Mean Minimum Temperature Research Articles

The response of annual minimum temperature on the eastern central Tibetan Plateau to large volcanic eruptions over the period 1380–2014 CE

Abstract. Volcanic eruptions have a significant impact on global temperature; their consequences are of particular interest in regions that are especially sensitive to climate change, like the Tibetan Plateau. In this study, we develop a temperature-sensitive tree-ring-width standard chronology covering the period 1348–2014 CE using Qilian juniper (Sabina przewalskii (Kom.)) samples collected from the Animaqin Mountains on the Tibetan Plateau. We reconstruct the annual (prior August to current July) mean minimum temperature (Tmin) since 1380 CE and show that our reconstruction explains 58 % of the variance during the 1960–2014 calibration period. Our results demonstrate that in 77.8 % of cases in which a volcanic eruption with a Volcanic Explosivity Index of 5 or greater occurs, temperature decreases in the year of or the year following the eruption. The results of the superposed epoch analysis also indicate that there is a high probability that the Tmin decreases for 2 years after a large volcanic eruption, especially when such eruptions occur in the Northern Hemisphere.

Which environmental factors are most relevant to the distribution of Sicyonia dorsalis (Penaeoidea: Sicyoniidae) in an upwelling region?

Knowledge of the environmental factors in an upwelling region is extremely important to understand their relationship with influences in the spatiotemporal densities of penaeid shrimps. Spatial and temporal patterns of distribution of Sicyonia dorsalis were evaluated in relation to temperature, salinity, organic matter, and sediment type in a tropical region influenced by upwelling, using monthly data (2010 to 2011 and 2013 to 2014). The very fine sand was found in 5 m depth and silt and clay and the highest organic matter (mean 16.94%) contents were predominated in 15 m depth. The mean minimum bottom temperature and the maximum salinity were found in spring (18.5 oC and 39.25 psu, respectively). The total of 686 shrimps captured and a consistent pattern of high relative abundance of shrimp in winter and spring and scarcity in autumn was observed. Shrimp abundance was highest in sites at 15 m and positively associated with sediment. The predominance of individuals in finer substrates (silt and clay) was related to higher levels of organic matter content (a food source for shrimp). Temperature was negatively associated with abundance, which was prominent from 19 to 21 °C. Temperature and sediment type were the factors that most influenced the spatiotemporal differences in the density of the S. dorsalis in an area influenced by the upwelling phenomenon. The study highlights the importance of understanding the patterns and drivers to the distribution of shrimps in order to develop modelling species distribution along the coastal region.

Model specification and data interpretation of climate in Pakistan

The issue of climate change has occurred very strongly during the last 2 decades on global scale in analysis of estimated inferences on the environment of vulnerable states. Pakistan is one of the states that has high vulnerability index to natural disaster. Currently, climate of Pakistan is growing warmer; and we are moving around different signals of change. Meanwhile, it is important to ascertain climate trend of temperature, rain, wind speed and humidity in Pakistan on sequential basis. Therefore, this study aims to ascertain the climate trend through model specification of Stretched distributions comprising Lindley Stretched Exponential distribution, Exponentiated Stretched Exponential distribution, Kumaraswamy Stretched Exponential distribution and Transmuted Stretched Exponential distribution. A sort of comparison among new proposed, classical and modern models is also put up to evaluate the relative quality of statistical models for Climate data through Maximized Log Likelihood, Akaike Information Criterion, Bayesian Information Criterion, Consistent Akaike Information Criterion, Hannan Quinn Information Criteria and Kolmogorov Smirnov test. Findings specify that Kumaraswamy Stretched Exponential distribution is the best fit for modeling mean minimum temperature (oC) data, Lindley Stretched Exponential distribution is the best fit for modeling total July’s rain (mm) data, Transmuted Stretched Exponential distribution is the best fit for modeling wind speed (knots) data, Exponentiated Stretched Exponential distribution is the best fit for modeling humidity (%) data according to model specification. Generally, the results demonstrate that and new proposed models are ascertained best models for specification of climate data in Pakistan. It is also observed that these models proved stretchy and flexible for modeling climate data in the state of Pakistan.

Change-point detection and trend analysis in monthly, seasonal and annual air temperature and precipitation series in Bartın province in the western Black Sea region of Turkey

Studies associated with climate change and variability are of great importance at both the global and local scale in the global climate crisis. In this study, change-point detection and trend analysis were carried out on mean, maximum, minimum air temperatures and total precipitation based on monthly, seasonal and annual scale in Bartın province located in the western Black Sea Region of Turkey. For this aim, 4-different homogenei-ty tests (von Neumann test, Pettitt test, Buishand range test and standard normal homogeneity test) for change-point detection, Modified Mann–Kendall test and Şen’s innovative trend test for trend analysis, and Sen’s slope test for the magnitude estimation of trends were used. According to the test results, the summer temperatures in particular show increasing trends at the 0.001 significance level. Mean maximum temperature in August, mean minimum temperature in June and August, and mean temperature in July and August are in increasing trend at the 0.001 significance level. Over a 51 year period (1965–2015) in Bartın province, the highest rate of change per decade in air temperatures is in August (0.55°C for Tmax, 0.46°C for Tmin and 0.43°C for Tmean) based on Sen’s slope. However, the study showed that apart from October precipitation, there is no significant trend in monthly, seasonal and annual precipitation in Bartın. Increasing trends in mentioned climate variables are also visually very clear and strong in Şen’s innovative trend method, and they comply with the statistical results. As a result, the study revealed some evidence that temperatures will increase in the future in Bartın and its environs.

Understanding the Resilience of Sal and Teak Forests to Climate Variability Using NDVI and EVI Time Series

Abstract This study attempts to understand the climatic resilience of two forest types of central India—that is, Tectona grandis (Teak) forest of Satpura Tiger Reserve and Shorea robusta (Sal) forest of Kanha Tiger Reserve—using normalized difference vegetation index (NDVI), enhanced vegetation index (EVI) extracted from MODIS, and climate variable data sets at highest spatial and temporal scales. Teak and Sal forests within the core area of the selected tiger reserves represent the least anthropogenic disturbances, and therefore, the observed changes in NDVI and EVI over the past 16 years could be analyzed in the context of climate change. The correlation analysis between climatic variables (minimum temperature, maximum temperature, mean temperature, and total annual rainfall) and forest response indicators (NDVI/EVI) at seasonal and annual scales revealed that Teak and Sal forests are more sensitive to change in past temperature as compared with rainfall. Also, the changes in NDVI and EVI of Sal forest are correlated more to minimum temperature, and that of Teak forest to maximum temperature. The analysis of sapling girth class of Sal and Teak further revealed that Sal as compared with Teak is more affected because of the changing climate variables of the recent past. The findings of the study will help manage forests more efficiently in the context of changing climate.

Climate effects on nesting phenology in Nebraska turtles.

A frequent response of organisms to climate change is altering the timing of reproduction, and advancement of reproductive timing has been a common reaction to warming temperatures in temperate regions. We tested whether this pattern applied to two common North American turtle species over the past three decades in Nebraska, USA. The timing of nesting (either first date or average date) of the Common Snapping Turtle (Chelydra serpentina) was negatively correlated with mean December maximum temperatures of the preceding year and mean May minimum and maximum temperatures in the nesting year and positively correlated with precipitation in July of the previous year. Increased temperatures during the late winter and spring likely permit earlier emergence from hibernation, increased metabolic rates and feeding opportunities, and accelerated vitellogenesis, ovulation, and egg shelling, all of which could drive earlier nesting. However, for the Painted Turtle (Chrysemys picta), the timing of nesting was positively correlated with mean minimum temperatures in September, October, December of the previous year, February of the nesting year, and April precipitation. These results suggest warmer fall, and winter temperature may impose an increased metabolic cost to painted turtles that impedes fall vitellogenesis, and April rains may slow the completion of vitellogenesis through decreased basking opportunities. For both species, nest deposition was highly correlated with body size, and larger females nested earlier in the season. Although average annual ambient temperatures have increased over the last four decades of our overall fieldwork at our study site, spring temperatures have not yet increased, and hence, nesting phenology has not advanced at our site for Chelydra. While Chrysemys exhibited a weak trend toward later nesting, this response was likely due to increased recruitment of smaller females into the population due to nest protection and predator control (Procyon lotor) in the early 2000s. Should climate change result in an increase in spring temperatures, nesting phenology would presumably respond accordingly, conditional on body size variation within these populations.

Projected near-term changes in temperature extremes over China in the mid-twenty-first century and underlying physical processes

This study investigates the near-term future changes of temperature extremes in summer (June–August) and winter (December–February) seasons over mainland China in the mid-twenty-first century (FP; 2045–2055) under representative concentration pathway (RCP) 4.5 scenario relative to the present day (PD; 1994–2011) by using an atmosphere–ocean-mixed-layer coupled model MetUM-GOML1. The projected changes in hot extremes exhibit a rise in hottest day temperature (TXx) and warmest night temperature (TNx) and an increase in frequencies of summer days (SU) and tropical nights (TR). The projected changes in cold extremes show a rise in coldest day temperature (TXn) and coldest night temperature (TNn) and a decrease in frequencies of ice days (ID) and frost days (FD). The projected changes in temperature extremes in both seasons are primarily determined by changes in seasonal mean daily maximum and minimum temperature while changes in temperature variability from daily to sub-seasonal time scales play a minor role. The future changes in temperature extremes over China, being consistent with the rise in seasonal temperature, are partly due to the increase in surface downward clear sky longwave radiation through the increased greenhouse gas concentrations and enhanced water vapor in the atmosphere, and partly due to the increase in net surface shortwave radiation as a result of the decreased aerosol emissions over Asia via aerosol-radiation interactions. Moreover, the seasonal mean surface warming can further be amplified with positive feedbacks by reducing the cloud cover, leading to positive changes in shortwave radiative effect through aerosol-cloud interactions and surface-atmosphere feedbacks during summer, and by positive changes in surface clear sky shortwave radiation through snow-albedo feedbacks over northern China and southwestern China during winter.

基于树轮记录的阿尔泰山中段1798年以来6-7月平均最低气温变化研究

PDF HTML阅读 XML下载 导出引用 引用提醒 基于树轮记录的阿尔泰山中段1798年以来6-7月平均最低气温变化研究 DOI: 10.5846/stxb201912312835 作者: 作者单位: 作者简介: 通讯作者: 中图分类号: 基金项目: 中国沙漠气象科学研究基金（Sqj2017004）；国家自然科学基金（41861006）；甘肃省高等学校科研项目（2018C-02） Changes of mean minimum temperature in June-July since 1798 in central Altay Mountain recorded by tree rings Author: Affiliation: Fund Project: 摘要 | 图/表 | 访问统计 | 参考文献 | 相似文献 | 引证文献 | 资源附件 | 文章评论 摘要:通过分析新疆阿尔泰山中段西伯利亚落叶松树轮宽度年表与气候因子的相关关系证明6-7月平均最低气温是研究区树木径向生长的主控气候因子（r=0.649，P<0.001）。利用线性回归方法构建了阿尔泰山中段1798-2017年6-7月平均最低气温方程，通过计算重建方程方差解释量（41.1%）和利用逐一剔除法对重建方程各项参数进行了稳定性检验，证明了重建方程是稳定可靠的。分析重建的平均最低气温年际变化表明，研究区经历了4个暖期（1906-1919年、1922-1935年、1945-1960年和1997-2017年）和4个冷期（1816-1831年、1840-1867年、1869-1886年和1888-1905年），并且与相邻地区平均气温重建序列冷暖变化阶段一致。基于多窗谱分析结果发现重建6-7月平均最低气温序列存在2a、2.4a、2.8-3a、11a、20-22a左右的变化周期，表明研究区气候变化主要受厄尔尼诺-南方涛动（ENSO）、太阳黑子活动和全球海温变化（SST）驱动。本研究为系统掌握阿尔泰山气候变化规律和科学预测未来气候变化提供了依据。 Abstract:The analysis of the relationship between the tree ring width chronology of Larix sibirica and climatic factors in central Altay Mountain, Xinjiang indicates that the mean minimum temperature from June to July is the main climatic factors for the radial growth of trees (r=0.649, P<0.001). Mean minimum temperature equation from June to July in the past 220 years in central Altay Mountain was constructed using the linear regression method, and the interpretation of the variance of the reconstructed equation was 41.1%. The leave-one-out method was used to test the stability of the reconstruction equation, and various test parameters proved that the reconstruction equation was stable and reliable. Inter-annual changes in the reconstructed mean minimum temperature indicated that there are four warm periods (1906-1919, 1922-1935, 1945-1960, and 1997-2017) and four cold periods (1816-1831, 1840-1867, 1869-1886, and 1888-1905) in the study area. These are consistent with the cold and warm stages of the reconstruction sequence of the mean temperature in the adjacent area. The reconstructed sequence with change periods of about 2a, 2.4a, 2.8-3a, 11a, and 20-22a based on the multi-taper analysis indicates that climate change is mainly driven by the global sea surface temperature (SST), sunspots and ENSO (El Niño-Southern Oscillation) in the study area. The reconstructed mean minimum temperature provides a basis for systematically mastering regularity and scientifically predicting future tendency of climate change in the Altay Mountain. 参考文献 相似文献 引证文献

Sex-specific differences in spring migration timing of Song Thrush Turdus philomelos at the Baltic coast in relation to temperatures on the wintering grounds

Environmental factors influencing the timing of bird migration frequently affect age and sex groups differently. We applied discriminant functions to determine the sex of adult Song Thrushes ringed during spring migration in 1968–2019 at Hel on the Polish Baltic coast. We aimed to determine any differences between the sexes in the timing of spring migration and changes in protandry, and to identify any relationships between migration timing and temperatures at the wintering grounds. We analysed relationships between the date of migration and the year and monthly mean minimum temperatures in December–February by sex, using multiple quantile regression for q10, q50 and q90 of spring passage. On average males migrated six days before females. Spring protandry increased over 1968–2019 and with warm winters. The sexes responded differently to winter temperatures, likely because of the species’ mating strategy. For males the warmer the winter, especially in February, the earlier spring migration began and the later it ended, prolonging its duration. The influence of February’s temperature on the beginning of males’ migration is likely explained by selective pressure for their early arrival to establish territories. The later end of their arrival with a warm winter might reflect more low-quality males surviving, and migrating later than high-quality males, than with cold winters. For females December and January temperatures had no effect on the beginning and the end of spring migration; but the warmer the February, the earlier migration started and the later it ended. Females probably benefitted from improved conditions in a warm February in two ways: early-arriving females maximized their breeding success with a chance to raise a second brood, and late-arriving females maximized their chances of surviving migration by prolonging fuelling and stopovers, which extended females’ arrivals.

Temporal studies of climatic and environmental parameters and their possible impact on selected reservoir fish production of Madhya Pradesh: A different methodological approach

Climate change has a significant influence on global biodiversity and would like to affect the structure and function of natural ecosystems. This study assessed the quantitative impact of climatic change on the selected reservoirs. The climatic data of Madhya Pradesh were collected from the Indian Meteorological Department (IMD). The temperature and rainfall data under the A1B scenario were processed using Linux-based Ferret software, whereas chlorophyll-a and water surface temperature data were retrieved from Landsat-8 imagery using SNAP and ARC GIS software. Annual Anomaly analysis for average temperature and rainfall found, warming in annual temperature at Indirasagar reservoir under A1B scenarios during 1991–2015, 2016–2040 and 2041–2065 while, rainfall decreased between 1991–2015 and 2016–2040 but would like to be increased during (20412065). Similar results were found in the case of the Gandhisagar reservoir as well. Seasonal trend analysis was done using a statistical non-parametric test, Mann-Kendall (M-K) test, which showed an increasing trend for average temperature in post-monsoon and Winter, while the decreasing trend was found in Monsoon and Pre-Monsoon in Indirasagar reservoir. This study also found a significant decreasing trend for rainfall in all three seasons except Monsoon. In the case of Gandhisagar reservoir, an increasing trend has found on average temperature for all the seasons while rainfall showed a significantly decreasing trend in all the seasons except Post-Monsoon. This study also predicted the reservoir fish production using different prediction models and Auto-Regressive Integrated Moving Average with exogenous variables (ARIMAX) model found as the most suitable model in case of forecasting. It was also found that mean maximum temperature, mean minimum temperature and mean wind speed were the most significant variables in predicting fish production.

Temperature and rainfall impacts on robusta coffee bean characteristics

Robusta coffee is the primary source of income for millions of smallholder farmers throughout the world’s tropics. The price smallholder farmers can get for their coffee is strongly influenced by bean characteristics (i.e. beans are of a sufficient size and have minimal defects). Climate is a key determinant of successful coffee production, but scant research has been undertaken to test and quantify climate impacts on robusta coffee bean physical characteristics. Here we investigate how climate relates to the risk of poor coffee bean characteristics in one of South East Asia’s key coffee producing areas, the central highlands of Vietnam. We use 5 years (2012–2016) of coffee bean characteristic data from 60 farms. Hierarchical modelling was used to investigate how rainfall and temperature related to two indicators of coffee bean characteristics (1) the probability of below average coffee bean size and (2) the probability of above average coffee bean defects. Low rainfall (<1600 mm) during the late growing season (July-September) greatly increased the risk (>80% probability) of below average coffee bean size. Conversely, high rainfall (>750 mm) and high mean minimum temperature (>22 °C) during harvest (October-December) increased the risk (>75% probability) of above average coffee bean defects. Various coffee bean characteristic subcomponents (e.g. insect damage and mouldy beans) and different bean sizes were also examined and were affected by a range of rainfall and temperature predictors across the flowering, growing and harvest seasons. With this information targeted risk-management strategies (e.g. targeted irrigation during hot and dry growing seasons, adjusting harvest timing and employing drying techniques during wet and cold harvest periods) could be developed to minimise the effect of climate conditions that increase the risk of coffee bean defects. Successfully managing the impacts identified here, could decrease coffee bean defects and in turn increase the incomes of smallholder coffee farmers.

Modelling tree height-diameter allometry of Chinese fir in relation to stand and climate variables through Bayesian model averaging approach

Tree height-diameter allometry reflects the response of specific species to above and belowground resource allocation patterns. However, traditional methods (e.g. stepwise regression (SR)) may ignore model uncertainty during the variable selection process. In this study, 450 trees of Chinese fir ( (Lamb.) Hook.) grown at five spacings were used. We explored the height-diameter allometry in relation to stand and climate variables through Bayesian model averaging (BMA) and identifying the contributions of these variables to the allometry, as well as comparing with the SR method. Results showed the SR model was equal to the model with the third highest posterior probability of the BMA models. Although parameter estimates from the SR method were similar to BMA, BMA produced estimates with slightly narrower 95% intervals. Heights increased with increasing planting density, dominant height, and mean annual temperature, but decreased with increasing stand basal area and summer mean maximum temperature. The results indicated that temperature was the dominant climate variable shaping the height-diameter allometry for Chinese fir plantations. While the SR model included the mean coldest month temperature and winter mean minimum temperature, these variables were excluded in BMA, which indicated that redundant variables can be removed through BMA.Cunninghamia lanceolata

Urban landscape selection by Eurasian collared dove (&lt;i&gt;Streptopelia decaocto&lt;/i&gt;) in eastern Spain

The Eurasian collared dove (Streptopelia decaocto) is an invader species, and its distribution is continuously on the increase. Today its expansion has spread to the American continent. In this study we describe the effects of the urban environment on the Eurasian collared dove in eastern Spain. The abundance and presence of this dove were analyzed in 46 localities using counting points. Overall, 220-point counts were surveyed between autumn 2015 and late-winter 2016. A hierarchical partitioning analysis was used to identify explanatory variables of different types such as resources, climate and urban structure, and human presence, which may influence the presence and abundance of this species. In the case of presence, the number of town inhabitants, parks, mean minimum temperature, exotic vegetation and schools had a positive association, while pedestrian number and restaurants had a negative association. Abundance was positively related to native vegetation, exotic vegetation, and water, while urban area was negatively associated with it. Exotic vegetation was the only variable that has a positive relation to presence and abundance. These results can help to predict the use of urban habitats in potential localities for its invasion.

INVESTIGATION OF CLIMATE CHANGE VARIABILITY UNDER CLIMATE CHANGE CONDITIONS OVER THE SEMI-ARID REGION

The purpose of the study was to investigate the variation in climatic parameters and possible climate effects in the Hyderabad region. The least-square regression method was used to find a linear change in climatic parameters (Temperature and Precipitation). The maximum, minimum, and mean temperatures; annual, and monsoon precipitations were considered under the study. In the last 100 years, the global temperature has been increased by 0.6 or 0.74 0C. In Hyderabad city, we predicted that the minimum temperature (Tmin), maximum temperature (Tmax), and mean temperature (Tmean) are varied in the range of 0.00490C/year to -0.01330C/year. The variability in the precipitation was observed in the last 30 years. Yearly and monsoon precipitation was decreasing with the rate of 1.24mm/year, and 1.34mm/year. The maximum precipitation occurs in July, August, and September; in the rest of the months, no or little precipitation occurred which may lead to a shortage of fresh water.

Diverse responses of spring phenology to preseason drought and warming under different biomes in the North China Plain

Global-change-type drought, a combination of drought and warmer temperatures, is projected to have severe effects on vegetation growth and ecosystem functions. Spring phenology is an important biological indicator to understand the response of vegetation growth to climate change. However, the differences in the response of spring phenology to global-change-type drought among various vegetation types remain unclear. Here, we extracted the start of growing season (SOS) from NDVI (Normalized Difference Vegetation Index) data using Spline-midpoint, HANTS-Maximum, and Timesat-SG methods in the North China Plain over the period 1982–2015. Then, we investigated the effects of preseason drought on SOS (based on the Standardized Precipitation Evapotranspiration Index, SPEI), and compared responses of SOS to the minimum temperature (Tmin), maximum temperature (Tmax), and mean temperature (Tmean) in different biomes. Results showed a trend of advanced SOS in 81.7% of pixels in the North China Plain, with an average rate of −0.5 days/yr. Negative correlations were found between preseason SPEI and SOS in 72.1% of the study region, and the SOS of grassland showed the least resistance to drought. Interannual variations of SOS were triggered by Tmin more than by Tmax in the North China Plain. Multiple regression analysis exhibited that a 1 °C increase in Tmin would advance SOS by 10.5, 7.6, 2.9, 2.1 days for wheat, other crops, forests, and grasslands, indicating warming displayed greater effects on advancing the SOS of wheat. Considering the coupled effects of preseason drought and warming on spring phenology, future warming would trigger earlier spring green-up, while drought might slow the trend. Besides, nonlinear responses of SOS to preseason SPEI and Tmin along the humidity gradient were discovered. This research provides a new reference for the biome-specific and nonlinear responses in phenology models to promote the understanding of phenology changes, contributing to ecosystem management under future global-change-type drought.

Temperature reconstruction based on 361 year old dendrochronology of Platycladus orientalis (L.) franco in the Wula Mountains, China

The northern edge of the East Asian monsoon region is also a transition zone of temperate continental and monsoon climate, which is a sensitive zone of global climate and ecological environment change. It is an urgent problem to find out the long-term climate change rules of this region. Using 101 tree core samples obtained from 54 trees, a 343-year tree-ring width chronology of the Platycladus orientalis (L.) Franco (1673–2016) in the Wula Mountains, Inner Mongolia, China was established. The analysis shows that the radial growth of P. orientalis is closely related to hydrothermal conditions, the average minimum temperature and relative humidity are the main factors that determine the growth of P. orientalis. Based on the strong correlation between the tree-ring indices and the annual average minimum temperature (r = −0.870, p < 0.001), we reconstructed an average annual minimum temperature series from 1673 to 2016 using a linear regression equation, and the reconstructed equation can explain 75.724% of the variance, respectively. According to the data from the past 343 years, the changes in the annual average minimum temperature series had the cycles of 58.6-, 7.7-, 3.4-, 3.1-, 2.2-, and 2.1-years; the series showed three warm periods (1824–1830, 1909–1922, and 1986–2011) and 4 cold periods (1703–1712, 1731–1738, 1754–1763, and 1937–1951). The low temperature periods recorded in the reconstructed series for the 17th and 18th centuries are consistent with the Little Ice Age that occurred in the northern hemisphere, and the heating rate significantly increased at the end of the 20th century. In addition, the cold and warm periods recorded by the reconstruction result is basically consistent with the extreme climate events recorded in the historical documents of the region and the reconstruction results in other regions. In this paper, the world's first chronology of P. orientalis tree ring width was established. A historical sequence of annual average minimum temperature of 343 years was reconstructed in a typical region of the East Asian monsoon climate. It fills in the blank of reconstruction sequence and variation characteristics of mean minimum temperature in the northern edge of East Asian monsoon and transition zone of temperate continental and monsoon climate in recent four centuries.

Temporospatial Flavonoids Metabolism Variation in Ginkgo biloba Leaves.

Ginkgo (Ginkgo biloba L.) is a high-value medicinal tree species characterized by its flavonoids beneficial effects that are abundant in leaves. We performed a temporospatial comprehensive transcriptome and metabolome dynamics analyses of clonally propagated Ginkgo plants at four developmental stages (time: May to August) across three different environments (space) to unravel leaves flavonoids biosynthesis variation. Principal component analysis revealed clear gene expression separation across samples from different environments and leaf-developmental stages. We found that flavonoid-related metabolism was more active in the early stage of leaf development, and the content of total flavonoid glycosides and the expression of some genes in flavonoid biosynthesis pathway peaked in May. We also constructed a co-expression regulation network and identified eight GbMYBs and combining with other TF genes (3 GbERFs, 1 GbbHLH, and 1 GbTrihelix) positively regulated the expression of multiple structural genes in the flavonoid biosynthesis pathway. We found that part of these GbTFs (Gb_11316, Gb_32143, and Gb_00128) expressions was negatively correlated with mean minimum temperature and mean relative humidity, while positively correlated with sunshine duration. This study increased our understanding of the molecular mechanisms of flavonoids biosynthesis in Ginkgo leaves and provided insight into the proper production and management of Ginkgo commercial plantations.

Analysis of the effects of climate, host resistance, maturity and sowing date on wheat stem rust epidemics

Under appropriate environmental conditions, stem rust (caused by Puccinia graminis Pers.:Pers. f. sp. tritici) is a destructive disease of wheat crops worldwide. Although fungicide application and host genotype resistance are the most commonly used methods to control wheat stem rust, efficient agronomic methods are needed to lower disease management expenses and improve sustainability of wheat production. However, an understanding of highly effective agronomic practices to control stem rust is still lacking. From 2013 to 2017, 282 wheat-stem-rust progress curves were studied using three agronomic, three climatic, and two disease variables at plot scale in Kermanshah province, Iran. Cultivar, sowing date, and disease-assessment time significantly affected stem rust severity. From principal component analysis (PCA), three principal components explained 79% of data variance. According to PCA and multiple regression model, AUDPC corresponded with disease-onset and maturity date, mean minimum temperature and number of rainy days over designated spring months, number of days with minimum temperature within 5–20 °C and maximum relative humidity above 60%, resistance index, and sowing date. These new findings suggested improvement of current predicting models by involving dates of maturation and sowing, and wheat resistance besides rainfall-temperature-wetness variables for more effective, economic and sustainable management of stem rust epidemics.

Evaluation and Comparison of the Effectiveness Rate of the Various Meteorological Parameters on UNEP Aridity Index Using Backward Multiple Ridge Regression

Climate changes and its undesirable impacts (such as melting glaciers, the occurrence of floods, hurricanes and droughts, etc.) are among the most important disasters that human beings have faced in recent decades. Considering the important role of the meteorological parameters on climate change, in this research the effectiveness rate of various meteorological parameters including the mean minimum and maximum annual temperature (Max-Temp and Min-Temp), the mean annual temperature (M-Temp), the mean annual sunshine (Sunshine), the mean annual relative humidity (Humidity), the mean annual wind speed (Wind) and the mean of annual precipitation (Rainfall) on United Nations Environmental Programme (UNEP) aridity index was assessed and prioritized using the Backward Multiple Ridge Regression (BMRR). In this study, the meteorological data series of 25 synoptic stations in Iran with different climate conditions during 1967–2017 was used. The results indicated that the BMRR method had a nice capability to predict the UNEP index using the above-mentioned meteorological parameters (the linear regression between observed and predicted the UNEP index had no difference with perfect reliable line (Y = X) at 0.05 significant levels and the R2 between two mentioned data series were significant at 0.01 levels at all stations). According to the results, Rainfall, Wind and Max-Temp parameters were the most effective parameters on the UNEP aridity index, respectively and the Min-Temp, M-Temp and Sunshine parameters were the least effective parameters on the UNEP index, respectively. Therefore, it is suggested that all human activities that have direct or indirect effects in the increasing temperature and reducing the rainfall must be revised and optimized based on the principles of sustainable development.

Effects of the invasive plant Xanthium strumarium on diversity of native plant species: A competitive analysis approach in North and Northeast China.

Xanthium strumarium is native to North America and now has become one of the invasive alien species (IAS) in China. In order to detect the effects of the invader on biodiversity and evaluate its suitable habitats and ecological distribution, we investigated the abundance, relative abundance, diversity indices, and the number of the invasive and native plants in paired invaded and non-invaded quadrats in four locations in North and Northeast China. We also analyzed the effects of monthly mean maximum and minimum temperatures, relative humidity (%), and precipitations (mm). Strong positive significant (P < 0.01) correlation and maximum interspecific competition (41%) were found in Huailai between invaded and non-invaded quadrats. Shannon’s Diversity Index showed that non-invaded plots had significantly (P < 0.05) more diversified species than invaded ones. The significant (P < 0.05) Margalef’s Richness Index was found in Huailai and Zhangjiakou in non-invaded recorded heterogeneous nature of plant communities. Similarly, significant (P < 0.05) species richness found in Huailai and Zhangjiakou in non-invaded quadrats compared to invaded ones. Maximum evenness of Setaria feberi (0.47, 0.37), Seteria viridis (0.43) found in Fushun and Zhangjiakou recorded more stable in a community compared to other localities. Evenness showed positive relationship of Shannon Entropy within different plant species. The higher dissimilarity in plant communities found in Huailai (87.06%) followed by Yangyuan (44.43%), Zhangjiakou (40.13%) and Fushun (29.02%). The significant (P < 0.01) value of global statistics R (0.943/94.3%) showed high species diversity recorded in Huailai followed by Zhangjiakou recorded by non-metric multidimensional scaling and analysis of similarity between invaded and non-invaded plots. At the end it was concluded that the diversity indices reduced significantly (P < 0.05) in invaded quadrats indicated that native plant species become less diverse due to X. strumarium invasion. The degrees of X. strumarium invasion affected on species richness resulted to reduce diversity indices significantly in invaded quadrats.