Geographically and Temporally Weighted Regression in Assessing Dengue Fever Spread Factors in Yunnan Border Regions

Objective This study employs the Geographically and Temporally Weighted Regression(GTWR)model to assess the impact of meteorological elements and imported cases on dengue fever outbreaks,emphasizing the spatial-temporal variability of these factors in border regions.Methods We conducted a descriptive analysis of dengue fever’s temporal-spatial distribution in Yunnan border areas.Utilizing annual data from 2013 to 2019,with each county in the Yunnan border serving as a spatial unit,we constructed a GTWR model to investigate the determinants of dengue fever and their spatio-temporal heterogeneity in this region.Results The GTWR model,proving more effective than Ordinary Least Squares(OLS)analysis,identified significant spatial and temporal heterogeneity in factors influencing dengue fever’s spread along the Yunnan border.Notably,the GTWR model revealed a substantial variation in the relationship between indigenous dengue fever incidence,meteorological variables,and imported cases across different counties.Conclusion In the Yunnan border areas,local dengue incidence is affected by temperature,humidity,precipitation,wind speed,and imported cases,with these factors’influence exhibiting notable spatial and temporal variation.

Species’ geographical range, environmental range and traits lead to specimen collection preference of dominant plant species of grasslands in Northern China

Many different factors,such as species traits,socio-economic factors,geographical and environmental factors,can lead to specimen collection preference.This study aims to determine whether grassland specimen collection in China is preferred by species traits(i.e.,plant height,flowering and fruiting period),environmental range(i.e.,the temperature and precipitation range)and geographical range(i.e.,distribution range and altitudinal range).Ordinary least squares models and phylogenetic generalized linear mixed models were used to analyze the relationships between specimen number and the explanatory variables.Random Forest models were then used to find the most parsimonious multivariate model.The results showed that interannual variation in specimen number between 1900 and 2020 was considerable.Specimen number of these species in southeast China was notably lower than that in northwest China.Environmental range and geographical range of species had significant positive correlations with specimen number.In addition,there were relatively weak but significant associations between specimen number and species trait(i.e.,plant height and flowering and fruiting period).Random Forest models indicated that distribution range was the most important variable,followed by flowering and fruiting period,and altitudinal range.These findings suggest that future floristic surveys should pay more attention to species with small geographical range,narrow environmental range,short plant height,and short flowering and fruiting period.The correction of specimen collection preference will also make the results of species distribution model,species evolution and other works based on specimen data more accurate.

Geographical Indication Intellectual Property Protection and Regional Public Brand Construction of Rape Industry in China

As China s largest oil crop,rape occupies a central position in ensuring the safety of China s cooking oil supply.This paper introduced China s rapeseed industry from the rape type,rapeseed production,planting area,national rapeseed production protected area,rape national dominant characteristic industrial clusters,and rapeseed industry,etc.Besides,from the aspects of geographical indication products,geographical indication trademarks,and geographical indications of agricultural products,this paper discussed the intellectual property protection of geographical indications of rape,rapeseed,and rapeseed oil in China.It analyzed the main problems such as the lag in the formulation of relevant standards for geographical indications and the low use of special signs for geographical indications,and finally came up with recommendations including building a public brand of geographical indications and expanding foreign exchanges of geographical indications.

Estimation of the potential geographical distribution of a new potato pest(Schrankia costaestrigalis) in China under climate change

Global food security is threatened by the impacts of the spread of crop pests and changes in the complex interactions between crops and pests under climate change.Schrankia costaestrigalis is a newly-reported potato pest in southern China.Early-warning monitoring of this insect pest could protect domestic agriculture as it has already caused regional yield reduction and/or quality decline in potato production.Our research aimed to confirm the potential geographical distributions(PGDs)of S.costaestrigalis in China under different climate scenarios using an optimal MaxEnt model,and to provide baseline data for preventing agricultural damage by S.costaestrigalis.Our findings indicated that the accuracy of the optimal MaxEnt model was better than the default-setting model,and the minimum temperature of the coldest month,precipitation of the driest month,precipitation of the coldest quarter,and the human influence index were the variables significantly affecting the PGDs of S.costaestrigalis.The highly-and moderately-suitable habitats of S.costaestrigalis were mainly located in eastern and southern China.The PGDs of S.costaestrigalis in China will decrease under climate change.The conversion of the highly-to moderately-suitable habitat will also be significant under climate change.The centroid of the suitable habitat area of S.costaestrigalis under the current climate showed a general tendency to move northeast and to the middle-high latitudes in the 2030s.The agricultural practice of plastic film mulching in potato fields will provide a favorable microclimate for S.costaestrigalis in the suitable areas.More attention should be paid to the early warning and monitoring of S.costaestrigalis in order to prevent its further spread in the main areas in China’s winter potato planting regions.

Elemental Assessments in Paddy Soil for Geographical Traceability of Rice from Peninsular Malaysia

This investigation aimed to establish the geographical traceability of Malaysian rice by assessing the elemental composition in paddy soil.Multi-element determination in combination with a chemometric approach was applied to evaluate the elemental concentrations of paddy soil from granaries cultivated with the same rice variety and to assess the relationship between elements in the soil and rice(SAR) system.A total of 29 elements(aluminum,arsenic,barium,bromine,calcium,chlorine,cobalt,chromium,cesium,europium,iron,gallium,hafnium,potassium,lanthanum,lutetium,magnesium,manganese,sodium,rubidium,antimony,scandium,samarium,thorium,titanium,uranium,vanadium,ytterbium and zinc) were successfully determined in paddy soil from Kedah,Selangor and Langkawi by neutron activation analysis.A significant difference(P < 0.05) between 18 elements in the soil samples was obtained.The chemometric approaches of principal component and linear discriminant analyses demonstrated clear discrimination and highly corrected classification(100%) of the soil samples.A high classification(98.1%) was also achieved by assessing 10 elements(aluminum,arsenic,bromine,chlorine,potassium,magnesium,manganese,sodium,rubidium and zinc),which similarly applied to rice geographical origin determination.Similar elements in SAR were also observed for differences in the pattern of correlation and bioaccumulation factor between the granaries.Furthermore,the generalized Procrustes analysis showed a 98% consensus between SAR and clear differences between the studied regions.The canonical correlation analysis demonstrated a significant correlation between the chemical profile of SAR(r~2 = 0.88,P < 0.001).Therefore,the current work model provides a reliable assessment to establish rice provenance.

Geographical distribution of Batrachospermaceae genera in Asia and its environmental factors

Batrachospermaceae is an important group of freshwater red algae.Available data of the latitude,longitude,and environmental factors on Batrachospermaceae distribution in Asia were analyzed to understand the geographical distribution of Batrachospermaceae genera in Asia.Statistical analyses,including one-way ANOVA,correlation analysis,stepwise regression analysis,principal component analysis,and linear discriminant analysis were conducted to characterize variation in geographical distribution and growth environment.Results reveal high variation in geographical distribution and growth environment among different Batrachospermaceae genera in Asia.Specifically,correlations between latitude and all environmental factors exclusive of altitude are significant,and longitude is significantly correlated with all environmental factors except for average relative humidity.The geographical distribution and growth environment of different Batrachospermaceae genera significantly differed.Altitude,maximum temperature,average temperature,minimum temperature,average relative humidity,average wind speed,maximum wind speed,and atmospheric pressure all contributed to explaining differences in the geographical distribution of Batrachospermaceae genera.Combining the results of correlation analysis,stepwise regression analysis,and principal component analysis,all environmental factors contributed to the different geographical distribution of Batrachospermum,Paludicola,Sheathia,Sirodotia,and Remainder(the rest),all environmental factors but atmospheric pressure contributed to the different geographical distribution of Kumanoa,and all environmental factors but average wind speed and maximum wind speed contributed to the different geographical distribution of Virescentia.However,the correlation between these significantly related environmental factors and taxa is not necessarily causative,and many other environmental factors,such as temperature,pH,conductivity,shading,current velocity,dissolved oxygen,hardness,substrata types,and nutrients etc.,are likely to have an important impact on the geographical distribution of taxa,which is an important topic for future research.

Monitoring the little fire ant,Wasmannia auropunctata(Roger 1863),in the early stage of its invasion in China:Predicting its geographical distribution pattern under climate change

Invasive alien ants(IAAs)are among the most aggressive,competitive,and widespread invasive alien species(IAS)worldwide.Wasmannia auropunctata,the greatest IAAs threat in the Pacific region and listed in“100 of the world’s worst IAS”,has established itself in many countries and on islands worldwide.Wild populations of W.auropunctata were recently reported in southeastern China,representing a tremendous potential threat to China’s agricultural,economic,environmental,public health,and social well-being.Estimating the potential geographical distribution(PGD)of W.auropunctata in China can illustrate areas that may potentially face invasion risk.Therefore,based on the global distribution records of W.auropunctata and bioclimatic variables,we predicted the geographical distribution pattern of W.auropunctata in China under the effects of climate change using an ensemble model(EM).Our findings showed that artificial neural network(ANN),flexible discriminant analysis(FDA),gradient boosting model(GBM),Random Forest(RF)were more accurate than categorical regression tree analysis(CTA),generalized linear model(GLM),maximum entropy model(MaxEnt)and surface distance envelope(SRE).The mean TSS values of ANN,FDA,GBM,and RF were 0.820,0.810,0.843,and 0.857,respectively,and the mean AUC values were 0.946,0.954,0.968,and 0.979,respectively.The mean TSS and AUC values of EM were 0.882 and 0.972,respectively,indicating that the prediction results with EM were more reliable than those with the single model.The PGD of W.auropunctata in China is mainly located in southern China under current and future climate change.Under climate change,the PGD of W.auropunctata in China will expand to higher-latitude areas.The annual temperature range(bio7)and mean temperature of the warmest quarter(bio10)were the most significant variables affecting the PGD of W.auropunctata in China.The PGD of W.auropunctata in China was mainly attributed to temperature variables,such as the annual temperature range(bio7)and the mean temperature of the warmest quarter(bio10).The populations of W.auropunctata in southern China have broad potential invasion areas.Developing strategies for the early warning,monitoring,prevention,and control of W.auropunctata in southern China requires more attention.

Exploring spatial non-stationarity of near-miss ship collisions from AIS data under the influence of sea fog using geographically weighted regression:A case study in the Bohai Sea,China

Sea fog is a disastrous weather phenomenon,posing a risk to the safety of maritime transportation.Dense sea fogs reduce visibility at sea and have frequently caused ship collisions.This study used a geographically weighted regression(GWR)model to explore the spatial non-stationarity of near-miss collision risk,as detected by a vessel conflict ranking operator(VCRO)model from automatic identification system(AIS)data under the influence of sea fog in the Bohai Sea.Sea fog was identified by a machine learning method that was derived from Himawari-8 satellite data.The spatial distributions of near-miss collision risk,sea fog,and the parameters of GWR were mapped.The results showed that sea fog and near-miss collision risk have specific spatial distribution patterns in the Bohai Sea,in which near-miss collision risk in the fog season is significantly higher than that outside the fog season,especially in the northeast(the sea area near Yingkou Port and Bayuquan Port)and the southeast(the sea area near Yantai Port).GWR outputs further indicated a significant correlation between near-miss collision risk and sea fog in fog season,with higher R-squared(0.890 in fog season,2018),than outside the fog season(0.723 in non-fog season,2018).GWR results revealed spatial non-stationarity in the relationships between-near miss collision risk and sea fog and that the significance of these relationships varied locally.Dividing the specific navigation area made it possible to verify that sea fog has a positive impact on near-miss collision risk.

Exploring the drivers of urban expansion in a medium-class urban agglomeration in India using the remote sensing techniques and geographically weighted models

Rapid urbanization urges the immediate attention of policymakers to ensure sustainable city development.Under-standing the urban growth drivers is essential to address effective strategies for urbanization-related challenges.This work aims to study Raiganj’s urban development and the factors associated with this expansion.This study employed global logistic regression(LR)and geographical weighted logistic regression(GWLR)to explore the role of different factors.The results showed that the role of the central business district(covariate>-1),commercial market(covariate>-3),and police station(covariate>-4)were significant to the development of new built-up areas.In the second period,major roads(covariate>-2)and new infrastructures(covariate>-4)became more relevant,particularly in the eastern and southern areas.GWLR was more accurate in assessing the different fac-tors’impact than LR.The results obtained are essential to understanding urban expansion in India’s medium-class cities,which is critical to effective policies for sustainable urbanization.

A geographical similarity-based sampling method of non-fire point data for spatial prediction of forest fires

Understanding the mechanisms and risks of forest fires by building a spatial prediction model is an important means of controlling forest fires.Non-fire point data are important training data for constructing a model,and their quality significantly impacts the prediction performance of the model.However,non-fire point data obtained using existing sampling methods generally suffer from low representativeness.Therefore,this study proposes a non-fire point data sampling method based on geographical similarity to improve the quality of non-fire point samples.The method is based on the idea that the less similar the geographical environment between a sample point and an already occurred fire point,the greater the confidence in being a non-fire point sample.Yunnan Province,China,with a high frequency of forest fires,was used as the study area.We compared the prediction performance of traditional sampling methods and the proposed method using three commonly used forest fire risk prediction models:logistic regression(LR),support vector machine(SVM),and random forest(RF).The results show that the modeling and prediction accuracies of the forest fire prediction models established based on the proposed sampling method are significantly improved compared with those of the traditional sampling method.Specifically,in 2010,the modeling and prediction accuracies improved by 19.1%and 32.8%,respectively,and in 2020,they improved by 13.1%and 24.3%,respectively.Therefore,we believe that collecting non-fire point samples based on the principle of geographical similarity is an effective way to improve the quality of forest fire samples,and thus enhance the prediction of forest fire risk.

Natural variations and geographical distributions of seed carotenoids and chlorophylls in 1167 Chinese soybean accessions

Understanding the composition and contents of carotenoids in various soybean seed accessions is important for their nutritional assessment.This study investigated the variability in the concentrations of carotenoids and chlorophylls and revealed their associations with other nutritional quality traits in a genetically diverse set of Chinese soybean accessions comprised of cultivars and landraces.Genotype,planting year,accession type,seed cotyledon color,and ecoregion of origin significantly influenced the accumulation of carotenoids and chlorophylls.The mean total carotenoid content was in the range of 8.15–14.72μg g–1 across the ecoregions.The total carotenoid content was 1.2-fold higher in the landraces than in the cultivars.Soybeans with green cotyledons had higher contents of carotenoids and chlorophylls than those with yellow cotyledons.Remarkably,lutein was the most abundant carotenoid in all the germplasms,ranging from 1.35–37.44μg g–1.Carotenoids and chlorophylls showed significant correlations with other quality traits,which will help to set breeding strategies for enhancing soybean carotenoids without affecting the other components.Collectively,our results demonstrate that carotenoids are adequately accumulated in soybean seeds,however,they are strongly influenced by genetic factors,accession type,and germplasm origin.We identified novel germplasms with the highest total carotenoid contents across the various ecoregions of China that could serve as the genetic materials for soybean carotenoid breeding programs,and thereby as the raw materials for food sectors,pharmaceuticals,and the cosmetic industry.

Geographical history的概念和汉译——兼论Alan R.H.Baker地理历史学思想

针对国内将贝克的geographical history一词译为"地理学史"或"地理史"的问题,结合他的新作对geographical history这一术语的论述及学科合法地位的诉求,认为应译为"地理历史学"。同时结合国内学者对"地理历史学"的术语混乱和学科诉求做了论述,分析了"地理历史学"术语混乱的部分原因。认为对国内外"地理历史学"思想应给予注意,给予"地理历史学"一个合法的学科地位。

Geographical Patterns and Temporal Variations of Regional Dry and Wet Heatwave Events in China during 1960–2008

Daily maximum/minimum temperatures and relative humidity records from 510 stations in China for the period 1960–2008 were used to investigate geographical patterns and temporal variations of heatwave （HW） events. Dry and wet HW events were compared by different definitions. Regionally, both dry and wet HW events are commonly located in southeastern China in the monsoon area, with neither type occurring in the northeast part of Northeast China and Southwest China, while the north-northwest region of the country experiences dry HW events and a few wet HW events. In the southeast of the country, site dry HW events occurred from April to September and mostly in June, while site wet HW events occurred from April to October and mostly in September. In total, 163 regional wet HW events were identified. The ten longest regional wet HW events lasted for more than 20 days, while the mean duration for 163 events was about 11 days. For the top ten events, six occurred after the 1990s, compared with four before this time. Global surface warming was clear since 1979, but the frequency and severity of regional wet HW events were relatively low in the 1980s, increasing remarkably since the 1990s. Possible reasons for this might be the strong interdecadal and interannual variations in regional atmospheric circulations, as well as water transport related directly to temperature contrasts in different regions, rather than global-mean temperature changes.

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.

PROGRESS IN STUDIES ON GEOGRAPHICAL ENVIRONMENTS OF THE QINGHAI-XIZANG PLATEAU

The Qinghai Xizang (Tibet) Plateau area was subjected to twice uplift and planation in the Tertiary. Intense uplifting of the plateau area has given rise to drastic changes and differentiation of physical environment on the plateau and the surrounding area since 3.4 Ma B.P. Significant environmental changes with dry tendency in interior of the plateau had occurred during the last 150 ka B.P. By comparative study on several mountains of the plateau, two systems of the structure type of the altitudinal belt are identified and nine groups are subdivided . A distribution model with close relevance to highland uplift effect has been generalized. A number of striking geo ecological phenomena and their spatial pattern such as moisture corridor, dry valleys, high cold meadow zone, and high cold arid core area are investigated and discussed. Based on the thermal conditions, moisture regimes and variation in landforms of the plateau is sequentially demarcated. A tentative scheme of 2 temperature belts, 10 natural zones and 28 physical districts has been proposed not including southern slopes of the East Himalayas. The Qinghai Xizang Plateau is sensitive to “green house effect”, showing close relation with global change. Characteristics of temperature and precipitation on the plateau during the last 2000 years, and response of glaciers, snow deposit and permafrost on the plateau to global change are dealt with in the present paper.

Quantification of driving factors on NDVI in oasis-desert ecotone using geographical detector method

Within oasis-desert ecotone regions,the normalized difference vegetation index(NDVI)is an important parameter for evaluating the growth of vegetation.An accurate quantitative study between NDVI and environmental and anthropogenic factors is critical for understand the driving factors of vegetation growth in oasis-desert ecotone.In 2016,four periods Landsat 8 OLI_TIRS images,relevant climatological parameters data(air temperature,air relative humidity,wind velocity and accumulated temperature),land cover type data and soil data were selected as proxies.In order to quantify the explanatory power for NDVI spatial and temporal distribution in the southern edge of Dunhuang City and northern side of the Mingsha Mountain,the geographical detector model was used to explain the potential influences of factors versus the spatial distribution of NDVI,and each explanatory variable's relative importance can be calculated.The factor detector results disclose that the spatial distribution of NDVI is primarily dominated by land cover type.The risk detector results show that,high NDVI region is located within woodland.The mean value of NDVI displays an increase and then decrease trend with air temperature increase.With the increase of wind velocity and decrease of air relative humidity,the NDVI value shows a decrease trend.The interactive q values between the two factors are higher than any q value of separated factors.Results also indicate that the strongest interactive effects of NDVI are different in distinct seasons.Consequently,anthropogenic activity is more important than environmental factors on NDVI in oasis-desert ecotone.We also demonstrate that air relative humidity rather than air temperature have played a greater role in NDVI spatial distribution.

Geographical Information System-Based Assessment of Ecological Security in Changbai Mountain Region

Ecological security defined as the creation of a condition where the physical surroundings of a community provide for the needs of its inhabitants without diminishing its natural stock,which is important for regional security and social stability.In recent years,land use patterns in the Changbai Mountain region have changed significantly with intensive human activities,and consequently led to increasing problems in regional ecological security.Based on the Pressure-State-Impact-Response(PSIR) model and the mathematical method of catastrophe progression supported by geographical information system(GIS),the ecological security situation of the study area under land use and cover change(LUCC) was evaluated.The results indicated that the ecological security in Changbai Mountain region varied nonlinearly,which got better from 1990 to 2000 but became worse from 2000 to 2007,the ecological security levels in Changbai Mountain region were mainly medium and medium to low during the past 17 years,with higher values of Ecological Security Index(ESI) in the central region and lower values in the east and west,the ecological security situation was more serious in the settlements and river valleys,where the LUCC was most remarkable.

The evolution of tea spatial agglomeration in China:An analysis based on different geographical scales

The spatial agglomeration of agricultural production is conducive to reducing planting costs, increasing production efficiency and improving product quality. It is an important way to promote the transformation and upgrad of tea industry and realize the modernization of China's tea industry. This study used Gini coefficient and spatial autocorrelation analysis to explore the characteristics of tea spatial agglomeration in China from three geographical scales: regional level, provincial level and prefecture level from the year 2005 to 2015. The results indicated that there was a significant scale effect on the tea spatial agglomeration. The agglomeration degree increased from the regional level, provincial level to prefecture level. The types of spatial agglomeration evolution of the three scales were Ushaped, continuous diffusion, and continuous agglomeration. The spatial autocorrelation of tea production could only be found at the prefecture level. Meanwhile, at the prefecture scale, we could not only reveal the pattern changes at the regional and provincial levels, but also identify tea production agglomeration regions. Compared with the large scale, the small scale could reveal the characteristics of tea spatial agglomeration in more details. Factors such as natural resource endowments, cost factor, technological advancement, agglomeration economy, and agricultural policy influenced the evolution of tea spatial agglomeration from different geographical scales. Finally, from the perspectives of spatial transfer of tea production, promoting spatial agglomeration, building tea production bases, and breaking administrative boundaries, we proposed several policy suggestions for optimizing the spatial layout of tea production.

Geographical Variation and Influencing Factors of Spartina alterniflora Expansion Rate in Coastal China

Biological invasion poses a huge threat to ecological security.Spartina alterniflora was introduced into China in 1979,and its arrival corresponded with negative effects on native ecosystems.To explore geographical variation of its expansion rate in coastal China,we selected 43 S.alterniflora sites from Tianjin Coastal New Area to Beihai.The area expansion rate,expansion rate paralleling and vertical to the shoreline were analysed based on Landsat images and field survey in 2015.Simple Ocean Data Assimilation(SODA)and climate data were collected to statistically analyse the influential factors of expansion rate.Results showed that significant difference of S.alterniflora area expansion rate among different latitude zones(P<0.01),increasing from 6.08%at southern(21°N–23°N)to 19.87% in Bohai Bay(37°N–39°N)along latitude gradient.There was a significant difference in expansion rate vertical to shoreline in different latitude zones(P<0.01)with the largest occurring in Bohai Bay(256m/yr,37°N–39°N),and showed an decreasing tendency gradually from north to south.No significant difference and latitudinal clines in expansion rate paralleling to shoreline were observed.Expansion rate had significant negative correlation with mean seawater temperature,the lowest seawater temperature,current zonal velocity and meridional velocity and presented a reducing trend as these biotic factors increased;however,they were not significantly correlated with the highest seawater temperature and mean seawater salinity.We identified significant correlations between expansion rate and annual mean temperature,the lowest temperature in January and annual precipitation,but there was little correlation with annual diurnal difference in temperature and the highest temperature in July.The rapid expansion rate in high-latitude China demonstrated a higher risk of potential invasion in the north;dynamic monitoring and control management should be established as soon as possible.

Genetic Differentiation of Different Geographical Populations of Bemisia tabaci (Gennadius) Complex

Bemisia tabaci （Gennadius） is a species complex, which includes different geographical populations with genetic differentiation. The recent progress on the genetic differentiation of various geographical populations of B. tabaci complex was introduced. The genetic differentiation was further analyzed on the basis of the sequences of mtDNA COI and rDNA ITS1 recorded in the world＇s GenBank. Five groups are defined on the basis of mtDNA COI and rDNA ITS1, including the Asia group, America group, Africa group, Australia group, and Biotype B/Mediterranean/Middle East/ Northern Africa/Biotype Ms group. There are several ungrouped geographical classifications, such as the Uganda population, Ivory Coast population, and Taiwan population. Geographical isolation may be the most important factor that contributed to the genetic differentiation of various geographical populations of B. tabaci. Many populations with biological advantages invaded new regions and caused severe economic losses within human activity. It is necessary to strengthen the research of B. tabaci biotype to prevent the spread of invaded populations and the invasion of potentially dangerous populations.