Energy deprivation affects nitrogen assimilation and fatty acid biosynthesis leading to leaf chlorosis under waterlogging stress in the endangered Abies koreana.

Energy deprivation triggers various physiological, biochemical and molecular changes in plants under abiotic stress. We investigated the oxidative damages in the high altitude grown conifer Korean fir (Abies koreana) exposed to waterlogging stress. Our experimental results showed that waterlogging stress led to leaf chlorosis, 35 days after treatment. A significant decrease in leaf fresh weight, chlorophyll and sugar content supported this phenotypic change. Biochemical analysis showed a significant increase in leaf proline, lipid peroxidase and 1,1-diphenyl-2-picrylhydrazyl (DPPH) free radical content of waterlogged plants. To elucidate the molecular mechanisms, we conducted RNA-sequencing (RNA-seq) and de novo assembly. Using RNA-seq analysis approach and filtering (P < 0.05 and false discovery rate <0.001), we obtained 134 unigenes upregulated and 574 unigenes downregulated. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis placed the obtained differentially expressed unigenes in α-linoleic pathway, fatty acid degradation, glycosis, glycolipid metabolism and oligosaccharide biosynthesis process. Mapping of unigenes with Arabidopsis using basic local alignment search tool for nucleotides showed several critical genes in photosynthesis and carbon metabolism downregulated. Following this, we found the repression of multiple nitrogen (N) assimilation and nucleotide biosynthesis genes including purine metabolism. In addition, waterlogging stress reduced the levels of polyunsaturated fatty acids with a concomitant increase only in myristic acid. Together, our results indicate that the prolonged snowmelt may cause inability of A. koreana seedlings to lead the photosynthesis normally due to the lack of root intercellular oxygen and emphasizes a detrimental effect on the N metabolic pathway, compromising this endangered tree's ability to be fully functional under waterlogging stress.

Experimental analysis of PM2.5 reduction characteristics between Korean red pine (Pinus densiflora) and sawtooth oak (Quercus acutissima) saplings under different densities and arrangement structures.

As global air pollution, particularly fine particulate matter (PM2.5), has become a major environmental problem, various PM2.5 mitigation technologies including green infrastructure have received significant attention. However, owing to spatial constraints on urban greening, there is a lack of management plans for urban forests to efficiently mitigate PM2.5. In this study, we assessed the PM2.5 reduction capabilities of Pinus densiflora (Korean red pine) and Quercus acutissima (sawtooth oak) by measuring the changes of PM2.5 concentrations using an experimental chamber system. In addition, the PM2.5 reduction efficiency in 90 min (PMRE90) and the amount of PM2.5 reduction per leaf area (PMRLA) were compared based on arrangement structures and density levels. The results showed that the PM2.5 reduction by plants was significantly greater than that of the control experiment without any plants, and an additional reduction effect of approximately 1.38 times was induced by a 1.5 m s-1 air flow. The PMRE90 of Korean red pine was the highest at medium density. In contrast, the PMRE90 of sawtooth oak was the highest at high density. The PMRLA of both species was highest at low densities. The different responses of the species to total reduction were well explained by total leaf area (TLA). The PMRE90 of both species was positively correlated with TLA. The PMRLA of sawtooth oak was approximately 2.3 times greater than that of Korean red pine. However, there were no significant differences in both PMRE90 and PMRLA between the arrangement structures. Our findings reveal the potential mechanisms of vegetation in reducing PM2.5 according to arrangement structure and density. This highlights the importance of efficiently using urban green spaces with spatial constraints on PM2.5 mitigation in the future.

Comparisons of PM2.5 mitigation with stand characteristics between evergreen Korean pine plantations and deciduous broad-leaved forests in the Republic of Korea.

Owing to industrialization and urbanization in recent decades, fine particulate matter (PM2.5) in the atmosphere has become a major environmental problem worldwide. This environmental issue pushed the use of forests as air filtering tools. However, there is a lack of continuous and long-term forest management to efficiently mitigate PM2.5. In this study, we assessed the potential of different forest types to control air pollution by measuring the seasonal PM2.5 concentrations inside and outside the forest for one year. In addition, the PM2.5 reduction efficiencies (PMREs) of two forest types were compared, and their relationship with stand characteristics was analyzed. The results showed that the average PMRE inside the forests was approximately 18.2%; the seasonal PMRE was highest in winter (approximately 28.1%) and lowest in summer (approximately 9.6%). The average PMRE of the Taehwa deciduous broad-leaved forest (TDF) (approximately 18.8%) was significantly higher than that of the Taehwa coniferous forest (TCF) (approximately 17.5%) (P < 0.001); differences were also observed seasonally. The PMRE in the TCF was higher in spring and summer (P < 0.001), while that in the TDF was higher in autumn and winter (P < 0.001). Furthermore, the PMRE in the TDF was negatively correlated with stand density (P = 0.003) and positively correlated with the average diameter at breast height (DBH) (P = 0.028). However, the PMRE in the TCF did not significantly correlate with stand characteristics. As such, the results of this study revealed the differences in PM2.5 mitigation according to stand characteristics, which should be considered in urban forest management.

Short-term severe drought influences root volatile biosynthesis in eastern white pine (Pinus strobus L).

Climate change-related drought stress is expected to shift carbon partitioning toward volatile organic compound (VOC) biosynthesis. The effect of drought stress on VOC synthesis remains unknown in several tree species. Therefore, we exposed eastern white pine (Pinus strobus) plants to severe drought for 32 days and performed physiological analysis (chlorophyll content, leaf water content, and root/shoot index), biochemical analysis (non-structural carbohydrates, proline, lipid peroxidation, and antioxidant assay), and total root VOC analysis. Drought stress decreased the relative water and soil moisture contents. Root proline accumulation and antioxidant activity increased significantly, whereas leaf chlorophyll synthesis and fresh weight decreased significantly in drought-treated plants. A non-significant increase in sugar accumulation (leaves and roots), proline accumulation (leaves), antioxidant activity (leaves), and lipid peroxidation (leaves and roots) was observed in drought-treated plants. Drought stress caused a non-significant decline in root/shoot ratio and starch accumulation (leaves and roots) and caused a significant increase in root abscisic acid content. Drought-treated plants showed an increase in overall monoterpene synthesis (16%) and decline in total sesquiterpene synthesis (3%). Our findings provide an overall assessment of the different responses of VOC synthesis to severe water deficit that may help unravel the molecular mechanisms underlying drought tolerance in P. strobus.

Identifying and extracting bark key features of 42 tree species using convolutional neural networks and class activation mapping.

The significance of automatic plant identification has already been recognized by academia and industry. There were several attempts to utilize leaves and flowers for identification; however, bark also could be beneficial, especially for trees, due to its consistency throughout the seasons and its easy accessibility, even in high crown conditions. Previous studies regarding bark identification have mostly contributed quantitatively to increasing classification accuracy. However, ever since computer vision algorithms surpassed the identification ability of humans, an open question arises as to how machines successfully interpret and unravel the complicated patterns of barks. Here, we trained two convolutional neural networks (CNNs) with distinct architectures using a large-scale bark image dataset and applied class activation mapping (CAM) aggregation to investigate diagnostic keys for identifying each species. CNNs could identify the barks of 42 species with > 90% accuracy, and the overall accuracies showed a small difference between the two models. Diagnostic keys matched with salient shapes, which were also easily recognized by human eyes, and were typified as blisters, horizontal and vertical stripes, lenticels of various shapes, and vertical crevices and clefts. The two models exhibited disparate quality in the diagnostic features: the old and less complex model showed more general and well-matching patterns, while the better-performing model with much deeper layers indicated local patterns less relevant to barks. CNNs were also capable of predicting untrained species by 41.98% and 48.67% within the correct genus and family, respectively. Our methodologies and findings are potentially applicable to identify and visualize crucial traits of other plant organs.

Canopy height affects the allocation of photosynthetic carbon and nitrogen in two deciduous tree species under elevated CO2.

Down-regulation of leaf N and Rubisco under elevated CO2 (eCO2) are accompanied by increased non-structural carbohydrates (NSC) due to the sink-source imbalance. Here, to investigate whether the canopy position affects the down-regulation of Rubisco, we measured leaf N, NSC and N allocation in two species with different heights at maturity [Fraxinus rhynchophylla (6.8 ± 0.3 m) and Sorbus alnifolia (3.6 ± 0.2 m)] from 2017 to 2019. Since 2009, both species were grown at three different CO2 concentrations in open-top chambers: ambient CO2 (400 ppm; aCO2); ambient CO2 × 1.4 (560 ppm; eCO21.4); and ambient CO2 × 1.8 (720 ppm; eCO21.8). Leaf N per unit mass (Nmass) decreased under eCO2, except under eCO21.8 in S. alnifolia and coincided with increased NSC. NSC increased under eCO2 in F. rhynchophylla, but the increment of NSC was greater in the upper canopy of S. alnifolia. Conversely, Rubisco content per unit area was reduced under eCO2 in S. alnifolia and there was no interaction between CO2 and canopy position. In contrast, the reduction of Rubisco content per unit area was greater in the upper canopy of F. rhynchophylla, with a significant interaction between CO2 and canopy position. Rubisco was negatively correlated with NSC only in the upper canopy of F. rhynchophylla, and at the same NSC, Rubisco was lower under eCO2 than under aCO2. Contrary to Rubisco, chlorophyll increased under eCO2 in both species, although there was no interaction between CO2 and canopy position. Finally, photosynthetic N content (Rubisco + chlorophyll + PSII) was reduced and consistent with down-regulation of Rubisco. Therefore, the observed Nmass reduction under eCO2 was associated with dilution due to NSC accumulation. Moreover, down-regulation of Rubisco under eCO2 was more sensitive to NSC accumulation in the upper canopy. Our findings emphasize the need for the modification of the canopy level model in the context of climate change.

Down-regulation of photosynthesis and its relationship with changes in leaf N allocation and N availability after long-term exposure to elevated CO2 concentration.

Down-regulation of photosynthesis under elevated CO2 (eCO2) concentrations could be attributed to the depletion of nitrogen (N) availability after long-term exposure to eCO2 (progressive nitrogen limitation, PNL) or leaf N dilutions due to excessive accumulation of nonstructural carbohydrates. To determine the mechanism underlying this down-regulation, we investigated N availability, photosynthetic characteristics, and N allocation in leaves of Pinus densiflora (shade-intolerant species, evergreen tree), Fraxinus rhynchophylla (intermediate shade-tolerant species, deciduous tree), and Sorbus alnifolia (shade-tolerant species, deciduous tree). The three species were grown under three different CO2 concentrations in open-top chambers, i.e., ambient 400 ppm (aCO2); ambient × 1.4, 560 ppm (eCO21.4); and ambient × 1.8, 720 ppm (eCO21.8), for 11 years. Unlike previous studies that addressed PNL, after 11 years of eCO2 exposure, N availability remained higher under eCO21.8, and chlorophyll and photosynthetic N use efficiency increased under eCO2. In the case of nonstructural carbohydrates, starch and soluble sugar showed significant increases under eCO2. The maximum carboxylation rate, leaf N per mass (Nmass), and ribulose-1,5-bisphosphate carboxylase/oxygenase (Rubisco) were low under eCO21.8. The ratio of RuBP regeneration to the carboxylation rate as well as that of chlorophyll N to Rubisco N increased with CO2 concentrations. Based on the reduction in Nmass (not in Narea) that was diluted by increase in nonstructural carbohydrate, down-regulation of photosynthesis was found to be caused by the dilution rather than PNL. The greatest increases in chlorophyll under eCO2 were observed in S. alnifolia, which was the most shade-tolerant species. This study could help provide more detailed, mechanistically based processes to explain the down-regulation of photosynthesis by considering two hypotheses together and showed N allocation seems to be flexible against changes in CO2 concentration.