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Journal of Geographical Sciences >

2016 , Vol. 26 >Issue 2: 203 - 218

DOI: https://doi.org/10.1007/s11442-016-1263-6

Orginal Article

Effectiveness of farmland transfer in alleviating farmland abandonment in mountain regions

  • SHAO Jing’an , 1, 2 ,
  • ZHANG Shichao 1, 2 ,
  • LI Xiubin 3
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  • 1. College of Geography and Tourism, Chongqing Normal University, Chongqing 400047, China
  • 2. Key Laboratory of Surface Process and Environment Remote Sensing in the Three Gorges Reservoir Area, Chongqing 400047, China
  • 3. Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101, China

Author: Shao Jing’an (1976-), Professor, specialized in regional environment evolution and climate responses. E-mail:

Received date: 2015-06-18

  Accepted date: 2015-07-20

  Online published: 2016-02-25

Supported by

Funds for International Cooperation and Exchange of National Natural Science Foundation of China (NSFC- IIASA Project), No.41161140352

Humanity and Social Science Youth Foundation of Ministry of Education of China, No.10YJCZH122

Copyright

Journal of Geographical Sciences, All Rights Reserved
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Abstract

Farmland abandonment is a type of land use change in the mountain region, and this change is under rapid development. Whether farmland transfer can prevent this process and promote the effective allocation of land resources or not is a question worth studying and discussion. With the help of the previous research findings, the objective of this paper was to find out the role of farmland transfer on preventing farmland abandonment, by using the methods of multiple view with two factors, and single factor correlation analysis. The results showed that: (1) At village level, a significant negative correlation between farmland transfer and farmland abandonment existed in the study site, with R2 = 0.7584. This correlation of farmland with high grade farming conditions presented more outstandingly. The fitted curve for the farmland at Level I had the largest R2 at 0.288, while that for the farmland at Level IV had the smallest R2 at 0.103. Which indicated that farmland transfer could prevent the abandonment of farmland with high grade farming conditions? (2) At plot level, the abandonment rate of farmland with high grade farming conditions was significantly lower than that of farmland with poor grade farming conditions. It was the lowest at 10.49% for the farmland with Level I farming conditions, whereas the farmland with Level I farming conditions was 26.21%. Abandoned farmland was mainly contributed by farmland with Level IV farming conditions in the study site. (3) At village level, the role of farming conditions on farmland abandonment was insignificant. The univariate correlation analysis revealed that the abandonment ratio was negatively correlated with the proportions of farmland at Levels I and II and their accumulated proportion; however, their R2 were small at 0.194, 0.258, and 0.275, respectively. The abandonment of farmland with high farming conditions still existed. The abandonment ratios of farmland at Levels I and II were high at 9.96% and 10.60%, respectively. This presented that farmland transfer on behalf of the land rental market was still not developed. (4) However, the village possessed the high rate of farmland transfer, and its rate of farmland abandonment with high grade farming conditions was all lower. When the transfer ratios of farmland were over 20%, the abandonment ratios of farmland at Levels I and II were 6.47% and 6.92%, respectively. Farmland abandonment was still controlled by the improvement of land rental market. And the functions of land rental market optimizing the utilization of farmland resources have been presented to a certain degree. (5) To further improve the marketing degree of land rental, the probability of farmland abandonment could be reduced. Especially, their function to farmland with high grade farming conditions was very obvious, and could avoid the waste of farmland resources with high grade farming conditions.

Key words： land rental market; farmland abandonment; farming conditions; farmland resource optimization; mountain region

Cite this article

SHAO Jing’an , ZHANG Shichao , LI Xiubin . Effectiveness of farmland transfer in alleviating farmland abandonment in mountain regions[J]. Journal of Geographical Sciences, 2016 , 26(2) : 203 -218 . DOI: 10.1007/s11442-016-1263-6

1 Introduction

Large areas of farmland in China’s mountainous regions are being left uncultivated (or abandoned), thus marking a new change in the relationship between man and land against the background of rural development and land use transformations. Currently, China’s rural regions are undergoing significant transformations in development pattern and land use, as driven by the growing wages of non-agricultural workers as well as the decreasing proportion of agricultural income in the family income (Long et al., 2014; Liu et al., 2014). Due to the rising opportunity cost of engaging in farming, large numbers of young adults in the remote mountainous regions are choosing to instead go into non-agricultural sectors in urban areas. In addition, as the rural labor force continues to dissipate, the social value of using land for agriculture is inevitably reduced, and consequently, considerable arable land is abandoned in the mountainous regions where manual labor is unlikely to be replaced by agricultural machinery. As a result of this changing dynamic, there is an expansion of natural ecological land (Pueyo and Beguería, 2007; Seeborg et al., 2000; Mullan et al., 2011; Hou et al., 2014), also known as “transformation from farmland to forest” (Sluiter and de Jong, 2007; Milenov et al., 2014). This problem will continue to worsen with the further migration of rural labor and the aging of those staying in their villages (Zaragozí et al., 2012; Shao et al., 2014; Zhang et al., 2014; Li et al., 2014). However, with goals of maintaining at least 1.8 billion mu of arable land and ensuring food safety, an important question is posed: how can the waste of farmland resources be reduced, especially those providing good farming conditions? Achieving the farmland preservation goal set by the government is and will be a focus of China’s efforts to promote sustainable land use and management as well as farmland preservation in future years.
Passed by the Central Committee at the 18th National Congress of the Communist Party of China, the policy concerning the major issues of the country’s rural reform gives priority to the establishment of rural farmland transfer markets with an aim to stimulate the transfer of contracted land management rights. This allows the market to play a role in promoting the efficient allocation of land resources. However, controversy exists over whether the market would positively impact the promotion of efficient allocation of land resources. Deininger and Jin (2005) and Yao (2007) found that the transfer of farmland played an important role in increasing both agricultural productivity and family income. Sklenicka et al. (2014) proposed that letting the land-use right be concentrated to a small number of users was key to the sustainable use of fragmentary farmland in mountain regions. Furthermore, Yu et al. (2013) suggested that the market-oriented allocation of agricultural land was the leading factor in increasing the efficiency of land use. Milenov et al. (2014) and Shao et al. (2007) proved that farmland transfer was conducive to promoting a more efficient use of farmland resources. However, farmers are unlikely to engage themselves in a market-oriented allocation of farmland resources due to the limitations of the peasant economy and an incomplete market. Furthermore, Burgess (2001) and Shang and Guo (2010) discovered that the incomplete market, market risk, and an imperfect policy implementation could obstruct the accomplishment of a market-oriented allocation of farmland, whereas Ye et al. (2006) and Guan (2011) thought that a property right system and the transaction cost could easily cause a farmland transfer market to fail.
Thus, a question worth discussing arises: can farmland transfer effectively prevent farmland, especially that with good farming conditions, from being left uncultivated in mountainous regions? In this study, the authors investigate whether the development of a rural land leasing market in a mountainous region could aid in improving the allocation of farmland resources and prevent the waste of favorable farmland, based on the assumptions that the rate of farmland transfer reflects the level of activity in a land leasing market and that farming conditions indicate the local resource endowment. This research is expected to provide a scientific basis for pushing forward the marketization of the rural land leasing sector in China’s mountainous regions.

2 Materials and methods

2.1 Regional overview

Shizhu County (area of 3012.24 km2) that is studied in this paper is located in the Wuling mountain region (107°59′22″-108°34′45″E, 29°39′29″-30°32′45″N), which lies on the border between Chongqing and Hubei (Figure 1). According to the geomorphic division of Sichuan Province, the sample area is located in the Eastern Sichuan Fold Belt, which is composed of medium mountains from Wushan Mountain to Daloushan Mountain. The nearly parallel (NE-SW) Qiyue Mountain and Fangdou Mountain, which stretch over the area and have a trough lying in-between, characterize the overall geomorphic features of the area. Medium and low mountains are the main geomorphic units. Additionally, the sample area has a humid subtropical monsoon climate and shows distinctly diversified climatic characteristics. Its annual average temperature is 16.5℃, and the annual average precipitation is 1103.0 mm. The main soil types include yellow soil, yellow-brown soil, purple soil, and rice paddy soil. Besides the Yangtze River, there are 11 rivers whose drainage areas exceed 100 km2 in this area. The vegetation types include tropical evergreen broadleaf forest and deciduous broadleaf forest, which are mainly composed of Pinus massoniana and firs with a coverage of about 52.8%.
Figure 1 Location of the study site and its topography
At the end of 2011, a total of 544,500 people lived in the 32 towns and 229 villages of the sample area. The per capita GDP of the area was about 19,400 yuan, and the per capita net income of rural residents was 5,981 yuan. Furthermore, 43.34% of the local labor force became migrant workers. The decreasing rural labor force has resulted in the transfer of 12239.72 ha of farmland, or 17.14% of the total area of farmland contracted to the households of the region. A moderate-scale operation was practiced on 17,609.13 ha of farmland (no less than 10 mu per household, 15 mu = 1 ha), which accounted for 24.66% of the total area of farmland contracted to households. A farmland transfer and moderate-scale operation have significantly optimized the allocation of farmland resources among different users as well as increased the land utilization rate and productivity per unit of area. Due to the farmland’s gradient and distance from settlements in addition to the relative disadvantages of agricultural production, a total of 11575.87 ha of farmland, or 16.18% of the total area of farmland contracted to local households, remained uncultivated (Shao et al., 2014).

2.2 Data collection

The study was conducted on both plot and village scales. On the plot scale, an investigation was carried out into the farming conditions and distribution of farmland, including cultivated land and uncultivated land. The village-scale analysis focused on relationships between farmland transfer, farmland abandonment, and farming conditions. It was necessary to find out whether the differences between village samples in the farmland transfer and abandonment situation were determined by varying farming conditions.
Therefore, data collection was undertaken on both the plot and village scales. On the plot scale, a 1:10,000 farmland distribution map of the sample area (2011) was obtained from the results of interpretation and superposition of the SPOT-5 image (with a resolution of 2.5 m), a vector topographic map (2002), and an afforestation distribution map (2002-2008) in previous research (Shao et al., 2014). The rural settlement distribution map and the village-scale administrative map over the same period were acquired from the Land and Resources and the Housing Authority of Shizhu Tujia Autonomous County. Furthermore, DEM data with a 30-m resolution were obtained from the Environmental and Ecological Science Data Center for West China. These images, maps, and data were projected onto the village-scale administrative map in order to obtain data concerning the transferred farmland, uncultivated farmland, and farming conditions of the area.
On the village scale, the transferred farmland areas were obtained mainly through participatory rural appraisals and field surveys, which were carried out by the research team in all 32 towns between May 15th and June 3rd in 2014. Moreover, 163 entities involved in farmland transfer were interviewed, including 93 ordinary rural households, 51 large farms, 12 specialized cooperatives, and 7 companies. For each town, the leaders at both the village and town levels were convened by the investigators at the town’s government office, and together, they conducted a participatory rural appraisal of transferred farmland areas (2011) by referring to the agricultural economic reports of the villages. Any place with a transferred farmland area of greater than 2.0 ha was plotted on the 1:10,000 farmland distribution map of each village. This process was repeated for all village samples by randomly sampling entities involved in the farmland transfer, such as ordinary rural households, large farms, specialized cooperatives, and companies. To verify and supplement the collected data, field surveys were carried out in some of the regions where the farmland transfer took place, and their GPS coordinates were recorded.

2.3 Data analysis

(1) Representation of farming conditions
Previous research results indicated that farming conditions (including the gradient (G) of the farmland plot as well as its distance (D) and altitude difference (A) from the settlement (Figure 2)) are the most important factors affecting the occurrence of farmland abandonment in the sample area, and additionally, there are negative correlations between the three factors and the uncultivated farmland area (Shao et al., 2014). Therefore, the farming conditions can be represented by the product of the three factors: G × D × A. The larger the three factors are, the larger their product and the worse the farming conditions, and vice versa.
Figure 2 Slope of patch, farming distance of patch, and relative elevation between patch and village
Data concerning the gradient of farmland plots and the topographic position index were obtained from previous research results. The altitude difference between a farmland plot and a settlement was the absolute value of the difference of the plot’s centroid altitude and the arithmetic mean of the settlements’ centroid altitudes. The centroids of the farmland plots and the related settlements were extracted from the DEM, and the altitudes of these centroids were extracted using Extract Value to Points. The arithmetic mean of the altitudes of the settlements’ centroids was calculated, and then, it was subtracted from each plot’s centroid altitude. The absolute value of the result was the altitude difference between each plot and settlement.
The linear distance from each plot to the settlement nearest to it was extracted from the rural settlement distribution map (2011). Then, the results were corrected by introducing the topographic position index, thereby yielding the corrected distance between each farmland plot and the nearest settlement.
(2) Classification of farming conditions
The farming conditions of the area’s farmland were divided into four levels for more easily analyzing their relationships with farmland transfer and abandonment (Figure 5c): higher levels suggest worse farming conditions. Furthermore, anisotropic changes in the farmland’s gradient as well as the distance and altitude difference from settlement would affect their product. If any one of them is zero while the other one or two are relatively large, then the product of the three factors could not accurately characterize the farming conditions, thus affecting the classification of farming conditions. This is because the product 0, which should represent good farming conditions, concealed the harsh farming conditions that were determined by the larger factor(s) according to the bucket theory.
Therefore, the classification method in previous research was used in the study. If a farmland plot satisfied any one of the three following conditions: G ≥ 25°, D ≥ 800 m, and A ≥ 100 m, then its farming conditions were directly classified as Level IV, rather than being represented by the product of the three factors. The three factors of the remaining plots were then standardized according to their correlations with the farming conditions. To avoid the influence of value 0 on the classification of farming conditions, a value of 1 was assigned to any factor equaling 0 prior to the standardization and multiplication operation. The multiplication results were arranged in order from smallest to largest, and together with those classified into Level IV, the results were then divided into four equal portions. In terms of farmland areas, the final classification results were generally consistent with the result in the Agricultural Land Classification in Sizhu County, Chongqing (2008).
(3) Statistical significance of indicators
To investigate the effectiveness of farmland transfer in reducing the farmland abandonment as well as the relationship between farmland abandonment and farming conditions, four indicators were introduced to the study: farmland transfer ratio (R1), abandonment ratio (R2), abandonment ratio of each farming conditions level (R3), and proportion of farmland at each farming conditions level. According to previous research results and the distribution patterns of the two ratios in the village samples, both the farmland transfer ratios and abandonment ratios were split into three intervals: R1, R2 ≤10%, 10% < R1, R2 < 20%, and R1, R2 ≥20%. Then, the areas of transferred farmland and uncultivated farmland at each level of farming conditions were estimated for each village sample.
The overall abandonment ratio R2 and the overall transfer ratio R1 of a village were respectively the ratios of the area of uncultivated farmland and that of transferred farmland to the total farmland area in the village. The abandonment ratio of each farming conditions level was the ratio of the area of uncultivated farmland at each level to the total farmland area in each village. The proportion of farmland at each level was the result of dividing the area of uncultivated farmland at each level by the total farmland area in each village. The abandonment ratio of a village in an R1 interval was the ratio of the area of uncultivated farmland at a level to the total area of farmland at this level in the village. For a village, the proportion of farmland at each level in an R1 or R2 interval was the result of dividing the area of farmland at each level in the village by the village’s total farmland area.
The relationships between these indicators were analyzed through three types of statistical analyses: (1) a statistical analysis of both the abandonment ratios (including the overall abandonment ratio and the abandonment ratios of different levels) and the transfer ratios was conducted in order to explain the relationship between the transfer ratio and abandonment ratio with an aim to determine the relationship between farmland transfer and abandonment in terms of the overall situation and resource endowment; (2) the relationship between the abandonment ratio and resource endowment was interpreted by analyzing the abandonment ratios of different levels and the statistical relationship between the proportions of farmland at different levels and abandonment ratios with an aim to discover if the abandonment ratio depends on the resource endowment; and finally, (3) a statistical analysis of the proportions of farmland with different farming conditions and the transfer ratios depicted the relationship between the transfer ratio and resource endowment with an aim to find out whether the transfer ratios in regions with good farming conditions were higher than those in regions with poor farming conditions.
(4) Statistical methods
Scatter plots with two variables were used to analyze the relationships between land abandonment and transfer, between the abandonment ratio of each level and the transfer ratio, between the abandonment ratio and proportion of farmland at each level, and between the transfer ratio and proportion of farmland at each level.
A univariate correlation analysis was used to determine accurate correlations between different variables. In analyzing the correlation between the farmland abandonment ratio and transfer ratio, the transfer ratio was a dependent variable, and each level’s abandonment ratio was an independent variable. When analyzing the correlations between the abandonment and transfer of farmland and farming conditions, the abandonment ratio and transfer ratio were dependent variables, while the proportion of farmland at each level was an independent variable.

3 Results and discussion

3.1 Did the occurrence of farmland abandonment depend on the farming conditions?

The transfer of farmland in a mountain region was strongly negatively correlated with farmland abandonment. In the sample area, the univariate correlation analysis suggested a relatively strong negative correlation between the transfer ratio and abandonment ratio, with R2 = 0.595 (Table 1). The significance test with a significance level of 0.01 demonstrated that the result was statistically significant. Furthermore, in the scatter plot (Figure 3), the R2 of the exponential trend line was 0.7584, thus indicating that the transfer ratio and abandonment ratio were strongly correlated. In terms of spatial distribution, the transfer ratio and abandonment ratio showed relatively significant negative correlation (Figures 5a and 5b). These findings demonstrate that there was a significant negative correlation between the transfer ratio and abandonment ratio, and the abandonment ratios were low in villages with high transfer ratios, which is consistent with the conclusions of previous research. However, the simple correlation analysis is insufficient for leading to the conclusion that the transfer of farmland in mountainous regions can help prevent farmland from being left uncultivated. This is because in a well-established land leasing market, farmland with good farming conditions is more likely to be used, rather than being abandoned, due to its high productivity. The villages exhibiting low abandonment ratios may have extensive farmland with good farming conditions. Therefore, it was necessary to determine whether the differences in the abandonment ratios between villages were determined by varying farming conditions.
Table 1 A single correlation between farmland abandonment ratio, farmland transfer ratio and the proportion of farmland of each level farming condition
Correlation analysis R2 Unstandardized coefficients Standard coefficient t Sig. F
B Standard error
Farmland abandonment ratio and
transfer ratio		 0.595 -1.172 0.064 -0.772 -18.272 0.000*** 333.852
Farmland abandonment ratio and the proportion of farmland of each level farming condition Level I 0.194 -0.319 0.043 -0.441 -7.398 0.000*** 54.736
Level II 0.258 -0.358 0.04 -0.508 -8.875 0.000*** 78.769
Levels I and II 0.275 -0.206 0.022 -0.524 -9.268 0.000*** 85.901
Level III 0.014 0.094 0.053 0.118 1.786 0.075* 3.191
Level IV 0.303 0.256 0.026 0.551 9.937 0.000*** 98.748
Farmland transfer ratio and abandonment ratio of each level farming condition Level I 0.288 -0.337 0.035 -0.537 -9.589 0.000*** 91.941
Level II 0.258 -0.223 0.025 -0.508 -8.875 0.000*** 78.769
Levels I and II 0.376 -0.187 0.016 -0.613 -11.705 0.000*** 136.997
Level III 0.19 -0.211 0.029 -0.436 -7.308 0.000*** 53.4
Level IV 0.103 -0.114 0.022 -0.321 -5.104 0.000*** 26.049
Farmland transfer ratio and the proportion of farmland of each level farming condition Level I 0.186 0.205 0.028 0.431 7.202 0.000*** 51.871
Level II 0.302 0.255 0.026 0.55 9.918 0.000*** 98.363
Levels I and II 0.294 0.141 0.014 0.542 9.728 0.000*** 94.631
Level III 0.036 -0.099 0.034 -0.189 -2.893 0.004** 8.368
Level IV 0.282 -0.163 0.017 -0.531 -9.444 0.000*** 89.196

Note: ***, ** and * indicated that there was significant correlation between two variables at the level of 0.01, 0.05 and 0.1.

Figure 3 The relationships between ratio of farmland transfer and ratio of farmland abandonment
On the plot scale, the abandonment ratios of farmland with favorable farming conditions were significantly lower than those of inferior farmland. The abandonment ratio of the farmland with Level IV farming conditions was 26.21%, which was the highest among all types of farmland, whereas the farmland with Level I farming conditions was the lowest at 10.49% (Figures 4, 5a and 5c). Though the abandonment ratios increased as the farming conditions declined from Level I to Level III, they were still smaller than the overall abandonment ratio of the sample area (16.18%), thus indicating that the farmland with Level IV farming conditions contributed most to the overall abandonment ratio.
Figure 4 The ratio of farmland abandonment under each level farming condition
Figure 5 The spatial distributions of farmland abandonment ratio, farmland transfer ratio and framing conditions
As shown in Figure 6, the farmland at Levels I and II accounted for 66.77% of the farmland whose abandonment ratios were smaller than 10%, which is higher than the proportions of farmland at the other two levels in this interval. The farmland at Level IV was 46.64% of the farmland whose abandonment ratios were larger than 20%, the highest proportion in this interval. These findings are consistent with previous research and field survey results that found that the abandonment ratio of a farmland increased with increasing gradient as well as increasing distance and altitude difference from a settlement. However, interestingly, among the farmland with abandonment ratios between 10% and 20%, the proportions of farmland with different farming conditions varied slightly, ranging from 23% to 25%, with little variation from level to level. This demonstrates that farmlands that were favorable for agricultural production were also abandoned. Moreover, the farmland with Level III farming conditions was relatively evenly distributed in different intervals of abandonment ratio. This was because Level III was the critical level of farming conditions for the agricultural production in this area. If a plot of farmland can provide better farming conditions, then it is productive and will likely to be used for agricultural production; otherwise, it will likely remain uncultivated.
Figure 6 The proportion of farmland of each level farming condition under different ranges of farmland abandonment ratio
Figure 7 The relationships between the proportion of farmland of Levels I and II farming conditions and farmland abandonment ratio
Figure 8 The relationships between proportion of farmland of each level farming condition and farmland abandonment ratio
On the village scale, the correlation between the farming conditions and abandonment ratio was relatively weak in the mountainous regions. The univariate correlation analysis revealed that the abandonment ratio was negatively correlated with the proportions of farmland at Levels I and II and their accumulated proportion (a significance test with a significance level of 0.01 demonstrated that the result attained statistical significance); however, their R2 were small at 0.194, 0.258, and 0.275, respectively (see Table 1). In addition, the scatter plots in Figures 7 and 8 also show negative correlations between the aforementioned relationships, and the R2 of the fitted logarithmic curves were also small. This suggested that the differences in the abandonment ratios of different villages could not be completely attributed to the varying farming conditions. Normally, in a well-established land leasing market, farmland with good farming conditions tends to be used rather than abandoned. In the sample area, however, the abandonment ratios of farmland at Levels I and II were high at 9.96% and 10.60%, respectively, thus implying that some farmland with good farming conditions was also left uncultivated.
In accordance with the principle of a market-oriented allocation of resources and with the land rent theory, farmland with good farming conditions has relatively high economic value and is, thus, supposed to be used, and in contrast, that with poor farming conditions is more likely to be left uncultivated if the local land leasing market is well established. Thus, the abandonment of farmland with good farming conditions in this area indicates that the land leasing market is too incomplete to promote the reuse of the uncultivated farmland with good farming conditions. Therefore, it can be concluded that the continued progress of marketization will be important for reducing the occurrence of farmland abandonment in the sample area.

3.2 Could the farmland transfer help reduce the occurrence of farmland abandonment?

The negative correlation between the abandonment ratio and transfer ratio was strong among the farmland with good conditions in the mountainous region. Though the transfer ratios and abandonment ratios of different levels were negatively correlated in all villages, as was indicated by the univariate correlation, the relationship was more statistically significant among the farmland with better farming conditions. The fitted curve for the farmland at Level I had the largest R2 at 0.288, while that for the farmland at Level IV had the smallest R2 at 0.103. The accumulated R2 for the farmland at Levels I and II was 0.376. In terms of spatial distribution, the abandonment ratio, transfer ratio, and farming conditions also display distinct relationships (Figure 5). In addition, the scatter plots in Figures 9 and 10 exhibit the same characteristics. A higher transfer ratio tends to result in a lower abandonment ratio, and this trend was especially remarkable for the farmland with good farming conditions.
Figure 9 The relationships between ratio of farmland transfer and ratio of farmland abandonment under each level farming condition
Figure 10 The relationships between ratio of farmland transfer and ratio of farmland abandonment under Levels I and II farming conditions
Figure 11 shows that when R1 < 10%, the abandonment ratio of each level was greater than 20%, which is higher than the overall abandonment ratio of the sample area (16.18%). Furthermore, the abandonment ratios of Levels III and IV were high at 30.77% and 42.79%, respectively. In the other two intervals, the abandonment ratios sharply declined. When R1 > 20%, the abandonment ratios declined by 67.01%-70.83% to the levels below 15%, which is lower than the overall abandonment ratio of the sample area. Among the farmlands at Levels I and II, the abandonment ratios varied slightly from interval to interval. Moreover, the abandonment ratio of Level III was closer to the abandonment ratios of the two lower levels than to that of Level IV, thus suggesting that the transfer of farmland was effective in controlling the abandonment of farmland with good or moderate farming conditions.
Figure 11 The ratio of farmland abandonment of each level farming condition under different ranges of farmland transfer ratio
Another similar question that needs to be addressed is whether the occurrence of farmland transfer was determined by farming conditions. In a complete land leasing market, the transfer ratios of farmland with good farming conditions, which is more productive land, are supposed to be higher than those of farmland with poor farming conditions. As shown in Figure 12, when R1 < 10%, the proportion of the farmland at Level IV was 45.16%, which is the largest among the farmland in this interval, and the accumulated proportion of the farmland at Levels I and II was 27.49%, similar to that of the farmland at Level III. When R1 > 20%, the accumulated proportion of farmland at Levels I and II was 63.60%, and the farmland at Level IV accounted for the smallest proportion at 12.67% of the farmland in this interval. This result indicates that if there is a land leasing market, then the farmland with good farming conditions is likely to be transferred and used despite its higher rental since it is distinctly advantageous for agricultural production. The transfer of land management rights can help lower the probability of farmland abandonment and optimize the allocation of resources.
Figure 12 The proportion of farmland of each level farming condition under different ranges of farmland transfer ratio
The characteristics of proportions of farmland in different intervals of the transfer ratio were similar to those in different intervals of the abandonment ratio. When the transfer ratio was between 10% and 20%, there was little variation in the proportions of farmland at different levels (22%-28%), indicating that the transfer ratio was not completely determined by the level of farming conditions. Moreover, the proportions of farmland at Level III in the three transfer ratio intervals were between 23% and 27% with there being little variation from interval to interval. This suggests that Level III was the critical level of farming conditions that governed the reuse and reallocation of farmland resources and was the lowest level that the land leasing market could affect. Accordingly, farmland with farming conditions poorer than this level was unlikely to be transferred.
On the village scale, the farming conditions’ effect on the transfer ratio did not vary much from village to village. The villages providing favorable farming conditions exhibited slightly higher transfer ratios, thereby implying that the farming conditions’ influence on the transfer ratios in different villages was statistically insignificant (Table 1). Therefore, their higher transfer ratios were not attributed to larger proportions of farmland with good farming conditions. The univariate correlation analysis indicated that the proportions of farmland at Levels I and II and their accumulated proportion were positively correlated with the transfer ratio, and in contrast, the proportion of farmland at Level IV was negatively correlated with the transfer ratio, but their R2 were small at just 0.186, 0.302, 0.294, and 0.282, respectively. In addition, the clutter plots in Figures 13 and 14 exhibit similar characteristics. These observations imply that the farming conditions do not fully account for the variation in the transfer ratio between villages, and in addition, they were not the major factor determining the occurrence of farmland transfer in the mountainous regions. Therefore, it has been concluded that the transfer ratio is not determined solely by farming conditions.
Figure 13 The relationships between the proportion of farmland of Levels I and II farming conditions and farmland transfer ratio
Figure 14 The relationships between the proportion of farmland of each level farming condition and farmland transfer ratio
The differences in the transfer ratio between villages did not vary much with the farming conditions, thus indicating that the land leasing market in the sample area was too immature to optimize the allocation of farmland resources. Therefore, the progress of marketization continues to greatly affect the occurrence of farmland transfer.
In the sample area, the abandonment ratio of the farmland with good farming conditions, especially the Levels I and II farming conditions, was strongly negatively correlated with the transfer ratio. In the villages with high transfer ratios, the abandonment ratios of farmland with good farming conditions were relatively low and decreased with the transfer ratio. This demonstrates that the land leasing market had some effect in increasing the utilization rate of farmland resources. Thus, it has been concluded that a more developed land leasing market will play a greater role in reducing farmland abandonment, especially farmland with good farming conditions, thus preventing the waste of favorable farmland resources. However, the market was still ineffective for preventing farmland with poor farming conditions from remaining uncultivated. The inferior farmland is being abandoned as a result of the farmland’s low productivity in addition to the costly expenses of using it for agricultural production. Previous research has concluded that the abandonment of inferior farmland by the market is conducive to the restoration of the degraded farmland and the ecological integrity in mountainous regions. In a larger sense, since the occurrence of farmland abandonment is affected by the progress of marketization, furthering the marketization of the land leasing sector will help achieve a more reasonable allocation of farmland resources.

4 Conclusions

(1) There was a strong negative correlation between the transfer ratio and the abandonment ratio of farmland in the sample area, with R2 = 0.7584. Higher transfer ratios resulted in lower abandonment ratios. At the plot level, the farmland with good farming conditions had distinct advantages over the farmland with poor farming conditions and exhibited much lower abandonment ratios. The abandonment ratio of the farmland with Level IV farming conditions was 26.21%, whereas the farmland with Level I farming conditions was the lowest at 10.49%. At the village level, the correlation between the farming conditions and abandonment ratio was relatively weak. Farmlands with good farming conditions were also abandoned. The abandonment ratios of farmland at Levels I and II were high at 9.96% and 10.60%, respectively.
(2) The negative correlation between the abandonment ratio and the transfer ratio was especially strong among the farmland with good conditions. The farmland transfer was found to be effective in reducing the abandonment of farmland with good or moderate farming conditions. The fitted curve for the farmland at Level I had the largest R2 at 0.288, while that for the farmland at Level IV had the smallest R2 at 0.103. The villages providing favorable farming conditions exhibited slightly higher transfer ratios, thus implying that farming conditions’ influence on the transfer ratios in different villages was statistically insignificant. The univariate correlation analysis indicated that the proportions of farmland at Levels I and II were positively correlated with the transfer ratio, but their R2 were small at just 0.186 and 0.302, respectively.
(3) The farming conditions’ effect on the abandonment ratio did not vary much from village to village. The univariate correlation analysis revealed that the abandonment ratio was negatively correlated with the proportions of farmland at Levels I and II and their accumulated proportion; however, their R2 were small at 0.194, 0.258, and 0.275, respectively. Thereby this indicating that the land leasing market dominated by farmland transfer was still undeveloped. The abandonment ratio of the farmland with good farming conditions was strongly negatively correlated with the transfer ratio. In the villages where the transfer ratios were high, the abandonment ratios were generally low, demonstrating that the land leasing market has the effect of increasing the utilization rates of farmland resources.
(4) As the occurrence of farmland abandonment in mountainous regions is still affected by the progress of marketization, improving the land leasing market will help prevent farmland, especially that with good farming conditions, from being left uncultivated. When the transfer ratios of farmland were over 20%, the abandonment ratios of farmland at Levels I and II was 6.47% and 6.92%, respectively. However, the market is still ineffective in preventing the abandonment of farmland with harsh farming conditions. In a larger sense, the abandonment of inferior farmland by the market is conducive to the restoration of the degraded farmland as well as the ecological integrity in mountainous regions.

The authors have declared that no competing interests exist.

References

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1
Burgess R, 2001. Land and welfare, theory and evidence from China. Working Paper, London School of Economics.Lack of access to land is often identified as a root cause of poverty and un- dernutrition in rural settings. Land generates income but, where food markets are imperfect, can also serve as source of cheaper food relative to the market. Using data from a rich and poor Chinese province we demonstrate that this latter own price effect is empirically important. Our results are consistent with food markets being imperfect in rural China. In these settings, reforms which equalise access to land will be particularly effective as beneficiaries obtain not only a new source of income but also the means for producing cheaper food. Redistribution of land will have a more profound impact on welfare than re- distribution of output from that land. Our analysis points to universal and egalitarian access to land as being the key safety net for the 800 million or so people living in rural China. It also helps to explain China's current and historical success in constraining poverty and undernutrition relative to other developing countries.

2
Deininger K, Jin S, 2005. The potential of land rental markets in the process of economic development: Evidence from China.Journal of Development Economics, 78(1): 241-270.We develop a model of land leasing with agents characterized by unobserved heterogeneity in ability and presence of an off-farm labor market. In this case, decentralized land rental may contribute to equity and efficiency goals and may have several advantages over administrative reallocation. The extent to which this is true empirically is explored using data from three of China's poorest provinces. Land rental markets and administrative reallocation reallocate land to those with lower endowments but the former are more effective in doing so and have a bigger productivity-enhancing effect. Information on hypothetical market participation suggests that reducing transaction costs in land rental markets could help to realize significant additional productivity gains.

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3
Ge Lin, Gao Ming, Hu Zhengfenget al., 2012. Reasons of cultivated land abandonment in mountainous area based on farmers’ perspective.Chinese Journal of Agricultural Resources and Regional Planning, 33(4): 42-46. (in Chinese)

4
Guan Yan, 2011. Analysis on market for transferring rural land by transaction cost economics.Economic Problems, (4): 17-20. (in Chinese)For the past few years,nationwide markets for transferring the use of the rural land are almost established.The intermidiaries of rural land circulation have started to play a role.The local grass-roots organizations such as villages or countries also actively have gotten involved in pushing forward with transferring the use of the rural land.However,as a whole,marketing degree of rural land circulation are not high yet.This thesis finds out the desires of peasants in Wuhan Hubei for land circulation by questionnaires,analyzes the current situation and the cause of formation of the market for transferring rural land from the angle of view of transaction cost,and proposes a certain number of countermeasures.

5
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7
Lin Ruirui, Zhu Daolin, 2014. A spatial and temporal analysis on land incremental values coupled with land rights in China.Habitat International, 44: 168-176.

8
Liu Yansui, Yang Ren, Long Hualouet al., 2014. Implications of land-use change in rural China: A case study of Yucheng, Shandong province.Land Use Policy, 40: 111-118.Based on surveys on rural land-use change at village scale in Yucheng City, Shandong province, this paper presents how land-use change takes place in response to inhibitive institutional forces in light of an outmoded land ownership system and unreasonable land use rights administration, and discusses it in the broader social context of industrialization, rural depopulation, a dual-track land market, and land use legislation. Spatial comparison of land use maps interpreted from aerial photographs in different period unveils a decrease in arable land for farming, and an increase in rural settlements, facilities land and unused land. Despite rural depopulation, rural settlements area nearly tripled during 1967-2008. Nearly all newly gained non-agricultural land originated from farmland at the village fringe while formerly facilities land and unused land had been converted to residential use and it was abandoned later. Thus, the destructive farmland conversion from productive use to non-agricultural uses took place at multiple stages. Questionnaire survey of 1650 households in 48 villages in Yucheng City indicated that 41% of the households had multiple dwellings, even though some of them are not occupied or even ruined. This finding may damp the rosy picture of the reportedly slowdown in China's farmland reduction in recent years as these destructive changes are too small to detect from satellite imagery, and it will also provide a practical scientific basis for constituting more strict farmland protection objectives and strategies for China in the near future. In order to hold back the destructive conversion trend from farmland to non-agricultural uses, the authors argue that policy and institution innovation concerning land use and urban ural development in China needs feature highly in the government's agenda.

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Long Hualou, Liu Yongqiang, Hou Xueganget al., 2014. Effects of land use transitions due to rapid urbanization on ecosystem services: Implications for urban planning in the new developing area of China.Habitat International, 44: 536-544.

10
Long Hualou, Zou Jian, Pykett Jet al., 2011. Analysis of rural transformation development in China since the turn of the new millennium.Applied Geography, 31(3): 1094-1105.Since the turn of the new millennium, the Chinese central government has focused significant attention on substantially improving rural residents' well-being and achieving the coordinated development of urban and rural areas. This paper examines China's rural transformation development based on three assessing indicator systems (the rural development level, the rural transformation level, and the urban-rural coordination level), using government socioeconomic data from 2000 to 2008. Spatial and statistical analyses, supported by SPSS 13 and ArcGIS 9.2 software, show that rural China has experienced universal and intense transformative development since 2000. China's urban-rural coordination development declined greatly between 2000 and 2008. Our analysis shows that rural transformation development that corresponds to a certain rural development level will lead to the effective development of regional rural systems and an improved urban-rural relationship. This paper suggests that more attention needs to be paid to the powerful factors that fuel rural transformation development, especially in coastal China, to coordinate urban-rural development under the pressure of rapid industrialization and urbanization in the new century. Given the multiscale nature of regional inequalities in rural transformation development, improving rural development policies aimed at various rural transformation development types might be the most effective way to shape a more coordinated urban-rural development pattern in China. (C) 2011 Elsevier Ltd. All rights reserved.

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Milenov P, Vassilev V, Vassileva Aet al., 2014. Monitoring of the risk of farmland abandonment as an efficient tool to assess the environmental and socio-economic impact of the Common Agriculture Policy.International Journal of Applied Earth Observation and Geoinformation, 32: 218-227.

12
Mullan K, Grosjean P, Kontoleon A, 2011. Land tenure arrangements and rural-urban migration in China.World Development, 39(1): 123-133.Obstacles to internal migration in China contribute to inefficiency, inequality, and land degradation. Academic and policy debate has primarily focused on discrimination against rural migrants on arrival in urban areas. Meanwhile, barriers to migration out of rural areas have received less attention. This paper examines the role of incomplete rural property rights in the migration decisions of rural households. We examine the relationship between tenure insecurity and restrictions on land rentals, and participation in outside labor markets. The results indicate that tenure insecurity reduces migration. This relationship is particularly pronounced on forest land, which has implications for the conservation of recently replanted forest areas. (C) 2010 Elsevier Ltd. All rights reserved.

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13
Pueyo Y, Beguería S, 2007. Modelling the rate of secondary succession after farmland abandonment in a Mediterranean mountain area.Landscape and Urban Planning, 83(4): 245-254.<h2 class="secHeading" id="section_abstract">Abstract</h2><p id="">Secondary succession after farmland abandonment has become a common process in north Mediterranean countries, especially in mountain areas. In this paper, a methodology is tested which combines Markov chains and logistic multivariate regression to model secondary succession after farmland abandonment in environments where abiotic constraints play a major role, like mountain areas. In such landscapes, a decay in the succession rate with time is usually found, as the best locations are progressively occupied. This is frequently addressed using non-stationary Markov chains. Here, we test if the combination of logistic multivariate regression with Markov chains, however, allows for spatially distributed transitions probabilities based on abiotic factors and therefore, it is able to reproduce the preferential colonization of the most favourable locations. The model is tested in the Ijuez Valley in the Spanish Pyrenees, which underwent generalized land abandonment during the 1950s. Results confirm a substantial improvement in the prediction success of the Markov-logistic model when compared to the standard Markov chain approach. As a result, the decay in the succession rate can be successfully modelled. The specific results for our study area are discussed further in an ecological context. The methodology proposed is applicable to any landscape where vegetation dynamics are constrained by environmental factors. However, the inclusion of land use as an explanatory factor would be necessary in human-managed landscapes.</p>

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Seeborg M C, Jin Z, Zhu Y, 2000. The new rural-urban labor mobility in China: Causes and implications.Journal of Socio-Economics, 29: 39-56.As the Chinese economy reforms, a huge new floating population of rural-urban migrants is transforming the urban labor force. This article explores some of the most important reasons for the emergence of the floating population in China. We argue that the neoclassical model alone is not adequate to explain the massive rural-urban internal migration underway in China. Instead, ideas drawn from both sociological theories of segmented markets and institutional economics are used to supplement the standard neoclassical explanation. We found that Chinese policy reforms in both rural and urban areas decreased the balkanization of labor markets and opened up employment opportunities for many rural-urban migrants. In rural areas, a set of agricultural market reforms, starting in 1978, increased farm incomes and simultaneously produced a large surplus labor supply. In urban areas, reforms beginning in the 1980s created an effective demand for rural migrants. Of particular importance was the development of a contract labor system and the emergence of a private sector.

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15
Shang Xin, Guo Qinghai, 2010. Analysis of behaviors of part-time peasant household based on rational economic man hypothesis.Journal of Jilin Agricultural University, 32(5): 597-602. (in Chinese)<p>This paper firstly analyzes the behaviors of parttime　peasant&nbsp;household based on the hypothesis that they are rational economic men. The causes of parttime　peasant household are: the decrease in comparative advantage of agricultural industry, the proactive policy for peasants&prime; nonagricultural employment,the binary system of peasants&prime; retaining land. Then it explains the conflict of tsmicro and macro objectives. Furthermore, it puts forward the corresponding countermeasures: to improve the farmland circulation system, to optimize regional agricultural industry structure, and to strengthen the rural human capital investment.</p>

16
Shao Jing’an, Wei Chaofu, Xie Deti, 2007. Farmers’ explanations of land transfer under the household responsibility system: The results from seven villages’ analysis in Chongqing.Geographical Research, 26(2): 275-286. (in Chinese)

17
Shao Jing’an, Zhang Shichao, Li Xiubin, 2014. Farmland marginalization in the mountainous areas: Characteristics, influencing factors and policy implications.Journal of Geographical Sciences, 25(6): 701-722.Based on SPOT-5 images, 1:1 million topographic maps, the maps of the returning farmland to forest project and the Chongqing forest project, social and economic statistics, etc., this paper identifies the features and factors influencing farmland marginalization. The results showed: (1) During 2002–2012, the rate of farmland marginalization was 16.18%, which was mainly found in the high areas of northern Qiyao mountains and the medium-altitude areas of southern Qiyao mountains. And this farmland marginalization will increase, associated with non-agriculturalization of rural labourers and aging of the remaining labourers. (2) Elevation, distance radius from villages and road connections had a great influence on farmland marginalization. Farmland marginalization rates showed an increasing trend with the increase of elevation, and 60.88% of the total farmland marginalization area is found at an altitude greater than 1000 m above sea level. The marginalization trend also increases with slope and distance from the distribution network. (3) Farmland area per labourer and the average age of farm labourers were major factors driving farmland marginalization. Farmland transfer and small agricultural machinery sets affect farmland marginalization with respect to management and productivity efficiency. (4) Farmland with “comparative-disadvantage-dominated marginalization” accounted for 55.32% of the total farmland marginalization area, followed by “location-dominated marginalization” (33.80%). (5) According to the specifics of each real situation, different policies are suggested to mitigate the marginalization. A “continuous marginalization” policy will encourage the return of farmland to forest in “terrain-dominated marginalization”. An “anti-marginalization” policy is suggested to create new rural accommodation and improve the rural road system to counteract “terrain-dominated marginalization”. And another “anti-marginalization” policy is planned to improve management and micro-mechanization for “comparative-disadvantage-dominated marginalization”. A new idea was developed to integrate high resolution remote sensing and statistical data with survey information to identify land marginalization and its driving forces in mountainous areas.

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18
Sklenicka P, Janovska V, Salek Met al., 2014. The farmland rental paradox: Extreme land ownership fragmentation as a new form of land degradation.Land Use Policy, 38: 587-593.The study discusses the tempo of the fragmentation process, which accelerates exponentially in countries with the equal inheritance system. It goes on to discuss defragmentation, social impacts of the dominance of the land rental market, and environmental impacts of significant homogenization of the land-use pattern. The serious negative impacts of extreme land-ownership fragmentation show that this phenomenon can be considered as a significant form of land degradation.

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19
Sluiter R, de Jong S M, 2007. Spatial patterns of Mediterranean land abandonment and related land cover transitions.Landscape Ecology, 22(4): 559-576.<a name="Abs1"></a>In Mediterranean France, land abandonment is a widespread change. To understand and predict the land abandonment process and its consequences, land cover change models are used. An essential step in the development of a land cover change model is the identification and quantification of the factors controlling land cover change. In this paper we present a change detection study using aerial photographs in combination with an extensive dataset of field data and geographical data, to identify and quantify these factors for a study area in Mediterranean France, 60&nbsp;km west of the city of Montpellier. We distinguished 11 land cover change classes and 7 associated &#8220;time since abandonment&#8221; classes at a detailed scale. Several environmental and non-environmental factors were found to be important variables for the land abandonment process. Differences in soil class explain a large part of the land abandonment pattern and the associated transition paths and transition rates. Most abandoned lands are located on regosols and lithosols, which are marginal soils with respect to water holding capacity. Within soil classes, we could recognise different transition paths and transition rates. However, within the 55&nbsp;years covered by this dataset detailed transitions from pioneer vegetation to vegetation higher in the succession, as described by other authors, were only found for a limited number of vegetation/soil combinations. We relate these slow transitions for some areas to ongoing grazing and for some other areas to irreversible degradation.

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20
Yao Y, 2007. The Chinese land tenure system: Practice and perspectives. In: Gulati A, Fan S (eds.). The Dragon and the Elephant: Agricultural and Rural Reforms in China and India. Baltimore: The Johns Hopkins University Press.

21
Ye Jianping, Jiang Yan, Feng Lei, 2006. Investigation of Chinese rural land circulation market: The analysis and suggestions based on the investigation of seventeen provinces in 2005.China Rural Survey, (4): 48-55. (in Chinese)

22
Yu Qiangyi, Wu Wenbin, Verburg P Het al., 2013. A survey-based exploration of land-system dynamics in an agricultural region of Northeast China.Agricultural Systems, 121: 106-116.Understanding the complexity of agricultural systems requires insight into the human–environment interactions. In this paper we used survey data to analyze land system change and its relation to farmer’s attitudes in a typical agricultural region of Northeast China, focusing on land tenure, crop choice and intensification. Our survey shows that land transfer was fairly common across the study area: average farmland acreage per household almost doubled from 1.3ha by early 1980s to 2.6ha by early 2010s, especially due to urban migration of farmers. The survey indicates an increase in land transfers over time with a sharp decrease of the average period of land transfer contracts. Crop choice displays a trend of decreasing diversity as several cereal crops are no longer grown in the study region and the majority of bean cultivation has been replaced by maize and tobacco. Land transfers can explain part of these changes, butnot necessarily the full change to a dominance of a smaller number of crops at the region level. Irrigation intensity is related to the locations of rivers, while agricultural inputs, along with land transfer and crop allocation, show a spatial pattern which is related to road accessibility. Survey results show that two family characteristics ( education level and the initially allocated land rights ) and two socioeconomic factors ( infrastructure and crop prices ) are important in making land transfer decisions, while external factors such as market , policy , local cropping system , and agricultural disasters have substantially influenced crop choice decisions. The survey approach is very valuable to analyze land system changes from a stakeholder’s perspective, especially in the absence of statistical data atfarm level.

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23
Zaragozí B, Rabasa A, Rodríguez-Sala J Jet al., 2012. Modelling farmland abandonment: A study combining GIS and data mining techniques. Agriculture,Ecosystems & Environment, 155: 124-132.Studies in animals have shown that the amygdala receives highly processed visual input, contains neurons that respond selectively to faces, and that it participates in emotion and social behaviour. Although studies in epileptic patients support its role in emotion, determination of the amygdala's function in humans has been hampered by the rarity of patients with selective amygdala lesions. Here, with the help of one such rare patient, we report findings that suggest the human amygdala may be indispensable to: (1) recognize fear in facial expressions; (2) recognize multiple emotions in a single facial expression; but (3) is not required to recognize personal identity from faces. These results suggest that damage restricted to the amygdala causes very specific recognition impairments, and thus constrains the broad notion that the amygdala is involved in emotion.

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24
Zhang Weiwen, Wang Wen, Li Xuewenet al., 2014. Economic development and farmland protection: An assessment of rewarded land conversion quotas trading in Zhejiang, China.Land Use Policy, 38: 467-476.Facing a substantial loss of farmland in the reform era, the Chinese central government established a highly centralized land management system in 1998 to guarantee its capacity to meet the domestic food needs. In order to maintain high-speed economic growth, local governments in China made great efforts to circumvent the stringent constraint on land use by launching various innovative land management schemes, among which Zhejiang's rewarded land conversion quotas (RLCQ) trading scheme, a program similar to the transfer of development rights (TDR) in Western countries, has attracted a lot of policy and scholarly attention. In this research, we first provide an overview of China's farmland protection policy and the RLCQ trading scheme in Zhejiang Province. Then, using the system GMM estimator for economic growth models and a panel dataset of 69 local jurisdictions in Zhejiang Province covering the period of 1989-2008, we assess the impacts of RLCQ trading on local economic growth. The empirical results corroborate our hypotheses that participation in land quota trading in general led to faster local economic growth, and that the trading had a stronger and more lasting impact on the economic growth of the quota buyers than on that of the sellers. The analysis suggests that in order to balance the competing goals of economic development and farmland protection, market-based land management tools have a good potential for further development in China and other countries confronting similar challenges.

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25
Zhang Ying, Li Xiubin, Song Wei, 2014. Determinants of cropland abandonment at the parcel, household and village levels in mountain areas of China: A multi-level analysis.Land Use Policy, 41: 186-192.Cropland abandonment accompanying economic development has been observed worldwide. China has experienced a large amount of land abandonment in recent years. However, the reasons for it are not entirely clear. Although abandonment decisions are made by individual households, the underlying conditions reflect processes operating at multiple levels. Therefore, we aimed to detect the influences on land abandonment at the parcel, household and village levels. We developed and employed a multi-level statistical model using farm household survey data and geographical maps of Wulong County. Our model revealed that of the variance in occurrence of land parcel abandonment, 7% and 13% can be explained at the household and village levels, respectively, while the remnant 80% can be explained at the land parcel features itself. We found that land abandonment is more prone to occur on parcels that are on steep slopes, have poor quality soil, or are remote from the laborers residences. Households with less agricultural labor per unit land area showed a high probability of land abandonment. We also found a nonlinear influence of labor age on land abandonment, with households comprising middle-aged laborers having a low land abandonment probability. Parcels in villages with high elevation, far from the county administrative center or with low prevalence of leased land are inclined to abandonment. We also found, surprisingly, that the household proportion of males among its agricultural laborers did not significantly influence the occurrence of land abandonment at the parcel level, probably due to the male agricultural laborers being overwhelmingly old (average age greater than 56 years). To alleviate land abandonment, we suggest improving land tenure and transfer security to ensure stable access to the land rental market, and also improving infrastructure in remote regions.

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