Jieshi Tang

Bio: Jieshi Tang is an academic researcher from Sichuan University. The author has an hindex of 1, co-authored 1 publications receiving 2 citations.

Global potential distribution prediction of Xanthium italicum based on Maxent model.

Abstract: Alien invasive plants pose a threat to global biodiversity and the cost of control continues to rise. Early detection and prediction of potential risk areas are essential to minimize ecological and socio-economic costs. In this study, the Maxent model was used to predict current and future climatic conditions to estimate the potential global distribution of the invasive plant Xanthium italicum. The model consists of 366 occurrence records (10 repeats, 75% for calibration and 25% for verification) and 10 climate prediction variables. According to the model forecast, the distribution of X. italicum was expected to shrink in future climate scenarios with human intervention, which may be mainly caused by the rise in global average annual temperature. The ROC curve showed that the AUC values of the training set and the test set are 0.965 and 0.906, respectively, indicating that the prediction result of this model was excellent. The contribution rates of annual mean temperature, monthly mean diurnal temperature range, standard deviation of temperature seasonal change and annual average precipitation to the geographical distribution of X. italicum were 65.3%, 11.2%, 9.0%, and 7.7%, respectively, and the total contribution rate was 93.2%. These four variables are the dominant environmental factors affecting the potential distribution of X. italicum, and the influence of temperature is greater than that of precipitation. Through our study on the potential distribution prediction of X. italicum under the future climatic conditions, it has contribution for all countries to strengthen its monitoring, prevention and control, including early warning.

Climate Change Increases the Expansion Risk of Helicoverpa zea in China According to Potential Geographical Distribution Estimation

Abstract: Simple Summary Helicoverpa zea is one of the most destructive lepidopteran agricultural pests in the world and can disperse long distances both with and without human transportation. It is listed in the catalog of quarantine pests for plants imported to the People’s Republic of China but has not yet been reported in China. On the basis of 1781 global distribution records of H. zea and eight bioclimatic variables, we predicted the potential geographical distributions (PGDs) of H. zea by using a calibrated MaxEnt model. The results showed that the PGDs of H. zea under the current climate are large in China. Future climate changes under shared socioeconomic pathways (SSP) 1-2.6, SSP2-4.5, and SSP5-8.5 for both the 2030s and 2050s will facilitate the expansion of PGDs for H. zea. Helicoverpa zea has a high capacity for colonization by introduced individuals in China. Customs ports should pay attention to the host plants of H. zea and containers harboring this pest. Abstract Helicoverpa zea, a well-documented and endemic pest throughout most of the Americas, affecting more than 100 species of host plants. It is a quarantine pest according to the Asia and Pacific Plant Protection Commission (APPPC) and the catalog of quarantine pests for plants imported to the People’s Republic of China. Based on 1781 global distribution records of H. zea and eight bioclimatic variables, the potential geographical distributions (PGDs) of H. zea were predicted by using a calibrated MaxEnt model. The contribution rate of bioclimatic variables and the jackknife method were integrated to assess the significant variables governing the PGDs. The response curves of bioclimatic variables were quantitatively determined to predict the PGDs of H. zea under climate change. The results showed that: (1) four out of the eight variables contributed the most to the model performance, namely, mean diurnal range (bio2), precipitation seasonality (bio15), precipitation of the driest quarter (bio17) and precipitation of the warmest quarter (bio18); (2) PGDs of H. zea under the current climate covered 418.15 × 104 km2, and were large in China; and (3) future climate change will facilitate the expansion of PGDs for H. zea under shared socioeconomic pathways (SSP) 1-2.6, SSP2-4.5, and SSP5-8.5 in both the 2030s and 2050s. The conversion of unsuitable to low suitability habitat and moderately to high suitability habitat increased by 8.43% and 2.35%, respectively. From the present day to the 2030s, under SSP1-2.6, SSP2-4.5 and SSP5-8.5, the centroid of the suitable habitats of H. zea showed a general tendency to move eastward; from 2030s to the 2050s, under SSP1-2.6 and SSP5-8.5, it moved southward, and it moved slightly northward under SSP2-4.5. According to bioclimatic conditions, H. zea has a high capacity for colonization by introduced individuals in China. Customs ports should pay attention to host plants and containers of H. zea and should exchange information to strengthen plant quarantine and pest monitoring, thus enhancing target management.

Predicting the distributions of Scleroderma guani (Hymenoptera: Bethylidae) under climate change in China

Abstract: Abstract The wasp Scleroderma guani is an important parasitic natural enemy of a variety of stem borers such as longicorn beetles. Studying and clarifying the suitable area of this wasp plays an important role in controlling stem borers. Based on information about the actual distribution of S. guani and on a set of environmental variables, MaxEnt niche model and ArcGIS were exploited to predict the potential distribution of this insect in China. This work simulated the geographical distribution of potential climatic suitability of S. guani in China at present and in different periods in the future. Combining the relative percent contribution score of environmental factors and the Jackknife test, the dominant environmental variables and their appropriate values restricting the potential geographical distribution of S. guani were screened. The results showed that the prediction of the MaxEnt model was highly in line with the actual distribution under current climate conditions, and the simulation accuracy was very high. The distribution of S. guani is mainly affected by bio18 (Precipitation of Warmest Quarter), bio11 (Mean Temperature of Coldest Quarter), bio13 (Precipitation of Wettest Month), and bio3 (Isothermality). The suitable habitat of S. guani in China is mainly distributed in the Northeast China Plain, North China Plain, middle‐lower Yangtze Plain, and Sichuan Basin, with total suitable area of 547.05 × 104 km2, accounting for 56.85% of China’s territory. Furthermore, under the RCP2.6, RCP4.5, and RCP8.5 climate change scenarios in the 2050s and 2090s, the areas of high, medium, and low suitability showed different degrees of change compared to nowadays, exhibiting expansion trend in the future. This work provides theoretical support for related research on pest control and ecological protection.