Search Results (643)

Prescribed fire is a critical land management practice in the Great Plains of North America, helping to maintain native rangelands and reduce wildfire risk. Barriers to prescribed fire practice remain due to concerns on potential fire escape and fire danger. A localized fire danger index can help address these concerns by providing clear, science-based guidance, encouraging safer and confident use of prescribed fire. Our goal is to support the development of a localized Grassland Fire Danger Index (GFDI) for prescribed fire management in the Great Plains. The specific objective of this study is to develop user-friendly sub-models for dead fuel moisture content (DFMC) and grass curing, which serve as components of the proposed GFDI. DFMC reflects short-term fuel moisture that affects ignition and fire spread, while grass curing represents seasonal drying that controls fuel availability. Both are critical for fire prediction and safe burns. Lower DFMC and higher grass curing levels are strongly associated with wildfire risks. Using Oklahoma Mesonet weather data, the DFMC sub-model improves the accuracy and sensitivity of existing models. The grass curing sub-model shows that 50% curing usually occurs around April 15–16, which matches the time for the most intensive prescribed fire activities in the region, indicating it as a safe and effective window for prescribed fire recognized by landowners. Our sub-models lay the foundation for development of GFDI in the region. Full article

Vegetation heterogeneity supports biodiversity, while homogeneity limits it. In the Great Plains, fire and herbivory enhance ecosystem function by increasing spatial heterogeneity. However, quantifying their effects on plant functional traits and spectral diversity remains challenging due to landscape complexity and scaling limitations. Hyperspectral remote sensing offers a high-resolution approach to assessing these dynamics, improving the evaluations of post-fire recovery and vegetation function. This study examines the impact of fire on plant functional traits and spectral diversity within a savanna landscape in the Edwards Plateau, Texas, using airborne hyperspectral and multispectral imagery. Specifically, it aims to (1) quantify the spatial patterns of plant functional traits and spectral diversity, (2) assess fire’s effects on these patterns, and (3) evaluate how soil type, woody structure, and burn patterns mediate fire responses. High-resolution airborne images from 2018 (pre-fire) and 2020 (post-fire) were analyzed to classify burned and unburned areas, pre-fire woody cover, and derive spectral indices representing plant functional traits, β-diversity components, and spectral evenness. The results indicate that temporal patterns in spectral diversity were driven primarily by soil properties and weather, with limited evidence that fire altered spectral evenness or β-diversity across soils. In contrast, spectral indices showed clearer—but still soil-dependent—fire effects: declines in canopy structure, greenness, and chlorophyll content were less pronounced in burned areas, indicating that fire partially moderated late-season senescence. Fire had a substantial influence on spatial patterns of spectral evenness (but not β-diversity) and vegetation spectral functional traits, and fire and dry-down increased spatial heterogeneity in spectral evenness and in spectral indices indicative of biophysical and biochemical traits across scales. These findings demonstrate that environmental drivers, particularly soil–moisture interactions and interannual moisture variability, exert a stronger control over post-fire spectral diversity than fire alone. Hyperspectral imaging effectively captured these dynamics, supporting its role in monitoring post-fire vegetation responses. In addition to the use of hyperspectral imaging, fire management strategies should consider broader ecological drivers, including soil and weather interactions, to improve the assessments of ecosystem resilience and recovery. Full article

Manure management costs are a substantial component of overall costs on a modern dairy farm. Due to the slim margins of contemporary milk production operations, dairies are under constant pressure to increase milking herd sizes to take advantage of size economies that enable them to compete in the global marketplace. This study provides a current assessment of manure management and overall costs and returns on four standard sizes of dairies typical of the southern Great Plains, particularly north central Texas. The study is necessitated by the fact that the changing economic landscape has resulted in substantial changes in manure management practices. This study also forms the basis for additional analyses that will explore alternative value-added options for dairy manure management. We utilize the Farm-level Economic Model to holistically simulate the costs and returns of four representative dairy herd sizes—small (300 cows), medium (720 cows), large (1500 cows), and very large (5000 cows). Based on prevailing assumptions about land areas farmed and farm management practices, we find that dairy farms require between 0.18 and 0.4 ha/cow to manage manure based on crop nitrogen uptake rates, versus 0.67 to 0.95 ha/cow for crop phosphorus uptake rates. Manure application costs alone range from USD 55/cow (USD 225/ha) to USD 115/cow (USD 300/ha) depending on dairy size, but some of these costs are offset by fertilizer cost savings. Proportion of manure hauled offsite ranges from 9% to 67% for phosphorus-based applications, depending on herd size, and net incomes per cow are reduced by USD 60 to USD 100 (USD 4.33 to USD 8.27 per Mg of milk) if manure is applied based on phosphorus uptake rates as compared to nitrogen uptake rates of receiving crops. Generating a broad array of economically viable value-added product options from dairy manure would enable farmers to be more competitive in a market characterized by thin margins. Full article

Clarifying the spatiotemporal evolution pattern of cultivated land use system resilience (CLUSR) in major grain-producing areas and identifying the key obstacles constraining its enhancement is of great significance for promoting the sustainable development of cultivated land use systems and ensuring regional food security. Taking the Songnen Plain, a typical major grain-producing area in China, as the study area, we constructed a CLUSR evaluation index system based on the “Resources–Utilization–Production–Ecology” (RUPE) framework and analyzed the spatiotemporal dynamics of CLUSR. Furthermore, we identified the primary factors impeding CLUSR enhancement. The results were as follows: (1) From 2005 to 2020, CLUSR values in the Songnen Plain ranged from 0.3353 to 0.4256, indicating a moderately low level overall but showing an upward trend. Across subsystems, the mean resilience scores followed the order ESR (0.121) > RER (0.114) > GPSR (0.090) > CLUR (0.055). (2) Spatially, CLUSR exhibited a distinct “high in the east and low in the west” pattern, with significant growth in the northwestern region. High–High clusters were primarily concentrated in the southeastern part of the study area, while Low–Low clusters exhibited a divergent spatial pattern. (3) From an indicator perspective, agricultural output value per unit of cultivated area, water coverage degree, agricultural labor input, agricultural mechanization level, cultivated land area, per capita yield of grain, and agricultural capital investment were identified as the dominant obstacles to CLUSR improvement. From a subsystem perspective, grain production stability and cultivated land use subsystems were the primary factors limiting CLUSR improvement in the Songnen Plain. (4) At the county level, obstacle factors were classified into three types: single, dual, and multiple obstacles. Nearly half of the counties were facing multiple constraints simultaneously. This study provides theoretical and practical implications for the formulation of cultivated land use policies in the Songnen Plain and other major grain-producing areas worldwide, thereby contributing to the sustainable utilization of cultivated land. Full article

Intersectoral labour mobility is a key driver of economic resilience and innovation in Europe. The redistribution of workers across sectors and regions enables economies to adapt to shocks, create flexibility and increase the rate of structural change. However, the dynamics of mobility have not been adequately investigated across varying scales of sectoral granularity and spatio-temporal dimensions. This paper applies the Intersectoral Mobility Index (MI) to all European NUTS-2 areas from 2008 to 2020, utilising Eurostat Structural Business Statistics. Two levels of sectoral aggregation (NACE Rev. 2, 1-digit and 2-digit) are employed to compute MI, capturing both broad and fine-grained reallocations. Classical indices of structural change (NAV, Krugman, Shorrocks) are combined with spatio-temporal modelling in ArcGIS Pro, employing Space–Time Cubes, time-series exponential smoothing forecasts, time-series clustering and emerging hot spot analysis. Results indicate that MI distributions are positively skewed and heavy-tailed, with peaks coinciding with systemic crises (2009–2011, 2020). At the 2-digit level, MI values are significantly higher, revealing intra-sectoral changes obscured in aggregated data. A statistically significant downward trend in mobility suggests an increasing structural rigidity following the global financial crisis. Regional clustering highlights heterogeneity: a small number of regions, such as Bremen, Madeira and the Southern Great Plain, have sustained high or unstable mobility, while most exhibit convergent mobility and low reallocation. This paper contributes to the conceptualisation of MI as a dual measure of resilience and innovation preparedness. It underscores the importance of multi-scalar and spatio-temporal methods in monitoring labour market flexibility. The findings have policy implications, including the design of targeted reskilling programmes, proactive labour market policies and just transition plans to maintain regional resilience during the EU’s green and digital transitions. Full article

This study investigates the multi-scale processes associated with one type of typical heavy rainfall event in North China, focusing on the interplay among synoptic circulation, mesoscale dynamics, and topographic influences. The synoptic setting, characterized by the East Asian Great Trough, the South Asian High, and a northward-extended Western Pacific Subtropical High, created favorable conditions for moisture transport and convective activity. The event unfolded in two distinct phases: nocturnal and afternoon phases. During the nocturnal phase, an intensified 850 hPa low-level jet transported substantial meridional moisture into North China. Terrain-induced convergence along the Taihang Mountains enhanced lifting, resulting in concentrated precipitation at the foothills. In contrast, during the afternoon phase, the eastward movement of a Mongolian low trough and its associated cyclonic circulation shifted rainfall toward the plains east of the Taihang Mountains. Convective clusters developed locally due to surface heating and were organized along the low-level jet on the eastern flank of the cyclone, further intensifying precipitation. These results underscore three key mechanisms: nocturnal low-level jet-driven moisture convergence, synoptic-scale trough propagation, and terrain-modulated mesoscale convection. Understanding their diurnal variability offers valuable insights for operational forecasting, monitoring, and early warning systems for high-impact rainfall events in North China. Full article

The great city of Mayapan has experienced a technological change in pottery making, and our results confirm a shift in the raw materials and possibly the potters’ knowledge about them. The dynamics of change during the Postclassic period in the Maya area are reflected in the material changes used to make pottery. A comprehensive analysis was conducted on a collection of 248 pottery items from the archaeological site of Mayapán in Yucatán, Mexico, dating from the Middle Preclassic to Postclassic periods (700 BC–1500 CE). Non-invasive methods were used for the entire pottery set, including X-ray fluorescence (XRF) and fiber-optic reflectance spectroscopy (FORS). Additionally, for a representative subset, minimally invasive techniques such as inductively coupled plasma optical emission spectrometry (ICP-OES) and laser-induced breakdown spectroscopy (LIBS) were employed. The resulting data enabled the identification of materials used in the pottery’s manufacture. The elemental composition of the objects was determined, revealing correlations between elements such as Si with Al that yield a $R^2$ factor of 0.94. The results indicate the presence of smectite clays, carbonates, and iron oxides. The results show that a higher proportion of carbonates was found in the pieces from the Postclassic period compared to those from the Preclassic period, which may be associated with a change in the manufacturing process. Likewise, the Postclassic pieces are distinguished by a greater contribution of the Mg-OH signal, unlike the Preclassic and Classic, which show a greater contribution of the Al-OH group. The implications for the technological knowledge of the potters suggest the use of different technologies across various periods and material changes driven by shifts in political and economic relations in the city and the northern plains. Full article

The starting torque of Self-lubricating Spherical Plain Bearings (SSPBs) has a significant impact on the reliability and service life of aircraft. Due to the low accuracy of the dynamic detection of the starting torque of the bearing, the starting torque cannot be measured accurately under high-frequency swinging conditions. Therefore, the problem of the dynamic detection accuracy of the starting torque of the bearing on a high-frequency swinging friction and wear tester was proposed to be investigated in this paper, and a dynamic simulation model of the swinging system of the tester was constructed. With the combination of the inertia torque test and the least square method, a mathematical model of the inertia torque was developed and the influence of the inertia torque on the results of the dynamic detection of the starting torque was revealed. At the same time, an error compensation procedure for the on-line dynamic detection of the starting torque was written. This research shows that the inertia torque of the swing system of the tester has a great influence on the detection accuracy of the starting torque. As the swing frequency increases, the inertia torque increases, and the dynamic detection accuracy of the starting torque is reduced. The dynamic detection error of the starting torque of the bearing can be efficiently compensated by the error compensation procedure, and then the detection accuracy can be improved. This research provides a good theory for the design of SSPBs and the reasonable control of the starting torque during the use of the bearings, and it is valuable for engineering practice. Full article

Against the backdrop of expanding off-farm employment, it is of great practical significance to examine how off-farm employment affects grain production and its underlying mechanisms, in order to build a more stable and sustainable national food security system. Drawing on micro-level data from wheat-producing households in the national Rural Fixed Observation Points survey from 2004 to 2021, this study systematically investigates the impact of off-farm employment on wheat planting decisions and the channels through which it operates. The findings reveal the following: (1) Off-farm employment encourages farmers to adjust their factor input structure and crop choices, leading to an increased proportion of wheat sown area. (2) Agricultural socialized services, especially mechanized operations, enhance the feasibility of factor substitution and effectively channel off-farm income into agricultural investment. Furthermore, the number of service providers at the village level plays a significant moderating role in this process; the more adequate the service supply, the stronger the positive effect of off-farm employment on wheat cultivation. (3) The influence of off-farm employment on wheat production is more pronounced in plain regions with favorable topographic conditions and among large-scale farming households. Based on these findings, the study recommends improving the agricultural service system, promoting better coordination between off-farm employment and agricultural development, and fostering a more stable and sustainable support system for grain production. Full article

Soil organic matter (SOM) is a key component of nutrient cycling and soil fertility in terrestrial ecosystems. SOM is of great significance to the stability of terrestrial ecosystems and the improvement of soil productivity; to further exert its role, it is first necessary to clarify its actual distribution and occurrence status in specific regions. Under the combined impacts of intensive agriculture, unreasonable farming practices, and climate change, the SOM content in the Songnen Plain is showing a degradation trend, posing multiple stresses on its soil ecosystem functions. This study aims to systematically track the dynamic changes of SOM in the Songnen Plain, assess its spatiotemporal evolution characteristics, and reveal its driving mechanisms. A total of 113 representative soil profiles were selected in 2023; standardized excavation and sampling procedures were employed in the Songnen Plain. Soil pH, SOM, total nitrogen (TN), total phosphorus (TP), total potassium (TK), particle size (PSD), texture, and Munsell soil colors of samples were determined. Temporal variation characteristics, as well as horizontal and vertical spatial distribution patterns, in SOM content in the Songnen Plain were assayed. Structural equation modeling (SEM), together with freeze–thaw of soil and soil color mechanism analyses, was applied to reveal the spatiotemporal dynamics and driving mechanisms of SOM. The result indicated that the distribution pattern of SOM content in horizontal space shows higher levels in the northeastern region and lower levels in the southwestern region, and decreased with increasing soil depth. SEM analysis indicated that TN and PSD were the main positive factors, whereas bulk density exerted a dominant negative effect. The ranking of contribution rates is TN > TK > TP > PSD > annual average temperature > annual precipitation > bulk density. Mechanistic analysis revealed a significant negative correlation between SOM content and R, G, B values, with soil color intensity serving as a visual indicator of SOM content. Freeze–thaw thickness of soil was positively correlated with SOM content. These findings provide a scientific basis for soil fertility management and ecological conservation in cold regions. Full article

Background: Genetic improvement in wheat yield is the most focused research area for the breeding community to ensure sustainable production. Wheat kernel traits and biomass are considered key contributors to enhance crop yield. Methods: This study was designed to explore the genetic diversity of kernel and biomass traits in popular wheat varieties from the US Southern Great Plains using 264 doubled haploid (DH) lines mainly derived from TAM 114 or TAM 204. This population was evaluated in two field environments planted in alpha lattice design during the 2020 crop season. Kernel traits were collected using the hp Scanjet G4010 photo scanner for image capturing and GrainScan v3. software for image analysis. Biomass parameters were collected and processed manually. For genotyping genomic libraries were prepared and sequenced on Illumina NovaSeq 6000 to generate paired end reads of 150 bp. Sequences were aligned to the IWGSC RefSeq genome assembly v2.1 using the Burrows Wheeler Aligner for SNP calling. Results: A total of 59,482 polymorphic SNP markers were retained for genetic analysis after the filtration at 50% missing data and 5% minor allele frequency. To investigate the marker–trait association and the genomic regions, four genome-wide association study models were implemented using the R package GAPIT version 3.5. Based on the Bonferroni correction <8.41 × 10⁻⁷ was used as a threshold to declare marker-trait associations (MTAs) significant. The BLINK model identified 12 MTAs on chromosomes 1A, 2A, 2B, 4A, 4B, and 6B. Conclusions: The identified MTAs can be used to develop diagnostic markers for efficient selection and utilization in recombination breeding and cultivar development process. Full article

A polyamidoamine-based hydrogel (H-M-GLY) and its montmorillonite-based composite (H-M-GLY/MMT) were studied as selective cleaning materials for cultural heritage conservation. H-M-GLY was synthesized from a glycine-based polyamidoamine oligomer with acrylamide terminals (M-GLY) through radical polymerization at pH 7.3 and had a basic character. The M-GLY oligomer was in turn synthesized from N,N′-methylenebisacrylamide and glycine in a 1:0.85 molar ratio. H-M-GLY/MMT was obtained by cross-linking a 1:0.1—weight ratio—M-GLY/MMT mixture at pH 4.0, to promote polyamidoamine-MMT interaction. The composite hydrogel absorbed less water than the plain hydrogel and proved tougher, due to montmorillonite’s electrostatic interactions with the positively charged M-GLY units. Scanning electron microscopic analysis showed that MMT was uniformly dispersed throughout the hydrogel. Both hydrogels were subjected to ink bleeding tests on papers written with either iron gall or India ink. Microscopic observation revealed neither bleeding nor release of hydrogel fragments. Being basic, H-M-GLY successfully deacidified the surface of aged paper. H-M-GLY/MMT, swollen in a 1:9 ethanol/water solution, was found to be effective in removing wax, known to trap carbonaceous particles and form dark stains on artistic artifacts. This study demonstrates the great potential of polyamidoamine-based hydrogels as versatile selective cleaning systems for cellulosic and other cultural heritage materials. Full article

The primary goal of Transportation systems is to provide transportation accessibility to opportunities. Equitable access to essential destinations encompassing social, recreational, educational, and civic opportunities needs to be more consistent across different social groups. This study evaluates the disparities in social justice using social equity as a measure of transit access and walk access to non-work amenities. These non-work amenities include grocery stores, personal services, retail outlets, recreational venues, entertainment centers, and healthcare facilities in the U.S. Logistic regression models are developed using the 2017 National Community Livability Survey data. The results indicate regressive public transit access for socially disadvantaged groups, including older citizens, non-drivers, Medicare/Medicaid beneficiaries, and non-metropolitan residents. Walk access inequities similarly affect older individuals, non-drivers, the physically disabled, the unemployed, students, women, and non-metropolitan residents. This research emphasizes the importance of addressing transit and walk-access inequities to non-work amenities within transportation systems. By acknowledging the disparities in transportation equity, decision-makers and communities can foster more inclusive and equitable access to essential destinations, thereby promoting social cohesion and overall community well-being. Full article

The research on the optimization and transformation of rural “production-living-ecological” functions (PLEFs) is of great significance for rural revitalization and sustainable development. Existing studies predominantly evaluate rural PLEFs at the macro level, with few micro-village case studies, and particularly empirical studies in China’s plain agricultural areas. This study takes Caiwu Village, a rural revitalization demonstration village in Yuanyang County, Henan Province, China, as a typical case. First, we constructed a village PLEF classification system based on micro-scale land use types. Then, methods such as GIS spatial analysis, actor network analysis, and satisfaction fuzzy comprehensive evaluation were comprehensively used to systematically analyze the process, mechanism, and effects of the rural PLEF transformation in Caiwu Village. Our research indicates the following: (1) Caiwu Village has gone through three stages of transformation: traditional agriculture leading, ecological agriculture starting, and agriculture-tourism integration development, indicating a shift from traditional agricultural production functions to modern production-ecological composite functions. (2) The PLEF transformation in Caiwu Village resulted from the synergy of multiple actors, including governments, cooperatives, villagers, and water-soil resources, through administrative recruitment and market recruitment. Finally, (3) there are significant differences in the effects of rural PLEF transformation based on villagers’ perception. Specifically, villagers report the highest satisfaction with ecological function, followed by living function, and the lowest satisfaction with production function. This study provides empirical evidence for understanding the differentiated transformation of PLEFs in villages in plain agricultural areas. The research results can provide decision-making references for optimizing and improving the PLEFs of Caiwu Village and other similar villages. Full article

Although the ultimate drivers of bat fatalities at wind turbines are still not well understood, the foraging behavior of insectivorous bats puts them at increased risk of collision with rotating blades. Wind energy facilities are commonly located in agriculture fields where bats can exploit periodic superabundant insect emergence events in the late summer and early autumn. Thermal imaging, acoustic monitoring, and bat carcass stomach content analyses show that bats prey upon insects on and near wind turbine towers. Studies have shown a positive association between insect abundance and bat activity, including in agricultural systems. We conducted a systematic review of bat diets for four common bat species in the Midwest and northern Great Plains to synthesize existing knowledge across species, assess the extent to which these bat focal species consume crop pests, and evaluate the potential for crop pest emergence models to predict temporal and spatial patterns of bat fatalities in this region. Big brown bats and eastern red bats consumed a variety of crop pests, including some for which emergence models may be available. In contrast, there were few studies for hoary bats or silver-haired bats, and the dietary evidence available has insufficient taxonomic resolution to conclude that crop pests were consumed. To augment existing data and illuminate relationships, we recommend that genetic diet analyses for bats, specifically hoary and silver-haired, be conducted in the late summer and autumn in this region. The results of these studies may provide additional candidate insect models to evaluate for predicting bat fatalities at wind turbines and clarify if the superabundant insect emergence hypothesis warrants further investigation. Full article