200 28.30 ≤ 1000 32.26 ≤ 6000 18.75
200-400 20.75 1000-2500 27.42 6000-8000 18.75
400-600 15.09 2500-4000 9.68 8000-10000 56.25
600-800 3.77 4000-5500 16.13 >10000 6.25
800-1000 7.54 5500-7000 1.61
>1000 24.53 7000-8500 1.61
>8500 11.29

3.4 Attitude of poor households toward forestry-based poor reduction programs

Our survey data showed that about 84.62% of the interviewed poor households were satisfied with the development of forestry industry and ecological programs by the government, indicating that the forestry-based industry and employment actively promoted poverty alleviation of the poor households.

3.5 Policy assessment of forestry-based ecological poverty alleviation

3.5.1 Policy making
The index of the forestry-based poverty alleviation policy formulation was 0.925, which falls into the excellent grade, and shows that the poor households interviewed were satisfied with the formulated poverty reduction policy. The policy-making goal was sound and clear, the policy scheme was feasible, the means were reasonable, and the policy process and content were complete. The policy index of objectives was 0.900, showing that the goals of the policy making were clear. The related policies can play a major role in increasing the income level, improving the production and living conditions of local farmers, and also improving the environment and forestry institutions. The scientific index of the policy options was 1.000, indicating that the policy-making plan was feasible and could meet the needs of the poor households in the studied prefectures, and that it was also practical in the aspects of policy orientation, adaptability and flexibility. The reasonable index of policy measurement was 0.990, suggesting that the measures for policy implementation were rational. The completeness index of the decision-making process was 0.900, which was in the good range, although there were some defects in the decision-making process. In contrast to these relatively good measures, the public participation index of the complete policy process was only 0.100, showing that the poor households were not enthusiastic in the decision-making process, perhaps due to a lack of good incentives and driving mechanisms.
3.5.2 Policy implementation
The results of AHP showed that the implementation index of the forestry-based poverty alleviation policy for the two prefectures was 0.739, which is in the middle grade, and indicates that the poor households were not satisfied with the implementation process of related policies, or that there were obstacles in the process of policy implementation. Among them, the accurate identification index, poverty reduction implementation index and the index of village resident staff were 0.658, 0.750 and 0.809, respectively, suggesting that the mechanism for the precise identification of the poor was not in place and the accurate identification of poor households was not well done. For example, some disabled households and poverty-stricken households were not accurately identified while some households out of poverty were not eliminated from the list and the information was not up-to-date.
3.5.3 Policy guarantee
The policy guarantee index of forestry-based poverty alleviation was 0.845, ranking in the good grade. In the second level, the index of policy setting was 1.000, demonstrating that the policy was complete and feasible. The index of human resources was in the medium grade, with a value of 0.786, showing that there were some concerns with an incomplete personnel management system, and unclear responsibilities. The fund guarantee index was 0.749, which is in the middle grade and indicates that in the process of forestry-based poverty alleviation, the fund input was insufficient and the funding source was limited.
3.5.4 Policy effect
The index of policy effectiveness was 0.8287, indicating that the overall effect of the forestry-based poverty alleviation policy is good. Within that index, the indices of economic, social and ecological performance were 0.857, 0.831and 0.752, respectively, and the subjective satisfaction index was 0.875. Among them, the ecological performance index was the lowest, indicating that in the implementation process of the forestry-based ecological poverty alleviation policy, the forest coverage, village afforestation, pest control and forest land area did not meet the national standards. There are some problems with forestry ecological engineering in implementing poverty alleviation. The economic performance, social performance and subjective satisfaction were all ranked with good grades, which showed that forestry-based poverty reduction had achieved good progress in increasing the income of farmers, and helping poor villages and towns out of poverty.

4 Discussion

There exists a debate between the forest “safety net” vs. “poverty trap” (Angelsen et al., 2014) and the effectiveness of forestry in achieving poverty reduction (Dokken and Angelsen, 2015). A global comparison analysis found that forest income contributed 22% of total household income, on average (Angelsen et al., 2014). Forest income may serve as a safety net in case of a negative income shock, particularly in the areas associated with a higher use of forest resources by poor households (Debela et al., 2012). But it has been documented that the poorer households obtain a higher percentage of their total income from the forest while richer households extract a higher absolute forest income (Adhikari et al., 2004; Mamo et al., 2007; Vedeld et al., 2007). However, Wunder (2001) questions the importance of the forest safety net function. He believes that the poverty alleviation effect of natural forests is limited. These studies are concerned with the forest income, i.e. the economic dependence of the poor on forest resources. To some extent, the economic benefit is at the expense of forest resources and the environment, which may lead to a vicious circle of environmental degradation and poverty trap if there is a deep dependence on the forest resources. So far, however, there is little empirical evidence on the effectiveness of the government’s efforts in forestry-based poverty reduction through subsidies and transfer payments.
Our case study in the Prefectures of Nujiang and Aba shows that Chinese governments carry out “Two Worries-free and Three Guarantees” to provide security of the basic living conditions and improve the livelihood of the poor households. Forestry-based ecological poverty alleviation policies have been successfully implemented through the eco-compensation of public welfare forests and the development of forestry industries, which has shown a good effect on increasing the income of the poor. The farmers in poor areas are satisfied with the existing ecological poverty alleviation policies for obtaining income from the three ecological projects. In the policy evaluation, the ecological benefits show a medium level. More field investigations and data analyses are needed to support the dual goals of environmental and economic benefit improvements. Through the implementation of forestry ecological protection and restoration programs, we can see that poverty alleviation and ecological compensation are mutually beneficial. On one hand, ecological compensation funds have helped to increase the incomes of poor people. On the other hand, land productivity could be improved via better ecological environmental conditions, as well as enhancing the development potential of poor people in the long run. To some extent, forestry-based poverty reduction policies are effective in arriving at the synergy of the environment with the economic goal.
In China, forestry-based poverty reduction largely depends on forestry economic activities. Different levels of government are responsible for directly implementing eco-compensation for poor households in ecologically vulnerable areas, such as key forestry program areas and ecological public welfare forest areas. The “blood transfusion” compensation mode of poverty reduction makes eco-compensation far removed from the flexible market mechanisms. However, this simple compensation mode is not sustainable, so it is not conducive to playing a positive role in helping farmers to eliminate poverty and increase their income in the long run (Feng et al., 2006; Li et al., 2010).
Nevertheless, compared with foreign countries, China’s forestry-based ecological poverty alleviation has produced significant benefits and has its own unique characteristics. In 2018, the Forestry Gross Output Value in Nujiang Prefecture was 1.948 billion yuan, and the per capita forestry income of farmers was 2635 yuan, accounting for 41% of the per capita disposable income (Zhang, 2019). From 2016 to 2019, China established 21000 specialized ecological poverty alleviation cooperatives, which attracted 1.2 million poor people to participate in the construction of ecological protection projects. Another 1 million registered poor people were recruited to serve as ecological forest rangers (Zhang, 2019). By vigorously developing ecological industries, China has boosted the income of approximately 15 million poor people. There has been a large scale of government investment. For example, from 2016 to 2019, just for the ecological forest rangers who were recruited among poor people, the total investment from the central government has reached 14 billion yuan, while 2.7 billion yuan of provincial financial funds have also been allocated (Zhang, 2019). From 2000 to 2018, the central government invested more than 750 billion yuan in six Forestry Ecological Projects (State Forestry-Grassland Administration, 2018). Forestry-based poverty alleviation methods are also highly diversified. Methods of preferential policies, such as implementing key Forestry Ecological Projects in poor areas, and recruitment of ecological forest rangers among poor people, have shown good effects. In addition, methods of industrial development using forestry resources, such as exploring characteristic forestry industries, understory growth or cultivation, eco-tourism, etc., have turned out to be effective ways to increase the income of the poor. Meanwhile, ideas to innovative poverty alleviation mechanisms have included conducting afforestation tasks through poverty alleviation cooperatives, intellectual support for the poor, forest carbon sequestration transactions based on market mechanisms, etc., which have helped to make progress in improving poor people’s living conditions (Wu and Yi, 2018; Zhang and Xia, 2018). China has achieved more practical experiences in forestry-based poverty alleviation than theoretical studies. The methods mentioned above were summarized through local practice via various experts. The problem is the resulting lack of comparisons between different methods, and a lack of studies on applicable scope and benefits (Dou et al., 2018). China’s forestry-based ecological poverty alleviation research has not yet developed a systematic theoretical research system (Qiu et al., 2017).
In the analysis of China’s forestry-based poverty alleviation policies, most studies focus on only one of the policies, and rarely provide a comprehensive overview, and thus the policies cannot be implemented from the overall perspective and there is a lack of a comprehensive effect evaluation system. Therefore, different forestry poverty reduction policies needed to be integrated for ensuring synergetic benefits. Forestry industry is the key solution for poverty alleviation. From the perspectives of the poverty-stricken areas, governments should recognize the local economic development status, regional industry advantages and resource advantages. On the basis of the synergy of ecological protection and economic development, we should integrate forestry poverty alleviation programs with the advantages of the local characteristic industries, and explore the projects with the most suitable forestry industry advantages. In particular, this approach is suitable for developing cooperative and family forest farm projects, and supporting the development of farmers, special and excellent new economic forests, bamboo forest, fast-growing and high-yield timber forest and other forestry industries. In addition, capacity building for the poor farmers through training courses on forestry business and marketing efforts for leading the forestry economy need to be developed.
In summary, we suggest that China’s forestry-based poverty alleviation should focus on the following aspects in the future:

(1) Precise identification of the severe poverty areas and extremely poor groups

Targeted poverty alleviation must be carried out through precise identification of the severely poverty-stricken areas and the extremely poor groups in the “Three Regions and Three Prefectures”. Major ecological engineering programs, characteristic industries and more modes of poverty reduction through relocation, micro-finance, and social assistance will be given priority to support the severe poverty-stricken areas and poor population. The precise identification of the poor people will be conducted through democratic evaluation, and take the elderly, patients, disabled and other specific poor people as priorities for support.

(2) Choosing the appropriate forestry poverty alleviation modes

At present, the research and analysis results show that the most effective modes of forestry-based ecological poverty alleviation are in developing forestry industry and providing employment to help the poor. First, for the areas with rich forest resources, characteristic planting and breeding industries with high economic benefits, good market conditions and quick results should be developed in order to extend the whole industry chain and add economic value by means of non-timber forest products (NTFPs). Second, public welfare posts and employment recommendations should be provided for the poor through eco-compensation to achieve the dual goals of poverty reduction and ecological protection.

(3) Broadening the channels of pro-poor funds

Cash compensation and employment have been proven to produce effective results for poverty reduction in a short time. Therefore, measures should be taken to integrate all kinds of forest related funds, improve the compensation standards and expand the channels of eco-compensation funds to support the poor population. In addition, forestry-based industrial compensation is a sustainable poverty reduction measure with strong “hematopoietic” characteristics for allowing the poor to receive a long-term stable income.

(4) Building up the forestry industry system for poverty alleviation

Industrial development is an important carrier for driving the economic development of severe poverty-stricken areas and sustaining economic income and employment. First, we should develop high-quality ecological industries and produce ecological products with rich characteristics and added values to help farmers develop industries and businesses. One recommendation is that new mechanisms, such as “e-commerce plus poverty alleviation” and “tourism plus poverty alleviation”, should be applied in supporting poverty alleviation.

(5) Improving the mechanism of ecological protection

As severe poverty-stricken areas are also the ones with fragile ecosystems, a lack of natural resources and tense human and land relationships, great importance should be attached to the impact of ecological protection on the economic development in the fight against poverty. For example, it is necessary to optimize the planting modes of the trees and fruits in ecological projects in the fragile environment, in order to prevent soil erosion and geological disasters.

5 Conclusions

In conclusion, four poverty alleviation pathways, including industry, employment, micro-finance and pairing assistance in villages, have obviously increased the incomes of filing poor households. They have also solved the problem of “Two Worries-free and Three Guarantees” by providing sufficient food and clothing, and ensuring basic medical insurance, compulsory education and housing security through renovation of dilapidated houses or relocation to safe places. The comprehensive index of the forestry ecological poverty alleviation policy was 0.866 in 2018, indicating good effects from the implementation of the forestry-based poverty alleviation policy. However, from the objectives of policy-making, policy implementation, policy guarantee, policy effect and other criteria of forestry-based poverty alleviation policy evaluation indices, relatively lower indices were found for these secondary indicators. There are still some shortcomings. Participation in poverty reduction policies is not active. The targeted identification system is not perfect. Lack of funds or limited sources of funds can be problematic during the policy implementation. In addition, the ecological effect of the policy implementation is not ideal. Therefore, it is necessary to build a long-term mechanism and formulate forestry-based ecological poverty alleviation programs and measures to ensure the effectiveness and sustainability of targeted poverty alleviation.
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