Shanyong He's research while affiliated with China West Normal University and other places

Biological invasions has caused significant damage to the ecological environment and economy of the world. Pest risk assessment is the most cost-effective means of preventing biological invasions to identify potentially suitable indexes for constructing pre-border weed risk assessment methods for China, we screened 80 metrics derived from 53 plant characteristics known to be related to invasive alien plants in other parts of the world and tested whether these metrics differed significantly between two groups of 103 invasive alien plants and 107 non-invasive plants in China. The results showed significant differences in 30 characteristics between invasive and non-invasive plants in China. Compared to the non-invasive plant group, the invasive plant group in China had a greater proportion of (1) plants native to the Americas, (2) plants belonging to the Asteraceae family, (3) polyploid plants, and had (4) a smaller proportion of plants propagated asexually only. The 30 metrics with significant differences were selected for LASSO regression to develop a predictive model to determine how well the metrics could distinguish between invasive and non-invasive alien plants already present in China. Finally an optimal model with 18 metrics was screened out. The optimal model was able to accurately discriminate 75% of non-invasive plants and 90% of invasive plants on the test set. Therefore the present study screened a range of useful metrics for the identification of invasive plants in China, and the high discriminative power of our models indicates that the subset of 18 variables retained in the final model could be useful for establishing a pre-border invasive plant screening tool for China in the future.

The front cover image is based on the Research Article Projecting the current and future potential global distribution of Hyphantria cunea (Lepidoptera: Arctiidae) using CLIMEX by Xuezhen Ge et al., DOI: 10.1002/ps.5083. Photo Credit: Lili Ren The front cover image is based on the Research Article Projecting the current and future potential global distribution of Hyphantria cunea (Lepidoptera: Arctiidae) using CLIMEX by Xuezhen Ge et al., DOI: 10.1002/ps.5083. Photo Credit: Lili Ren

BACKGROUND The international invasive and quarantined defoliating insect Hyphantria cunea Drury (Lepidoptera: Arctiidae) causes huge ecological and economic losses in the world. Furthermore, future climate change may alter the distribution of H. cunea and aggravate the damage. In the present study, we used CLIMEX to project the potential global distribution of H. cunea according to both historical climate data (1961–1990) and future climate warming estimates (2011–2100) to define the impact of climate change. RESULTS Under the historical climate scenario, we found that H. cunea can survive on every continent, and temperature is the main factor that limits its establishment. With climate change, suitability will increase in middle and high latitude regions, while decrease in the low latitude regions. Moreover, tropic regions will be the most sensitive to climate change impacts for the pest to survive. The impacts of climate change will also increase over time, whether they be positive impacts or negative impacts. CONCLUSION The projected potential distributions provide a theoretical basis for quarantine and control strategies for the management of this pest in each country. Furthermore, these results provide substantial guidance for studies of the effects of climate change on other major forest pests. © 2018 Society of Chemical Industry

The Australian Weed Risk Assessment system (AWRA) is an effective pre-border weed-screening tool that has played an active role in preventing the introduction of alien weeds into Australia and has been utilized in several other countries worldwide. Here, we selected 131 species of naturalized exotic plants (including 76 species of given non-weeds and 55 species of given weeds) to evaluate the AWRA in China for the first time. The AWRA performed better for discriminating major weeds than non-weeds and minor weeds, as it correctly rejected 84% of major weeds and did not wrongly accept a major weed. Among non-weeds, 76% were correctly classified with the final outcome of “accept” and 7.9% were wrongly rejected by the AWRA. This system correctly rejected 56% of minor weeds but accepted only 2.8% of minor weeds. The remaining 23% of all alien plants tested were classified as “evaluate further” by the AWRA. The area under the ROC curve (AUC) was 0.944, suggesting that the AWRA would be highly efficient at discriminating alien plants in China. In addition, we compared the scores of seven attributes of the AWRA between prior plant categories and analyzed their correlation with weed status. The average score for each attribute differed significantly between the two prior categories (weed and non-weed), but the average scores of the attribute “undesirable traits” did not significantly differ between any two of the three categories (non-weeds, minor weeds, and major weeds). There was a significant positive correlation between the scores of each attribute of the AWRA and weed status. The correlation coefficient for “dispersal mechanisms” and weed status was the highest and that for “undesirable traits” was the lowest. We believe that the AWRA can serve as an important weed-screening tool for plant introduction management in China.

As the primary pest of palm trees, Rhynchophorus ferrugineus (Olivier) (Coleoptera: Curculionidae) has caused serious harm to palms since it first invaded China. The present study used CLIMEX 1.1 to predict the potential distribution of R. ferrugineus in China according to both current climate data (1981-2010) and future climate warming estimates based on simulated climate data for the 2020s (2011-2040) provided by the Tyndall Center for Climate Change Research (TYN SC 2.0). Additionally, the Ecoclimatic Index (EI) values calculated for different climatic conditions (current and future, as simulated by the B2 scenario) were compared. Areas with a suitable climate for R. ferrugineus distribution were located primarily in central China according to the current climate data, with the northern boundary of the distribution reaching to 40.1°N and including Tibet, north Sichuan, central Shaanxi, south Shanxi, and east Hebei. There was little difference in the potential distribution predicted by the four emission scenarios according to future climate warming estimates. The primary prediction under future climate warming models was that, compared with the current climate model, the number of highly favorable habitats would increase significantly and expand into northern China, whereas the number of both favorable and marginally favorable habitats would decrease. Contrast analysis of EI values suggested that climate change and the density of site distribution were the main effectors of the changes in EI values. These results will help to improve control measures, prevent the spread of this pest, and revise the targeted quarantine areas.

Anoplophora chinensis (Forster) (Coleoptera: Cerambycidae) is an A1 class quarantine pest, native to China, Japan, and North Korea. The A. chinensis outbreak in China has severely affected the local environment and economic development. This study investigates potential areas in China with suitable climate for A. chinensis using historical climate data (1971–2000) and future climate-warming estimates generated by CLIMEX1.1. These future estimates are based on simulated climate data (2010–2039) provided by the Tyndall Centre for Climate Change Research (TYN SC 2.0). The results suggest that a wide area of China will have a climate suitable for A. chinensis, and every province may contain some suitable areas for this pest. The predicted areas are distributed primarily in central and southern China, with an estimated distribution range of 18.2–49.5°N and 81.3–135.0°E. Using a global-warming scenario and predictions based on historical climate data, the areas in China with a climate generally suitable for A. chinensis are predicted to decline, whereas the areas that are highly suitable for A. chinensis are predicted to expand particularly to the northeast and northwest. The estimated distribution range covered 18.2–49.1°N and 73.6–135.0°E. Anoplophora chinensis hosts grow in much of China; therefore, the pest could possibly establish this entire predicted area. These results support enhanced quarantine and control measures combined with stronger monitoring systems to prevent the spread and export of A. chinensis.