Human Activities and Ecological Security

Impact of Agricultural Labor Transfer on Agricultural Nonpoint Source Pollution: A Case Study of Jiangxi, China

  • ZHANG Peiwen ,
  • LU Hua , * ,
  • CHEN Yijing ,
  • SHU Cheng , *
Expand
  • Institute of Ecological Civilization, Jiangxi University of Finance and Economics, Nanchang 330013, China
* LU Hua, E-mail:;
SHU Cheng, E-mail:

ZHANG Peiwen, E-mail:

Received date: 2020-08-04

  Accepted date: 2020-11-30

  Online published: 2021-07-30

Supported by

The National Natural Science Foundation of China(71803071)

The National Natural Science Foundation of China(72063014)

The Natural Science Foundation of Jiangxi Province(20181BAB211006)

Humanities and Social Sciences Foundation in Ministry of Education of China(20YJC790014)

The Humanities and Social Science Foundation of Jiangxi Province(JJ20204)

Abstract

A large proportion of the rural labor force in China will continue to transfer to non-agricultural sectors in the near future, which will inevitably lead to the transformation of the agricultural production mode and the structure of the farmers’ livelihood. The Chinese government is making great efforts to govern agricultural nonpoint source pollution (ANSP), and farmers' environmental behavior is a key factor that must be considered in the formulation of agricultural environmental policies. Based on a set of micro survey data on farmers in the study area and econometric methods, this study investigates the impact of agricultural labor transfer on ANSP by considering the substitution effect of agricultural factors and the effect of agricultural economies of scale. The results show that the increase of the agricultural labor force will not be conducive to reducing ANSP, while the income increase brought by agricultural labor transfer will improve the input structure of agricultural factors and have a positive impact on ANSP reduction. Government departments should provide subsidies or incentive measures to help agricultural social service organizations to expand their coverage and increase the frequency of socialized agricultural services, in order to guide farmers in the use of environment-friendly agricultural technology to reduce the ANSP caused by agricultural factors at the source. Furthermore, it is necessary to facilitate the development of small-sized agricultural machinery suitable for small-area land cultivation.

Cite this article

ZHANG Peiwen , LU Hua , CHEN Yijing , SHU Cheng . Impact of Agricultural Labor Transfer on Agricultural Nonpoint Source Pollution: A Case Study of Jiangxi, China[J]. Journal of Resources and Ecology, 2021 , 12(3) : 358 -366 . DOI: 10.5814/j.issn.1674-764x.2021.03.005

1 Introduction

China's urbanization process is accelerating, and the agricultural labor force will inevitably transfer to the urban and non-agricultural sectors. During the 13th Five-Year Plan period of China, urban and rural areas will continue to have an active floating population. By 2020, the floating population of China will have gradually increased to 291 million, of which the total agricultural transfer population will account for 220 million, and family migration will continue to increase (China's migrant population development report, 2016). The high level of agricultural labor transfer has greatly promoted the rapid growth of non-agricultural sectors of the economy but has also deepened the aging of the agricultural labor force and increased the number of women involved, while the overall agricultural labor supply is decreasing. Agriculture not only has a strong dependence on the natural ecological environment but also impacts it. The input of agricultural production factors has produced environmental externalities, and the adverse impact of agricultural labor transfer on the environment has gradually emerged.
Farmers' environmental behavior is a key factor that must be considered in the formulation of agricultural environmental policies because it is directly related to their implementation cost. Under the current rural system in China, effectively guiding farmers' good environmental behavior and motivating them to voluntarily participate in environmental governance is the key to solving agricultural environmental problems, and any environmental policies that lack the participation of farmers would lessen their motivation and willingness to protect the environment (Wang, 1999; Greiner and Gregg, 2011; Lu et al., 2020). Luo et al. (2020) used the DID model to investigate the mechanism by which environmental policies influenced chemical fertilizer pollution in major grain producing areas, and found that the effect of environmental policies on reducing chemical fertilizer pollution was mainly due to the expansion of farmers' planting scale. China's environmental constraints are tightening, and it is inevitable that agricultural modernization will improve the agricultural ecological environment by improving the allocation structure of agricultural factor inputs. In general, the externalities of agricultural production will inevitably appear if property rights are not clear (Coarse, 1959, 1960), and the multifunctional nature of agricultural systems means that agricultural production activities not only produce positive externalities, but also produce negative externalities which often have the characteristics of imperceptibility, time lag and uncertainty, such as ANSP (Pretty and Frank, 2000).
Agricultural labor transfer is a rational choice for farmers pursuing income maximization. Will such behavior necessarily lead to environmental degradation? The existing research has not reached consensus on this issue. According to the farmer behavior theory, as the economic entity that pursues profit and utility maximization, farmers' resource endowments have a strong influence on their behavioral decision-making; and when their behavior is motivated by the moral goals such as fairness and altruism, it can reduce negative externalities to the environment (Singh et al., 1986; Colman, 1994). Some scholars have pointed out that agricultural labor transfer can alleviate the predicaments of agricultural production and further improve the technical efficiency of the food production environment (Tian and Zhu, 2018). However, farmers' economic behavior, at the micro level, is the direct cause of agricultural environmental pollution (Hu, 1997), and this effect may vary among farmers with different farm scales (Yao et al., 2017). Luan et al. (2020) used the Spatial Durbin Model to analyze the impact of labor transfer on fertilizer pollution, and found that labor transfer has a positive direct effect and a spatial spillover effect on fertilizer pollution, and also that the indirect spillover effect is greater than the direct effect. Based on 2000-2016 provincial data in China, Shao and Li (2020) used a Spatial Panel Model and found that labor transfer had a significant impact on agricultural pollution by changing the proportions of agricultural livelihood capital and cultivated land, however, Luo et al. (2020) discovered that the promotion of labor transfer and the expansion of farm scale are conducive to achieving the reduction of ANSP of chemical fertilizers through environmental policies.
ANSP refers to the pollution of the water environment caused by nutrients such as nitrogen and phosphorus, pesticides and other organic or inorganic pollutants through surface runoff and farmland leakage during agricultural production activities, mainly including chemical fertilizer pollution, pesticide pollution, centralized-breeding factory pollution, domestic sewage and garbage pollution. ANSP is the most widely distributed non-point source pollution at present and has become the primary source of pollution for the deterioration of the water environment quality in China. Recent efforts for controlling the pollutants caused by livestock and poultry farming through the regulation and supervision of large-scale livestock and poultry aquaculture have achieved remarkable results.
The excessive application of chemical fertilizers is an important cause of ANSP in China (First National Pollution Source Survey Report, 2014). According to 2015 data from the Food and Agriculture Organization of the United Nations (FAO), the total nitrogen input in China's food production in 2015 was 228.48 kg ha-1, which is 3.7 times the world average of 61.89 kg ha-1 and 2.9 times the total nitrogen application amount of 77.46 kg ha-1 in the United States. The application intensity of chemical fertilizer in China is 1.6 times higher than the world average. In 2015, the utilization rate of chemical fertilizer for major crops in China was 35.2%, and it is forecasted to reach 40% by 2020. The inefficient application of chemical fertilizer is a common problem, which also leads to its excessive application (Agricultural Modernization Plan (2016-2020)). Shi et al. (2016) also concluded that the amount of chemical fertilizer applied in China's grain production exceeds the optimal economic application rate. The degrees of excessive fertilization in corn, wheat and rice production are 50.74%, 27.26% and 24.67%, respectively, based on a compilation of the cost-benefit data for these agricultural products over ten years.
Land, capital and labor are fungible to some extent in agricultural production. According to the theory of induced change, the relative scarcity of an effective agricultural labor force will induce farmers to make adaptive adjustments, such as saving relatively scarce resources and pursuing the minimum cost and maximum profit. How does the factor substitution generated by agricultural labor transfer influence ANSP? Most studies have found that labor transfer reduces the labor supply for agricultural production. Farmers increasingly want to improve the marginal productivity of labor; thus they tend to reduce the number of fertilization applications while increasing the amount of fertilizer applied each time to avoid yield loss and reduce risk in the context of increasing labor costs (Calhoun, 1989; Horowitz and Lichtenberg, 1993; Abdoulaye and Sanders, 2005; Jepson, 2005; Gong et al., 2010; Hu and Yang, 2015). Driven by time constraints and economic interests, farmers no longer rely on intensive farming, as they did predominantly in the past. Instead, they rely excessively on the input of modern factors such as chemical fertilizers (Ebenstein et al., 2011; Willinmson, 2011; Chang and Mishra, 2012; Pan, 2014). Some scholars believe that with the continuous transfer of the agricultural labor force, an increasing amount of land will be transferred for the cultivation of cash crops that demand more fertilizer (Peng et al., 2008; Xin et al., 2012). The increase in non-agricultural income also reduces farmers' financial constraints, allowing them to purchase more agricultural production materials and leading to more intensive fertilization (He et al., 2006; Huang et al., 2008; Ebenstein, 2012). Some studies have pointed out that young and educated farmers are more likely to accept agricultural environmental protection policies, so the transfer of a large number of young and middle-aged laborers will lead to an overall decline of farmers' awareness of ecological and environmental protection, which will hinder the promotion of environment friendly technologies such as soil testing formulas (Zhang, 2008; Vanslembrouck et al., 2012). Wei et al. (2012) considered the defects and shortcomings of China's existing agricultural land property rights system to be an important institutional source of ANSP. Different property rights systems will lead to different resource utilization behaviors. However, while an effective land property rights system means rationalizing people's economic behaviors, Wei et al. (2012) did not quantitatively test these behaviors from the micro level of the farmers.
Environmental pollution is a serious problem in China, and efforts have been made to govern ANSP. Agricultural labor transfer brought about a change in farmers' agricultural production behaviors and ultimately produced ANSP as an externality. Yet, what is the underlying influencing mechanism? What are the results of micro quantitative research? The existing literature on this issue is still relatively lacking. Therefore, in order to systematically analyze the impact of agricultural labor transfer on ANSP, and based on externality theory and induced change theory, this study demonstrates the mechanism of labor transfer on ANSP in China from the perspective of the factor substitution effect and the economies of scale effect, and verifies that mechanism by using micro survey data. The conclusions of this study have extremely important reference value for the control of ANSP in China against the background of the continuous agricultural labor transfer. The structure of this paper is as follows. First, the mechanism through which agricultural labor force transfer impacts ANSP is systematically analyzed, and an econometric model is constructed. Second, data sources are presented, and the key descriptive statistics of the data are provided. Finally, the results and conclusions are presented and discussed.

2 Mechanism analysis

Agricultural environmental problems occur when technological and institutional changes lag behind changes in resource endowments. The theory of induced change argues that a change in the relative scarcity of resources will lead to adaptive technology selection and encourage organizational systems to use relatively abundant resources. Land, labor and capital are all substitutable to some extent in agricultural production. Motivated by profit maximization, farmers will reconfigure agricultural factors according to the changes in their prices. In essence, agricultural labor transfer brings about changes in the structure of agricultural factors and ultimately causes ANSP as a negative externality.
(1) Mechanism 1: Substitution effect
First, agricultural labor transfer reduces the amount of labor that farmers can access for agricultural production. When machinery is difficult to use at a large scale (for example, in hilly and mountainous areas), farmers tend to reduce the number of fertilization applications and increase the amount of chemical fertilizer applied each time to compensate for the adverse effect of the labor shortage, leading to excessive or inefficient use of the fertilizers and increasing ANSP. Second, the increase in non-agricultural income due to agricultural labor transfer increases household income. On the one hand, this increased income reduces the capital constraints on purchasing agricultural fertilizer, and the amount of fertilizer applied may increase. On the other hand, the increase in household income will weaken the dependence of farmers on agricultural production which may reduce the application of fertilizer. Third, the increase in total household income will enhance farmers' ability to resist risks, and the planting structure may shift from single-growing food crops to cash crops with greater fertilizer demands, driving an increase in chemical fertilizer application. Finally, as a form of natural production and a part of social reproduction, agriculture has a higher risk and higher uncertainty in terms of yield, and farmers tend toward risk aversion. The additional input of chemical fertilizers has become an important way for farmers to avoid risks and ensure stable agricultural yields.
(2) Mechanism 2: Economies of scale effect
As an important part of deepening China's rural reform, the transfer of agricultural labor improves the ratio of rural labor to land and promotes the development of a market for the transfer of farmland management rights; therefore, agricultural production has shown a trend toward large-scale farmland management. First, the integrity and stability of agricultural land property rights have been continuously improved as China's rural reform has advanced. Agricultural land in China has gradually shifted from low-efficiency farmers to become more concentrated among high-efficiency farmers, and agricultural production factors have improved in the direction of Pareto optimality. Second, the transfer of farmland management rights has brought about the expansion of farm size and the birth of a series of modes for organizing modernized agricultural production. Scaling the operations of agricultural land will reduce the marginal cost of factor inputs, which may reduce ANSP. However, the transfer of farmland management rights objectively causes a difference in land property in terms of contracted land and transferred land. The negative externalities of agricultural production will inevitably occur when the land property rights are not clear and exclusive (Corse, 1959, 1960), and will eventually cause ANSP. The analysis framework is shown in Fig. 1:
Fig. 1 Mechanism for the impact of agricultural labor transfer on ANSP

3 Material and methodology

3.1 Model

To quantitatively measure the impact of agricultural labor transfer on ANSP, the following econometric model was constructed:
${{Y}_{i}}={{\delta }_{i0}}+{{\delta }_{i1}}agrlabor+{{\beta }_{i}}{{X}_{i}}+{{\mu }_{i}} \left( i=1,...,n \right)$
where, Yi is ANSP of a farmer, which has the characteristics of dispersion, randomness, and difficulty in monitoring and quantifying; agrlabor is family farming labor; Xi is the vector of family characteristic variables and the vector of land characteristic variables—such as the proportion of household non-agricultural income in total income; the age, education and health of the household head; the area dedicated to growing grain; the marketization of grain grown; whether there is a nearby agricultural fertilization service organization; terrain conditions of the grain-growing area; and availability of agricultural technology training. μi is the random disturbance term; δ0, δ1, and β are the regression coefficients that need to be estimated, and i indicates an individual in the selected sample. At present, it is difficult to control the application of fertilizers, and soil and water have a limited ability to conserve fertilizers; the output of nitrogen into water bodies is thus relatively high. Since the excessive application of chemical fertilizers is an important cause of ANSP in China (First National Pollution Source Survey Report), this paper uses the “excessive nitrogen” index for farmers' agricultural production to quantitatively measure ANSP. Excess nitrogen is the difference between the amount of nitrogen input and the amount required by the crop as quantitatively determined by nutrient balance theory. The formula for calculating this excess (Y) is as follows:
$Y=total\_N-need\_N$
where, total_N represents the nitrogen introduced by farmers using chemical fertilizers, and need_N represents the nutrients required for the crops to achieve normal economic yields( The data were extracted from the section “ The Amounts of Nutrients (Nutrient Coefficient) Required to Produce 100 kg of Major Field Crops” in the book “Principles and Technology of Fertilization” which was produced under the supervision of Tan (2011) as a textbook. Specifically, the nutrient coefficients are 3 for wheat, 2.57 for corn, 2.3 for rice, 5 for cotton, 0.45 for potatoes, 7.2 for soybeans, 0.19 for sugar cane, 5.8 for rapeseed, 4.1 for tea, 0.3 for apples, 0.47 for pears, 0.4 8 for peaches, 0.3 for field vegetables, and 0.3 for field gourds, respectively.). It should be noted that this paper does not intend to accurately measure the total excess nitrogen in farmers' agricultural production but only to analyze farmers' behavior under the context of agricultural labor transfer. Livestock is mainly affected by capital, and the nitrogen emissions from manure are not included in the calculation; further, the nitrogen contributions from soil foundation fertility, agricultural films and irrigation water are not taken into account due to data limitations.

3.2 Data

Jiangxi Province (Fig. 2) is a major grain producing area located in southeastern China. The total area of cultivated land in the province is 3.08×104 km2, accounting for 18.48% of the total land area in China. The problem of ANSP in Jiangxi Province is quite serious and the government has adopted many stringent ANSP control measures and other policies. In addition, the phenomenon of agricultural labor transfer in Jiangxi Province is also obvious throughout the country. Therefore, while this study is based on this particular area, it has important reference value for the national control of ANSP. The data used in this study are derived from the microdata of farmers from rural fixed observation points in Jiangxi Province of China in 2014. The data were extracted by stratified random sampling( Stratified random sampling was one of the random sampling methods. For example: Nanchang County in Jiangxi Province has a total of 13 towns, which were sorted into 2 groups according to the area of cultivated land. Then, one town was randomly selected from the 2 groups. In the same way, villages belonging to each town were divided into two groups, then one village was randomly selected from each group.) from 60 villages in 20 counties in Jiangxi Province, including Guangfeng County, Leping County, Duchang County, Taihe County, Anfu County, Yongfeng County, Wanan County, Shanggao County, Wanzhai County, Zhangshu County, Nanchang County, Jinxian County, Xinjian County, Le'an County, Dongxiang County, Xinfeng County, Ganxian County, Huichang County, Ruijin City, and Xinfeng County. The sample data comprehensively include factors such as the region, topographical features, and economic conditions.
The questionnaire mainly includes the following aspects: 1) the condition of grain production infrastructure, such as whether the cultivated land has a road for mechanical plows, the irrigation conditions, whether there is an agricultural service organization in the village or nearby, and the topographical conditions of the grain-growing area; 2) factor inputs, outputs and sales of agricultural production products, such as fertilizer, pesticides, seed, labor, grain yields and sales; and 3) agricultural technology training, such as multiple agricultural technology trainings in one year and willingness of farmers to participate in agricultural technology training. To ensure the quality of the questionnaire, its content was revised several times during a pre-investigation trial. The formal investigation was conducted through face-to-face interviews between the investigator and the farmers. The investigator administered the questionnaire on behalf of the study. After the survey was completed, the questionnaire was collected, and a total of 436 valid questionnaires were obtained.

3.3 Statistics

Table 1 shows the descriptive statistics for each variable. Excessive nitrogen is very common in the sample area, and the excessive application of chemical fertilizers is also common. This finding is consistent with the conclusions of Qiu et al. (2014), who stated that China's fertilizer application per unit of cultivated land has far exceeded both the global average level and the optimal amount and that it continues to show a clear upward trend. The average number of family agricultural laborers is 2, and the effective agricultural labor supply is insufficient. More than half of total household income comes from nonagricultural income, and thus agricultural income is no longer the main source of income for the families (Cai, 2016). Approximately 40% of all grain was sold; so, while it was mainly grown for family use in the sample areas, the proportion of grain that is sold is increasing. In addition, there are few agricultural fertilization service organizations in or near the villages in the sample areas, and the agricultural service market is still developing. Few farmers are participating in agricultural technology training, and agricultural production is relying more on tradition and less on modern agricultural technologies. The grain-growing areas are mainly hilly and mountainous areas with poor topography and irrigation conditions. The average farm size is approximately 0.37 ha, and land fragmentation is high, which limits potential economies of scale.

4 Results

Stata13.0 (StataCorp LLC, College Station, TX, USA) software was used for the empirical analysis. To control for heteroscedasticity, autocorrelation and the possible influence of outliers, robust estimation was used for the regression. The F-test indicates significance at the 1% level, and the fit result of the model is good and shows that the model has strong explanatory power. The mean VIF is 1.11, and the model can be considered to be free of multicollinearity problems. The R2 value is 0.125, and the result also shows a certain explanatory power for the cross-sectional data. In general, a correlation analysis is required when analyzing the causal relationship between two variables. However, Spearman statistics can only reflect the correlation between the two variables, but they fail to prove the causal relationship between the two variables. On the contrary, if a causal relationship exists between the two variables, there must be a correlation between them. The specific regression results and Spearman statistics are shown in Table 2.
Table 1 Descriptive statistics of the variables
Variables Assignment Mean Std. Dev.
Excess nitrogen The amount of nitrogen input minus the amount of crop nutrients required 105.9 193.87
Number of agricultural laborers Person 1.93 0.85
Health of the head of household 1 = very good; 2 = good; 3 = general; 4 = bad 2.11 1.00
Non-agricultural income ratio Proportions of non-agricultural income in total income 0.52 0.36
Are irrigation conditions suitable for cultivated land? 0 = no; 1 = yes 0.56 0.50
Education of the head of household 0 = 0; 1 = primary school; 2 = junior high school;
3 = high school; 4 = university and above
1.40 0.82
Age of head of the household Years 52.28 11.62
Terrain conditions 1= plain; 2= mountain; 3 =hill 2.33 0.88
Farm size ha 0.37 0.92
Purpose of agricultural production Proportions of agricultural production for sale at market 0.42 0.40
Is there an agricultural fertilization service
organization in or near the village?
0= no; 1= yes 0.16 0.37
Number of times participating in agricultural
techniques training
Per year 0.19 0.59
Table 2 Regression results for relationship between agricultural labor transfer and ANSP
Variables Coef. Std. Dev. Spearman
Number of agricultural laborers 6.49 7.517 0.035
Health of the head of household 6.67 9.043 0.090*
Non-agricultural income ratio ‒90.08*** 25.751 ‒0.116**
Are irrigation conditions suitable for cultivated land? ‒18.87 18.635 ‒0.036
Education of the head of household 5.88 9.777 0.036
Age of the head of household 0.08 0.651 0.045
Terrain conditions 29.85*** 9.618 0.155***
Farm size 0.62 1.627 0.2669***
Purpose of agricultural production 80.00*** 24.711 0.037
Is there an agricultural fertilization service organization in or near the villages? ‒119.81*** 17.528 ‒0.309***
Number of times per year participating in agricultural techniques training ‒3.54 20.830 ‒0.149***
Constant 35.84 57.135
Observations 436
R2 0.125
VIF 1.11

Note: ***, ** and * represent 1%, 5% and 10% significance levels, respectively.

4.1 The impact of agricultural labor transfer on ANSP

The impact of the nonagricultural income ratio on excess nitrogen is significantly negative at 1%, that is, the higher the nonagricultural income ratio is, the less excess nitrogen is produced through agricultural production. Agricultural labor transfer is the result of the optimal allocation of rural household resources. The increase in the agricultural labor force will not be conducive to improving the agricultural environment during the promotion of agricultural modernization in China. In contrast, the nonagricultural transfer of agricultural labor will increase farmers' income, as well as the use of mechanization and other factors to replace labor input and improve the agricultural environment. Yao et al. (2017) also believe that the upgrading of the structure of agricultural production factors offers a significant positive externality affecting the environment, and the increase in farmers' agricultural income can improve agricultural environmental efficiency. The impact of the number of agricultural laborers on excess nitrogen is positive but not significant. To some extent, this result also indicates that the retention of agricultural laborers will not improve the agricultural environment and that only agricultural labor transfer can provide some conditions for improving ANSP. Zhong et al. (2016) also found that agricultural labor transfer will increase the grain acreage.
The effect of the marketization degree of grain planting on excess nitrogen is significantly positive at the 1% level. That is, when farmers grow grain mainly for sale, they pay less attention to the ANSP caused by fertilization in their pursuit of stable output, and in this context, excessive fertilization is very common. Under the condition that the market for agricultural products cannot effectively achieve both high quality and a good price in China, farmers will ultimately pursue higher output instead of quality in agricultural production, and this is bound to make it less likely that they will reduce fertilizer application. The influence of agricultural fertilization service organizations in or near villages on excessive nitrogen is significantly negative at the 1% level; that is, the positive external impact of the services provided by agricultural fertilization organizations significantly reduces the amount of fertilizer applied by farmers and improves the agricultural environment. This finding also indicates that the development of the agricultural socialized services promoted by agricultural labor transfer can improve farmers' agricultural factor input structure and the agricultural environment.

4.2 The impact of other control variables on ANSP

The impact of agricultural technology training on excessive nitrogen application is negative. The more often farmers attend agricultural technology training, the higher the probability that they correctly apply fertilizer and the lower the inefficiency of their fertilizer applications. Thus, expanding the area of agricultural socialized services, increasing the number of services or increasing agricultural technology training for farmers will be conducive to improving the efficiency of agricultural factor inputs, alleviating the extensive management of agricultural production caused by an insufficient supply of agricultural labor, and thus ultimately improving ANSP. The effect of the age of the head of the household on excess nitrogen is positive; that is, the older the head of the household is, the more excess nitrogen will be used. The phenomenon of aging in agricultural production in China is serious, and the constraints of topography mean that machinery is unable to effectively replace labor. The tendency of farmers to use more fertilizer to alleviate the shortage in the agricultural labor supply will increase. As a part of natural production and social reproduction, agriculture has highly uncertain yields, and farmers have strong risk aversion, especially the aging farmers in China's hilly and mountainous areas. The input of additional chemical fertilizer has become an important means for farmers to avoid risks and ensure a stable agricultural yield, resulting in more fertilization and increasing ANSP.
The impact of farm size on excess nitrogen is positive but not significant, which is contrary to the conclusion of Lu and Xie (2018). Lu and Xie (2018) found that the change in farm size due to land transfer is beneficial for reducing the marginal cost of agricultural inputs and reducing the degree of ANSP based on data from the plains areas in China. However, in the hilly and mountainous areas in China, it is very difficult for farmers to transfer to the land adjacent to their contracted land in a single transaction due to the limitations of terrain and the higher transaction cost. Therefore, the scale management of farmland in these areas is difficult, and the economic benefit of scale fertilizer application is also not apparent. In general, to reduce the labor time between home and land, farmers tend to reduce the number of fertilizer applications and increase the amount of fertilizer applied each time, which not only reduces the effects of fertilization but also increases fertilizer waste and aggravates ANSP. In addition, the increase in nonagricultural wages and the inability of machinery to effectively replace labor reinforces the low returns on agriculture, making farmers more inclined to apply more fertilizer in an effort to reduce risks and ensure stable yields. The effect of terrain conditions on excess nitrogen was significantly positive at the 5% level. Land fragmentation is serious in the hilly and mountainous areas in China, and the small-scale dispersal of plots results in wasted time traveling between various plots, wasted land caused by plot boundaries, and wasted resources caused by leakage and evaporation during transportation. These unfavorable factors will increase the amount of chemical fertilizer applied by farmers.

5 Discussion

The environmental problems caused by agriculture have become increasingly serious in China, and efforts have been made to better manage ANSP. Effectively guiding farmers' environmental behavior and encouraging them to voluntarily participate in environmental governance is the key to solving agricultural environmental problems in China. Farmers are the first group to directly and profoundly experience the deterioration of the agricultural environment, and they are also the source of agricultural environmental protection. For many years, the government in China has focused only on the technical path and the effect of implementing controls on ANSP, but it has ignored the effect of farmers' behavior on governing agricultural environmental pollution. With the on-going nonagricultural transfer of agricultural laborers, the agricultural production mode and livelihood structure of farmers in China have undergone great changes, and farmers are now highly differentiated and heterogeneous. Scale farmers will become the main force in agricultural development in China and so they will be the main force driving the control of ANSP in the future. Therefore, the government should adopt relevant incentive measures for scale farmers and further strengthen education and training in environmentally friendly agricultural technology in order to reduce the ANSP caused by agricultural inputs at the source. In addition, the government should also actively guide scale farmers to participate in agricultural pollution control and strengthen their demonstration role in governing ANSP reduction.
Agricultural labor transfer will promote the development of agricultural socialized service organizations and provide farmers with agricultural services such as tillage, raising seedlings, fertilization, machine insertion, harvesting and transportation, thus alleviating the problems caused by the shortage in the agricultural labor supply. The government could provide subsidies or incentives for agricultural social service organizations to expand the coverage and frequency of their agricultural social services. The Chinese government is vigorously implementing a rural revitalization strategy which aims to increase farmers' enthusiasm for retaining land, especially under the continuous advancement of the “separation of three powers” over agricultural land and policy guarantees on the stability of land contract rights. Farmers' understanding of land property rights continues to improve, and their long-term expectations for the land and the income from land appreciation are increasing. Therefore, government departments can make full use of the rural revitalization strategy period and vigorously publicize the positive role of ANSP treatment. Farmers should be encouraged to participate in the treatment of ANSP, and the treatment effect could also be improved.
Farmers vary in their resource endowments, levels of environmental awareness and abilities to adapt to the changing market environment. The government should also pay attention to the differences between farmers, reduce governance costs and increase implementation efficiency. Future research can further group farmers, combine the characteristics of different types of farmers and the characteristics of agricultural production, determine the key factors in farmers' agricultural decisions, and provide theoretical support and a practical foundation for the control of ANSP. This study has some shortcomings. For example, the degree of nonagricultural employment could vary, or nonagricultural employment could occur in different locations, such as within townships, in towns outside the county, or elsewhere in the county or province, all of which would change the impact of agricultural labor transfer on ANSP. A detailed analysis can be conducted based on this perspective in order to provide more targeted suggestions for governing ANSP.

6 Conclusions

Based on the micro survey data of farmers and econometric methods, this study investigated the impact of agricultural labor transfer on ANSP considering the substitution effect of agricultural factors and the effect of agricultural economies of scale. The main conclusions are as follows.
Firstly, the increase of the agricultural labor force will not be conducive to improving the agricultural environment during the process of agricultural modernization in China. In contrast, the income increase brought by agricultural labor transfer will promote the upgrading of the input structure of agricultural production factors and improve the agricultural environment.
Secondly, expanding the coverage area or increasing the number of agricultural social service programs, and strengthening agricultural technology training for farmers are conducive to improving the efficiency of agricultural inputs and alleviating the extensive agricultural management caused by an insufficient supply of agricultural labor.
Thirdly, due to terrain restrictions, the transaction cost of farmland transfer in hilly and mountainous areas is high, the scale operation of agricultural land resulting from the transfer of agricultural labor is difficult, and the environmental effects of the agricultural land scale operation are not obvious.
Finally, at present, the grain-growing purpose of selling is not conducive to improving the agricultural environment (Lu et al., 2019). In the context that the market cannot achieve both good quality and good prices for agricultural products, the pursuit of yield will become a priority for agricultural production, and farmers will adopt an extensive mode of agricultural operation to maintain stable yields.
1
Abdoulaye T, Sanders J H . 2005. Stages and determinants of fertilizer use in semiarid African agriculture: The Niger experience. Agricultural Economics, 32(2):167-179.

DOI

2
Calhoun C . 1989. Estimating the distribution of desired family size and excess fertility. The Journal of Human Resources, 24(4):709-724.

DOI

3
Chang H H, Mishra A K . 2012. Chemical usage in production agriculture: Do crop insurance and off-farm work play a part? Journal of Environmental Management, 105:76-82.

DOI

4
Colman D . 1994. Ethics and externalities: Agricultural stewardship and other behaviour: Presidential address. Journal of Agricultural Economics, 45(3): 299‒311.

DOI

5
Corse R H . 1959. The federal communications commission. The Journal of Law and Economics, 2(1): 1‒40.

DOI

6
Corse R H . 1960. The problem of social cost. The Journal of Law and Economics, 3(1): 1‒44.

DOI

7
Ebenstein A . 2012. The consequences of industrialization: Evidence from water pollution and digestive cancers in China. Review of Economics and Statistics, 94(1):186-201.

DOI

8
Ebenstein A, Zhang J, McMillan M C , et al. 2011. Chemical fertilizer and migration in China. National Bureau of Economic Research, 17245:1-33.

9
Gong Q W, Mu X L, Tian Z H . 2010. Analysis of factors affecting farmers’ risk assessment and evasion ability of excessive fertilization—Based on questionnaire survey of 284 farmers in Jianghan Plain. Chinese Rural Economy, (10):66-76. (in Chinese)

10
Greiner R, Gregg D . 2011. Farmers’ intrinsic motivations, barriers to the adoption of conservation practices and effectiveness of policy instruments: Empirical evidence from northern Australia. Land Use Policy, 28(1):257-265.

DOI

11
He H R, Zhang L X, Li Q . 2006. Study on fertilization behavior of farmers and agricultural non-point source pollution. Journal of Agrotechnical Economics, (6): 2‒10. (in Chinese)

12
Horowitz J K, Lichtenberg E . 1993. Insurance, moral hazard, and chemical use in agriculture. American Journal of Agricultural Economics, 75(4):926-935.

DOI

13
Hu H, Yang Y B . 2015. Study on farmers’ fertilizer application from the perspective of factor substitution—Based on the National Rural Fixed Observation Point Farmers Data. Journal of Agrotechnical Economics, ( 3):84-90. (in Chinese)

14
Hu W . 1997. Household land tenure reform in China: Its impact on farming land use and agro-environment. Land Use Policy, 14(3): 175‒186.

DOI

15
Huang J, Hu R, Cao J , et al. 2008. Training programs and in-the-field guidance to reduce China’s overuse of fertilizer without hurting profitability. Journal of Soil and Water Conservation, 63(5): 165‒167.

16
Jepson W . 2005. A disappearing biome? Reconsidering land-cover change in the Brazilian savanna. The Geographical Journal, 171(2):99-111.

DOI

17
Lu H, Xie H L . 2018. Impact of changes in labor resources and transfers of land use rights on agricultural non-point source pollution in Jiangsu Province, China. Journal of Environmental Management, 207:134-140.

DOI

18
Lu H, Zhang P W, Hu H , et al. 2019. Effect of the grain-growing purpose and farm size on the ability of stable land property rights to encourage farmers to apply organic fertilizers. Journal of Environmental Management, 251:109621. DOI: 10.1016/j.jenvman.2019.109621.

DOI

19
Lu H, Hu L X, Zheng W W , et al. 2020. Impact of household land endowment and environmental cognition on the willingness to implement straw incorporation in China. Journal of Cleaner Production, 262:121479. DOI: 10.1016/j.jclepro.2020.121479.

DOI

20
Luo S X, He K, Zhang J B . 2020. The more grain production, the more fertilizers pollution? Empirical evidence from major grain-producing areas in China. Chinese Rural Economy, (1): 108‒131. (in Chinese)

21
Pan D . 2014. The spatial-temporal difference of driving effects for fertilizer use intensity changes and its determinants in China. Economic Geography, 34(3): 121‒126, 136. (in Chinese)

22
Peng H Y, Shi Z T, Liu X Y , et al. 2008. Analysis of infection in environment and farmers’ economical income with the change of growing structure of crops. Environmental Science and Management, (2): 44‒48. (in Chinese)

23
Pretty J, Frank B R . 2000. Participation and social capital formation in natural resource management: Achievements and lessons. Plenary paper for International Landcare 2000 Conference, March 2nd-5th 2000, Melbourne, Australia: The Tasmanian Landcare Association.

24
Qiu H G, Luan H, Li J , et al. 2014. The impact of risk aversion on farmers’ excessive fertilizer application behavior. Chinese Rural Economy, (3): 85‒96. (in Chinese)

25
Shao S, Li B L . 2020. Effects of rural labor transfer on rural environmental pollution in China: An empirical investigation based on spatial panel model. Journal of China University of Geosciences (Social Sciences Edition), 20(1): 39‒55. (in Chinese)

26
Shi C L, Guo Y, Zhu J F . 2016. Evaluation of over fertilization in China and its influencing factors. Research of Agricultural Modernization, 37(4): 671‒679. (in Chinese)

27
Singh I, Squire L, Strauss J. 1986. Agricultural household models: Extensions, applications, and policy. Washington DC, USA: Johns Hopkins University Press.

28
Tan J F. 2011. Principles and techniques of crop fertilization. Beijing, China: China Agricultural University Press. (in Chinese)

29
Tian H Y, Zhu Z Y . 2018. Rural labor migration, scale of operation and environmental technical efficiency of grain production. Journal of South China Agricultural University (Social Science Edition), 17(5): 69‒81. (in Chinese)

30
Vanslembrouck I, Huylenbroeck G, Verbeke W . 2002. Determinants of the willingness of Belgian farmers to participate in agri-environmental measures. Journal of Agricultural Economics, 53(3): 489‒511.

DOI

31
Wang Y S . 1999. Household responsibility system, behavior of farmers and environmental problems in China’s agriculture. Journal of Peking University (Philosophy and Social Sciences), 36(3): 44‒51. (in Chinese)

32
Wei X, Li S P, Zhang Z C , et al. 2012. Analysis of agricultural non-point source pollution behavior based on farmland property rights system. Rural Economy, (5): 108‒112. (in Chinese)

33
Xin L J, Li X B, Tan M H . 2012. Temporal and regional variations of China’s fertilizer consumption by crops during 1998‒2008. Journal of Geographical Sciences, 22(4): 643‒652.

DOI

34
Yao Z F, Tang H J, Liu X . 2017. Scale management behavior, externality and agricultural environmental efficiency. Finance and Economics, (12): 69‒83. (in Chinese)

35
Zhang F S. 2008. China fertilizer industry and scientific fertilization strategy research report. Beijing, China: China Agricultural University Press. (in Chinese)

36
Zhong F N, Lu W Y, Xu Z G . 2016. Does rural labor force go out for work go against grain production? Analysis of the behavior and constraint conditions of the substitution of factors and the adjustment of planting structure. Chinese Rural Economy, (7): 36‒47. (in Chinese)

Outlines

/