Xiaofei Liu

Seasonal migration represents one of the most fascinating behaviours observed throughout the animal kingdom. Understanding the spatial ecological and evolutionary dynamics of seasonally migratory animals is important to predict their responses to anthropogenic climate change. Unlike the directional and closed‐circuit round‐trip migratory pattern in most seasonally migratory animal species, many migratory insects exhibit a tangled reticular movement instead of a simple transition between sites. Consequently, the interplay between gene flow and natural selection in seasonal dispersal of insects may display a unique pattern and affect the potential of migratory insects to climate change. To characterise such pattern and evaluate the adaptive potential of seasonally migratory insects to future climate, we used genomic data from 32 populations of the seasonal dispersal and invasive oriental fruit fly ( Bactrocera dorsalis ) sampled across year‐round and seasonal areas in the mountains of southwest China (MSWC). Despite significant ecological niche differences between populations of year‐round and seasonal areas, we found no significant population structure both within and across areas. In addition, genomic landscape and vulnerability analyses suggested that the northwestern and northeastern populations possessed distinct genetic compositions and reduced adaptive potential compared to the southern populations. Finally, we predicted the migration distance and direction that may allow the current populations to persist under future climates. Our findings demonstrate that gene flow plays a predominant role in homogenising genetic variation at genome‐wide scale while natural selection shapes genetic variation patterns at specific loci possibly involved in adaptation in seasonally migratory insects.

How do individuals across diverse societies navigate interpersonal conflicts? We investigated wisdom-related strategies—such as intellectual humility, perspective-taking, and compromise—across eleven countries. In Study 1 (N=2,493), autobiographical recall of real-world conflicts yielded a robust three-factor structure: Perspectival Metacognition, Conflict Resolution, and Self-Transcendence. Study 2 (N=1,952) replicated this structure using standardized scenarios of social rejection and trust betrayal, establishing approximate measurement invariance across cultures. Though wisdom features were largely consistent across regions, Continental East Asian samples scored highest on Perspectival Metacognition, whereas regions endorsing independent agency were more likely to actively seek Conflict Resolution. At the same time, we observed robust individual and situational differences. In both studies, higher need for cognition and relational self-construal were aligned with wiser strategy use. Situationally, conflicts involving social rejection (vs. trust betrayal) elicited lower negative affect in the open-ended reflections and higher scores of wisdom-related strategies. Indeed, we observed high cross-situational variability: within-person variance exceeded between-person differences in all Study 2 samples (accounting for 70% of variance), challenging trait-centric conceptualizations of wisdom. These findings suggest that wisdom in conflict is less a stable trait and more a situationally grounded affordance, universally organized around three core metacognitive processes.

Public understanding is critical for invasive alien species (IAS) management, yet national-scale cognition patterns remain understudied. We analyzed TikTok and Sina Microblog data to assess public cognition in China regarding three IAS: Solidago canadensis , Solenopsis invicta , and Trachemys scripta . Three dimensions of cognition, including focus (high-frequency terms), associations (term-pair linkages), and tendencies (sentiment polarity), were quantified using word frequency, semantic co-occurrence networks, and quantile-based sentiment analyses, respectively. Results revealed cross-species disparities: On TikTok, S. canadensis was concerned with its invasiveness (e.g., "Found everywhere", "Fertility → Overlord flower"), while Sina Microblog emphasized its agricultural utility (e.g., "Hu Sheep", "Digestion → Sheep dung"). S. invicta discussions centered on recognition/coping measures on TikTok (e.g., "Red fire ant", "Wound → Soapy water") versus ecological impacts on Sina Microblog (e.g., "Invasive species", "Consequence → Environment"), and T. scripta focused on pet raising issues (TikTok) (e.g., "My home", "Eyes → Can't open eyes") and regulatory policies (Sina Microblog) (e.g., "Release", "Heavy penalty → Country"). These disparities likely stem from species-specific traits and their interactions with human. Cross-platform differences were pronounced: TikTok’s experiential narratives showed polarized sentiment ( S. canadensis median = 0.63; lower/upper quartiles = 0.06/0.94), while Sina Microblog’s policy-driven discourse was predominantly positive (medians: 0.60–0.89). Algorithmic biases amplified these differences: prioritizing emotional content (TikTok) versus institutional narratives (Sina Microblog). A key gap was the scarcity of management strategies, limiting public engagement. Our findings advocate for platform-specific interventions (e.g., TikTok demos of removal techniques) and algorithmic transparency to improve IAS management.

Our knowledge of how niche dynamic patterns respond to invasion trajectories and influence invasion risk prediction is elusive for the majority of notorious invaders, hindering scientific understanding, biosecurity planning and practice, and management implementation of biological invasions. We used Mikania micrantha, one of the world's worst invasive alien species (IAS), to test the hypothesis that multiple invasion trajectories could induce niche dynamics inconsistency and increase risk uncertainty of IAS. We compiled a robust database of M. micrantha occurrence across its native range in Central and South America and invaded range in China. This database was used to clarify different invaded ranges and invasion trajectories of M. micrantha in China. Principal components analysis of climatic variables associated with the database was used to explore the niche dynamic patterns associated with multiple invasion trajectories of M. micrantha. Maximum entropy algorithm was used to predict the high‐risk area of M. micrantha invasion using occurrence datasets for invaded ranges where niches remained conservative, and to detect area changes with the inclusion of occurrence datasets for invaded ranges where niche shifts occurred. M. micrantha invasion occurred in three geographically distinct regions, with conservative climate niches in southern and southeastern China and climatic niche shifts in southwestern China. A high‐risk area for M. micrantha invasion spanned multiple provinces and cities and expanded considerably with the inclusion of the occurrence dataset for southwestern China. Our findings contribute to the theoretical understanding of invasion mechanisms and the practical optimization of biosecurity planning and implementation.

Our knowledge of how niche dynamic patterns respond to invasion trajectories and influence invasion risk prediction is elusive for the majority of notorious invaders, hindering scientific understanding, biosecurity planning and practice, and management implementation. We used Mikania micrantha, one of the most notorious invasive alien species in the world, to test the hypothesis that multiple invasion trajectories could induce niche dynamics inconsistency and increase risk uncertainty of invasive alien species. We compiled a robust database of M. micrantha occurrence across its native range in Central and South America and invaded ranges in China. This database was used to clarify different invaded ranges and invasion trajectories of M. micrantha in China. Principle Component Analysis of climatic variables associated with the database was used to detect its niche dynamic patterns associated with multiple invasion trajectories. Maximum Entropy algorithm was used to predict the high-risk area of M. micrantha invasion using occurrence datasets for invaded ranges where niches remained conservative, and to identify area changes with the inclusion of occurrences datasets for invaded ranges where niche shifts occurred. M. micrantha invasion occurred in three geographically distinct regions, with conservative climate niches in southern and southeastern China and climatic niche shifts in southwestern China. A high-risk area for M. micrantha invasion spanned multiple provinces and cities, and expanded considerably with the inclusion of the occurrence dataset for southwestern China. Our findings contribute to the theoretical understanding of invasion mechanisms and the practical optimization of biosecurity planning and implementation.

To explore how the concentration of suspended solids affects the spectral characteristics and what quantitative relationship exists between them. We selected the Baiyangdian as the study area, this paper synchronously collects sampling points' spectral and water quality data. It establishes the quantitative relationship between suspended solids concentration and spectral reflectance combined with laboratory simulation experiments to realize the suspended solids inversion model. The separability of suspended solids in Baiyangdian water is studied by analyzing variance, and the separability band interval is selected. The laboratory simulation experiment mechanism analysis is used to verify whether the interval range is reasonable. The Pearson correlation coefficient method determines the band with an enormous correlation difference in this interval for combination, and the optimal inversion model is constructed. The results show that the separability band range of water reflectance and suspended solids concentration is 376-1326nm, and the sensitive band with the highest positive and negative correlation between normalized water reflectance and suspended solids concentration is 760nm and 491nm. The water suspended solids concentration inversion model is constructed after combining the two bands. The research shows that the inversion model of the sinusoidal curve fitting model has a good effect, and the coefficient of determination of equation fitting can reach 81%.

Rapid temperature changes in mountain ecosystems pose a great threat to alpine plant species and communities. Rhododendron species, as the major component of alpine and sub-alpine vegetation, have been demonstrated to be sensitive to climate changes. Therefore, understanding how alpine Rhododendron species spread to new habitats and how their geographical distribution range shifts is crucial for predicting their response to global climate change and for facilitating species conservation and reintroduction. In this study, we applied MaxEnt modeling and integrated climate, topography, and soil variables in three periods under three climate change scenarios to predict the suitable habitat for four Rhododendron species in China. We measured the potential distribution change in each species using the change ratio and the direction of centroid shifts. The predicted results showed that (1) the threatened species R. protistum would have a maximum decrease of 85.84% in its distribution range in the 2070s under RCP 8.5, and R. rex subsp. rex as a threatened species would experience a distribution range expansion (6.62–43.10%) under all of the three climate change scenarios in the 2070s. (2) R. praestans would experience a reduction in its distribution range (7.82–28.34%) under all of the three climate change scenarios in the 2070s. (3) The four Rhododendron species would be moved to high latitudes in the north-westward direction as a whole in the future, especially the two threatened species R. protistum and R. rex subsp. rex. (4) Aside from climate variables, soil factors also exert an important influence on the distribution of Rhododendron species. This study revealed the species-specific response of Rhododendron species to climate change. The results can not only provide novel insights into conservation strategies of Rhododendron species, but also propose a valuable method for the habitat selection during the reintroduction of endangered species.

1. Hyphantria cunea is a problematic invasive species that has caused considerable damage to agricultural and forestry ecosystems in China. 2. We compared 19 bioclimate variables between its native country (the United States of America) and China to elucidate the environmental factors associated with its presence. Using present climate data (1970–2000) and projected future climate data (2050 and 2070) based on two Representative Concentration Pathways (RCPs 2.6 and 8.5), we used MaxEnt to predict the suitable habitat areas for H. cunea in the USA and China. Using these analyses, we predicted the niche change of H. cunea in China using the ‘ecospat’ package in R. 3. Our model predicts that climate change will generally increase the extent of suitable habitat in both China and the USA, although low latitude areas will be limited by future climate change. We also report low niche overlap between the USA and Chinese populations of H. cuena and significant differences in bioclimate variables associate with its presence in each country. Therefore, our results suggest H. cunea has adapted to several climatic conditions in China. This indicates the niche of H. cunea may shift and adapt to novel environmental conditions over the course of its spread. 4. Overall, the analysis of the environmental characteristics, niche changes, and suitable areas of H. cunea provides a basis for pest control and management strategies aimed at preventing further spread. Our methods may also be used to study other similar invasive species.