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Lightning-ignited wildfires (LIWs), which predominantly occur in remote regions, pose significant challenges for prediction and mitigation, while contributing disproportionately to burned areas in Texas. Persistent knowledge gaps regarding key ignition drivers and their nonlinear interdependencies hinder the development of targeted prevention strategies and robust early warning systems. To address these limitations, we compiled a statewide dataset spanning 2010–2020 comprising 4775 LIWs and employed an optimized repeated-random undersampling strategy to mitigate class imbalance. Using this dataset, we developed an eXtreme gradient boosting-based machine learning model that integrates meteorological, soil, vegetative, lightning, topographic, and human activity variables to predict LIW probability. The most accurate classifier achieved an out-of-sample prediction accuracy of 85.81%, outperforming the fire weather index and methodologies of random forests and logistic regression. Key drivers of ignition were identified as higher lightning frequency, elevated temperatures, and lower fuel moisture content. Spatial analysis revealed LIW clustering in needleleaf forests of eastern Texas, where maximum fuel loading (indicated by normalized difference vegetation index) and lightning density interacted to create ignition-prone conditions.

Channel encroachment intensifies competition among channels and changes the relationships within the supply chain. This study examines the manufacturer’s agency channel encroachment decision and its impact when it has already operated a platform reselling channel and a retailer channel on the platform. Equilibrium results reveal that the manufacturer’s agency channel encroachment triggers a competition effect, leading to a reduction in market demand for both the platform’s reselling channel and the retailer’s channel, as a larger share of the market shifts toward the manufacturer’s agency channel. To compensate for the losses in sales experienced by the platform and retailer, the manufacturer lowers the wholesale price. The manufacturer consistently benefits from channel encroachment and a Pareto improvement region exists, allowing all supply chain participants to improve their profits. The model is extended to consider sequential decision-making and asymmetric substitution. In comparison, under sequential decision-making, the manufacturer tends to focus more on the competitive effects of channel encroachment, leading to a reduction in channel sales. However, this approach only enhances the manufacturer’s agency profit when the retailer’s substitution capability is relatively strong. The manufacturer faces greater competitive pressure from the retailer under asymmetric channel substitution. Although the manufacturer increases the wholesale price and adjusts sales across channels according to the competitive situation, its profits are always lower than in the symmetric substitution case. The presence of a Pareto improvement region in the extended model confirms the robustness of our findings.

To better support wildfire predictions and risk assessment, multiple fire danger rating indices (FDRIs) have been developed but their credibility in China remains obscure. Compared with the satellite fire observations, 13 FDRIs are evaluated for the historical (2003–2021) forest fire frequency in China from four different time scales: active seasons, trends, interannual variations (IAVs) and discrimination of fire/non-fire days (DFDs). Most FDRIs effectively capture the double active seasons over Southwest China and the dominant active season over Northeast and South China but fail over the other regions. FDRIs with cloud cover perform better in capturing climatological fire seasonality. All FDRIs fail to reproduce the significant decreasing trend of forest fires speculatively due to local fire management and discordant changes in meteorological elements. Most FDRIs have the advantages of the IAVs and DFDs over Southwest China but exhibit deficiencies over the other regions. FDRIs incorporating wind speed perform best in representing both IAVs and DFDs, indicating the indispensable effect of surface wind on the interannual/daily variation of fire danger. This study provides a credible reference for utilizing FDRIs in China, as well as offers insights for developing better regional FDRIs to represent different time-scale variations.

ContextUrban greenspace can significantly decrease the land surface temperature (LST). The spatial characteristics and vegetation composition of urban greenspace have a great influence on its cooling capacity.ObjectivesWe sought to distinguish the cooling effect by different spatial pattern factors of greenspace and by the interaction of these factors, which may be useful in understanding cooling effect and designing urban greenspace.MethodsBoth the greenspace derived from SPOT6 and LST retrieved from Landsat-8 images are employed to identify the dominant factors influencing LST and investigate the interaction between any two dominant factors in the Beijing metropolitan area.ResultsThe results indicate that the dominant spatial factors affecting LST vary by greenspace type, i.e., for grass, the number of patches (NP) and patch density (PD) have a significant effect on LST while for coniferous forest, the landscape shape index (LSI) is the dominant spatial factor. And the NP and percentage of landscape are the dominant spatial factors for broad-leaved forest and mixed forest, respectively. The interaction of any two dominant factors is larger than their individual effects, and the interaction between the NP and LSI of greenspace is not as strong as the interaction between the NP and PD.ConclusionsUrban greenspace design and planning need to consider the spatial pattern of different types of greenspace. On this basis, we proposed a pattern effective in cooling LST in cities climatically similar to Beijing, which could provide theoretical reference for the design and planning of urban greenspace.

The Tropical Rainfall Measurement Mission (TRMM) satellite is the first to be designed to measure precipitation, and its precipitation products have been assessed in a variety of ways. Data for its post-real-time level 2 product (3B42) performed well in terms of the precipitation amount at the monthly scale because they were corrected by a precipitation dataset that was gauged every month. However, the performance of this dataset in terms of precipitation frequency and intensity is still not ideal. To this end, TRMM 3B42 products were evaluated using precipitation data from 747 meteorological stations over mainland China in this study. The Pearson’s correlation coefficient (CC), relative bias (RB), and relative error (RE) were used to assess the capability of TRMM products in terms of estimating the frequency, intensity, and amount of precipitation for different categories of precipitation during nighttime and daytime in a multiscale analysis (including interannual variation, seasonal cycles, and spatial distribution). Our results showed the following: (1) The 3B42 products reproduced interannual trends of the frequency and amount of precipitation (except for trace precipitation) with an average correlation coefficient of 0.84. (2) 3B42 performed well at calculating the annual and monthly precipitation amount, but performed poorly for frequency and even worse for intensity. The biases in these two properties canceled out, however, which led to a better estimate of the amount. (3) 3B42 represented the distribution of the subdaily amount of precipitation over a majority of the regions in the east, but did not perform well on the Tibetan Plateau or in northwest China. The performance of 3B42, as detailed in this study, can serve as valuable guidance to data users and algorithm developers.

Growth of high-elevation forests is generally temperature-limited and thus sensitive to warming. The Tibetan Plateau has experienced fast warming rates associated with decreased summer monsoon rainfall over the last century. However, whether such warming and monsoon-induced drought could offset a potential warming-driven enhancement of forest growth has not been examined. Here, we have compiled high-elevation forest growth data at 40 sites over the monsoonal Tibetan Plateau (MTP), and combined them in a high-elevation forest growth index (HEFGI) spanning 1567-2010. Tree growth in this region was significantly and positively correlated with July-October minimum temperatures during 1950-2010 (R2 = 0.53 P < 0.001), and insignificantly coherent with soil moisture and precipitation. The HEFGI of MTP reaches its highest values from the 2000s onwards. This result suggests that the mean HEFGI of MTP has not been negatively affected by the current drying trend and responded positively to increased temperatures.

Lightning-ignited fire is sensitive to climatic change and responsible for large fires in boreal forests. In addition to global-warming caused fire increase, large-scale climate oscillations have significantly contributed to fire variability. However, the leading climate oscillation driving lightning-ignited fire and the mechanisms connecting regional and large-scale climate in the boreal forest of Northeast China, the most fire-prone biome of China, are still unclear. By compositing fire, climate, and atmospheric data, we found that the previous Atlantic Multidecadal Oscillation (AMO) was significantly coherent with the May to August temperature-evapotranspiration variability and lightning-ignited fire occurrence. These connections were valid at both the interannual and multidecadal time scales. Different from previous viewpoints, we found no connection of fire occurrence with the El Niño-Southern Oscillation and Pacific Decadal Oscillation. A warm AMO was followed by high sea level pressure and geopotential height over the study region. We assume these atmospheric anomalies are associated with descending atmospheric motion, producing adiabatic warming and less precipitation on the land surface, both of which favour high fuel aridity and lightning ignition. Therefore, we believe that the winter AMO could be a promising predictor for lightning-ignited fire occurrences in the following summer.

We present a literature review on quality and operations management problems in food supply chains. In food industry, the quality of the food products declines over time and should be addressed in the supply chain operations management. Managing food supply chains with operations management methods not only generates economic benefit, but also contributes to environmental and social benefits. The literature on this topic has been burgeoning in the past few years. Since 2005, more than 100 articles have been published on this topic in major operations research and management science journals. In this literature review, we concentrate on the quantitative models in this research field and classify the related articles into four categories, that is, storage problems, distribution problems, marketing problems, and food traceability and safety problems. We hope that this review serves as a reference for interested researchers and a starting point for those who wish to explore it further.

To systematically elucidate the chronological patterns of embryonic development and morphological changes in the larval and juvenile stages of Silurus glanis, and provide fundamental biological insights into this species, in this study, fertilized eggs were obtained through artificial spawning induction technology. After removing adhesiveness from fertilized eggs using trypsin, a detailed developmental study was conducted. The study systematically analyzed the chronological sequence of embryonic development and the morphological change patterns of larval and juvenile fish. The results showed the following: The fertilized eggs of S. glanis are yellow, spherical, and sticky, and the stickiness allows eggs to attach to spawning substrates, enhancing hatching success. The egg diameter after water absorption was (2.88 ± 0.13) mm. The embryonic development took 47 h and 55 min, with a total accumulated temperature of 1245.56 h degrees Celsius, the developmental process includes seven stages and twenty-six periods, namely the zygophase stage, cleavage stage, blastula stage, gastrula stage, neurula stage, organogenesis stage, and hatching stage. At a temperature of (26.0 ± 0.9) °C, the hatched individuals went through the pre-yolk sac larval stage, late larval stage, juvenile fry stage, and juvenile stage. In the pre-yolk sac larval stage, otoliths appeared in the bilateral otic vesicles, a pair of barbel primordia emerged under the mandible, a short and thin straight intestine formed in the abdominal cavity, and the oral fissure first appeared. In the late larval stage, the fin rays were initially formed, the intestine became thicker and longer, the oral fissure, anus, and cloaca were formed, and the larvae could float and start feeding on exogenous food. In the juvenile fry stage, the differentiation of various organs was basically complete, the nostrils became larger, and both the anal fin and caudal fin had dark black markings. In the juvenile stage, the maxillary barbels elongated, the mucus layer thickened on the body and back, the abdomen is light white, and it had the external morphological characteristics of an adult fish. By measuring and calculating the total length, body length, body height, and head length of S. glanis larvae and juveniles (0–40 days), the results showed that the growth characteristics conformed to the following fish growth formula: TL = 0.0141x2 + 0.8096x + 8.2421 (R2 = 0.9916), where x denotes days after hatching. This study has preliminarily mastered the chronological patterns of the embryonic development, growth, and formation of the morphological characteristics in larval and juvenile S. glanis, providing scientific data and laying a theoretical foundation for the division of early developmental stages, reproduction, hatching, and fry cultivation.

Summer temperature dominates environmental degradation and water resource availability on the Tibetan Plateau (TP), affecting glacier melting, permafrost degradation, desertification and streamflow, etc. Extending summer temperature records back before the instrumental period is fundamentally important for climatic and environmental studies over long timescales. By pooling 39 tree-ring width records from the TP that show significant (P < 0.05) correlations with the summer (June-August) minimum temperature (MinT) of the nearest grid point, we reconstructed a 366-year summer MinT record for the southern TP (STP). Reconstructed and instrumental data are highly coherent within the 1950-2010 calibration interval (R2 = 0.50, P < 0.001). The reconstruction captures major temperature anomalies, such as the coldest interval of the 1810s-1820s and unprecedented warming since the 1990s. We found that the linear trends of the instrumental and reconstructed STP summer MinTs are significantly lower than those for the larger Eurasian continent over the periods 1950-2010 and 1850-1950, respectively. The lower warming rate of STP summer MinT since 1850 could be due to increased evaporative cooling, and the absence of warming enhancement factors such as snow-albedo and energy-absorbing aerosols in summer. The reconstructed summer warming rate for the STP appears to be significantly overestimated by the ensemble mean of the Coupled Model Intercomparison Project Phase 5 (CMIP5) historical simulation.