Reveal the severe spatial and temporal patterns of abandoned cropland in China over the past 30 years

High-resolution mapping of China's flooded croplands

Climate change and the increasing frequency of floods have undermined China's food security. Creating detailed maps of flooded croplands is essential to improve prevention and adopt effective adaptation initiatives. Previous large-scale flood mapping efforts were hampered by limited meteorological and hydrological data, and the susceptibility of optical satellite images to cloud cover, leading to high uncertainty when downscaled to the cropland-scale. Here, using 4968 near-real-time (NRT) Sentinel-1 SAR (S1) images (spatial resolution: 10 m), we generated China's first set of high-resolution flooded cropland maps covering the period from 2017 to 2021. Our results demonstrate that croplands accounted for 43.8% to 49.8% of China's total flooded areas (ranging from 82,175 km2 to 122,037 km2). We also created high-resolution flood maps specifically for rice and maize crops. The inundated rice areas ranged from 8428 km2 to 22,123 km2, accounting for 22.34% to 41.91% of the annual flooded croplands, or 2.82% to 7.45% of the annual rice cropland. In comparison, the inundated maize cropland fluctuated from 2619 km2 to 5397 km2, representing 5.38% to 13.56% of the annual flooded croplands. Our findings revealed extensive floods in rural areas, highlighting the urgent need to prioritize flood prevention and mitigation efforts in such regions. In light of China's allocation of an additional 1-trillion-RMB treasury bonds for water infrastructure projects, the high-resolution flood maps can be used to select sites for flood control projects, and evaluate the impact of flooding on crop yields and food security, thus targeting poverty alleviation in rural areas of China.

Understanding the process and mechanism of agricultural land transition in China: Based on the interactive conversion of cropland and natural ecological land

The interaction conversion between cropland (CL) and natural ecological land (NEL) provides critical insights into the processes of agricultural land transition. However, current frameworks and methodologies for systematically detecting and analyzing this transition are still insufficient and require further refinement. The objective of the study is to develop a theoretical model of agricultural land transition and examines its evolutionary processes in China. The findings reveal that the interactive conversion between CL and NEL exhibits symmetry in both temporal trajectories and spatial patterns. The agricultural land transition can be divided into three stages at the national level, characterized by a shift in the dominant conversion pattern: from NEL-to-CL, to CL-to-NEL, and then back to NEL-to-CL. However, significant imbalances are observed in the transition processes across various provinces. Over time, the four pathways of agricultural land transition-NEL-dominated to NEL-dominated, CL-dominated to CL-dominated, NEL-dominated to CL-dominated, and CL-dominated to NEL-dominated-have yet to progress simultaneously. The dominance of a single pathway gradually became more prominent, with its proportion in different provinces increasing from 25% in the early period to 40% in the later period. Among the various factors influencing agricultural land transition, resource utilization, socio-economic factors, and policy implementation have a stronger impact than natural and climatic conditions. Furthermore, resource flows and planning interventions drive the initial agricultural land transition, while urbanization and population growth induce the second phase. Overall, this study enhances the theoretical understanding of agricultural land transition and offers decision-making guidance for rational and orderly agricultural land use conversion. Its ultimate aim is to provide valuable insights into the sustainable utilization and efficient management of agricultural land globally.

A 10-meter resolution dataset of abandoned and reclaimed cropland from 2016 to 2023 in Inner Mongolia, China

Amid growing global food security concerns and frequent armed conflicts, real-time monitoring of abandoned cropland is essential for strategic planning and crisis management. This study develops a method to map abandoned cropland accurately, crucial for maintaining the food supply chain and ecological balance. Utilizing Sentinel-1/2 satellite data, we employed multi-feature stacking and machine learning to create the ARCC10-IM (Abandoned and Reclaimed Cropland Classification at 10-meter resolution in Inner Mongolia) dataset, which tracks annual cropland activity. A novel temporal segmentation algorithm was developed to extract cropland abandonment and reclamation patterns annually, using sliding time windows over several years. This research differentiates cropland states-active cultivation, unstable fallowing, continuous abandonment, and reclamation-providing continuous, regional-scale maps with 10-meter resolution. ARCC10-IM is crucial for land planning, environmental monitoring, and agricultural management in arid areas like Inner Mongolia, enhancing decision-making and technology in land use tracking.

Revealing the distribution and change of abandoned cropland in Ukraine based on dual period change detection method

Since the outbreak of the Russia-Ukraine conflict in 2022, Ukraine has experienced different types of abandoned cropland, such as unused and unattended cropland, as a result of war damage, agricultural infrastructure destruction, and refugee outflows. Common methods for detecting abandoned cropland have difficulty effectively identifying and distinguishing these different types. This study proposes a Dual-period Change Detection method to reveal the spatial distribution and changes of different types of abandoned cropland in Ukraine, which can aid in agricultural assessments and international assistance in conflict-affected areas. The method mainly utilizes time-series NDVI data to fit the crop curves corresponding to cropland on a pixel-by-pixel basis, and then establishes discrimination rules for different types of abandoned cropland based on the crop curves, so as to detect unused cropland in the pre-conflict period (2015-2021) as well as unused cropland and unattended cropland in the post-conflict period (2022-2023). Finally, the detection results are validated and accuracy assessed using medium and high resolution spatiotemporal remote sensing imagery interpretation. The results show that the overall accuracy of the abandoned cropland extraction in Ukraine ranges from 83 to 96% during the study period. Before the conflict, the national average unused rate was 1.6%, with the lowest in 2021 and the highest in 2018. In 2022, the unused cropland area was approximately twice the average unused area before the conflict, and it was widely distributed, with the area of unattended cropland reaching 462,000 hectares, mainly in the eastern part of Ukraine. In 2023, compared to 2022, the unused cropland area decreased by 67.8%, while unattended cropland increased by 116.7%. Both types of abandoned cropland exhibited spatial clustering, with major clusters identified in the Crimea region, Kherson Oblast, Zaporizhzhia Oblast, and Donetsk Oblast.

The 30 m land cover dataset for capturing land cover changes induced by ecological restoration from 1990 to 2022 on the Chinese Loess Plateau

Continuous time-series of land cover is critical for attributing runoff, sediment and carbon changes on the Chinese Loess Plateau (CLP). However, current land cover products with annal temporal resolution lack spatial identification accuracy, particularly in capturing authentic changes of cropland, forest and grassland. To address these issues, a 30 m annual land cover dataset was proposed by the Yellow River Conservancy Commission (YRCC_LPLC) for the CLP from 1990 to 2022. Different levels of land cover were classified using different combinations of spectral, monthly and annual temporal and topographic features and Random Forest classifier. Compared to other land cover products (45.64%-73.38%), the accuracy of YRCC_LPLC has a better performance with an overall accuracy of 85.16%. The YRCC_LPLC is capable of capturing not only the explicit spatial variation but also the change direction and change time of land cover, especially for the most critical conversion of cropland into forest and grassland induced by implementation of Grain to Green Program on the CLP.

Evaluation of land ecological security and driving factors in the Lower Yellow River Flood Plain based on quality, structure and function

Land ecological security (LES) is crucial for human well-being and sustainable development, especially in areas like the Lower Yellow River Flood Plain (LYRFP), which faces flood threats, economic challenges, and ecological fragility. This study introduces a "Quality-Structure-Function" framework for evaluating LYRFP's LES, incorporating ecological baselines and the impacts of land use changes on human well-being for a comprehensive assessment. Using the Optimal Parameter Geographic Detector (OPGD) model, we analyzed agricultural, industrial, and socio-economic factors as potential LES drivers. The findings indicate a gradual improvement in LES over the past two decades, with spatial variations-higher in upstream and estuarine areas and lower in the middle. Significant enhancements post-2010 were observed in Shandong Province, unlike the modest gains in Henan. Spatial heterogeneity in LES was evident across floodplain segments, with Jitai Beach witnessing the most decline, Dongying Beach the most improvement, and Zhengkai Beach the largest internal disparities. Economic growth and reduced agricultural activities positively impacted LES, while population growth-related human activities contributed to its decline. This study suggested land use safety improvements in LYRFP by considering spatiotemporal and influencing factors for regional ecological protection and development.

Short-term warming supports mineral-associated carbon accrual in abandoned croplands

Effective soil organic carbon (SOC) management can mitigate the impact of climate warming. However, the response of different SOC fractions to warming in abandoned croplands remains unclear. Here, categorizing SOC into particulate and mineral-associated organic carbon (POC and MAOC) with physical fractionation, we investigate the responses of POC and MAOC content and temperature sensitivity (Q10) to warming through a 3-year in situ warming experiment (+1.6 °C) in abandoned croplands across 12 sites in China (latitude: 22.33-46.58°N). Our results indicate that POC content remains unchanged while MAOC content significantly increases under warming. POC and MAOC content changes are mainly influenced by root biomass and microbial necromass carbon changes, respectively. The Q10 of MAOC is significantly lower than that of POC regardless of the warming or control treatment, suggesting that MAOC represents the most persistent and least vulnerable carbon fraction within SOC. Collectively, the sequestration of stable soil carbon can be enhanced in abandoned croplands under short-term warming.

Desertification sensitivity and its impacts on land use change in the Tarim Basin, Northwest China

Desertification poses a major challenge in the northwestern arid areas of China. Land use activities are increasingly endangered by desertification, including direct impact (e.g., farmland abandonment) and indirect impact (e.g., farmland area control). However, previous studies have primarily focused on the impact of land use on desertification processes, while there has been limited research on the direct and indirect impacts of desertification on land use. Based on the Mediterranean Desertification and Land Use (MEDALUS) and Future Land Use Simulation (FLUS) models, we identify the spatiotemporal distribution of desertification sensitivity and analyze the direct and indirect impacts of desertification on land use in the Tarim Basin from 2000 to 2020. The results showed that the desertification sensitivity areas were primarily concentrated in the critical areas (proportion > 50 %), followed by the fragile and potential areas. In terms of the direct impact, the areas of abandoned farmland due to desertification were 68.25 km2 and 1444.25 km2 during the periods of 2000-2010 and 2010-2020, respectively. Additionally, 3893.25 km2 of farmland was at risk of abandonment. After being abandoned, the farmland was primarily converted into grassland. In terms of the indirect impact, the differences between predicted (simulations without farmland area control) and observed farmland area, serving as an indicator of farmland area control to reduce desertification risks, were 1065.75 km2 in 2010 and 4614.00 km2 in 2020. Our paper provides new insights into the direct and indirect impacts of desertification on land use, providing references for formulating desertification control policies and regional land use planning.

Reclamation of abandoned cropland switches fungal community assembly from deterministic to stochastic processes

Soil microbial communities are major drivers of cycling of soil nutrients that sustain plant growth and productivity. Yet, a holistic understanding of the impact of abandoned agricultural land reclamation on the soil microbe is still poorly understood, especially for the microbial community assembly mechanisms. Here, we investigated the influence of reclamation on the relative importance of stochastic and deterministic processes in shaping microbial community assembly. After reclaiming abandoned cropland for corn and soybean cultivation, the fungal community assembly was shifted to stochastic processes, while bacterial communities remained predominantly influenced by stochastic processes. Our study revealed that reclamation did not significantly affect bacterial diversity, community niche breadth, and community similarity. In contrast, fungal communities exhibited lower alpha diversity, narrower niche breadths, greater niche overlap and higher community similarity in corn and soybean cultivation treatment in response to reclamation. Moreover, soil pH and soil available phosphorus were the most important environmental factors influencing fungal richness, niche breadths, community assembly processes, and community similarity. Together, the reclamation of abandoned cropland promoted the transformation of the fungal community assembly from deterministic process to a stochastic process, leading to decreased fungal diversity and broader ecological niche width, ultimately resulting in greater similarity among fungal communities. This finding provides insight into the varied responses of microbial diversity and ecological process to abandoned cropland reclamation, offering valuable guidance for the conservation and sustainable management of abandoned cropland in future land-use practices.

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.

A 30-m annual grassland dataset from 1991 to 2020 for Inner Mongolia, China

Grassland is a widely distributed land use type that provides essential resources for livestock production and serves as a crucial ecosystem component. Over the past decades, grassland has significantly degraded and shrunk due to climate change and human activities, with ongoing changes in its area. This study utilized the Google Earth Engine (GEE) and the Res-UNet++ model to analyze the phenological and spectral characteristics of grasslands in Landsat images for long-term annual monitoring. Additionally, the LandTrendr algorithm was utilized to correct long-term time series data for grasslands, yielding a map of grassland distribution in Inner Mongolia from 1991 to 2020. The results indicate that the overall spatial accuracy from 1991 to 2020 exceeded 96%, with a Kappa coefficient over 0.92, demonstrating high monitoring accuracy. In particular, the 2019 grassland monitoring area showed high consistency with data from the Third National Land Survey (TNLS), with a coefficient of determination (R^2) reaching 0.97, reflecting the high accuracy and reliability.

Spatial-temporal characterization of cropland abandonment and its driving mechanisms in the Karst Plateau in Eastern Yunnan, China, 2001-2020

The karst plateau is dominated by mountainous and hilly landforms, with low mechanization level of cropland, high difficulty of cultivation, and obvious phenomenon of cropland abandonment, which threatens regional food security. This study aims to analyze the spatial-temporal variation and its driving mechanisms of abandoned cropland in the Karst Plateau in Eastern Yunnan, China (KPEYC) between 2001 and 2020. To achieve this goal, 18 key factors from population, economic environment, cropland attributes, and farming conditions are selected. Moreover, correlation analysis, geodetector, and regression analysis methods are applied from three perspectives: temporal change, spatial distribution and spatial-temporal change. The results show that: (i) The cropland abandonment rate (CAR) in the KPEYC shows a fluctuating trend, with an average value of 9.78%, and the spatial distribution shows a pattern of "high in the center and low in the south and north". (ii) From the perspective of temporal change, gross value of agricultural production, and gross value of industrial production have the largest correlation coefficients with CAR. (iii) The explanatory power of gross tertiary industrial production, gross value of industrial production, followed by soil thickness. (iv) Gross value of agricultural production, and gross tertiary industrial production are the core driving forces for the spatial-temporal change of CAR. The higher the gross value of agricultural production and gross tertiary industrial production, the lower the CAR. elevation, soil thickness, and traffic mileage are the main driving factors for the spatial-temporal change of CAR. The study indicates that economic factors are decisive for cropland abandonment in the KPEYC. Based on the results, this study can provide decision-making support for local prevention and control of cropland abandonment, and the local community needs to promote land transfer and concentration and local urbanization according to local conditions, improve agricultural policies, improve farming conditions, etc. in order to increase farmers' enthusiasm for production, promote the rational use of cropland, and solidly push forward ecological restoration and management, optimize ecological spatial patterns, manage serious areas of rocky desertification, and appropriately alleviate the contradiction between people and land.

Multi-objective ecological restoration priority in China: Cost-benefit optimization in different ecological performance regimes based on planetary boundaries

In the context of the "United Nations Decade on Ecosystem Restoration", optimizing spatiotemporal arrangements for ecological restoration is an important approach to enhancing overall socioecological benefits for sustainable development. However, against the background of ecological degradation caused by the human use of most natural resources at levels that have approached or exceeded the safe and sustainable boundaries of ecosystems, it is key to explain how to optimize ecological restoration by classified management and optimal total benefits. In response to these issues, we combined spatial heterogeneity and temporal dynamics at the national scale in China to construct five ecological performance regimes defined by indicators that use planetary boundaries and ecological pressures which served as the basis for prioritizing ecological restoration areas and implementing zoning control. By integrating habitat conservation, biodiversity, water supply, and restoration cost constraints, seven ecological restoration scenarios were simulated to optimize the spatial layout of ecological restoration projects (ERPs). The results indicated that the provinces with unsustainable freshwater use, climate change, and land use accounted for more than 25%, 66.7%, and 25%, respectively, of the total area. Only 30% of the provinces experienced a decrease in environmental pressure. Based on the ecological performance regimes, ERP sites spanning the past 20 years were identified, and more than 50% of the priority areas were clustered in regime areas with increased ecological stress. As the restoration area targets doubled (40%) from the baseline (20%), a multi-objective scenario presents a trade-off between expanded ERPs in areas with highly beneficial effects and minimal restoration costs. In conclusion, a reasonable classification and management regime is the basis for targeted restoration. Coordinating multiple objectives and costs in ecological restoration is the key to maximizing socio-ecological benefits. Our study offered new perspectives on systematic and sustainable planning for ecological restoration.

Identifying and monitoring of abandoned farmland in key agricultural production areas on the Qinghai‒Tibet Plateau: A case study of the Huangshui Basin

Curbing the continuous abandonment of large areas of farmland is important for meeting the global food demand and promoting agricultural and rural development. Accurate identification is the key to the effective management and utilization of abandoned farmland. The identification of abandoned land based on a long time series of remote sensing data has become rapid and effective. Therefore, a set of training and test datasets generated from invariant samples and reference sample sets is established in this paper. On this basis, the Google Earth Engine (GEE) is used to classify Landsat and Sentinel high-precision long-term remote sensing images from 2000 to 2022. In addition, a change detector based on the sliding window algorithm is proposed to extract abandoned farmland in the Huangshui Basin from 2002 to 2020, and the intensity, trend, frequency, reclamation rate and utilization efficiency are analyzed. The results revealed that the OA of land use classification in the Huangshui Basin from 2000 to 2022 was between 0.852 and 0.91, and the kappa coefficient was between 0.822 and 0.89, indicating a good classification effect. From 2002 to 2020, the accumulated abandoned farmland area in the Huangshui Basin continued to increase, showing a fluctuating upward trend, and the phenomenon of farmland abandonment and reclamation occurs repeatedly in some areas. From the overall distribution, the abandoned area gradually increased from the central region to the southeast. With the passage of time, the amount of abandoned farmland in the valley increased gradually, and the abandoned area was transferred from the high mountains to the valley area. The average annual abandonment rate of supplementary farmland was 50.45%, which was much greater than that of basic farmland. Most of the supplementary farmland could not be effectively and judiciously used, and the utilization efficiency was low. The research results provide data support for the reuse of abandoned farmland in ecologically fragile plateau areas, the formulation of targeted strategies, the implementation of timely adjustments, and the establishment of new ideas and methods for the accurate identification of abandoned farmland.

Evaluation of the efficiency and drivers of complemented cropland in Southwest China over the past 30 years from the perspective of cropland abandonment

Complemented croplands are a crucial component of cropland resources and play a significant role in ensuring national food security. In recent decades, to counter the loss of prime farmland caused by urban construction, the Chinese government introduced a requisition-compensation balance policy, leading to the substantial expansion of new croplands. Therefore, there is an urgent need to determine whether these complemented croplands can be effectively used. Taking Southwest China as a case study, we used high-precision long-term land-use data from 1990 to 2020 to reveal the dynamics of complemented cropland utilization, evaluate the efficiency of complemented cropland utilization from the perspective of abandoned farmland, and identify the factors driving complemented cropland use efficiency based on more than 13 million land parcels. The results showed that: (1) From 1990 to 2020, complemented cropland amounted to approximately 1170.07 × 104 hm2, accounting for 32.67% of the total arable land area in 1990. The potential grain production capacity of these complemented croplands was significantly lower than that of base croplands. (2) The abandonment of complemented croplands was more serious than that of base croplands, and 47.03% of the complemented croplands experienced abandonment at least once during the study period, and the average efficiency of the complemented croplands was 75.61%. (3) The labor population ratio, elevation, and land parcel size played pivotal roles in influencing the complemented cropland utilization efficiency; however, there was substantial variation among the different provinces. Labor replacement, overcoming farming difficulties brought by mountainous terrain, and improving farmers' income are the keys to alleviating cropland abandonment in mountainous areas and improving cropland utilization efficiency. This study provides novel insights into the efficiency assessment and exploration of the mechanisms driving complemented croplands and can provide references for cropland management.

Short-term evaluation of soil physical, chemical and biochemical properties in an abandoned cropland treated with different soil organic amendments under semiarid conditions

This study evaluate the effects of four organic soil amendments on soil. Physical, chemical and biochemical properties were compared to untreated and natural (not cultivated) soils in a semiarid region (Andalusia, Spain). A large set of physical, chemical biochemical properties and, the composition of bacterial communities; and overall soil quality index (SQI) were evaluated on soils treated with organic soil amendments of animal origin (compost from sheep and cow manure [CS] or chicken manure, [CK], vegetal origin (greenhouse crop residues [CC]), and vermicompost (CV). Immediately after application, the animal origin compost significantly increased pH, electrical conductivity (EC), and total nitrogen (TN) as well as the enzymatic activities associated with the carbon (C) cycle but decreased the richness and evenness of bacterial communities. After 3 months of treatment, all measured properties recovered except for EC, TN and dehydrogenase activity (whose increase was stable over time), as did bacterial richness, which remained lower. The vegetal-originating compost increased EC and pH whereas the other effects were not significant throughout the monitoring period. CV application did not affect soil properties. The SQI was the highest for soils treated with CK compost, both immediately after application and over time. The soil treatments with the other organic amendments did not result in a significantly different SQI over time compared to both untreated and natural sites.

One-third of cropland within protected areas could be retired in China for inferior sustainability and effects

Cropland encroachment on protected areas causes natural habitat loss, which may damage ecosystem functions and biodiversity conservation, leading to trade-offs between crop production and habitat conservation. Here we investigate the sustainable utilization and effects of cropland within protected areas, on which we make trade-offs with an established framework. Analyses show that 3.08 million hectares of cropland are identified within protected areas, about two-thirds less sustainable or less beneficial. 41 % and 26 % are expected to be retired for inferior sustainability and effects under the strictest and laxest habitat protection scenario, respectively. Although these retirements would cause a loss of crop benefits of 0.3-0.7 billion US dollars, they could bring ecological benefits of 2.9-3.6 billion US dollars annually. Approximately 11 % of cropland within protected areas is identified in poor agricultural conditions, and 19 % occupies areas of high protection importance, both of which are recommended for priority retirement. This study reveals the characteristics and impacts of cropland in protected areas and provides a quantified trade-off approach for conflicts between cropland and natural habitats, with important implications for production, conservation, and their trade-offs.

Understanding the indirect impacts of urbanization on vegetation growth using the Continuum of Urbanity framework

Numerous studies investigated the direct impacts of urbanization on the loss and fragmentation of vegetated lands associated with urban expansion. Fewer studies, however, have examined the indirect impacts of urbanization on vegetation related to changes in livelihoods, lifestyles, and connectivity in non-urbanized areas, especially in the context of large-scale urban-rural migration. Here, we employ the Continuum of Urbanity framework to examine how changes in livelihoods, lifestyles, and connectivity in non-urbanized areas associated with urbanization affect vegetation, and thereby to understanding the indirect impacts of urbanization. We found there was a significant trend in human-induced EVI (HEVI) increase in non-urban areas, and such trend was coupled with decreased population density (PD) in forest land and grassland, but increased population density in cropland. The negative correlation between PD and HEVI became increasingly stronger from 2000 to 2011, but weakened since 2011. Livelihood income, lifestyles represented by consumption, and information connectivity to the outside world indirectly impacted HEVI by driving PD changes in non-urban areas. This indirect effect has shifted from positive to negative over the 20 years. These findings suggest that the indirect impacts of urbanization on vegetation growth are complicated and multifaceted, and understanding such impacts would be critically important to help turn urbanization into an opportunity for regional sustainable development.

Discovery of Chiral Diamine Derivatives Containing 1,2-Diphenylethylenediamine as Novel Antiviral and Fungicidal Agents

Severe plant virus diseases lead to poor harvests and poor crop quality, and the lack of effective suppressive drugs makes plant disease control a huge challenge. Natural product-based structural simplification is an important strategy for finding novel pesticide candidates. According to our previous research on the antiviral activities of harmine and tetrahydroharmine derivatives, a series of chiral diamine compounds were designed and synthesized by means of structural simplification using diamines in natural products as the core structure in this work, and the antiviral and fungicidal activities were investigated. Most of these compounds displayed higher antiviral activities than those of ribavirin. Compounds 1a and 4g displayed higher antiviral activities than ningnanmycin at 500 μg/mL. The antiviral mechanism research revealed that compounds 1a and 4g could inhibit virus assembly by binding to tobacco mosaic virus (TMV) CP and interfere with the assembly process of TMV CP and RNA via transmission electron microscopy and molecular docking. Further fungicidal activity tests showed that these compounds displayed broad-spectrum fungicidal activities. Compounds 3a, 3i, 5c, and 5d with excellent fungicidal activities against Fusarium oxysporum f.sp. cucumerinum can be considered as new fungicidal candidates for further research. The current work provides a reference to the development of agricultural active ingredients in crop protection.