Farmland Abandonment Research Articles

The Current Scenario of Farmland Abandonment in China: A Systematic Review

The significant expansion of farmland abandonment not only poses a threat to agricultural sustainability, but also challenges biodiversity conservation and food security. This study aims to initiate a deep systematic analysis of the current scenario of Chinese farmland abandonment, which is timely and urgent as a starting point to fully understand the current state of knowledge of it. In total, 181 articles out of 5384 articles through four databases (CNKI, Web of Science core collection, Scopus, and CAB Abstracts) are extracted and synthesized by the PRISMA method. A total of 12 experts from 11 countries with specialized knowledge in the research field are interviewed. It is found that farmland abandonment in East China is the most frequently reported, which is followed by the Southwest. The research focus in China has shifted from mountainous areas to agricultural and pastoral areas and major grain-producing areas. Chinese farmland abandonment is defined principally from the perspective of the managerial approach. An inventory that categorizes these different drivers of farmland abandonment is built, which includes socio-economic aspects, biophysical attributes, policy, household characteristics, and specific events. Socio-economic aspects, especially off-farm employment, are the most commonly studied factors. Meanwhile, the aging of the population is also noteworthy. Different trajectories should be applied accordingly due to the significant differences between North and South China. Furthermore, there is an optimistic attitude towards the ecological impact of abandoned farmland in China. However, more evidence should be given on it. Those findings will hopefully provide some insights for the scientific community and policy makers.

A novel interpretation of farmland abandonment: evidence from the famine experience

The growing severity of farmland abandonment in rural areas has sparked concerns about the lack of people willing to cultivate the land. This study attempts to find the endogenous factors of farmland land abandonment among Chinese farmers and to curb land degradation to stabilize food security. Based on the China Labor-force Dynamics Survey (2016–2018), this paper explores the effect of famine experience on farmland abandonment using logit and DID models. We find that famine experience does increase the probability and extent of farmland abandonment, and undergo a series of robustness tests. We also find that the famine stigma effect increases the likelihood and extent of farmland abandonment by increasing risk aversion and reducing social trust and investment in agriculture. The growth of urbanization in China worsens the effects of famine, whereas local communal production services remove the effects of famine. The overall findings of this study provide useful insights for the government to protect land quality and food security and to carefully consider the role played by communities.

Reducing farmland abandonment by raising women’s education levels: Evidence from China

With the rapid industrialization and the growing demand for male labor in urban industries, agricultural production in many developing countries presents obvious feminization features. Accordingly, improving the education level of rural women is the key to increasing farmland return and reducing farmland abandonment. Using data from the China Labor-force Dynamics Survey (CLDS), this study examines the effect of rural women’s education on farmland abandonment. The results reveal that for each increase in the education level of a hostess in a rural household, the abandoned farmland of that household decreases by 40 m2. The increase in women’s education level can promote the use of the Internet, help households access credit, and better control the costs of agricultural production, thus curbing farmland abandonment. In addition, women’s education can play a stronger role in reducing farmland abandonment for rural areas where the land rental market is well developed, as well as for families whose male hosts go out to join non-farm work.

Farmland Abandonment and Afforestation—Socioeconomic and Biophysical Patterns of Land Use Change at the Municipal Level in Galicia, Northwest Spain

Farmland Abandonment and Afforestation—Socioeconomic and Biophysical Patterns of Land Use Change at the Municipal Level in Galicia, Northwest Spain

Will fire-smart landscape management buffer the effects of climate and land-use changes on fire regimes?

BackgroundLong-term farmland abandonment has increased fuel build-up in many Euro-Mediterranean mountainous regions. The high fuel hazard in these landscapes, combined with ongoing climate change, is increasing the frequency of extreme wildfires, thus altering contemporary fire regimes. Mitigating the loss of the landscape’s capacity to regulate large and intense fires is crucial to prevent future harmful effects of fires. As such, effective strategies to manage these fire-prone landscapes are needed. Yet, further understanding of their performance under global change scenarios is required. This study assessed the effects of fire-smart management strategies on future landscape dynamics, fire regulation capacity (FRC), and fire regime in a Mediterranean fire-prone mountainous landscape in Portugal (30,650 ha) undergoing long-term land abandonment and climate change scenarios. For that, we applied the LANDIS-II model under climate change scenarios (RCP 4.5 and 8.5) and long-term farmland abandonment (2020–2050) according to three fire-smart management strategies focused on fire prevention compared with a business-as-usual (BAU) strategy based on fire suppression.ResultsFuture fire activity and land dynamics resulted in changes that fostered landscape heterogeneity and fragmentation and favoured fire-adapted forests and agroforestry systems while decreasing the dominance of shrublands and croplands. FRC decreased over time, particularly under RCP 8.5 and the BAU strategy. In turn, fire-smart strategies better prevented large and intense fires than the BAU strategy, but their effectiveness decreased under RCP 8.5. The loss of FRC resulted in increased burned area and fire frequency, which predicts a shift from contemporary fire regimes but more markedly under RCP 8.5 and in the BAU strategy.ConclusionsFire-smart strategies outperformed BAU in averting current fire regime intensification. Merging forest- and silvopasture-based management is the most promising approach in taming the effects of climate and farmland abandonment on future fire activity. Our study underlines that planning and management policies in fire-prone Mediterranean mountain landscapes must integrate fire-smart strategies to decrease landscape fuel hazard and buffer the impact of global change on future fire regimes.

Semantic Web Techniques for Extracting and Analyzing of Cropland Abandonment in Hilly Areas

Due to rising rural labor costs, farmland abandonment is common in China's hilly areas. Timely, accurate extraction of its spatiotemporal changes is crucial for sustainable farmland use. This study presents a novel approach for extracting abandoned cropland using NDVI time series from Sentinel-2 satellite images, exploiting the difference in vegetation phenology between abandoned and cultivated croplands. Dynamic Time Warping (DTW) algorithm was used to determine the similarity between NDVI time-series curves of different cropland types. The similarity metrics were used to find the optimal NDVI threshold for abandoned cropland through F1-score evaluation. The method's overall accuracy is 92.4%, higher than comparison methods at 84.60% and 75.6%. The approach captures year-round vegetation changes, expands time dimension data, and improves accuracy. Spatiotemporal analysis revealed decreased patch size, increased shape complexity, and more dispersed distribution of abandoned cropland over time. Major factors were proximity to settlements, roads, water bodies.

An OVR-FWP-RF Machine Learning Algorithm for Identification of Abandoned Farmland in Hilly Areas Using Multispectral Remote Sensing Data

Serious farmland abandonment in hilly areas, and the resolution of commonly used satellite-borne remote sensing images are insufficient to meet the needs of identifying abandoned farmland in such regions. Furthermore, addressing the problem of identifying abandoned farmland in hilly areas with a certain level of accuracy is a crucial issue in the research of extracting information on abandoned farmland patches from remote sensing images. Taking a typical hilly village as an example, this study utilizes airborne multispectral remote sensing images, incorporating various feature factors such as spectral characteristics and texture features. Aiming at the issue of identifying abandoned farmland in hilly areas, a method for extracting abandoned farmland based on the OVR-FWP-RF algorithm is proposed. Furthermore, two machine learning algorithms, Random Forest (RF) and XGBoost, are also utilized for comparison. The results indicate that the overall accuracy (OA) of the OVR-FWP-RF, Random Forest, and XGboost classification algorithms have reached 92.66%, 90.55%, and 90.75%, respectively, with corresponding Kappa coefficients of 0.9064, 0.8796, and 0.8824. Therefore, by combining spectral features, texture features, and vegetation factors, the use of machine learning methods can improve the accuracy of identifying ground objects. Moreover, the OVR-FWP-RF algorithm outperforms the Random Forest and XGboost. Specifically, when using the OVR-FWP-RF algorithm to identify abandoned farmland, its producer accuracy (PA) is 3.22% and 0.71% higher than Random Forest and XGboost, respectively, while the user accuracy (UA) is also 5.27% and 6.68% higher, respectively. Therefore, OVR-FWP-RF can significantly improve the accuracy of abandoned farmland identification and other land use type recognition in hilly areas, providing a new method for abandoned farmland identification and other land type classification in hilly areas, as well as a useful reference for abandoned farmland identification research in other similar areas.

Assessment of gully influencing factors and susceptibility using remote sensing-based frequency ratio method in Sunshui River Basin, Southwest China.

Gully erosion is a serious global environmental problem associated with land degradation and ecosystem security. Examining the influencing factors of gullies and determining susceptibility hold significance in environmental sustainability. The study evaluates the spatial distribution, influencing factors, and susceptibility of gullies in the Sunshui River Basin in Sichuan Province, Southwest China. The frequency ratio method supported by satellite images and the gully inventory dataset (1614 gully head points) with different influencing factors were applied to assess the distribution and susceptibility of gullies. Additionally, gully head points were grouped into a training set (70%, 1130 points) and a test set (30%, 484 points). Spatial distribution results indicated that most gullies are located in the middle and upper part of the basin, characterized by moderate elevation (2100-3300m), steep slopes (11.63-27.34°), abandoned farmland, and Cambisols soil, and fewer gullies are located in lower part characterized by lower elevation, gentle slopes, and low vegetation coverage. Land use and land cover influence on susceptibility is significantly greater than other factors with a prediction rate of 33.9, especially farmland abandonment, while the occurrence of gullies is also more often on southwest-orientated slopes. Gully susceptibility highlighted that the study area affected by the very low, low, moderate, high, and very high susceptibilities to these gullies covered an area of about 16%, 23%, 32%, 26%, and 3% of the total basin respectively, which indicates 61% of the study area is susceptible to gully erosion. Moderate to high susceptibility is situated in the upper and middle part, consistent with the spatial distribution of gullies in the basin, and very high susceptibility (3%) is distributed in both the lower and upper parts of the basin. These results have important implications for soil loss control, land planning, and integrated watershed management in the mountainous areas of Southwest China.

Precipitation and time effects on vegetation change in Southern Arizona abandoned farmland

Farmland abandonment represents a significant issue globally, and in arid environments reclaiming ecosystems is challenging. In the Sonoran Desert, much irrigated farmland has been abandoned since 1950. Our objective was to compare changes in vegetative (canopy) cover and species over a 26-year period on abandoned farmland and unfarmed controls in southcentral Arizona (precipitation <300 mm/year). We evaluated time since abandonment and precipitation effects on these variables between 1976 and 2003 with point frame methods on eight farmland sites using stepwise multiple regression. Results suggest antecedent precipitation (AP) is more important than time since abandonment in explaining cover changes. On 26 abandoned sites, we used non-parametric ANOVA to show that vegetative cover (point frame and line intercept methods) declined by about 43% from 1977 to 2023, which was greater than on non-farmed controls. Few farmlands had cover and species composition like reference communities in 2003. Paired farmland-control sites exhibited similar vegetation in 1977 and 2003 suggesting local factors (e.g., soil chemistry, roadways) may have overwhelmed that of farming. Uninterrupted (natural) surface water flow may predict where revegetation was most successful. Our research indicates that farmland may exist in alternative states, and passive revegetation will not reestablish native Sonoran Desert communities on most abandoned farmland sites.

Understanding Japan's Land-use Dynamics between 1987 and 2050 using Land Accounting and Scenario Analysis

Amidst global concerns about land use change and its far-reaching impact on biodiversity and human well-being, there is a growing need to understand how land use stock and flow changes over time through land use accounting. While existing studies on land accounting have focused on historical land changes, little attention has been paid to future transitions. This study assessed historical patterns and projected future shifts in land use dynamics from 1987 to 2050 across Japan by combining high-resolution land use and land cover datasets, land change simulations, and land accounting. In the analyses, particular attention was paid to the historical and future trends of farmland abandonment by leveraging data at 100-m resolution built on national vegetation surveys. High-resolution analysis of farmland abandonment issue with national scale in Japan is a novelty. From 1987 to 1998, the land stock analysis results showed a pronounced marked increase in residential land (10.4%) and grassland (16.9%); the flow analysis results showed that urban residential sprawl expansion was mainly formed by secondary (32.6%) and plantation (21.1%) forest areas, coinciding with increasing population and economic growth. Projections from 2010 to 2050 indicate a marked increase in abandoned farmland (67.2% per decade), a trend influenced by rapid population decline and presumably agricultural policies, especially significant in regions such as Hokkaido and Kyushu. The findings of this study are crucial for shaping policy and decision-making, underlining the need for sustainable land management strategies that effectively balance urban growth, agricultural productivity, and environmental preservation in Japan.

Analysis of the spatial differentiation and driving force of arable land abandonment and non-grain in the hilly mountainous areas of Gannan

Food security has a bearing on national development and people's livelihoods and is an important guarantee of social stability for national development. The problems of arable land abandonment and non-grain are becoming more and more serious, and national food security is difficult to guarantee, which will seriously hinder the forward development of China's society and economy. Taking Ruijin City of Jiangxi Province as an example, this study calculated the abandonment level and non-grain level of arable land in Ruijin City respectively from two aspects, and explored the spatial differentiation law of farmland abandonment and non-grain level in the hilly and mountainous areas of southern Jiangxi Province by using spatial autocorrelation and cold and hot spot analysis methods, and the causes of arable land abandonment and non-grain spatial differentiation in the hilly mountainous areas of Gannan were revealed by the methods of Geodetector factor detection and interaction detection. Conclusions of the study: (1) Ruijin City, the abandoned area was 1216.73 hm2, the abandonment rate of each village ranged from 0.01 % to 50.62 %, and the comprehensive abandonment rate was 4.90 %; the area of non-grain was 2937.27 hm2, and the rate of non-grain of each village ranged from 0.01 % to 100.00 %, and the comprehensive non-grain rate was 11.83 %. The area of non-grain was 2937.27 hm2, and the rate of non-grain in each village ranged from 0.01 % to 100.00 %, and the comprehensive rate of non-grain was 11.83 %. (2) The phenomenon of abandonment of arable land and non-grain in Gannan hilly and mountainous areas has a certain clustering and driving effect in space. Globally, the phenomena of arable land abandonment and non-grain in Ruijin City are positively correlated, with the global Moran's I of arable land abandonment rate being 0.05, and the global Moran's I of arable land non-grain being 0.73. (3) Whether or not arable land in the hilly mountainous areas of Gannan is abandoned is affected by the combination of socioeconomics, natural resources, farming conditions, and economic location, with elevation, the degree of arable land contiguity, and population density being the dominant factors. The interaction of elevation, degree of concentration and contiguity, field regularity, and per capita arable land area increased the spatial variability of arable land abandonment in the hilly mountainous areas of Gannan. Whether the phenomenon of non-grain occurs or not is affected by socio-economic conditions, farming conditions and economic location, of which the proportion of paddy fields, land transfer price, arable land area, and urban-rural gradient are the dominant factors. The proportion of paddy land, the price of land transfer, the area of arable land, and the urban-rural gradient interact with each other, and the tendency of arable land to be planted with non-grain crops is more serious.

The Impact of and Mechanism behind High-Standard Farmland Construction in Farmland Abandonment: A Moderated Mediating Analysis

The Impact of and Mechanism behind High-Standard Farmland Construction in Farmland Abandonment: A Moderated Mediating Analysis

Does off-farm work induce farmland abandonment? Evidence from China

PurposeThis study investigates whether, how and under what circumstances off-farm work induces farmland abandonment, which is of great importance for developing countries to cope with food security.Design/methodology/approachExploiting large-scale panel data from the newly released Chinese Family Database, this study employs a two-way fixed effects model to empirically estimate the causal relationship between off-farm work and farmland abandonment.FindingsIn the context of large-scale labor migration in rural China, current off-farm work leads to an increase in the probability and area of farmland abandoned due to insufficient agricultural labor. However, off-farm work does not harm farm households in plain areas, or villages with land rental markets, abundant agricultural labor, and agricultural machinery, while it harms others. Moreover, farmers who work off-farm in the local area are less likely to abandon their farmland than those in other areas. Additionally, when the number of off-farm workers in a household exceeds two, the probability and area of farmland abandonment will miraculously decline, as the household will no longer live entirely on agriculture.Originality/valueThis study may fill the gap in clarifying the relationship between off-farm work and farmland abandonment, and identify scenarios where off-farm work may not cause farmland abandonment through multiple dimensions, providing insights into the governance of farmland abandonment during rural-urban transformation in developing countries.

Recreational agroecosystem service value evidenced by mobile phone data: implications for incentive enhancement in terraced paddy land

Summary Farmland abandonment contributes to agroecosystem degradation and food crises. Sustainable farmland use requires a well-designed agri-environmental policy to provide farmers with incentives, including agroecosystem services apart from food production. One of these is recreation. Here, we focus on a Japanese terraced paddy land. We assessed seasonal changes in the value of recreational ecosystem services by integrating mobile phone big data of on-site visitors, collected between 2018 and 2020, into a valuation method. The application of mobile data enables the precise and consistent analysis of non-market agroecosystem services. The recreational value of the paddy land varied with season but overall was high. Sustainable farmland use provides social benefits, and we support the validity of agri-environmental policies that relate to economic incentives for agroecosystem conservation. However, the results show that the incentives provided by the public/government may be insufficient in comparison to this recreational value. Our findings provide information regarding the appropriate amount of economic support required to achieve sustainable agricultural land use in this setting.

Changes in Soil Erosion Resistance after Farmland Abandonment in the Karst Rocky Desertification Area of Southwest China

Changes in Soil Erosion Resistance after Farmland Abandonment in the Karst Rocky Desertification Area of Southwest China

The Relationship between Farmland Abandonment and Urbanization Processes: A Case Study in Four Chinese Urban Agglomerations

Clarifying the relationship between urbanization and farmland abandonment in urban agglomerations (UAs) is crucial to guide the formulation of arable land management policies and strategies for sustainable urban development. Despite numerous studies confirming the correlation between farmland abandonment and certain urbanization factors, the exploration of the patterns and underlying mechanisms of farmland abandonment in China’s UAs remains worthy of systematic investigation. In this study, we conducted an analysis of the spatiotemporal trends in farmland abandonment and examined the key drivers of farmland abandonment in four representative Chinese UAs—Beijing–Tianjin–Hebei (BTH), Chengdu–Chongqing (CC), Pearl River Delta (PRD), and Yangtze River Delta (YRD). Our findings reveal that farmland abandonment has been intensified with increasing fragmentation and aggregation patches across these UAs. Abandonment experience was the main driver of continuous abandonment. Moreover, natural conditions persistently influenced farmland abandonment in the BTH, while land urbanization and economic urbanization were predominant drivers in the CC. The abandonment in the PRD was mainly driven by population urbanization, while the abandonment in the YRD was primarily driven by economic urbanization and land urbanization. The research findings provide data support and scientific explanation for land policy-making in these typical UAs under different development strategies.

Contrasting roles of plant, bacterial, and fungal diversity in soil organic carbon accrual during ecosystem restoration: A meta-analysis

Plant and microbial diversity plays vital roles in soil organic carbon (SOC) accumulation during ecosystem restoration. However, how soil microbial diversity mediates the positive effects of plant diversity on carbon accumulation during vegetation restoration remains unclear. We conducted a large-scale meta-analysis with 353 paired observations from 65 studies to examine how plant and microbial diversity changed over 0–160 years of natural restoration and its connection to SOC accrual in the topsoil (0–10 cm). Results showed that natural restoration significantly increased plant aboveground biomass (122.09 %), belowground biomass (153.05 %), and richness (21.99 %) and SOC accumulation (32.34 %) but had no significant impact on microbial diversity. Over time, bacterial and fungal richness increased and then decreased. The responses of major microbial phyla, in terms of relative abundance, varied across restoration and ecosystem types. Specifically, Ascomycota and Zygomycota decreased more under farmland abandonment than under grazing exclusion. In forest, Bacteroidetes, Ascomycota, and Zygomycota significantly decreased after natural restoration. The increase in SOC and Basidiomycota was higher in forest than in grassland. Based on standardized estimates, structural equation modeling showed that plant diversity had the highest positive effect (0.55) on SOC accrual, and while fungal diversity (0.15) also had a positive effective, bacterial diversity (−0.20) had a negative effect. Plant diversity promoted SOC accumulation by directly impacting biomass and soil moisture and total nitrogen and indirectly influencing soil microbial richness. This meta-analysis highlights the significant roles of plant diversity and microbial diversity in carbon accumulation during natural restoration and elucidates their relative contributions to carbon accumulation, thereby aiding in more precise predictions of soil carbon sequestration.

Exploring cultural landscape narratives to understand challenges for collaboration and their implications for governance

ABSTRACT Ongoing land use change, including both land abandonment and agricultural intensification and expansion, not only present a threat for biodiversity and ecosystem health but also for the persistence of cultural landscapes. However, farmland abandonment and the resulting loss of traditional cultural landscapes is an under-researched topic in the literature. Our work in a transdisciplinary action research project in the Spreewald Biosphere Reserve suggested that challenges to preserve the cultural landscape are rooted in diverging landscape understandings and future aspirations. Dealing with and integrating different perceptions and viewpoints is a key challenge in landscape governance. Narratives as storylines about a topic or an issue have a structural and temporal dimension and can help understand land-use conflicts and different viewpoints. We adopted a social constructivist perspective on landscape to engage with meanings and perceptions (including values) that constitute landscape to diverse stakeholders. To understand these differences in meaning, we drew on Q-methodology and conducted 38 interviews with key stakeholders. We elicited three co-existing and partly overlapping landscape narratives. These differ with regard to meanings of the term cultural landscape, including how stakeholders characterise the landscape, how they appreciate it, and what they perceive as threats. We show how such differences in meanings and values attributed to the landscape translate to different problem framings and future aspirations and thus present a barrier for collaborative management and governance. We highlight how participatory vision development could help address narrative tensions and argue that a more integrative perspective would better include cultural aspects.

Analyzing land use and land cover change in the Pra River Basin: A multi-tool approach for informed decision-making

Quantifying land use and land cover change (LULCC) is essential for addressing societal challenges and conserving ecosystems. This study focuses on analyzing the dynamics of five LULC classifications at a 30 m spatial resolution using satellite imagery from Landsat, coupled with various tools (Google Earth Engine, ArcMap, QGIS, and IDRISI SELVA) and indicators such as the Bare Soil Index (BSI). Historic time series data (2007, 2015, and 2023) were utilized to assess land change and predict future scenarios (2030 and 2063) using (CA) Markov models of the land change modeler (LCM). With a kappa coefficient and overall accuracy of 95 %, and 93 % respectively, our analysis reveals that LUC has significantly impacted nearly a third of the Pra River Basin (PRB) land area in two decades (2007–2023) after the launch of Agenda 2063 (The Africa We Want), with projected future impacts doubling under a business-as-usual (BAU) scenario. Geographical variations in LULC change processes are evident, with farmland abandonment, deforestation, and agricultural expansion observed predominantly in the northwestern region (Upper Pra, Anum, and Birim) of the basin. A 25 % increment of cultivated/farmland from 2007 to 2015 and a further 8 % in 2023. The northeast region (Upper and Lower Offin, Twifo Praso) faces deforestation and encroachment along riverbanks, along with built-up expansion due to mining activities. The northern region (Oda and Upper Pra) experiences exponential built-up and bare land increment. Accelerated phases of LULC change are attributed to factors such as mining (illegal and small-scale), agricultural production, migration, and population increment highlighting the influence of economic activities on land use dynamics. The concept gives a hybrid approach of using multi-tools in offering critical awareness of the state of the river system and encouraging the need for informed decision-making towards the anthropogenic impacts on the basin through effective management of LULC classes.

From Crops to Kilowatts: An Empirical Study on Farmland Conversion to Solar Photovoltaic Systems in Kushida River Basin, Japan

In Japan, rural areas are grappling with population decline and aging, leading to a shortage of labor for farmland maintenance. This has resulted in the abandonment of farmland or its conversion for solar photovoltaic (PV) use. However, this unplanned conversion raises concerns about agricultural productivity decline, landscape degradation, biodiversity loss, water resource maintenance, and disaster prevention. This study focuses on the Kushida watershed, examining (1) accurate farmland classification using remote sensing data, (2) the geographical distribution of farmland converted to PV systems from 2016 to 2021 and concentrated along the river, especially on north-facing slopes, (3) the highest conversion rates in wheat fields, followed by legume fields, tea fields, and paddy fields, and (4) no clear correlation between farmland conversions and changes in the number of farmers, but associations with farmland geography and solar radiation levels. These findings contribute to a nuanced understanding of sustainable rural development in Japan, emphasizing the importance of considering geographical factors in the conversion of farmland to PV.