Unmanned aerial vehicles (UAVs) are platforms that have been increasingly used over the last decade to collect data for forest insect pest and disease (FIPD) monitoring. These machines provide flexibility, cost efficiency, and a high temporal and spatial resolution of remotely sensed data. The purpose of this review is to summarize recent contributions and to identify knowledge gaps in UAV remote sensing for FIPD monitoring. A systematic review was performed using the preferred reporting items for systematic reviews and meta-analysis (PRISMA) protocol. We reviewed the full text of 49 studies published between 2015 and 2021. The parameters examined were the taxonomic characteristics, the type of UAV and sensor, data collection and pre-processing, processing and analytical methods, and software used. We found that the number of papers on this topic has increased in recent years, with most being studies located in China and Europe. The main FIPDs studied were pine wilt disease (PWD) and bark beetles (BB) using UAV multirotor architectures. Among the sensor types, multispectral and red–green–blue (RGB) bands were preferred for the monitoring tasks. Regarding the analytical methods, random forest (RF) and deep learning (DL) classifiers were the most frequently applied in UAV imagery processing. This paper discusses the advantages and limitations associated with the use of UAVs and the processing methods for FIPDs, and research gaps and challenges are presented.

Eucalyptus Longhorned Borers (ELB) are some of the most destructive pests in regions with Mediterranean climate. Low rainfall and extended dry summers cause stress in eucalyptus trees and facilitate ELB infestation. Due to the difficulty of monitoring the stands by traditional methods, remote sensing arises as an invaluable tool. The main goal of this study was to demonstrate the accuracy of unmanned aerial vehicle (UAV) multispectral imagery for detection and quantification of ELB damages in eucalyptus stands. To detect spatial damage, Otsu thresholding analysis was conducted with five imagery-derived vegetation indices (VIs) and classification accuracy was assessed. Treetops were calculated using the local maxima filter of a sliding window algorithm. Subsequently, large-scale mean-shift segmentation was performed to extract the crowns, and these were classified with random forest (RF). Forest density maps were produced with data obtained from RF classification. The normalized difference vegetation index (NDVI) presented the highest overall accuracy at 98.2% and 0.96 Kappa value. Random forest classification resulted in 98.5% accuracy and 0.94 Kappa value. The Otsu thresholding and random forest classification can be used by forest managers to assess the infestation. The aggregation of data offered by forest density maps can be a simple tool for supporting pest management.

Estimates of heritability from open-pollinated progeny trials were generally biased by heterogeneous selfing across families and by the presence of dominance, even when the intraclass correlation between sibs was adjusted for the average number of full- and half-sibs and for relatedness among the parents in the population. For high levels of selfing, with a constant selfing rate and inbreeding depression across families, dominance causes a downward bias in the heritabilities. Where rates of selfing and inbreeding depression varied, heritability was overestimated. However, except for low heritabilities, bias was of little practical importance, providing the correct coefficient of relationship among open-pollinated progeny was used.

Eucalyptus globulus Labill. is a widespread forest tree species, reported as naturalized across the introduced range, often showing abundant natural regeneration after wildfires. This paper studies a post-fire cohort of seedlings derived from a small, isolated E. globulus stand in central Portugal. The aim is to better understand the genetic dynamics and dispersal mechanisms of naturally established E. globulus populations in the introduced range. The seedling density at 55 m from adult trees was 12,000 ha⁻¹, the farthest seedling being registered at 101 m. Post-fire expansion occurred in a southward direction, in accordance with predominant wind. Seedlings had significantly lower levels of genetic diversity (Ae = 5.8.; He = 0.8) than adult trees (Ae = 6.5; He = 0.8). Crossings were strongly unbalanced, with only eight trees contributing to the sampled seedlings, and one single tree contributing to 52% of these seedlings. Moreover, the co-ancestry amongst seedlings more than doubled (from θ = 0.03 to 0.076), and the population status number was around one third of the value registered for the adult population (from Ns = 16.2 to 6.6). Despite its isolation, external pollen was detected in the stand, and appears to have travelled at least 700 m, contributing to 22% of the offspring. Overall, the seedling cohort is much less diverse than the parent trees, with expected lower resilience and persistence to environmental stresses.