Drought damage and waterlogging damage are the most frequent abiotic injuries throughout the lifespan of trees. Nonetheless, because the signs of visible damage are similar between these types of injury, physiological indicators must be analyzed to make a scientific differential diagnosis. This study was aimed at investigating growth and physiological indicators of drought (DS) and waterlogging stress (WL) in Prunus yedoensis. Overall growth indices such as tree height, diameter at root collar (DRC), and total dry weight could be ranked in the decreasing order “control > DS > WL.” In particular, there was a prominent decrease in root growth in WL, and DRC in DS was lower by 9.2% than DRC before the experiment. As for water saturation deficit (WSD) increased to 37.4% by 28 days after treatment initiation (DAT) in DS. WL showed a sharp decline of photosynthetic indicators such as the net photosynthesis rate (A), stomatal conductance (g_s), and maximum carboxylation rate (V_cmax) starting from 7 DAT. By contrast, DS manifested a significant decrease starting from 14 DAT. The DS had higher levels of leaf and root inorganic components than WL did, suggesting an improvement in the osmoregulatory ability. The overall nutritional status of WL was low due to deterioration of the absorption function of the roots. In both DS and WL, energy transfer rates of photochemical reactions, e.g. absorbed photon leads to reduction further than Q_A^- (Φ_PO), absorbed photon leads to electron transport further than Q_A^- (Φ_EO), and absorbed photon leads to reduction of Q_A^- (Ψ_O), decreased, as did vitality indices, e.g. the performance index on absorption basis (PI_abs), driving force on absorption basis (DF_abs), and the structure function index on absorption basis (SFI_abs). However, WL featured a decrease in Electron transport flux from Q_A to Q_B (ETo/RC) and Electron transport flux until PSI acceptors (REo/RC), whereas DS experienced a slight increase or almost no change. Consequently, PI_abs, DF_abs, SFI_abs, and the drought factor index are highly sensitive environmental-stress indicators, whereas WSD, DRC growth, chlorophyll a content, ETo/RC, and REo/RC appear to have high potential as diagnostic indicators of drought or waterlogging damage.

No natural habitat of Sedirea japonica has been found in Korea for the past 20 years. This study was conducted to provide basic physiological data for the conservation strategy of this endangered plant in response to climate change. Soil fruit daylight system (SFDS) chambers were used and four treatment groups (2.6LVPD, 2.6HVPD, 8.5LVPD, and 8.5HVPD) were designed based on the RCP scenario (RCP 2.6, and 8.5) and VPD conditions (low VPD; LVPD, and high VPD; HVPD). Air dryness was induced in the HVPD groups during the daytime by increasing the atmospheric vapor pressure deficit (VPD). There was no significant difference based on the RCP scenario. However, the difference between LVPD and HVPD was considerable. Total CO₂ uptake and transpiration were lower than those of LVPD due to the duration decrease of Phase I in 2.6HVPD and 8.5HVPD. There was a reduction in total biomass, leaf thickness, length, and the number of leaves. ABS/RC, DI₀/RC, φD₀, V_K, V_J, and other chlorophyll fluorescence markers increased. φP₀, RE₀/RC, φE₀, ψE₀, φR₀, RC/CS₀, Sm, N, PI_abs, DF_abs, SFI_abs, and PI_abs,Total declined. Daily drought stresses impact the physiological mechanisms occurring at nighttime. The defense mechanisms against drought stress occur by conserving water by controlling the stomata, inactivating the reaction center, and increasing the dissipated energy through heat. In summary, S. japonica is flexible against drought stress.

This study was conducted to evaluate the physiological and growth responses of Sedirea japonica cultured in chambers under RCP 6.0 and different light conditions. S. japonica was grown in a soil–plant daylight system chamber under two treatments, a control (CO₂ = 400 ppm) and a climate change treatment (CCT) (CO₂ = 650 ppm, temperature = control + 3 °C), and three different shading treatments (60%, 90%, and no-shading). S. japonica showed the characteristics of typical Crassulacean acid metabolism (CAM) plants. As the shading rate increased, it increased chlorophyll content, leaf area, and leaf dry weight to efficiently absorb and use light. The CCT had a lower CO₂ absorption rate, stomatal conductance, and growth rate and slightly higher water utilization efficiency than the control. This was because stomatal closure occurred in the CCT to reduce water loss due to a relatively higher temperature. As CO₂ fixation decreased and consumption increased due to respiration, the overall growth was inhibited. The CCT without shading revealed a dynamic photoinhibition phenomenon showing a significant increase in ABS/RC, TRo/RC, ETo/RC, and DIo/RC and a decrease in PI _ABS and DF _ABS. In this group, leaf, root, and total dry weight, chlorophyll content, and carotenoid content were the worst growth indices.

Climate change affects the frequency and intensity of extreme weather, such as drought and floods. This study aimed to investigate the effects of drought stress on the growth and physiological characteristics of Z. jujuba var. inermis based on the RCP 6.0 scenario. The experiment was performed in a soil-plant daylight system (SPDS) chamber under four conditions: Control-WW, Control-DS (Drought), RCP 6.0-WW (CO 2 650 ppm, control + 3°C), and RCP 6.0-DS. Although the net photosynthetic rate (A) was higher under RCP 6.0 than the control condition, V cmax and J max , which indicate the photosynthetic capacity, were lower by 19.6% and 27.8%, respectively. Furthermore, in the RCP 6.0 group, the carbon fertilization effect tended to stimulate growth; thus, the total dry weight in RCP 6.0-WW was approximately 35% higher than that in Control-WW. When the drought treatment was included, A decreased by 57% in Control-DS compared to Control-WW, and in RCP 6.0-DS, A decreased by 73% compared to RCP 6.0-WW. Moreover, RCP-DS showed the lowest values of V cmax , J max , PI abs , DF abs , and SFI abs , meaning that the photosynthetic capacity and vitality of the photosynthetic apparatus were diminished under combined climate change and drought stress. Furthermore, stomatal limitations (Ls) regulated photosynthesis in Control-DS, whereas in RCP 6.0-DS, non-stomatal limitations, in this case V cmax , J max , PI abs , DF abs , and SFI abs , were observed. Despite a decrease in mesophyll conductance (g m), g m /g s remained relatively high. Furthermore, even with stomatal closure, g m was maintained at a relatively high level by utilizing the intercellular CO 2 concentration (C i), demonstrating the plant's response to drought stress. Although there was an increase in the overall biomass, it was noted that water consumption increased under additional drought stress, showing that growth and physiological damage were aggravated. Therefore, it is essential to conduct experiments related to the growth and physiological characteristics of commercially valuable seedlings such as Jujube to identify the adverse effects of climate change alongside extreme weather. Further, active efforts with regard to plant management should be undertaken in addition to the implemented measures to reduce greenhouse gas emissions. 12

Background: This study was conducted to investigate the changes in the photosynthetic parameters, chlorophyll content, chlorophyll fluorescence, and growth characteristics of Aruncus dioicus var. kamtschaticus seedlings under different shading treatments. Methods and Results: The shading treatment was regulated with the shading level (non-shaded, 35%, 55%, and 75% shading). Photosynthetic activities, such as net photosynthetic rate, stomatal conductance, stomatal transpiration rate, and performance index on absorption basis ($PI_{ABS}$)were the highest under 35% shading ($4.36{\mu}mol\;CO_2{\cdot}m^{-2}{\cdot}s^{-1}$, $54.2mmol\;H_2O{\cdot}m^2{\cdot}s^{-1}$, $0.66mmol\;H_2O{\cdot}m^{-2}{\cdot}s^{-1}$, and 1.3, respectively), and the lowest under 75% shading. This implies that the decrease in net photosynthetic rate may be due to an inability to regulate water and $CO_2$ exchanged through the stomata. Thechlorophylla, b, and a + b contents were increased with elevating shading level and the chlorophyll a/b ratio showed non-significant differences. It was found that the dry weight (leaf, shoot, and whole) was the highest (1.14 g, 0.49 g, and 2.31 g, respectively) under 35% shading and the t/R ratio was the highest under 75% shading. Conclusions: It is concluded that 75% shading exhibited a strong reduction of photosynthetic activity, and 35% shading showed the best conditions for the early growth and cultivation of A. dioicus var. kamtschaticus.

The Civilian Access Control Zone (CACZ), south of the Demilitarized Zone (DMZ) separating North and South Korea, has functioned as a unique bio-reserve owing to restrictions on human use. However, it is now increasingly threatened by damaged land and slope failures. In this study, a machine-learning-based method was used to assess slope stability by introducing the random forest (RF), support vector machine (SVM), extreme gradient boosting (XGBoost), and logistic regression (LR) approaches. These classification models were trained and evaluated on 393 slope stability cases from 2009 to 2019 to assess slope stability in the northern area of the Civilian Control Line, South Korea. For comparison, the performance of these classification models was measured by considering the accuracy, Cohen’s kappa, F1-score, recall rate, precision, and area under the ROC curve (AUC). Furthermore, 14 influencing factors (slope, vegetation, structure conditions, etc.) were considered to explore feature importance. The evaluation and comparison of the results showed that the performance of all classifier models was satisfactory for assessing the stability of the slope, the ability of LR was validated (accuracy = 0.847; AUC = 0.838), and XGBoost proved to be the most efficient method for predicting slope stability (accuracy = 0.903; AUC = 0.900). Among the 14 influencing factors, the external condition was the most important. The proposed supervised learning method offers a promising method for assessing slope status, may be beneficial for government agencies in early-stage risk mitigation, and provides a database for efficient restoration management.