Individual Traits Research Articles

Search for signals of positive selection of circadian rhythm genes PER1, PER2, PER3 in different human populations.

The diversity of geographically distributed human populations shows considerable variation in external and internal traits of individuals. Such differences are largely attributed to genetic adaptation to various environmental influences, which include changes in climatic conditions, variations in sleep and wakefulness, dietary variations, and others. Whole-genome data from individuals of different populations make it possible to determine the specific genetic sites responsible for adaptations and to further understand the genetic structure underlying human adaptive characteristics. In this article, we searched for signals of single nucleotide polymorphisms (SNPs) under selection pressure in people of different populations. To identify selection signals in different population groups, the PER1, PER2 and PER3 genes that are involved in the coordination of thermogenic functions and regulation of circadian rhythms, which is directly reflected in the adaptive abilities of the organism, were investigated. Data were analyzed using publicly available data from the 1000 Genomes Project for 23 populations. The Extended Haplotype Homozygosity Score statistical method was chosen to search for traces of selection. The comparative analysis performed identified points subject to selection pressure. The SNPs were annotated through the GWAS catalog and manually by analyzing Internet resources. This study suggests that living conditions, climate, and other external factors directly influence the genetic structure of populations and vary across races and geographic locations. In addition, many of the selection variants in the PER1, PER2, PER3 genes appear to regulate biological processes that are associated with major modern diseases, including obesity, cancer, metabolic syndrome, bipolar personality disorder, depression, rheumatoid arthritis, diabetes mellitus, lupus erythematosus, stroke and Alzheimer's disease, making them extremely interesting targets for further research aimed at identifying the genetic causes of human disease.

Impacts of microplastic ingestion on fish communities in Haizhou Bay, China

Microplastics are pervasive throughout aquatic ecological communities. While their negative impacts on the life history traits of aquatic species are well studied, the effects on community dynamics remain elusive. Consequently, community-level assessments of microplastic effects on marine food webs are largely lacking, creating significant knowledge gaps regarding marine ecosystem structure and dynamics in the context of microplastic contamination. Here we expand a multispecies size-spectrum model by incorporating microplastic impacts on individual life-history traits, ultimately allowing us to study microplastic-mediated structural and functional changes in fish communities. As expected, microplastic ingestion may drive species extinction, but the microplastic-to-food ratio threshold for extinction is species-specific, and not necessarily correlated with species’ asymptotic weights. Interestingly, species responses to microplastics also propagate through the community as ingestion triggers both bottom-up and top-down effects on community dynamics. Which specific type of cascading effect is dominating depends on which species is ingesting microplastics as well as its trophic role in the community. Generally, low-trophic-level species ingesting microplastics can exert large detrimental effects on community biomass. Thus, this study highlights the necessity for a comprehensive risk assessment of species-specific responses to microplastic contamination as well as an understanding of individual species’ role in their communities.

The polychotomy of NFT ownership: Motivational heterogeneity and underlying drivers

We investigate the motivations behind non-fungible token (NFT) ownership. Utilizing survey data from NFT owners, we identify four distinct groups based on their primary motivations: (1) Utilizers, who emphasize functional uses; (2) Socializers, motivated by community and networking; (3) Speculators, focused on profit potential; and (4) Aesthetes, who appreciate artistic and cultural aspects. Our analysis indicates that individual traits such as risk-taking, impulsivity, and investment knowledge significantly influence group membership. These findings suggest that NFT users are a diverse cohort with varied motivations rather than a homogeneous group.

Individual cognitive traits can be predicted from task-based dynamic functional connectivity with a deep convolutional-recurrent model.

There has been increased interest in understanding the neural substrates of intelligence and several human traits from neuroimaging data. Deep learning can be used to predict different cognitive measures, such as general and fluid intelligence, from different functional magnetic resonance imaging experiments providing information about the main brain areas involved in these predictions. Using neuroimaging and behavioral data from 874 subjects provided by the Human Connectome Project, we predicted various cognitive scores using dynamic functional connectivity derived from language and working memory functional magnetic resonance imaging task states, using a 360-region multimodal atlas. The deep model joins multiscale convolutional and long short-term memory layers and was trained under a 10-fold stratified cross-validation. We removed the confounding effects of gender, age, total brain volume, motion and the multiband reconstruction algorithm using multiple linear regression. We can explain 17.1% and 16% of general intelligence variance for working memory and language tasks, respectively. We showed that task-based dynamic functional connectivity has more predictive power than resting-state dynamic functional connectivity when compared to the literature and that removing confounders significantly reduces the prediction performance. No specific cortical network showed significant relevance in the prediction of general and fluid intelligence, suggesting a spatial homogeneous distribution of the intelligence construct in the brain.

Phytoplankton morphological traits and biomass outline community dynamics in a coastal ecosystem (Gulf of Trieste, Adriatic Sea)

AbstractTrait-based ecology has recently gained increasing importance in phytoplankton research. In particular, the taxonomic and morphological traits, such as size and shape of phytoplankton cells, can help to unveil the ecological processes and their drivers in the pelagic domain. Our study aims to shed light on the trophodynamics of phytoplankton communities in a coastal ecosystem in the northern Adriatic Sea (Gulf of Trieste) using data on individual traits such as biomass, size and shape of phytoplankton taxa during a one-year study. The phytoplankton parameters were investigated at the levels of the whole community, groups, and individual cells, analysing also the probability distributions of biomass and size of the latter level. The results showed good agreement between abundance and biomass data, as well as individual size and biomass with differences partly explained by cell shapes. We have emphasized the role of the local freshwater source in bottom-up control, alternating with top-down control of phytoplankton dynamics through taxonomic and morphological diversity. The predominant bimodal and non-power law distribution, especially during and around the biomass peaks, confirmed the importance of nano- and microphytoplankton size classes and the role of blooms in destabilizing the trophic webs. We suggest that the analyses of distribution types of individual cell size and biomass can be appropriate to spot ecological processes driving to unconstrained phytoplankton proliferation or to periods of trophic web stability.

Unpacking the Link Between Big Five Personality Traits and Waqf Participation in The Malaysian Armed Forces

This research delves into the utilization of Personality Traits theory to comprehend the underlying motivations behind Waqf practices among military personnel. Implementing a structured questionnaire as the main tool for data collection, a total of 487 responses were secured. The research tools utilized in this study were derived from prevailing scholarly literature in the realm of personality psychology. The empirical findings of this study validate the substantial influence of personality traits, encompassing behavioral control and environmental components, on the inclination of military personnel to participate in endowment practices. This elucidates the complexities inherent in charitable contributions within this specific cohort. The discoveries underscore the importance of individual personality traits in shaping philanthropic behaviors among military personnel. Elements such as behavioral control and environmental factors play pivotal roles in molding the propensity towards Waqf practices within this distinct demographic. These insights harbor practical implications for policymakers, military institutions, and scholars, furnishing a more profound insight into how personality traits and environmental elements impact endowment behaviors. This investigation emphasizes the necessity of taking into account personality traits when scrutinizing charitable endeavors among military personnel. By comprehending these motivations, policymakers and military entities can more effectively endorse and bolster Waqf practices among their members. Furthermore, these results contribute to the wider discussion on the convergence of personality psychology and philanthropy, enhancing our understanding of charitable behaviors in specialized settings such as the military.

Morphological Traits Are Not Consistently Related to Population Size in Four Migratory Caribou Populations Across North America.

To develop effective management to maintain or restore populations of large herbivores, wildlife managers require sound empirical data on their variations in size and associated parameters. Many studies have highlighted links between morphological traits of individuals and population density; however, less attention has been devoted to whether or not morphological traits can reliably inform on population size in years when no population estimates are available. We evaluated the relationships between three morphological traits (hind foot length, body mass, and body fat) and population size interpolated over three decades, for four migratory caribou (Rangifer tarandus) herds in northern Canada and Alaska. Our sample included 8865 measurements of 4473 individuals. We used a Bayesian modeling approach to evaluate the relationships between morphology and population size across different sex and age classes, considering different temporal scales and, when possible, phases of population growth or decline. We found that morphological traits were not consistently linked to population size. Statistically significant relationships existed for some combinations of herd and age classes, but weak to absent relationships were more common. Our study suggests that morphological traits alone cannot replace data obtained from aerial surveys to approximate population size when population trends are unknown. We discuss the usefulness of morphological traits to explain population size, and recognize their role as complementary metrics to inform the management and conservation of large herbivores, but conclude that morphological data should not be used to predict population size without information on population trends.

The National Trend of Data of the Scale of Attitude Toward Culture of Living with Disaster Risk (SAC-LDR)

In this study, we analyzed data collected from an internet survey targeting Japanese citizens on the Scale of Attitude toward Culture of Living with Disaster Risk (SAC-LDR), which was proposed in our previous study. The scale quantifies respondents’ attitude toword living with nature and its risks, to examine how the SAC-LDR scores are affected by the respondents’ attributes, such as age or lifestyle, and frequency distributions and correlations between variables. We found that: (1) the SAC-LDR scores had a mean value of 41.1 out of 60 and displayed not a completely normal distribution, but a distribution with slightly long left tail; (2) the SAC-LDR scores had a high correlation with the Power to Live with Disasters, which represents individual traits favorable to surviving through disasters; and (3) the SAC-LDR scores displayed regional differences within Japan.

From unwanted to wanted: Blending functional weed traits into weed distribution maps

AbstractSite‐specific weed management (SSWM) is increasingly employed to reduce herbicide inputs. Incorporating functional traits of weed species allows for the selection of SSWM methods that effectively reduce the abundance of weeds with a high competitive potential (disservice) while preserving weeds that provide beneficial ecosystem services (service). In this study, we aim to assess relevant weed functional traits and translate this information into a spatial trait distribution map for weed (dis‐)service provision. The distribution of weed abundance in a field was recorded using a spatial grid. Data on functional traits for the recorded weed species were extracted from published datasets and combined into the two variables, service and disservice. Individual traits (service/disservice) were weighted for each pixel of the weed distribution map based on the number of individual plants per species. Principal component analysis was employed to generate independent variables to describe the potential for service and disservice provision. As a result, two (dis‐)service trait‐based distribution maps were generated: one highlights field areas that provide enhanced ecological services, while the other displays areas with a high disservice potential. The results show that around 61% of the area in the field had a high service potential. The area with a high disservice was slightly higher than the half of the area with a high service, while about 32% of the field has both high service and disservice potential in the same area. This study presents a spatially explicit approach to incorporate information on weed functional traits into SSWM approaches targeted at reducing weed competition while at the same time enhancing weed functional diversity.

AN ANALYSIS OF BEHAVIOURAL FINANCE AND ITS INFLUENCE ON INVESTMENT DECISION

This research delves into the fascinating realm of Behavioural Finance, exploring its significant influence on investment decision-making among residents in India's National Capital Region (NCR). By drawing on insights from relevant studies, this work seeks to uncover the intricate link between human behaviour and financial decision-making within this demographic. The study begins by examining the unique financial behaviours of investors in the region, aiming to identify the key investor profiles that shape the investment environment. As a multidisciplinary field combining elements of psychology, sociology, and finance, Behavioural Finance provides the primary framework for this exploration. The research distinguishes between its micro and macro perspectives: the detailed analysis of individual behavioural traits of investors and the broader identification of inefficiencies in the market. Recognizing the pervasive impact of behavioural biases on investment behaviours and decisions, this study offers an in-depth review of diverse research within the Behavioural Finance domain. It sheds light on how human psychology and social dynamics interact with financial decision-making, highlighting the crucial role of Behavioural Finance in contemporary financial practices. In an era where financial markets are not merely governed by rationality but are also shaped by complex human behaviours, this research offers valuable insights into the dynamics of Behavioural Finance. By illuminating the distinct investment choices, the study aims to deepen our understanding of the factors influencing these decisions, ultimately equipping investors and financial professionals with more informed decision-making strategies.

Impact of Social Media Use, Social Comparison & Self-Esteem Among Adolescents

The present research examined how social media, social comparison, and self-esteem affect adolescents. After an extensive literature review, these hypotheses were developed. 1) Social media use, social comparison, and self-esteem among teenagers will be significantly related. 2) Social media use will affect self-esteem among adolescents.3) Adolescent self-esteem will be affected by social comparison.4) Gender will affect adolescent social media use, comparison, and self-esteem of the 249 samples, 153 are female and 96 are male. Survey participants were 14–25 years old. Data were purposively sampled from Faisalabad educational institutions. The findings were assessed using these methods. Participant demographics were collected using a sheet. Adolescent self-esteem was measured with a scale. The Social Comparison scale measured self-comparative behavior. Participants' social media use was measured using a scale. Analyze the data using correlation, regression, and independent sample tests. Findings illuminate individual traits and tendencies.

Error management atmosphere, employee career resilience and employee innovation behavior: The mediating role of psychological empowerment

In order to study the specific influence path and mechanism of different dimensions under error management culture on employees' innovation behavior, this paper takes the perception of error management atmosphere and employee career resilience as independent variables, psychological empowerment is taken as intermediary variable, active innovation motivation is taken as the moderating variable of psychological empowerment and employee innovation behavior, and employee innovation behavior is taken as the dependent variable. This paper systematically discusses the multi-dimensional and multi-level relationships among error management culture, employee occupational resilience, psychological empowerment, active innovation motivation and employee innovation behavior. The research finds that by enhancing employees' psychological empowerment, that is, making them feel the meaning, self-efficacy, self-determination and influence of work, enterprises can stimulate employees' intrinsic motivation and encourage them to be more actively involved in innovation activities. This research not only enriches our understanding of how organizational culture shapes the way employees behave, but also reveals the critical role that individual employee traits (such as occupational resilience) and psychological states (such as psychological empowerment) play in the innovation process. This paper provides some suggestions on how to build a culture that encourages innovation and tolerates errors.

Genetic Insights into Externalizing and Internalizing Traits through Integration of the Research Domain Criteria and Hierarchical Taxonomy of Psychopathology.

There is considerable comorbidity between externalizing (EXT) and internalizing (INT) psychopathology. Understanding the shared genetic underpinnings of these spectra is crucial for advancing knowledge of their biological bases and potential health impacts, and for informing empirical models like the Research Domain Criteria (RDoC) and Hierarchical Taxonomy of Psychopathology (HiTOP). We conducted a multivariate genome-wide association study (GWAS) of EXT and INT psychopathology by applying genomic structural equation modeling to summary statistics from 16 EXT and INT traits in European-ancestry individuals (n = 16,400 to 1,074,629). Downstream analyses explored associations across RDoC units of analysis (i.e., genes, molecules, cells, circuits, physiology, and behaviors). The GWAS identified 409 lead single nucleotide polymorphisms (SNPs) for EXT, 85 for INT, and 256 for EXT+INT (i.e., shared) traits. Bivariate causal mixture models estimated that nearly all EXT and INT causal variants overlapped, despite a genetic correlation of 0.37 (SE = 0.02). Drug repurposing analyses identified potential therapeutic targets, including perturbagens affecting dopamine and serotonin pathways. EXT genes had enriched expression in GABAergic, cortical, and hippocampal neurons, while INT genes were more narrowly linked to GABAergic neurons. EXT+INT liability was associated with reduced grey matter volumes in the amygdala and subcallosal cortex. These findings reveal both genetic overlap and distinct molecular and neurobiological pathways underlying EXT and INT psychopathology. By integrating genomic insights with the RDoC and HiTOP frameworks, this study advances our understanding of the mechanisms driving these dimensions of psychopathology.

Human brain state dynamics are highly reproducible and associated with neural and behavioral features.

Neural activity and behavior vary within an individual (states) and between individuals (traits). However, the mapping of state-trait neural variation to behavior is not well understood. To address this gap, we quantify moment-to-moment changes in brain-wide co-activation patterns derived from resting-state functional magnetic resonance imaging. In healthy young adults, we identify reproducible spatiotemporal features of co-activation patterns at the single-subject level. We demonstrate that a joint analysis of state-trait neural variations and feature reduction reveal general motifs of individual differences, encompassing state-specific and general neural features that exhibit day-to-day variability. The principal neural variations co-vary with the principal variations of behavioral phenotypes, highlighting cognitive function, emotion regulation, alcohol and substance use. Person-specific probability of occupying a particular co-activation pattern is reproducible and associated with neural and behavioral features. This combined analysis of state-trait variations holds promise for developing reproducible neuroimaging markers of individual life functional outcome.

Assertive behavior. Structural analysis

Introduction. A brief history of the emergence of the concepts of “assertiveness” and «assertive behavior» is presented , and their definitions are given. The importance of assertive behavior for personality development is shown. Argues for the need to investigate the structural components of assertive behavior. Materials and Methods. The research methods used were: structural analysis of modern scientific literature on the research problem, summarizing, comparing, systematizing and interpreting data. Results. Based on the analysis, comparison and systematization of the concepts of assertiveness and assertive behavior presented in modern domestic and foreign scientific literature, a complex of the most significant structural components of assertive behavior is identified. These include: self-confidence, autonomy, responsibility, self-control, communication skills, positive and tolerant attitudes, constructive ways of resolving conflicts and disputes. A model of assertive behavior is presented. It is shown that in the works aimed at increasing assertiveness and assertive behavior, the emphasis is placed on improving individual personality traits, but this approach will not give an optimal result, since it is necessary to have a complex impact on all components of the assertive conduction structure. Discussion and Conclusions. The study of theoretical approaches to the study of assertive behavior allows us to propose an expanded definition of this concept as a holistic entity, identify its main structural elements, and develop a model of assertive behavior. It is shown that when developing formative programs of assertive behavior it is necessary to have a complex impact on all components of its structure.

A Case Study on the Odor Preferences and Influencing Factors in Chinese Residential Environments

Research on odor preference is needed to improve indoor environment quality. There-fore, to create a better odor environment in the living space, it is necessary to determine the common characteristics of odor preferences in the living environment for individuals with a similar cultural background. In this study, representative odors that are found in Chinese living spaces were selected and the odor preferences and individual traits were examined using online surveys. A total of 1236 valid responses were collected and the factors affecting odor preferences were assessed, including social, geographic, and behavioral attributes, using correlation and descriptive analysis. The results revealed that gender, age, occupation, income, mode, and frequency were correlated with odor preference characteristics in the living environment and were the primary factors for the odor preference characteristics. Further analysis revealed that the odor preferences across the gender, age, income, and frequency groups were consistent with the trend for the overall characteristics. The results of the study showed that there were significant differences in odor preferences in the living environment across occupations and living patterns. Different occupational groups showed different characteristics in odor preferences, while the complexity of living patterns and the frequency of odor exposure also had a significant impact on odor preferences. These research findings will enable us to develop customized fragrance solutions based on specific olfactory preferences related to gender, age, occupation, income level, and lifestyle. Integrating the study conclusions into the spatial layout, selection of decorative materials, and ventilation design of residential spaces has practical significance for creating living environments that better meet the needs of residents.

Seasonal variability and seagrass traits affect methane fluxes in a subtropical meadow

Abstract Plant traits which vary both within and between species often drive biogeochemical cycling. Understanding the relative role of within‐ and between‐species trait variability in driving carbon cycling is essential to scaling site measurements to global carbon budgets. In seagrass meadows, carbon and nitrogen mineralization rates and associated greenhouse gas emissions are highly variable, impeding our ability to reliably predict whether meadows are net carbon sinks. Evaluating the influence of within‐ and between‐species trait variability on greenhouse gas fluxes will improve our understanding of local‐scale drivers of greenhouse gas production and consumption in seagrass meadows. To test the effects of plant traits on dissolved greenhouse gas fluxes, we performed mesocosm incubations with live, intact seagrass plants. We compared methane (CH4) and nitrous oxide (N2O) fluxes under dark and light conditions from sediments dominated by Halodule wrightii and Thalassia testudinum across dormant, early and peak growing seasons in a subtropical meadow along the west coast of peninsular Florida. We also measured oxygen (O2) fluxes to interpret greenhouse gas fluxes within the context of community metabolism. We measured several seagrass traits, such as above‐ and below‐ground biomass and leaf and root area and assessed their impact as well as the impact of species identity on dissolved gas fluxes. We found that abiotic factors linked to metabolism (i.e. light and temperature) influenced greenhouse gas fluxes across seasons. In addition to light conditions and sampling month, plant size (a composite trait variable) was a significant predictor of O2 consumption and CH4 production under dark conditions, and better predicted fluxes than individual plant traits. CH4 production was slightly higher in H. wrightii‐dominated sediments, but species identity was less important than plant size in driving CH4 production. N2O fluxes were low and not influenced by plant traits or species identity. Synthesis: Our results indicate that within‐species more so than between‐species trait variability drives the direction and magnitude of CH4 fluxes in seagrass meadows. We identified a trade‐off where seagrass biomass is often associated with enhanced sediment carbon storage, but in our study, plant size promoted CH4 production, potentially offsetting the benefits of long‐term storage.

From Voxel to Gene: A Scoping Review on MRI Radiogenomics' Artificial Intelligence Predictions in Adult Gliomas and Glioblastomas-The Promise of Virtual Biopsy?

Gliomas, including the most severe form known as glioblastomas, are primary brain tumors arising from glial cells, with significant impact on adults, particularly men aged 45 to 70. Recent advancements in the WHO (World Health Organization) classification now correlate genetic markers with glioma phenotypes, enhancing diagnostic precision and therapeutic strategies. This scoping review aims to evaluate the current state of deep learning (DL) applications in the genetic characterization of adult gliomas, addressing the potential of these technologies for a reliable virtual biopsy. We reviewed 17 studies, analyzing the evolution of DL algorithms from fully convolutional networks to more advanced architectures (ResNet and DenseNet). The methods involved various validation techniques, including k-fold cross-validation and external dataset validation. Our findings highlight significant variability in reported performance, largely due to small, homogeneous datasets and inconsistent validation methods. Despite promising results, particularly in predicting individual genetic traits, the lack of robust external validation limits the generalizability of these models. Future efforts should focus on developing larger, more diverse datasets and integrating multidisciplinary collaboration to enhance model reliability. This review underscores the potential of DL in advancing glioma characterization, paving the way for more precise, non-invasive diagnostic tools. The development of a robust algorithm capable of predicting the somatic genetics of gliomas or glioblastomas could accelerate the diagnostic process and inform therapeutic decisions more quickly, while maintaining the same level of accuracy as the traditional diagnostic pathway, which involves invasive tumor biopsies.

Exploring intraspecific and interspecific variation of coral reef algae using a novel trait‐based framework

Abstract The development of trait‐based approaches has accelerated our understanding of how communities assemble, respond to environmental change and may best be managed in the Anthropocene. Understanding the magnitude and pattern of interspecific variability forms a critical underpinning of trait‐based approaches while exploring intraspecific variability can identify the potential of species to adapt to changing environmental drivers. Our work is motivated by the critical need for a novel conceptual framework for understanding the functional ecology of macroalgae, as the current paradigm is still mired in functional group models developed in the 1980s. Our objective was to quantify interspecific and intraspecific functional trait variability in three common and morphologically diverse species of tropical marine macroalgae by exploring traits relating to the ecological functions of resource acquisition, resistance to herbivory, and resistance to physical disturbance and the trade‐offs between them. We quantified intraspecific and interspecific variability of 11 functional traits for three common and morphologically diverse species of tropical macroalgae from five fringing reefs of Mo'orea, French Polynesia that were likely to capture a wide range of environmental variability. Differences in traits among species and sites were determined with PERMANOVA, visualised with non‐metric multidimensional scaling, and trade‐offs between pairs of traits explored with correlation. Finally, spatial patterns among select traits across all species were quantified. Species clustered together in distinctly different trait spaces driven by trade‐offs among suites of functional traits. Two of three species had considerable intraspecific variability, though this variability occurred at different scales, while one clustered tightly. Exploration of individual traits across species and sites revealed trade‐offs between two strategies for resource acquisition, growing tall and strong versus investing in large surface area. Synthesis. We captured novel patterns of interspecific and intraspecific variability for tropical marine macroalgae. We found fundamental differences in traits between species that may represent ecological strategies while considerable intraspecific variability demonstrates a wide range in abilities to respond to environmental drivers. Overall, our work provides novel insights into intra and interspecific trait variation that form an essential underpinning for using a trait‐based framework in a taxon that is increasingly dominant on tropical reefs.

Intraspecific variation in leaf morphology of three widespread woody species along climatic gradients

Abstract The variation and plasticity of leaf morphology plays a pivotal role in the response to environmental changes for plant individuals. Discovering the large-scale pattern of such variation can reveal plants' general adaptive strategies. We analyzed leaf morphology of three widespread woody species in the northern hemisphere using specimen data from the iDigBio and GBIF databases, to investigate the variations in the individual mean traits, in the inter- and intra-individual variability of traits, and in the allometry between traits, along climatic gradients. We found that larger and wider leaves were associated with warmer, wetter and low-sunlight habitats, while smaller but wider leaves are linked to higher wind speed, indicating the response of leaf morphology to multiple climate stresses. The inter-individual variation in leaf area was smaller in colder and windier conditions, suggesting the trait convergence among individuals under environmental filtering, while the intra-individual variation in leaf relative width was smaller in warmer habitats, indicating the similar growth optimum of leaves within one individual in more favorable conditions. Finally, the allometric exponent between leaf length (X-axis) and width (Y-axis) became greater under lower solar radiation and higher wind speed, while the squared correlation coefficient (r2) indicating phenotypic integration showed a decoupling trend under colder conditions, indicating that climate affected the variation tendency of leaf relative width during leaf enlargement. These results reveal the common patterns of leaf morphology responding to climate variation spatially and underscore the necessity to consider inter- and intra-individual variability when examining plant responses to environmental changes.