Due to the increased frequency and intensity of forest damage caused by diseases and pests, effective methods are needed to accurately monitor the damage degree. Unmanned aerial vehicle (UAV)-based hyperspectral imaging is an effective technique for forest health surveying and monitoring. In this study, a framework is proposed for identifying the severity of damage caused by Tomicus spp. (the pine shoot beetle, PSB) to Yunnan pine (Pinus yunnanensis Franch) using UAV-based hyperspectral images. Four sample plots were set up in Shilin, Yunnan Province, China. A total of 80 trees were investigated, and their hyperspectral data were recorded. The spectral data were subjected to a one-way ANOVA. Two sensitive bands and one sensitive parameter were selected using Pearson correlation analysis and stepwise discriminant analysis to establish a diagnostic model of the damage degree. A discriminant rule was established to identify the degree of damage based on the median value between different degrees of damage. The diagnostic model with R₆₉₀ and R₇₉₈ as variables had the highest accuracy (R² = 0.854, RMSE = 0.427), and the test accuracy of the discriminant rule was 87.50%. The results are important for forest damage caused by the PSB.

Yunnan is located on the southwest border of China, with a complex geographical environment and rich biodiversity, which is the first stop for many migratory pests to enter China. In recent years, Ceracris kiangsu has migrated into China through the China–Laos border line. The migratory C. kiangsu has shown typical characteristics of migratory locusts, which has seriously jeopardized the ecological security, biosecurity and food security of China. In order to prevent and control C. kiangsu from the source as soon as possible, this study used hotspot analysis and trajectory analysis to clarify the migration dynamics, source regions and migration corridors of C. kiangsu. The results showed that the migratory C. kiangsu was mainly distributed in the towns of Jiangcheng County, and the source regions were concentrated in Phongsaly, Laos. There are three cross-border migration corridors of C. kiangsu, among which the Laos–Niuluohe border migration corridor running through the entire migration cycle is the most important corridor. The study answered three key questions about the prevention and control of C. kiangsu. Ascertaining when C. kiangsu arrived at Yunnan, where it came from, and where the population then went will greatly improve the efficiency of the prevention and control of C. kiangsu as well as provide a theoretical basis for subsequent monitoring and early warning.

Danaus genutia, commonly known as the tiger butterfly, is a visually appealing species in the Danaidae family. As it is not currently classified as endangered, it is excluded from key protected species lists at national and local levels, limiting focus on its population and habitat status, which may result in it being overlooked in local butterfly conservation initiatives. Yunnan, characterized by high butterfly diversity, presents an ideal region for studying habitat suitability for D. genutia, which may support the conservation of regional biodiversity. This study employs the MaxEnt ecological niche model, predictions regarding suitable habitat distribution, and trends for D. genutia and identifying primary environmental factors influencing their distribution. The results indicate that the niche model that includes interspecies relationships provides a distribution prediction closely aligned with the observed range of D. genutia. Under current climatic conditions, highly suitable habitats for both D. genutia and its host plant, Cynanchun annularium, are located predominantly in the Yuanjiang River Valley. Optimal conditions occur at average annual temperatures of 19.80–22 °C for D. genutia and 22–24 °C for C. annularium. The distribution range of C. annularium is a vital biological factor limiting D. genutia’s habitat. By 2040, projections under four future climate scenarios indicate a potential increase in the total area of suitable habitats for D. genutia, with a general trend of northward expansion.

Color and odor are crucial cues for butterflies during foraging and courtship. While most sexual dimorphic butterflies rely more on vision, our understanding of how butterflies with similar coloration use different signals remains limited. This study investigated the visual and olfactory behavioral responses of the similarly colored butterfly Byasa hedistus during foraging and courtship. While visiting artificial flowers of different colors, we found that B. hedistus exhibits an innate color preference, with a sequence of preferences for red, purple, and blue. The frequency of flower visits by B. hedistus significantly increased when honey water was sprayed on the artificial flowers, but it hardly visited apetalous branches with honey water. This proves that locating nectar sources by odor alone is difficult in the absence of floral color guides. During courtship, males are active while females hardly chase; only two models were observed: males chasing males and males chasing females. The courtship process includes four behaviors: slowing approach, straight chasing, hovering, and spinning. B. hedistus cannot distinguish between sexes based on color, as there is no significant difference in color and shape between them. Twenty-three VOCs (>1%) were identified in B. hedistus, with 21 shared by both sexes, while ketones are specific to males. These VOCs are principally represented by cineole, β-pinene, and linalool. When cineole was added to butterfly mimics, many butterflies were attracted to them, but the butterflies did not seem to distinguish between males and females. This suggests that cineole may be the feature VOC for identifying conspecific groups. Adding β-pinene and linalool to mimics induced numerous butterflies to chase, hover, spin around, and attempt to mate with them. This suggests that β-pinene and linalool are crucial cues indicating the presence of females.

Butterflies have the ability to learn to associate olfactory information with abundant food sources during foraging. How the co-occurrence of both food and food odours affects the learning behaviour of adults and whether butterflies perceive the odour of their surroundings and develop a preference for that odour during the pupal stage have rarely been tested. We examined the effect of experience with food odour components (α-pinene and ethyl acetate) during the pupal and adult stages on the foraging behaviour of the flower-visiting butterfly Tirumala limniace. We found that α-pinene exposure during the pupal stage changed the foraging preference of newly emerged adults. T. limniace exhibits olfactory learning in the adult stage, and adult learning may influence their previous pupal memory. Moreover, adults’ odour preference did not continue to increase over multiple training times. The learning ability of adults for floral odours (α-pinene) was greater than that for non-floral odours (ethyl acetate). In contrast to previous studies, we found that males learned odours more efficiently than females did. This could be attributed to differences in antennal sensilla, affecting sensitivity to compounds and nectar demand between males and females. Our study provides further insight into how olfactory learning helps flower-visiting butterflies use food odours to forage better.

Humans have made tremendous efforts to explore how biodiversity changes affect ecosystem processes and human well-being. It has been found that, in addition to biodiversity, various drivers of global change also play significant roles in ecosystem functioning. Land use is a key driver of global change, yet research on land use intensity has predominantly focused on agricultural and grassland ecosystems. There remains limited understanding of how land use intensity alters the relationships among biodiversity, ecosystem functions, and multifunctionality, particularly in forest ecosystems. This paper reviews recent advances in research on soil ecosystem multifunctionality, covering the effects of woodland use intensity, above- and belowground biodiversity, microbial diversity, and biotic interactions, as well as abiotic drivers. Through a comprehensive analysis of the integrated impacts of biodiversity, biotic interactions, and abiotic factors on soil ecosystem multifunctionality, the necessity of enhancing microbial research and its application in ecosystems is emphasized, providing a theoretical basis for forest management.