Drivers of farmers’ behavior toward compensation scheme for cultivated land protection in chengdu pilot area, China

Figures & data

Figure 1. The development of economic compensation policies for cultivated land protection in China.

Table 1. Four pilot economic incentive schemes for cultivated land protection in China

Regions	Time	Scheme	Subsidy recipient	Types of cultivated land to be subsidized	Compensation standard	Objective of the subsidy	Punishment measures
Chengdu	2008	Cultivated land protection fund (CLPF)	Farmers and village collectives	Prime farmland, general quality cultivated land	Prime farmland: 854 USD/ha per year. General quality cultivated land: 641 USD/ha per year.	Improve farmers’ enthusiasm and initiative to protect cultivated land (quantity, quality, and ecology)	Yes
Suzhou	2010	Ecological compensation	Farmers and village collectives	Cultivated land	Cultivated land: 854 USD/ha per year; rice fields (66.7–666.7 ha): (854 + 427) USD/ha per year; rice fields (more than 666.7 ha): (854 + 854) USD/ha per year.	protect the ecological functions of cultivated land	No
Guangdong	2012	Economic compensation for prime farmland protection	Village collectives	prime farmland	about 64 USD/ha per year; the standard should be adjusted every 3–5 years in combination with economic development.	Fully motivate the organizations of grassroots management to protect basic farmland	No
Zhejiang	2016	Compensation for cultivated land protection	Farmers and village collectives	Prime farmland, general quality cultivated land	Grassroot governments make their own decisions based on local economic levels and make adjustments every year.	Improve farmers’ enthusiasm and initiative toward protecting cultivated land	No

Figure 2. Research framework of this study.

note: the solid arrows denote the direct effects. the dotted arrows denote the indirect effects.

Figure 3. General situation in the study area and the distribution of samples.

note: the sub-figure (a) shows the location of the study area and sample distribution. the different colors in the sub-figure (b) denote land use types. the data for the administrative regions were provided by the resource and environment data cloud platform in 2015, and the data for land use types were provided by the resource and environment data cloud platform in 2018 (http://www.resdc.cn/).

Figure 4. Descriptive statistics of the variables of farmers’ characteristics.

Note: the black solid squares with horizontal lines above and below in sub-figure (c) denote the mean and standard deviation (SD), respectively. EL denotes farmers’ education level. LFS denotes labor force size. CLA denotes cultivated land area. FCLA denotes flowing out of cultivated land area. AAHI denotes average annual household income. TAAI denotes total annual agricultural income.

Figure 5. Descriptive statistics of farmers’ understanding of the CLPF.

Note: KW denotes farmers’ knowledge of the CLPF. SO denotes farmers’ overall satisfaction. OA denotes the degree of objectives achievement. IHI denotes the degree of impact on household income. FLSC denotes the degree of change in family’s living standards. IPS denotes the degree of impact on pension security.

Figure 6. Distribution of farmers’ behavior toward participating in the CLPF.

Note: TISR denotes farmers’ behavior in quantity protection. AFCSI denotes farmers’ behavior in quality protection. IEECL denotes farmers’ behavior in ecological environment protection.

Table 2. Correlation between farmers’ behavior and the influencing factors

Influencing Factors	Farmers’ Behavior
	Farmers’ behavior in quantity protection (TISR^a)	Farmers’ behavior in ecological environment protection (IEECL^b)	Farmers’ behavior in quality protection (AFCSI^a)
Farmers’ knowledge of the CLPF (KW)	0.218**	0.250**	0.166**
Farmers’ overall satisfaction (SO)	0.040	0.160**	0.122*
Degree of objectives achievement (OA)	0.200**	0.271**	0.114
Degree of impact on household income (IHI)	0.048	0.032	0.142*
Degree of change in family’s living standards (FLSC)	0.051	0.004	0.217**
Degree of impact on pension security (IPS)	−0.006	0.037	0.173**
Gender	−0.048	−0.115*	0.002
Age	−0.119*	−0.024	0.027
Education level (EL)	0.109	0.150**	0.017
Village cadres (VC)	0.046	0.176**	0.076
Labor force size (LFS)	−0.188**	−0.176**	−0.034
Cultivated land area (CLA)	0.095	−0.015	0.159**
Flowing out of cultivated land area (FCLA)	0.052	0.046	−0.303**
Average annual household income (AAHI)	0.127*	−0.043	0.100
Total annual agricultural income (TAAI)	−0.095	0.074	0.226**

* Significant at p < 0.05, ** Significant at p < 0.01. “a:” A Spearman’s rank-order correlation was selected because both TISR and AFCSI were binary variables. “b:” A Pearson correlation analysis was selected because IEECL was approximately normally distributed.

Table 3. Path coefficients between farmers’ behavior in farmland quantity protection and the influencing factors

Factors	Direct path coefficients	Indirect path coefficients
	→TISR	→KW	→OA	→LFS	→AAHI
KW	0.124	0.000	0.056	0.029	0.009
OA	0.135	0.051	0.000	−0.003	−0.013
LFS	−0.251	−0.015	0.001	0.000	0.079
AAHI	0.213	0.005	−0.008	−0.093	0.000

F-value = 10.052, P < 0.01, Adjusted R2 = 0.3306. “→” denotes the influence direction of the factors. TISR denotes farmers’ behavior in quantity protection. KW denotes farmers’ knowledge of the CLPF. OA denotes the degree of objectives achievement. LFS denotes labor force size. AAHI denotes average annual household income.

Table 4. Path coefficients between farmers’ behavior in farmland ecological environment protection and the influencing factors

Factors	Direct path coefficients	Indirect path coefficients
	→IEECL	→KW	→OA	→Gender	→VC	→LFS
KW	0.129	0.000	0.075	0.003	0.024	0.020
OA	0.180	0.053	0.000	0.008	0.031	−0.002
Gender	−0.113	−0.003	−0.013	0.000	0.023	−0.009
VC	0.151	0.020	0.037	−0.018	0.000	−0.014
LFS	−0.169	−0.015	0.002	−0.006	0.012	0.000

F-value = 10.268, P < 0.01, Adjusted R2 = 0.3685. “→” denotes the influence direction of the factors. IEECL denotes farmers’ behavior in ecological environment protection. KW denotes farmers’ knowledge of the CLPF. OA denotes the degree of objectives achievement. VC denotes village cadres. LFS denotes labor force size.

Table 5. Path coefficients between farmers’ behavior in farmland quality protection and the influencing factors

Factors	Direct path coefficients	Indirect path coefficients
	→AFCSI	→KW	→IPS	→CLA	→FCLA
KW	0.130	0.000	0.023	0.041	−0.027
IPS	0.140	0.021	0.000	0.071	−0.055
CLA	0.298	0.018	0.033	0.000	−0.184
FCLA	−0.428	0.008	0.018	0.128	0.000

F-value = 19.701, P < 0.01, Adjusted R2 = 0.4498. “→” denotes the influence direction of the factors. AFCSI denotes farmers’ behavior in quality protection. KW denotes farmers’ knowledge of the CLPF. IPS denotes the degree of impact on pension security. CLA denotes cultivated land area. FCLA denotes flowing out of cultivated land area.