Spatial And Temporal Variation In The Geographical Distribution And Prediction Of Pine Wood Nematode Disease Under Different Climate Scenarios

Pine wilt nematode is a fast-spreading and destructive forest pest that poses a serious threat to China’s forest resources.In recent years,the area of China’s forests affected by pine wilt nematode has been increasing year by year and the spread of the disease has been expanding.The study of the evolution of the geographical distribution of pine wilt nematode under the influence of climate change and the prediction of future development trends can provide theoretical basis and technical support for the effective monitoring,prediction and timely control of pine wilt nematode.This study used distribution data from four periods(1982-1992,1992-2002,2002-2012,2012-2022)and contemporaneous bioclimatic variable data developed by two institutions(Dataset 1 and Dataset 2),combined with a knife-cut approach to analyse the drivers of spatial distribution changes of pine wood nematode disease in China over the last 40 years,and its spatial distribution over the historical period The data were then used to analyse the spatial distribution of pine wilt nematodes in China over the past 40 years,and the changes in their spatial distribution over the historical period.Three ecological niche models(Max Ent,ENFA,GARP)were then used to predict the potential distribution areas of pine wood nematode disease under the current climate scenario(2002-2022)based on environmental-climatic drivers,and the natural breakpoint method was used to classify the distribution areas of pine wood nematode disease into four classes and count the distribution areas of different classes.The actual distribution data were used to evaluate the prediction results of the three ecological niche models,and the optimal model Max Ent was selected.Using this model,the potential distribution areas of pine wilt nematode disease were predicted for two future periods(2021-2040 and 2041-2060),and the threshold values were determined to classify the potential distribution areas into two classes of suitable/unsuitable,with a total of 11 climate models selected for each period,corresponding to four climate scenarios under each climate model(SSP1-2.6,SSP2-4.5,SSP3-7.0 and SSP5-8.5scenarios)were selected for each period,and the range of variation index RCI and kappa values were used to evaluate the degree of variability of the predicted results for different climate models(GCMs)and different scenarios(SSPs).A two-factor ANOVA was used to determine the uncertainty contribution of GCMs and SSPs in predicting future distribution areas.Finally,the BCC-CSM2-MR climate model was selected to integrate ensemble prediction methods to predict the distribution areas of pine wood nematode under four climate scenarios for two future periods(2021-2040 and 2041-2060),and the natural breakpoint method was used to classify the predicted results into 4 classes and calculate the direction and distance of mass transfer.The main findings are as follows:(1)The main drivers of changes in the spatial distribution of pine wilt nematode disease based on the knife cut method were,in dataset 1,the main driver based on the magnitude of the contribution of environmental factors in the four historical periods,the driest month precipitation(bio14),the increasing trend of environmental factors in the four historical periods,the main drivers were isothermality(bio3),warmest month maximum temperature(bio5),annual precipitation(bio12),and warmest month precipitation(bio18);in dataset 2,the main drivers are drought index(di),cumulus temperature greater than 5°C(gdd5),and mean temperature of the warmest month(mtwa),based on the increasing trend in environmental factor contribution,and the main driver is maximum temperature(tmax).Of these,driest month precipitation(bio14)and drought index(di)are the highest contributors in both datasets,respectively,and are closely related.(2)The results of centroid transformation showed that during 1982-1992,the centroid of pine wilt disease distribution area shifted to the southwest of Nanjing City,Jiangsu Province to Yicheng City,Anhui Province.From 1992 to 2002,the centroid shifted to the southwest of Yicheng City,Anhui Province to Jiujiang City,Jiangxi Province.From 2002 to 2012,the centroid shifted to the southwest of Jiujiang City,Jiangxi Province to Yueyang City,Hunan Province.From2012 to 2022,the centroid shifted to the northeast of Yueyang City,Hunan Province,and finally the centroid was located in Jingzhou City,Hubei Province.(3)Under the current climate scenario(2002-2022),the average AUC values of the training and validation sets of Max Ent,ENFA and GARP models were used as evaluation indicators,and the AUC of the Max Ent model was the Maximum,and the Max Ent model had the best performance in predicting the potential distribution area of pine wood nematode disease.(4)Analysis of variability using two indicators,RCI and Kappa,for 11 different climate models(GCMs)and four different types of scenarios(SSPs)showed that RCI did not reach a significant level(p>0.05)and Kappa reached the required significance(p<0.05).According to the Kappa values,in the period 2021-2040,the greatest variability was in the Can ESM5 model and SSP1-2.6 scenario,and the least variability was in the IPSL-CM6A-LR model and SSP2-4.5scenario;in the period 2041-2060,the greatest variability was in the BCC-CSM2-MR model and SSP5-8.5 scenario The greatest variation was in the BCC-CSM2-MR model and the SSP5-8.5scenario,while the least variation was in the IPSL-CM6A-LR model and the SSP2-4.5 scenario.The results of the two-factor ANOVA indicated that the different categories of climate models(GCMs)were the main factor in RCI and Kappa uncertainty,with the different scenarios(SSPs)being the secondary factor.(5)According to the changes in the area of different classes of potential future distribution areas of pine wood nematode disease,during the period 2021-2040,the area of high suitable distribution areas of pine wood nematode disease increased slightly under the SSP1-2.6 and SSP5-8.5 scenarios,while the area of high suitable distribution areas mainly showed a partial decrease under the SSP2-4.5 and SSP3-7.0 scenarios;during the period 2041-2060,the area of high suitable distribution areas of the four climate scenarios showed a small increase in the area of high suitability distribution and a further increase in the risk of pine wood nematode transmission.(6)The results of the centroid transition in the potential distribution area of pine wood nematode disease showed that the potential distribution area of the centroid under different scenarios was mainly in Hubei and Hunan provinces,with the centroid transition in a southwestnortheast direction under the SSP1-2.6 scenario and the centroid eventually located in Linxiang City,Yueyang City,Hunan Province,with the centroid in a southeast-northwest direction under the SSP2-4.5 and SSP3-7.0 scenarios,with the centroid in a northwest direction under the SSP5-8.5 scenario,the centroid transferred to the northwest,and in the ensemble projection scenario,the centroid transferred to the southwest-northeast,and in the SSP2-4.5,SSP3-7.0,SSP5-8.5 and ensemble projection scenarios,the centroid was ultimately located in Honghu City,Jingzhou City,Hubei Province.In this study,the effects of climate change on the potential distribution area of pine wilt disease were explored by combining the spatial distribution changes of pine wilt disease under different climate scenarios in history,current and future.The driving factors of spatial change were analyzed,and the direction of centroid change in the distribution area in the next 40 years was calculated.The research can provide a basis for the monitoring and prevention and control of pine wilt disease in China,and provide a reference for relevant forestry planning and pest development prediction.It is of great significance to maintain the stability and sustainable development of China ’s forest system.