Correlation between Climatic Factors and Genetic Diversity of Phrynocephalus forsythii

Global climate change is a threat to animals in nearly all biomes and ecosystems, especially for ectotherm whose life activities highly depend on environmental thermal regime. Population genetic diversity which is essential for adaptation to environmental change is a useful index for long-term species survival. In this paper, genetic diversity of eight Phrynocephalus forsythii population which distributed in Tarim Basin, China, were evaluated based on three mtDNA gene and its correlation with environment factors were investigated using RDA. Our result revealed that, the level of genetic diversity of P. forsythii populations was related to its location but there was no significant correlation between genetic distances and geographic distances in P. forsythii. However, we find that mtDNA of P. forsythii was subjected to selection pressure during evolution and population genetic diversity was significantly positively related to variation coefficient of rainfall(VCR) and altitude(AL), while significantly negatively related to longitude(N) and annual average temperature(AAT). Our result supported the previous prediction that excessive ambient heat is a threat to P. forsythii.

Relationship between age, size, fecundity and climatic factors in Panax wangianus an endangered medicinal plant in the sacred grove forest of North-East India

Panax wangianus （Syn. Panax pseudoginseng） S. C. Sun （Araliaceae） is a critically endangered, medicinal plant of North-East India. The objective of this study was to determine how plant size affects flowering phenology and to evaluate the effect of climatic factors on flowering, fruiting and seed production. Data on vegetative and repro- ductive characters were monitored from 2016 individuals of Panax wangianus population in Law Lyngdoh, Smit sacred grove in Nongkrem, Shillong, India. Leaflet area was measured by a planimeter. Size variables of both vegetative and reproductive traits in different age classes were measured. Climatic factors were recorded from 2007 to 2009. Age was recorded by counting the number of bud scale scars on the rhizome. Light intensity and relative humidity were measured using a photometer, LiCor Model LI-189 and thermohygrometer respectively. Different climatic variables are correlated with vegetative and reproductive phenological events. Statistical analysis revealed that a strong positive correlation was observed between the age versus vegetative and reproductive characters, except 1%–2% plants showed neoteny. Morphological variations were observed in natural conditions on the basis of the number of prong and carpellate conditions. Phenological status revealed that most of the individuals of the age class 35–50 years and above 50 years contributed the most to flowering, fruiting and seed production. Age class was significant to predict the size of the plant and its reproductive capacity. Climatic factors such as temperature, precipitation and relative humidity show synergistic effect on both the vegetative and reproductive phases in Panax wangianus in the undisturbed Nongkrem sacred grove. The color of flowers of P. wangianus also varied depending upon the sunlight intensity. Therefore, in the view of conservationand management, the age class of 35–50 years and above 50 years is the most important for population sustainability.

Maize grain yield and water use efficiency in relation to climatic factors and plant population in northern China

Water scarcity has become a limiting factor for increasing crop production.Finding ways to improve water use efficiency(WUE)has become an urgent task for Chinese agriculture.To understand the response of different maize populations to changes in precipitation and the effects of changes in maize populations on WUE,this study conducted maize population experiments using maize hybrids with different plant types(compact and semi compact)and different planting densities at 25 locations across China.It was found that,as precipitation increased across different locations,maize grain yield first increased and then decreased,while WUE decreased significantly.Analyzing the relationship between WUE and the main climatic factors,this study found that WUE was significantly and negatively correlated with precipitation(R(daily mean precipitation)and R(accumulated precipitation))and was positively correlated with temperature(TM(daily mean maximum temperature),T_(M-m)(T_(m),daily mean minimum temperature)and GDD(growing degree days))and solar radiation(Ra(daily mean solar radiation)and Ra(accumulated solar radiation))over different growth periods.Significant differences in maize grain yield,WUE and precipitation were found at different planting densities.The population densities were ranked as follows according to maize grain yield and WUE based on the multi-site experiment data:60000 plants ha^(-1)(P_(2))>90000 plants ha^(-1)(P_(3))>30000 plants ha^(-1)(P_(1)).Further analysis showed that,as maize population increased,water consumption increased significantly while soil evaporation decreased significantly.Significant differences were found between the WUE of ZD958(compact type)and that of LD981(semi-compact type),as well as among the WUE values at different planting densities.In addition,choosing the optimum hybrid and planting density increased WUE by 21.70 and 14.92%,respectively,which showed that the hybrid played a more significant role than the planting density in improving WUE.Therefore,choosing drought-resistant hybrids could be more effective than increasing the planting density to increase maize grain yield and WUE in northern China.Comprehensive consideration of climatic impacts,drought-resistant hybrids(e.g.,ZD958)and planting density(e.g.,60000 plants ha^(-1))is an effective way to increase maize grain yield and WUE across different regions of China.

Variability of Sea Ice from 2008 to 2019 in the Bohai and Northern Huanghai Sea, China and the Relationship with Climatic Factors

Sea ice has important effect on the marine ecosystem and people living in the surrounding regions in winter.However,the understanding on changes of sea ice in the Bohai and northern Huanghai Sea(BNHS),China is still limited.Based on the images from Visible and InfraRed Radiometer(VIRR)onboard Chinese second generation polar-orbit meteorological series satellites FY-3A/B/C,the sea ice areas in the BNHS were extracted from December 2008 to March 2019,the spatio-temporal distribution charac-teristics of sea ice and the relationship between sea ice area and climatic factors were analyzed,then a preliminary sea ice forecast model based on the climatic factors was developed.The results showed that sea ice area in the BNHS in each December was relatively small and rather high sea ice occurrence probability appeared in the offshore areas in Liaodong Bay and northern Huanghai Sea.The sea ice area in January or February each year was the largest,and sea ice occurred in most of areas in Liaodong Bay and northern Huanghai Sea with rather high probability and in some areas in Bohai Bay and Laizhou Bay with relatively high probability.How-ever,the sea ice area in each March was the smallest,and sea ice was even melted completely occasionally,hence with relatively low occurrence probability in Liaodong Bay.As for the inter-annual variability of sea ice in the BNHS during the research period,the sea ice area was largest in winter 2010/11 and smallest in winter 2014/15,and annual sea ice area presented a decreasing trend.The at-mospheric temperature,western Pacific subtropical high(WPSH),Asia polar vortex(APV),Asian monsoon circulation(AMC)and Eurasian monsoon circulation(EMC)were very important climatic factors for sea ice formation and they had significant correlations with sea ice area.Therefore,a preliminary sea ice forecast model was constructed by using eight climatic factors including western Pacific subtropical high area index(WPSHAI),western Pacific subtropical high intensity index(WPSHII),western Pacific subtro-pical high northern boundary position index(WPSHNBPI),Asia polar vortex area index(APVAI),Asian zonal circulation index(AZCI),Asian meridional circulation index(AMCI),Eurasian zonal circulation index(EZCI)and mean minimum atmospheric tem-perature(MMAT).The model was confirmed to have a robust forecast effect by using F-test and validated sample data.The results are useful for monitoring sea ice with remote sensed data and forecasting sea ice conditions by climatic indices.

Change of Vegetation Cover and Its Relationships with Climatic Factors in Large-area Eucalyptus Introduced Region of Yunnan

Taking Lancang County as a study area with a large area of eucalyptus introduction in Yunnan, spatiotemporal change characteristics of vegetation cover, as well as the relationships between Enhanced Vegetation Index（EVl） and climatic factors （temperature and precipitation） were analyzed by using the data of MODIS-EVI from 2005 to 2010. The results indicated that： （1） The vegetation cover was overall good, and the annual average values of EVl were greater than 0.395 and showed a slow increasing trend from 2005 to 2010 in study area; the monthly average values of EVl ranged from 0.296 to 0.538, and seasonal variability was obvious. Monthly average values of EVl usually fell to the lowest level in February and March, and reached the peak in July and August. From the perspective of space, average EVl over the years significantly varied in different towns of Lancang County. During 2005 -2010, in 92.534% area of total, vegetation coverage change were not obvious; in 7.25% area of total, vegeta- tion becoming better; only in 0.02% area of total, vegetation cover were getting worse. （2） Monthly average values of EVl were significantly correlated with monthly average rainfall in Lancang County. The maxima of monthly average EVI and rainfall appeared in August on summer, while the minima of monthly average EVl and rainfall appeared in February and January on winter respectively. （3） Monthly average EVl was somewhat relative with monthly average temperature. The maxima of monthly average EVl and temperature appeared in June and August respectively, while the minima appeared in January and February respectively.

Investigating the Effect of Climatic Factors of Roshtkhar Town (Khorasan Razavi, Iran) on the Development and Cultivation of Pistachio Using GIS Software

The use of Geographic Information System (GIS) has significantly helped managers provide optimal models of sustainable agricultural development, identify local features related to agricultural production and their proper zoning, identify agricultural needs and constraints and finally provide the appropriate structure of land use. The main purpose of this study was to determine areas capable of cultivating Pistachio according to the parameters affecting the Pistachio cultivation in Roshtkhar town. Statistics of meteorological stations of the town were taken from Meteorology Organization of Khorasan Razavi for the period of 1989-2010 in order to determine climatic parameters required to cultivate Pistachio. For mapping surface elevation, slope, aspect, and TIN of the geographic organization of armed forces with a scale of 1:250,000 topographic maps were used. For mapping vegetation and land use in the area under study, land capability map of the area on a scale of 1:250,000 from the institute of soil and water was used. Also information on cultivation and annual production of agricultural statistics, published by Agriculture was used. Finally, it was concluded that the northeast and southwest of Roshtkhar town are the most prone areas to cultivate Pistachio.

Radial growth response of Pinus densiflora and Quercus spp.to topographic and climatic factors in South Korea

Aims This study aimed to develop radial growth models and to predict the potential spatial distribution of Pinus densiflora(Japanese red pine)and Quercus spp.(Oaks)in South Korea,considering topographic and climatic factors.Methods We used a dataset of diameter at breast height and radial growth estimates of individual trees,topographic and climatic factors in systematic sample plots distributed over the whole of South Korea.On the basis that radial growth is attributed primarily to tree age,we developed a radial growth model employing tree age as an explanatory variable.We estimated standard growth(SG),defined as radial growth of the tree at age 30,to eliminate the influence of tree age on radial growth.In addition,SG estimates including the Topographic Wetness Index,temperature and precipitation were calculated by the Generalized Additive Model.Important Findings As a result of variogram analysis of SG,we found spatial autocorrelation between SG,topographic and climatic factors.Incremental temperature had negative impacts on radial growth of P.densiflora and positive impacts on that of Quercus spp.Precipitation was associated with positive effects on both tree species.Based on the model,we found that radial growth of P.densiflora would be more vulnerable than that of Quercus spp.to climatic factors.Through simulation with the radial growth model,it was predicted that P.densiflora stands would be gradually replaced with Quercus spp.stands in eastern coastal and southern regions of South Korea in the future.The models developed in this study will be helpful for understanding the impact of climatic factors on tree growth and for predicting changes in distribution of P.densiflora and Quercus spp.due to climate change in South Korea.

Which climatic factors limit radial growth of Qilian juniper at the upper treeline on the northeastern Tibetan Plateau？

There are differing views regarding the climatic factors that limit radial growth of Qilian juniper （Juniperus przewalskii Kom.） at the upper treelines on the northeastern Tibetan Plateau. In this study, trees from an upper tree northeastern Tibetan Plateau were selected to limits the radial growth of Qilian juniper. Using ine site in the Anyemaqen Mountains of the present new evidence that low temperature a signal-free regional curve standardization （SF-RCS） method, a ring-width chronology for Qilian juniper was developed extending from AD 1082 to 2010. The results of correlation analysis between tree-ring index and instrumental climatic variables showed that both winter （December in the previous year and January in the current year） and summer （July and August in the current year） temperatures were signifi- cantly and positively correlated with the tree-ring index. Precipitation in June was also significantly and positively correlated with the tree-ring index, but was not as important as low temperature in controlling tree growth. To test the key limiting climatic factor for tree radial growth at different altitudes, an indicator termed the ＂relative distance to upper treeline＂ （RDUT） was developed to quantify the representativeness of collected samples for the forest＇s upper treeline. The RDUT showed that the upper 20% of the forest belt may be an important boundary in terms of capturing the temperature signal from tree-ring width at the upper treelines on the northeastern Tibetan Plateau. Our findings enhance the existing understanding that temperature is the limiting factor at upper treelines on the northeastern Tibetan Plateau, and will be useful in the reconstruction of past temperature in future studies.

Impacts of landscape and climatic factors on snow cover in the Altai Mountains,China

Snow properties and their changes are crucial to better understanding of hydrological processes,soil thermal regimes,and surface energy balances.Reliable data and information on snow depth and snow water equivalent(SWE)are also crucial for water resource assessments and socio-economic development at local and regional scales.However,these data are extremely limited and unreliable in northern Xinjiang,China.This study thus aims to investigate spatial variations of snow depth,SWE,and snow density based on winter snowfield surveys during 2015 through 2017 in the Altai Mountains,northwestern China.The results indicated that snow depth(25-114 cm)and SWE(40-290 mm)were greater in the alpine Kanas-Hemu region,and shallow snow accumulated(9-42 cm for snow depth,26-106 mm for SWE)on the piedmont sloping plain.While there was no remarkable regional difference in the distribution of snow density.Snow property distributions were strongly controlled by topography and vegetation.Elevation and latitude were the most important factors affecting snow depth and SWE,while snow density was strongly affected by longitude across the Altai Mountains in China.The influence of topography on snow property distributions was spatially heterogenous.Mean snow depth increased from 13.7 to 31.2 cm and SWE from 28.5 to 79.9 mm,respectively,with elevation increased from 400 to 1000 m a.s.l.on the piedmont sloping plain.Snow depth decreased to about 15.1 cm and SWE to about 28.5 mm from 1000 to 1800 m a.s.l.,then again increased to about 98.1 cm and 271.7 mm on peaks(-2000 m a.s.l.)in the alpine Kanas-Hemu.Leeward slopes were easier to accumulate snow cover,especially on north-,east-,and southeast-facing slopes.Canopy interception was also the cause of the difference in snow distribution.Snow depth,SWE,and snow density in forests were reduced by 8%-53%,2%-67%and-4%to+48%,respectively,compared with surrounding open areas.Especially when snow depth was less than 40 cm,snow depth and SWE differences in forests were more exaggerated.This study provides a basic data set of spatial distributions and variations of snow depth,SWE and snow density in the Altai Mountains,which can be used as an input parameter in climate or hydrological models.These first-hand observations will help to better understand the relationship between snow,topography and climate in mountainous regions across northern China and other high-mountain Asian regions.

Changes in Climate Factors and Their Impacts on Wind Erosion Climatic Erosivity in Farming-pastoral Zone of Northern China

Climate change can affect wind erosion power and hence induce changes in wind erosion rates.In this study,the wind erosion climate factor(C-factor),proposed by the Food and Agriculture Organization of the United Nations,was used to assess the impact of changes in climate on wind erosion climatic erosivity.The Mann-Kendall test was employed to detect trends in the C-factor during the period of 1961–2017 in the farming-pastoral zone of northern China.Sensitivity analysis was used to determine the sensitivity of the C-factor to changes in key climate factors.Furthermore,a comparison of the contributions of different climate factors was carried out to understand their impact on changes in the C-factor.The results indicated that most of the surveyed region exhibited decreasing trends in wind speed at a confidence level of 90%,while maximum and minimum temperatures showed increasing trends throughout the study area.As a consequence of decreasing wind speed,the annual C-factor exhibited significant decreasing trends,with a mean slope of–0.58/yr.Seasonal analysis revealed that in most regions,the changes in the C-factor had significant decreasing trends in spring,winter,and autumn,while in more than two-thirds of the study area,no significant change trends in the C-factor were detected in summer at a confidence level of 90%.Sensitivity analysis showed that the C-factor was most sensitive to wind speed,and that the sensitivity coefficients from July to September were much higher than those in other months.Contribution analysis revealed that,for most stations,wind speed(with greater values of sensitivity coefficients)was the dominant factor in the change of C-factor,while for some stations,the minimum temperature made the most contribution to the C-factor’s change due to its dramatic changes during the study period.Although the minimum temperature sensitivity coefficient was the lowest of all the sensitivity coefficients,it is urgent to evaluate the expected impact of minimum temperature due to its possible changes in the future.

Analysis of Relation between Variation Characteristics and Climatic Influencing Factors of Shallow Ground Temperature in Shijiazhuang

Based on the daily observation data of shallow ground temperature, total cloud cover, precipitation, evaporation capacity and frozen soil of 5 stations in Shijiazhuang from 1981 to 2010, using methods such as linear trend and complete correlation coefficient, relation between variation characteristics and climatic influencing factors of shallow ground temperature was analyzed to lay the foundation for studying impact factors of shallow ground temperature and provide references for daily maintenance of automatic observation business. The results showed that fluctuant variability and fluctuant range of mean shallow layer ground temperature in Shijiazhuang became smaller with soil layer being deeper for all years and seasons, and the fluctuant variability was maximal in spring and minimal in winter, while the fluctuant range was maximal in summer and minimal in winter; mean shallow layer ground temperature for all years had a warming trend with an obvious warming trend in winter, and warming range in winter was smaller and the extent was weaker with soil layer being deeper while a cooling trend occurred in summer; there was a coincident trend between total cloud cover at night and shallow ground temperature in winter, and between evaporation capacity and shallow ground temperature in summer, while there was an inconsistent trend between maximum depth of frozen soil, period of freezing weather and shallow ground temperature in winter, and between total cloud cover in the davtime, orecioitation and shallow around temperature in summer.

Modeling Study of the Evolution of the Climate Crisis over Time

The research proposal has the following scope. In relation to the general objective, the aim is to model the evolution of the climate crisis over time taking as variables global warming, greenhouse gases, atmospheric temperature and ocean temperature, as well as the continuity of the natural phenomena in terms of their measurement, temporality and projection. To achieve the above, the description of the following specific objectives is proposed: - Identify the variables corresponding to the climate crisis, their relationship and correlation between them;- Develop projection models with mathematical and statistical arrangements to project them in a given time and, in this way, - Propose mitigation measures for different unfavorable scenarios. The main variables that are currently directly linked to Climate Change are: CO2, the atmospheric index, precipitation, temperature and wind speed. The correlation that exists between climatic elements is very high, both in historical behavior and projected behavior for 2035, their correlation is estimated at 0.90, 0.95, 0.93 and 91 respectively. The mathematical models used to manipulate the historical and projected analysis of the variables studied: are the normal arrangements, this ensures that the values can be used on a common scale;Then there is the analysis of the historical variables using the linear trend, and finally there is the analysis of the variables projected to the year 2035 using the polynomial trend. In both situations, the direct relationship of greenhouse gases, mainly CO2, is directly related to the variations of the variables over time, which is a very worrying result because we can no longer talk about climate change, but rather about CLIMATE CRISIS. To a large extent, a change in the paradigm of exploitation of the resources of our mother earth is required. Alert in an SOS manner to the great powers, which make reasonable use of technology, for this attenuation measures are proposed.

Sensitivity of runoff to climatic variability in the northern and southern slopes of the Middle Tianshan Mountains,China

Temperature and precipitation play an important role in the distribution of intra-annual runoff by influencing the timing and contribution of different water sources.In the northern and southern slopes of the Middle Tianshan Mountains in China,the water sources of rivers are similar;however,the proportion and dominance of water sources contributing to runoff are different.Using the Manas River watershed in the northern slope and the Kaidu River watershed in the southern slope of the Middle Tianshan Mountains as case studies,we investigated the changes in annual runoff under climate change.A modified hydrological model was used to simulate runoff in the Kaidu River and Manas River watersheds.The results indicated that runoff was sensitive to precipitation variation in the southern slope and to temperature variation in the northern slope of the Middle Tianshan Mountains.Variations in temperature and precipitation substantially influence annual and seasonal runoff.An increase in temperature did not influence the volume of spring runoff;but it resulted in earlier spring peaks with higher levels of peak flow.Damages caused by spring peak flow from both slopes of the Middle Tianshan Mountains should be given more attention in future studies.

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

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

Advancing Malaria Prediction in Uganda through AI and Geospatial Analysis Models

The resurgence of locally acquired malaria cases in the USA and the persistent global challenge of malaria transmission highlight the urgent need for research to prevent this disease. Despite significant eradication efforts, malaria remains a serious threat, particularly in regions like Africa. This study explores how integrating Gregor’s Type IV theory with Geographic Information Systems (GIS) improves our understanding of disease dynamics, especially Malaria transmission patterns in Uganda. By combining data-driven algorithms, artificial intelligence, and geospatial analysis, the research aims to determine the most reliable predictors of Malaria incident rates and assess the impact of different factors on transmission. Using diverse predictive modeling techniques including Linear Regression, K-Nearest Neighbor, Neural Network, and Random Forest, the study found that;Random Forest model outperformed the others, demonstrating superior predictive accuracy with an R2 of approximately 0.88 and a Mean Squared Error (MSE) of 0.0534, Antimalarial treatment was identified as the most influential factor, with mosquito net access associated with a significant reduction in incident rates, while higher temperatures correlated with increased rates. Our study concluded that the Random Forest model was effective in predicting malaria incident rates in Uganda and highlighted the significance of climate factors and preventive measures such as mosquito nets and antimalarial drugs. We recommended that districts with malaria hotspots lacking Indoor Residual Spraying (IRS) coverage prioritize its implementation to mitigate incident rates, while those with high malaria rates in 2020 require immediate attention. By advocating for the use of appropriate predictive models, our research emphasized the importance of evidence-based decision-making in malaria control strategies, aiming to reduce transmission rates and save lives.

Relationship between multi-scale climate factors and performance of ecological engineering on the Loess Plateau, China

The long-term “Grain-to-Green Program” (GGP) on China’s Loess Plateau is a major global ecological engineering project which has significantly boosted vegetation renewal. Some studies have found that the rate of restoration is quite rapid during the implementation of ecological engineering, however, the influence of multi-scale climatic conditions on the performance of ecological engineering is unclear. In this study, multiple sources of remote sensing data were used to estimate the dynamics of vegetation structural and functional indicators, water-related local climatic factors, and atmospheric circulation factors. These datasets were also used to detect possible causes for vegetation restoration on the Loess Plateau over the past 20 years. The results show that widespread increases in rates of normalized difference vegetation indexes (NDVI), leaf area indexes (LAI), gross primary production (GPP), and aboveground biomass carbon (ABC) during 2000–2016 were significantly higher than before 2000. GPP was significantly correlated with rainfall and surface runoff on a monthly scale, and there were significant positive correlations between GPP and atmospheric circulation. Our results demonstrate that both vegetation structural and functional indicators rapidly increase, and ecological engineering greatly accelerated vegetation restoration after 2000. Local climatic conditions and atmospheric circulation patterns enhance vegetation growth and impact of ecological engineering.

Modeling the Influence of Climate Factors on Malaria Transmission Dynamics in North Kordofan State, Sudan

Background: Despite great efforts by the government to control malaria in Sudan, the disease is the most significant human disease and was widespread in North Kordofan State. Morbidity and mortality of the disease are increasing in the State. Usually, the disease reached its peak after rainy season. This study aims to estimate the role of climate factors on malaria transmission dynamic by modeling the relationship between malaria cases and climatic variables, such as rainfall, relative humidity, and temperature, in Kordofan State. Methods: We used Pearson correlation coefficient and an ordinary least square method to assess this relationship. Results: The results show that there are statistically significant associations between malaria cases and rainfall, relative humidity, and minimum temperature (P-value < 0.001). The regression analysis results suggest that the appropriate model for predicting malaria incidence includes malaria cases lagged by one month, maximum temperature, and minimum temperature. This model explained 72% of the variance in monthly malaria incidence. Conclusion: The results of this study suggest that climatic factors have potential use for malaria prediction in the State.

Drought Change Trend Using MODIS TVDI and Its Relationship with Climate Factors in China from 2001 to 2010

Changes in drought trends and its relationship with climate change in China were examined in this study. The temperature vegetation drought index （TVDI） datasets recorded during 2001 to 2010 in China were constructed by using the moderate-resolution imaging spectroradiometer （MODIS） data, and the temporal and spatial variations in drought were analyzed. In addition, the mean temperature, mean precipitation, mean relative humidity, and mean sunshine duration data collected from 557 local weather stations in China were analyzed. The relationships between drought and these climate factors were also analyzed by using correlation analysis and partial correlation analysis. Changes in drought tendency were shown to differ among four regions throughout the country. The lfuctuations in climate in the regions of northeastern China, Qinling-Huaihe, and central Qinghai were caused by the increase in soil moisture, and that in southern Tibet was caused by the intensiifcation of drought. Meteorological factors exhibited varied effects on drought among the regions. In southern China, the main inlfuential factor was temperature;other factors only showed minimal effects. That in the northern and northwestern regions was sunshine duration, and those in the Qinghai-Tibet Plateau were relative humidity and temperature.

Impact of climate factors on runoff in the Kaidu River watershed:path analysis of 50-year data

Runoff formation is a complex meteorological-hydrological process impacted by many factors,especially in the inland river basin.Based on the data of daily mean air temperature,precipitation and runoff during the period of 1958-2007 in the Kaidu River watershed,this paper analyzed the changes in air temperature,precipitation and runoff and revealed the direct and indirect impacts of daily air temperature and precipitation on daily runoff by path analysis.The results showed that mean temperature time series of the annual,summer and autumn had a significant fluctuant increase during the last 50 years（P 0.05）.Only winter precipitation increased significantly（P 0.05） with a rate of 1.337 mm/10a.The annual and winter runoff depthes in the last 50 years significantly increased with the rates of 7.11 mm/10a and 1.85 mm/10a,respectively.The driving function of both daily temperature and precipitation on daily runoff in annual and seasonal levels is significant in the Kaidu River watershed by correlation analysis.The result of path analysis showed that the positive effect of daily air temperature on daily runoff depth is much higher than that of daily precipitation in annual,spring,autumn and winter,however,the trend is opposite in summer.