The role of climate factors in geographic variation in body mass and wing length in a passerine bird

Background: Geographic variation in body size is assumed to reflect adaptation to local environmental conditions. Although Bergmann's rule is usually sufficient to explain such variation in homeotherms, some exceptions have been documented. The relationship between altitude, latitude and body size, has been well documented for some vertebrate taxa during the past decades. However, relatively little information is available on the effects of climate variables on body size in birds.Methods: We collected the data of 267 adult Eurasian Tree Sparrow(Passer montanus) specimens sampled at 48 localities in China's mainland, and further investigated the relationships between two response variables, body mass and wing length, as well as a suit of explanatory variables, i.e. altitude, latitude, mean annual temperature(MAT), annual precipitation(PRC), annual sunshine hours(SUN), average annual wind speed(WS), air pressure(AP) and relative humidity(RH).Results: Our study showed that(1) although the sexes did not differ significantly in body mass, males had longer wings than females;(2) body mass and wing length were positively correlated with altitude but not with latitude;(3) body mass and wing length were negatively correlated with AP and RH, but not significantly correlated with WS. Body mass was positively correlated with SUN and inversely correlated with MAT. Wing length was not correlated with MAT in either sex, but was positively correlated with SUN and negatively correlated with PRC in male sparrows;(4) variation in body mass could be best explained by AP and SUN, whereas variation in wing length could be explained by RH and AP in both sexes. In addition, variation in male sparrows can be explained by SUN, WS and PRC but not in females.Conclusions: Two different proxies of body size, body mass and wing length, correlated with same geographic factors and different climate factors. These differences may reflect selection for heat conservation in the case of body mass, and for efficient flight in the case of wing length.

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.

Effects of Climate Factors in Greenhouses on the Growth Development and Quality of Houttuynia cordata Thunb.

[Objectives]This study was conducted to demonstrate whether greenhouse planting can solve the problem of insufficient supply of fresh H.cordata Thunb.in winter and spring.[Methods]The effects of meteorological factors on the growth and quality of H.cordata Thunb.were analyzed.[Results]The highest temperature and lowest temperature in greenhouses were 6-12℃and 5-10℃higher than those in the open fields,respectively,and the average temperature difference between the greenhouses and the open fields was large in the early stage,but small in the late stage.The effective accumulated temperature≥10℃was 3463℃in the greenhouses and 2046℃in the open fields.Although the humidity in the open fields was higher than that in the greenhouses,the humidity in the greenhouses was relatively stable and that in the open field changed greatly.The light intensity of the greenhouses was lower than that of the open fields.In terms of the periods from film covering day to seedling emergence,seedling emergence to full emergence,and full emergence to crop closure,greenhouse planting was shortened by 47,11,and 5 d,respectively,compared with open field planting,but the period from crop closure to flowering was extended by 40 d.The plant height of the plants planted in the greenhouses reached 0.1 cm on January 7,while those planted in the open fields did not have seedlings until February 25,and the plant height,daily growth rate,yield and effective components in volatile oil of the plants planted in the greenhouses were significantly higher than those planted in the open fields.The growth,development and quality of H.cordata Thunb.reached the extremely significant or significant level with temperature,but had no significant correlation with humidity and light intensity,indicating that temperature had the greatest impact on the growth,development and quality of H.cordata Thunb.when planted in the greenhouses.[Conclusions]This study provides a theoretical basis for protected cultivation and explores new planting methods for the further development of its industry.

Assessing the Effect of Climate Factors on Dengue Incidence via a Generalized Linear Model

Changes in climate factors such as temperature, rainfall, humidity, and wind speed are natural processes that could significantly impact the incidence of infectious diseases. Dengue is a widespread disease that has often been documented when it comes to the impact of climate change. It has become a significant concern, especially for the Malaysian health authorities, due to its rapid spread and serious effects, leading to loss of life. Several statistical models were performed to identify climatic factors associated with infectious diseases. However, because of the complex and nonlinear interactions between climate variables and disease components, modelling their relationships have become the main challenge in climate-health studies. Hence, this study proposed a Generalized Linear Model (GLM) via Poisson and Negative Binomial to examine the effects of the climate factors on dengue incidence by considering the collinearity between variables. This study focuses on the dengue hot spots in Malaysia for the year 2014. Since there exists collinearity between climate factors, the analysis was done separately using three different models. The study revealed that rainfall, temperature, humidity, and wind speed were statistically significant with dengue incidence, and most of them shown a negative effect. Of all variables, wind speed has the most significant impact on dengue incidence. Having this kind of relationships, policymakers should formulate better plans such that precautionary steps can be taken to reduce the spread of dengue diseases.

Solanum lycopersicum: Novelties for Climate Factors and Its Agronomic Management for High Yields

The intensive production of vegetables such as tomatoes depends on various strategies to achieve high yields.Purpose of this manuscript is to provide scientific and technological strategies for the intensive production of tomato or other vegetables in mega-production factories. However, with the advancement of knowledge, new improvements in the strategies will be incorporated. We have carried out research related to growth and yield variables in S. Lycopersicum. From this research we have worked on the intensive production of this noble vegetable at an industrial level. The results obtained are improvements in the production system. The improvements include the selection of the appropriate variety, germination and development of seedlings in a certified nursery. Trans-plantation in soil or hydroponics. The conditions of nutrient applications from the irrigation head system. The ventilation system and monitoring of climatic factors both day and night (temperature and relative humidity). Monitoring of macro- and micronutrients in the plant system, including Ca, K, Fe, and Zn. Soil fertility analyzes should include: primary and secondary macronutrients (ppm), organic matter (OM), EC, pH, bulk density (BD), and cation exchange capacity (CEC). The nutritional diagnosis to confirm ranges of sufficiency. As a tool in plant nutrition programs, foliar application can include biostimulants and growth regulators. The foregoing can be considered strategies for the integral management of the tomato crop.

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.

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.

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.

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.

Variability in the climate-radial growth correlation of Pinus massoniana of different diameter classes

The physiological characteristics of trees change with age,suggesting that growth-related climate signals vary over time.This study aimed to clarify the impacts of different diameter classes on the chronological characteristics of Pinus massoniana Lamb.and its response to climatic factors.Chronologies of P inus massoniana were established in small diameter(14.1 cm),middle diameter(27.3 cm),and large diameter(34.6 cm)trees according to dendrochronology.The results show that:(1)radial growth of different diameter classes had varied characteristics and climate sensitivities;(2)radial growth of small diameter trees was affected by climatic factors of the previous and the current year,while large diameter trees were mainly affected by climatic factors of the current year;and(3)precipitation and temperature were key factors that restricted the radial growth of small and large diameter trees,respectively.

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.

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.

Interannual Variation and Statistical Prediction of Summer Dry and Hot Days in South China from 1970 to 2018

The frequent occurrence of dry and hot(DH)days in South China in summer has a negative impact on social development and human health.This study explored the variation characteristics of DH days and the possible reasons for this knotty problem.The findings revealed a notable increase in the number of DH days across most stations,indicating a significant upward trend.Additionally,DH events were observed to occur frequently.The number of DH days increased during 1970-1990,decreased from 1991 to 1997,and stayed stable after 1997.The key climate factors affecting the interannual variability of the number of DH days were the Indian Ocean Basin warming(IOBW)in spring and the East Asian Summer Monsoon(EASM).Compared with the negative phase of IOBW,in the positive phase of IOBW,500 hPa and 850 hPa geopotential height enhanced,the West Pacific subtropical high strengthened and extended abnormally to the west,more solar radiation reached the surface,surface outgoing longwave radiation increased,and there was an anomalous anticyclone in eastern South China.The atmospheric circulation characteristics of the positive and negative phases of ESAM were opposite to those of IOBW,and the abnormal circulation of the positive(negative)phases of ESAM was unfavorable(favorable)for the increase in the number of DH days.A long-term prediction model for the number of summer DH days was established using multiple linear regression,incorporating the key climate factors.The correlation coefficient between the observed and predicted number of DH days was 0.65,and the root-mean-square error was 2.8.In addition,independent forecasts for 2019 showed a deviation of just 1 day.The results of the independent recovery test confirmed the stability of the model,providing evidence that climatic factors did have an impact on DH days in South China.

Phylogenetic diversity of eastern Asia-eastern North America disjunct plants is mainly associated with divergence time

The underlying causes of biodiversity disparities among geographic regions have long been a fundamental theme in ecology and evolution.However,the patterns of phylogenetic diversity(PD) and phylogenetic beta diversity(PBD) of congeners that are disjunctly distributed between eastern Asia-eastern North America(EA-ENA disjuncts) and their associated factors remain unknown.Here we investigated the standardized effect size of PD(SES-PD),PBD,and potentially associated factors in 11natural mixed forest sites(five in EA and six in ENA) where abundant EA-ENA disjuncts occur.We found that the disjuncts in ENA possessed higher SES-PD than those in EA at the continental scale(1.96vs-1.12),even though the number of disjunct species in ENA is much lower than in EA(128 vs 263).SESPD of the EA-ENA disjuncts tended to decrease with increasing latitude in 11 sites.The latitudinal diversity gradient of SES-PD was stronger in EA sites than in ENA sites.Based on the unweighted unique fraction metric(UniFrac) distance and the phylogenetic community dissimilarity,PBD showed that the two northern sites in EA were more similar to the six-site ENA group than to the remaining southern EA sites.Based on the standardized effect size of mean pairwise distances(SES-MPD),nine of eleven studied sites showed a neutral community structure(-1.96 ≤SES-MPD ≤1.96).Both Pearson’s r and structural equation modeling suggested that SES-PD of the EA-ENA disjuncts was mostly associated with mean divergence time.Moreover,SES-PD of the EA-ENA disjuncts was positively correlated with temperaturerelated climatic factors,although negatively correlated with mean diversification rate and community structure.By applying approaches from phylogenetics and community ecology,our work sheds light on historical patterns of the EA-ENA disjunction and paves the way for further research.

Carbon storage of the forest and its spatial pattern in Tibet,China

The raising concentration of atmospheric CO_2 resulted in global warming.The forest ecosystem in Tibet played an irreplaceable role in maintaining global carbon balance and mitigating climate change for its abundant original forest resources with powerful action of carbon sink.In the present study,the samples of soil and vegetation were collected at a total of 137 sites from 2001 to 2018 in Tibet.Based on the field survey of Tibet's forest resources and 8^(th) forest inventory data,we estimated the carbon storage and carbon density of forest vegetation(tree layer,shrub,grass,litter and dead wood) and soil(0-50 cm) in Tibet.Geostatistical methods combined with Kriging spatial interpolation and Moran's I were applied to reveal their spatial distribution patterns and variation characteristics.The carbon density of forest vegetation and soil in Tibet were 74.57 t ha^(-1) and 96.24 t ha^(-1),respectively.The carbon storage of forest vegetation and soil in Tibet were 344.35 Tg C and 440.53 Tg C,respectively.Carbon density of fir(Abies forest) was 144.80 t ha^(-1) with the highest value among all the forest types.Carbon storage of spruce(Picea forest) was the highest with 99.09 Tg C compared with other forest types.The carbon density of fir forest and spruce forest both increased with the rising temperature and precipitation.Temperature was the main influential factor.The spatial distribution of carbon density of forest vegetation,soil,and ecosystem in Tibet generally showed declining trends from western Tibet to eastern Tibet.Our results facilitated the understanding of the carbon sequestration role of forest ecosystem in the Tibet.It also implied that as the carbon storage potential of Tibet's forests are expected to increase,these forests are likely to serve as huge carbon sinks in the current era of global warming and climate change.

Predicting cutaneous leishmaniasis using SARIMA and Markov switching models in Isfahan, Iran: A time-series study

Objective:To determine the potential effect of environment variables on cutaneous leishmaniasis occurrence using time-series models and compare the predictive ability of seasonal autoregressive integrated moving average(SARIMA)models and Markov switching model(MSM).Methods:This descriptive study employed yearly and monthly data of 49364 parasitologically-confirmed cases of cutaneous leishmaniasis in Isfahan province,located in the center of Iran from January 2000 to December 2019.The data were provided by the leishmaniasis national surveillance system,the meteorological organization of Isfahan province,and Iranian Space Agency for vegetation information.The SARIMA and MSM models were implemented to examine the environmental factors of cutaneous leishmaniasis epidemics.Results:The minimum relative humidity,maximum relative humidity,minimum wind speed,and maximum wind speed were significantly associated with cutaneous leishmaniasis epidemics in different lags(P<0.05).Comparing SARIMA and MSM,Akaikes information criterion(AIC),and mean absolute percentage error(MAPE)in MSM were much smaller than SARIMA models(MSM:AIC=0.95,MAPE=3.5%;SARIMA:AIC=158.93,MAPE:11.45%).Conclusions:SARIMA and MSM can be a useful tool for predicting cutaneous leishmaniasis in Isfahan province.Since cutaneous leishmaniasis falls into one of two states of epidemic and non-epidemic,the use of MSM(dynamic)is recommended,which can provide more information compared to models that use a single distribution for all observations(Box-Jenkins SARIMA model).

Vegetation dynamics of coal mining city in an arid desert region of Northwest China from 2000 to 2019

Coal mining has led to serious ecological damages in arid desert region of Northwest China.However,effects of climatic factor and mining activity on vegetation dynamics and plant diversity in this region remain unknown.Wuhai City located in the arid desert region of Northwest China is an industrial city and dominated by coal mining.Based on Landsat data and field investigation in Wuhai City,we analyzed the vegetation dynamics and the relationships with climate factors,coal mining activity and ecological restoration projects from 2000 to 2019.Results showed that vegetation in Wuhai City mostly consisted of desert plants,such as Caragana microphylla,Tetraena mongolica and Achnatherum splendens.And the vegetation fractional coverage(VFC)and greenness rate of change(GRC)showed that vegetation was slightly improved during the study period.Normalized difference vegetation index(NDVI)was positively correlated with annual mean precipitation,relative humidity and annual mean temperature,indicating that these climate factors might play important roles in the improved vegetation.Vegetation coverage and plant diversity around the coal mining area were reduced by coal mining,while the implementation of ecological restoration projects improved the vegetation coverage and plant diversity.Our results suggested that vegetation in the arid desert region was mainly affected by climate factors,and the implementation of ecological restoration projects could mitigate the impacts of coal mining on vegetation and ecological environment.