Strong positive direct impact of soil moisture on the growth of central asian grasslands.

As the issue of global climate change becomes increasingly prominent, the grassland ecosystems in Central Asia are facing severe challenges posed by the impacts of climate change. However, the dominant factors, impact pathways, and cumulative and time-lagged effects of climate factors on various grassland indices remain to be explored. This study selected data from 1988 to 2019, including Fractional Vegetation Cover (FVC), Leaf Area Index (LAI), Net Primary Productivity (NPP), and Vegetation Optical Depth (VOD), to characterize grassland coverage, greenness, biomass accumulation, and water content features. Utilizing multiple linear regression, path analysis, and correlation analysis, this study investigated the dominant effects, direct impacts, indirect influences, and cumulative and time-lagged effects of climate factors on various grassland indices from spatial and climatic zone perspectives. The research findings indicate that over time, the grassland FVC and NPP exhibited increasing trends, while the LAI and VOD showed decreasing trends. Grassland indices are primarily influenced by precipitation and soil moisture (SM). The direct impact of SM on grassland indices was higher than precipitation. Vapour pressure deficit (VPD) has a direct negative impact on grassland indices. Grassland indices are subject to positive indirect effects from precipitation via SM and negative indirect effects from VPD via SM. Precipitation and SM mainly exhibited no cumulative and time-lagged effects on the impact of grassland VOD. VPD primarily demonstrated cumulative and time-lagged effects on grassland indices. The research findings offer valuable insights for conserving grassland ecosystems in Central Asia, as well as for shaping socioeconomic strategies and formulating climate policies.

Environmental, climatic, socio-economic factors and non-pharmacological interventions: A comprehensive four-domain risk assessment of COVID-19 hospitalization and death in Northern Italy.

INTRODUCTION: Up to now, studies on environmental, climatic, socio-economic factors, and non-pharmacological interventions (NPI) show diverse associations, often contrasting, with COVID-19 spread or severity. Most studies used large-scale, aggregated data, with limited adjustment for individual factors, most of them focused on viral spread than severe outcomes. Moreover, evidence simultaneously evaluating variables belonging to different exposure domains is scarce, and none analysing their collective impact on an individual level. METHODS: Our population-based retrospective cohort study aimed to assess the comprehensive role played by exposure variables belonging to four different domains, environmental, climatic, socio-economic, and non-pharmacological interventions (NPI), on individual COVID-19-related risk of hospitalization and death, analysing data from all patients (no. 68472) tested positive to a SARS-CoV-2 swab in Modena Province (Northern Italy) between February 2020 and August 2021. Using adjusted Cox proportional hazard models, we estimated the risk of severe COVID-19 outcomes, investigating dose-response relationships through restricted cubic spline modelling for hazard ratios. RESULTS: Several significant associations emerged: long-term exposure to air pollutants (NO2, PM10, PM2.5) was linked to hospitalization risk in a complex way and showed an increased risk for death; while humidity was inversely associated; temperature showed a U-shaped risk; wind speed showed a linear association with both outcomes. Precipitation increased hospitalization risk but decreased mortality. Socio-economic and NPI indices showed clear linear associations, respectively negative and positive, with both outcomes. CONCLUSIONS: Our findings offer insights for evidence-based policy decisions, improving precision healthcare practices, and safeguarding public health in future pandemics. Refinement of pandemic response plans by healthcare authorities could benefit significantly.

The Prognostic Effect of Air Pollution in Patients Presenting to the Emergency Department with Carbon Monoxide Poisoning.

OBJECTIVE: Weather conditions such as low air temperatures, low barometric pressure, and low wind speed have been linked to more cases of carbon monoxide (CO) poisoning. However, limited literature exists regarding the impact of air pollution. This study aims to investigate the relationship between outdoor air pollution and CO poisoning in 2 distinct cities in Turkey. METHODS: A prospective study was conducted at 2 tertiary hospitals, recording demographic data, presenting complaints, vital signs, blood gas and laboratory parameters, carboxyhemoglobin (COHb) levels, meteorological parameters, and pollutant parameters. Complications and outcomes were also documented. RESULTS: The study included 83 patients (Group 1 = 44, Group 2 = 39). The air quality index (AQI) in Group 2 (61.7 ± 27.7) (moderate AQI) was statistically significantly higher (dirtier AQI) than that in Group 1 (47.3 ± 26.4) (good AQI) (P = 0.018). The AQI was identified as an independent predictor for forecasting the need for hospitalization (OR = 1.192, 95% CI: 1.036 - 1.372, P = 0.014) and predicting the risk of developing cardiac complications (OR: 1.060, 95% CI: 1.017 - 1.104, P = 0.005). CONCLUSIONS: The AQI, derived from the calculation of 6 primary air pollutants, can effectively predict the likelihood of hospitalization and cardiac involvement in patients presenting to the emergency department with CO poisoning.

Chemotaxonomic variation of volatile components in Zanthoxylum Bungeanum peel and effects of climate on volatile components.

BACKGROUND: Zanthoxylum bungeanum Maxim. is widely distributed across China, and the aroma of its peel is primarily determined by its volatile components. In this study, we analyzed the characteristics of volatile components in Z. bungeanum peels from different regions and investigated their correlation with climatic factors. RESULTS: The results identified 126 compounds in Z. bungeanum, with 27 compounds exhibiting distinct odor characteristics. Linalool was the most abundant, with an average relative content of 21.664%. The volatile oil of Z. bungeanum predominantly features spicy, floral, citrus, and mint aromas. The classification results indicated a significant difference in elevation at the ZB10 collection points in Shaanxi Province compared to other groups. Temperature, average annual precipitation, and wind speed were crucial factors influencing the accumulation of volatile components. CONCLUSIONS: This study is beneficial for enhancing the quality of Z. bungeanum, expanding the understanding of how climatic factors influence the accumulation of volatile substances, and promoting agricultural practices in regions with similar climatic conditions.

Phenotypic variation in hypocotyl elongation among elite sand rice (Agriophyllum squarrosum) lines.

Sand rice (Agriophyllum squarrosum), widely distributed in Central Arid Asia and prevalent in the sand dunes of northern China, presents a promising potential as a climate-resilient crop. The plasticity of hypocotyl growth is the key trait for sand rice to cope with wind erosion and sand burial, ensure seedling emergence, and determine plant architecture. In this study, we assessed the overall hypocotyl phenotype of six sand rice elite lines, which were collected from different regions of northern China, and selected by our group over past decade through common garden trials. Significant phenotypic variations were observed in thousand-seed weight (TSW), seedling emergence percentage, hypocotyl length and diameter, and seedling fresh weight among the lines. The elite line Aerxiang (AEX) exhibited excellent agronomic performance with superior and synchronous emergence, and high survival percentage, distinguishing itself as a prime candidate for further large-scale cultivation. Contrastingly, the lines from the arid regions showed markedly lower performance. Partial Least Squares Path Modeling (PLSPM) was used to assess the impact of seed provenance climate factors, including annual mean temperature (AMT) and annual mean precipitation (AMP), on trait variability among lines. The findings indicate a significant correlation between climate factors and hypocotyl length, highlighting the intricate adaptation of sand rice to local climate. The comprehensive understanding of the mechanisms behind phenotypic variations offers valuable insights for sand rice de novo domestication and innovative germplasm resources, and lays the foundation for ecological restoration in sandy areas.

The potential habitat of Angelica dahurica in China under climate change scenario predicted by Maxent model.

Since the 20th century, global climate has been recognized as the most important environmental factor affecting the distribution of plants. Angelica dahurica (A. dahurica) has been in great demand as a medicinal herb and flavoring, but the lack of seed sources has hindered its development. In this study, we utilized the Maxent model combined with Geographic Information System (GIS) to predict the potential habitat of A. dahurica in China based on its geographical distribution and 22 environmental factors. This prediction will serve as a valuable reference for the utilization and conservation of A. dahurica resources.The results indicated that: (1) the Maxent model exhibited high accuracy in predicting the potential habitat area of A. dahurica, with a mean value of the area under the ROC curve (AUC) at 0.879 and a TSS value above 0.6; (2) The five environmental variables with significant effects were bio6 (Min temperature of the coldest month), bio12 (Annual Precipitation), bio17 (Precipitation of Driest Quarter), elevation, and slope, contributing to a cumulative total of 89.6%. Suitable habitats for A. dahurica were identified in provinces such as Yunnan, Guizhou, Guangxi, Sichuan, Hunan, and others. The total area of suitable habitat was projected to increase, with expansion primarily in middle and high latitudes, while areas of decrease were concentrated in lower latitudes. Under future climate change scenarios, the centers of mass of suitable areas for A. dahurica were predicted to shift towards higher latitudes in the 2050s and 2090s, particularly towards the North China Plain and Northeast Plain. Overall, it holds great significance to utilize the Maxent model to predict the development and utilization of A. dahurica germplasm resources in the context of climate change.

Modeling the impacts of extreme climate scenarios on soil acidity (pH and exchangeable aluminum) in Abbay River Basin, Ethiopia.

The Abbay River Basin faces the looming threat of extreme climate events, including prolonged droughts and erratic rainfall patterns, which can significantly affect soil health and fertility. This study aimed to explore the influence of extreme climate conditions on soil pH and exchangeable aluminum, aiming to promote sustainable agricultural practices in Ethiopia. The Africa Soil Information Service (ASIS) provided datasets on soil pH and exchangeable aluminum. The European Copernicus Climate Change Data Store was used to download historical and future datasets of extreme climatic indices from 1980 to 2010 and 2015-2050, respectively. The Coupled Model Intercomparison Project Phase 6 model ensemble was used to predict future climate impacts under three shared socioeconomic scenarios: SSP1-2.6, SSP2-4.3, and SSP5-8.5. Data extraction, quality control, and clustering were conducted before analysis, and the model was validated for its accuracy and reliability in predicting soil parameter changes. An artificial neural network model was utilized to predict the effects of extreme climate indices on soil pH and exchangeable aluminum concentrations. The model was designed to accurately and reliably predict changes in soil parameters. This study compared the changes in soil pH and aluminum concentrations using paired t tests. The model's diagnostic results indicated a significant impact of extreme climate scenarios on soil pH and exchangeable aluminum. Extreme climate factors such as heavy precipitation and cooler night time temperatures significantly contribute to soil acidification and an increase in aluminum concentration. Under the SSP1-2.6 and SSP2-4.5 emission scenarios, soil pH levels are expected to increase by 8.38 % and 3.79 %, respectively. These changes in soil pH are expected to have significant impacts on the exchangeable aluminum content in the soil, with increases of 37 % and 5.38 %, respectively, under the same emission scenarios. However, the SSP5.8 scenario predicted a 45 % increase in exchangeable aluminum and a 9.36 % decrease in soil pH. Therefore, this study significantly enhances our understanding of the influence of climate change on soil health. The development of strategies to mitigate climate change impacts on agriculture in the region must consider the effects of extreme climate indices.

Climate factors determine large-scale spatial patterns of stomatal index in Chinese herbaceous and woody dicotyledonous plants.

The stomatal index (SI, %) and its response to climate factors (temperature and precipitation) can help our understanding of terrestrial carbon and water cycling and plant adaptation in the ecosystem, however, consensus has not yet been reached in this regard. In this study, we compiled an extensive dataset from the Chinese flora to investigate the response of SI to environmental change, including 891 herbaceous and woody species from 188 published papers. The results showed that mean values of the adaxial SI and abaxial SI for all species were 14.06 and 19.22, respectively, and the ratio of adaxial to abaxial SI was 0.84. For the adaxial SI, abaxial SI, and the ratio of adaxial to abaxial SI, the range of these values varied between 0.05-43.67, 0.01-48.17, and 0.03-4.31, respectively. Compared with woody plants, herbaceous plants showed higher values in both adaxial and abaxial SI. In terms of the impact of climate factors, the abaxial SI of herbaceous plants changed slower than the adaxial SI, while woody plants showed the opposite trend. Threshold effects of increased temperature and precipitation on SI were observed, indicating that SI responded differently to changes in climate factors at different levels. Climate factors play a crucial role in driving the adaxial SI than abaxial SI. Our findings highlight the significant challenges posed by divergent responses of SI in forecasting future water and carbon cycles associated with climatic and environmental change.

Evolutionary history shapes variation of wood density of tree species across the world.

The effect of evolutionary history on wood density variation may play an important role in shaping variation in wood density, but this has largely not been tested. Using a comprehensive global dataset including 27,297 measurements of wood density from 2621 tree species worldwide, we test the hypothesis that the legacy of evolutionary history plays an important role in driving the variation of wood density among tree species. We assessed phylogenetic signal in different taxonomic (e.g., angiosperms and gymnosperms) and ecological (e.g., tropical, temperate, and boreal) groups of tree species, explored the biogeographical and phylogenetic patterns of wood density, and quantified the relative importance of current environmental factors (e.g., climatic and soil variables) and evolutionary history (i.e., phylogenetic relatedness among species and lineages) in driving global wood density variation. We found that wood density displayed a significant phylogenetic signal. Wood density differed among different biomes and climatic zones, with higher mean values of wood density in relatively drier regions (highest in subtropical desert). Our study revealed that at a global scale, for angiosperms and gymnosperms combined, phylogeny and species (representing the variance explained by taxonomy and not direct explained by long-term evolution process) explained 84.3% and 7.7% of total wood density variation, respectively, whereas current environment explained 2.7% of total wood density variation when phylogeny and species were taken into account. When angiosperms and gymnosperms were considered separately, the three proportions of explained variation are, respectively, 84.2%, 7.5% and 6.7% for angiosperms, and 45.7%, 21.3% and 18.6% for gymnosperms. Our study shows that evolutionary history outpaced current environmental factors in shaping global variation in wood density.

Climate change impacts on oyster aquaculture - Part I: Identification of key factors.

Oysters are enriched with high-quality protein and are widely known for their exquisite taste. The production of oysters plays an important role in the local economies of coastal communities in many countries, including Atlantic Canada, because of their high economic value. However, because of the changing climatic conditions in recent years, oyster aquaculture faces potentially negative impacts, such as increasing water acidification, rising water temperatures, high salinity, invasive species, algal blooms, and other environmental factors. Although a few isolated effects of climate change on oyster aquaculture have been reported in recent years, it is not well understood how climate change will affect oyster aquaculture from a systematic perspective. In the first part of this study, we present a systematic review of the impacts of climate change and some key environmental factors affecting oyster production on a global scale. The study also identifies knowledge gaps and challenges. In addition, we present key research directions that will facilitate future investigations.

Climate Factors Influence Above- and Belowground Biomass Allocations in Alpine Meadows and Desert Steppes through Alterations in Soil Nutrient Availability.

Biomass is a direct reflection of community productivity, and the allocation of aboveground and belowground biomass is a survival strategy formed by the long-term adaptation of plants to environmental changes. However, under global changes, the patterns of aboveground-belowground biomass allocations and their controlling factors in different types of grasslands are still unclear. Based on the biomass data of 182 grasslands, including 17 alpine meadows (AMs) and 21 desert steppes (DSs), this study investigates the spatial distribution of the belowground biomass allocation proportion (BGBP) in different types of grasslands and their main controlling factors. The research results show that the BGBP of AMs is significantly higher than that of DSs (p < 0.05). The BGBP of AMs significantly decreases with increasing mean annual temperature (MAT) and mean annual precipitation (MAP) (p < 0.05), while it significantly increases with increasing soil nitrogen content (N), soil phosphorus content (P), and soil pH (p < 0.05). The BGBP of DSs significantly decreases with increasing MAP (p < 0.05), while it significantly increases with increasing soil phosphorus content (P) and soil pH (p < 0.05). The random forest model indicates that soil pH is the most important factor affecting the BGBP of both AMs and DSs. Climate-related factors were identified as key drivers shaping the spatial distribution patterns of BGBP by exerting an influence on soil nutrient availability. Climate and soil factors exert influences not only on grassland biomass allocation directly, but also indirectly by impacting the availability of soil nutrients.

Chemical Composition Variation in Essential Oil and Their Correlation with Climate Factors in Chinese Prickly Ash Peels (Zanthoxylum armatum DC.) from Different Habitats.

Essential oils are secondary metabolites in plants with a variety of biological activities. The flavor and quality of Zanthoxylum armatum DC. are mainly determined by the essential oil components in the Chinese prickly ash peels. In this study, the correlation between climate change in different regions and the content of essential oils of Z. armatum was investigated using gas chromatography-mass spectrometry (GC/MS) and multivariate statistical analysis. The Z1-24 refers to 24 batches of samples from different habitats. A total of 145 essential oils were detected in 24 batches of samples, with the highest number of terpene species and the highest content of alcohol. The relative odor activity (ROAV) values identified nine main flavor compounds affecting the odor of Z. armatum. Linalool, decanal, and d-limonene were the most critical main flavor compounds, giving Z. armatum a spicy, floral, oily, and fruity odor. The results of hierarchical cluster analysis (HCA) and principal component analysis (PCA) classified Z5 into a separate group, Z2 and Z7 were clustered into one group, and the rest of the samples were classified into another group. Correlation analysis and path analysis showed that temperature and precipitation were the main climatic factors affecting essential oils. Comparisons can be made with other plants in the genus Zanthoxylum to analyze differences in essential oil type and content. This study contributes to the identification of Z. armatum quality, promotes the accumulation of theories on the effects of climatic factors on essential oils, and enriches the site selection and breeding of Z. armatum under similar climatic conditions.

Grazing alters the soil nematode communities in grasslands: A meta-analysis.

Grazing causes great disturbances in grassland ecosystems and may change the abundance, diversity, and ecological function of soil biota. Because of their important role in nutrient cycling and as good environmental indicators, nematodes are very representative soil organisms. However, the mechanisms by which grazing intensity, livestock type, duration, and environmental factors (e.g., climate and edaphic factors) affect soil nematodes remain poorly understood. In this study, we collected 1964 paired observations all over the world from 53 studies to clarify the grazing response patterns of soil nematodes and their potential mechanisms. Overall, grazing significantly decreased the abundance of bacterial-feeding (BF) nematodes (-16.54%) and omnivorous-predatory (OP) nematodes (-36.81%), and decreased nematode community diversity indices (Shannon-Weiner index: -4.33%, evenness index: -9.22%, species richness: -5.35%), but had no effect on ecological indices under a global regional scale. The response of soil nematodes to grazing varied by grazing intensity, animals, and duration. Heavy grazing decreased OP nematode abundance, but had no effect on the abundance of other trophic groups, or on diversity or ecological indices. Grazing by small animals had stronger effects than that by large animals and mixed-size animals on BF, fungal-feeding (FF), plant-feeding (PF) and OP nematodes, the Shannon-Wiener index, and the species richness index. The abundance of FF and OP nematodes influenced significantly under short-term grazing. The evenness index decreased significantly under long-term grazing (>10 years). Climate and edaphic factors impacted the effects of grazing on nematode abundance, diversity, and ecological indices. When resources (i.e., rain, heat, and soil nutrients) were abundant, the negative effects of grazing on nematodes were reduced; under sufficiently abundant resources, grazing even had positive effects on soil nematode communities. Thus, the influence of grazing on soil nematode communities is resource-dependent. Our study provides decision makers with grazing strategies based on the resource abundance. Resource-poor areas should have less grazing, while resource-rich areas should have more grazing to conserve soil biodiversity and maintain soil health.

Identification of Important Factors When Measuring School Climate: Latent Construct Validation and Exploration.

BACKGROUND: Researchers regularly must decide what information is necessary to understand school climate and how to include climate in a study. For example, which factors and/or scales should be used, is using just 1 scale for school climate sufficient, and to what extent does the selection of a single scale influence the research findings? AIMS: Understanding what factors to consider and which available scales to review will assist those interested in measuring school climate. METHODS: This study explores 8 validated scales related to school climate. Data used are from a previous study (Social and Character Development cooperative agreement funded by IES #R305L030072 and #R305A080253) that looked at Positive Action, a social emotional and character development program for elementary-, middle-, and high-school students. RESULTS AND CONCLUSION: Scale correlations and factor analyses show how these scales work together to measure overall middle school climate.

Decision tree ensemble with Bayesian optimization to predict the spatial dynamics of chlorophyll-a concentration: A case study in Bay of Bengal.

An accurate prediction of the spatial distribution of phytoplankton biomass, as represented by Chlorophyll-a (CHL-a) concentrations, is important for assessing ecological conditions in the marine environment. This study developed a hyperparameter-optimized decision tree-based machine learning (ML) models to predict the geographical distribution of marine phytoplankton CHL-a in the Bay of Bengal. To predict CHL-a over a large spatial extent, satellite-derived remotely sensed data of ocean color features (CHL-a, colored dissolved organic matter, photosynthetically active radiation, particulate organic carbon) and climatic factors (nighttime sea surface temperature, surface absorbed longwave radiation, sea level pressure) from 2003 to 2022 are used to train and test the models. Results obtained from this study have shown the highest concentrations of CHL-a occurred near the Bay's coastal belts and river estuaries. Analysis revealed that aside from photosynthetically active radiation, organic components exhibited a stronger positive relationship with CHL-a than climatic features, which are correlated negatively. Results showed the chosen decision tree methods to all possess higher R2 and lower root mean square error (RMSE) errors. Furthermore, XGBoost outperforms all other models in predicting the geographic distribution of CHL-a. To assess the model efficacy on seasonal basis, a best performing XGBoost model was validated in the Bay of Bengal region which has shown a good performance in predicting the spatial distribution of Chl-a as well as the pixel values during the summer, winter and monsoon seasons. This study provides the best ML model to researchers for predicting CHL-a in the Bay of Bengal. Further it helps to improve our knowledge of CHL-a spatial dynamics and assist in monitoring marine resources in the Bay of Bengal. It worth noting that the water quality in the Indian Ocean is very dynamic in nature, therefore, additional efforts are needed to test the efficacy of this study model over different seasons and spatial gradients.

Spatio-temporal distribution and contributing factors of tegumentary and visceral leishmaniasis: A comparative study in Bahia, Brazil.

Tegumentary (TL) and visceral (VL) leishmaniasis are neglected zoonotic diseases in Brazil, caused by different parasites and transmitted by various vector species. This study investigated and compared spatio-temporal patterns of TL and VL from 2007 to 2020 in the state of Bahia, Brazil, and their correlations with extrinsic factors. The results showed that the total number of cases of both TL and VL were decreasing. The number of municipalities with reported cases reduced for TL over time but remained almost unchanged for VL. There were few municipalities with reported both diseases. Statistical analysis showed that local TL incidence was associated positively with natural forest. Local VL incidence was associated positively with Cerrado (Brazilian savannah) vegetation. This study identified different patterns of occurrence of VL and TL and the risk areas that could be prioritized for epidemiological surveillance.

Differentiated responses of the phyllosphere bacterial community of the yellowhorn tree to precipitation and temperature regimes across Northern China.

Introduction: As an ephemeral and oligotrophic environment, the phyllosphere harbors many highly diverse microorganisms. Importantly, it is known that their colonization of plant leaf surfaces is considerably influenced by a few abiotic factors related to climatic conditions. Yet how the dynamics of phyllosphere bacterial community assembly are shaped by detailed climatological elements, such as various bioclimatic variables, remains poorly understood. Methods: Using high-throughput 16S rRNA gene amplicon sequencing technology, we analyzed the bacterial communities inhabiting the leaf surfaces of an oilseed tree, yellowhorn (Xanthoceras sorbifolium), grown at four sites (Yinchuan, Otogqianqi, Tongliao, and Zhangwu) whose climatic status differs in northern China. Results and Discussion: We found that the yellowhorn phyllosphere's bacterial community was generally dominated by four phyla: Proteobacteria, Firmicutes, Actinobacteria, and Bacteroidetes. Nevertheless, bacterial community composition differed significantly among the four sampled site regions, indicating the possible impact of climatological factors upon the phyllosphere microbiome. Interestingly, we also noted that the α-diversities of phyllosphere microbiota showed strong positive or negative correlation with 13 bioclimatic factors (including 7 precipitation factors and 6 temperature factors). Furthermore, the relative abundances of 55 amplicon sequence variants (ASVs), including three ASVs representing two keystone taxa (the genera Curtobacterium and Streptomyces), exhibited significant yet contrary responses to the precipitation and temperature climatic variables. That pattern was consistent with all ASVs' trends of possessing opposite correlations to those two parameter classes. In addition, the total number of links and nodes, which conveys community network complexity, increased with rising values of most temperature variables. Besides that, remarkably positive relevance was found between average clustering coefficient and most precipitation variables. Altogether, these results suggest the yellowhorn phyllosphere bacterial community is capable of responding to variation in rainfall and temperature regimes in distinctive ways.

Leaf phenotypic variation and its response to environmental factors in natural populations of Eucommia ulmoides.

BACKGROUND: Eucommia ulmoides leaves have high medicinal and economic value as a dual-purpose substance for medicine and food. Employing leaves from 13 natural populations of Eucommia ulmoides as research objects, this study reveals the variation patterns of intra-specific and inter-specific trait variation and explores the response of leaf characteristics to geographical and climatic changes, aiming to provide a scientific basis for the efficient utilization of leaf resources and the breeding of superior varieties. RESULTS: Descriptive statistical analysis and nested analysis of variance showed significant differences in 11 leaf traits of Eucommia ulmoides inter-populations and intra-populations, with an average coefficient of variation of 17.45%. The coefficient of variation for average leaf phenotypic traits is 20.77%, and the leaf phenotypic variation is mainly from the variation intra-populations. Principal component analysis reveals that the cumulative contribution rate of the top three principal components which mainly contributed to the phenotypic variation of Eucommia ulmoides leaves reached 74.98%, which could be sorted into size traits (34.57%), color traits (25.82%) and shape traits (14.58%). In addition, correlation analysis expresses there is a specific co-variation pattern among leaf traits, with a strong connection between shape, size, and color traits. Geographic and climatic distances are significantly correlated, and mantel test and correlation analysis indicate that leaf traits of Eucommia ulmoides are mainly influenced by altitude. With the increase of altitude, the leaves become smaller. Partial correlation analysis shows that after controlling climate factors, the correlation between some characters and geographical factors disappears significantly. Temperature and precipitation have a great influence on the variation of leaf phenotypic traits, and the larger the leaves are in areas with high temperature and heavy rainfall. CONCLUSIONS: These findings contribute to a further understanding of the leaf morphological characteristics of Eucommia ulmoides and the extent to which the environment influences leaf trait variation. They can provide a scientific basis for the protection and application of Eucommia ulmoides leaf resources in the future.

The impact of the synergistic effect of SO2 and PM2.5/PM10 on obstructive lung disease in subtropical Taiwan.

Background: Chronic Obstructive lung diseases (COPD) are complex conditions influenced by various environmental, lifestyle, and genetic factors. Ambient air pollution has been identified as a potential risk factor, causing 4.2 million deaths worldwide in 2016, accounting for 25% of all COPD-related deaths and 26% of all respiratory infection-related deaths. This study aims to evaluate the associations among chronic lung diseases, air pollution, and meteorological factors. Methods: This cross-sectional study obtained data from the Taiwan Biobank and Taiwan Air Quality Monitoring Database. We defined obstructive lung disease as patients with FEV1/FVC < 70%. Descriptive analysis between spirometry groups was performed using one-way ANOVA and the chi-square or Fisher's exact test. A generalized additive model (GAM) was used to evaluate the relationship between SO2 and PM2.5/PM10 through equations and splines fitting. Results: A total of 2,635 participants were enrolled. Regarding environmental factors, higher temperature, higher relative humidity, and lower rainfall were risk factors for obstructive lung disease. SO2 was positively correlated with PM10 and PM2.5, with correlation coefficients of 0.53 (p < 0.0001) and 0.52 (p < 0.0001), respectively. Additionally, SO2 modified the relative risk of obstructive impairment for both PM10 [ß coefficient (ß) = 0.01, p = 0.0052] and PM2.5 (ß = 0.01, p = 0.0155). Further analysis per standard deviation (per SD) increase revealed that SO2 also modified the relationship for both PM10 (ß = 0.11, p = 0.0052) and PM2.5 (ß = 0.09, p = 0.0155). Our GAM analysis showed a quadratic pattern for SO2 (per SD) and PM10 (per SD) in model 1, and a quadratic pattern for SO2 (per SD) in model 2. Moreover, our findings confirmed synergistic effects among temperature, SO2 and PM2.5/PM10, as demonstrated by the significant associations of bivariate (SO2 vs. PM10, SO2 vs. PM2.5) thin-plate smoothing splines in models 1 and 2 with obstructive impairment (p < 0.0001). Conclusion: Our study showed high temperature, humidity, and low rainfall increased the risk of obstructive lung disease. Synergistic effects were observed among temperature, SO2, and PM2.5/PM10. The impact of air pollutants on obstructive lung disease should consider these interactions.

Effects of geo-climate factors on phenotypic variation in cone and seed traits of Pinus yunnanensis.

Evaluating variations in reproductive traits and the response of the variations to geo-climate conditions are essential for understanding the persistence, evolution, and range dynamics of plant populations. However, there are insufficient studies to attempt to analyze the importance of geo-climate factors in explaining within- or among-population variation in reproductive traits. We examined 14 traits for 2671 cones of Pinus yunnanensis collected from nine populations in the mountains of Southwest China to characterize the patterns of phenotypic variation of traits and estimate environmental effects on these trait performances and trait variation. We found the contribution of intrapopulation variation to the overall variation was greater than the interpopulation variation and the larger coefficients of variation for the populations lying at the edge of northern and southern regions. Climatic variables are more important than geographical and tree size variables in their relationships to cone and seed traits. Populations in more humid and warmer climate expressed greater cone and seed weight and seed number but lower seed abortion rate, while the larger coefficients of variation in seed weight and number were detected in northern and southern marginal regions with drier or colder climate. Our study illustrates that intraspecific trait variation should be considered when examining plant species response to changing climate and suggests that the high variability rather than high quality of seed traits in the marginal regions with drier or colder climate might foster plant-population persistence in stressful conditions.