Farmland abandonment and its determinants in the different ecological villages of the Koshi river basin, central Himalayas: Synergy of high-resolution remote sensing and social surveys

Investigating the Spatial Distribution and Influencing Factors of Non-Grain Production of Farmland in South China Based on MaxEnt Modeling and Multisource Earth Observation Data

Excessive non-grain production of farmland (NGPF) seriously affects food security and hinders progress toward Sustainable Development Goal 2 (Zero Hunger). Understanding the spatial distribution and influencing factors of NGPF is essential for food and agricultural management. However, previous studies on NGPF identification have mainly relied on high-cost methods (e.g., visual interpretation). Furthermore, common machine learning techniques have difficulty in accurately identifying NGPF based solely on spectral information, as NGPF is not merely a natural phenomenon. Accurately identifying the distribution of NGPF at a grid scale and elucidating its influencing factors have emerged as critical scientific challenges in current literature. Therefore, the aims of this study are to develop a grid-scale method that integrates multisource remote sensing data and spatial factors to enhance the precision of NGPF identification and provide a more comprehensive understanding of its influencing factors. To overcome these challenges, we combined multisource remote sensing images, natural/anthropogenic spatial factors, and the maximum entropy model to reveal the spatial distribution of NGPF and its influencing factors at the grid scale. This combination can reveal more detailed spatial information on NGPF and quantify the integrated influences of multiple spatial factors from a microscale perspective. In this case study of Foshan, China, the area under the receiver operating characteristic curve is 0.786, with results differing by only 1.74% from the statistical yearbook results, demonstrating the reliability of the method. Additionally, the total error of our NGPF identification result is lower than that of using only natural/anthropogenic information. Our method enhances the spatial resolution of NGPF identification and effectively detects small and fragmented farmlands. We identified elevation, farming radius, and population density as dominant factors affecting the spatial distribution of NGPF. These results offer targeted strategies to mitigate excessive NGPF. The advantage of our method lies in its independence from negative samples. This feature enhances its applicability to other cases, particularly in regions lacking high-resolution grain crop-related data.

Unraveling patterns, causes, and nature-based remediation strategy for non-grain production on farmland in hilly regions

The surge in non-grain production on farmland (NGPF) poses significant threats to food security and land sustainability, particularly in hilly regions. However, there remains a lack of clarity on how to effectively balance grain and non-grain production in relation to land remediation. Using Wannian County as a case study, we investigate the evolution of this by leveraging high-precision land surveys and satellite imagery. Through the application of bootstrapped partial linear regression models, we identify key influencers behind each type of NGPF. In proposing land remediation solutions, we integrate the results of NGPF and land quality evaluations to identify mismatches between non-grain production and land attributes (i.e., topography, geology, soil, and land use). Our findings reveal a substantial growth in NGPF, expanding from 3838.72 ha to 5659.64 ha (2010-2020), and predominantly occurring on farmland with favorable natural conditions and connected locations such as proximity to roads, town centers, and industrial plants. Surprisingly, the basic farmland protection policy shows limited effectiveness in curbing NGPF, except for garden operations. We identify 1674 NGPF patches suitable for conversion to grain production and provide land remediation suggestions tailored to low-quality farmland with specific natural barriers, thus complementing the demand for regional non-grain production. This study thereby innovatively proposes nature-based land remediation strategies to address the non-grain production dilemma by tailoring NGPF and land quality, offering valuable insights for sustainable farmland management in China and beyond.

Spatiotemporal patterns, sustainability, and primary drivers of NDVI-derived vegetation dynamics (2003-2022) in Nepal

Understanding the vegetation dynamics and their drivers in Nepal has significant scientific reference value for implementing sustainable ecological policies. This study provides a comprehensive analysis of the spatio-temporal variations in vegetation cover in Nepal from 2003 to 2022 using MODIS NDVI data and explores the effects of climatic factors and anthropogenic activities on vegetation. Mann-Kendall test was used to assess the significant trend in NDVI and was integrated with the Hurst exponent to predict future trends. The driving factors of NDVI dynamics were analyzed using Pearson's correlation, partial derivative, and residual analysis methods. The results indicate that over the last 20 years, Nepal has experienced an increasing trend in NDVI at 0.0013 year-1, with 80% of the surface area (vegetation cover) showing an increasing vegetation trend (~ 28% with a significant increase in vegetation). Temperature influenced vegetation dynamics in the higher elevation areas, while precipitation and human interventions influenced the lower elevation areas. The Hurst exponent analysis predicts an improvement in the vegetation cover (greening) for a larger area compared to vegetation degradation (browning). A significantly increased area of NDVI residuals indicates a positive anthropogenic influence on vegetation cover. Anthropogenic activities have a higher relative contribution to NDVI variation followed by temperature and then precipitation. The results of residual trend and Hurst analysis in different regions of Nepal help identify degraded areas, both in the present and future. This information can assist relevant authorities in implementing appropriate policies for a sustainable ecological environment.

Enhancing the resilience of food production systems for food and nutritional security under climate change in Nepal

Background

Climate change in Nepal has posed a considerable challenge to agricultural productivity and has threatened food and nutritional security at multiple levels. This study aims to assess the impacts of climate change on national food production and food and nutritional security as well as document issue-based prioritized adaptation options for a resilient food production system.

Methods

This study considers temperature, precipitation, and their anomalies as the key factors affecting food production in Nepal. Nationwide precipitation trends along with their association with the annual production of major cereal crops in Nepal were assessed using data from the last three decades (1990–2018). The annual productions of the major cereal crops were summed and normalized to calculate the production index scores in the districts. Scores were plotted and visualized into maps using the Geographical Information System. In three ecological regions, the distribution of flood and extreme rainfall events and cases of malnutrition from 2005 to 2018 were plotted. The effects of climate change and highest priority adaptation options at the district level were documented through a review of national policies and literature studies and qualitative research based on Focus Group Discussions (FGDs).

Results

Between 1990 and 2018, the overall average production of major cereal crops in Nepal was increased by around 2,245 MT annually. In the district level index analysis, the highest production score was found for Jhapa and Morang while the lowest production score was found for Humla. Cases of malnutrition in some districts coincided with flood and heavy rainfall events, indicating that climate change and extreme climatic events have a role to play in food production and security. Growing drought-tolerant crops, changes in crop cycle, riverbed farming practices, developing short-term strategies, such as contingency crop planning, changing planting dates, planting short duration varieties, schemes evacuation, and long-term strategies, such as encouraging out-migration of population to safer locations, resettlement programs with transformative livelihood options, and sustainable agricultural practices were found to be key prioritized adaptation measures for a resilient food production system.

Conclusion

In Nepal, climate change and the increasing frequency and magnitude of extreme climatic events adversely affect the food production system, which has become a serious threat to food and nutritional security. The implementation of evidence-based practices to build a resilient food system specific to climate-vulnerable hotspots at the district and local levels is the nation's current need.

Agricultural Services: Another Way of Farmland Utilization and Its Effect on Agricultural Green Total Factor Productivity in China

Improving agricultural green total factor productivity (AGTFP) is an important aspect of sustainable agricultural development. Agricultural services, a new way of farmland utilization in agricultural production, solved the problem of ‘who and how to farm’ in the context of labor off-farm migration. The literature has analyzed different factors that affect AGTFP, but there is a relative dearth of research into agricultural services and AGTFP. Therefore, based on the panel data of 31 provinces from 2011 to 2020, this study firstly measured carbon emissions in agricultural production and then took it as an unexpected output to measure the AGTFP by using the global Malmquist–Luenberger (GML) productivity index. Finally, the effect of agricultural services on AGTFP and its decomposition were empirically verified. The main findings are as follows: (1) Between 2011 and 2020, agricultural carbon emissions increased from 85.63 million tons to 90.99 million tons in the first five years and decreased gradually to 78.64 million tons in 2020; the government policy significantly affects carbon emissions reduction. (2) AGTFP has been increasing for the past decade, and the average growth rate of AGTFP reached 1.016, and agricultural services promoted AGTFP growth significantly, in which technological progress was the crucial driving factor. (3) Taking the Heihe–Tengchong line as the demarcation, the improving effect of agricultural services on AGTFP in the eastern region is better than the western region.

Ecological Risk Assessment of Transboundary Region Based on Land-Cover Change: A Case Study of Gandaki River Basin, Himalayas

Land-cover change is a major cause of global ecosystem degradation, a severe threat to sustainable development and human welfare. In mountainous regions that cross national political boundaries, sensitive and fragile ecosystems are under complex disturbance pressures. Land-cover change may further exacerbate ecological risks in these regions. However, few studies have assessed the ecological risks in transboundary areas. This study focused on the Gandaki Basin (GRB), a typical transboundary region in the Himalayas. Based on the dynamic change in land cover, the landscape ecological risk index (ERI) model was constructed to assess the ecological risk in the GRB, revealing the evolution characteristics and spatial correlation of such a risk during the period 1990–2020. The results showed that all land cover types in the GRB have changed over the last 30 years. The interconversion of cropland and forestland was a distinctive feature in all periods. Overall, the medium and medium to low ecological risk level areas account for approximately 65% of the study area. The areas of high ecological risk were mainly distributed in the high elevation mountains of the northern Himalayas, while the low risk areas were located in the other mountains and hills of Nepal. In addition, the ecological risk in the Gandaki basin has shown a fluctuating trend of increasing over the past 30 years. However, there were different phases, with the order of ecological risk being 2020 > 2000 > 2010 > 1990. Ecological risks displayed positive spatial correlation and aggregation characteristics across periods. The high–high risk clusters were primarily located in the high and medium high ecological risk areas, while the low–low risk clusters were similar to low risk levels region. The findings provided the reference for ecosystem conservation and landscape management in transboundary areas.

Exploring the Role of Contiguous Farmland Cultivation and Adoption of No-Tillage Technology in Improving Transferees’ Income Structure: Evidence from China

Seasonal alternations of extreme weather such as continuous drought and rare rainstorms significantly influence farmers’ adoption of agricultural technologies. Compared with traditional tillage, no-tillage technology has more advantages to cope with extreme weather. It is hypothesized that the cultivation of contiguous farmland is still minimal in spite of the transference of farmland on a large scale in China, which ultimately halts the adoption of no-tillage technology and influences the income of households. The current study used 793 farmland transferees’ data from Shaanxi, Gansu, and Ningxia provinces of China to explore this phenomenon empirically. By employing the endogenous switching regression model, the study revealed that contiguous farmland significantly promotes the adoption of no-tillage technology and positively influences households’ agricultural and non-agricultural income. Meanwhile, the moderating effect of the stability of farmland rental contracts is explored. Further, it was also found that education level, organizational participation, relationship networks, and information acquisition channels influence the income of transferees who opt for no-tillage technology. The study further revealed that if a transferee who opts for no-tillage technology switches to traditional technology, their agricultural and non-agricultural income will decrease by 0.2893 and 1.6979 ten thousand yuan (RMB), respectively. In contrast, if a transferee who opts for traditional technology then switches to adopt no-tillage technology, their agricultural and non-agricultural income will increase by 0.1919 and 1.3044 ten thousand yuan (RMB), respectively. Conclusively, the current study’s empirical findings offer policymakers possible guidelines to devise strategies and encourage transferees to opt for no-tillage applications to increase their families’ income.

Degree of Abandoned Cropland and Socioeconomic Impact Factors in China: Multi-Level Analysis Model Based on the Farmer and District/County Levels

At present, abandoned cropland has become a common phenomenon spreading to countries around the world. China has seen widespread abandoned cropland in recent years. However, there are extremely few empirical studies of cropland abandonment and influencing factors nationwide. In this study, survey data from 8071 farmer households in 14 Chinese provinces were used to analyze the degree of cropland abandonment in China and its spatial distribution. A multi-level model was constructed to quantitatively explore the socioeconomic factors affecting the degree of cropland abandonment, at both the farmer and district/county levels. The results show that: (1) the proportion of farmers and the spatial distribution of abandoned cropland are consistent. (2) Chongqing City, Guangdong Province, and Shanxi Province are high-value areas of abandoned cropland, while Shandong, Liaoning, Henan and Jiangsu provinces are low-value areas. (3) Among the differences in cropland abandonment, 68.5% and 31.5% can be explained at the farmer and district/county level, respectively. (4) At the farmer level, all labor and cropland transfer indicators, including land labor quantity per unit area, male agricultural labor ratio, farmers mainly of middle-aged labor, cropland transfer area and cropland subcontract amount, have significant negative effects on the degree of abandoned cropland. There is a significant negative correlation between the value of agricultural operating fixed assets in the agricultural input indicators and the degree of abandoned cropland, but participation in professional, cooperative, economic, agricultural organizations has no significant impact on the degree of abandoned cropland. The per capita disposable income, which represents the quality of life indicator, has a significant positive impact on the degree of abandoned cropland. (5) At the district/county level, the proportion of the total co-working labor force and the transfer rate of cropland are negatively related to the degree of cropland abandonment, and the proportion of the co-working labor force outside the district/county is positively related to the degree of cropland abandonment. In addition, we briefly analyzed the mechanism and process of cropland abandonment from the perspective of farmers’ decision-making. Finally, the policy suggestions to alleviate the abandonment of cropland were put forward from the district/county and farmer level, respectively.

Cropland Abandonment and Influencing Factors in Chongqing, China

Cropland abandonment occurs frequently in many countries and regions around the world, particularly in those with poor environmental conditions, such as mountainous regions. In Chongqing county, China, over 76% of the total area is mountainous. Due to the lack of reliable remote sensing monitoring and identification methods, the spatial and temporal distribution of abandoned cropland areas and its underlying causes are poorly understood. Thus, the extent of cropland abandonment in Chongqing, since 2001, was estimated using land use trajectories. The following results were obtained: (1) the cropland abandonment rate was 12.2–15.4% from 2001 to 2020, with an average of 13.3%; (2) hotspots of abandoned cropland were concentrated in the north and southeast. Cropland abandonment was clustered in the northern, southeastern, and southwestern areas; (3) socio-economic factors (including gross domestic product density, population density, and road density) had a greater impact on the spatial distribution of abandoned cropland than environmental factors. Based on the results, the government should strive to reduce production costs associated with poor agricultural infrastructure, sporadic cropland, and higher labor costs by providing grain subsidies, undertaking cropland consolidation, encouraging land transfer, and improving agricultural infrastructure.

Climate Change and Its Impacts on Farmer's Livelihood in Different Physiographic Regions of the Trans-Boundary Koshi River Basin, Central Himalayas

The impact of climate change on farmers’ livelihoods has been observed in various forms at the local and regional scales. It is well known that the Himalayas region is affected by climate change, as reflected in the basic knowledge of farmers in the region. A questionnaire-based survey involving a total of 747 households was conducted to gather information on climate change and its impact, where the survey addressed four physiographic regions of the trans-boundary Koshi River Basin (KRB). Moreover, climatic data were used to calculate climatic trends between 1980 and 2018. The Mann–Kendall trend test was performed and the Sen’s slope calculated to analyze the inter-annual climatic trends over time. The survey noted that, for the basin, there was an increase in temperature, climate-induced diseases of crops, an increase in the frequency of pests as well as drought and floods and a decrease in rainfall, all which are strong indicators of climate change. It was perceived that these indicators had adverse impacts on crop production (89.4%), human health (82.5%), livestock (68.7%) and vegetation (52.1%). The observed climatic trends for all the physiographic regions included an increasing temperature trend and a decreasing rainfall trend. The rate of change varied according to each region, hence strongly supporting the farmers’ local knowledge of climate change. The highest increasing trend of temperature noted in the hill region at 0.0975 °C/a (p = 0.0002) and sharpest decreasing trend of rainfall in the mountain region by −10.424 mm/a (p = 0.016) between 1980 and 2018. Formulation of suitable adaptation strategies according to physiographic region can minimize the impact of climate change. New adaptation strategies proposed include the introduction of infrastructure for irrigation systems, the development of crop seeds that are more tolerant to drought, pests and disease tolerance, and the construction of local hospitals for the benefit of farming communities.

Agricultural Land Abandonment in the Hill Agro-ecological Region of Nepal: Analysis of Extent, Drivers and Impact of Change

Despite widely reported trends of agricultural land abandonment across many parts of the globe, this land use change phenomenon is relatively new in the context of Nepal. In recent years, rural farming communities in the hill region are gradually reducing the intensity of farming, leading to underutilisation and abandonment of agricultural lands. Adopting a mixed methods research approach, this study investigated the extent of agricultural land abandonment, its underlying causal drivers and perceived impacts in the hill agro-ecological region of Nepal. A structured survey of 374 households and six focus group discussions were carried out in three districts. The study revealed that around 40% of agricultural lands in the hill agro-ecological region have been abandoned and 60% of farmers have left at least one parcel of agricultural land abandoned. It was found that biophysical drivers (distance from homestead to parcel, slope of the parcel, land fragmentation, land quality and irrigation availability) and socio-demographic drivers (family size, higher education of the household members, domestic migration and out-migration) were responsible for agricultural land abandonment. Negative impacts of land abandonment were observed on the rural landscape, human-made farm structures, socio-economic systems, local food production and food security. In line with global studies, this research suggest that marginal land quality, demographic changes and rising alternative economic opportunities elsewhere contribute to farmland abandonment. This study also discusses land management approaches and policy implications to address the issue of agricultural land abandonment.

Qualifying Land Use and Land Cover Dynamics and Their Impacts on Ecosystem Service in Central Himalaya Transboundary Landscape Based on Google Earth Engine

Land use and land cover (LULC) changes are regarded as one of the key drivers of ecosystem services degradation, especially in mountain regions where they may provide various ecosystem services to local livelihoods and surrounding areas. Additionally, ecosystems and habitats extend across political boundaries, causing more difficulties for ecosystem conservation. LULC in the Kailash Sacred Landscape (KSL) has undergone obvious changes over the past four decades; however, the spatiotemporal changes of the LULC across the whole of the KSL are still unclear, as well as the effects of LULC changes on ecosystem service values (ESVs). Thus, in this study we analyzed LULC changes across the whole of the KSL between 2000 and 2015 using Google Earth Engine (GEE) and quantified their impacts on ESVs. The greatest loss in LULC was found in forest cover, which decreased from 5443.20 km2 in 2000 to 5003.37 km2 in 2015 and which mainly occurred in KSL-Nepal. Meanwhile, the largest growth was observed in grassland (increased by 548.46 km2), followed by cropland (increased by 346.90 km2), both of which mainly occurred in KSL-Nepal. Further analysis showed that the expansions of cropland were the major drivers of the forest cover change in the KSL. Furthermore, the conversion of cropland to shrub land indicated that farmland abandonment existed in the KSL during the study period. The observed forest degradation directly influenced the ESV changes in the KSL. The total ESVs in the KSL decreased from 36.53 × 108 USD y−1 in 2000 to 35.35 × 108 USD y−1 in 2015. Meanwhile, the ESVs of the forestry areas decreased by 1.34 × 108 USD y−1. This shows that the decrease of ESVs in forestry was the primary cause to the loss of total ESVs and also of the high elasticity. Our findings show that even small changes to the LULC, especially in forestry areas, are noteworthy as they could induce a strong ESV response.