Waterlogging induces oxidative damage by accumulation of reactive oxygen species due to stomatal closure. Plants alter their physiological and molecular mechanisms to reduce and adapt to oxidative stress. This mechanism of adaptation to stress, known as hardening, can support future stress tolerance. Pinus densiflora seedlings were grown under waterlogging treatment for three years and then transplanted to another site to identify the waterlogging hardening effect on transplanting. Transcriptome analysis was conducted before and after transplanting, and physiological factors were measured after transplanting. After transplanting, wounding stress is the main cause of transplant stress, and 13 genes related to phenylpropanoid were upregulated for the recovery of wounded roots in waterlogged hardened seedlings. The leaf starch and soluble sugar content of the waterlogged hardened seedlings were 50.3% and 40.5% lower due to the formation of cell walls. However, auxin-related genes were downregulated in waterlogging hardened seedlings, resulting in a lower tendency for height growth in hardened waterlogged seedlings. Waterlogging hardening mitigated transplant stress by wounding more than non-hardening, whereas waterlogging hardening may negatively affect seedling height. Our study provides evidence for the hardening effect of long-term waterlogging on transplanted P. densiflora seedlings.

Changes in vegetation activities driven by climate change serve as both a sensitive indicator and a key driver of climate impacts, underscoring the need for accurate phenological predictions. Delays in leaf senescence due to rising air temperatures increase the risk of damage from early frost, potentially affecting growth and survival in subsequent years. This study aimed to quantify long-term changes in leaf senescence timing for palmate maple and ginkgo trees, explore their associations with environmental factors, and compare the performance of multiple modeling approaches to identify their strengths and limitations for phenological predictions. Using data from 48 sites across South Korea (1989–2020), this study analyzed trends in the timing of leaf senescence for maple and ginkgo trees and compared the performance of process-based models (CDD_T, CDD_P, TP_T, TP_P), a linear regression model, and machine-learning models (random forest, RF; gradient-boosting decision tree, GBTD). Leaf senescence timing for both species has progressively been delayed, with ginkgo trees showing a faster rate of change (0.20 vs. 0.17 days per year, p < 0.05). Delayed senescence was observed in most regions (81% for maple and 75% for ginkgo), with statistically significant delays (p < 0.05) at half of the sites. Machine-learning models demonstrated the highest training accuracy (RMSE < 4.0 days, r > 0.90). Evaluation with independent datasets revealed that the RF and process-based TP_P (including minimum temperature and photoperiod) using a site-specific approach performed best (RMSE < 5.5 days, r > 0.75). Key environmental factors identified by RF included autumn minimum or mean temperatures and a summer photoperiod. By conducting this comparative assessment, the study provides insights into the applicability of different modeling approaches for phenology research and highlights their implications for vegetation management and climate change adaptation.

Climate change alters vegetation patterns, pushing subtropical forests further north. These forests play a crucial role for carbon neutrality efforts due to their significant CO₂ assimilation potential. This study investigated CO₂ assimilation rate along with growth, morphological, and physiological traits in 23 half-sib families of Quercus acuta and 26 half-sib families of Q. glauca, two prominent East Asian evergreen broadleaf species. Q. acuta exhibited significantly higher growth rates, with diameter at breast height (DBH) and aboveground biomass exceeding those for Q. glauca by 12.1% and 69.9%, respectively (p < 0.001). Leaf traits, including leaf mass pear area (LMA), leaf nitrogen, and chlorophyll content, were also greater in Q. acuta, showing 24.5%, 45.8%, and 15.6% higher values (p < 0.001). While photosynthetic traits were similar, Q. acuta exhibited a 12.7% higher intrinsic water-use efficiency (_iWUE) (p < 0.01). Among half-sib families, marginal differences were observed in growth traits (p < 0.1), and significant differences in leaf morphology and physiological traits (p < 0.05) were observed. A positive correlation was found between growth and physiological traits associated with the CO₂ assimilation rate in Q. acuta, but not in Q. glauca. These findings highlight the potential of Q. acuta and Q. glauca for supporting future carbon neutrality efforts and provide traits supporting carbon uptake, valuable for selecting tree species with enhanced carbon sequestration potential.