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Using the US Geological Survey groundwater model, we compared spatial distribution, flow exchange, and storage of groundwater between cropland and forestland in the Upper Yazoo River Watershed, Mississippi, from 1900 to 2014. Under normal climate, average groundwater head declined 2.7 m in cropland but only 1 m in forestland over the 115 years. The average groundwater flow from forestland to cropland surpassed the reverse flow by a factor of 238, owing to a higher elevation in forestland and intensive groundwater pumping in cropland. Cropland was a net groundwater sink while forestland was a net groundwater source under all climates. Our findings underscore the discernible impacts of climate changes on groundwater storage and suggest that afforestation in the region would be an alternative for saving groundwater resources and supplying more waters to croplands. This study offers valuable insights into groundwater supply planning not only in Mississippi but also in comparable situations worldwide. [ABSTRACT FROM AUTHOR]

Understanding the status of soil properties and revealing their spatiotemporal variation patterns in study areas are important for achieving precision agriculture and promoting the steady improvement of farmland quality. By combining field survey sampling with ArcGIS spatial interpolation, the change rate, correlation, and transfer matrix were applied to analyze the spatiotemporal variations in soil properties in Feixi County farmlands in 2010 and 2022. The average soil pH increased from 5.80 to 5.96, maintaining weak acidity. The analyzed levels remained moderate, and the average available phosphorus (AP) decreased by 5.31 mg·kg−1. The average organic matter (OM), total nitrogen (TN), and available potassium (AK) increased by 4.89 g·kg−1, 0.23 g·kg−1, and 16.41 mg·kg−1, respectively. Soil nutrient contents were higher in the coastal areas of Chaohu Lake. The coefficients of variation and the rate of change of OM, TN, and AK were similar, whereas the coefficient of variation of pH was relatively small. The coefficients of variation and the rate of change for AP were relatively high. Moderate-level soil properties significantly changed in the area, with direct conversion between low and high levels. The spatial and temporal characteristics of OM and TN were similar. In the absence of targeted agricultural technical guidance, the soil property grade is usually medium, the soil property grade will fluctuate up and down without direction, and there is a direct transition between low and high content. Taking Feixi County as a case study in East China, the research results clearly show the changes and trends of major nutrient elements, providing a research idea for cities in East Asia, which mainly engage in rice cultivation and in the development of agriculture and urbanization, and providing data support and references for the future soil nutrient zoning management of farmers' precise fertilization, production, and planting for sustainable development. [ABSTRACT FROM AUTHOR]

During the last two decades, smallholder farmers in north-western Ethiopia have expanded eucalyptus fields into large areas of croplands until they recently started to reverse that trend. This study assessed the extent, drivers, and impacts of cropland to eucalyptus plantation changes during the 2000–2023 period and the recent land use reversal eucalyptus to cropland. It also analyzed the effect of the shift on land productivity and food security by comparing maize yields obtained from eucalyptus-cleared fields with those from permanent croplands. The assessment was conducted in the north-western highlands of Ethiopia and employed remote sensing techniques, yield difference comparisons, focus group discussions, and key informant interviews. Landsat-and Sentinel 2A-based multi-temporal image analyses were used to identify and map the coverage of eucalyptus plantation since 2000. Maize yield per plot was collected from 125 systematically selected paired 2mX2m plots, and yield differences were compared. One of the paired plots represented eucalyptus-cereal field changes, while the second represented cropland-maize plots. The multi-temporal image analysis result showed that eucalyptus plantation coverage was increased from 1000 ha in 2000 to 249,260 ha in 2023. Approximately 98% of that expansion was made onto crop fields. Latter, a large portion of that area was reconverted to cropland, mainly maize field due to substantial falls of market demand for eucalyptus logs. The oscillating land use changes imply that smallholders' land use decisions are informed by intrinsic and extrinsic economic considerations, not by scientific-evidence-based landscape suitability and ecological analyses. Moreover, to check the effects of eucalyptus on subsequent productivity of croplands, we compared maize yield differences between cropland-maize and eucalyptus-maize field plots. The yield comparison result showed 35% average yield increment from eucalyptus-maize plots than yields from cropland-maize plots. This finding tends to defy the widely held perception that 'growing eucalyptus tree plants on farmlands negatively affects the subsequent productivity of those plots'. However, this finding was based on a 1-year cross-sectional data. Further cross-sectional studies are important to arrive at conclusive results on the impacts of eucalyptus trees on productivity of those plots when converted to croplands. [ABSTRACT FROM AUTHOR]

Animal‐mediated pollination is a key ecosystem service required to some extent by almost three‐quarters of the leading human food crops in global food production. Anthropogenic pressures such as habitat loss and land‐use intensification are causing shifts in ecological community composition, potentially resulting in declines in pollination services and impacting crop production. Previous research has often overlooked interspecific differences in pollination contribution, yet such differences mean that biodiversity declines will not necessarily negatively impact pollination. Here, we use a novel species‐level ecosystem service contribution matrix along with mixed‐effects models to explore how groups of terrestrial species who contribute differently to crop pollination respond globally to land‐use type, land‐use intensity, and availability of natural habitats in the surrounding landscape. We find that the species whose contribution to crop pollination is higher generally respond less negatively (and in some cases positively) to human disturbance of land, compared to species that contribute less or not at all to pollination. This result may be due to these high‐contribution species being less sensitive to anthropogenic land conversions, which has led humans to being more reliant on them for crop pollination. However, it also suggests that there is potential for crop pollination to be resilient in the face of anthropogenic land conversions. With such a high proportion of food crops requiring animal‐mediated pollination to some extent, understanding how anthropogenic landscapes impact ecological communities and the consequences for pollination is critical for ensuring food security. [ABSTRACT FROM AUTHOR]

In the face of global population growth and climate change, the protection and rational utilization of cropland are crucial for food security and ecological balance. However, the complex topography and unique ecological environment of the Qinghai-Tibet Plateau results in a lack of high-precision cropland monitoring data. Therefore, this paper constructs a high-quality cropland dataset for the YarlungZangbo-Lhasa-Nyangqv River region of the Qinghai-Tibet Plateau and proposes an MSC-ResUNet model for cropland extraction based on Landsat data. The dataset is annotated at the pixel level, comprising 61 Landsat 8 images in 2023. The MSC-ResUNet model innovatively combines multiscale features through residual connections and multiscale skip connections, effectively capturing features ranging from low-level spatial details to high-level semantic information and further enhances performance by incorporating depthwise separable convolutions as part of the feature fusion process. Experimental results indicate that MSC-ResUNet achieves superior accuracy compared to other models, with F1 scores of 0.826 and 0.856, and MCC values of 0.816 and 0.847, in regional robustness and temporal transferability tests, respectively. Performance analysis across different months and band combinations demonstrates that the model maintains high recognition accuracy during both growing and non-growing seasons, despite the study area's complex landforms and diverse crops. [ABSTRACT FROM AUTHOR]

Soil organic carbon (SOC) storage is a critical ecosystem service for reducing CO2 emissions. Terrestrial ecosystems, including the agriculture lands, hold the second largest carbon reserves after oceans, containing 2,344 Gt of carbon. Agroforestry plays an important role in sequestering (SOC) which is essential for mitigating CO2. Due to increased anthropogenic activities, global CO2 emissions continue to rise. In agroecological zones, SOC serves as a key reservoir for atmospheric CO2. This research evaluates sustainability comparison between two land types for carbon sequestration potential and soil fertility parameters in District Multan, Pakistan; mango-based agroforestry (MBA) and cropland (CL) respectively. Soil samples were collected randomly at a depth of 20 cm from the locations; under tree shade in mango-based agroforestry (MBAUS), outside the tree shade (MBA), and cropland (CL). These samples were tested for analysis for (SOC), organic matter (OM %), nitrogen percentage (N %), saturation percentage (SP %), bulk density (BD), and carbon-to-nitrogen (C: N) ratio between mean values of agroforestry and CL. Results indicated that the amount of SOC was higher in agroforestry (0.64) compared to CL (0.43). Similarly, OM% was 1.15 in agroforestry and 0.75% in CL. N% was 0.055 in agroforestry and 0.037 in CL, C: N ratio (12:1) in agroforestry versus (11:1) in CL. SP was greater in CL (36.1) than in agroforestry (34.1), similarly, BD was higher in CL (1.361 g/cm3) and (1.077 g/cm3) in agroforestry. The study employed a completely randomized design (CRD) with three treatments and four replications. ANOVA was used for data analysis. According to the results, the carbon sequestration potential and fertility index of agroforestry was quite double that of cropland. [ABSTRACT FROM AUTHOR]

Nigeria is the most populous country in Africa, and the essential foods for Nigerians are cereal crops, including maize, rice, sorghum, millet, and wheat. However, their productivity is significantly affected by population pressure, poor cropland utilization, and high fertilizer costs. Against this backdrop, this study examines the relationship between cereal production, cereal cropland area, fertilizer usage, and the rural population (farm labor). The study utilizes the novel dynamic autoregressive distributed lag simulation (DYARDLS) model and analyzes annual time series data for Nigeria from 1980 to 2021. The unit root test results suggest that the chosen variables are stationary. Furthermore, the bound test affirms that all variables are cointegrated, with a significance level of 1%. The results from the DYARDLS show that in the long run, a percentage change in rural population and cereal cropland area boosts cereal food production by 0.018% and 0.51%, respectively. Meanwhile, a 1% change in the food production index exacerbates cereal output by 0.25% in the long run and 1.06% in the short run. We also find that fertilizer consumption could improve cereal production in the short and long run, but the results are insignificant. In conclusion, we demonstrate that our study variables are the decisive determining factors of cereal productivity and cannot be disregarded in the mission to attain food security. [ABSTRACT FROM AUTHOR]

[Objective] The rich and coarse sediment areas of middle Yellow River basin is a typical ecologically fragile area in China. Accurately quantifying the spatiotemporal dynamic changes of cropland in this region is crucial for evaluating regional food security, ecological restoration benefits, soil erosion conditions, and the downstream tranquility of the Yellow River. Methods］ Based on five high-re solution (3() m) land use/cover dataset products (CNLUCC, CtLC_FCS30, CLCD, AGLC-2()()()-201 5, GlobeLand30), this study employed methods such as cropland dynamic degree, deviation coefficient, transfer matrix, and spatial consistency analysis to comparatively analyze the spatiotemporal characteristics of cropland in the rich and coarse sediment areas. A high-precision fused dataset with a 3() m resolution was formed and validated. Based on this fused product, an analysis of the quantity, distribution, and structural characteristics of cropland in rich and coarse sediment areas of middle Yellow River basin in 199()--2020 years was conducted. Results] There are significant differences in cropland characteristics among existing multi-source dataset products, with the fused products demonstrating higher accuracy compared to using any of the five existing products individually. Analysis based on the fused products reveals a trend of initially increasing followed by fluctuating decline in cropland area in 199()----2020, with the implementation of the Grain for Green project serving as a turning point. Tn 199()一2020, there has been a net decrease of 3 170.59 km2 in cropland area, representing a reduction of 17.63%. Furthermore, the proportion of cropland with slopes greater than 15° has been decreasing annually. The main types of dynamic transfer of cropland are into grassland, followed by artificial surfaces. The implementation of ecological projects such as the Grain for Green program, along with urbanization construction, is the primary cause of the decrease in cropland. Conclusion] Researchers are encouraged to comprehensively analyze the strengths and weaknesses of multi-source products based on their research objectives. Exploring effective methods for fusing and interpreting multi-source data, with a focus on target land classes, can lead to a more in-depth understanding of the land characteristics in a specific region and, consequently, more precise research conclusions. [ABSTRACT FROM AUTHOR]

Accurate cropland distribution data are essential for efficiently planning production layouts, optimizing farmland use, and improving crop planting efficiency and yield. Although reliable cropland data are crucial for supporting modern regional agricultural monitoring and management, cropland data extracted directly from existing global land use/cover products present uncertainties in local regions. This study evaluated the area consistency, spatial pattern overlap, and positional accuracy of cropland distribution data from six high-resolution land use/cover products from approximately 2020 in the alpine agricultural regions of the Hehuang Valley and middle basin of the Yarlung Zangbo River (YZR) and its tributaries (Lhasa and Nianchu Rivers) area on the Qinghai-Tibet Plateau. The results indicated that (1) in terms of area consistency analysis, European Space Agency (ESA) WorldCover cropland distribution data exhibited the best performance among the 10 m resolution products, while GlobeLand30 cropland distribution data performed the best among the 30 m resolution products, despite a significant overestimation of the cropland area. (2) In terms of spatial pattern overlap analysis, AI Earth 10-Meter Land Cover Classification Dataset (AIEC) cropland distribution data performed the best among the 10 m resolution products, followed closely by ESA WorldCover, while the China Land Cover Dataset (CLCD) performed the best for the Hehuang Valley and GlobeLand30 performed the best for the YZR area among the 30 m resolution products. (3) In terms of positional accuracy analysis, the ESA WorldCover cropland distribution data performed the best among the 10 m resolution products, while GlobeLand30 data performed the best among the 30 m resolution products. Considering the area consistency, spatial pattern overlap, and positional accuracy, GlobeLand30 and ESA WorldCover cropland distribution data performed best at 30 m and 10 m resolutions, respectively. These findings provide a valuable reference for selecting cropland products and can promote refined cropland mapping of the Hehuang Valley and YZR area. [ABSTRACT FROM AUTHOR]

Abstract Nutrient budgeting for cropland is a crucial tool for assessing nutrient mining or excess application. We estimated the nutrient budget of nitrogen (N), phosphorus (P), and potassium (K) in cropland for South Asia during the last five decades (from 1970 to 2018) using equation-based empirical methods. Nutrient budget for the last five decades shows a negative balance of N (3.94 million tons, Mt), P (23.87 Mt), and K (247.23 Mt). Inorganic fertilizer remained the major input source for N and P, and its decadal average share increased for N (from 27.9% to 72.8%) and P (from 72.1% to 94.5%) from 1970 to 2010s and the share of manure, deposition, and crop residue to N, P and K input decreased. Deposition remained a major source of K input and its share decreased from 64.0% to 35.5% during the period. The share of crop removal to the decadal output of N (58.6% to 53.4%) and P (49.0% to 23.1%) decreased, and K (72.5% to 76.0%) increased from 1970 to 2010s. The higher losses of fertilizer N, and accumulation of P and K fertilizers in soils, resulted in decreasing partial factor productivity of N (from 72.2% to 16.9%), P (from 217.0% to 42.2%), and K (from 480.3% to 113.8%) from 1970 to 2018. Nutrient budget helps in identifying the regional imbalance (mining/accumulation) of the major nutrients, it will provide valuable information on the present status of country-level nutrient use for reorientation of their nutrient/fertilizer use policies.

Abstract Nigeria is the most populous country in Africa, and the essential foods for Nigerians are cereal crops, including maize, rice, sorghum, millet, and wheat. However, their productivity is significantly affected by population pressure, poor cropland utilization, and high fertilizer costs. Against this backdrop, this study examines the relationship between cereal production, cereal cropland area, fertilizer usage, and the rural population (farm labor). The study utilizes the novel dynamic autoregressive distributed lag simulation (DYARDLS) model and analyzes annual time series data for Nigeria from 1980 to 2021. The unit root test results suggest that the chosen variables are stationary. Furthermore, the bound test affirms that all variables are cointegrated, with a significance level of 1%. The results from the DYARDLS show that in the long run, a percentage change in rural population and cereal cropland area boosts cereal food production by 0.018% and 0.51%, respectively. Meanwhile, a 1% change in the food production index exacerbates cereal output by 0.25% in the long run and 1.06% in the short run. We also find that fertilizer consumption could improve cereal production in the short and long run, but the results are insignificant. In conclusion, we demonstrate that our study variables are the decisive determining factors of cereal productivity and cannot be disregarded in the mission to attain food security.

Background: Soil salinization is one of the key factors restricting the production of cropland. Once rice is subjected to alkali stress at the bud burst stage, the yield will suffer irreparable serious loss. Compared with salt tolerance, studies on QTL mapping and candidate gene analysis of rice alkali tolerance are limited. Results: In this study, we used the F2:3 population derived from the alkali-tolerant cultivar LD21 and the alkali-sensitive cultivar WL138 to construct an alkali-tolerant DNA mixing pool, and the BSA (Bulked Segregation Analysis) method was used for re-sequencing. The main QTL qRSLB9 controlling the relative shoot length of rice under alkali stress was mapped by QTL-seq. The candidate interval was narrowed to 346.5 kb by regional linkage mapping, which containing 6 DEGs screened through transcriptome sequencing. The qRT-PCR and candidate gene sequencing showed that LOC_Os09g24260 was most likely to control relative shoot length (RSL) in rice as a major gene who encodes the WD domain, G-beta repeat domain-containing protein. Conclusions: Based on these results, LOC_Os09g24260 was the candidate gene of qRSLB9 conferring alkalinity tolerance to rice at the bud burst stage. Our study provides valuable genetic information and materials for breeding new rice varieties with alkalinity tolerance.How to cite: Wang J, Bian J, Liu L, et al. Screening and analysis of candidate genes conferring alkalinity tolerance in rice (Oryza sativa L.) at the bud burst stage based on QTL-seq and RNA-seq. Electron J Biotechnol 2024;71. https://doi.org/10.1016/j.ejbt.2024.07.002.

Faced with increasing global soil degradation, spatially explicit data on cropland soil organic matter (SOM) provides crucial data for soil carbon pool accounting, cropland quality assessment and the formulation of effective management policies. As a spatial information prediction technique, digital soil mapping (DSM) has been widely used to spatially map soil information at different scales. However, the accuracy of digital SOM maps for cropland is typically lower than for other land cover types due to the inherent difficulty in precisely quantifying human disturbance. To overcome this limitation, this study systematically assessed a framework of “information extraction-feature selection-model averaging” for improving model performance in mapping cropland SOM using 462 cropland soil samples collected in Guangzhou, China in 2021. The results showed that using the framework of dynamic information extraction, feature selection and model averaging could efficiently improve the accuracy of the final predictions (R2: 0.48 to 0.53) without having obviously negative impacts on uncertainty. Quantifying the dynamic information of the environment was an efficient way to generate covariates that are linearly and nonlinearly related to SOM, which improved the R2 of random forest from 0.44 to 0.48 and the R2 of extreme gradient boosting from 0.37 to 0.43. Forward recursive feature selection (FRFS) is recommended when there are relatively few environmental covariates (500). The Granger-Ramanathan model averaging approach could improve the prediction accuracy and average uncertainty. When the structures of initial prediction models are similar, increasing in the number of averaging models did not have significantly positive effects on the final predictions. Given the advantages of these selected strategies over information extraction, feature selection and model averaging have a great potential for high-accuracy soil mapping at any scales, so this approach can provide more reliable references for soil conservation policy-making.

Abstract To investigate the distribution characteristics of selenium (Se) in mountainous soil-crop systems and examine the threshold value of Se-rich soil, 275 soil samples and 153 associated crop samples (rice, maize, tea, nuts, konjac, mushrooms, buckwheat, and coffee) were collected in Ximeng County, a typical mountainous area in southwest China. The total Se, available Se, organic matter, pH, sampling point elevation, and crop Se content were analyzed to examine the distribution characteristics of soil Se and the ability of primary crops to enrich Se in Ximeng County. Random forest and multiple regression models were established to identify the factors influencing the available soil Se and the crop Se enrichment coefficient. Finally, the Se-rich soil threshold was examined based on the total Se, available Se, and Se content in primary crops (rice, maize, and tea). The results showed soil Se resource abundance in the study region, with high Se soil accounting for 64.72% of the entire area. The soil Se content displayed significant spatial autocorrelation. The average Se enrichment coefficient of the main cultivated crops included mushrooms > nuts > rice > coffee > tea > maize > buckwheat > konjac. The total Se content in the soil had the highest impact on the available Se content in the soil and the Se enrichment coefficient of crops. A Se-rich soil threshold of 0.3 mg·kg−1 was used for rice and maize, while that of tea was 0.4 mg·kg−1. This result provided a theoretical basis for developing and utilizing Se resources in mountainous soil in southwestern China and dividing the Se-rich soil threshold.

Abstract Despite fertilization efforts, phosphorus (P) availability in soils remains a major constraint to global plant productivity. Soil incorporation of biochar could promote soil P availability but its effects remain uncertain. To attain further improvements in soil P availability with biochar, we developed, characterized, and evaluated magnesium-oxide (MgO) and sepiolite (Mg4Si6O15(OH)2·6H2O)-functionalized biochars with optimized P retention/release capacity. Field-based application of these biochars for improving P availability and their mechanisms during three growth stages of maize was investigated. We further leveraged next-generation sequencing to unravel their impacts on the plant growth-stage shifts in soil functional genes regulating P availability. Results showed insignificant variation in P availability between single super phosphate fertilization (F) and its combination with raw biochar (BF). However, the occurrence of Mg-bound minerals on the optimized biochars’ surface adjusted its surface charges and properties and improved the retention and slow release of inorganic P. Compared to BF, available P (AP) was 26.5% and 19.1% higher during the 12-leaf stage and blister stage, respectively, under MgO-optimized biochar + F treatment (MgOBF), and 15.5% higher under sepiolite-biochar + F (SBF) during maize physiological maturity. Cumulatively, AP was 15.6% and 13.2% higher in MgOBF and SBF relative to BF. Hence, plant biomass, grain yield, and P uptake were highest in MgOBF and SBF, respectively at harvest. Optimized-biochar amendment stimulated microbial 16SrRNA gene diversity and suppressed the expression of P starvation response and P uptake and transport-related genes while stimulating P solubilization and mineralization genes. Thus, the optimized biochars promoted P availability via the combined processes of slow-release of retained phosphates, while inducing the microbial solubilization and mineralization of inorganic and organic P, respectively. Our study advances strategies for reducing cropland P limitation and reveals the potential of optimized biochars for improving P availability on the field scale. Graphical Abstract

Monitoring agricultural land over vast geographical areas presents challenges due to the absence of accurate, comprehensive and precise data, which has become a complex process that is difficult to do in terms of both timespans and consistency. Hence, this study presents an improved approach for the identification of agricultural land by utilizing the capabilities of Sentinel-1 and Sentinel-2 satellites with a variety of vegetation and non-vegetation indices and machine learning algorithms. The Multispectral Correlation Mapper (MCM) and Random Forest (RF) algorithms are adopted to train different agricultural lands, crop types and sowing and cultivation seasons. The 45-bands mega-file data cube (MFDC) fusion for each season incorporates essential indices and features derived from the Sentinel-1 and Sentinel-2 datasets for both seasons, i.e. Rabi (winter-spring season) and Kharif (summer-autumn season). The proposed method demonstrated resilience when applied to satellite datasets while effectively reducing the impact of non-agricultural elements such as shrubs, grass, bare soil and orchards. The results demonstrate a notable ability to differentiate between the Rabi and Kharif seasons, resulting in a high level of precision in measuring the extent of cultivated land during the Rabi and Kharif seasons with an area of 626,947 acres and 590,858 acres, respectively. The total land area, ascertained from the observation of the comprehensive cropping pattern and agricultural modifications during the entire year (June 2021–May 2022) is 635,655 acres. The validation exercise shows the higher accuracy of this method for cropland, with an overall accuracy of 98.8%, kappa of 0.97, user accuracy of 98.69% and producer accuracy of 99.13%. Additionally, it was spatially compared with the ESRI, ESA and MODIS cropland layers and government statistical data. Furthermore, the research investigates the temporal dynamics of agricultural growth phases using spectral bands and indices. This approach improves the accuracy of precise cropland identification and provides useful insights into crop phenology. [ABSTRACT FROM AUTHOR]

Since China's reform and opening up in 1978, the reclamation and abandonment of cropland in Xinjiang have become significant features of the land use change in the arid land of Northwest China. However, the spatiotemporal changes and driving mechanisms of cropland reclamation and abandonment over long time periods are still unclear, but this is crucial in understanding cropland changes in inland arid land, providing important insights for land management and agricultural development. Based on 40 years of remote sensing data on resources and the environment, this study examines the spatiotemporal characteristics of cropland reclamation and abandonment in Xinjiang over four periods since 1980. Additionally, it uses an optimal parameter geographical detector model to quantify the driving factors for each period. The results indicate that cropland reclamation experiences a "slow decrease–rapid increase" trend, forming a "V-shaped" pattern, while abandonment shows a "rapid decrease–slow decrease–slow increase" trend, forming a "U-shaped" pattern. These trends can be divided into three periods: 1980–1990 (unstable growth), 1990–2010 (stable growth), and 2010–2020 (growth with constraints). The movement pattern of cropland reclamation's center of gravity is "slightly southeast–slightly northeast–southwest", whereas the abandonment's center of gravity shifts "northeast–southwest–northeast". Further analysis reveals that the impact of agricultural technological investment and infrastructure on cropland reclamation has increased, while the influence of natural environmental factors has decreased. Although climate and water resources remain key factors in cropland abandonment, the influence of economic and social factors has gradually diminished, and the impact of agricultural mechanization has steadily risen. [ABSTRACT FROM AUTHOR]

Agricultural expansion is one of the main causes of deforestation of tropical montane forests in the central Andes of Peru. The hydrological impacts of converting forests to cropland are well known; however, an issue that is not entirely clear is related to the hydrological effects that can result from the conversion of montane forests to agroforestry systems and the recovery of the hydrological functions of montane forests after a disturbance. In this study, we compare the hydrological processes of different land covers previously modified by agricultural expansion, in order to determine the impact of the conversion of tropical montane forest to agricultural land on the ecosystem service of water provision and regulation. To achieve this, we establish study plots in four land cover types located in the central Andes of Peru (mature montane forest (BMC), natural regenerating secondary forest (BMR), coffee agroforestry systems (AF), and cropland (C)), for the purpose of measuring the vegetation structure and soil properties in them, and subsequently carry out a soil water balance in each plot to calculate the actual evapotranspiration, surface runoff, and groundwater recharge. The results revealed the following percentages (based on precipitation) for the hydrological components in the four land cover types: annual actual evapotranspiration—BMR (41.2%), AF (40.4%), BMC (40.0%), and C (38.0%); annual surface runoff—C (16.1%), BMC (8.3%), BMR (5.2%), and AF (4.6%); and annual groundwater recharge—AF (43.0%), BMR (41.6%), C (34.0%), and BMC (31.7%). Furthermore, the study also examined the relationship between vegetation structure and the hydrological components across the four land cover types. The findings indicated that the reduction of thicker and taller trees could increase surface runoff generation, whereas the presence of thinner and shorter trees could facilitate groundwater recharge. These results shed light on the complex interactions between land cover types, vegetation structure, and hydrological processes, emphasizing the importance of considering these factors in water resource management and land use planning. [ABSTRACT FROM AUTHOR]

Sediment connectivity indexes serve as a diagnostic tool for investigating the overall hydro-geomorphological functioning. The primary factors influencing sediment connectivity are rainfall and changes in land cover. For the period 1995–2016, we investigated changes in sediment connectivity in two ca.1000 km2 catchments located in the Ethiopian Highlands and evaluated the potential sediment sources of the catchment. These catchments are characterized by severe land degradation and high sediment yields. The sediment connectivity of the catchments was computed using SedIn-Connect, incorporating variables such as a digital elevation model, rainfall erosivity, soil erodibility, surface roughness, cover management, and surface runoff to formulate the weight factor. Rainfall variability was calculated using TAMSAT data, and land cover maps were derived using Landsat data in Google Earth Engine. The findings show substantial spatial variability in sediment connectivity across the two catchments. The modified index of connectivity value has a positive correlation with sediment yield from two stations whereby the sediment connectivity is higher in the Gumara Catchment than in the Rib Catchment. In both catchments, bare land, cropland, shrubland, and grassland exhibited higher connectivity, whereas forest and rural settlements displayed lower connectivity. Croplands registered the most pronounced increase in connectivity, mirroring similar trends observed in shrublands and grasslands. Conversely, forested areas demonstrated relatively stable connectivity patterns. Notably, croplands nestled in steep slopes and proximate to rivers emerged as potential sediment sources capable of influencing sediment connectivity within the two catchments. [ABSTRACT FROM AUTHOR]

Food security, a crucial issue for the development of humankind, is often severely constrained by water scarcity. As a globally recognized most advanced agricultural water-saving technology, drip irrigation under plastic mulch (DIPM) has played a significant role in grain production. However, a comprehensive review of the dual impacts of this practice in farmland remains lacking. This study has conducted an exhaustive review of DIPM research from 1999 to 2023 and employed CiteSpace software to perform a co-occurrence and clustering analysis of keywords in order to reveal research hotspots and trends. The results show that the attention to DIPM technology has increased annually and reached a peak in 2022. China leads in the number of publications in this field, reflecting its emphasis on agricultural water-saving technologies. This study critically discusses the dual impacts of DIPM on farmland. On the positive side, DIPM can improve soil temperature and moisture, enhance nutrient availability, promote water and nutrient absorption by roots, and increase the crop growth rate and yield while reducing evaporation and nitrogen loss, suppressing weed growth, decreasing herbicide usage, and lowering total greenhouse gas emissions. On the negative side, it will cause pollution from plastic mulch residues, damage the soil structure, have impacts on crop growth, and lead to increased clogging of drip irrigation systems, which will increase agricultural costs and energy consumption, hinder crop growth, hamper soil salinization management, and further reduce the groundwater level. The future development of DIPM technology requires optimization and advancement. Such strategies as mechanized residual-mulch recovery, biodegradable mulch substitution, aerated drip irrigation technology, and alternate irrigation are proposed to address existing issues in farmland triggered by DIPM. This review advocates for the active exploration of farming management practices superior to DIPM for future agricultural development. These practices could lead to higher yields, water–nitrogen efficiency, and lower environmental impact in agricultural development. [ABSTRACT FROM AUTHOR]

Converting natural vegetation for agriculture has resulted in the loss of approximately 5% of the current global terrestrial soil organic carbon (SOC) stock to the atmosphere. Increasing the agricultural area under grassland may reverse some of these losses, but the effectiveness of such a strategy is limited by how quickly SOC recovers after conversion from cropland. Using soil data and extensive land‐use histories gathered during the national German agricultural soil inventory, this study aims to answer three questions regarding agricultural land‐use change (LUC): (i) how do SOC stocks change with depth following LUC; (ii) how long does it take to reach SOC equilibrium after LUC; and (iii) what is the legacy effect of historic LUC on present day SOC dynamics? By using a novel approach that substitutes space for time and accounts for differences in site properties using propensity score balancing, we determined that sites that were converted from cropland to grassland reached a SOC equilibrium level 47.3% (95% confidence interval (CI): 43.4% to 49.5%) above permanent cropland levels 83 years (95% CI: 79 to 90 years) after conversion. Meanwhile, sites converted from grassland to cropland reached a SOC equilibrium level −33.6% (95% CI: −34.1% to −33.5%) below permanent grassland levels after 180 years (95% CI: 151 to 223 years). We estimate that, over the past century, today's German agricultural soils (16.6 million ha) have gained about 40 million Mg C. Furthermore, croplands with historic LUC from grassland are losing SOC by −0.26 Mg ha−1 year−1 (10% of agricultural land) while grasslands historically converted from cropland are gaining SOC by 0.27 Mg ha−1 year−1 (18% of agricultural land). This study shows that even long‐standing temperate agricultural sites likely have ongoing SOC change as a result of historical LUC. [ABSTRACT FROM AUTHOR]

Food security is a major challenge for China at present and will be in the future. Revealing the spatiotemporal changes in cropland and identifying their driving forces would be helpful for decision-making to maintain grain supply and sustainable development. Hainan Island is endowed with rich agricultural resources due to its unique climatic conditions and is facing tremendous pressure in cropland protection due to the huge variation in natural conditions and human activities over the past few decades. The purpose of this study is to assess the spatiotemporal changes in and driving forces of cropland on Hainan Island in the past and predict future cropland changes under different scenarios. Key findings are as follows: (1) From 2000 to 2020, the cropland area on Hainan Island decreased by 956.22 km2, causing the center of cropland to shift southwestward by 8.20 km. This reduction mainly transformed into construction land and woodland, particularly evident in coastal areas. (2) Among anthropogenic factors, the increase in the human footprint is the primary reason for the decrease in cropland. Land use changes driven by population growth, especially in economically active and densely populated coastal areas, are key factors in this decrease. Natural factors such as topography and climate change also significantly impact cropland changes. (3) Future scenarios show significant differences in cropland area changes. In the natural development scenario, the cropland area is expected to continue decreasing to 597 km2, while in the ecological protection scenario, cropland conversion is restricted to 269.11 km2; however, in the cropland protection scenario, the trend of cropland reduction is reversed, increasing by 448.75 km2. Our findings provide a deep understanding of the driving forces behind cropland changes and, through future scenario analysis, demonstrate the potential changes in cropland area under different policy choices. These insights are crucial for formulating sound land management and agricultural policies to protect cropland resources, maintain food security, and promote ecological balance. [ABSTRACT FROM AUTHOR]

Heavy metal composite pollution, such as Cd–Pb, occurs commonly in agriculture soils around the world, potentially harming the ecological environment and human health via food chain/network migration. There are numerous strategies for treating and rehabilitating polluted farmland today, including the use of attractive plants for phytoremediation. However, it is unclear how to use attractive plants to properly treat and fully utilize Cd–Pb composite damaged farms. The combined Cd–Pb pollution of agriculture in Xieping village, Huixian county, Gansu province is increasingly prevalent. Therefore, based on the results of literature research and the actual situation of the study area, nine kinds of ornamental plants with Cd–Pb composite pollution remediation potential and comprehensive utilization value were first selected in this paper, and the greenhouse test was carried out in the Cd–Pb composite pollution farmland in the study area. Second, the bioconcentration factor (BCF), transfer coefficient (TF), and economic feasibility principle were utilized to select the best treatment plants, and a novel model of effective remediation and comprehensive exploitation of Cd–Pb composite damaged farmland was developed. The results showed that the nine tested plants grew well under the Cd–Pb combined pollution stress, and all of them showed certain tolerance. However, the biomass, Cd–Pb accumulation, enrichment and transport capacity of the different plants were significantly different. Among them, Paeonia suffruticosa Andr., Rumex acetosa L., Calendula officinalis L., Rose chinensis Jacq., Tagetes erecta L. and Impatiens balsamina L. show excellent restorative abilities. Combining the ornamental value, safety and economy of flowering plants, P. suffruticosa, R. chinensis, C. officinalis, T. erecta and I. balsamina were finally selected as the plants for the effective remediation and comprehensive utilisation of Cd–Pb composite pollution in farmland. In conclusion, this study proposes a new model for the effective remediation and comprehensive utilisation of heavy metal composite pollution in farmland by flowering plants with economic feasibility. [ABSTRACT FROM AUTHOR]

Background: Integrating trees into agricultural landscapes can provide climate mitigation and improves soil fertility, biodiversity habitat, water quality, water flow, and human health, but these benefits must be achieved without reducing agriculture yields. Prior estimates of carbon dioxide (CO2) removal potential from increasing tree cover in agriculture assumed a moderate level of woody biomass can be integrated without reducing agricultural production. Instead, we used a Delphi expert elicitation to estimate maximum tree covers for 53 regional cropping and grazing system categories while safeguarding agricultural yields. Comparing these values to baselines and applying spatially explicit tree carbon accumulation rates, we develop global maps of the additional CO2 removal potential of Tree Cover in Agriculture. We present here the first global spatially explicit datasets calibrated to regional grazing and croplands, estimating opportunities to increase tree cover without reducing yields, therefore avoiding a major cost barrier to restoration: the opportunity cost of CO2 removal at the expense of agriculture yields. Results: The global estimated maximum technical CO2 removal potential is split between croplands (1.86 PgCO2 yr− 1) and grazing lands (1.45 PgCO2 yr− 1), with large variances. Tropical/subtropical biomes account for 54% of cropland (2.82 MgCO2 ha− 1 yr− 1, SD = 0.45) and 73% of grazing land potential (1.54 MgCO2 ha− 1 yr− 1, SD = 0.47). Potentials seem to be driven by two characteristics: the opportunity for increase in tree cover and bioclimatic factors affecting CO2 removal rates. Conclusions: We find that increasing tree cover in 2.6 billion hectares of agricultural landscapes may remove up to 3.3 billion tons of CO2 per year – more than the global annual emissions from cars. These Natural Climate Solutions could achieve the Bonn Challenge and add 793 million trees to agricultural landscapes. This is significant for global climate mitigation efforts because it represents a large, relatively inexpensive, additional CO2 removal opportunity that works within agricultural landscapes and has low economic and social barriers to rapid global scaling. There is an urgent need for policy and incentive systems to encourage the adoption of these practices. [ABSTRACT FROM AUTHOR]

To investigate the distribution characteristics of selenium (Se) in mountainous soil-crop systems and examine the threshold value of Se-rich soil, 275 soil samples and 153 associated crop samples (rice, maize, tea, nuts, konjac, mushrooms, buckwheat, and coffee) were collected in Ximeng County, a typical mountainous area in southwest China. The total Se, available Se, organic matter, pH, sampling point elevation, and crop Se content were analyzed to examine the distribution characteristics of soil Se and the ability of primary crops to enrich Se in Ximeng County. Random forest and multiple regression models were established to identify the factors influencing the available soil Se and the crop Se enrichment coefficient. Finally, the Se-rich soil threshold was examined based on the total Se, available Se, and Se content in primary crops (rice, maize, and tea). The results showed soil Se resource abundance in the study region, with high Se soil accounting for 64.72% of the entire area. The soil Se content displayed significant spatial autocorrelation. The average Se enrichment coefficient of the main cultivated crops included mushrooms > nuts > rice > coffee > tea > maize > buckwheat > konjac. The total Se content in the soil had the highest impact on the available Se content in the soil and the Se enrichment coefficient of crops. A Se-rich soil threshold of 0.3 mg·kg−1 was used for rice and maize, while that of tea was 0.4 mg·kg−1. This result provided a theoretical basis for developing and utilizing Se resources in mountainous soil in southwestern China and dividing the Se-rich soil threshold. [ABSTRACT FROM AUTHOR]

Despite fertilization efforts, phosphorus (P) availability in soils remains a major constraint to global plant productivity. Soil incorporation of biochar could promote soil P availability but its effects remain uncertain. To attain further improvements in soil P availability with biochar, we developed, characterized, and evaluated magnesium-oxide (MgO) and sepiolite (Mg4Si6O15(OH)2·6H2O)-functionalized biochars with optimized P retention/release capacity. Field-based application of these biochars for improving P availability and their mechanisms during three growth stages of maize was investigated. We further leveraged next-generation sequencing to unravel their impacts on the plant growth-stage shifts in soil functional genes regulating P availability. Results showed insignificant variation in P availability between single super phosphate fertilization (F) and its combination with raw biochar (BF). However, the occurrence of Mg-bound minerals on the optimized biochars' surface adjusted its surface charges and properties and improved the retention and slow release of inorganic P. Compared to BF, available P (AP) was 26.5% and 19.1% higher during the 12-leaf stage and blister stage, respectively, under MgO-optimized biochar + F treatment (MgOBF), and 15.5% higher under sepiolite-biochar + F (SBF) during maize physiological maturity. Cumulatively, AP was 15.6% and 13.2% higher in MgOBF and SBF relative to BF. Hence, plant biomass, grain yield, and P uptake were highest in MgOBF and SBF, respectively at harvest. Optimized-biochar amendment stimulated microbial 16SrRNA gene diversity and suppressed the expression of P starvation response and P uptake and transport-related genes while stimulating P solubilization and mineralization genes. Thus, the optimized biochars promoted P availability via the combined processes of slow-release of retained phosphates, while inducing the microbial solubilization and mineralization of inorganic and organic P, respectively. Our study advances strategies for reducing cropland P limitation and reveals the potential of optimized biochars for improving P availability on the field scale. Article Highlights: MgO and sepiolite doping optimized biochar's surface properties for phosphorus (P) retention and slow release The potential formation of Mg-PO4 phases on the optimized biochar surface regulated P retention and release MgO and sepiolite-ptimized biochars increased soil available P by promoting microbial P mineralization and solubilization. [ABSTRACT FROM AUTHOR]

Food security is important to guarantee national security and people's livelihoods, but the increasingly serious problem of non-grain production (NGP) on croplands has exacerbated the risk of food security and directly affected the sustainable development of the national economy and society. This study adopted 130 cities (states) in the Yangtze River Economic Belt as the research units and used ArcGIS10.8, GeoDA1.22, and Origin2022 software and spatial autocorrelation, standard deviational ellipse, and GeoDetector methods to conduct analyses. This study explored the spatial evolution patterns and factors influencing cropland NGP in the Yangtze River Economic Belt. The results show, firstly, that the NGP rate of cropland in the Yangtze River Economic Belt increased from 35.85% in 2006 to 38.62% in 2022. The number of cities (states) with mild and moderate NGP decreased, while the number of cities (states) with severe NGP increased significantly. Secondly, the spatial distribution of the rate of cropland NGP in the Yangtze River Economic Belt had a strong positive correlation, with "high–high agglomeration" tending to be dispersed, "low–low agglomeration" tending to be concentrated, and the overall trajectory of the center of gravity migrating from the northeast to the southwest. Thirdly, the single-factor detection found that the per capita food possession, slope, elevation, and average annual precipitation had strong explanatory power regarding the spatial difference in cropland NGP in the Yangtze River Economic Belt, and the interaction of any two influencing factors showed nonlinear enhancement. The results of this study can help to precisely identify the spatial and temporal evolution characteristics of cropland NGP in the Yangtze River Economic Belt, which is of great significance for supporting the country in controlling the risk of NGP cultivation, promoting the sustainable development of the Yangtze River Economic Belt, and guaranteeing food security. [ABSTRACT FROM AUTHOR]

Microorganisms help govern soil organic carbon (SOC) turnover and accumulation. Whilst it is increasingly clear that microbial necromass is a precursor of SOC formation, the relationship between living microorganisms, necromass turnover and SOC persistence remains elusive. In this study, we used phospholipid fatty acids and amino sugars to quantify living versus dead microbial carbon concentrations and evaluated the utility of each pool as an indicator of SOC persistence across a range of climates (low‐, mid‐ and high‐latitude sites) and ecotypes (old‐growth forests vs. managed croplands). We found that microbial necromass was higher in forest than in cropland soils and was positively correlated with soil moisture, SOC and total nitrogen (TN). However, the flow of microbial biomass into necromass and SOC was decoupled in forest sites, likely because the high soil SOC/TN ratio accelerated necromass turnover and recycling by living microorganisms. In contrast, microbial biomass and necromass pools were tightly coupled in croplands and influenced by multiple environmental and biological factors (e.g., necromass concentrations exhibited greater variability in soils with more bacteria than fungi, and those with more gram‐positive than gram‐negative taxa). Contrasting our expectations, the proportion of microbially‐derived necromass in SOC was decoupled from soil properties and microbial biomass in both ecotypes. Whilst SOC and pH appear to be universal drivers of necromass cycling, feedbacks between living biomass, necromass and SOC are shaped by local factors. Our results contribute to ecological theory by highlighting the environmental and biological factors underpinning SOC formation and turnover that can be used to inform land‐management practices that optimize below‐ground carbon sequestration. [ABSTRACT FROM AUTHOR]

Soil organic carbon (SOC), total nitrogen (TN), total phosphorus (TP), and total potassium (TK) are important indicators for evaluating soil fertility. Exploring the content and spatial distribution of these indicators is of great significance for optimizing cropland management measures and developing sustainable agriculture. Yunnan Province is one of the most important agricultural regions in southwestern China, characterized by large variations in the topography and an uneven distribution of soil fertility. In this study, the data of 8571 topsoil (0–20 cm) samples selected from Yunnan Province and a portion of related spatial data were used to carry out electronic mapping of the spatial distribution of soil sand content, clay content, silt content, SOC, TN, TP, TK content, and C:N ratio at 1 km resolution using the Random Forest (RF) model. The results indicated that the average measured contents of SOC, TN, TP, TK, and C:N ratio in the topsoil of Yunnan Province were 18.78 ± 0.09 g/kg, 1.78 ± 0.01 g/kg, 0.98 ± 0.01 g/kg, 13.89 ± 0.08 g/kg, and 10.56 ± 0.02, respectively. The spatial analysis showed that higher SOC was mainly distributed in northern and eastern Yunnan, and the spatial distribution pattern of TN and TP was similar to that of SOC. While higher TK was mainly distributed in southwestern Yunnan Province. There was a significant positive correlation between SOC and TN and TP contents with correlation coefficients of 0.889 and 0.463, however, there was a significant negative correlation between SOC and TK content with correlation coefficients of −0.060. It was also indicated that elevation, temperature, precipitation, clay content, sand content, and silt content were the most important factors affecting SOC, TN, TP, and TK content. The present study provided an understanding of soil nutrients characteristics and their affecting factors, which is helpful to optimize agricultural management practices and develop sustainable agriculture according to soil fertility. [ABSTRACT FROM AUTHOR]

Context: Expansion of urban green space (UGS) enhances greenery and its benefits in cities. However, the impacts of such expansions on regional landscape sustainability and their spatiotemporal traits across the national scale remain unclear. Objectives: This study uncovers a trade-off between agricultural ecosystem services and urban human well-being—the loss of grain production due to UGS expansion consuming cropland—in China from 2000 to 2020. It proposes a safety boundary for UGS expansion to minimize the costs of grain production while addressing the escalating demand for UGS exposure. Methods: UGS expansion and cropland loss are quantified using land cover products, with statistical data contributing to the established relationship between grain loss and UGS coverage. UGS expansion scenarios for 2040 are simulated through bottom-up modeling. Results: Quadrupled UGS area growth contributed approximately one-third to urban expansion during 2000–2020 in China. Despite improvements in per capita UGS area implying enhanced UGS exposure during rapid urbanization, UGS expansion resulted in a national grain production loss of 4.2 ± 1.4 million t from 2000 to 2020, accelerating post-2010. This loss is equivalent to the annual food intake of 9.3 million Chinese people. We propose a 30.87% UGS coverage target in China by 2040 to preserve UGS access while minimizing grain loss under future urbanization. Conclusions: Acknowledging the critical role of UGS expansion in the issue of cropland loss to urbanization is imperative. Our results offer insights into ensuring human well-being and ecosystem services through landscape and urban planning. [ABSTRACT FROM AUTHOR]

This paper seeks to address the deficiency of utilizing satellite-based GRACE observations and model-based GLDAS water budget components in estimating the changes in the groundwater storage in Konya Endorheic Basin (KEB), a basin experiencing considerable land use land cover (LULC) change, primarily agricultural expansion. Cereal cultivation in the basin has a slight decreasing trend, however, the cultivation of crops with high water consumption, such as maize and sunflower, is increasing substantially. And total agricultural areas are increasing. GRACE-GLDAS approach does not accurately give the long-term groundwater decline in the basin, mainly because the land surface models employed in GLDAS cannot realistically simulate variations in water budget components as they do not consider the changes in LULC and do not possess an elaborated irrigation scheme. Here, we used a fully-distributed mesoscale hydrologic model, mHM, that can handle multiple LULC maps from different years. The model was modified to incorporate the spatio-temporal changes of agricultural fields in KEB and an explicit irrigation scheme since we hypothesized that the groundwater depletion is mainly caused by well irrigation. mHM was calibrated against streamflow observations for the period 2004–2019. The simulations show that the use of mHM with the incorporated features gives groundwater storage changes that are more consistent with the well-based observations than those obtained from the GRACE-GLDAS approach. On the other hand, the mHM simulation with a static LULC map, as in GLDAS models but with a better representation of irrigated fields, provides groundwater anomaly changes that are more consistent with the GRACE-GLDAS results, a further justification of insufficiency of the GLDAS-based approach in estimating groundwater variations for basins with considerable landscape change. [ABSTRACT FROM AUTHOR]

AbstractSoil erosion is still a vector of environmental and economic concern affecting most parts of the world, especially in Sub-Saharan African countries. Nevertheless, recent human activities in the hills, coupled with poor conservation measures and practices, could have amplified the rate at which soil is lost in the southwestern highlands of Ethiopia. This study focuses on quantifying and prioritizing micro-watersheds that require conservation actions by piloting spatial modeling of soil loss in the upper Bilate watershed. Sentinel image, soil, DEM, rainfall, and support practice data were used. A Revised Universal Soil Loss Equation (RUSLE) using GIS and satellite images was applied. The estimated average annual soil loss rate was demonstrated to be 24.1 t ha−1yr−1 and varied between 0.05 and 498.24 t ha−1yr−1. About 51.2% of the total revealed has a high soil truncation trait, of which 40% of the cropland has exceeded the soil loss tolerances of Ethiopia and tropical regions. The most affected micro-watersheds are MWS 16, 8, 6, and 3, which contributed 39.4% of the average annual loss rate, indicating the hotspots of soil loss problems in the region. This will have far-reaching off-site impacts on food security, soil productivity, human lives, infrastructures, and ecosystem service provisions.

ABSTRACT Animal‐mediated pollination is a key ecosystem service required to some extent by almost three‐quarters of the leading human food crops in global food production. Anthropogenic pressures such as habitat loss and land‐use intensification are causing shifts in ecological community composition, potentially resulting in declines in pollination services and impacting crop production. Previous research has often overlooked interspecific differences in pollination contribution, yet such differences mean that biodiversity declines will not necessarily negatively impact pollination. Here, we use a novel species‐level ecosystem service contribution matrix along with mixed‐effects models to explore how groups of terrestrial species who contribute differently to crop pollination respond globally to land‐use type, land‐use intensity, and availability of natural habitats in the surrounding landscape. We find that the species whose contribution to crop pollination is higher generally respond less negatively (and in some cases positively) to human disturbance of land, compared to species that contribute less or not at all to pollination. This result may be due to these high‐contribution species being less sensitive to anthropogenic land conversions, which has led humans to being more reliant on them for crop pollination. However, it also suggests that there is potential for crop pollination to be resilient in the face of anthropogenic land conversions. With such a high proportion of food crops requiring animal‐mediated pollination to some extent, understanding how anthropogenic landscapes impact ecological communities and the consequences for pollination is critical for ensuring food security.

Knowledge-based evidence about potential and existing rainfed cropping is crucial for decision-making for sustainable land use and food security. Using multi-criteria spatial analysis techniques, this study assessed the current status of cropland availability and projected impacts on future crop production in Ethiopia. The study primarily defined the extent of the Rainfed Cropping Area (RCA) and assessed the performances of different cropping practices. After precisely mapping cultivated area, cropping intensification potentials were estimated. Subsequently, disregarding the existing cultivated area, completely unsuitable areas, and protected and intact forest areas, the potentially available arable land using suitability analysis techniques was determined. In addition, the performance of existing crop production systems was evaluated against the natural potential. The findings reveal that RCA covers ~60% of the country’s landmass, of which cropping is practiced in only 33%. The coverage of Potentially Available Cropland (yet uncultivated) accounts for 16% of the country’s RCA. This is dominantly located in sparsely populated western and southwestern parts of the country. This study confirms that Horizontal Cropping Intensification (HCI) in the RCA of Ethiopia reaches only 33%. On the other hand, Vertical Cropping Intensification (VCI) practices cover only 10%, while about 1/3 of the RCA is suitable for VCI strategies at various levels of suitability. The performance of existing VCI-oriented cropping (which covers only 10% of the RCA) is very poor. Challenges to the use of the available cropland and ways of addressing land shortage for needy farmers are highlighted to inform efforts to readdress landlessness and food insecurity in Ethiopia.

During the last two decades, smallholder farmers in north-western Ethiopia have expanded eucalyptus fields into large areas of croplands until they recently started to reverse that trend. This study assessed the extent, drivers, and impacts of cropland to eucalyptus plantation changes during the 2000–2023 period and the recent land use reversal eucalyptus to cropland. It also analyzed the effect of the shift on land productivity and food security by comparing maize yields obtained from eucalyptus-cleared fields with those from permanent croplands. The assessment was conducted in the north-western highlands of Ethiopia and employed remote sensing techniques, yield difference comparisons, focus group discussions, and key informant interviews. Landsat-and Sentinel 2A-based multi-temporal image analyses were used to identify and map the coverage of eucalyptus plantation since 2000. Maize yield per plot was collected from 125 systematically selected paired 2mX2m plots, and yield differences were compared. One of the paired plots represented eucalyptus-cereal field changes, while the second represented cropland-maize plots. The multi-temporal image analysis result showed that eucalyptus plantation coverage was increased from 1000 ha in 2000 to 249,260 ha in 2023. Approximately 98% of that expansion was made onto crop fields. Latter, a large portion of that area was reconverted to cropland, mainly maize field due to substantial falls of market demand for eucalyptus logs. The oscillating land use changes imply that smallholders’ land use decisions are informed by intrinsic and extrinsic economic considerations, not by scientific-evidence-based landscape suitability and ecological analyses. Moreover, to check the effects of eucalyptus on subsequent productivity of croplands, we compared maize yield differences between cropland-maize and eucalyptus-maize field plots. The yield comparison result showed 35% average yield increment from eucalyptus-maize plots than yields from cropland-maize plots. This finding tends to defy the widely held perception that ‘growing eucalyptus tree plants on farmlands negatively affects the subsequent productivity of those plots’. However, this finding was based on a 1-year cross-sectional data. Further cross-sectional studies are important to arrive at conclusive results on the impacts of eucalyptus trees on productivity of those plots when converted to croplands.

Accurate and detailed spatial–temporal soil information is crucial for soil quality assessment worldwide, particularly in the countries with large populations and extensive agricultural areas. Using remote sensing technology to generate bare soil reflectance composites has been shown as a prerequisite for effectively modeling soil properties. However, most bare soil extraction methods rely on the single-period satellite imagery, making it difficult to produce a complete bare soil map. Although some developed methods have explored the advantages of multitemporal images, single indicators (e.g., Normalized Difference Vegetation Index and Normalized Burn Ratio 2) are prone to misidentifying bare soil as other land cover types such as impervious surface. Additionally, these methodologies were designed for specific areas and coarse spatial resolution images, leaving their generalizability to other areas or larger scales underexplored. Therefore, we proposed a Two-Dimensional Bare Soil Separation (TDBSS) framework to generate the bare soil composites of Chinese cropland at 10-m spatial resolution using multi-temporal Sentinel-2 images. This method employs the Normalized Difference Red/Green Redness Index and Soil Adjusted Vegetation Index as bidimensional indicators. We identified optimal thresholds for these indicators by analyzing ecoregion-specific samples and then implemented them across nine major agricultural zones in China. Additionally, we evaluated the framework against three prevalent bare soil extraction methods (i.e., Barest Pixel Composite, Soil Composite Mapping Processor, and Geospatial Soil Sensing System) based on spatial accuracy. The results showed that TDBSS outperformed the others with the highest overall accuracy of 78.28% and the lowest omission error of 0.198. The findings indicated that the TDBSS algorithm is competent in mapping bare soil at a national scale. The produced composite map of bare soil reflectance is particularly valuable for retrieving soil attributes in Chinese cropland. The TDBSS method can be easily implemented across broad areas with computational efficiency, contributing to land management, food security, and the development of policies for precision agriculture.

Satellite-based field delineation has entered a quasi-operational stage due to recent advances in machine learning for computer vision. Transfer learning allows for the resource-efficient transfer of pre-trained field delineation models across heterogeneous geographies. However, the scarcity of labeled data for complex and dynamic smallholder landscapes remains a major bottleneck. The key innovation of this study is to overcome this challenge by using pre-trained models to generate sparse (i.e., not fully annotated) field delineation pseudo-labels for fine-tuning models across geographies and sensor characteristics. We build on a FracTAL ResUNet trained for crop field delineation in India (median field size of 0.24 ha) based on multi-spectral imagery at 1.5 m spatial resolution. We use this model to generate pseudo-labels for the use in Northern Mozambique (median field size of 0.06 ha) based on sub-meter resolution true-color satellite imagery. We designed multiple pseudo-label selection strategies based on field-level probability scores and compared the quantities, area properties, seasonal distribution, and spatial agreement of the pseudo-labels against human-annotated training labels (n = 1,512). We then used the human-annotated labels and the pseudo-labels for model fine-tuning and compared predictions against human field annotations (n = 2,199). We evaluated performance with regards to object-level spatial agreement and site-level field size estimation. Our results indicate i) a good baseline performance of the pre-trained model in both field delineation (mean intersection over union (mIoU) of 0.634) and field size estimation (mean root mean squared error (mRMSE) of 0.071 ha), and ii) the added value of regional fine-tuning with performance improvements in nearly all experiments (mIoU increases of up to 0.060, mRMSE decreases of up to 0.034 ha). Moreover, we found iii) substantial performance increases when using only pseudo-labels (up to 77 % of the mIoU increases and 68 % of the mRMSE decreases obtained by human-annotated labels), and iv) additional performance increases (mIoU+0.008, mRMSE: −0.003 ha) when complementing human annotations with pseudo-labels. Pseudo-labels are architecture-agnostic, can be efficiently generated at scale, and thus facilitate domain adaptation in label-scarce settings. The workflow presented here is a stepping stone for overcoming the persisting challenges in mapping heterogeneous smallholder agriculture.

Global climate change is considered one of the greatest environmental threats in the world. It is expected to significantly change the global hydrological cycle. The two main water cycle components, potential evapotranspiration (PET) and precipitation (P), are closely related to vegetation dynamics. In this study, the partial correlation analysis method was used to analyzed the relationship between Normalized Difference Vegetation Index (NDVI) and climate factors (PET and P) based on grid cells. PET was calculated by FAO-56 Penman-Monteith method. Moreover, we also investigated the NDVI and climate factors in different vegetation cover types. The results showed that grassland, forest and cropland in China were positively correlated with PET and P. The time scales of the maximum partial correlation coefficients between NDVI and PET of grassland vegetation were mostly longer than 5-6 months. These time scales were longer than the time scales related to P. The partial correlation coefficients between NDVI and PET, P of forest vegetation were higher in northern China, whereas the spatial distribution of related time scales was the opposite. The partial correlation coefficients between NDVI and PET, P of forest vegetation were higher in northern China. However, the spatial distribution of related time scales was the opposite. The correlations between NDVI and PET, P of cropland vegetation and the time scales related to PET had clear spatial heterogeneity. The time scale of the correlation between NDVI and P for cropland in the northern China was about 2 months. P had a strong influence on the growth of various types of vegetation in the study area, and grassland vegetation was affected by P over the shortest time scale. We compare and analyze the results of this study with other related studies. These results provide a reference for exploring the dynamic changes in different vegetation types and factors impacting them. [ABSTRACT FROM AUTHOR]

Rapid urbanization currently poses a threat to cropland areas. Therefore, exploring the pattern of change in cropland areas and its driving mechanism is of great significance in safeguarding regional economic development and food security. In this study, data regarding cropland in the Changsha-Zhuzhou-Xiangtan city group (CZTCG) from 2000 to 2020 were collected, and dynamic changes in cropland in the past 20 years were analyzed. Based on this, the mechanisms that drive cropland change were explored in the context of multiple dimensions. Furthermore, an Inertial Development Scenario and a Cropland Priority Scenario were designed to simulate land use/land cover (LULC) changes in the CZTCG in 2025 and 2035, and, in particular, to analyze the characteristics of future spatiotemporal changes of cropland. The results demonstrated that the cropland area in the CZTCG in the past 20 years has shown a two-stage trend of increasing (2000-2015, increase of 8.25%) and decreasing (2015-2020, decrease of 2.91%), and the main reasons for cropland loss in the whole process of change were forest and building, with serious loss of cropland area in Changsha County and Wangcheng District. Between 2000 and 2020, socio-economic factors (GDP, total agricultural output), topography (elevation, slope), and climate change (average annual temperature, annual precipitation) were highly correlated with changes in cropland area, exhibiting significant temporal and regional variability. The simulation results indicate that until 2035, the Cropland Priority Scenario shows a significant increase in the area of cropland in the study area compared to the Inertial Development Scenario. Consequently, the implementation of a strategy that prioritizes cropland can effectively protect it, while helping to promote ecological development and regional socio-economic development. [ABSTRACT FROM AUTHOR]

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Revealing the relationship between land use changes and soil erosion provides a reference for formulating future land use strategies. This study simulated historical and future soil erosion changes based on the RULSE and GeoSOS-FLUS models and used a random forest model to explain the relative importance of natural and anthropogenic factors on soil erosion. The main conclusions are as follows: (1) From 1990 to 2020, significant changes in land use occurred in Kunming, with a continuous reduction in woodland, grassland, and cropland, being converted into construction land, which grew by 195.18% compared with 1990. (2) During this period, the soil erosion modulus decreased from 133.85 t/(km²·a) in 1990 to 130.32 t/(km²·a) in 2020, with a reduction in soil loss by 74,485.46 t/a, mainly due to the conversion of cropland to construction and ecological lands (woodland, grassland). (3) The expansion of construction land will continue, and it is expected that by 2050, the soil erosion modulus will decrease by 3.77 t/(km²·a), 4.27 t/(km²·a), and 3.27 t/(km²·a) under natural development, rapid development, and ecological protection scenarios, respectively. However, under the cropland protection scenario, the soil erosion modulus increased by 0.26 t/(km²·a) compared with 2020. (4) The spatial pattern of soil erosion is influenced by both natural and anthropogenic factors, and as human activities intensify in the future, the influence of anthropogenic factors will further increase. Traditionally, the expansion of construction land is thought to increase soil loss. Our study may offer a new perspective and provide a reference for future land use planning and soil loss management in Kunming. [ABSTRACT FROM AUTHOR]

Reconstructing historical land-use and land-cover change (LULCC) inevitably involves interpolation across regions for which there is limited data to support reconstructions. Here, we evaluate the extent to which the global land-use model HYDE v3.2.1 reflects historical land use in sub-Saharan Africa (including Madagascar) when compared to archaeological and historical reconstructions. Both the HYDE models and Widgren’s archaeological and historical reconstructions estimate that agriculture was widely scattered across sub-Saharan Africa in 1800 CE. However, in steep terrain, at slopes greater than 10°, the HYDE model estimated 0% cropland allocation while archaeological and historical observations suggest intensive, mixed and extensive farming was common in these areas. In addition, while HYDE allocates farmland primarily into high-quality soils, archaeological reconstructions suggest that intensive farming occurred across a wide range of soil qualities. Gaps in our knowledge of cropland distribution have significant impacts on models of biodiversity change since understanding biodiversity in the Anthropocene is reliant on our understanding of past land-use changes. While HYDE’s mismatches are known, the research presented here provides an important resource in identifying where these allocation rules fail. These mismatches in global land-use models such as HYDE might also be replicated for other regions of the world, such as South America. These mismatches also need to be accounted for when generating model projections that use historical land-use models to impute present and future trends in land-use, climate and biodiversity change. Localised archaeological and historical data can therefore be used to support historical global land-use reconstructions for Africa and other regions across the world. [ABSTRACT FROM AUTHOR]

Grasslands are one of the most widespread terrestrial biomes. In Europe, the majority of grasslands depends on human management, and as a result, grassland areas are facing different dynamics and transitions to other land cover types. This study identifies the trajectories in grassland cover in Europe from 1990 to 2018. Using a 1 km × 1 km grid spanning most European countries, we identified increasing, decreasing and mixed development trajectories of grassland cover. For each development trajectory, we selected four representative hotspots and identified the land cover and its changes over different periods. Our results reveal that the decreasing development trajectory occurred on 35% of the aggregated grids with hotspots in Eastern Europe, the Mediterranean region and the UK. The increasing development trajectory occurred on 20% of the aggregated grids, centred in Central Europe, and the mixed development trajectory occurred on 3% of the aggregated grids. Within the selected hotspots, the development trajectories were linked to transitions among agricultural land cover classes or to transitions with shrubs and urban areas. The development trajectories also indicated strong country-specific differences, suggesting a strong impact of national policies. The generated outcomes of this study can be used to support decision-making on future pathways for grassland habitats on a European scale. [ABSTRACT FROM AUTHOR]

Species‐specific management strategies have been implemented to address persistently low continental populations of several duck species, including the northern pintail (Anas acuta). In the Canadian Prairie Pothole Region (PPR), addressing threats from spring‐seeded cereals on pintail productivity may provide sufficient gains to recover populations. Research on pintail duckling ecology has revealed that duckling survival may be greater in grassland‐dominated landscapes than in annual cropland‐dominated landscapes, possibly limiting the benefits of fall‐seeded cropping practices. Winter wheat crops increase nest success and may assist nesting pintail populations through provision of nesting refuges from spring tillage operations, earlier hatch, and greater nest densities compared to traditional spring‐seeded cereal crops. Yet inadequate duckling survival may reduce these benefits. Our principal objective was to examine if pintail reproductive success in winter wheat in cropland‐dominated landscapes was comparable to grassland‐dominated landscapes or, alternatively, if duckling survival rates in cropland‐dominated landscapes offset the gains of greater nesting success in winter wheat. We captured and radio‐marked 104 nesting female pintails in grasslands and croplands of southern Saskatchewan, during 2011–2012. We modeled cumulative survival to 30 days post hatch in relation to landscape composition and land cover type, specifically, the influence of nesting in fall‐seeded crops. Predicted 30‐day survival for ducklings hatched in perennial cover (40.8% [85% CI = 40.0–44.6%]) in grassland‐dominated landscapes and winter wheat (38.2% [32.0–44.4%]) in cropland‐dominated landscapes was more than double survival of ducklings hatched in spring‐seeded cropland (16.9% [12.6–21.6%]) in cropland‐dominated landscapes. Ducklings moving through local environments with more perennial cover and seasonal wetlands, but less wetland edge, had increased survival. The benefit of greater nest survival in winter wheat was not completely superseded by reduced duckling survival for broods raised in intensive agricultural landscapes. The retention of grassland landscapes and expansion and promotion of fall‐seeded crops in cropland‐dominated landscapes can benefit northern pintails across broad regions of the PPR. [ABSTRACT FROM AUTHOR]

In mining areas with high groundwater tables, mining subsidence can lead to the inundation of cropland by water, causing damage to cropland and posing a threat to national food security. The implementation of concurrent mining and reclamation techniques can effectively enhance the reclamation rate of cropland. This technique requires engineers to initiate reclamation measures before cropland waterlogging occurs. Therefore, when mining a panel underground, an accurate calculation of the time when cropland becomes waterlogged, known as the theoretical reclamation timing, is crucial. To address this issue, this study proposes a computational method for the theoretical reclamation timing of cropland under the conditions of single-panel mining based on intelligent optimization algorithms. In addition, this paper also proposes an optimization method for the theoretical reclamation timing of cropland within a district based on an intelligent optimization algorithm. Utilizing this method makes optimizing the layout of multiple panels possible, thereby delaying the theoretical reclamation timing for cropland within a district. This approach aims to shorten the duration of reclamation projects and minimize their interference with agricultural activities. Through experimental validation, this paper demonstrates the reliability of these two methods. This study is beneficial for the rational planning of reclamation projects. [ABSTRACT FROM AUTHOR]

Background and Aims: Understanding microbial compositions and functions in arable soils is crucial for effective agroecosystem management. While many studies have explored this topic, large-scale investigations are lacking, resulting in the absence of consistent and reliable patterns of communities and functions of soil microorganisms. Methods: To address this gap, we performed an integrated analysis of published sequencing data from the soils of three main arable fields: upland, paddy, and paddy-upland rotation. Results: Bacterial diversity (richness, Shannon) was highest in upland soils. Actinobacteria and Planctomycetes were enriched in upland soils, while Proteobacteria, Chloroflexi, and Nitrospirae preferred paddy and paddy-upland rotation soils. Bacteria in upland soils have a greater functional potential to decompose aromatic compounds, as well as for chitinolysis and ureolysis. Methanotrophy, methylotrophy, sulfur-related respiration, and most nitrogen metabolic processes were enriched in paddy fields. Bacteria in upland soils are characterized by increased dormancy potential and a faster response to resource input than those in paddy and paddy-upland rotation soils. Stochastic processes poorly contribute to the bacterial assembly in paddy soils, indicating strong environmental filtering due to anaerobic conditions. The spatial turnover in bacterial community composition was much faster than the functional potential, indicating high functional redundancy, especially in paddy soils. Edaphic factors were the major contributors to bacterial composition, whereas the cropland type influenced the predicted functions. Conclusions: Land use defines microbial composition, functional attributes, and ecological characteristics (e.g., dormancy potential, assembly processes, and functional redundancy). These findings deepen our knowledge of microbial biogeographic patterns in soils of agricultural ecosystems and provide new insights into sustainable cropland management. [ABSTRACT FROM AUTHOR]

Gridded landcover datasets like the NASS Cropland Data Layer (CDL) provide a useful resource for analyses of cropland management. However, many farm operation decisions are made at the field level, not the pixel level. To capture relationships between land cover and field characteristics – size, contiguity, etc. – some method is needed to aggregate gridded data into crop fields. To provide a uniform and consistent approach for aggregation of gridded data at the field level over a series of years, this research project developed a set of Crop Sequence Boundaries (CSBs), which are polygons that delineate areas of homogeneous cropping sequences for the contiguous US. The CSBs are open-sourced algorithm-based, geospatial polygons derived using historic CDLs together with road and rail networks to capture areas with common cropping sequences. The CSB approach used geospatial functions in Google Earth Engine (GEE) and in the ArcGIS Pro application. These geospatial functions are run in parallel by sub-dividing the contiguous US into smaller regions based on road and rail boundaries to prevent overlaps or gaps in the data. As a new set of algorithmically delineated field polygons, the CSBs enhance applications requiring large-scale crop mapping with vector-based data. [ABSTRACT FROM AUTHOR]

Recently, the Agricultural Policy Extender (APEX) model was enhanced with a grazing module, and the modified grazing database, APEXgraze, recommends sustainable livestock farming practices. This study developed a combinatorial deterministic approach to calibrate runoff-related parameters, assuming a normal probability distribution for each parameter. Using the calibrated APEXgraze model, the impact of grazing operations on native prairie and cropland planted with winter wheat and oats in central Oklahoma was assessed. The existing performance criteria produced four solutions with very close values for calibrating runoff at the farm outlet, exhibiting equifinality. The calibrated results showed that runoff representations had coefficients of determination and Nash–Sutcliffe efficiencies >0.6 in both watersheds, irrespective of grazing operations. Because of non-unique solutions, the key parameter settings revealed different metrics yielding different response variables. Based on the least objective function value, the behavior of watersheds under different management and grazing intensities was compared. Model simulations indicated significantly reduced water yield, deep percolation, sediment yield, phosphorus and nitrogen loadings, and plant temperature stress after imposing grazing, particularly in native prairies, as compared to croplands. Differences in response variables were attributed to the intensity of tillage and grazing activities. As expected, grazing reduced forage yields in native prairies and increased crop grain yields in cropland. The use of a combinatorial deterministic approach to calibrating parameters offers several new research benefits when developing farm management models and quantifying sensitive parameters and uncertainties that recommend optimal farm management strategies under different climate and management conditions. [ABSTRACT FROM AUTHOR]

In croplands, soil erosion resistance varies with both natural processes and human disturbances. To clarify the temporal variation in soil erosion resistance, nine cropland plots with three treatments (continuous fallow, fallow after tillage and tillage with corn) were established in the dry–hot valley region of China. A total of 144 field runoff simulation experiments were conducted from May to October to measure the soil detachment rate (Dc), rill erodibility (Kr) and critical shear stress (τc). The results revealed that the natural dry—wet alternation had little influence on the continuous-fallowed soil erosion resistance. On the other hand, the tillage disturbance that occurred in May sharply increased the Dc and Kr to 2.24 and 3 times that of the continuous-fallow treatment, respectively. Then, the erosion resistance could be enhanced with surface consolidation for the fallow-after-tillage treatment. However, after three months of fallow, the Kr was still 89.5% of the fresh tilled soil. In contrast, crop growth could significantly improve aggregate stability and reduce the Kr to 38.2% in August and even further to 23.7% in October compared to the fresh tilled soil. It could be concluded that crop growth is more efficient in enhancing erosion resistance than the mechanical effect. The above results would benefit from the accurate modeling of cropland soil erosion dynamics and guide agricultural management in dry–hot climate regions. [ABSTRACT FROM AUTHOR]