Research Articles

Extent and spatial distribution of terrace abandonment in China

  • DONG Shijie , 1, 2 ,
  • XIN Liangjie 1 ,
  • LI Shengfa 3 ,
  • XIE Hualin 4 ,
  • ZHAO Yuluan 5 ,
  • WANG Xue 1 ,
  • LI Xiubin , 1, 2, * ,
  • SONG Hengfei 1, 2 ,
  • LU Yahan 1, 2
  • 1. Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101, China
  • 2. University of Chinese Academy of Sciences, Beijing 100049, China
  • 3. Key Lab of Guangdong for Utilization of Remote Sensing and Geographical Information System/Guangdong Open Laboratory of Geospatial Information Technology and Application, Guangzhou Institute of Geography, Guangdong Academy of Sciences, Guangzhou 510070, China
  • 4. Institute of Ecological Civilization, Jiangxi University of Finance and Economics, Nanchang 330013, China
  • 5. College of Geography and Environmental Science, Guizhou Normal University, Guiyang 550001, China
*Li Xiubin, Professor, E-mail:

Dong Shijie, PhD, E-mail:

Received date: 2023-03-07

  Accepted date: 2023-04-15

  Online published: 2023-07-24

Supported by

Key Program of National Natural Science Foundation of China(41930757)

GDAS' Project of Science and Technology Development(2020GDASYL-20200104005)


Driven by urbanization and industrialization, arable land in hilly and mountainous regions of China is gradually becoming marginalized, with the extent of arable land abandonment rapidly expanding from poor-quality sloping arable land to high-quality terraces. The abandonment of large-scale terraces will lead to a series of socio-economic and ecological effects. A national sample survey was used to investigate the extent and spatial distribution of terrace abandonment in China, and a total of 560 valid village questionnaires from 329 counties were collected in the mountainous areas of China. The main findings are as follows: (1) The phenomenon of terrace abandonment was widespread throughout the country, with 54% of the total surveyed villages exhibiting terrace abandonment, and the area of abandoned terraces accounting for 9.79% of the total. (2) The degree of terrace abandonment is high in the south and low in the north. The most serious region with abandonment was the hilly and mountainous areas in the south, especially in the middle and lower Yangtze River region. (3) The main driving factors of terrace abandonment were rural labor migration, agricultural mechanization level, irrigation conditions, and transportation conditions for cultivation. Targeted measures should be taken based on the specific conditions of each area to alleviate terrace abandonment. Measures such as improving terrace mechanization are universally applicable. Specifically, low-quality terraces can be withdrawn orderly, and for high-quality terraces, multiple measures are needed to consolidate agricultural production, such as adjusting the planting structure, strengthening agricultural infrastructure construction, and encouraging the transfer of land-use rights as well as large-scale operation.

Cite this article

DONG Shijie , XIN Liangjie , LI Shengfa , XIE Hualin , ZHAO Yuluan , WANG Xue , LI Xiubin , SONG Hengfei , LU Yahan . Extent and spatial distribution of terrace abandonment in China[J]. Journal of Geographical Sciences, 2023 , 33(7) : 1361 -1376 . DOI: 10.1007/s11442-023-2133-7

1 Introduction

Since the 1980s, the development of urbanization and industrialization in China has resulted in a significant influx of rural labor into non-agricultural industries and as a consequent increase in the cost of agricultural labor, leading to severe marginalization of arable lands in mountainous areas (Liu and Li, 2006; Li and Zhao, 2011; Shao et al., 2014). Farmers have responded to this marginalization by adjusting crop cultivation structures, changing land use intensification, and increasing mechanization (Jiang et al., 2019; Kong et al., 2022). These responses have resulted in the increased use of arable land for non-farming and non-grain production purposes as well as the transition from two-season to single-season farming crops (Jiang et al., 2019; Kong et al., 2022). Arable land abandonment is an extreme manifestation of land marginalization. Arable land in mountainous areas is most likely to be abandoned because of poor farming conditions and low yields (Li and Li, 2016). The off-farm migration of rural labor is the main driver of arable land abandonment (Kolecka et al., 2017; Xu et al., 2019; Xie and Huang, 2022). Furthermore, differences in labor force characteristics (Zhang et al., 2014; Yang et al., 2019; Chen et al., 2022), arable land resource endowment (Zhang et al., 2016; Mou et al., 2022; Wang et al., 2022), and agricultural infrastructure (Mou et al., 2022; Xie and Huang, 2022) contribute to variations in the degree and spatial distribution of arable land abandonment. Recent research had extensively investigated and reported this phenomenon in China. The idle rate of arable land was 5.72% in 2013 (Jin and Xin, 2018), 14.32% in mountainous counties during 2015-2016 (Li et al., 2017), and approximately 20% nationwide in 2019 (Li et al., 2022). The degree of arable land abandonment exhibited significant regional differences, with higher rates in the central and western regions compared to the eastern regions (Jin and Xin, 2018), and higher rates in southern provinces than in northern provinces (Guo et al., 2020). Existing studies suggested that the degree and extent of arable land abandonment in China is increasing (Li et al., 2017; Jin and Xin, 2018; Zhang et al., 2019).
Terraces are strips or wavy sections of fields built along contour lines on mountain slopes (Li, 2011). They are the result of people’s long-term transformation and adaptation to nature, and are generally high-quality arable land in mountainous areas. Terraces are widely distributed worldwide, concentrated along the Mediterranean coast, in southern Africa, Central America, East Asia, and Southeast Asia. China was one of the first countries to build terraces, and has the most extensive distribution. Terracing in China dates back to the Qin and Han dynasties. The “Learning from Dazhai in Agriculture” movement in the 1960s led to the large-scale development of terraces (Li, 2011). In recent years, the Chinese government has constructed many terraces to control soil erosion in mountainous areas (CPGPRC, 2017). According to the Second National Land Survey in China, the scale of terraces in China is 18,610 thousand ha, accounting for 13.7% of the total area of arable land. Terraces are a crucial arable land resource in mountainous areas, offering functions such as reducing runoff, controlling soil erosion, improving soil fertility, and resisting natural disasters (Wei et al., 2016). Terraces effectively increase grain production (Liu et al., 2011) and, in historical times, played a vital role in meeting the demand for grain production due to population growth. To date, terracing remains a key measure to control soil erosion in China’s hilly and mountainous areas (Cao et al., 2021), contributing to an average benefit of 48.9% and 53.0% respectively in reducing runoff and sediment (Chen et al., 2017a). However, as the marginalization of mountainous areas intensifies, terraces are also experiencing the same effect, similar to sloping arable land. Abandoned land has extended from low-quality sloping land to higher-quality terraces. Many famous terrace scenic spots in China are facing serious abandonment, such as the Ziquejie terrace scenic spot in Xinhua county, Hunan province, with an abandonment rate of 20% in 2017 (DEHP, 2017), and the Hakka Terrace in Sishun township, Chongyi county, Jiangxi province, with an abandonment rate of up to 39% in 2014 (Miu et al., 2018).
The large-scale abandonment of terraces will lead to significant social and ecological implications. Terraces are high-quality cultivated land resources in mountainous areas. The non-grain (Cao et al., 2022) and extensive utilization (Xin et al., 2011) caused by the abandonment of terraces and the adjustment of agricultural planting structure poses a certain threat to food security. Additionally, terrace abandonment triggers a complex process of ecological evolution, including changes in mountain plant communities (Peña-Angulo et al., 2019; Rusterholz et al., 2020), soil erosion (Lasanta et al., 2001; Lesschen et al., 2008), carbon storage, landscape, and biodiversity (Arnaez et al., 2011; Londoño et al., 2017; Wang et al., 2019). Recently, the extent of arable land abandonment has increased, and this issue has garnered attention beyond academic research. As a result, China’s central and local governments have issued policy guidance documents to regulate arable land abandonment. In January 2021, the Ministry of Agriculture and Rural Affairs issued the “Guidance on the Coordinated Utilization of Abandoned Land for Developing Agricultural Production” (Development Planning Division, Ministry of Agriculture and Rural Affairs of China ([2021] No.1) (MARAPRC, 2021), emphasizing the importance of coordinated utilization of abandoned arable land and the adoption of measures to promote its reutilization.
However, research on terrace abandonment in China is mostly limited to small-scale or case studies (Miu et al., 2018; Wang et al., 2019; Zhang et al., 2020; Wu, 2021; Mou et al., 2022). Currently, research focuses more on the soil and water effects (Wang et al., 2019), biodiversity changes, and cultural loss risks (Miu et al., 2018). Such studies cannot adequately reflect the overall extent and spatial variability of terrace abandonment in China, making it difficult to support the formulation of policies aimed at addressing this issue. To address this gap, this study employs a national-scale questionnaire survey to evaluate the degree of terrace abandonment in China, analyze the spatial variation characteristics and drivers of terrace abandonment, and provide scientific references for the formulation of policies related to terrace utilization, conservation, and agricultural development.

2 Data acquisition and research methodology

2.1 Research object and scope of the study area

2.1.1 Research object

Terraces can be categorized as water and dry terraces based on cultivation methods as well as earth, stone, and mixed earth and stone terraces based on the type of field ridge; It can also be classified as wavy, reverse-slope, and horizontal terraces based on structure and appearance (Li, 2011; Chen et al., 2017b). In this study, “terrace” refers to a subdivision of arable land within the classification of land use status. It is defined as a strip or wave-like field built along contour lines on hillsides with slopes greater than 2°, excluding terraced gardens used for fruit and tea. Structurally, they are predominantly horizontal and reverse-slope terraces. In terms of cultivation methods, they are mainly used for rice cultivation in southern China and for dry crops in northern China. Based on relevant studies (Huang et al., 2008; Shi and Li, 2013; Xiao et al., 2019), abandoned terraces in this study refer to those left uncultivated for more than two consecutive years. Terraces converted to non-agricultural use due to the national reforestation project and fallow policy are not included in the scope of this study.

2.1.2 Survey area scope

The questionnaire survey conducted in this study is limited to counties (county-level cities and districts) in China’s hilly and mountainous areas with terraces. According to China’s Second National Land Survey completed in 2009, terraces are found in 1708 counties (county-level cities and districts) across 27 provincial-level regions (hereafter province) in China. It should be noted that four provinces, namely Heilongjiang, Tianjin, Shanghai, and Jiangsu, do not have obvious distribution of terraces, and data for Hong Kong SAR, Macao SAR, and Taiwan province are currently unavailable (Figure 1).
Figure 1 Regions of terraced fields and provincial areas of terraced fields in China

Note: Figure 1a is based on the standard map (GS (2016) 1595) downloaded from the standard map service website of the Ministry of Natural Resources, and the base map is unmodified, the same below.

To explore the spatial variation of terrace abandonment, according to the terraces distribution status of the Second National Land Survey and the national soil and water conservation zoning, this study divided Chinese terraces into six terrace distribution areas based on county-level administrative districts. The terraces in China are mostly concentrated in the northern rocky mountainous area (NRMA), the Loess Plateau area (LPA), the southern hilly and mountainous area (SHMA), and the southwestern mountainous area (SMA). As the terraced areas in the northern area and the Qinghai-Tibet Plateau area are smaller and have fewer collected samples, they were not included in the analysis (Figure 1).

2.2 Survey plan

2.2.1 Determination of the sample size for the survey

The size of the sample required for the questionnaire survey is influenced by various factors, such as the survey purpose, accuracy, method, degree of variation in the research object, and overall size of the survey (Yuan and Li, 2013). Although the sample size increases with the overall size of the survey, this relationship is not linear, and the increase in sample size becomes smaller and eventually stabilizes as the overall size increases (Feng, 2018). Several methods can be used to determine an appropriate sample size, and under similar survey conditions, different calculation methods yield similar sample sizes. In this study, we use the following formula (Krejcie and Morgan, 1970):
S = X2NP(1–P)/d2(N–1)+X2P(1–p)
where S represents the required sample size for the survey, X2 represents the Chi-Square value for one degree of freedom at the required confidence level (taken as 3.841), N represents the overall size, P represents the percentage of the overall population (taken as 0.5 at its maximum sample variability), and d represents the accuracy (taken as 0.05).
The total number of counties (N) with terraces in China is 1708, and the sample size (S) is determined to be 314 counties using equation (1), with a sampling proportion of 18%. Because of the wide survey area and high degree of regional heterogeneity in this study, a combination of stratified and random sampling was employed to ensure a balanced sample distribution and to improve the sampling efficiency and reliability of the sample survey results. To meet the requirements of stratified sampling, the proportion of terraced counties to be sampled in each province was based on the average of the proportion of terraced areas in each provincial administrative unit and proportion of the number of terraced counties. In addition, 1-2 administrative villages were randomly sampled in each selected county, and 4-6 farming households randomly surveyed in each administrative village.

2.2.2 Field survey

There were two ways to obtain questionnaires: the field survey conducted by college students when they returned to their hometowns during the winter and summer vacations and the field survey conducted by the members of the research group. University students who returned to their hometowns during winter and summer vacations were recruited to conduct the survey considering that terraces in China are widely distributed and a large number of samples cannot be surveyed in each area; this helped to increase the efficiency of the survey and reduce costs. Furthermore, university students, who are familiar with the basic situation of their own administrative villages, were able to communicate effectively, making it easier to obtain accurate survey results. To improve the reliability of the survey, university students majoring in disciplines such as geography, agriculture, and sociology were selected and given training and real-time guidance.
Three survey rounds were conducted by university students in January-March 2020, June-September 2020, and January-March 2021. However, because terraced areas are located in mountainous areas with limited access and the questionnaire survey was affected by the COVID-19 pandemic, the sample size in the design plan was not met. Therefore, supplementary surveys were conducted in areas with insufficient samples, such as Hubei, Hunan, Sichuan, Guizhou, Yunnan, Guangxi, Guangdong, Gansu, Shaanxi, and Anhui. Three supplementary field surveys were conducted in November-December 2020, March 2021, and April 2021.
During the survey, one village questionnaire and 4-6 farm household questionnaires were collected from each administrative village, and a survey report was written. The village-level questionnaire was designed to capture information on the village labor force, arable land area and quality, transfer of land use rights, arable land abandonment, and crop cultivation. The information of the village-level questionnaire was collected from the informed village cadres, mainly village directors and clerical staff. The household-level questionnaire was designed to capture information on family arable land area, arable land use, basic information on family members, and family income. The farm household questionnaire targeted households that operated arable land in the administrative village. Both village-level and household-level questionnaires covered the previous year’s situation, that is, the survey time points were 2019 and 2020.

2.2.3 Questionnaire collection

The survey carried out by university students and the research group covered a total of 346 counties across China, which accounts for 20% of the total number of terraced counties in the country. In total, 598 administrative village questionnaires and 2960 farming household questionnaires were collected. No questionnaires were collected in Tibet and Xinjiang.
The process of correcting and cleaning the questionnaires involved the following steps. (1) Checking and identifying possible errors and outliers in the questionnaires based on the information provided in the survey report, basic common sense and logic, and data consistency. (2) Communicating with the survey administrators via telephone callbacks to correct any errors or missing question items. (3) Conducting telephone callbacks by the research group to address unclear question items. (4) Eliminating questionnaires that did not meet the survey requirements, had obvious errors, and were not correctable. (5) Randomly deleting some samples in individual provinces due to oversampling as required by the sample survey.
Finally, 560 valid administrative village questionnaires and 2204 valid household questionnaires were obtained. The administrative village questionnaires covered 329 counties (Figure 2), accounting for 19% of the total number of terraced counties in China, exceeding the sample size threshold of 314 counties. The university students completed 399 questionnaires for administrative villages, accounting for 71% of the total, and the research team conducted 161 complementary surveys, accounting for 29%. In 2020, 490 village questionnaires were completed, accounting for 88% of the total, while 70 questionnaires were completed in 2021, accounting for 12%. The composition of the farming household questionnaires was the same as that for administrative villages.
Figure 2 Distribution of the surveyed counties in China

2.3 Research methods

2.3.1 Methodology for calculating the rate of terrace abandonment

The rate of terrace abandonment in this study was calculated based on the administrative village questionnaires to account for potential bias in the farming household survey due to migration of farmers. As the number of surveyed villages varied among different counties, the data for each county were initially processed according to the requirements of stratified sampling (Li et al., 2017). Then, the abandonment rate was calculated for different scales using the following formula:
$CB{{A}_{i}}=\underset{j=1}{\overset{n}{\mathop{\mathop{\sum }^{}}}}\,VB{{A}_{ij}}/n$
$C{{A}_{i}}=\underset{j=1}{\overset{n}{\mathop{\mathop{\sum }^{}}}}\,V{{A}_{ij}}/n$
where CBAi denotes the average area of abandoned terraces in research county i, which is the mean value of the total abandoned terrace area of n administrative villages in the county; VBAij represents the abandoned terrace area of administrative village j in research county i; CAi represents the average area of terraces in research county i, which is the mean value of the total terrace area of n administrative villages in the county; VAij is the total terrace area of administrative village j in research county i; and R is the rate of terrace abandonment, which is the ratio of the total average area of abandoned terraces in m research counties to that of terraces in m research counties.

2.3.2 Analysis of variance (ANOVA) method

This study utilized ANOVA to validate the spatial differentiation level of terrace abandonment. ANOVA examines whether the differences in the means of two or more dependent variables are statistically significant, also known as the F-test. The ANOVA is based on the idea of variation decomposition, which can categorize the variation of the whole sample into random variation and variation due to treatment factors. It can prove the existence of variation caused by treatment factors (Zhang, 2017). Generally, ANOVA requires the randomization and independence of samples under each treatment level, homogeneity of variance between groups, and normal distribution of dependent variables. Before performing a single-factor ANOVA, homogeneity of variance test should be conducted. When the sample does not pass the test, the Welch test is preferred over the F-test. When there are multiple treatment factors, post hoc comparisons can be performed. Under conditions where homogeneity of variance is not met, Tamhane’s T2 test is used as the result of multiple comparisons. In this study, SPSS 26.0 was employed to conduct a single-factor ANOVA.

3 Results

3.1 Characteristics of the temporal evolution of terrace abandonment

It can be observed that the phenomenon of terrace abandonment in China has been evolving since the 1980s based on an analysis of 244 administrative village questionnaires with records of terrace abandonment. Since 2000, there has been a significant increase in the number of villages with abandoned terraces (Figure 3). Before 2000, villages with abandoned terraces were mainly located in SHMA. However, after 2000, there had been a significant increase in the number of villages with abandoned terraces in the LPA, SHMA, and SMA. Notably, between 2010 and 2015, there was a significant increase in the number of villages with abandoned terraces. In contrast, the number of villages with abandoned terraces was low in the NRMA, and the temporal trend noted above was not salient.
Figure 3 Temporal changes of surveyed villages with terrace abandonment in China

3.2 Quantity of villages with abandoned terraces

The proportion of villages with abandoned terraces in China accounted for 54% of the total number of villages surveyed, with 65% in the southern provinces and 28% in the northern provinces. Among the four major terrace areas, the SHMA has the most severe terrace abandonment, with villages with abandoned terraces accounting for 72% of the total. In the SMA, the proportion was 55%, 38% in the LPA, 20% in the NRMA.
Among the provinces surveyed, no abandoned terraces were observed in the surveyed villages in Jilin, Liaoning, Inner Mongolia, Qinghai, and Hainan, whereas abandoned terraces occurred in other provinces to varying degrees. Specifically, the proportion of the number of villages with abandoned terraces was over 60% in Guangdong, Fujian, Guizhou, Zhejiang, Hunan, Anhui, Chongqing, and Hubei. That proportion ranged from 20% to 60% in Jiangxi, Ningxia, Sichuan, Guangxi, Yunnan, Shaanxi, Shanxi, Gansu, and Hebei. Moreover, the proportion accounted for less than 20% in Henan and Shandong (Figure 4).
Figure 4 The number of surveyed villages with terrace abandonment in China

3.3 Area of abandoned terraces

In China, the abandonment rate of terrace area was 9.79%, with the degree of abandonment significantly higher in southern than in northern China. Among the four major terrace areas, there were significant differences in the degree of abandonment. The highest degree of abandonment occurred in the SHMA, with a rate of 20.96%, followed by 7.16% in the SMA, 4.36% in the LPA, and 3.04% in the NRMA.
The one-way ANOVA results showed statistically significant differences (Welch test, p < 0.05) in the degree of abandonment between the northern and southern China as well as the four major terrace areas. The Tamhane multiple comparisons revealed significant differences (p < 0.05) among the degree of abandonment in the NRMA, the SHMA and the SMA. Moreover, significant differences (p < 0.05) were found between the degree of abandonment in the LPA and SHMA. The differences passed the significance test (p < 0.05) between the SHMA and the NRMA, LPA, and SMA. The significance test was not passed in the LPA, NRMA, and SMA.
Similarly, as with the characteristics of the four major terrace areas, there were significant differences in the degree of terrace abandonment among provinces, with the most severe cases concentrated in the middle and lower Yangtze River region. Specifically, the most severe abandonment of terraces occurred in Guangdong and Beijing, with abandonment rates of 44.67% and 30%, respectively. The provinces of the middle and lower Yangtze River region, such as Fujian, Jiangxi, Zhejiang, Chongqing, Anhui, Hubei, and Hunan, had abandonment rates between 10% and 25%. Meanwhile, the abandonment rates in Guizhou and Shaanxi were between 6% and 10%, while in Guangxi, Shanxi, Ningxia, Sichuan, Yunnan, Hebei, Gansu, and Henan, the rates were between 2% and 6%. The abandonment rates in Shandong, Hainan, Qinghai, Jilin, Liaoning, and Inner Mongolia were below 2% (Figure 5).
Figure 5 Provincial terrace abandonment rate in China

4 Discussion

4.1 Evaluation of survey results

Previous studies have focused on the abandonment rate of arable land. To increase comparability with other survey data, this study also calculated the abandonment rate of arable land in the survey area using the same method as the terrace abandonment rate calculation.
The results showed that the abandonment rate of arable land in Chinese terraced areas was 9.01%, which was higher than the national abandonment rate of 5.72% in 2013 calculated by Jin Fangfang et al. using China Household Income Survey data in 2013 (Jin and Xin, 2018). This is probably because the scope of Jin Fangfang et al.’s study included plain areas with lower abandonment rates and the degree of arable land abandonment increased over time. However, the abandonment rate of arable land in the mountainous counties nationwide, calculated by Li Shengfa et al. using a sampling survey method in 2014-2015, was 14.32% (Li et al., 2017), which was higher than the rate found in this study. This difference may be due to the wider geographical scope of this survey, which covered not only mountainous counties but also relatively flat hilly areas.
Regarding the timing, arable land abandonment in China began to increase after 2000 (Li et al., 2017; Zhang et al., 2019), with a sudden increase in 2005 (Li et al., 2017). Similarly, the terrace abandonment phenomenon in this study also began to emerge around 2000 and increased significantly around 2010. The development of terrace abandonment lagged behind that of slope farmland abandonment, which is in line with the characteristics of marginal development of farmland (Li and Li, 2019).
Regarding regional differences in the degree of arable land abandonment, arable land abandonment is more serious in southern and western China (Li et al., 2017; Jin and Xin, 2018), especially in regions such as the Yangtze River Basin and the Yunnan-Guizhou Plateau (Li et al., 2017; Zhang et al., 2019; Li et al., 2022). However, in this study, abandoned terraces were more concentrated and mainly distributed in the middle and lower Yangtze River region. Apart from a few provinces, the southwestern and northern China had a relatively low degree of abandonment.
Our study showed that China’s terrace abandonment rate was 9.79%. According to the Second National Land Survey in China, the total area of terraces in China is 280 million mu (1 mu ≈666.7 m²). Therefore, the area of abandoned terraces was estimated at 28 million mu, which is similar to the arable land area of Zhejiang or six times the planned scale of terraces converted from sloping arable land (4.91 million mu) across China during the 13th Five-Year Plan (2016-2020) (CPGPRC, 2017).
The large-scale abandonment of terraced fields undoubtedly wastes labor and capital inputs, reduces livelihood assets of mountain farmers, and increases ecological risks and food production losses. In addition, during this survey, no suitable survey sites or surveyors were found in Xinjiang and Tibet, and questionnaires were not collected in these two provinces. According to the data from the Second National Land Survey in China, the terraces in Xinjiang and Tibet accounted for a relatively low 0.12% and 0.21% in the national total terrace area, respectively. Therefore, ignoring these two regions on the national terrace abandonment rate calculation would not significantly affect the results.

4.2 Causes of terrace abandonment

Village cadres serve as both the practical managers of the village and operators of the arable land, possessing a strong cognitive ability regarding the causes of terrace abandonment. Based on the cognitive responses provided by the village cadres, this study summarized the reasons for terrace abandonment (Figure 6a). The order of recognition is as follows: (1) a large number of migrant workers; (2) low level of mechanization in terrace farming; (3) poor irrigation conditions in terraces; (4) poor transportation conditions for farming; (5) damage by wild animals; and (6) poor fertility of the terraces. Regarding each major terrace area, labor migration was the primary factor, followed by mechanization levels. Notably, damage by wild animals was more significant in the SHMA. Other factors demonstrated relatively little variability among areas.
Figure 6 The primary driving factors of terrace abandonment
Specifically, the proportion of migrant workers was highest in the SHMA, followed by the SMA, LPA, and NRMA. The LPA had the highest level of mechanization in terrace farming, followed by the NRMA. The rates of terrace mechanization in the SHMA and the SMA were similar. The irrigation conditions were better in the SMA and SHMA, and worse in the NRMA and LPA. In terms of quality, the terraces are of poor quality in the NRMA, while the differences among other areas were insignificant. Regarding the condition of farming transportation, the LPA had the highest proportion of villages with tractor roads. The SMA and NRMA had a similar proportion, while the SHMA had the lowest proportion. In terms of damage by wild animals, the proportion of villages with wildlife damage was higher in the LPA and SHMA, followed by the SMA, while the proportion was low in the NRMA (Figures 6b-6d).
The findings indicate that areas with a higher proportion of migrant workers and lower levels of mechanization have a higher rate of terrace abandonment. The areas with better farming transportation conditions had a lower rate of terrace abandonment. Regarding damage by wild animals, the rule that the more severe the damage, the higher the terrace abandonment rate, applied to all regions except for the LPA. There was no consistent trend between the differences in irrigation conditions, terrace quality, and abandoned areas. Therefore, we concluded that the causes of terrace abandonment were consistent with the marginalization mechanism of cultivated land in mountainous areas. The rising opportunity cost of farming and increasing costs of agricultural labor have led to increased costs for non-mechanized terrace farming, reduced profits, and consequently, terrace abandonment. In the process of labor force outflow in agriculture, promoting the substitution of labor by machinery and improving the agricultural production environment are the key to reducing terrace abandonment.

5 Conclusions and policy implications

5.1 Conclusions

This study sampled 1708 terraced counties in China, a total of 560 administrative village questionnaires and 2204 farming household questionnaires were obtained, covering 25 provinces and 329 counties. This is the first study in China about terrace abandonment using a large fieldwork sample. The main findings are as follows:
(1) Terrace abandonment in China was severe and widely distributed. The degree of abandonment was significantly higher in the south than in the north. In terms of area, the rate of terrace abandonment across China was 9.79%, and 54% of villages had abandoned terraces. By region, the abandonment rate of terraces in the SHMA was the highest at 20.96%, especially in the middle and lower Yangtze River region. At the provincial level, the abandonment rate of terraces exceeded 10% in nine provinces, mainly in the south. From highest to lowest, the order of abandonment rate was Guangdong, Beijing, Fujian, Jiangxi, Zhejiang, Chongqing, Anhui, Hubei and Hunan.
(2) Terrace abandonment first emerged in the 1980s, but became more pronounced around 2000 and increased significantly in the period between 2010 and 2015. Before 2000, terrace abandonment mainly occurred in the SHMA. Since 2000, terrace abandonment had increased significantly in LPA, SHMA, and SMA. The phenomenon of terrace abandonment in the NRMA was less, and the development trend of abandonment was not obvious.
(3) The main reasons for terrace abandonment were the large number of migrant workers and the low degree of mechanization in terrace farming. According to the survey responses of village cadres, the large number of migrant workers was the primary factor affecting terrace abandonment, which corresponded to the objective statistical results that the proportion of migrant workers was the highest in the SHMA where the degree of abandonment was most severe. In addition, the degree of mechanization and the transportation conditions also had a significant impact on terrace abandonment.

5.2 Policy implications

The field investigation revealed that local governments are currently implementing the following measures to prevent terrace abandonment: (1) formulating mandatory measures to prevent arable land abandonment, such as a policy in some regions where “village collectives will take back arable land if it has been abandoned for more than two years”; (2) transferring terraces under the leadership of local governments to develop special industries or tourism; and (3) subsidizing special industries or terraced scenic spots. However, these measures have not been effective due to the lack of sustainability and effectiveness, as well as high implementation costs. In addition, although the government has increasingly focused on preventing arable land abandonment in recent years and issued several relevant policy documents, there is a lack of specific policies regarding terraces.
It is necessary to enhance terrace abandonment management by using classification and zoning to effectively prevent terrace abandonment and ensure national food security and stable livelihoods for farmers in mountainous areas. Based on the research findings, the following measures are proposed: (1) For terraces with a large slope, long cultivation distance, and poor quality, “retiring” the land and returning it to forestry can be implemented in a structured way. For terraces that are closer to villages and of better quality, characteristic forestry, fruit, and other economic crops should be promoted according to local conditions. (2) The transfer of land use rights can be encouraged to promote the effective use of terraces. (3) Agricultural infrastructure should be improved to appropriately promote the mechanization of terraces. For terraces with a gentle slope and larger plots in the Loess Plateau region, medium and even large-scale agricultural machinery can be promoted through the consolidation of land plots and road construction. For terraces with a large slope and smaller plots in hilly and mountainous areas in southern China, small agricultural machinery can be promoted. (4) Strengthening subsidies for agricultural machinery purchases should be considered, with a focus on promoting socialized services for agricultural machinery to alleviate labor shortages and lower production costs in agriculture.
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