The Huangshui River, a vital tributary in the upper reaches of the Yellow River within the eastern Qinghai-Tibet Plateau, is home to the endemic black fly species S. qinghaiense. In this study, we conducted a systematic survey of the distribution of the species in the Huangshui River basin, revealing its predominant presence along the river\'s main stem. Based on four ecological niche models-MaxEnt with parameter optimization; GARP; BIOCLIM; and DOMAIN-we conduct a comparative analysis; evaluating the accuracy of AUC and Kappa values. Our findings indicate that optimizing parameters significantly improves the MaxEnt model\'s predictive accuracy by reducing complexity and overfitting. Furthermore, all four models exhibit higher accuracy compared to a random model, with MaxEnt demonstrating the highest AUC and Kappa values (0.9756 and 0.8118, respectively), showcasing significant superiority over the other models (p < 0.05). Evaluation of predictions from the four models elucidates that potential areas of S. qinghaiense in the Huangshui River basin are primarily concentrated in the central and southern areas, with precipitation exerting a predominant influence. Building upon these results, we utilized the MaxEnt model to forecast changes in suitable areas and distribution centers during the Last Interglacial (LIG), Mid-Holocene (MH), and future periods under three climate scenarios. The results indicate significantly smaller suitable areas during LIG and MH compared to the present, with the center of distribution shifting southeastward from the Qilian Mountains to the central part of the basin. In the future, suitable areas under different climate scenarios are expected to contract, with the center of distribution shifting southeastward. These findings provide important theoretical references for monitoring, early warning, and control measures for S. qinghaiense in the region, contributing to ecological health assessment.

Climate and human activities are the basic driving forces that control and influence the spatial distribution and change of vegetation. Using trend analysis, the Hurst index, correlation analysis, the Moran index, path analysis, residual analysis, and other methods, the effects of human activities and climate factors on vegetation change were analyzed. The results show that: (1) The research area\'s normalized difference vegetation index (NDVI) exhibited a substantial upward trend from 2001 to 2020, increasing at a rate of 0.003/a, and the vegetation cover was generally healthy. The generally constant NDVI region made up 78.45% of the entire area, and the grassland, cultivated land, and forest land showed the most visible NDVI aggregation features. (2) The Vegetation is mainly promoted by water and heat, particularly precipitation, have a major impact on plants, with the direct influence of precipitation on vegetation growth being much greater than the indirect effect through the temperature. (3) The trend of NDVI residuals showed obvious spatial variability, presenting a distribution characteristic of high in the south and low in the north. The results of this study can provide a basis for the scientific layout of ecological protection and restoration projects in the Yinshanbeilu area.

BACKGROUND: Environmental factors difference is the key factor for the difference in the production, transformation and accumulation of effective components in plants. UPLC-MS/MS and multivariate statistical methods were applied to describe the region difference of amides compounds in Chinese prickly ash peels from different regions and their correlation with climatic factors and soil factors.
RESULTS: Amides compounds contents were significantly higher in high altitude areas, with obvious altitude change trend. Two ecotypes were classified based on the amides compounds contents, one was the high altitude-cool type from Qinghai, Gansu, Sichuan and western Shaanxi province, and the other one was low altitude-warm type from eastern Shaanxi, Shanxi, Henan, Hebei and Shandong province. Amides compounds content were negatively correlated with annual mean temperature, max temperature of warmest month, mean temperature of wettest quarter and mean temperature of warmest quarter (P < 0.01). Except for hydroxy-γ-sanshool and ZP-amide A, the residual amides contents were significantly positively correlated with organic carbon, available nitrogen, phosphorus and potassium in soil and negatively correlated with soil bulk density. Low temperature, low precipitation and high organic carbon in soil were conducive to amides accumulation.
CONCLUSIONS: This study aided in site specific exploration of high amides contents yielding samples, enriched the environment factors effects on amides compounds, and provided scientific foundation for the improvement of Chinese prickly ash peels quality and the location of high-quality production areas.

The near-surface lapse rate reflects the atmospheric stability above the surface. Lapse rates calculated from land surface temperature (γTs) and near-surface air temperature (γTa) have been widely used. However, γTs and γTa have different sensitivity to local surface energy balance and large-scale energy transport and therefore they may have diverse spatial and temporal variability, which has not been clearly illustrated in existing studies. In this study, we calculated and compared γTa and γTs at ~ 2200 stations over China from 1961 to 2014. This study finds that γTa and γTs have a similar multiyear national average (0.53 °C/100 m) and seasonal cycle. Nevertheless, γTs shows steeper multiyear average than γTa at high latitudes, and γTs in summer is steeper than γTa, especially in Northwest China. The North China shows the shallowest γTa and γTs, then inhibiting the vertical diffusion of air pollutants and further reducing the lapse rates due to accumulation of pollutants. Moreover, the long-term trend signs for γTa and γTs are opposite in northern China. However, the trends in γTa and γTs are both negative in Southwest China and positive in Southeast China. Surface incident solar radiation, surface downward longwave radiation and precipitant frequency jointly can account for 80% and 75% of the long-term trends in γTa and γTs in China, respectively, which provides an explanation of trends of γTa and γTs from perspective of surface energy balance.

Under the variant climate conditions in the transitional regions between tropics and subtropics, the impacts of climate factors on influenza subtypes have rarely been evaluated. With the available influenza A (Flu-A) and influenza B (Flu-B) outbreak data in Shenzhen, China, which is an excellent example of a transitional marine climate, the associations of multiple climate variables with these outbreaks were explored in this study. Daily laboratory-confirmed influenza virus and climate data were collected from 2009 to 2015. Potential impacts of daily mean/maximum/minimum temperatures (T/Tmax/Tmin), relative humidity (RH), wind velocity (V), and diurnal temperature range (DTR) were analyzed using the distributed lag nonlinear model (DLNM) and generalized additive model (GAM). Under its local climate partitions, Flu-A mainly prevailed in summer months (May to June), and a second peak appeared in early winter (December to January). Flu-B outbreaks usually occurred in transitional seasons, especially in autumn. Although low temperature caused an instant increase in both Flu-A and Flu-B risks, its effect could persist for up to 10 days for Flu-B and peak at 17 C (relative risk (RR) = 14.16, 95% CI: 7.46-26.88). For both subtypes, moderate-high temperature (28 C) had a significant but delayed effect on influenza, especially for Flu-A (RR = 26.20, 95% CI: 13.22-51.20). The Flu-A virus was sensitive to RH higher than 76%, while higher Flu-B risks were observed at both low (< 65%) and high (> 83%) humidity. Flu-A was active for a short term after exposure to large DTR (e.g., DTR = 10 C, RR = 12.45, 95% CI: 6.50-23.87), whereas Flu-B mainly circulated under stable temperatures. Although the overall wind speed in Shenzhen was low, moderate wind (2-3 m/s) was found to favor the outbreaks of both subtypes. This study revealed the thresholds of various climatic variables promoting influenza outbreaks, as well as the distinctions between the flu subtypes. These data can be helpful in predicting seasonal influenza outbreaks and minimizing the impacts, based on integrated forecast systems coupled with short-term climate models.

Climate change is projected to affect the hydrological cycles in China, while the effects are expected to vary spatiotemporally. Understanding the variations in water security conditions and their sensitivity to climatic variables is crucial for assessing regional ecosystem responses to climate change. In the present study, we estimated the water yield capacity, an important indicator of water security in North China (NC), at a spatial resolution of 1 km during the last two decades based on the Budyko framework and quantified the sensitivity of water yield change to climate change among different vegetation types. The results showed that the performances of the Budyko framework were reliable both at the pixel scale and across large watersheds. The annual water yield in North China was estimated to be 7.61 ± 2.67 ∗ 1010 m3/yr, with an average mean water yield (MWY) of 49.51 ± 17.49 mm/yr. The spatial pattern of mean water yield change (MWYC) exhibited high heterogeneity; 46% of the study region was dominated by an increasing trend, while 9.84% was statistically significant (P < 0.05). Compared with temperature, the water yield capacity was more sensitive to precipitation variation. A consistent trend of variation was found in cropland between water yield and precipitation, while negative sensitivity coefficients were found in natural vegetation types. The variation in sensitivity coefficients (Swyp) in natural vegetation showed that in regions with a decrease in precipitation, the variation in water yield capacity also decreased, while in regions with an increase in precipitation from 0 to 8 mm/yr, the water yield capacity first decreased and then increased with precipitation. Our findings suggest that grass and shrubs would be more beneficial to regional water security in North China\'s revegetation, while afforestation would provide protection for the regional environment from extreme rainfall events.

High temperature is an environmental factor that impairs sow fertility. In this study, we identified the critical weeks for heat stress effects on aspects of fertility performance, namely weaning-to-first-service interval (WSI) and farrowing rate (FR). We also examined the threshold temperatures above which the fertility performance deteriorated and whether there were any differences between parities regarding heat stress effects or thresholds. Performance data of sows in 142 herds from 2011 to 2016 were matched to appropriate weekly averaged daily maximum temperatures (Tmax) from weather stations close to the herds. Two types of ratios (i.e., ratio for WSI and odds ratio for FR) were used to identify the critical weeks for heat stress by comparing the respective measures for two sow groups based on Tmax in different weeks around weaning or service events. The ratios for WSI were calculated between groups of sows exposed to Tmax ≥ 27 °C or <27 °C in each week before weaning, with the Tmax cutoff value based on a recent review study. Similarly, the odds ratios for FR for the two groups were calculated in weeks around service. The weeks with the largest differences in the fertility measures between the two Tmax groups (i.e., the highest ratio for WSI and the lowest odds ratio for FR) were considered to be the critical weeks for heat stress. Also, piecewise models with different breakpoints were constructed to identify the threshold Tmax in the critical week. The breakpoint in the best-fit model was considered to be the threshold Tmax. The highest ratios for WSI were obtained at 1 to 3 wk before weaning in parity 1 and 2 or higher sow groups. The threshold Tmax leading to prolonged WSI was 17 °C for parity 1 sows and 25 °C for parity 2 or higher sows. Increasing Tmax by 10 °C above these thresholds increased WSI by 0.65, and 0.33 to 0.35 d, respectively (P < 0.01). For FR, the lowest odds ratios were obtained at 2 to 3 wk before service in parity 0, 1, and 2 or higher sow groups. The threshold Tmax leading to reductions in FR was 20, 21, and 24 to 25 °C for parity 0, 1, and 2 or higher sow groups, respectively. Increasing Tmax by 10 °C above these thresholds decreased FR by 3.0%, 4.3%, and 1.9% to 2.8%, respectively (P < 0.01). These results indicate that the critical weeks for heat stress were 2 to 3 wk before service for FR and 1 to 3 wk before weaning for WSI. The decreases in fertility performance in parity 0 to 1 sows started at temperatures 3 to 8 °C lower than in parity 2 or higher sows.

Elevation is involved in determining plant diversity in montane ecosystems. This study examined whether the distribution of plants in the Yatsugatake Mountains, central Japan, substantiated hypotheses associated with an elevational diversity gradient. Species richness of trees, shrubs, herbs, ferns, and bryophytes was investigated in study plots established at 200-m elevational intervals from 1,800 to 2,800 m. The changes in plant diversity (alpha and beta diversities, plant functional types, and elevational ranges) with elevation were analyzed in relation to climatic factors and elevational diversity gradient hypotheses, that is, mass effect, mid-domain effect, and Rapoport\'s elevational rule. In addition, the elevational patterns of dominance of plant functional types were also analyzed. A comparison of alpha and beta diversities revealed that different plant groups responded variably to elevation; the alpha diversity of trees and ferns decreased, that of herbs increased, whereas the alpha diversity of shrubs and bryophytes showed a U-shaped relationship and a hump-shaped pattern. The beta diversity of shrubs, herbs, and bryophytes increased above the subalpine-alpine ecotone. In accordance with these changes, the dominance of evergreen shrubs and graminoids increased above this ecotone, whereas that of evergreen trees and liverworts decreased. None of the plant groups showed a wide elevational range at higher elevations. These elevational patterns of plant groups were explained by climatic factors, and not by elevational diversity gradient hypotheses. Of note, the changes in the dominance of plant groups with elevation can be attributed to plant-plant interactions via competition for light and the changes in physical habitat. These interactions could alter the elevational diversity gradient shaped by climatic factors.

Soil organic carbon (SOC) in the subsoil may not be so resistant to decomposition as previously assumed, while the mechanisms controlling C dynamics in subsoils are not yet known. This study aimed to (1) identify the factors that control SOC pools in subsoil and (2) compare the differences in SOC pools and controlling factors between the subsoil and topsoil. Subsoils (20-40 cm) were sampled along elevational gradients from two volcanic regions with less-disturbed vegetation each from Tanzania (11 sites) and Indonesia (12 sites). The sizes and mean residence times of labile, intermediate, and stable SOC pools were estimated by fractionation and model fitting to CO2 release during long-term incubation. The controlling factors of each SOC pool were determined by accompanying partial correlation and path analyses. In subsoil, the intermediate SOC pool predominantly controlled the SOC stability within decades. Climatic, geochemical, and biotic factors controlled different SOC pools. Temperature negatively affected the sizes of all three pools. The nanocrystalline minerals contents predominantly and positively controlled the sizes of intermediate and stable SOC pools, and the mean residence time of intermediate SOC pool. Biotic and climatic factors (i.e., microbial biomass, available N for microbes, and excess precipitation) controlled the labile SOC pool. Compared with topsoil, stabilized organic matters were more in the intermediate rather than in the stable SOC pool, and the temperature had a more significant effect on the stable SOC pool in subsoil than in topsoil. Available N for microbes partially controlled the labile and intermediate SOC pools in subsoil (more limited available N for microbes), but not in topsoil. Thus, subsoil SOC would be more sensitive to climate change than topsoil SOC. This study helped to understand the SOC stabilization mechanism and emphasized the high climate- and mineral-dependence of SOC in subsoil of tropical volcanic regions.

Evidence of immediate and delayed effects of climatic drivers on hospital admissions for schizophrenia is limited and inconsistent. We aimed to assess the association between climatic factors and daily hospital admissions for schizophrenia in Queensland, Australia.
Daily hospital admissions for schizophrenia from January 1, 1996 to December 31, 2015 in all private and public hospitals of Queensland were obtained from Queensland Health. The association between climatic factors and hospital admissions for schizophrenia were analysed using Generalised Linear Models with Poisson distribution (GLM) and Distributed Lag non-linear Models (DLNM) across different climatic zones.
In South East Queensland, only daily mean temperature showed an immediate negative effect on schizophrenia admissions (RR 0.93, 95%CI 0.90-0.98, p value < 0.001). For other regions, the adverse effect of temperature on hospital admissions was not significant, however, relative humidity (North: RR 1.01, 95%CI 1.00-1.02, p = 0.05) and air pressure (North: RR 1.03, 95%CI 1.00-1.05, p = 0.04; South West: RR 1.01, 95%CI 1.00-1.02, p = 0.05) had an immediate and positive effect on hospital admissions. Moreover, climatic factors had some delayed effects on schizophrenia admissions in different regions of Queensland, i.e. temperature over 0-4 lag days (South East: RR 0.97, 95%CI 0.94-0.98, p = 0.05; South West: RR 0.96, 95%CI 0.94-0.98, p = 0.01), relative humidity over 0-7 lag days (North: RR 0.95, 95%CI 0.92-0.98, p = 0.01; Central: RR 1.02, 95%CI 1.00-1.03, p = 0.05) and rainfall over 0-21 lag days (North: RR 1.03, 95%CI 1.01-1.04, p = 0.01). Meta-analysis showed significant pooled delayed effects of temperature (0-15 days lag: RR 0.95, 95% CI 0.93-0.98, p value < 0.001), relative humidity (0-7 days: RR 0.96, 95%CI 0.92-0.99, p < 0.001); rainfall (0-21 lag days: RR 1.03, 95%CI 1.01-1.04, p < 0.001) and air pressure (0-7 days lag: RR 1.02, 95%CI 1.00-1.04, p < 0.001) on schizophrenia admissions in Queensland.
As this is the largest study from Australia and also internationally to extensively examine both short term and delayed association between climatic factors and daily admissions for schizophrenia, the results of the study indicate that climate plays an important role in the sudden exacerbation of acute episodes of schizophrenia. Thus, preventive measures could be taken to reduce the severity of symptoms as well as hospital admissions due to schizophrenia during vulnerable periods.