Search Results (1,470)

The accuracy assessment of cropland products is a critical prerequisite for agricultural planning and food security evaluations. Current accuracy assessments of remote sensing-based cropland products focused on the consistency of spatial patterns for specific years, yet the reliability of these cropland products in time-series analysis remains unclear. Using cropland area data from the second and third national land surveys of China (referred to as NLSCD) as a benchmark, we evaluate the area-based and spatial-based consistency of cropland changes in five 30 m time-series land cover products covering 2010 and 2020, including the annual cropland dataset of China (CACD), the annual China Land Cover Dataset (CLCD), China’s Land-use/cover dataset (CLUD), the Global Land-Cover product with Fine Classification System (GLC_FCS30), and GlobeLand30. We also employed the GeoDetector model to explore the relationships between the consistency in cropland change and the environmental factors (e.g., cropland fragmentation, topographic features, frequency of cloud cover, and management practices). The area-based consistency analysis showed that all five cropland products indicate a declining trend in cropland areas in China over the past decade, while the amount of cropland loss ranges from 5.59% to 57.85% of that reported by the NLSCD. At the prefecture-level city scale, the correlation coefficients between the cropland area changes detected by five cropland products and the NLSCD are low, with GlobeLand30 having the highest coefficient at 0.67. The proportion of prefecture-level cities where the change direction of cropland area in each cropland product is inconsistent with the NLSCD ranges from 13.27% to 39.23%, with CLCD showing the highest proportion and CLUD the lowest. At the pixel scale, the spatial-based consistency analysis reveals that 79.51% of cropland expansion pixels and 77.79% of cropland loss pixels are completely inconsistent across five cropland products, with the southern part of China exhibiting greater inconsistency compared to Northwest China. Besides, the frequency of cloud cover and management practices (e.g., irrigation) are the primary environmental factors influencing consistency in cropland expansion and loss, respectively. These results suggest low consistency in cropland change across five cropland products, emphasizing the need to address these inconsistencies when generating time-series cropland datasets via remote sensing. Full article

The carambola fruit fly, Bactrocera carambolae Drew & Hancock, is native to Southeast Asia, infests about 150 plant species, and is considered a quarantine pest insect in several regions of the world. Bactrocera carambolae has invaded Suriname, French Guyana, and northern Brazil. In Brazil, it was first recorded in 1996 and has been restricted to the states of Amapá and Roraima due to official control efforts of the Ministry of Agriculture and Food Supply (Ministério da Agricultura e Pecuária—MAPA). This is the first study to estimate the genetic structure and diversity of South American populations of B. carambolae. A total of 116 individuals from 11 localities in Brazil and 7 localities in Suriname were analyzed. Additional sequences available at GenBank from Indonesia (Lampung) and Thailand (San Pa Tong and Muang District) were also used in the analysis. We sequenced a fragment of the mitochondrial gene cytochrome oxidase subunit I. A total of 35 haplotypes were found. Haplotypes from Indonesia were closest to the haplotypes from South America, separated only by a few mutational steps. This suggests that Indonesia is the likely source for the introduction of B. carambolae into South America. The Southeast Asian populations appeared as the most ancestral group in the phylogenetic trees. The high similarity and sharing of several haplotypes among populations within South America indicate a lack of genetic structure. The mismatch distribution and neutrality tests suggest that South American populations have undergone a rapid growth and expansion following a single founder event. The low genetic diversity and the population expansion evidenced by the neutrality tests lend support to the hypothesis of a recent introduction of a single lineage of the carambola fruit fly into South America. Full article

The semi-arid Caatinga biome is particularly susceptible to fire dynamics. Periodic droughts amplify fire risks, while anthropogenic activities such as agriculture, pasture expansion, and land-clearing significantly contribute to the prevalence of fires. This research aims to evaluate the effectiveness of a fire detection model and analyze the spatial and temporal patterns of burned areas, providing essential insights for fire management and prevention strategies. Utilizing deep neural network (DNN) models, we mapped burned areas across the Caatinga biome from 1985 to 2023, based on Landsat-derived annual quality mosaics and minimum NBR values. Over the 38-year period, the model classified 10.9 Mha (12.7% of the Caatinga) as burned, with an average annual burned area of approximately 0.5 Mha (0.56%). The peak burned area reached 0.89 Mha in 2021. Fire scars varied significantly, ranging from 0.18 Mha in 1985 to substantial fluctuations in subsequent years. The most affected vegetation type was savanna, with 9.8 Mha burned, while forests experienced only 0.28 Mha of burning. October emerged as the month with the highest fire activity, accounting for 7266 hectares. These findings underscore the complex interplay of climatic and anthropogenic factors, highlighting the urgent need for effective fire management strategies. Full article

Research investigates the transformations in production–living–ecological spaces (PLES) across diverse scenarios and their ecological effects, with the aim of offering advice for environmental preservation and long-term growth in Sichuan Province. Utilizing the PLUS model, we simulated the PLES configuration in Sichuan Province for the year 2030 and subsequently evaluated its ecological impacts using an ecological effect assessment model. The findings reveal that: (1) population and GDP are key drivers of the expansion of Industrial-Production Spaces (IMPS), Urban-Living Spaces (ULS), and Rural-Living Spaces (RLS), whereas altitude has a crucial influence on shaping the expansion of Agricultural-Production Spaces (APS), Forest-Ecological Spaces (FES), Grassland-Ecological Spaces (GES), Water-Ecological Spaces (WES), and Other-Ecological Spaces (OES); (2) significant changes in PLES are observed in Sichuan Province by 2030 across four scenarios, with notable distinctions between the production priority scenario and the other three; (3) variations in ecological quality exist among the four scenarios concerning PLES; (4) the reasons behind better or worse ecological conditions differ across scenarios. The research demonstrates that the PLUS model can effectively simulate PLES in Sichuan Province under multiple scenarios for 2030, offering various potential development pathways and their corresponding ecological effects, thereby aiding in the selection of optimal development pathways. Full article

Evapotranspiration is a crucial component of the water cycle and is significantly influenced by climate change and human activities. Agricultural expansion, as a major aspect of human activity, together with climate change, profoundly affects regional ET variations. This study proposes a quantification framework to assess the impacts of climate change (ET_m) and agricultural development (ET_h) on regional ET variations based on the Random Forest algorithm. The framework was applied in a large-scale agricultural expansion area in China, specifically, the Songhua River Basin. Meteorological, topographic, and ET remote sensing data for the years of 1980 and 2015 were selected. The Random Forest model effectively simulates ET in the natural areas (i.e., forest, grassland, marshland, and saline-alkali land) in the Songhua River Basin, with R² values of around 0.99. The quantification results showed that climate change has altered ET by −8.9 to 24.9 mm and −3.4 to 29.7 mm, respectively, in the natural areas converted to irrigated and rainfed agricultural areas. Deducting the impact of climate change on the ET variation, the development of irrigated and rainfed agriculture resulted in increases of 2.9 mm to 55.9 mm and 0.9 mm to 53.4 mm in ET, respectively, compared to natural vegetation types. Finally, the Self-Organizing Map method was employed to explore the spatial heterogeneity of ET_h and ET_m. In the natural–agriculture areas, ET_m is primarily influenced by moisture conditions. When moisture levels are adequate, energy conditions become the predominant factor. ET_h is intricately linked not only to meteorological conditions but also to the types of original vegetation. This study provides theoretical support for quantifying the effects of climate change and farmland development on ET, and the findings have important implications for water resource management, productivity enhancement, and environmental protection as climate change and agricultural expansion persist. Full article

The reconstruction of land spatial planning and the increasing severity of carbon emissions pose significant challenges to carbon peak and carbon neutrality strategies. To establish low-carbon and sustainable agricultural spatial planning while achieving dual carbon strategy goals, it is essential to accurately analyze the mechanisms of agricultural spatial transfer and their carbon emission effects, as well as the key factors influencing carbon emissions from agricultural spatial transfer. Therefore, this study, based on land use remote sensing data from 2000 to 2020, proposes a carbon emission accounting system for agricultural space transfer. The carbon emission total from agricultural space transfer in the Harbin-Changchun urban agglomeration over the 20-year period is calculated using the carbon emission coefficient method. Additionally, the spatiotemporal patterns and influencing factors are analyzed using the standard deviation ellipse method and the geographical detector model. The results indicate that: (1) The agricultural space in the Harbin-Changchun urban agglomeration has increased, with a reduction in living space and an expansion of production space. Among land type conversions, the conversion between cultivated land and forest land has been the most intense. (2) The conversion of agricultural space to grassland and built-up land has been the primary source of net carbon emissions. The carbon emission center has shown a migration path characterized by “eastward movement and southward progression,” with a high-north to low-south distribution pattern. Significant carbon emission differences were observed at different spatial scales. (3) Natural environmental factors dominate the carbon emissions from agricultural space transfer, while socioeconomic and policy factors act as driving forces. Elevation is the primary factor influencing carbon emissions from agricultural space transfer. Interactions between factors generally exhibit nonlinear enhancement, with the interaction between elevation, annual precipitation, and industrial structure showing a strong explanatory power. Notably, the interactions between elevation, average annual precipitation, and industrial structure demonstrate significant explanatory power. These findings highlight the necessity for government action to balance agricultural spatial use with ecological protection and economic development, thereby providing scientific references for optimizing future land spatial structures and formulating regional carbon balance policies. Full article

Floods are one of the most devastating natural hazards that have intensified due to land use land cover (LULC) changes in recent years. Flood risk assessment is a crucial task for disaster management in flood-prone areas. In this study, we proposed a flood risk assessment framework that combines flood vulnerability, hazard, and damages under long-term LULC changes in the Tajan watershed, northern Iran. The research analyzed historical land use change trends and predicted changes up to 2040 by employing a Geographic Information System (GIS), remote sensing, and land change modeling. The flood vulnerability map was generated using the Random Forest model, incorporating historical data from 332 flooded locations and 12 geophysical and anthropogenic flood factors under LULC change scenarios. The potential flood damage costs in residential and agricultural areas, considering long-term LULC changes, were calculated using the HEC-RAS hydraulic model and a global damage function. The results revealed that unplanned urban growth, agricultural expansion, and deforestation near the river downstream amplify flood risk in 2040. High and very high flood vulnerability areas would increase by 43% in 2040 due to human activities and LULC changes. Estimated annual flood damage for agriculture and built-up areas was projected to surge from USD 162 million to USD 376 million and USD 91 million to USD 220 million, respectively, considering 2021 and 2040 land use change scenarios in the flood-prone region. This research highlights the importance of land use planning in mitigating flood-associated risks, both in the studied area and other flood-prone regions. Full article

Indiscriminate expansion of agricultural activities into wetlands affects the sustainability of wetland-dependent livelihoods. Systems research is an important tool for identifying and dealing with the underlying drivers of wetland degradation; however, there is limited research employing system tools in Sub-Saharan Africa. This research employed causal loop diagrams and system archetypes to characterize common wetland resource systems in Sub-Saharan Africa, using the wetland agricultural system of Uganda as a case study. Mental models of wetland users were indirectly elicited by interviewing 66 wetland users. Causal loop diagrams were generated to illustrate the multiple, interdependent feedback linkages within the system. The case study wetland is mainly used for farming (40%), vegetation harvesting (26%), and fishing (24%), while other activities like hunting and grazing are carried out by 10% of wetland users. A reinforcing feedback loop was dominant, illustrating how initial encroachment on the wetland to meet livelihood needs can accelerate further encroachment. Based on the dominant loop and current interventions, we characterized the system using three archetypes: tragedy of the commons, shifting the burden, and fixes that fail. A two-pronged approach was proposed, where solutions for decelerating wetland degradation, like restoration activities, can be implemented in the short term while planning long-term measures that take into account the need for alternative livelihoods for wetland-dependent communities and targeting a paradigm shift through continuous sensitization of stakeholders on the benefits of sustainable wetland management. Full article

The growing integration of Internet of Things (IoT) devices into various sectors like healthcare, transportation, and agriculture has dramatically increased their presence in everyday life. However, this rapid expansion has exposed new vulnerabilities within computer networks, creating security challenges. These IoT devices, often limited by their hardware constraints, lack advanced security features, making them easy targets for attackers and compromising overall network integrity. To counteract these security issues, Behavioral-based Intrusion Detection Systems (IDS) have been proposed as a potential solution for safeguarding IoT networks. While Behavioral-based IDS have demonstrated their ability to detect threats effectively, they encounter practical challenges due to their reliance on pre-labeled data and the heavy computational power they require, limiting their practical deployment. This research introduces the IoT-FIDS (Flow-based Intrusion Detection System for IoT), a lightweight and efficient anomaly detection framework tailored for IoT environments. Instead of employing traditional machine learning techniques, the IoT-FIDS focuses on identifying unusual behaviors by examining flow-based representations that capture standard device communication patterns, services used, and packet header details. By analyzing only benign traffic, this network-based IDS offers a streamlined and practical approach to securing IoT networks. Our experimental results reveal that the IoT-FIDS can accurately detect most abnormal traffic patterns with minimal false positives, making it a feasible security solution for real-world IoT implementations. Full article

With the increasing expansion and deepening of GIS applications across diverse industries, the limitations of industry-specific GIS application systems in terms of development efficiency, flexibility, and customization have become increasingly apparent. This paper employes the concept of application suites and proposes a design approach for tailored GIS application suites in digital agriculture, considering its specific application requirements. Additionally, it outlines an implementation method based on low-code development and microservice technologies. A GIS application system for digital agriculture was developed to conduct experimental validation. The results indicate that the GIS application suite developed in this study demonstrates readily deployable characteristics, granular assembly capabilities, and ease of scalability, facilitating the rapid development of customized GIS applications for digital agriculture. This approach enhances both development efficiency and flexibility while meeting the customization needs inherent to such applications. Full article

Background: Zingiber Mill., a morphologically diverse herbaceous perennial genus of Zingiberaceae, is distributed mainly in tropical to warm-temperate Asia. In China, species of Zingiber have crucial medicinal, edible, and horticultural values; however, their phylogenetic relationships remain unclear. Methods: To address this issue, the complete plastomes of the 29 Zingiber accessions were assembled and characterized. Comparative plastome analysis and phylogenetic analysis were conducted to develop genomic resources and elucidate the intraspecific phylogeny of Zingiber. Results: The newly reported plastomes ranged from 161,495 to 163,880 bp in length with highly conserved structure. Results of comparative analysis suggested that IR expansions/contractions and changes of repeats were the main reasons that influenced the genome size of the Zingiber plastome. A large number of SSRs and six highly variable regions (rpl20, clpP, ycf1, petA-psbJ, rbcL-accD, and rpl32-trnL) have been identified, which could serve as potential DNA markers for future population genetics or phylogeographic studies on this genus. The well-resolved plastome phylogeny suggested that Zingiber could be divided into three clades, corresponding to sect. Pleuranthesis (sect. Zingiber + sect. Dymczewiczia) and sect. Cryptanthium. Conclusions: Overall, this study provided a robust phylogeny of Zingiber plants in China, and the newly reported plastome data and plastome-derived markers will be of great significance for the accurate identification, protection, and agricultural management of Zingiber resources in the future. Full article

The risk of soil salinization is prevalent in arid and semi-arid regions, posing a critical challenge to sustainable agriculture. This study addresses the need for accurate assessment of regional root-zone soil salt content (SSC) and understanding of underlying driving mechanisms, which are essential for developing effective salinization mitigation and water management strategies. A remote sensing inversion technique, initially proposed to estimate root-zone SSC in cotton fields, was adapted and validated more widely to non-cotton farmlands. Validation results (with a coefficient of determination R² > 0.53) were obtained using data from a three-year (2020–2022) regional survey conducted in the arid Manas River Basin (MRB), Xinjiang, China. Based on this adapted technique, we analyzed the spatiotemporal distributions of root-zone SSC across all farmlands in MRB from 2001 to 2022. Findings showed that root-zone SSC decreased significantly from 5.47 to 3.77 g kg⁻¹ over the past 20 years but experienced a slight increase of 0.15 g kg⁻¹ in recent five years (2017–2022), attributed to cultivated area expansion and reduced irrigation quotas due to local water shortages. The driving mechanisms behind root-zone SSC distributions were analyzed using an approach combined with two machine learning algorithms, eXtreme Gradient Boosting (XGBoost) and SHapley Additive exPlanation (SHAP), to identify influential factors and quantify their impacts. The approach demonstrated high predictive accuracy (R² = 0.96 ± 0.01, root mean squared error RMSE = 0.19 ± 0.03 g kg⁻¹, maximum absolute error MAE = 0.14 ± 0.02 g kg⁻¹) in evaluating SSC drivers. Factors such as initial SSC, crop type distribution, duration of film mulched drip irrigation implementation, normalized difference vegetation index (NDVI), irrigation amount, and actual evapotranspiration (ET_a), with mean ($\left|\mathrm{SHAP} \mathrm{value}\right|$) ≥ 0.02 g kg⁻¹, were found to be more closely correlated with root-zone SSC variations than other factors. Decreased irrigation amount appeared as the primary driver for recent increased root-zone SSC, especially in the mid- and down-stream sections of MRB. Recommendations for secondary soil salinization risk reduction include regulation of the planting structure (crop choice and extent of planting area) and maintenance of a sufficient irrigation amount. Full article

Nanocellulose has prompted extensive exploration of its applications in advanced functional materials, especially humidity-responsive materials. However, the sunflower pith (SP), a unique agricultural by-product with high cellulose and pectin content, is always ignored and wasted. This work applied sulfuric acid hydrolysis and sonication to sunflower pith to obtain nanocellulose and construct film materials with humidity-responsive properties. The SP nanoparticle (SP-NP) suspension could form a transparent film with stacked layers of laminated structure. Due to the tightly layered structure and expansion confinement effect, when humidity increases, the SP-NP film responds rapidly in just 0.5 s and completes a full flipping cycle in 4 s, demonstrating its excellent humidity-responsive capability. After removing hemicellulose and lignin, the SP cellulose nanocrystals (SPC-NC) could self-assemble into a chiral nematic structure in the film, displaying various structural colors based on different sonication times. The color of the SPC-NC film dynamically adjusted with changes in ambient humidity, exhibiting both functionality and aesthetics. This research provides a new perspective on the high-value utilization of sunflower pith while establishing a practical foundation for developing novel responsive cellulose-based materials. Full article

The loss of native forests in Argentina has been a concern, driven by factors such as agriculture expansion and urbanization. Therefore, understanding the conservation status of sampled populations and their adaptation to different plant communities is essential. This research focused on the heterogeneity analysis of the associated woody and semi-woody vegetation to Hexachlamys edulis (O. Berg) Kausel and D. Legrand, a species commonly known as “ubajay” in Entre Ríos, Argentina. The study aimed to record the species present in the populations, explore plant communities associated with H. edulis, identify other potentially useful agroforestry species, compare locations based on the similarity of accompanying species, and explain the conservation status of each population. Results revealed a total of 71 species belonging to 39 families. The Myrtaceae family was the most relevant, particularly in terms of native species representation. The analysis of biodiversity indicators, including richness, the Shannon index, and dominance revealed variations among the studied sites. The anthropic indicator highlighted the impact of human activity, with Concordia showing a higher ratio of native-to-exotic species. Cluster analysis and ordination techniques revealed groupings of censuses from the same localities, indicating differences in vegetation composition between sites. Significant differences in species composition were found among the sampled populations. Overall, the study can serve as baseline information for future research on the dynamics of vegetation in these areas and on the studied H. edulis species. Finally, these findings contribute to understanding how wild species like H. edulis adapt to different plant communities, which might be valuable for developing new agroecological approaches or identifying potential companion planting species in future agricultural systems. Full article

In recent decades, the integrity and security of the ecosystem in the Sanjiang Plain have faced severe challenges due to land reclamation. Understanding the impact of paddy field expansion on regional ecosystem services (ESs), as well as revealing the trade-offs and synergies (TOS) between these services to achieve optimal resource allocation, has become an urgent issue to address. This study employs the InVEST model to map the spatial and temporal dynamics of five key ESs, while the Optimal Parameter Geodetector (OPGD) identifies primary drivers of these changes. Correlation analysis and Geographically Weighted Regression (GWR) reveal intricate TOS among ESs at multiple scales. Additionally, the Partial Least Squares-Structural Equation Model (PLS-SEM) elucidates the direct impacts of paddy field expansion on ESs. The main findings include the following: (1) The paddy field area in the Sanjiang Plain increased from 5775 km² to 18,773.41 km² from 1990 to 2020, an increase of 12,998.41 km² in 40 years. And the area of other land use types has generally decreased. (2) Overall, ESs showed a recovery trend, with carbon storage (CS) and habitat quality (HQ) initially decreasing but later improving, and consistent increases were observed in soil conservation, water yield (WY), and food production (FP). Paddy fields, drylands, forests, and wetlands were the main ES providers, with soil type, topography, and NDVI emerging as the main influencing factors. (3) Distinct correlations among ESs, where CS shows synergies with HQ and SC, while trade-offs are noted between CS and both WY and FP. These TOS demonstrate significant spatial heterogeneity and scale effects across subregions. (4) Paddy field expansion enhances regional SC, WY, and FP, but negatively affects CS and HQ. These insights offer a scientific basis for harmonizing agricultural development with ecological conservation, enriching our understanding of ES interrelationships, and guiding sustainable ecosystem management and policymaking. Full article