Mean Annual Relative Humidity Research Articles

A novel missense mutation within KRT75 gene strongly affects heat stress in Chinese cattle.

The KRT75 gene (Keratin 75) is a member of the type II epithelial α-keratin gene family which plays a key role in hair and nail formation. And the coat conformation affects heat tolarence in mammals. Therefore, the aim of this study was to identify novel single nucleotide polymorphisms (SNPs) of the KRT75 gene and further evaluate its relation to heat stress in Chinese cattle. A missense mutation (NC_037332.1: g.1052T>C) of the bovine KRT75 was identified using the Bovine Genome Variation Database (BGVD). The g.1052T>C variant was then genotyped in 519 individuals of 22 cattle breeds. Further analyses showed that the frequency of T allele in Chinese indigenous cattle breeds gradually diminished from northern groups to southern groups, whereas the frequency of C allele displayed a contrary patternl. Simultaneously, the frequency of the CC and CT genotype for southern groups was much greater than that of the TT genotype. Additionally, association analysis showed the genotypes were remarkably associated with mean annual temperature (T), relative humidity (RH) and temperature humidity index (THI) (P<0.01). Our results demonstrated that the KRT75 gene might be a candidate gene associated with the heat stress in Chinese cattle.

Environmental determinants of leaf litter ant community composition along an elevational gradient

AbstractAnt communities are extremely diverse and provide a wide variety of ecological functions in tropical forests. Here, we investigated the abiotic factors driving ant composition turnover across an elevational gradient at Mont Itoupé, French Guiana. Mont Itoupé is an isolated mountain whose top is covered by cloud forests, a biogeographical rarity that is likely to be threatened according to climate change scenarios in the region. We examined the influence of six soil, climatic, and LiDAR‐derived vegetation structural variables on leaf litter ant assembly (267 species) across nine 0.12‐ha plots disposed at three elevations (ca. 400, 600, and 800m asl). We tested (a) whether species cooccurring within a same plot or a same elevation were more similar in terms of taxonomic, functional, and phylogenetic composition, than species from different plots/elevations, and (b) which environmental variables significantly explained compositional turnover among plots. We found that the distribution of species and traits of ant communities along the elevational gradient was significantly explained by a turnover of environmental conditions, particularly in soil phosphorus and sand content, canopy height, and mean annual relative humidity of soil. Our results shed light on the role exerted by environmental filtering in shaping ant community assembly in tropical forests. Identifying the environmental determinants of ant species distribution along tropical elevational gradients could help predicting the future impacts of global warming on biodiversity organization in vulnerable environments such as cloud forests.

Climate and tree seed production predict the abundance of the European Lyme disease vector over a 15-year period

BackgroundTo predict the risk of tick-borne disease, it is critical to understand the ecological factors that determine the abundance of ticks. In Europe, the sheep tick (Ixodes ricinus) transmits a number of important diseases including Lyme borreliosis. The aim of this long-term study was to determine the abiotic and biotic factors driving the annual abundance of I. ricinus at a location in Switzerland where Lyme borreliosis is endemic.MethodsOver a 15-year period (2004 to 2018), we monitored the abundance of I. ricinus ticks on a monthly basis at three different elevations on Chaumont Mountain in Neuchâtel, Switzerland. We collected climate variables in the field and from nearby weather stations. We obtained data on beech tree seed production from the literature, as the abundance of Ixodes nymphs can increase dramatically two years after a masting event. We used AIC-based model selection to determine which ecological variables drive annual variation in tick density.ResultsWe found that elevation site, year, seed production by beech trees two years prior, and mean annual relative humidity together explained 73.2% of the variation in our annual estimates of nymph density. According to the parameter estimates of our models, (i) the annual density of nymphs almost doubled over the 15-year study period, (ii) changing the beech tree seed production index from very poor mast (1) to full mast (5) increased the abundance of nymphs by 86.2% two years later, and (iii) increasing the field-collected mean annual relative humidity from 50.0 to 75.0% decreased the abundance of nymphs by 46.4% in the same year. Climate variables collected in the field were better predictors of tick abundance than those from nearby weather stations indicating the importance of the microhabitat.ConclusionsFrom a public health perspective, the increase in nymph abundance is likely to have increased the risk of tick-borne disease in this region of Switzerland. Public health officials in Europe should be aware that seed production by deciduous trees is a critical driver of the abundance of I. ricinus, and hence the risk of tick-borne disease.

Correlation of spatial distribution and habitat factors of Firmiana danxiaensis based on GeoDetector

Firmiana danxiaensis is an endemic species of Danxia landform in China. Identifying the main driving factors of its distribution can provide scientific basis for the conservation of F. danxiaensis and related habitats. With GeoDetector, we analyzed the correlation (measured by q value) between the spatial distribution of F. danxiaens and its habitat factors in F. danxiaens Nature Reserve in Nanxiong City and the Guangdong Danxia Mountain Tourism Scenic Area (core scenic area). Factors measured in this study included geographical elements (geomorphological type, soil subtype, elevation, slope, aspect) and climatic elements (annual precipitation and annual sunshine hours, mean annual relative humidity and mean annual wind speed). Our results showed that the main habitat factors affecting the spatial distribution of F. danxiaensis were soil subtype, annual sunshine hours, and geomorphologic genesis type. The q values of those three factors were higher than the mean values of all factors. In the pairwise combination of habitat factors, the interaction between geomorphologic genesis types ∩ annual sunshine hours and soil subtypes ∩ annual sunshine hours was enhanced by two factors and the q value was greater than the mean value of all combinations, with a strong correlation. Compared with other factors, the q value of soil subtypes, annual sunshine hours and geomorphologic genesis types were significantly different in the ecological detection of spatial distribution correlation of F. danxiaensis. The spatial distribution of F. danxiaensis was significantly correlated with soil subtypes, geomorphologic genesis types and annual sunshine hours, indicating that the GeoDetector is a useful method for vegetation habitat factor analysis and species distribution prediction.

The temporal and spatial relationships between climatic parameters and fire occurrence in northeastern Iran

Fire is a natural disturbance in a wide range of ecosystem types around the world. Although the majority of fires are caused by anthropogenic ignitions, climate and weather are known to influence the risk of fire spread, regardless of ignition source. However, the specific relationships among these factors remain under-studied for many regions of the world. The objective of this study was to investigate the effect of climatic variables on forest and rangeland fire regimes in the Golestan Province of Iran in three recent decades. Specifically, we sought to determine: (a) the quantitative temporal relationships between climatic variables and fire occurrence; and (b) the spatial relationships between climatic variables and fire occurrence. To assess quantitative temporal relationships, we used correlation and regression analyses to identify and describe statistically significant relationships between climatic data (mean annual temperature, mean annual precipitation, mean annual relative humidity, and mean annual wind velocity) and fire data (number of fire and area burned), using climatic data from the Golestan Meteorological Administration and fire statistics from the Golestan Natural Resources Administration (GNRA). To determine the spatial relationships between climatic variables and fire occurrence, we combined geospatial data on climatic variables (mean annual temperature, mean annual rainfall, wind effect, and topographic wetness index (TWI)) obtained from ASTER-GDEM and active fires derived from MODIS fire products in a random forest (RF) model approach to construct a map of fire susceptibility at 30 m spatial resolution. Our results showed that there was a significant temporal relationship between the number of fires and mean annual temperature, mean annual relative humidity, and mean annual wind velocity. There were also significant temporal relationships between area burned and mean annual relative humidity and mean annual wind velocity. Based on the RF model, the mean annual rainfall had the highest relative importance in fire spatial occurrence. Validation of the fire susceptibility map using area under the curve (AUC) indicated that the RF model created an accurate fire susceptibility map (AUC: 0.823), suggesting that the map can be used as a spatio-temporal climatic alarm system for fire occurrence in the different climatic conditions of the Golestan Province. The results from this study will be important for helping perform climate-change analyses for investigating future temporal and spatial patterns of wildfire in the Golestan Province.

Factors affecting severe weather threat index in urban areas of Turkey and Iran

BackgroundDistinguishing dynamic variations of the climate from the physical urban indicators is a challenge to assess the factors affecting weather severity. Hence, the time-series of the severe weather threat index (SWEAT) were considered in the four urban areas of Turkey and Iran to identify its affecting factors among the climatic variables and urban indicators in 2018. The SWEAT data were obtained from the upper-air sounding database of the University of Wyoming. The climatic variables were extracted from the Asia Pacific data research center (APDRC). The spatial statistics for urban expansion were collected from global human built-up and settlement extent (HBASE) data sets. A quantitative measuring of the Pearson correlation test was used to expose the relationships between dependent index (SWEAT) and independent variables (climatic and anthropogenic).ResultsResults revealed that the high and extreme severity classes of the weather condition in the Ankara, Istanbul, Mashhad, and Tehran are estimated as 7.7% (28 days), 15.3% (56 days), 1.1% (4 days), and 4.4% (16 days), respectively. The strongest values of the annual SWEAT index, exposing the unstable and severe weather conditions, were observed for Istanbul and Ankara urban regions. This result may be corresponding to the highest values of mean annual precipitation and relative humidity in addition to the largest values of urban expansion and sprawl index. The statistical correlation tests in annual scale confirmed the effective role of climatic elements of precipitation, relative humidity, and cloudiness (R from 0.94 to 0.99) and the urban expansion indicators (R from 0.86 to 0.91) in increasing annual severe weather index of SWEAT at above 85–95% of confidence level.ConclusionsThe correlations between the urban expansion indicators and outcome SWEAT index can be strengthened by some climatic elements (e.g., precipitation, humidity, and cloudiness), revealing the mediator and magnifier task. However, the mentioned correlations can be weakened by another climatic variable (i.e., air temperature), revealing a moderator and modifier task. Ultimately, investigation of the weather severity indices (e.g., SWEAT index) could be applied to identify the local and regional evidence of climate change in the urban areas.

Prioritization of the effectiveness rate of various climatic variables on the annual yield of rain-fed winter wheat using different statistical models

The annual yield of different plant species is affected by various parameters such as soil and water properties, climatic variables, etc. Due to the importance of the role of climatic variables on the yield of rain-fed winter wheat (as a strategic and effective plant species in the food security of the people of Iran), in this research the influence of climatic variables including the mean annual maximum temperature (MAT), the mean annual minimum temperature (MIT), the mean annual sunshine (SS), the mean annual relative humidity (HU), the mean annual wind speed (W) and the annual rainfall (R) on the annual yield of rain-fed winter wheat (AYWW) were evaluated based on the records of 10 stations from 1967 to 2016 scattered in Iran. To evaluate the impact of climate variables on the AYWW, the backward time series regression (BTSR), the backward logistic generalized estimating equation (BLGEE) and the backward generalized estimating equation (BGEE) statistical methods were used. All the statistical methods showed that W and SS variables were respectively the most and the least effective variables on the AYWW. Effective variables on AYWW in the BTSR were found to be the W, MIT and R (in 5, 4 and 1 stations out of 10), Effective variables on AYWW in the BLGEE were found to be the W, MIT, R and MAT (in 5, 3, 1 and 1 stations out of 10) and effective variables on AYWW in the BGEE were found to be the W, MIT, R and HU (in 5, 3, 1 and 1 stations out of 10).

The contributions of socioeconomic and natural factors to the acid deposition over China

China has experienced severe acid rain pollution during the past decades due to excessive sulfur oxides (SO2) and nitrous oxides (NOx) emissions, which further caused lake acidification, biodiversity losses and climate change. Although the major sources of acid deposition have been clarified previously, the contributions of socioeconomic (natural) factors to the regional acid deposition remained unknown. Therefore, a series of valuable data including socioeconomic (natural) variables and measured pH value in the rainwater at the city level were collected to identify the key factors influencing the rainwater pH value at the national and the regional scale using the spatial econometric model/geographical detector technique and geographical weight regression (GWR) model, respectively. The results showed that the annual mean pH value in the rainwater in China was 6.54 ± 0.72. The rainwater pH in winter (6.01 ± 0.41) was significantly lower than those observed during summer (6.74 ± 0.64), spring (6.71 ± 0.71) and autumn (6.71 ± 0.69). The spatial econometric model indicated that socioeconomic indicators including per capita gross industrial production (GIP), ratio of built-up area to the urban land (RBU), foreign direct investment (FDI), SO2 emission, and meteorological factors of annual mean precipitation (AMP), and annual mean relative humidity (AMRH) were the main factors for the acid deposition. The geographical detector technique implied that the power of determinants were in the order of AMRH (10.00%) = AMP (10.00%) > SO2 emission (8.51%) > FDI (8.32%) > RBU (7.64%) > per capita GIP (7.00%). The GWR implied that GIP, FDI, and SO2 emission made relatively higher contribution to acid deposition in East China relative to other regions owning to the huge population and the higher energy consumption. The higher rainfall amount and RH in Southeast China significantly increased the pollutant deposition fluxes and promoted the heterogeneous transformations of precursors of acid rain, respectively. The findings herein shed light upon the socioeconomic forces for the acid deposition in China for the first time and provided the new information for government sectors to control the acid rain pollution in the future.

Productive and reproductive performance of Holstein cows in Agreste, Pernambuco, from 2007 to 2017

The aim of this study was to assess the productive and reproductive performance of Holstein cows grown in the Agreste region of Pernambuco. Dairy records were collected from three farms located in the Agreste region of the state of Pernambuco each month between 2007 and 2017. According to the National Institute of Meteorology the average annual temperature during the collection period was 24.21 oC, mean annual rainfall was 551.7 mm and mean annual relative humidity was 75.92%. A total of 42,677 data points concerning milk production, milk components and somatic cell score (SCS), as well as other zootechnical information regarding reproductive management, are analyzed herein. In order to assess cow productive performance, lactation curve estimates were performed according to calving order by applying the Wood model, while milk production, milk components and SCS were analyzed according to calving order and farm, season, calving year and the interaction between calving order and season. Regarding reproductive evaluations, farm effects on indices such as age at first calving (IPP), calving interval (IP) and service period (PS) were evaluated. Data were processed using analysis of variance SAS PROC GLM commands, while PROC NLIN commands were used to estimate the curves. Significant (p < 0.05) farm, calving order, season, calving year and interaction effects on production values, milk composition and SCS were noted. Higher amounts of certain milk components (lactose, total solids and non-fat solids) were observed in primiparous cows. Multiparous cows were the most productive in relation to the amount of milk produced milk (34.15 kg/milk/day) and, consequently, presented the highest SCS (4.48). The Wood model showed a good fit of lactation curve characterized by an ascending phase until peaking and a descending phase following the peak. Regarding the assessed reproductive indices, a significant effect (p < 0.05) of farm was observed on IP and PS. The parameters calving order, farm, season, year of calving, interaction between calving order and season, as well as the effect of farm on reproductive indices (IP and PS) are the most important factors in the evaluation of production and milk quality of cows raised in semiarid environments.

Elevational patterns of temperature and humidity in the middle Tianshan Mountain area in Central Asia

The vertical distribution of vegetation types along an elevational gradient in mountain areas largely depends on the elevational changes in air temperature and humidity. In this study, we presented the seasonal and diurnal variations in the elevational gradients of air temperature and humidity on the southern and northern slopes in the middle Tianshan Mountain Range using data collected throughout the year via HOBO data loggers. The measurements were conducted at 12 different elevations from 1548 to 3277 m from September 2004 to August 2005. The results showed that the annual mean air temperature decreased along the elevational gradients with temperature lapse rates of (0.71±0.20)°C/100 m and (0.59±0.05)°C/100 m on the northern and southern slopes, respectively. The annual mean absolute humidity significantly decreased with increasing elevation on the northern slope but showed no significant trend on the southern slope. The annual mean relative humidity did not show a significant trend on the northern slope but increased with increasing elevation on the southern slope. The mean air temperature lapse rate exhibited significant seasonal variation, which is steeper in summer and shallower in winter, and this value varied between 0.37°C/100 m and 0.75°C/100 m on the southern slope and between 0.30°C/100 m and 1.02°C/100 m on the northern slope. The mean absolute and relative humidity also exhibited significant seasonal variations on both slopes, with the maximum occurring in summer and the minimum occurring in winter or spring. The monthly diurnal range of air temperature on both slopes was higher in spring than in winter. The annual range of air temperature on the southern slope was higher than that on the northern slope. Our results suggest that significant spatiotemporal variations in humidity and temperature lapse rate are useful when analyzing the relationships between species range sizes and climate in mountain areas.

Influence of socioeconomic disparities, temperature and humidity in kidney stone composition

Introduction:Large variations in demographic, economic and environmental factors might influence the worldwide distribution of urolithiasis, but scarce data are available concerning their associations with stone composition. We aimed to evaluate the frequency and composition of kidney stones and their associations with temperature, humidity, and human development index (HDI).Materials and Methods:A total of 1,158 stones from distinct patients (47±14 years old, male/female 2:1) were included. The mean annual temperature and relative humidity of each town were considered separately.Results:Calcium oxalate monohydrate (COM) was disclosed in 38.8% of patients, calcium oxalate dihydrate (COD) in 22.1%, mixed COD/apatite in 9.4%, pure apatite in 1.9%, brushite in 1.8%, struvite in 8.3%, pure uric acid in 11.1%, mixed uric acid/COM in 5.6%, and cystine/rare types in 0.8%. Mean HDI of all pooled cities was 0.780±0.03. However, people living in HDI<0.800 regions had twice the odds of having a struvite stone versus those living in HDI>0.800 (OR=2.14, 95% CI 1.11-4.11). Furthermore, a progressive increase in the struvite stones frequency from 4.5 to 22.8% was detected from HDI>0.800 through HDI<0.700. No significant difference for other stone types was disclosed. Separate logistic regression models assessed the association of each stone composition with gender, temperature, humidity and HDI as covariates.Conclusion:Patients living in low HDI areas are more prone to develop struvite stones, possibly due to lower access to healthcare. Temperature and humidity did not represent a specific risk factor for any stone type in the present sample.

Assessment of weather variability over Safaga harbour, Egypt

Meteorological conditions are key elements in the management of any harbour. The present study aims to present and analyse the meteorological conditions over Safaga Harbour of Egypt. The work is based on meteorological data recorded on hourly basis from January 2007 to December 2017 from the automated weather station in the Harbour. Results revealed a general trend of slight increase in the mean annual air temperature anomaly over the study period with a rate of 0.01 °C/year. The mean annual sea level pressure anomaly also had an increasing trend with a rate of 0.11 hPa/year. The dominant wind directions over the Harbour were N-NW-WNW during the study period. The year 2015 was the year of the lowest annual mean wind speed (9.74 kt), while 2008 was the year of the highest one (13.40 kt). There was a trend of decrease in the mean annual wind speed anomaly with a rate of −0.3 kt/year. Results also revealed a general trend of decrease in the mean annual relative humidity anomaly with a rate of −0.37%/year. Six, seven, thirteen and seventeen extreme values were detected for the air temperature, sea level pressure, wind speed and relative humidity, respectively.

Similar potential of foliar δ13C and silicon levels for inferring local climate information in the Tibetan Plateau region

Stable carbon isotope ratios (δ13C) are widely used as climate proxies for assessing and predicting climatic information at an annual resolution. However, the detailed information in the isotopes that results from intra-annual climate scenarios and is associated with mineral accumulation remains unclear. Combined with investigations of elements and ash contents, variations in foliar δ13C in relation to annual, winter and summer climate scenarios were investigated in a dendroclimatologically important tree species Sabina przewalskii Kom. Foliar δ13C exhibited a significant negative correlation with mean annual temperature, mean annual precipitation and mean annual relative humidity as well as significant positive correlations with elevation. Climatic factors in winter and summer have opposite effects on the variation of δ13C. The beneficial mineral element Si had a significant positive correlation with foliar δ13C, whereas the essential mineral elements K, Ca, and Mg did not. Specifically, Si and δ13C have similar correlations with climate factors and elevation. These results suggest that measurement of Si content has a similar potential to δ13C for use as an alternative climate indicator when detailed climatic information may otherwise be limited and provide a basis for understanding the integration of δ13C in plant responses to climate.

MTOR Variation Related to Heat Resistance of Chinese Cattle.

Simple SummaryDue to unique geographical distribution and appearance characteristics, China cattle has been divided into three groups: northern cattle (dominated by Bos taurus in northern China), central cattle (admixture of Bos taurus and Bos indicus in the middle region) and southern cattle (dominated by Bos indicus in southern China). With this rule, it was believed that southern in cattle are more heat resistant than northern cattle. Previous studies showed that the mechanistic target of the rapamycin (MTOR) (NC_037343.1:c.2062G>C) gene could be associated with heat resistance. This study used PCR and sequencing to type this locus in 1030 individuals of 37 cattle breeds and proved the mutation of this locus could be related to heat tolerance in Chinese cattle.With the inexorable rise of global temperature, heat stress deserves more and more attention in livestock agriculture. Previous studies have shown that the mechanistic target of rapamycin (MTOR) (NC_037343.1:c.2062G>C) gene contributes to the repair of DNA damage repair and is associated with the adaptation of camels in dry and hot environments. However, it is unknown whether this mutation is related to the heat tolerance of Chinese cattle. In this study, PCR and sequencing were used to type the mutation locus in 1030 individuals of 37 cattle breeds. The analysis results showed that the frequency of G allele of the locus gradually diminished from the northern group to the southern group of native Chinese cattle, whereas the frequency of the C allele showed an opposite pattern, displaying a significant geographical difference across native Chinese cattle breeds. Additionally, an analysis of the locus in Chinese indigenous cattle revealed that this SNP was significantly associated with mean annual temperature (T), relative humidity (RH) and temperature humidity index (THI) (p < 0.01), suggesting that cattle with C allele was distributed in regions with higher T, RH and THI. In conclusion, this study proved that the mutation of MTOR gene in Chinese cattle could be associated with the heat tolerance.

A Missense Mutation of the HSPB7 Gene Associated with Heat Tolerance in Chinese Indicine Cattle.

Simple SummaryA missense mutation (NC_037329.1: g.136054902 C > G: p. Ala69Gly) was identified in the heat shock protein family B (small) member 7 (HSPB7) gene in indicine cattle, which might be a candidate mutation associated with the heat tolerance. Here, Polymerase Chain Reaction and DNA sequencing methods were used to detect this mutation in 774 individuals belonging to 32 Chinese indigenous cattle breeds. The distribution of alleles of NC_037329.1: g.136054902 C > G displays significant geographical difference across native Chinese cattle breeds and cattle carrying allele G distributed in regions with higher mean annual temperature, relative humidity, and temperature humidity index. Our results demonstrate that the mutation of the HSPB7 gene in Chinese indicine cattle might be a candidate gene associated with the heat tolerance.The small heat shock proteins (HSPB) are expressed in response to heat stress, and the heat shock protein family B (small) member 7 (HSPB7) gene has been reported to play an important role in heat tolerance pathways. Only a missense mutation (NC_037329.1: g.136054902 C > G: p.Ala69Gly) was identified in the HSPB7 gene in indicine cattle, which might be a candidate mutation associated with the heat tolerance. Here, we explore the allele frequency of this mutation in 774 individuals belonging to 32 Chinese indigenous cattle breeds using polymerase chain reaction (PCR) and DNA sequencing methods. The distribution of alleles of NC_037329.1: g.136054902 C > G displays significant geographical difference across native Chinese cattle breeds that the allele C was dominant in northern cattle groups, while allele G was dominant in southern indicine cattle groups. Additionally, the association analysis indicated that the G allele was significantly associated with mean annual temperature (T), relative humidity (RH), and temperature humidity index (THI) (p < 0.01), suggesting that cattle carrying allele G were distributed in regions with higher T, RH, and THI. Our results demonstrate that the mutation of the HSPB7 gene in Chinese indicine cattle might be a candidate gene associated with the heat tolerance.

Leaf wax n-alkane patterns of six tropical montane tree species show species-specific environmental response.

It remains poorly understood how the composition of leaf wax n‐alkanes reflects the local environment. This knowledge gap inhibits the interpretation of plant responses to the environment at the community level and, by extension, inhibits the applicability of n‐alkane patterns as a proxy for past environments. Here, we studied the n‐alkane patterns of five Miconia species and one Guarea species, in the Ecuadorian Andes (653–3,507 m a.s.l.). We tested for species‐specific responses in the average chain length (ACL), the C31/(C31 + C29) ratio (ratio), and individual odd n‐alkane chain lengths across an altitudinally driven environmental gradient (mean annual temperature, mean annual relative air humidity, and mean annual precipitation). We found significant correlations between the environmental gradients and species‐specific ACL and ratio, but with varying magnitude and direction. We found that the n‐alkane patterns are species‐specific at the individual chain length level, which could explain the high variance in metrics like ACL and ratio. Although we find species‐specific sensitivity and responses in leaf n‐alkanes, we also find a general decrease in “shorter” (<C29) and an increase in “longer” (>C31) chain lengths with the environmental gradients, most strongly with temperature, suggesting n‐alkanes are useful for reconstructing past environments.

Spatial distribution characteristics of tumor marker CA724 reference values in China.

ObjectsThis study aims to explore the Cancer antigen 724 (CA724) reference values spatial distribution characteristics in healthy Chinese adults. The study can provide regional reference for medical diagnosis.Study DesignThe relationship between CA724 and 25 geographical environmental factors was analyzed firstly. Artificial neural network simulation training was used to construct the prediction model. The national forecast distribution map of the CA724 reference values was obtained by the geostatistical mapping method. Analyzing and exploring the influence mechanism of geographical environment factors on CA724 reference values.MethodsCollecting 34470 cases from more than 106 cities healthy adults CA724 reference values via several paper databases in 10 recent years. Correlation analysis, RBF artificial neural networks and trend surface analysis were applied to explore if there was any tendency of spatial variation. The Kriging interpolation of geostatistical analysis was developed to reveal the spatial distribution characteristics of the CA724 reference values.ResultsThe distribution of CA724 reference values of Chinese healthy adults shows a downward trend from south to north. CA724 reference values have negative correlations with latitude, annual sunshine duration and topsoil cation exchange capacity in clay. CA724 have positive correlations with annual mean air temperature, annual mean relative humidity, and annual precipitation amount. High temperature and high humidity environment will reduce gastrointestinal function and breeze various mold bacteria. Lack of sunshine can easily lead to vitamin C deficiency in the body. These will increase the incidence of gastrointestinal diseases and gastric cancer, then increase the CA724 value.ConclusionCA724 reference values show spatial autocorrelation and regional variation. There are some geographical environment factors effected Chinese healthy adults CA724 reference values. Geographic factors such as sunshine, temperature, and humidity have effects on CA724 reference values can provide new ideas and directions of prevention and clinical diagnosis in the future.

Fossil mega- and micro-flora from Bernasso (Early Pleistocene, southern France): A multimethod comparative approach for paleoclimatic reconstruction

Bernasso is an Early Pleistocene locality that has a well-dated floral fossil content including both pollen grains and megaremains. Pollen record shows vegetation changes corresponding to two glacial and one interglacial periods. The megafloral fossil assemblage was interpreted as an association of present-day Mediterranean and Caucasian taxa that developed during a late interglacial stage of the beginning of the Pleistocene. In the present study, climatic reconstruction using the Climate Leaf Analysis Multivariate Program (CLAMP) and the Leaf Margin Analysis (LMA) methods based on the megaflora on one hand and using the Climatic Amplitude Method (CAM) based on the pollen flora on the other hand have been used to check the qualitative climatic estimates based on the comparison between paleovegetation data and similar modern ecosystems. CLAMP and LMA analyses show that the Bernasso climate was colder than the present-day climate of Southern France and of the Hyrcanian and Euxinian regions. On contrary, CAM shows mean annual temperatures higher than the modern Bernasso temperature and equivalent to the temperature of the Hyrcanian and Euxinian regions. Mean annual precipitation and relative humidity reconstructed by CLAMP and CAM are in agreement and indicate that the climate was wetter than today at Bernasso. The differences between the three methods highlight important methodological biases that could be solved by including additional calibration sites in Europe and in the Mediterranean region.

Site analysis in the Argentinean Andean region for the placement of astrophysical observatories and solar photovoltaic power plants. The case of the “Leoncito 2” site

After a detailed search for possible sites where to place astrophysical facilities in Argentinean Andean region, a location labeled as LEO 2 (31°24′22″ S, 69°29′32″ W, 1630 masl) is proposed. It is placed near the largest Astronomical Observatory of Argentina: Complejo AStronómico El LEOncito (CASLEO). Its advantages are: a good altitude to detect the maximum development of cosmic ray showers, high spectral transmittance to UV and visible ranges, very low aerosol content (mean particle concentration measured at ground with an optical particle counter PM2.5 = 1.52 µg m−3 and PM>2.5 = 6.83 µg m−3, mean Aerosol Optical Depth at 550 nm = 0.027 (measured from space using the SeaWiFS instrument on board of the SeaStar NASA satellite). A local meteorological analysis was done, using data measured in situ, which shows a typical desertic site with the following mean annual (std. dev.) values:mean annual temperature 18.93 (7.66) °C, mean annual relative humidity 28.76 (20.55)%, low/ moderate mean annual average wind speed 11.63 (8.78) km/h, low mean water content (0.73 cm) and rather low mean cloud coverage fraction (cloud coverage fraction): 0.29 (0.02) (for the period 2003–2016 from Aqua/NASA satellite MODIS device) and 0.25 (0.01) (for the period 2000–2016, Terra/NASA satellite MODIS device). Concerning the conditions for the placement of photovoltaic solar power plants, some positive aspects that can be remarked are a large rather flat available surface (336 km2) with very good levels of annual mean horizontal solar irradiation: Global (2334 kWh m−2per year), Direct (3127 kWh m−2 per year) and Diffuse (394 kWh m−2 per year). Optimum angle to place solar panels at this site is determined and the global tilted solar irradiation is calculated (2689 kWh m−2 per year). In comparison with an African (Ouarzazate, Morocco) and Asian (Dubai) sites, the analysed site present better annual irradiation levels being the Global horizontal irradiation at the Argentinean site 8.1% and 10.3% higher than those calculated for the African and Asian site respectively. Also, a comparison is made of different solar cells (monocrystalline Si, polycrystalline Si and perovskite), through the calculation of the generated photocurrent (mean produced solar photovoltaic current per unit cell surface), considering the atmospheric and solar radiation parameters found for the studied site. We thus conclude that the proposed site in the Andes range is well suited for the placement of Astrophysical facilities, as well as Photovoltaic solar power plants.

A novel approach for predicting the probability of ignition of palaeofires using fossil leaf assemblages

AbstractMany metrics are used to predict and manage wildfires today but it is difficult to directly apply these to past wildfires histories. Developing an approach that enables estimation of these fire metrics in the past would provide significant power in our ability to compare past fire risk with that of the modern day. We use the Climate Leaf Analysis Multivariate Program (CLAMP) to estimate warm month mean temperature and annual mean relative humidity for a modern day leaf dataset and establish a novel methodology by which we can generate ‘pseudo‐daily’ meteorological parameters to calculate the probability of ignition (p(I)), an aspect of the North American Fire Danger Rating System. We test this methodology on Tortonian aged fossil leaves (11.62–7.25 Ma) from five sites across California, which reveal that the Tortonian was cooler and considerably more humid and that p(I) was lower during this time than in the region today.