Rice cultivation changes and its relationships with geographical factors in Heilongjiang Province,China

Rice planting patterns have changed dramatically over the past several decades in northeast China （NEC） due to the combined influence of global change and agricultural policy. Except for its great implications for environmental protection and climate change adaption, the spatio-temporal changes of rice cultivation in NEC are not clear. In this study, we conducted spatio-temporal analyses of NEC＇s major rice production region, Heilongjiang Province, by using satellite-derived rice cultivation maps. We found that the total cultivated area of rice in Heilongjiang Province increased largely from 1993 to 2011 and it expanded spatially to the northern and eastern part of the Sanjiang Plain. The results also showed that rice cultivation areas experienced a larger increase in the region managed by the Reclamation Management Bureau （RMB） than that managed by the local provincial government. Rice cultivation changes were closely related with those geographic factors over the investigated periods, represented by the geomorphic （slope）, climatic （accumulated temperature）, and hydrological （watershed） variables. These findings provide clear evidence that crop cultivation in NEC has been modified to better cope with the global change.

Normal Reference Value of Red Blood Cell Count of Chinese Presenile Men and Geographical Factors

This paper aims at providing a scientific basis for unifying the normal reference value standards of red blood cell count of Chinese presenile men. The paper, using microscopical counting method, studies the relationship between the normal reference values of 38,061 samples of red blood cell count of presenile men and eight geographical factors in 297 units in China. It is found that the correlation of geographical factors and the normal reference value of red blood cell count of presenile men is quite significant （F=303.00, P=-0.000）. By using the method of stepwise regression analysis, one regression equation is inferred. It is concluded that if geographical data are obtained in a certain area, the normal reference value of red blood cell count of presenile men in this area can be reckoned by using the regression analysis. Furthermore, according to the geographical factors, China can be divided into eight regions： Northeast China Region, North China Region, Shanxi-Shaanxi-Irmer Mongolia Region, Middle and Lower Reaches of the Changjiang River Region, Southeast China Region, Northwest China Region, Southwest China Region and Qinghai-Tibet Plateau Region.

Reference value of old people's hematocrit and geographical factors

This paper is written in order to provide a scientific basis for a unified standard of the reference value of Chinese healthy old people's hematocrit. It studies the relationship between the reference values of healthy old people's hematocrit, tested according to the Wintrobe Laws and five geographical factors. It is found that the altitude is the most important factor affecting the reference value of old people's hematocrit. As the altitude gradually increases, the reference value of their hematocrit also increases, the relationship is quite significant. By using the method of stepwise regression analysis, two multivariate regression equations are deduced:1=50.2+0.00248X1-0.0534X3-0.388X4+0.00383X5±2.2, 2=44.5+0.00231X1-0.0600X3-0.260X4+0.00341X5±2.1. If the geographical index values in a particular area in China are known, the reference value of old people's hematocrit in this area can be established by means of the regression equations. Furthermore, according to the dependent relationship of the reference value of old people's hematocrit on geographical factors, China can be divided into six regions: Qinghai-Tibet, Plateau, Southwest, Northwest, Southeast, North and Northeast.

Normal reference value of forced vital capacity of Chinese younger women and geographical factors

Objective To supply a scientific basis for standardizing the normal reference value of forced vital capacity(FVC)of Chinese younger women.Methods We studied the relationship between the normal reference value of 21767 samples of FVC of younger women and eight geographical factors in 157 areas in China.Results It was found that the correlation between geographical factors and the normal reference value of FVC of younger women was quite significant(F=5.884,P=0.000).By adopting the method of mathematical regression analysis,one regression equation was inferred:=3.146+0.00006919X1+0.01315X4-0.006966X6+0.09524X8±0.254.In the above equation,is the normal reference value of younger women’ FVC(L);X1 is the altitude(m);X4 is the annual mean air temperature(℃);X6 is the annual mean relative humidity(%);X8 is the annual mean wind speed(m/s);0.254 is the value of the residual standard deviation.Conclusion If geographical values are obtained in a certain area,the normal reference value of FVC of younger women in this area can be obtained by using the regression equation.Furthermore,according to the geographical factors,China can be divided into eight regions:Northeast China Region,North China Region,Shanxi-Shaanxi-Inner Mongolia Region,middle and lower reaches of the Yangzte River Region,Southeast China Region,Northwest China Region,Southwest China Region,and Qinghai-Tibet Plateau Region.

A New Method to Predict Erythrocyte Sedimentation Rate with Natural Geographical Factors and Location by Case-based Reasoning: A Case Study of China

Reference values of erythrocyte sedimentation rate(ESR)are the key to interpret ESR blood test in clinic.The common local reference ESR values are more accuracy in blood test that are established with natural geographical factors by using the multiple linear regression(MLR)model and the artificial neural network(ANN).These knowledge-based methods have limitations since the knowledge domains of ESR and natural geographical factors are limited.This paper presents a new cases-depended model to establish reference ESR values with natural geographical factors and location using case-based reasoning(CBR)since knowledge domain of ESR and geographical factors is weak.Overall 224 local normal ESR values of China that calculated from 13623 samples were obtained,and the corresponding natural geographical factors and location that include altitude,sunshine hours,relative humidity,temperature,precipitation,annual temperature range and annual average wind speed were obtained from the National Geomatics Center of China.CBR was used to predict the unseen local reference ESR values with cases.The average absolute deviation(AAD),mean square error(MSE),prediction accuracy(PA),and Pearson correlation coefficient(r)between the observed and estimated data of proposed model is 33.07%,9.02,66.93% and 0.78,which are better than those of ANN and MLR model.The results show that the proposed model provides higher prediction accuracy than those of the artificial neural network and multiple linear regression models.The predicted values are very close to the observed values.Model results show significant agreement of cases data.Consequently,the model is used to predict the unseen local reference ESR with natural geographical factors and location.In spatial,the highest ESR reference areas are distributed in the southern-western district of China that includes Sichuan,Chongqing,Guangxi and Guizhou provinces,and the reference ESR values are greater than 23 mm/60 min.The higher ESR reference values are distributed in the middle part and northern-eastern of China which include Hubei,Henan,Shaanxi,Shanxi,Jilin and Heilongjiang provinces,and the reference ESR values are greater than 18 mm/60min.The lowest ESR reference values are distributed in the northern-western of China that includes Tibet and Xinjiang,and the reference ESR values are lower than 5 mm/60min.

Geographical Factor as a Basis for Research of State BordersmAn Example of Georgia

The work deals with analysis of geographical factor as one of the main factor determining the historical change of a border on the example of Georgia. The research was conducted in two main directions： the evaluation of historical transformations of state borders of Georgia throughout of XIX-XX centuries and identification the leading geographical factors. Special emphasis has been made on geographical and cartometric analysis of modern state border of Georgia. In order to identify the historical transformations of state border that have used different methods as well as GIS-technologies, the research is based on the historical, cartographical and statistical data. On the base of a lot of cartographic sources, it is concluded that the borderline in modem topographic maps is often plotted by ignoring the international practice related to plotting the state borders across the physical-geographical objects. This is why the geographical factor seems important in the historical transformations of the state border creating similarly a negative perspective in the future. The main results of research are： （1） classification of geographical factors causing the transformations of the state borders; （2） Evaluation of sensitivity of state border; and （3） creation of DB of the state border of Georgia, allowing continuing the studies in the future.

Geography and Rural Household Income:A Village Level Study in Henan Province,China

This study uses the data from a sample survey conducted in April 2007 on 1 251 rural households in 11 villages of Henan Province, the largest less developed agricultural province in China, to examine how geography affects rural household income （RHI）. The quantitative analysis indicates following results. I） The significance of the traditional geographical factors reduces as RHI rank increases. 2） The landform does not affect the RHI significantly. The per capita income of rural household in a plain area is lower than that in a mountainous area. And 3） the capital endowment and status of non-farm economic activities contribute to the increase of RHI. But the probability and intensity of non-farm economic activities of rural households in urban outskirts villages are higher than that in non-urban outskirts villages. Based on the results, the paper further concludes that geography still plays a significant role in rural development, but it is changing over time. The agricultural resources （such as per capita arable land） significantly affect RHI with the relatively lower income level, while the geographical location shows a more significant impact on RHI with the relatively high income level. Along with economic development, the proximity replaces the traditional geographical factors such as landform and physical resources as the major determining factor in RHI.

Preliminary research on problems of northeastChina's participation in the northeast Asianeconomic cooperation

According to various factors influencing the economic openness, this paper probestentatively into the way Northeast China complies with and participates in the Northeast Asiancooperation, with perticular attention to the analysis and estimation of the advantageousgeographical condition of the extenal cooperation in Northeast China from the present situation ofdeveloping the external economy and cooperation with the adjacent countries.

Rates of litter decomposition in terrestrial ecosystems:global patterns and controlling factors

Aims We aim to construct a comprehensive global database of litter decomposition rate(k value)estimated by surface floor litterbags,and investigate the direct and indirect effects of impact factors such as geographic factors(latitude and altitude),climatic factors(mean annual tempePlrature,MAT;mean annual precipitation,MAP)and litter quality factors(the contents of N,P,K,Ca,Mg and C:N ratio,lignin:N ratio)on litter decomposition.Methods We compiled a large data set of litter decomposition rates(k values)from 110 research sites and conducted simple,multiple regression and path analyses to explore the relationship between the k values and impact factors at the global scale.Important findings The k values tended to decrease with latitude(LAT)and lignin content(LIGN)of litter but increased with temperature,precipitation and nutrient concentrations at the large spatial scale.Single factor such as climate,litter quality and geographic variable could not explain litter decomposition rates well.However,the combination of total nutrient(TN)elements and C:N accounted for 70.2%of the variation in the litter decomposition rates.The combination of LAT,MAT,C:N and TN accounted for 87.54%of the variation in the litter decomposition rates.These results indicate that litter quality is the most important direct regulator of litter decomposition at the global scale.This data synthesis revealed significant relationships between litter decomposition rates and the combination of climatic factor(MAT)and litter quality(C:N,TN).The global-scale empirical relationships developed here are useful for a better understanding and modeling of the effects of litter quality and climatic factors on litter decomposition rates.

Factors Influencing Alzheimer's Disease Risk: Whether and How They are Related to the APOE Genotype

Alzheimer's disease(AD)is the most prevalent neurodegenerative disease featuring progressive cognitive impairment.Although the etiology of late-onset AD remains unclear,the close association of AD with apolipoprotein E(APOE),a gene that mainly regulates lipid metabolism,has been firmly established and may shed light on the exploration of AD pathogenesis and therapy.However,various confounding factors interfere with the APOE-related AD risk,raising questions about our comprehension of the clinical findings concerning APOE.In this review,we summarize the most debated factors interactingwith theAPOEgenotype and ADpathogenesis,depict the extent to which these factors relate to APOEdependent AD risk,and discuss the possible underlying mechanisms.

Geographical Impact and Ecological Restoration Modes of the Spatial Differentiation of Rural Social-Ecosystem Vulnerability:Evidence from Qingpu District in Shanghai

Vulnerability research is the core issue and one of the research hotspots of sustainable development science.Vulnerability and its evaluation framework provide a new perspective for rural social-ecosystem studies.This paper introduced the‘input-output’efficiency theory and constructed the‘SEE-PSR’framework for the analysis of social-ecosystem vulnerability in the rural area in Qingpu District of Shanghai City.The DEA models,spatial autocorrelation model,multivariate logistic regression model,geographical detector and hierarchical cluster model were used to analyze the spatial differences of social-ecosystem vulnerability,and its geographical impact mechanisms and ecological restorations,in 184 administrative villages in this area.The results can be divided into three main points.(1)The results of the‘input-output’efficiency model of the EW-DEA based on entropy weight aggregation crossover was more reliable and accurate for the evaluation of rural social-ecosystem vulnerability.The vulnerability of the social-ecosystems in the administrative villages showed a trend of gradual decline from east to west,with an average value of vulnerability of 0.583,and the vulnerability of social systems had become an important factor in constraining the decrease of the vulnerability of the social-ecosystems in the region.(2)The distances from the center of Shanghai City,from Dianshan Lake,from the center of Qingpu District and from the water area were the four dominant geographical factors affecting the vulnerability of the social-ecosystem in this region.The geographical impacts exhibited the spatial differentiations of systemic structure,the substitution of typological attributes and the transformation level.(3)The geographical factors coupling the impact types of the social-ecosystem vulnerability were divided spatially into 10 types.The geographic multi-factor coupling impact types were dominant,which presented multi-cyclic spatial patterns and were dominated by the central multi-factor which was surrounded by the single factor types on both sides.According to the different types,some feasible ways of ecological restoration were proposed,which drew on the experiences of integrated territory consolidation to remediate the vulnerability of rural social-ecological systems.The results of this study can provide scientific reference for rural spatial reconstruction,regional ecological restoration and sustainable development for the regions characterized by conflict in the‘strict protection of the ecological environment and vigorous development of the economy’.

The characteristics of temperature variability with terrain, latitude and longitude in Sichuan- Chongqing Region

Using the daily temperature data of 95 meteorological stations from Sichuan-Chongqing Region and its surrounding areas, this paper adopted these methods （e.g., linear regression, trend coefficient, geographical statistics, gray relational analysis and spatial analysis functions of GIS） to analyze the relations of temperature variability with topography, latitude and longitude. Moreover, the rank of gray correlation between temperature variability and elevation, longitude, latitude, topographic position and surface roughness also was meas- ured. These results indicated： （1） The elevation affected temperature variability most obviously, followed by latitude, and longitude. The slope of the linear regression between temperature change rate and elevation, latitude and longitude was 0.4142, 0.0293 and -0.3270, respectively （2） The rank of gray correlation between temperature change rate and geographic factors was elevation 〉 latitude 〉 surface roughness 〉 topographic position 〉 longitude. The gray correla- tion degree between temperature change rate and elevation was 0.865, followed by latitude with 0.796, and longitude with 0.671. （3） The rate of temperature change enhanced with the increase of elevation. Especially, the warming trend was significant in the plateau and mountain areas of western Sichuan, and mountain and valley areas of southwestern Sichuan （with the warming rate of 0.74℃/10a during the 1990s）. However, there was a weak warming trend in Sichuan Basin and its surrounding low mountain and hilly areas. （4） The effects of latitude on temperature change rate presented the specific regulation, which the warming rate of low-latitude areas was more significant than that of high-latitude areas. However, they were consistent with the regulation that the increasing of low temperature controlled most of the warming trend, due to the effects of terrain and sically, temperature variability along longitude elevation on annual mean temperature. （5） Ba- direction resulted from the regular change of elevation along longitude. It was suggested that, in Sichuan-Chongqing Region, special features of temperature variability largely depended on the terrain complexity （e.g., undulations, mutations and roughness）. The elevation level controlled only high or low annual mean temperature and the range of temperature change rate in the macro sense.

Urban Systems:Understanding and Predicting the Spatial Distribution of China's Population

With urbanization and population migration,some Chinese cities fall into decline whereas others prosper.Using nighttime light data,we redefine the city based on economic function and evaluate the city size distribution in representative countries.The results provide evidence not only for Zipfs law,but also for a distortion in China s current city size distribution.This study proposes a feasible method to predict urban population distribution based on the role of geographical factors in regional development,following the idea of spatial equilibrium.This prediction suggests that the divergence of city size in China tends to be pronounced,with inter-regional income disparity being narrowed and the city size distribution following Zipfs law.The Chinese government should further relax restrictions on population inflow into large cities and prepare for more migration in the future.

Spatial distribution of surface energy fluxes over the Loess Plateau in China and its relationship with climate and the environment

China's Loess Plateau is located at the edge of the Asian summer monsoon in a transition zone of climate and ecology. In the Loess Plateau, climate and environments change along with space, which has an obvious impact on the spatial distribution of surface energy fluxes. Because of scarce land-surface observation sites and short observation time in this area, previous studies have failed to fully understand the land-surface energy balance characteristics over the entire the Loess Plateau and their effect mechanisms. In this paper, we first test the simulation ability of the Community Land Model(CLM) model by comparing its simulated data with observed data. Based on the simulation data for the Loess Plateau over the past thirty years, we then analyze the spatial distribution of surface energy fluxes and compare the pattern differences between the area averages for the driest year and wettest year. Furthermore, we analyze the relationship between the spatial distribution of the components of the surface energy balance with longitude, latitude, altitude, precipitation and temperature. The main results are as follows: the spatial distribution of surface energy fluxes are significantly different, with the surface net radiation and sensible heat flux increasing from south to north and latent heat flux and soil heat flux decreasing from southeast to northwest. The sensible heat flux at the driest point is nearly twice as high as that at the wettest point, whereas the latent heat flux and soil heat flux at the driest point are half as much as that at the wettest point. The impact of variations of annual precipitation on the components of the surface energy balance is also obvious, and the maximum magnitude of the changes to the sensible heat flux and latent heat flux is nearly 30%. To a certain extent, geographical factors(including longitude, latitude, and altitude) and climate factors(including temperature and precipitation) affect the surface energy fluxes. However, the surface net radiation is more closely related to latitude and altitude, sensible heat flux is more closely related to the monsoon rainfall and latitude, and latent heat flux and soil heat flux are more closely related to the monsoon rainfall.