4 Discussion
We analyzed genomic data and phenotypic traits to explore the genetic architecture of several environment-associated adaptations of Q. longinux, a dominant evergreen forest tree species on the subtropical island of Taiwan in East Asia. We identified several SNPs with strong effects on adaptation to environmental factors, including some factors that have rarely been discussed in GEA studies (e.g., soil- and wind-related factors). We found that leaf traits were influenced by the interaction of demographic and environmental factors. Moreover, we determined that the populations in northern and southeastern Taiwan are the most vulnerable to future climate change. Finally, we identified populations with unique genetic and phenotypic characteristics in southern Taiwan. These populations are potential targets for conservation efforts in forest management to preserve unique and adaptive genetic resources.
 
4.1 Distinct genetic separation of southern populations from eastern and western populations in Taiwan
Three putative genetic clusters were classified using PCA and StrAuto. The eastern and western clusters were mainly separated from each other by the CMR and were mixed in northern and southern Taiwan. Similar patterns of east–west divergence have been observed for other plants in Taiwan [98, 99], implying that the mountain ridges and rugged topography act as profound barriers to gene flow and contribute to the divergence of species occupying low-to-middle elevations in Taiwan. The third cluster, HC, was limited to the Henchung Peninsula in southern Taiwan, which has been identified as the main glacial refuge in Taiwan for other Fagaceae species, such as Q. glauca and Castanopsis carlesii [100, 101]. The EEMS analysis revealed higher genetic diversity in HC and genetically admixed populations in southern and northern Taiwan. The populations of HC were genetically differentiated from other populations, as suggested by higher pairwise FST and distinct trajectory of changes in Ne in the past 1,000 years. Taken together, our results reveal significant genetic differentiation between the eastern cluster, western cluster, and HC and suggest that HC, morphologically classified as Q. longinux var. kuoi, in the southernmost part of Taiwan may have diverged earlier than the other two clusters.
 
A distinct group of Q. longinux populations, group HC, with unique leaf and fruit traits in tropical marine climates in southern Taiwan was previously classified as Q. longinux var. kuoi. This variety has no whitish epicuticular wax coating on abaxial surfaces [48]. The classification of this variety is consistent with the genetic and morphological separation of the southernmost population from other populations of Q. longinux that we observed in the present study. Niche analyses also demonstrated that the habitats harboring Q. longinux var. kuoi were significantly different from those of the other populations, with no ecological overlaps, indicating that Q. longinux var. kuoi may face different environmental pressures. Moreover, we found evidence of adaptive divergence between Q. longinux var. kuoi and other populations. For example, the low spring precipitation and high clay content in habitats in southeastern Taiwan may act as strong environmental stresses that initiate genetic and phenotypic adaptation (e.g., drought resistance) in response to local conditions. In plant species, hostile environmental conditions in edge populations prompt local adaptation processes [102]. The substantial divergence, relatively high genetic diversity, and high offsets of the populations in southern Taiwan indicate that Q. longinux var. kuoi is a conservation unit that should be prioritized for protection as a source of adaptive genetic variations related to high temperature and drought resistance under climate change.
 
4.2 Topography as a key driver of genetic differentiation in Quercus longinux
The IBR model caused by the topographical barrier was the most influential factor restricting gene flow and driving the overall genetic differentiation of Q. longinux. The conductance layers of topographical barriers and the EEMS analysis also revealed significantly higher resistance in regions at high elevations. The diverse topography and mountainous areas of Taiwan have led to genetic diversification of various plants and animals [103, 104]. Elevation has been recognized as the main driver of genetic differentiation in other Quercus species distributed in temperate regions [105]. We found that topographical resistance in alignment with mountain ridges was the most profound factor contributing to genetic differentiation on Taiwan Island. Fagaceae typically disperse their seeds through rodents or birds, while their pollens are transported by wind [106-109]. Rodents are the primary carriers and predators of several Quercus species in temperate ecosystems [110, 111] and subtropical forests [112]. Studies suggest that genetic clusters of rodents found at mid-elevations in Taiwan, where most Fagaceae species grow, are separated by mountain ridges and rugged topography [113-115]. Therefore, the dispersal distance of Quercus seeds in Taiwan may be limited by the dispersal abilities of sympatric rodents. Monteiro, Veiga [116] also suggested that elevational barriers are a common obstacle to gene flow for animals in tropical and subtropical regions. Animals in these areas face difficulties in crossing high elevations due to their inability to acclimate to sudden changes in temperature [117].
 
4.3 Environmental heterogeneity drives adaptive genetic divergence and phenotypic variation
IBE was the most strongly supported model based on putative adaptive loci, whereas IBR mainly drove genetic differentiation based on all SNPs. PCA also revealed less genetic admixture when genetic differentiation was assessed by GEA outliers compared to neutral SNPs, indicating that the three genetic clusters (i.e., eastern, western, and HC) were exposed to different environmental pressures and had undergone adaptive divergence. However, the partial RDA revealed a large intersection of explained variation (45%) shared by environment, geography, and colonization history, suggesting that environmental variation highly covaried with other confounding factors. Similar covariations have been observed for other evergreen species. For example, the south-to-north postglacial expansion of the red spruce along the Appalachian Mountains created high collinearity between genetic structure, climate gradients, and geographic distributions [118]. Similarly, evergreen subtropical trees in Taiwan underwent south–north expansions after the Last Glacial Maximum and may have developed adaptations to latitudinal gradients of temperature and precipitation, resulting in confounding relationships between geography, genetic structure, and adaptation. Consequently, it was challenging to attribute and disentangle the genetic variation explained by each category of predictors, leading to a non-significant impact of pure climate variables.  
 
Leaf shape is affected by various environmental factors, such as precipitation and temperature, which maximizes photosynthetic efficiency and adaptation to harsh environments [75, 119-121]. We found that several leaf traits of Q. longinux were influenced by environmental factors (Fig. S11; Table S10). The negative correlation between leaf length and annual precipitation contradicts previous findings [51, 122]. However, we observed a positive correlation between annual precipitation and wind speed in winter and a negative correlation between annual precipitation and solar radiation in summer (Fig. S14). Strong wind and weaker solar radiation may counteract the effects of increased annual precipitation on leaf length. Similar confounding effects of climatic factors on leaf growth and elongation were observed in Fagus sylvatica [76]. We demonstrated that the interaction of environment and geographic relationships mainly contributed to the explained variation in leaf traits. Demographic history provided only a limited contribution to leaf variation, suggesting that phenotypic plasticity or local adaptation contributed by local climate surpasses the impact of demographic history on leaf traits.
 
Temperature and precipitation are known drivers of genetic adaptation in Fagaceae [34]. This study expands the environmental factors considered compared to previous GEA studies and demonstrates that significant selection is initiated by multiple environmental factors in an endemic Quercus species. First, we found that wind speed in cold seasons influenced leaf traits and adaptive genetic variation (Table S7; Fig S11). Wind intensity has been shown to reduce plant growth and height and increase stem thickness [123, 124]. Wind also influences transpiration rates and stomatal conductance, indirectly affecting photosynthetic efficiency and water requirements [125, 126]. Some genes correlated with wind speed were also significantly associated with precipitation-related factors (e.g., ATPD, NF-YCP), implying that elevated evaporation rates caused by strong wind may result in drought-like stress, which plants may respond to through similar genetic pathways. Second, we determined that soil-related variables contributed 60% of the variation in adaptive divergence, indicating critical roles of these variables in local adaptation of Q. longinux. The characteristics of soil particle sizes represent the potential water content and salt stress in local soils. In general, soil particle size is negatively correlated with water availability, implying potential abiotic pressure from water deprivation during dry seasons [36, 127]. Consistent with this conclusion, we observed a correlation between genes involved in the response to drought and grid size. In summary, our findings provide a new perspective for future GEA studies by indicating that some environmental variables with important but rarely tested physiological impacts can be used to unravel the intricate mechanisms by which plants respond and adapt to heterogeneous environments.
 
4.4 Adaptive genes underlying local adaptation in Quercus longinux
We identified several genes involved in adaptation to the local environment (Table S6). We also identified two significantly enriched functional pathways, oxidative phosphorylation and photosynthesis, which have been implicated in plant adaptation and physiological responses to abiotic stress [128, 129]. Oxidative phosphorylation helps regulate reactive oxygen species (ROS) generation by plant mitochondria under abiotic stresses. The efficiency and regulation of photosynthesis strengthen the plant and sustain its growth and development under stressful or unfavorable conditions [130]. These results suggest that the identified adaptive SNPs underlie the response to different abiotic stresses. We also observed associations between the allele frequencies of the annotated genes and environmental gradients. For example, loci of ADH1 are strongly associated with annual mean temperature and precipitation in spring. ADH1 is responsive to multiple abiotic stimuli, including low temperature, hypoxia, flooding, salt, and dehydration [131-133]. In legumes, ADH1 is a target of miRNA regulation under water‐deficit to coordinate ROS levels [134]. Under stressful cold situations, ADH1 plays a crucial role in maintaining the stability of membrane structure to enhance cold resistance in plants [128]. Other genes involved in precipitation- and temperature-associated adaptation include orthologs of AT2G40435, which is involved in responses to biotic and abiotic stresses [135, 136]; NET1D, which is expressed in root tissues and mediates uptake in response to stress [137]; and HSP70, which stabilizes and refolds heat-inactivated proteins to protect cells from heat damage [138]. 
 
Although we used several procedures to evaluate the putative adaptive SNPs identified in this study, the interpretations of the constructed GEA relationships and identified outliers are subject to limitations. First, we scanned the outliers using relatively few loci (approximately 2,000 SNPs), which may bias the identified loci and elevate the false-positive rate in GEA approaches [139]. Second, a large proportion of the variation was explained by several confounding factors simultaneously, making it challenging to detect true adaptive signals from spatial autocorrelation and colonization history [118]. Controlling for genetic structures may reduce the false-positive rate but cause many or most adaptive loci to be missed [118, 139]. To minimize the false-positive rate, we used two other FST-based outlier analyses in addition to LFMM. This approach strongly reduces the false-positive rate but may bias the scanning toward strong selective sweeps by excluding several small-effect loci that may be equally important in shaping adaptive variation.
 
4.5 Assessing genetic vulnerability and climate adaptation in Quercus longinux
The projections of genetic offset from GF and RONA revealed that the populations in northern Taiwan might experience the most considerable turnover of genetic composition to cope with future climate change (Fig. 7). Winter precipitation in northern Taiwan is expected to more than double according to both emission models (current: 302 mm, RCP2.6: 682 mm, RCP8.5: 635 mm). The drastic increase in winter precipitation will negatively impact forest productivity [140] because the complex relationship between precipitation and water availability affects plant growth and phenology [140, 141]. Winter precipitation significantly impacts the phenology of oaks, including the onset and duration of flowering, bud bursting, and leaf flushing, and thus may greatly affect the likelihood and extent of gene flow between populations [142]. Considering the long generation time of oaks and the difficulty of juvenile growth in occupied forests, the expected changes in allele frequency to adapt to increased winter precipitation in the northern populations (RONA > 0.6) may not be achievable through standing genetic variation alone.
 
Under the emission model of intensified global warming (RCP8.5), southward migration over long distances (> 200 km) will increase to minimize forward genetic offset. Although we accounted for migration in estimating genetic offset, the northernmost and southeastern populations consistently showed relatively high local, forward, and reverse offsets. Our results indicate that no current populations across the distribution of Q. longinux are preadapted to future climates in these regions. The northern and southeastern populations are crucial genetic sources for climatic adaptation in other regions and should be prioritized in conservation strategies and protection efforts. Moreover, the rugged topography in mountainous regions may further hamper the movement of populations to higher elevations. Assisted gene flow from other populations preadapted to future climates may help marginal populations mitigate the effects of climate change [143]. For example, southern populations (e.g., HC) may act as potential sources of adaptation to high temperatures and seasonal arid climates for populations at higher altitudes and latitudes where higher future temperatures are predicted. However, the source populations must be selected carefully to ensure genetic compatibility with the sink populations and new environments [143]. 
 
Acknowledgments
The authors express their gratitude to Yun-Hsin Lai for her invaluable contributions to sample collection and leaf morphology measurement. Special thanks to Dr. Chih-Kai Yang and Huan-Ching Lin for their assistance in sample collection. The authors also thank Dawn Schmidt for her assistance in English editing.
 
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Data Accessibility
The following primary datasets associated with this paper have been deposited on Figshare under the DOI: 10.6084/m9.figshare.24276946:
1. VCF files encompassing all individuals subjected to analysis in this study.
2. Leaf morphological traits of each sample measured in this study.
3. Binary habitat layer estimated with ENM.
4. Environmental data corresponding to each sampling site.
5. Topographical and climate resistance layers simulated in this study.
 
Funding
This work was supported by the National Science and Technology Council under project ID NSTC 112-2621-B-003-001-MY3.
 
Competing Interests
The authors have no relevant financial or non-financial interests to disclose.
 
Author contribution
P.C.L. designed and supervised the project. P.W.S. collected samples and performed laboratory experiments and statistical analyses. P.W.S. and P.C.L. drafted the manuscript. J.T.C. and M.X.L. assisted with data interpretation, provided valuable feedback, and revised the manuscript. All authors have read and approved the final version of the manuscript.