Modeling and Mapping the Current and Future Distribution of Pseudomonas Syringae Pv. Actinidiae Under Climate Change in China

PLoS One. 2018 Feb 1;13(2):e0192153. doi: 10.1371/journal.pone.0192153. eCollection 2018.

Abstract

Objective: Bacterial canker of kiwifruit caused by Pseudomonas syringae pv. actinidiae (Psa) is a major threat to the kiwifruit industry throughout the world and accounts for substantial economic losses in China. The aim of the present study was to test and explore the possibility of using MaxEnt (maximum entropy models) to predict and analyze the future large-scale distribution of Psa in China.

Method: Based on the current environmental factors, three future climate scenarios, which were suggested by the fifth IPCC report, and the current distribution sites of Psa, MaxEnt combined with ArcGIS was applied to predict the potential suitable areas and the changing trend of Psa in China. The jackknife test and correlation analysis were used to choose dominant climatic factors. The receiver operating characteristic curve (ROC) drawn by MaxEnt was used to evaluate the accuracy of the simulation.

Result: The results showed that under current climatic conditions, the area from latitude 25° to 36°N and from longitude 101° to 122°E is the primary potential suitable area of Psa in China. The highly suitable area (with suitability between 66 and 100) was mainly concentrated in Northeast Sichuan, South Shaanxi, most of Chongqing, West Hubei and Southwest Gansu and occupied 4.94% of land in China. Under different future emission scenarios, both the areas and the centers of the suitable areas all showed differences compared with the current situation. Four climatic variables, i.e., maximum April temperature (19%), mean temperature of the coldest quarter (14%), precipitation in May (11.5%) and minimum temperature in October (10.8%), had the largest impact on the distribution of Psa.

Conclusion: The MaxEnt model is potentially useful for forecasting the future adaptive distribution of Psa under climate change, and it provides important guidance for comprehensive management.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • China
  • Climate Change*
  • Models, Theoretical*
  • Pseudomonas syringae / isolation & purification*
  • Pseudomonas syringae / metabolism

Associated data

  • figshare/figshare.5734806

Grant support

Our work was supported by the modern agricultural industry technology http://www.scnycxtd.com/ system of Sichuan innovation team and the project of meteorological service for agriculture, rural areas and farmers in Sichuan, and the funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.