# The Impact of Family Sustainable Livelihood and Environmental Cognition on Herdsmen’s Choice of Production Behavior

Authors: Qihang Wang; Yinjia Miao
Journal: Advances in Materials Science and Engineering
 (2022)

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## Abstract

This study analyzed the influence of sustainable livelihood and environmental cognition on herdsmen’s production behaviors on basis of logistic model. The consequences illustrated that the social capital followed by material capital, financial capital, and human capital has the greatest impact on herdsmen’s production behaviors, but the natural capital played a vital role in promoting herdsmen’s choice of raising breeding scale. The area and quality of grassland in herdsman families’ sustainable livelihood could encourage herdsmen to increase breeding scale, while the quantity of livestock, structure of house, the number of labor, the level of education, the status of health, and the income of families could promote herdsmen to restrain the breeding scale. The cognition of policy and ecological environment also had a significant positive effect on herdsmen restraining breeding scale.


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## Body

## 1. Preface

China is rich in natural grassland area, accounting for 41.7% of the territory area. However, the grassland degradation had become a serious environmental and ecological problem because of the nature and human. As the most vital users and producers, the herdsmen’s breeding scale is a significant factor affecting grassland ecology [1, 2]. Sun et al. [3] indicated that the conflict between their growing livelihood demands and reasonable breeding quantity of grassland was the main reason of enlarging breeding scale. Sun et al. [4] showed that herdsmen had protection awareness, but the government could not realize the influence of breeding scale changing on herdsmen’s lives comprehensively which could destroy protection of grassland resources by the governmental policy. The sustainable developed breeding policy should be formulated by combining the reality of local herdsman families’ livelihood capital and improve herdsmen’s settlement level, expand income channels, and standardize cooperatives’ operation via accelerating the grassland circulation, so as to control the breeding scale and maintain the grassland ecological resources [3]. In the process of grassland protection, government should enhance the participation of herdsmen, strengthen the publicity of grassland degradation and related policy content, expand the ways of herdsmen to increase their income, and then strengthen the living standards of herdsmen groups [3, 5]. Ding et al. [6] studied the Grassland Ecological Subsidy Policy and Livestock Reduction Behavior, and Wu et al. [7] used logit model to analyze the impact of livelihood strategies. In summary, although the existing literature researched herdsmen’s breeding behaviors from the perspective of livelihood capital could provide reference for herdsmen’s production behaviors, there is still room for further research. Most of the academic researches on Herdsmen’s production behavior were focused on government policies and herdsmen’s livelihood factors, but the consideration of internal factors, namely, herdsmen’s environmental cognition, was rarely involved. In this study, the herdsmen in Wuchuan and Qinglong areas of Guizhou Province were taken as the research objects, and the production behavior of herdsmen’s animal husbandry is discussed from two aspects of environmental cognition and family livelihood, which provides reference value for the government to improve the grassland policy and promote the sustainable development of grassland ecology.


## 2. Theoretical Research and Research Hypothesis

### 2.1. Concept Definition

In the 1980s, “sustainable livelihood” was first proposed. Zhang et al. [8] analyzed the research process of “sustainable livelihood” in China based on bibliometric method and believed that, among a large number of sustainable livelihood analysis systems, the sustainable livelihood framework constructed by DFID was the most widely used in the research field of China. The sustainable livelihood capitals of herdsman families mentioned in this article mainly include five different forms of capital (material capital, natural capital, human capital, social capital, and financial capital).In the field of environmental psychology, environmental cognition is an important cornerstone of adapting to the environment and acting on the environment. It is a way for individuals to distinguish the environment, what impression the environment forms in their minds, and how this impression affects the individual acting on the environment. Environmental behavior is an important dimension of environmental cognition, which includes four dimensions: “environmental knowledge, environmental values, environmental protection attitude and environmental protection behavior” [9]. On the contrary, “Environmental cognition and environmental behavior are two independent concepts, and there is no contained relationship” [10]. This study illustrates that the production behavior of herdsmen was closely related to the change of grassland ecological environment, and the cognitive level of grassland ecological environment was an important subconscious dominant factor of herdsmen’s breeding behavior. Wang et al. [11] elucidated that the research of environmental cognition should be considered from three dimensions of policy environment, ecological environment, and economic environment. Because the economic environment was included in the family livelihood capital, it was no longer considered again here.


### 2.2. Livelihood Capital and Herdsman’s Production Behavior

Natural capital is the stock of natural resources, which is the basis of herdsmen’s survival and development. When there are abundant natural resources, herdsmen will lack the motivation to broaden their livelihood strategies and are more likely to expand their breeding scale. For example, Su Fang et al. (2009) pointed out that farmers with more natural resource capital tend to regard agricultural income as a key livelihood strategy. For example, Sun et al. [12] pointed out that farmers with more natural resource capital tended to regard agricultural income as a key livelihood strategy. Herdsmen’s livelihood was highly dependent on natural resources, and extremely rich natural resources could meet the basic demands of herdsmen’s husbandry, so that herdsmen usually would not consider other ways of livelihood [13]. On this basis, the following assumptions were made in this study:H1: when other factors are controlled, the more abundant the herdsman’s natural capital is, the more likely the herdsman is to choose to improve the production behavior of breeding scale.Human capital is the general term of knowledge, skills, and health status and is the basis of all livelihood activities. When the human capital of herdsmen is more abundant, they are more likely to try other livelihood strategies and reduce the scale of breeding. For example, Wu et al. [14] elucidated that, for young herdsmen, it was necessary to strictly implement compulsory education and encourage them to carry out higher education. For the students in pastoral areas, the tuition fees should be reduced appropriately, and the same environment as urban students should be provided, so as to lay a solid foundation for their diversified livelihood strategies in the future. According to the specific situation of the poor farmers, we should actively develop training and strengthen the skill of the labor force. For the labor force who continues to carry out agricultural activities, we should strengthen the skill training in agriculture, such as the cultivation technology of mountain fungi, goats, and cattle. For migrant workers, it was necessary to strengthen employment training in labor export and expand the livelihood channels of poor households [15]. On this basis, the following assumptions were made in this study:H2: when other factors are controlled, the richer the human capital of herdsmen is, the more likely they are to choose to reduce the scale of production.Social capital is the social resources that herdsmen could use to serve their livelihood. The richer the social resources are, the more opportunities and information they could obtain. Financial capital and social resources provided strong support and guarantee for herdsmen to develop diversified livelihood activities [13]. The long-term stable trust relationship could strengthen their awareness of grassland protection and promote their common willingness of protecting grassland and reducing the scale of breeding [16]. Based on this, the following assumptions were proposed in this study:H3: when other factors control, the richer the social capital of herdsmen is, the more likely they are to choose to reduce the scale of production.Material capital is the essential means of production for herdsmen maintaining their livelihood. When the material capital is abundant, the family’s livelihood burden would be kept at a low level, and then the scale of livestock would be reduced. For example, Xie et al. [16] pointed out that the herdsman families with relatively large breeding scale, who would initiatively reduce the quantity of livestock and had less economic losses, were more likely to reduce the animal husbandry scale. Based on this, the following assumptions were proposed in this study:H4: when other factors are controlled, the richer the material capital of herdsmen is, the more likely the herdsmen are to choose to reduce the production behavior of breeding scale.Financial capital is the synthesis of all cash and cashable funds in the process of production and consumption. The higher the family income was, the larger the proportion of mutton sheep breeding was, and the lower the possibility of expanding the breeding scale was [3]. The gradual increase of herdsman’s family’s economic income represented the enhancement of their livelihood level, and the burden of enhancing their livelihood level through traditional animal husbandry would become smaller [17]. According to this, the following assumptions were proposed in this study:H5: when controlling other factors, the richer the herdsmen’s financial capital is, the more likely they are to choose to reduce the scale of production.


### 2.3. Environmental Cognition and Production Behavior

There was a natural basis for the subject who utilizes resources, but it was more restricted by the society (the group norms, value orientation, cultural tradition, and other aspects). The cognitive differences of the resource utilization theme on social policies and different types of geographical environment had more or less influence on their behavior patterns [11]. In the process of policy cognition, the more herdsmen understood the grassland reward and subsidy policy, the higher their satisfaction with the policy is and the lower the possibility of broadening the breeding scale is. In the ecological cognition, the more fully herdsmen understood the ecological environment of the nearby grassland, the less they would expand the breeding scale [17]. On this basis, the following assumptions are proposed in this study:H6: when other factors are controlled, the higher the level of environmental cognition is, the more likely the herdsmen are to choose the production behavior of reducing the breeding scale.


## 2.1. Concept Definition

In the 1980s, “sustainable livelihood” was first proposed. Zhang et al. [8] analyzed the research process of “sustainable livelihood” in China based on bibliometric method and believed that, among a large number of sustainable livelihood analysis systems, the sustainable livelihood framework constructed by DFID was the most widely used in the research field of China. The sustainable livelihood capitals of herdsman families mentioned in this article mainly include five different forms of capital (material capital, natural capital, human capital, social capital, and financial capital).In the field of environmental psychology, environmental cognition is an important cornerstone of adapting to the environment and acting on the environment. It is a way for individuals to distinguish the environment, what impression the environment forms in their minds, and how this impression affects the individual acting on the environment. Environmental behavior is an important dimension of environmental cognition, which includes four dimensions: “environmental knowledge, environmental values, environmental protection attitude and environmental protection behavior” [9]. On the contrary, “Environmental cognition and environmental behavior are two independent concepts, and there is no contained relationship” [10]. This study illustrates that the production behavior of herdsmen was closely related to the change of grassland ecological environment, and the cognitive level of grassland ecological environment was an important subconscious dominant factor of herdsmen’s breeding behavior. Wang et al. [11] elucidated that the research of environmental cognition should be considered from three dimensions of policy environment, ecological environment, and economic environment. Because the economic environment was included in the family livelihood capital, it was no longer considered again here.


## 2.2. Livelihood Capital and Herdsman’s Production Behavior

Natural capital is the stock of natural resources, which is the basis of herdsmen’s survival and development. When there are abundant natural resources, herdsmen will lack the motivation to broaden their livelihood strategies and are more likely to expand their breeding scale. For example, Su Fang et al. (2009) pointed out that farmers with more natural resource capital tend to regard agricultural income as a key livelihood strategy. For example, Sun et al. [12] pointed out that farmers with more natural resource capital tended to regard agricultural income as a key livelihood strategy. Herdsmen’s livelihood was highly dependent on natural resources, and extremely rich natural resources could meet the basic demands of herdsmen’s husbandry, so that herdsmen usually would not consider other ways of livelihood [13]. On this basis, the following assumptions were made in this study:H1: when other factors are controlled, the more abundant the herdsman’s natural capital is, the more likely the herdsman is to choose to improve the production behavior of breeding scale.Human capital is the general term of knowledge, skills, and health status and is the basis of all livelihood activities. When the human capital of herdsmen is more abundant, they are more likely to try other livelihood strategies and reduce the scale of breeding. For example, Wu et al. [14] elucidated that, for young herdsmen, it was necessary to strictly implement compulsory education and encourage them to carry out higher education. For the students in pastoral areas, the tuition fees should be reduced appropriately, and the same environment as urban students should be provided, so as to lay a solid foundation for their diversified livelihood strategies in the future. According to the specific situation of the poor farmers, we should actively develop training and strengthen the skill of the labor force. For the labor force who continues to carry out agricultural activities, we should strengthen the skill training in agriculture, such as the cultivation technology of mountain fungi, goats, and cattle. For migrant workers, it was necessary to strengthen employment training in labor export and expand the livelihood channels of poor households [15]. On this basis, the following assumptions were made in this study:H2: when other factors are controlled, the richer the human capital of herdsmen is, the more likely they are to choose to reduce the scale of production.Social capital is the social resources that herdsmen could use to serve their livelihood. The richer the social resources are, the more opportunities and information they could obtain. Financial capital and social resources provided strong support and guarantee for herdsmen to develop diversified livelihood activities [13]. The long-term stable trust relationship could strengthen their awareness of grassland protection and promote their common willingness of protecting grassland and reducing the scale of breeding [16]. Based on this, the following assumptions were proposed in this study:H3: when other factors control, the richer the social capital of herdsmen is, the more likely they are to choose to reduce the scale of production.Material capital is the essential means of production for herdsmen maintaining their livelihood. When the material capital is abundant, the family’s livelihood burden would be kept at a low level, and then the scale of livestock would be reduced. For example, Xie et al. [16] pointed out that the herdsman families with relatively large breeding scale, who would initiatively reduce the quantity of livestock and had less economic losses, were more likely to reduce the animal husbandry scale. Based on this, the following assumptions were proposed in this study:H4: when other factors are controlled, the richer the material capital of herdsmen is, the more likely the herdsmen are to choose to reduce the production behavior of breeding scale.Financial capital is the synthesis of all cash and cashable funds in the process of production and consumption. The higher the family income was, the larger the proportion of mutton sheep breeding was, and the lower the possibility of expanding the breeding scale was [3]. The gradual increase of herdsman’s family’s economic income represented the enhancement of their livelihood level, and the burden of enhancing their livelihood level through traditional animal husbandry would become smaller [17]. According to this, the following assumptions were proposed in this study:H5: when controlling other factors, the richer the herdsmen’s financial capital is, the more likely they are to choose to reduce the scale of production.


## 2.3. Environmental Cognition and Production Behavior

There was a natural basis for the subject who utilizes resources, but it was more restricted by the society (the group norms, value orientation, cultural tradition, and other aspects). The cognitive differences of the resource utilization theme on social policies and different types of geographical environment had more or less influence on their behavior patterns [11]. In the process of policy cognition, the more herdsmen understood the grassland reward and subsidy policy, the higher their satisfaction with the policy is and the lower the possibility of broadening the breeding scale is. In the ecological cognition, the more fully herdsmen understood the ecological environment of the nearby grassland, the less they would expand the breeding scale [17]. On this basis, the following assumptions are proposed in this study:H6: when other factors are controlled, the higher the level of environmental cognition is, the more likely the herdsmen are to choose the production behavior of reducing the breeding scale.


## 3. Description of Data Source and Variable

### 3.1. Data Source

The data of this study came from the field survey conducted in Wuchuan County and Qinglong County of Guizhou Province from October 2019 to March 2021. The reason why the two places were chosen for the study was that they were the southern modern grassland ecological animal husbandry demonstration counties vigorously built by Guizhou Province. The two local governments had been sticking to the bottom line of ecological development, focusing on the poverty alleviation of industry, strengthening the quality of livestock and poultry products and farmers’ benefit, changing the mode of industrial development, and fully promoting the healthy and rapid development of ecological animal husbandry. In this study, 434 households were investigated, including 273 households in Wuchuan County, accounting for 62.9%, and 161 households in Qinglong County, accounting for 37.1%. A total of 434 questionnaires were sent out, of which 384 were valid, with an effective rate of 88.48%.


### 3.2. Description of Variable

#### 3.2.1. Explained Variables

This study used the statistical method on the change of breeding scale [17] for reference and utilized the change rate of breeding scale to express the breeding scale changes (Breed), recording “a” equal to the number of mutton sheep in 2018 minus the number of mutton sheep in 2017. When “a” was less than −0.2, it showed that the breeding scale had been reduced a lot and assigned 5; when −0.2 ≤ “a” < −0.05, it represented that the breeding scale had been reduced a little and assigned 4; when −0.05 ≤ “a” < −0.05, it showed that the breeding scale had not been changed and assigned 3, and so on.


#### 3.2.2. Explanatory Variables

This study carried out analysis from five different dimensions: material capital, natural capital, human capital, social capital, and financial capital. From the perspective of human capital (Human), the health status, average level of education, and the number of family labor force were selected as the measurement indicators [15]. From the perspective of natural capital (Natural), grassland quality and grassland area were selected as the main measurement indicators [16]. From the perspective of material capital (Mat), the number of mutton sheep, household appliances, housing structure, and the numbers of scientific and technological products were selected as a measure [18]. In terms of social capital (Social), the social network relationship, village cadre experience, and cooperative participation were selected as reference. In terms of financial capital (Finan), this study selected total family income and credit capital as the measure [15, 19].


#### 3.2.3. Control Variables

From the perspective of policy cognition (Policy), it referred to the policy cognition researches [20, 21], covering herdsmen’s familiarity with reward and subsidy policies and their satisfaction with relevant policies. For ecological environment cognition (Env), it referred to the definition of environmental cognition researches [22], covering grassland ecological change cognition, and grassland degradation cognition of herdsmen is shown in Table 1.Table 1
Meaning of relevant variables and statistical results.
VariablesVariable definition and assignmentMean valueVarianceChange of breeding scalehad been reduced a lot = 5had been reduced a little = 4 had not been changed = 3 had been increased some = 2 had been increased a lot = 12.631.37Gender of intervieweeMale = 1, female = 00.390.46Age of intervieweeAge of interviewee36.5812.21Health status of interviewees“Excellent” = 5“Good” = 4 “Average” = 3 “Bad” = 2 “Worse” = 1 “Incapacity to work” = 01.830.91Education level of the interviewee“College degree or above” = 5“High school education” = 4 “Junior high school education” = 3 “Primary school education” = 2 “Illiteracy” = 12.091.14Number of family labor forceNumber of family labor force2.520.93Total household income in 2018(Total household income in 2018 − mean value)/mean value0.000.76Credit situationAccess to credit: access to loans from commercial banks, rural credit cooperatives, and other organizationsYes = 1; No = 00.120.28Grassland areaFamily owned grassland area4.383.76Grassland qualityExcellent = 5Good = 4 Average = 3 Bad = 2 Worse = 11.670.95Number of mutton sheepTotal number of domestic mutton sheep in 2018108.3494.52Housing structureSoil mixing = 1Wood mixing = 2 Brick = 3 One floor frame structure = 4 Two floors frame structure = 52.261.01Number of household appliances and technology productsOne type = 1Two types = 2 Three types = 3Four types = 4Over five types = 52.452.12Relationship with relatives and friendsWorse = 1Bad = 2 General = 3 Good = 4 Very close = 53.213.48Experience of village cadresYes = 1No = 00.060.16Cooperative participationYes = 1No = 00.120.41Policy cognitionVery familiar with the bonus and subsidy policy = 5Quite understanding = 4 General understanding = 3 Quite not understanding = 2 Have no idea = 13.182.27Satisfaction with grassland subsidy policy, very satisfied = 5Relatively satisfied = 4 Generally satisfied = 3 Relatively dissatisfied = 2 Disappointed = 13.091.58Cognition of ecological environmentFences make the breeding less transferred and make the grassland under great ecological pressureVery disagree = 1 Less agree = 2 Average = 3 Quite agree = 4 Very agree = 53.312.19


#### 3.2.4. Empirical Model

The empirical model used in the study is as follows:(1)Breed=a0+a1∗Human+a2∗Natural+a3∗Mat+a4∗Social+a5∗Finan+ε,(2)Breed=a0+a1∗Human+a2∗Natural+a3∗Mat+a4∗Social+a5∗Finan+a6∗Policy+a7∗Env+ε.


### 3.3. Description of Sample

The basic information of herdsmen is shown in Table2 via the statistical analysis of 384 limited samples. In the 384 limited samples, the proportion of female samples is relatively large, reaching 66.66%, which might because women were the main labor force of family breeding. From the perspective of herdsmen’s age characteristics, about 68% of herdsmen are mainly 30–50 years old, indicating that the family breeding was mainly for middle-aged and young people. In terms of the education level of herdsmen, herdsmen’s educational level was generally low. There are more than half of herdsmen with primary school culture and below, while only 95 herdsmen have the culture of high school and above. In terms of the number of mutton sheep breeding, more than half of the herdsmen’s families have the number of mutton sheep concentrated in 100–300, accounting for 57.55%. According to the statistics of family income in 2018, the proportion of income in 50000–70000 yuan is the highest, accounting for 40.36%.Table 2
Basic characteristics of samples.
CharacteristicsSample characteristics classificationNumbersProportion (%)Gender of respondentsMale12833.33Female25666.66Age of respondentsLess than 30 years old3127.1230–40 years old11630.2040–50 years old14537.7650–60 years old6917.97Over 60 years old235.99Education level of respondentsIlliteracy5113.28Primary school14437.50Junior high school9424.48High school6416.67College degree or above318.07Scale of breeding (number of mutton sheep)Less than 1005614.58100–20011730.47200–30010427.08300–4007542.45More than 4003213.28Family income in 2018Less than ￥1000112.86￥10000–30000348.85￥30000–5000013234.38￥50000–7000015540.36More than ￥700005213.54


## 3.1. Data Source

The data of this study came from the field survey conducted in Wuchuan County and Qinglong County of Guizhou Province from October 2019 to March 2021. The reason why the two places were chosen for the study was that they were the southern modern grassland ecological animal husbandry demonstration counties vigorously built by Guizhou Province. The two local governments had been sticking to the bottom line of ecological development, focusing on the poverty alleviation of industry, strengthening the quality of livestock and poultry products and farmers’ benefit, changing the mode of industrial development, and fully promoting the healthy and rapid development of ecological animal husbandry. In this study, 434 households were investigated, including 273 households in Wuchuan County, accounting for 62.9%, and 161 households in Qinglong County, accounting for 37.1%. A total of 434 questionnaires were sent out, of which 384 were valid, with an effective rate of 88.48%.


## 3.2. Description of Variable

### 3.2.1. Explained Variables

This study used the statistical method on the change of breeding scale [17] for reference and utilized the change rate of breeding scale to express the breeding scale changes (Breed), recording “a” equal to the number of mutton sheep in 2018 minus the number of mutton sheep in 2017. When “a” was less than −0.2, it showed that the breeding scale had been reduced a lot and assigned 5; when −0.2 ≤ “a” < −0.05, it represented that the breeding scale had been reduced a little and assigned 4; when −0.05 ≤ “a” < −0.05, it showed that the breeding scale had not been changed and assigned 3, and so on.


### 3.2.2. Explanatory Variables

This study carried out analysis from five different dimensions: material capital, natural capital, human capital, social capital, and financial capital. From the perspective of human capital (Human), the health status, average level of education, and the number of family labor force were selected as the measurement indicators [15]. From the perspective of natural capital (Natural), grassland quality and grassland area were selected as the main measurement indicators [16]. From the perspective of material capital (Mat), the number of mutton sheep, household appliances, housing structure, and the numbers of scientific and technological products were selected as a measure [18]. In terms of social capital (Social), the social network relationship, village cadre experience, and cooperative participation were selected as reference. In terms of financial capital (Finan), this study selected total family income and credit capital as the measure [15, 19].


### 3.2.3. Control Variables

From the perspective of policy cognition (Policy), it referred to the policy cognition researches [20, 21], covering herdsmen’s familiarity with reward and subsidy policies and their satisfaction with relevant policies. For ecological environment cognition (Env), it referred to the definition of environmental cognition researches [22], covering grassland ecological change cognition, and grassland degradation cognition of herdsmen is shown in Table 1.Table 1
Meaning of relevant variables and statistical results.
VariablesVariable definition and assignmentMean valueVarianceChange of breeding scalehad been reduced a lot = 5had been reduced a little = 4 had not been changed = 3 had been increased some = 2 had been increased a lot = 12.631.37Gender of intervieweeMale = 1, female = 00.390.46Age of intervieweeAge of interviewee36.5812.21Health status of interviewees“Excellent” = 5“Good” = 4 “Average” = 3 “Bad” = 2 “Worse” = 1 “Incapacity to work” = 01.830.91Education level of the interviewee“College degree or above” = 5“High school education” = 4 “Junior high school education” = 3 “Primary school education” = 2 “Illiteracy” = 12.091.14Number of family labor forceNumber of family labor force2.520.93Total household income in 2018(Total household income in 2018 − mean value)/mean value0.000.76Credit situationAccess to credit: access to loans from commercial banks, rural credit cooperatives, and other organizationsYes = 1; No = 00.120.28Grassland areaFamily owned grassland area4.383.76Grassland qualityExcellent = 5Good = 4 Average = 3 Bad = 2 Worse = 11.670.95Number of mutton sheepTotal number of domestic mutton sheep in 2018108.3494.52Housing structureSoil mixing = 1Wood mixing = 2 Brick = 3 One floor frame structure = 4 Two floors frame structure = 52.261.01Number of household appliances and technology productsOne type = 1Two types = 2 Three types = 3Four types = 4Over five types = 52.452.12Relationship with relatives and friendsWorse = 1Bad = 2 General = 3 Good = 4 Very close = 53.213.48Experience of village cadresYes = 1No = 00.060.16Cooperative participationYes = 1No = 00.120.41Policy cognitionVery familiar with the bonus and subsidy policy = 5Quite understanding = 4 General understanding = 3 Quite not understanding = 2 Have no idea = 13.182.27Satisfaction with grassland subsidy policy, very satisfied = 5Relatively satisfied = 4 Generally satisfied = 3 Relatively dissatisfied = 2 Disappointed = 13.091.58Cognition of ecological environmentFences make the breeding less transferred and make the grassland under great ecological pressureVery disagree = 1 Less agree = 2 Average = 3 Quite agree = 4 Very agree = 53.312.19


### 3.2.4. Empirical Model

The empirical model used in the study is as follows:(1)Breed=a0+a1∗Human+a2∗Natural+a3∗Mat+a4∗Social+a5∗Finan+ε,(2)Breed=a0+a1∗Human+a2∗Natural+a3∗Mat+a4∗Social+a5∗Finan+a6∗Policy+a7∗Env+ε.


## 3.2.1. Explained Variables

This study used the statistical method on the change of breeding scale [17] for reference and utilized the change rate of breeding scale to express the breeding scale changes (Breed), recording “a” equal to the number of mutton sheep in 2018 minus the number of mutton sheep in 2017. When “a” was less than −0.2, it showed that the breeding scale had been reduced a lot and assigned 5; when −0.2 ≤ “a” < −0.05, it represented that the breeding scale had been reduced a little and assigned 4; when −0.05 ≤ “a” < −0.05, it showed that the breeding scale had not been changed and assigned 3, and so on.


## 3.2.2. Explanatory Variables

This study carried out analysis from five different dimensions: material capital, natural capital, human capital, social capital, and financial capital. From the perspective of human capital (Human), the health status, average level of education, and the number of family labor force were selected as the measurement indicators [15]. From the perspective of natural capital (Natural), grassland quality and grassland area were selected as the main measurement indicators [16]. From the perspective of material capital (Mat), the number of mutton sheep, household appliances, housing structure, and the numbers of scientific and technological products were selected as a measure [18]. In terms of social capital (Social), the social network relationship, village cadre experience, and cooperative participation were selected as reference. In terms of financial capital (Finan), this study selected total family income and credit capital as the measure [15, 19].


## 3.2.3. Control Variables

From the perspective of policy cognition (Policy), it referred to the policy cognition researches [20, 21], covering herdsmen’s familiarity with reward and subsidy policies and their satisfaction with relevant policies. For ecological environment cognition (Env), it referred to the definition of environmental cognition researches [22], covering grassland ecological change cognition, and grassland degradation cognition of herdsmen is shown in Table 1.Table 1
Meaning of relevant variables and statistical results.
VariablesVariable definition and assignmentMean valueVarianceChange of breeding scalehad been reduced a lot = 5had been reduced a little = 4 had not been changed = 3 had been increased some = 2 had been increased a lot = 12.631.37Gender of intervieweeMale = 1, female = 00.390.46Age of intervieweeAge of interviewee36.5812.21Health status of interviewees“Excellent” = 5“Good” = 4 “Average” = 3 “Bad” = 2 “Worse” = 1 “Incapacity to work” = 01.830.91Education level of the interviewee“College degree or above” = 5“High school education” = 4 “Junior high school education” = 3 “Primary school education” = 2 “Illiteracy” = 12.091.14Number of family labor forceNumber of family labor force2.520.93Total household income in 2018(Total household income in 2018 − mean value)/mean value0.000.76Credit situationAccess to credit: access to loans from commercial banks, rural credit cooperatives, and other organizationsYes = 1; No = 00.120.28Grassland areaFamily owned grassland area4.383.76Grassland qualityExcellent = 5Good = 4 Average = 3 Bad = 2 Worse = 11.670.95Number of mutton sheepTotal number of domestic mutton sheep in 2018108.3494.52Housing structureSoil mixing = 1Wood mixing = 2 Brick = 3 One floor frame structure = 4 Two floors frame structure = 52.261.01Number of household appliances and technology productsOne type = 1Two types = 2 Three types = 3Four types = 4Over five types = 52.452.12Relationship with relatives and friendsWorse = 1Bad = 2 General = 3 Good = 4 Very close = 53.213.48Experience of village cadresYes = 1No = 00.060.16Cooperative participationYes = 1No = 00.120.41Policy cognitionVery familiar with the bonus and subsidy policy = 5Quite understanding = 4 General understanding = 3 Quite not understanding = 2 Have no idea = 13.182.27Satisfaction with grassland subsidy policy, very satisfied = 5Relatively satisfied = 4 Generally satisfied = 3 Relatively dissatisfied = 2 Disappointed = 13.091.58Cognition of ecological environmentFences make the breeding less transferred and make the grassland under great ecological pressureVery disagree = 1 Less agree = 2 Average = 3 Quite agree = 4 Very agree = 53.312.19


## 3.2.4. Empirical Model

The empirical model used in the study is as follows:(1)Breed=a0+a1∗Human+a2∗Natural+a3∗Mat+a4∗Social+a5∗Finan+ε,(2)Breed=a0+a1∗Human+a2∗Natural+a3∗Mat+a4∗Social+a5∗Finan+a6∗Policy+a7∗Env+ε.


## 3.3. Description of Sample

The basic information of herdsmen is shown in Table2 via the statistical analysis of 384 limited samples. In the 384 limited samples, the proportion of female samples is relatively large, reaching 66.66%, which might because women were the main labor force of family breeding. From the perspective of herdsmen’s age characteristics, about 68% of herdsmen are mainly 30–50 years old, indicating that the family breeding was mainly for middle-aged and young people. In terms of the education level of herdsmen, herdsmen’s educational level was generally low. There are more than half of herdsmen with primary school culture and below, while only 95 herdsmen have the culture of high school and above. In terms of the number of mutton sheep breeding, more than half of the herdsmen’s families have the number of mutton sheep concentrated in 100–300, accounting for 57.55%. According to the statistics of family income in 2018, the proportion of income in 50000–70000 yuan is the highest, accounting for 40.36%.Table 2
Basic characteristics of samples.
CharacteristicsSample characteristics classificationNumbersProportion (%)Gender of respondentsMale12833.33Female25666.66Age of respondentsLess than 30 years old3127.1230–40 years old11630.2040–50 years old14537.7650–60 years old6917.97Over 60 years old235.99Education level of respondentsIlliteracy5113.28Primary school14437.50Junior high school9424.48High school6416.67College degree or above318.07Scale of breeding (number of mutton sheep)Less than 1005614.58100–20011730.47200–30010427.08300–4007542.45More than 4003213.28Family income in 2018Less than ￥1000112.86￥10000–30000348.85￥30000–5000013234.38￥50000–7000015540.36More than ￥700005213.54


## 4. Process of Empirical Analysis

### 4.1. Research Methods

In this study, 384 valid questionnaires were collected and analyzed by SPSS 23.0, and the impact of material capital, natural capital, human capital, social capital, financial capital, environmental cognition, and relevant measurement indexes on herdsmen’s production activities was analyzed by using Stata 14.0 mathematical statistics software and logistic model.


### 4.2. Empirical Analysis

#### 4.2.1. Impact of Sustainable Livelihood Capital on Herdsmen’s Production Behaviors

In order to verify the rationality of the hypothesis, the logistic model was used to implement regression analysis of the human capital, social capital, material capital, natural capital, and financial capital in the sustainable livelihood of herdsmen’s families, so as to test the impact of various herdsmen families’ livelihood capital on herdsmen production behaviors. The regression analysis results are shown in Table3.Table 3
The regression results of the sustainable livelihood capital of the family to the scale of breeding.
VariablesCoefficientOdds ratioStandard deviationZ valueNatural capital2.1625∗∗∗11.294310.16743.21Human capital3.0125∗∗14.652113.36922.26Physical capital3.2618∗∗∗24 .120323.46703.25Financial capital2.3243∗∗∗12.873911.52182.71Social capital3.3267∗∗∗27.182425.64293.39Constant terms8.673∗∗∗0 .00110.00114.98Logarithm likelihood value−232.1246Chi-square value61.2051∗∗∗Pseudo Ｒ20.1531Sample size384Note.∗,∗∗,∗∗∗ indicate that they have passed the significance test at the statistical level of 10%, 5%, and 1%, respectively.According to the regression results in Table3, it can be seen that all the sustainable livelihood capital of the family has passed the significance test, which showed that the sustainable livelihood of the family did have an important impact on the production behavior of mutton sheep. It preliminarily verified the previous research’s hypothesis and illustrated that the natural capital variable in the sustainable livelihood had a positive correlation with the improvement of the breeding scale of herdsmen. Meanwhile, the finance capital, social capital, material capital, and human capital all had a positive correlation with limiting herdsmen’s breeding scale. The social capital variable of livelihood capital could have the most vital impact on herdsmen’s breeding scale output, followed by material capital, while the natural capital had the least impact on herdsmen’s breeding scale.


#### 4.2.2. Regression Analysis of the Sustainable Livelihood of Herdsmen’s Families and Environmental Cognitive Level on Herdsmen’s Production Behaviors

The impact of livelihood capital on herdsmen’s production behaviors can be seen in Table3. Next, we utilized Stata 14.0 software to incorporate the environmental cognition of control variables into the model for regression analysis, and the analysis results are shown in Table 4. Model 1 did not include the environmental cognition level of control variables into the analysis results, while model 2 was the results after the environmental cognition level had been included. According to the regression results in Table 4, comparing the results of model 2 with those of model 1, it is obvious that the goodness of fit, logarithmic likelihood, and chi-square values of model 2 are all better than those of model 1, so it is necessary to analyze the regression results of model 2.(1)
In terms of natural capital, grassland area had a significant positive effect on herdsmen’s production behavior of raising breeding scale, and the effect of grassland quality on herdsmen’s production behavior had not been verified. The reason for this might be that the size of grassland area was a vital factor affecting the grassland’s bearing capacity. If the larger the grassland area owned by herdsmen is, the greater the bearing capacity of their grassland would be, herdsmen might be willing to increase the number of breeding, and the willingness to increase the scale of breeding would become stronger. Because the quality of their own grassland was not compared with other factors through the comparative analysis, there was no clear judgment on the quality of the grassland, so the influence of the quality of the grassland on the production behavior of the herdsmen is not significant, so H1 had been partially verified.(2)
In terms of human capital, all indicators of human capital had passed the verification, and the number of labor force, education level, and health status had a significant positive impact on herdsmen’s choice to reduce breeding scale. The reason might be that the richer the herdsmen’s family labor force was, the higher their education level was, the better their health status was, the more herdsmen choose to go out to work in cities, the more optimistic their income would be, and the lower their dependence on the income from animal husbandry would become. In addition, with the deterioration of grassland ecological environment and the continuous reduction of the income from animal husbandry in recent years, herdsmen with rich human capital may choose to restrain the breeding scale in production decision making so as to reduce their excessive dependence on animal husbandry income so as to improve their living standards by seeking other livelihood channels; thus H2 had been fully verified.(3)
In terms of social capital, cooperative participation, village cadres experience, and social network relationship had significant positive effects on herdsmen’s production behavior of reducing breeding scale. Perhaps it was because herdsmen had established close relationship networks with their relatives and friends after years of production activities. These networks could help herdsmen capture market, policy, environment, and other information related to animal husbandry timely and accurately, thus establishing a long-term and stable trust relationship. It was easy to form a common willingness of control breeding scale for protecting grassland and improving ecology. If the herdsman was a village cadre, his production behavior in animal husbandry would play a demonstration role for other herdsmen, especially when he chose to restrain the scale of animal husbandry and reduce the dependence of animal husbandry income. The cooperative members could realize the exchange and sharing of information and resources, and the production behavior of members would be affected by the unified planning, management, and production of cooperatives. And H3 had been fully verified.(4)
In terms of material capital, the number of mutton sheep and housing structure had a significant positive impact on herdsmen’s production behavior of reducing breeding scale among the indicators of material capital. The reason might be that the grassland ecology had been deteriorating in recent years, in which the overgrazing of herdsmen was the main cause of grassland degradation. If the number of mutton sheep was relatively large, the possibility of overgrazing would be greater, so the production behavior of reducing the scale of breeding would be actively chosen and the housing structure of herdsmen could fully reflect them. If the housing conditions were good, the livelihood level was good. This kind of situation might be due to the fact that herdsmen’s families did not need to rely solely on breeding to obtain the corresponding economic income, and their income channels were diversified, so they would choose to reduce the production behavior of breeding scale, so H4 had been partially verified.(5)
In terms of financial capital, it was found that only the total household income had passed the test, and other measurement indicators had not been verified, through the analysis of regression results. After analysis, it might be that the level of family income was a direct reflection of herdsmen’s livelihood. Herdsmen with higher total family income meant that the less likely they were to over rely on traditional farming, the less likely their farming income would have an impact on the level of family livelihood, so the more likely they were to choose to reduce the number of farms. In addition, herdsmen with higher family income were more willing to enjoy high quality life and excellent grassland ecology, so as to reduce the number of livestock, increase the grassland ecological quality, and improve the quality of life, which was partially verified by H5.(6)
In terms of environmental cognition level, the policy cognition and ecological environment cognition were used as control variables to analyze in model 2. The results showed that policy cognition and ecological environment cognition had significant positive effects on herdsmen’s inhibition of breeding scale. On the one hand, it might be that the scale of mutton sheep breeding had been kept at a relatively high level in recent years. With the full implementation of relevant national award and subsidy policies, the livelihood pressure of herdsmen had been greatly relieved. In addition, the regulatory function of government agencies had resulted in the reduction of the scale of mutton sheep breeding. On the other hand, it might be affected by the national development strategy. At present, the state had made great efforts to build ecological civilization and increase environmental protection. The level of grassland ecological cognition of herdsmen had been significantly improved. The herdsmen with higher ecological cognition had stronger willingness to promote grassland restoration by restraining the scale of breeding, so H5 had been fully verified.Table 4
Regression results of livelihood capital and environmental cognition measurement indexes on Herdsmen’s production behavior.
VariablesModel 1Model 2CoefficientOR valueCoefficientOR valueNatural capitalGrassland area0.1241∗∗∗∗0.85240.1218∗∗0.8463Grassland quality0.26720.73280.25810.7134Physical capitalQuantity of mutton sheep0.0031∗∗∗1.00320.0027∗∗∗1.003Housing structure0.3216∗∗∗1.00350.3209∗∗∗1.0032Number of household appliances and technology products−0.01240.8946−0.012320.8938Human capitalNumber of family labor force0.3074∗∗∗1.29890.3185∗∗∗1.2996Average level of education0.0618∗∗1.06390.0671∗∗1.0712Health status0.0214∗1.02130.0219∗1.0239Social capitalExperience of village cadres0.2689∗∗∗0.92410.2516∗∗∗0.9048Cooperative participation0.3217∗∗∗1.30410.3025∗∗∗1.2897Social network relationship0.2864∗∗∗1.14310.2691∗∗∗1.0956Financial capitalFamily income in 20180.1542∗∗∗1.24630.0857∗∗∗1.0925Credit situation−0.03280.89550.02490.9141Control variablePolicy cognition0.2416∗∗∗1.2861Cognition of ecological environment0.3512∗∗∗1.4276Constant term−2.4618∗∗∗0.0127∗∗∗Log likelihood value−224.1568−187.2105Chi-square value87.9700∗∗∗132.6900∗∗∗Pseudo R20.16810.2415Sample size384384Note.∗,∗∗,∗∗∗ indicate that they have passed the significance test at the statistical level of 10%, 5%, and 1%, respectively.


## 4.1. Research Methods

In this study, 384 valid questionnaires were collected and analyzed by SPSS 23.0, and the impact of material capital, natural capital, human capital, social capital, financial capital, environmental cognition, and relevant measurement indexes on herdsmen’s production activities was analyzed by using Stata 14.0 mathematical statistics software and logistic model.


## 4.2. Empirical Analysis

### 4.2.1. Impact of Sustainable Livelihood Capital on Herdsmen’s Production Behaviors

In order to verify the rationality of the hypothesis, the logistic model was used to implement regression analysis of the human capital, social capital, material capital, natural capital, and financial capital in the sustainable livelihood of herdsmen’s families, so as to test the impact of various herdsmen families’ livelihood capital on herdsmen production behaviors. The regression analysis results are shown in Table3.Table 3
The regression results of the sustainable livelihood capital of the family to the scale of breeding.
VariablesCoefficientOdds ratioStandard deviationZ valueNatural capital2.1625∗∗∗11.294310.16743.21Human capital3.0125∗∗14.652113.36922.26Physical capital3.2618∗∗∗24 .120323.46703.25Financial capital2.3243∗∗∗12.873911.52182.71Social capital3.3267∗∗∗27.182425.64293.39Constant terms8.673∗∗∗0 .00110.00114.98Logarithm likelihood value−232.1246Chi-square value61.2051∗∗∗Pseudo Ｒ20.1531Sample size384Note.∗,∗∗,∗∗∗ indicate that they have passed the significance test at the statistical level of 10%, 5%, and 1%, respectively.According to the regression results in Table3, it can be seen that all the sustainable livelihood capital of the family has passed the significance test, which showed that the sustainable livelihood of the family did have an important impact on the production behavior of mutton sheep. It preliminarily verified the previous research’s hypothesis and illustrated that the natural capital variable in the sustainable livelihood had a positive correlation with the improvement of the breeding scale of herdsmen. Meanwhile, the finance capital, social capital, material capital, and human capital all had a positive correlation with limiting herdsmen’s breeding scale. The social capital variable of livelihood capital could have the most vital impact on herdsmen’s breeding scale output, followed by material capital, while the natural capital had the least impact on herdsmen’s breeding scale.


### 4.2.2. Regression Analysis of the Sustainable Livelihood of Herdsmen’s Families and Environmental Cognitive Level on Herdsmen’s Production Behaviors

The impact of livelihood capital on herdsmen’s production behaviors can be seen in Table3. Next, we utilized Stata 14.0 software to incorporate the environmental cognition of control variables into the model for regression analysis, and the analysis results are shown in Table 4. Model 1 did not include the environmental cognition level of control variables into the analysis results, while model 2 was the results after the environmental cognition level had been included. According to the regression results in Table 4, comparing the results of model 2 with those of model 1, it is obvious that the goodness of fit, logarithmic likelihood, and chi-square values of model 2 are all better than those of model 1, so it is necessary to analyze the regression results of model 2.(1)
In terms of natural capital, grassland area had a significant positive effect on herdsmen’s production behavior of raising breeding scale, and the effect of grassland quality on herdsmen’s production behavior had not been verified. The reason for this might be that the size of grassland area was a vital factor affecting the grassland’s bearing capacity. If the larger the grassland area owned by herdsmen is, the greater the bearing capacity of their grassland would be, herdsmen might be willing to increase the number of breeding, and the willingness to increase the scale of breeding would become stronger. Because the quality of their own grassland was not compared with other factors through the comparative analysis, there was no clear judgment on the quality of the grassland, so the influence of the quality of the grassland on the production behavior of the herdsmen is not significant, so H1 had been partially verified.(2)
In terms of human capital, all indicators of human capital had passed the verification, and the number of labor force, education level, and health status had a significant positive impact on herdsmen’s choice to reduce breeding scale. The reason might be that the richer the herdsmen’s family labor force was, the higher their education level was, the better their health status was, the more herdsmen choose to go out to work in cities, the more optimistic their income would be, and the lower their dependence on the income from animal husbandry would become. In addition, with the deterioration of grassland ecological environment and the continuous reduction of the income from animal husbandry in recent years, herdsmen with rich human capital may choose to restrain the breeding scale in production decision making so as to reduce their excessive dependence on animal husbandry income so as to improve their living standards by seeking other livelihood channels; thus H2 had been fully verified.(3)
In terms of social capital, cooperative participation, village cadres experience, and social network relationship had significant positive effects on herdsmen’s production behavior of reducing breeding scale. Perhaps it was because herdsmen had established close relationship networks with their relatives and friends after years of production activities. These networks could help herdsmen capture market, policy, environment, and other information related to animal husbandry timely and accurately, thus establishing a long-term and stable trust relationship. It was easy to form a common willingness of control breeding scale for protecting grassland and improving ecology. If the herdsman was a village cadre, his production behavior in animal husbandry would play a demonstration role for other herdsmen, especially when he chose to restrain the scale of animal husbandry and reduce the dependence of animal husbandry income. The cooperative members could realize the exchange and sharing of information and resources, and the production behavior of members would be affected by the unified planning, management, and production of cooperatives. And H3 had been fully verified.(4)
In terms of material capital, the number of mutton sheep and housing structure had a significant positive impact on herdsmen’s production behavior of reducing breeding scale among the indicators of material capital. The reason might be that the grassland ecology had been deteriorating in recent years, in which the overgrazing of herdsmen was the main cause of grassland degradation. If the number of mutton sheep was relatively large, the possibility of overgrazing would be greater, so the production behavior of reducing the scale of breeding would be actively chosen and the housing structure of herdsmen could fully reflect them. If the housing conditions were good, the livelihood level was good. This kind of situation might be due to the fact that herdsmen’s families did not need to rely solely on breeding to obtain the corresponding economic income, and their income channels were diversified, so they would choose to reduce the production behavior of breeding scale, so H4 had been partially verified.(5)
In terms of financial capital, it was found that only the total household income had passed the test, and other measurement indicators had not been verified, through the analysis of regression results. After analysis, it might be that the level of family income was a direct reflection of herdsmen’s livelihood. Herdsmen with higher total family income meant that the less likely they were to over rely on traditional farming, the less likely their farming income would have an impact on the level of family livelihood, so the more likely they were to choose to reduce the number of farms. In addition, herdsmen with higher family income were more willing to enjoy high quality life and excellent grassland ecology, so as to reduce the number of livestock, increase the grassland ecological quality, and improve the quality of life, which was partially verified by H5.(6)
In terms of environmental cognition level, the policy cognition and ecological environment cognition were used as control variables to analyze in model 2. The results showed that policy cognition and ecological environment cognition had significant positive effects on herdsmen’s inhibition of breeding scale. On the one hand, it might be that the scale of mutton sheep breeding had been kept at a relatively high level in recent years. With the full implementation of relevant national award and subsidy policies, the livelihood pressure of herdsmen had been greatly relieved. In addition, the regulatory function of government agencies had resulted in the reduction of the scale of mutton sheep breeding. On the other hand, it might be affected by the national development strategy. At present, the state had made great efforts to build ecological civilization and increase environmental protection. The level of grassland ecological cognition of herdsmen had been significantly improved. The herdsmen with higher ecological cognition had stronger willingness to promote grassland restoration by restraining the scale of breeding, so H5 had been fully verified.Table 4
Regression results of livelihood capital and environmental cognition measurement indexes on Herdsmen’s production behavior.
VariablesModel 1Model 2CoefficientOR valueCoefficientOR valueNatural capitalGrassland area0.1241∗∗∗∗0.85240.1218∗∗0.8463Grassland quality0.26720.73280.25810.7134Physical capitalQuantity of mutton sheep0.0031∗∗∗1.00320.0027∗∗∗1.003Housing structure0.3216∗∗∗1.00350.3209∗∗∗1.0032Number of household appliances and technology products−0.01240.8946−0.012320.8938Human capitalNumber of family labor force0.3074∗∗∗1.29890.3185∗∗∗1.2996Average level of education0.0618∗∗1.06390.0671∗∗1.0712Health status0.0214∗1.02130.0219∗1.0239Social capitalExperience of village cadres0.2689∗∗∗0.92410.2516∗∗∗0.9048Cooperative participation0.3217∗∗∗1.30410.3025∗∗∗1.2897Social network relationship0.2864∗∗∗1.14310.2691∗∗∗1.0956Financial capitalFamily income in 20180.1542∗∗∗1.24630.0857∗∗∗1.0925Credit situation−0.03280.89550.02490.9141Control variablePolicy cognition0.2416∗∗∗1.2861Cognition of ecological environment0.3512∗∗∗1.4276Constant term−2.4618∗∗∗0.0127∗∗∗Log likelihood value−224.1568−187.2105Chi-square value87.9700∗∗∗132.6900∗∗∗Pseudo R20.16810.2415Sample size384384Note.∗,∗∗,∗∗∗ indicate that they have passed the significance test at the statistical level of 10%, 5%, and 1%, respectively.


## 4.2.1. Impact of Sustainable Livelihood Capital on Herdsmen’s Production Behaviors

In order to verify the rationality of the hypothesis, the logistic model was used to implement regression analysis of the human capital, social capital, material capital, natural capital, and financial capital in the sustainable livelihood of herdsmen’s families, so as to test the impact of various herdsmen families’ livelihood capital on herdsmen production behaviors. The regression analysis results are shown in Table3.Table 3
The regression results of the sustainable livelihood capital of the family to the scale of breeding.
VariablesCoefficientOdds ratioStandard deviationZ valueNatural capital2.1625∗∗∗11.294310.16743.21Human capital3.0125∗∗14.652113.36922.26Physical capital3.2618∗∗∗24 .120323.46703.25Financial capital2.3243∗∗∗12.873911.52182.71Social capital3.3267∗∗∗27.182425.64293.39Constant terms8.673∗∗∗0 .00110.00114.98Logarithm likelihood value−232.1246Chi-square value61.2051∗∗∗Pseudo Ｒ20.1531Sample size384Note.∗,∗∗,∗∗∗ indicate that they have passed the significance test at the statistical level of 10%, 5%, and 1%, respectively.According to the regression results in Table3, it can be seen that all the sustainable livelihood capital of the family has passed the significance test, which showed that the sustainable livelihood of the family did have an important impact on the production behavior of mutton sheep. It preliminarily verified the previous research’s hypothesis and illustrated that the natural capital variable in the sustainable livelihood had a positive correlation with the improvement of the breeding scale of herdsmen. Meanwhile, the finance capital, social capital, material capital, and human capital all had a positive correlation with limiting herdsmen’s breeding scale. The social capital variable of livelihood capital could have the most vital impact on herdsmen’s breeding scale output, followed by material capital, while the natural capital had the least impact on herdsmen’s breeding scale.


## 4.2.2. Regression Analysis of the Sustainable Livelihood of Herdsmen’s Families and Environmental Cognitive Level on Herdsmen’s Production Behaviors

The impact of livelihood capital on herdsmen’s production behaviors can be seen in Table3. Next, we utilized Stata 14.0 software to incorporate the environmental cognition of control variables into the model for regression analysis, and the analysis results are shown in Table 4. Model 1 did not include the environmental cognition level of control variables into the analysis results, while model 2 was the results after the environmental cognition level had been included. According to the regression results in Table 4, comparing the results of model 2 with those of model 1, it is obvious that the goodness of fit, logarithmic likelihood, and chi-square values of model 2 are all better than those of model 1, so it is necessary to analyze the regression results of model 2.(1)
In terms of natural capital, grassland area had a significant positive effect on herdsmen’s production behavior of raising breeding scale, and the effect of grassland quality on herdsmen’s production behavior had not been verified. The reason for this might be that the size of grassland area was a vital factor affecting the grassland’s bearing capacity. If the larger the grassland area owned by herdsmen is, the greater the bearing capacity of their grassland would be, herdsmen might be willing to increase the number of breeding, and the willingness to increase the scale of breeding would become stronger. Because the quality of their own grassland was not compared with other factors through the comparative analysis, there was no clear judgment on the quality of the grassland, so the influence of the quality of the grassland on the production behavior of the herdsmen is not significant, so H1 had been partially verified.(2)
In terms of human capital, all indicators of human capital had passed the verification, and the number of labor force, education level, and health status had a significant positive impact on herdsmen’s choice to reduce breeding scale. The reason might be that the richer the herdsmen’s family labor force was, the higher their education level was, the better their health status was, the more herdsmen choose to go out to work in cities, the more optimistic their income would be, and the lower their dependence on the income from animal husbandry would become. In addition, with the deterioration of grassland ecological environment and the continuous reduction of the income from animal husbandry in recent years, herdsmen with rich human capital may choose to restrain the breeding scale in production decision making so as to reduce their excessive dependence on animal husbandry income so as to improve their living standards by seeking other livelihood channels; thus H2 had been fully verified.(3)
In terms of social capital, cooperative participation, village cadres experience, and social network relationship had significant positive effects on herdsmen’s production behavior of reducing breeding scale. Perhaps it was because herdsmen had established close relationship networks with their relatives and friends after years of production activities. These networks could help herdsmen capture market, policy, environment, and other information related to animal husbandry timely and accurately, thus establishing a long-term and stable trust relationship. It was easy to form a common willingness of control breeding scale for protecting grassland and improving ecology. If the herdsman was a village cadre, his production behavior in animal husbandry would play a demonstration role for other herdsmen, especially when he chose to restrain the scale of animal husbandry and reduce the dependence of animal husbandry income. The cooperative members could realize the exchange and sharing of information and resources, and the production behavior of members would be affected by the unified planning, management, and production of cooperatives. And H3 had been fully verified.(4)
In terms of material capital, the number of mutton sheep and housing structure had a significant positive impact on herdsmen’s production behavior of reducing breeding scale among the indicators of material capital. The reason might be that the grassland ecology had been deteriorating in recent years, in which the overgrazing of herdsmen was the main cause of grassland degradation. If the number of mutton sheep was relatively large, the possibility of overgrazing would be greater, so the production behavior of reducing the scale of breeding would be actively chosen and the housing structure of herdsmen could fully reflect them. If the housing conditions were good, the livelihood level was good. This kind of situation might be due to the fact that herdsmen’s families did not need to rely solely on breeding to obtain the corresponding economic income, and their income channels were diversified, so they would choose to reduce the production behavior of breeding scale, so H4 had been partially verified.(5)
In terms of financial capital, it was found that only the total household income had passed the test, and other measurement indicators had not been verified, through the analysis of regression results. After analysis, it might be that the level of family income was a direct reflection of herdsmen’s livelihood. Herdsmen with higher total family income meant that the less likely they were to over rely on traditional farming, the less likely their farming income would have an impact on the level of family livelihood, so the more likely they were to choose to reduce the number of farms. In addition, herdsmen with higher family income were more willing to enjoy high quality life and excellent grassland ecology, so as to reduce the number of livestock, increase the grassland ecological quality, and improve the quality of life, which was partially verified by H5.(6)
In terms of environmental cognition level, the policy cognition and ecological environment cognition were used as control variables to analyze in model 2. The results showed that policy cognition and ecological environment cognition had significant positive effects on herdsmen’s inhibition of breeding scale. On the one hand, it might be that the scale of mutton sheep breeding had been kept at a relatively high level in recent years. With the full implementation of relevant national award and subsidy policies, the livelihood pressure of herdsmen had been greatly relieved. In addition, the regulatory function of government agencies had resulted in the reduction of the scale of mutton sheep breeding. On the other hand, it might be affected by the national development strategy. At present, the state had made great efforts to build ecological civilization and increase environmental protection. The level of grassland ecological cognition of herdsmen had been significantly improved. The herdsmen with higher ecological cognition had stronger willingness to promote grassland restoration by restraining the scale of breeding, so H5 had been fully verified.Table 4
Regression results of livelihood capital and environmental cognition measurement indexes on Herdsmen’s production behavior.
VariablesModel 1Model 2CoefficientOR valueCoefficientOR valueNatural capitalGrassland area0.1241∗∗∗∗0.85240.1218∗∗0.8463Grassland quality0.26720.73280.25810.7134Physical capitalQuantity of mutton sheep0.0031∗∗∗1.00320.0027∗∗∗1.003Housing structure0.3216∗∗∗1.00350.3209∗∗∗1.0032Number of household appliances and technology products−0.01240.8946−0.012320.8938Human capitalNumber of family labor force0.3074∗∗∗1.29890.3185∗∗∗1.2996Average level of education0.0618∗∗1.06390.0671∗∗1.0712Health status0.0214∗1.02130.0219∗1.0239Social capitalExperience of village cadres0.2689∗∗∗0.92410.2516∗∗∗0.9048Cooperative participation0.3217∗∗∗1.30410.3025∗∗∗1.2897Social network relationship0.2864∗∗∗1.14310.2691∗∗∗1.0956Financial capitalFamily income in 20180.1542∗∗∗1.24630.0857∗∗∗1.0925Credit situation−0.03280.89550.02490.9141Control variablePolicy cognition0.2416∗∗∗1.2861Cognition of ecological environment0.3512∗∗∗1.4276Constant term−2.4618∗∗∗0.0127∗∗∗Log likelihood value−224.1568−187.2105Chi-square value87.9700∗∗∗132.6900∗∗∗Pseudo R20.16810.2415Sample size384384Note.∗,∗∗,∗∗∗ indicate that they have passed the significance test at the statistical level of 10%, 5%, and 1%, respectively.


## 5. Conclusion

Based on the data of 384 herdsmen in Wuchuan and Qinglong of Guizhou Province, this study made an empirical analysis of the impact of environmental awareness and sustainable livelihood capital on Herdsmen’s farming activities and finally drew the following conclusions:(1)
Among the factors influencing herdsmen’s choice of production behavior, social capital played the most important role in promoting herdsmen’s choice of reducing the number and scale of breeding and then human capital, material capital, and financial capital, but natural capital had a certain role in promoting herdsmen’s production behavior of expanding the scale of breeding.(2)
Among all kinds of measurement indicators involved in livelihood capital, cooperatives, village cadres, housing structure, livestock breeding scale, the number of labor force, health status, education level, and family income all had significant roles in promoting herdsmen’s choice to inhibit the production behavior of breeding scale. The grassland area and grassland quality of natural capital could improve herdsmen’s breeding scale remarkably.(3)
The environmental cognition of herdsmen had significant positive effect on the scale of inhibition. In the measurement indicators of environmental cognition, policy cognition, and ecological environment cognition had vital positive effects on Herdsmen’s choice to reduce the breeding scale, so the impact of herdsmen’s environmental cognition level on their choice of production behavior could not be ignored.Based on the above conclusions and discussions, we believe that we should solve the problem of single livelihood of herdsmen, strengthen the publicity and protection of environmental protection knowledge, build a perfect ecological compensation mechanism, let herdsmen share the external benefits of ecological protection, and encourage herdsmen to actively participate in the response of ecological protection behavior.In addition, this study also has the following limitations, which need to be improved in the future. First, the research data in this paper belong to cross-sectional survey data, which can not dynamically track the research samples and continuously observe the production behavior of herdsmen. Second, this study mainly focuses on the impact of sustainable livelihoods on herdsmen production behavior, but the external institutional environment may also have an important impact, such as business environment and market development degree, which need to be discussed in the future



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*Source: 4278331-2022-04-13.xml*