Spatiotemporal Dynamics and Factors Driving the Distributions of Pine Wilt Disease-Damaged Forests in China

Wei Wang,Wanting Peng,Geng He,Xiuyu Liu,Yongli Cai

doi:10.3390/f13020261

Abstract

Many forests have suffered serious economic losses and ecological consequences of pine wilt disease (PWD) outbreaks. Climate change and human activities could accelerate the distribution of PWD, causing the exponential expansion of damaged forest areas in China. However, few studies have analyzed the spatiotemporal dynamics and the factors driving the distribution of PWD-damaged forests using continuous records of long-term damage, focusing on short-term environmental factors that influence multiple PWD outbreaks. We used a maximum entropy (MaxEnt) model that incorporated annual meteorological and human activity factors, as well as temporal dependence (the PWD distribution in the previous year), to determine the contributions of environmental factors to the annual distribution of PWD-damaged forests in the period 1982–2020. Overall, the MaxEnt showed good performance in modeling the PWD-damaged forest distributions between 1982 and 2020. Our results indicate that (i) the temporal lag dependence term for the presence/absence of PWD was the best predictor of the distribution of PWD-damaged forests; and (ii) Bio14 (precipitation in the driest month) was the most important meteorological factor for affecting the PWD-damaged forests. These results are essential to understanding the factors governing the distribution of PWD-damaged forests, which is important for forest management and pest control worldwide.

Highlights

Forests are the largest component of the terrestrial carbon cycle, acting as a large carbon sink in terrestrial ecosystems and maintaining the Earth’s carbon balance [1]
The location data obtained at the district level were converted to points by using the centroids of districts, as several other authors have done [31,32], which could be used for the further analysis of the distribution of PWDdamaged forests
Our results indicate that the maximum entropy (MaxEnt) model performed well in annual comparisons of the environmental factors that contributed to the distribution of Pine wilt disease (PWD)-damaged forests, especially during outbreaks of the disease

Summary

Introduction

Forests are the largest component of the terrestrial carbon cycle, acting as a large carbon sink in terrestrial ecosystems and maintaining the Earth’s carbon balance [1]. Pine wilt disease (PWD), caused by the presence of pine wood nematode (PWN), is one of the most severe forest diseases worldwide [2,3]. PWD-damaged forests were discovered in 718 county-level administrative divisions in 17 provinces of China by the end of December 2020, with ~19.5 million dead trees and ~1.81 million hectares infected [9]. This widespread PWD outbreak in China caused major economic losses and ecological consequences for pine forests [5,10,11]

Methods

Results

Discussion

Conclusion