Advancing Forest Pest Management: Integrative Insights from Prediction, Monitoring, and Control

1. Introduction

Invasive species are among the most serious threats to forest health worldwide, with their impacts expected to intensify under ongoing climate change and the expansion of international trade [1]. The invasion process is typically divided into four sequential stages: introduction, establishment, spread, and saturation [2]. To minimize or mitigate the impacts of biological invasions, a unified, stage-specific response framework has been proposed—encompassing prevention before introduction, eradication during the early stage, and containment and mitigation during and after range expansion [3]. Early detection and rapid response are especially critical during the initial invasion stages, as their success depends heavily on effective monitoring, which remains indispensable for invasive species management [4].

Ecological modeling has proven highly effective in predicting the occurrence risks and dispersal patterns of forest insect pests and diseases [5,6,7,8]. These models not only forecast potential outbreaks but also help identify the underlying drivers of pest and disease dynamics. By clarifying the mechanisms of invasion and spread, modeling supports the development of targeted and effective management strategies. Moreover, such tools provide valuable information for policymakers by offering short-term forecasts of outbreak risk and spread potential, despite inherent uncertainties in model predictions.

Monitoring continues to be a cornerstone of forest pest management, providing essential data on pest density, distribution, and outbreak extent—information that underpins the design of efficient control strategies. Field surveys and remote sensing are the two primary monitoring approaches [9,10]. Remote sensing offers broad spatial coverage and rapid assessments, though its accuracy can be constrained by weather conditions and limitations in species-level identification [11]. In contrast, ground-based surveys deliver detailed, direct observations of pest status, and recent methodological advances have significantly improved the precision of density estimates and spatial mapping [9].

A variety of management methods and strategies have been developed and implemented to control forest pests in recent years. Biological control agents derived from microorganisms and natural enemies have been extensively evaluated under both laboratory and field conditions [12,13,14,15,16]. Building on these efforts, combinations of control agents and application techniques have been tested to enhance management efficiency. Collectively, these approaches offer promising tools for mitigating the adverse effects of pest outbreaks on forest ecosystems.

The aim of this Special Issue, “Management of Forest Pests and Diseases II”, is to advance the understanding of innovative methods and approaches for developing effective management strategies against forest pests. The contributing studies investigate outbreak causes and drivers through monitoring and analytical techniques. To promote environmentally sustainable management, this Special Issue also highlights control options based on natural enemies and microbially derived substances, evaluating their potential to reduce pest impacts on forest ecosystems. By integrating predictive modeling, causal analysis, and diverse management practices, this Special Issue provides new insights and strategies that support the development of sustainable, adaptive forest pest management.

2. Papers in This Special Issue

This Special Issue includes twelve papers addressing the modeling, monitoring, and management of forest pests. Among them, four papers focused on the occurrence and dispersal modeling of forest pests. Notably, three of these studies examined invasive species recently introduced to Korea, highlighting that invasive species pose a major threat to the country’s forest health.

Goroshko et al. [5] analyzed the outbreak risk of the Siberian moth (Dendrolimus sibiricus) in Central Siberia. Using ground-based data and remote sensing, the study identified the dominance of Siberian fir (Abies sibirica Ledeb.), Siberian spruce (Picea obovata Ledeb.), and Scots pine (Pinus sylvestris L.), as well as proximity to disturbed forests, as the most influential factors contributing to outbreak risk. Lee et al. [6] predicted potential occurrence areas of the western conifer seed bug (Leptoglossus occidentalis), which was introduced to Korea in 2010. Using species distribution models based on maximum entropy and random forest algorithms, they found that anthropogenic factors—particularly proximity to roads and night light intensity—were the strongest predictors of occurrence probability. Zhang et al. [7] developed lattice structure and spatial network models to explain the human-mediated dispersal of L. occidentalis across South Korea. Their models successfully captured the species’ rapid spread from southeastern to northwestern regions around 2016, identifying distance to roads, traffic volume, and forest-product transport as key drivers of dispersal. Wu and Lee [8] used a convolutional neural network model integrating geographical and meteorological variables to predict the occurrence of pine wilt disease in Korea. Their analysis showed that precipitation in September and maximum temperature in May were the most influential environmental factors.

Three papers focused on monitoring forest pests. Kim et al. [17] examined the effects of chilling temperature on the survival and post-diapause development of Asian spongy moth (Lymantria dispar asiatica) eggs. Egg survival declined following exposure to –12 °C for 100 days, while developmental rates accelerated with increasing chilling temperature. Booth et al. [9] proposed efficient survey methods for the spotted lanternfly (Lycorma delicatula) using traps and lures. The circle trap proved most effective for capturing adults, while trap efficiency for immature stages was similar across designs; however, methyl salicylate lures were not effective for monitoring this species. Booth et al. [9] analyzed the internal transcribed spacer (ITS) sequences of Hymenoscyphus fraxineus, the causal agent of ash dieback disease in Germany. ITS sequences showed 98.8%–100% identity with European and Asian reference sequences, suggesting that genetic diversification in the ITS region is an ongoing process.

The remaining five papers addressed management strategies for forest pests. Ni et al. [15] screened Beauveria bassiana strains for the biological control of Plecoptera bilinealis, a serious leaf-eating pest of Dalbergia odorifera, a second-level protected wild plant species in China. Among ultraviolet- and microwave-mutagenized strains, HNCMBJ-P-01 was the most virulent, causing 80% mortality in the target pest. Xia et al. [16] investigated the antagonistic activity and mechanisms of endophytic Bacillus subtilis against Camellia oleifera anthracnose caused by Colletotrichum fructicola. Spraying the fermentation broth reduced the disease index by up to 66.2%, likely through the accumulation of hydrogen peroxide and activation of peroxidase. Nguyen et al. [14] evaluated the antifungal activity of culture filtrates from the endophytic fungus Nectria balsamea against Dryadomyces quercus-mongolicae. The filtrate completely inhibited mycelial growth, sporulation, and spore germination, demonstrating its potential as a biocontrol agent. Raykova et al. [12] assessed the influence of tree vitality, silvicultural management, and genetic tolerance on the spread and severity of ash dieback caused by the invasive fungus H. fraxineus. In trees with diameters at breast height between 25 and 31 cm, those with higher vitality and genetic tolerance exhibited reduced susceptibility, explaining 42% of disease severity variation. Finally, Li et al. [13] developed integrated management methods for controlling verticillium wilt of smoke trees by testing combinations of five control agents and three application methods. The combination of propiconazole via irrigation with trunk injection of carbendazim and prochloraz proved to be the most effective treatment.

3. Conclusions

Invasive species remain a major focus of research, reflecting the growing global concern over their impacts on forest ecosystems and overall forest health. Predicting the occurrence risk and dispersal patterns of invasive forest pests provides essential information for developing effective management strategies. Building on this foundation, reliable monitoring methods tailored to the biological and ecological characteristics of target pests are crucial. Furthermore, diverse management options must be evaluated and integrated to establish suitable and sustainable control strategies. The optimal combination of control methods and agents offers the greatest potential to mitigate the adverse impacts of forest pests on forest health. We hope that this Special Issue contributes to the development of optimized management strategies for forest pests and supports the long-term maintenance of healthy forest ecosystems worldwide.