Maximum Entropy Modeling to Predict the Impact of Climate Change on Pine Wilt Disease in China

Abstract

Pine wilt disease is a devastating forest disease caused by the pinewood nematode Bursaphelenchus xylophilus, which has been listed as the object of quarantine in China. Climate change influences species and may exacerbate the risk of forest diseases, such as the pine wilt disease. The maximum entropy (MaxEnt) model was used in this study to identify the current and potential distribution and habitat suitability of three pine species and B. xylophilus in China. Further, the potential distribution was modeled using the current (1970–2000) and the projected (2050 and 2070) climate data based on two representative concentration pathways (RCP 2.6 and RCP 8.5), and fairly robust prediction results were obtained. Our model identified that the area south of the Yangtze River in China was the most severely affected place by pine wilt disease, and the eastern foothills of the Tibetan Plateau acted as a geographical barrier to pest distribution. Bioclimatic variables related to temperature influenced pine trees’ distribution, while those related to precipitation affected B. xylophilus’s distribution. In the future, the suitable area of B. xylophilus will continue to increase; the shifts in the center of gravity of the suitable habitats of the three pine species and B. xylophilus will be different under climate change. The area ideal for pine trees will migrate slightly northward under RCP 8.5. The pine species will continue to face B. xylophilus threat in 2050 and 2070 under the two distinct climate change scenarios. Therefore, we should plan appropriate measures to prevent its expansion. Predicting the distribution of pine species and the impact of climate change on forest diseases is critical for controlling the pests according to local conditions. Thus, the MaxEnt model proposed in this study can be potentially used to forecast the species distribution and disease risks and provide guidance for the timely prevention and management of B. xylophilus.

Species Distribution Models of the Spartina alterniflora Loisel in Its Origin and Invasive Country Reveal an Ecological Niche Shift

“…For the available records that lacked latitude and longitude information, we used Google Earth to query the latitude and longitude information corresponding to the sample plots according to the place names. In this study, the limited number of distribution points were retained within a certain distance according to the spatial screening method, and systematic sampling was performed again according to the principle of uniformity and randomness to ensure that the geographic autocorrelation of the data points is minimized (Tang et al, 2021a). The distribution information of S. alterniflora in China (113 points) and in America (287 points) can be obtained and saved as a.csv file for later use.…”

Ophiostomatoid species associated with pine trees (Pinus spp.) infested by Cryphalus piceae from eastern China, including five new species

“…Among these, almost half were previously undescribed species (Yin et al 2016;Chang et al 2017;Wang et al 2018;Chang et al 2019;Chang et al 2020;Wang et al 2020). Owing to climate change, the economic damage caused by these bark beetles and nematodes has exponentially increased in China (Li 2013;Tang et al 2021), initiating studies focusing on the biology and control of these beetles . These studies simultaneously cataloged the diversity of symbiotic fungi associated with these beetles, influencing fungal species discovery (Sun et al 2013;Zhao and Sun 2017).…”

Ophiostomatoid Fungi Associated with Cryphalus Piceae in Shandong province in eastern China

“…Pitfalls associated with morphological and molecular characterization of ophiostomatoid fungi can also promote taxonomic misidenti cation, in uencing the diversity. Owing to climate change, economic damages caused by these bark beetles and nematodes has exponentially increased in China (Li, 2013;Tang et al, 2021). This initiated studies focusing on the biology and controlling of these beetles (Sun et al, 2013).…”