Journal Article

Establishment and Application of a Novel Forest Pest–Disease Base Index Model

Cheng, Yuan, Jia, Xin, Han, Xing, Zhang, Chenwei, Li, Lu, Ren, Xiaoli, Hu, Ruirui, Fan, Guiyan, Liang, Jun

2026

Overview

The occurrence of forest pests and diseases is synergistically driven by stand factors (canopy closure, stand density, DBH, etc.) and site factors (elevation, soil type, slope aspect, etc.). To evaluate the effect grade of site factors on the degree of occurrence of specific forest pests and diseases after their interaction with stand factors, and to further determine the infestation severity of specific pests and diseases in stands established on suitable forestlands post-afforestation, a novel forest pest–disease base index model is defined based on the fundamental principles governing the occurrence of forest pests and diseases in specific pure forest stands. The model mandates the selection of pure forest ecosystems and the establishment of standard plots, within which a comprehensive survey of all site factors, stand factors, and target pest and disease incidence is conducted. Through methods such as stepwise regression analysis, key stand factors that influence forest pest and disease occurrence are identified, and a functional relationship between these factors and the forest pest–disease index is established. The optimal model, known as the principal curve, is obtained by relating the key stand factors to the pest–disease index. By proportionally stretching this principal curve, a series of forest pest–disease base index curves, namely the forest pest–disease base index model, is generated. These curves represent different pest–disease base index levels from bottom to top, corresponding to different grades of site effects on forest pest and disease occurrence. Furthermore, a model linking the pest–disease base index and site factors is established to evaluate the potential occurrence of pests and diseases in suitable forestlands. Applied to pure Pinus densiflora stands in Kunyu Mountain, this model quantitatively assesses the grade of site effects on the degree of occurrence of P. densiflora blight and Cephalcia kunyushanica, thereby verifying feasibility and practical applicability. It not only provides theoretical and technical support for pest and disease prediction prior to artificial forest establishment and the determination of infestation severity in post-afforestation stands but also improves ecological regulation methods for forest harmful organisms.

• Publisher: MDPI AG
• Subject: Afforestation / Biodiversity / Blight / China / Disease / Diseases / Ecosystems / Epidemics / Forest ecosystems / Forests / Humidity / Infestation / Insects / Neural networks / Pathogens / Pests / Population density / Regression analysis / Soil types / Temperature / Terrestrial ecosystems / Trees