Effects of meteorological factors on the defoliation dynamics of the larch caterpillar (Dendrolimus superans Butler) in the Great Xing\u2019an boreal forests

Lei Fang,Jian Yang,Ellen Crocker,Zhijun Yu,Yue Yu,Guofei Fang,Xu Zhang,Xudong Zhang

doi:10.1007/s11676-020-01277-6

Abstract

Larch caterpillars are widely distributed in the Great Xing’an boreal forests; however, the relationship between caterpillar defoliation dynamics and climatic factors is poorly understood. The aims of this study are to investigate the primary weather conditions that might influence forest defoliation and to identify the most important life stage of the larch caterpillar at which forest defoliation might be mitigated by incorporating more inhibitory influences from climatic factors. The life cycle of the larch caterpillar was partitioned into four stages and multiple linear regression and mixed effect models were combined with a relative weight analysis approach to evaluate the importance and influence of meteorological variables on defoliation dynamics. The results show that warmer temperatures in growing seasons and overwintering periods can increase the defoliation area, while rainy and humid growing seasons decrease the defoliation area. Total precipitation during the early instar larval period had the greatest power to explain the variance in defoliation dynamics and had a very strong inhibitory effect, followed by the accumulative temperatures of the late instar larval period which had a positive impact, and precipitation during the middle instar larval period which had a negative impact. Weather conditions during the early instar larval period had the greatest influence on the area defoliated and accounted for 40% of the explained variance. This study demonstrates that climatic warming and drying will increase the risk of larch caterpillar outbreaks in the Great Xing’an Mountains.

Highlights

Forest insects are critical destructive agents that can directly exert stress effects on forest growth or even lead to substantial tree mortality, thereby decreasing timber production and ecosystem services related to water and soil retention and carbon sinks (Dale et al 2001; Kurz et al 2008; Medvigy et al 2012; Zhang et al 2014; Flower and Gonzalez-Meler 2015)
The multiple linear regression (MLR) model, whose explanatory variables consisted of the accumulated temperature of the growing season (LATG), total precipitation during the growing season (LTP) and mean daily relative humidity during the growing season (EMRH), explained the maximum variance in the defoliation area of the larch caterpillar, while variable combinations such as the accumulated temperature of the growing season (MATG)-total precipitation during the growing season (ETP)-EMRH, LATG-total precipitation during the growing season (MTP)-EMRH, LATG-MTPmean daily relative humidity during the growing season (MMRH) and MATG-MTP-EMRH explained over 38.0% of the variance
Meteorological factors are closely associated with the defoliation dynamics of larch caterpillars in the Great Xing’an boreal forests

Summary

Introduction

Forest insects are critical destructive agents that can directly exert stress effects on forest growth or even lead to substantial tree mortality, thereby decreasing timber production and ecosystem services related to water and soil retention and carbon sinks (Dale et al 2001; Kurz et al 2008; Medvigy et al 2012; Zhang et al 2014; Flower and Gonzalez-Meler 2015). Monitoring and predicting outbreaks of forest insects are topics that have. Many studies have shown that high-latitude regions will experience stronger warming trends in winter (Dale et al 2001; Bale and Hayward 2010; Venette 2013), which may significantly shorten the duration of winter and decrease the inhibitory effects of cold temperatures on forest insects. Under such trends, it is predicted that more insects will successfully survive winter, negatively affecting forest health. Warming is expected to dramatically influence the population dynamics of forest insects; temperature is frequently regarded as an important predictor of forest insect outbreaks (Yamamura et al 2005; Bentz et al 2016; Zidon et al 2016)

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