Greening Tree Species Research Articles

Effects of urban green space habitats and tree species on ectomycorrhizal fungal diversity

Ectomycorrhizal fungi (EMF) are key symbiotic microbial components for the growth and health of trees in urban greenspace habitats (UGSHs). However, the current understanding of EMF diversity in UGSHs remains poor. Therefore, in this study, using morphological classification and molecular identification, we aimed to investigate EMF diversity in three EMF host plants: Cedrus deodara in the roadside green belt, and C. deodara, Pinus massoniana, and Salix babylonica in the park roadside green belt, in Guiyang, China. A total of 62 EMF Operational Taxonomic Units (OTUs) were identified, including 13 EMF OTUs in the C. deodara roadside green belt, and 23, 31, and 9 EMF OTUs in the park green belts. C. deodara, P. massoniana, and S. babylonica were respectively identified in park green belts. Ascomycota and Basidiomycota were the dominant phylum in the EMF communities in roadside and park green habitat, respectively. The Shannon and Simpson indexes of the C. deodara EMF community in the park green belt were higher than those in the roadside green belt. EMF diversity of the tree species in the park green belt was P. massoniana > C. deodara > S. babylonica. Differences in EMF community diversity was observed among the different greening tree species in the UGSHs. UGSHs with different disturbance gradients had a significant impact on the EMF diversity of the same greening tree species. These results can be used as a scientific reference for optimizing the design and scientific management of UGSHs.

Evaluation of Ecological Service Functions of Urban Greening Tree Species in Northern China Based on the Species-Specific Air Purification Index

Urban forests, as an integral part of nature-based solutions (NBS), are significant contributors to improving urban air quality, delivering ecological service functions and environmental benefits to human health and well-being. Suitable urban forest management, including proper species selection, needs to be defined to efficiently reduce air pollutants in cities, with a focus on the removal ability of the main air pollutants (PM2.5, PM10, O3, and NO2), the ecological adaptability to O3 and NO2, and allergenic effects. This study ranked 73 urban greening tree species in northern Chinese cities based on their ability to maximize air quality and minimize disservices. This study proposed a novel Species-Specific Air Purification Index (S-API), which is suitable for air quality improvement for tree/shrub species. Urban managers are recommended to select species with an S-API > 1.47—that is, species that have a high removal capacity of PM2.5, PM10, O3, and NO2, are O3- and NO2-tolerant, and are non-allergenic (e.g., Castanea mollissima Blume, Ginkgo biloba L., Hibiscus syriacus L., Ilex chinensis Sims, Juniperus procumbens (Endl.) Iwata et Kusaka, Liriodendron chinense (Hemsl.) Sarg., Morus alba L., Styphnolobium japonicum (L.) Schott, Syringa oblata Lindl., and Ulmus pumila L.). The S-API of urban greening species thus represents a potentially useful metric for air pollutant risk assessment and for selecting appropriate species for urban greening in cities facing serious air pollution challenges.

Variations in the leaf economics spectrum, anatomical, ultrastructural, and stomatal traits of five tree species in the urban-rural air pollution environment

Rapid urbanization has contributed to global increases in air pollution derived from urban areas. Unlike natural forests, urban forests are exposed to higher concentrations of airborne pollutants due to the strong urban-suburban-rural pollutant emission gradients. However, there remains a pressing lack of available information pertaining to the urban air pollution-related effects on the leaf economics spectrum, anatomical, ultrastructural, and stomatal traits of tree species along an urban-rural gradient. Here, the degree to which urban air pollution impacts the adaption of greening tree species and associated service functions was assessed by sampling five common tree species (Acer pictum, Fraxinus chinensis, Koelreuteria paniculata, Salix babylonica, Sophora japonica) along urban-rural-natural forests in the Beijing metropolitan region of China. These analyses revealed a significant reduction in leaf mass per unit area (–13.4 %), leaf thickness (–16.7 %), and stomatal area (–27.5 %) with increasing proximity to areas of greater air pollution that coincide with significant increases in leaf tissue density (+12.6 %), leaf nitrogen content (+10.1 %), relative chlorophyll content (+2.7 %), and stomatal density (+11.9 %). Higher air pollution levels were associated with organelle changes including gradual disintegration of chloroplasts, larger intercellular spaces and apparent starch and plastoglobuli deposition. Air pollution was conducive to the strengthening of the trade-off potential and adaptation strategies of trees in urban ecosystems, which are associated with trees with a rapid investment return strategy associated with thick leaves and strong photosynthetic capacity. These results provide strong empirical evidence of the profound air pollution-induced changes in leaf functional traits and adaption ability of urban forest tree species.

Multi-omics analysis of Populus simonii × P. nigra leaves under Hyphantria cunea stress.

Poplar is an important greening and timber tree species in China, which has great economic and ecological values. However, the spread of Hyphantria cunea has become increasingly serious in recent years, resulting in huge economic loss of poplar production. Exploring the molecular mechanism of poplar reponse to H. cunea stress has significant implications for future development of new insect-resistant poplar varieties using genetic engineering technology. In this study, a total of 1039 differentially expressed genes (DEGs), 106 differentially expressed proteins (DEPs) and 212 differentially expressed metabolites (DEMs) were screened from Populus simonii × P. nigra leaves under H. cunea stress by transcriptome, proteomics and metabolomics analysis, respectively. GO and KEGG analysis showed that the DEGs and DEPs are associated with endopeptidase inhibitor activity, stress response, α-linolenic acid metabolism, phenylpropanoid biosynthesis and metabolic pathways, cysteine and methionine metabolism pathways and MAKP signaling pathway. Metabolomics analysis showed the most of DEMs were lipids and lipid molecules, and the pathways associated with transcriptome mainly include plant hormone signal transduction, α-linolenic acid metabolic pathway, amino sugar and nucleotide sugar metabolism, and phenylpropanoid biosynthesis. In particular, multi-omics analysis showed that several pathways such as α-linolenic acid metabolic, phenylpropanoid biosynthesis and metabolic pathway and cysteine and methionine metabolic pathway were significantly enriched in the three omics, which may play an important role in the resistance to pests in poplar.

The complete chloroplast genome of Polyspora axillaris (Theaceae)

Polyspora axillaris (Roxb. ex Ker Gawl.) Sweet 1825, is a shrub or tree that is about 9 meters tall in the Theaceae family, mainly distributed in China and Vietnam, and it is widely used as a green tree species in many regions owing to its rapid growth and good adaptability. It is rich in various beneficial extracts for humans, but there are limited studies on it. In this study, we sequenced and annotated the complete plastome of P. axillaris. The chloroplast genome length of P. axillaris is 156,770 bp, with a total of 132 genes, including 37 tRNA genes, 8 rRNA genes and 87 protein-coding genes. The complete chloroplast genome of P. axillaris contains two Inverted Repeats (IRs) of 26,077 bp, a Large Single-Copy (LSC) region of 86,286 bp and a Small Single-Copy (SSC) region of 18,330 bp. The overall G/C content in the chloroplast is 37.3%. Phylogenetic inference shows that P. axillaris formed a sister relationship with P. hainanensis, along with 10 Theaceae species. The research result of P. axillaris will contribute to the genetic preservation of the species and the phylogenetic study of Polyspora.

Estimation of historical daily PM2.5 concentrations for three Chinese megacities: Insight into the socioeconomic factors affecting PM2.5

Studying historical changes in the 2.5 μm particulate matter concentration (PM2.5) can clarify the relationship between air pollution and socioeconomic development. Daily PM2.5 levels and meteorological data (2012–2022) for three large cities (Beijing, Shanghai, and Xi'an) at different development stages in different regions of China were used to construct a random forest (RF) model for estimating historical PM2.5 data for the period 1973–2011, a time period in which few measurements were made. The eigenvalue for visibility was the largest in the RF model; visibility explained 0.76–0.87 of the variance in PM2.5 for the three cities. The daily estimated PM2.5 was validated, with an R2 of 0.654–0.780 and average absolute error of 11.52–31.73 μg m−3 in the model. PM2.5 concentrations predicted by the RF model for 2004–2011 were highly correlated with gravimetric measurements (R = 0.585, p < 0.01). We extensively validated the results of RF using manual weighing PM2.5 data, online monitoring concentration of PM10, and aerosol optical depth (AOD), demonstrating the accuracy of the model. Over the study period, the PM2.5 level first increased and then decreased in the three cities; however, the year at which the trend changed differed. We further explored the effects of urbanization and economic growth on PM2.5 levels by investigating the correlations between socioeconomic indicators and PM2.5. The magnitude of the permanent population of Beijing and gross regional production growth in Shanghai were both significantly positively correlated with the PM2.5 level. Increasing the size of urban green areas can reduce PM2.5; this effect was strongest for the southern city of Shanghai, may due to their different climates and green tree species. Energy consumption and emissions from primary industries were strongly positively correlated with the urban PM2.5 level. An in-depth understanding of the factors affecting PM2.5 concentrations could help policymakers improve air quality management strategies, especially for densely populated megacities.

A Study on the Leaf Retention Capacity and Mechanism of Nine Greening Tree Species in Central Tropical Asia Regarding Various Atmospheric Particulate Matter Values

With the rapid advancement of the global economy, there has been a noticeable escalation in the level of inhalable particulate matter (PM) pollution in the atmosphere. The utilization of plants has been recognized as an effective means to mitigate the escalation in the atmospheric PM concentration through the capture and retention of this particulate matter on their leaves. This research focuses on investigating the PM retention capacity of nine commonly found greening plant species in Changsha, China, located in the country’s mid-subtropical region. In this study, we employed an air aerosol generator (QRJZFSQ-II) and a portable leaf area meter (LI-3000C) to systematically evaluate the PM retention in unit leaf area for different PM values. In addition, the leaf surface structure was observed via scanning electron microscopy, and the relationship between the leaf microstructure and the retained particles was quantitatively analyzed. The results showed that (1) there were significant differences in the retention of TSP, PM10, and PM2.5 per unit leaf area among the nine greening tree species analyzed. Rosa saturata was found to have the best retention effect regarding TSP and PM2.5, and Rhododendron simsii was found to have the best retention effect regarding PM10. (2) There were significant differences in the contents of TSP and PM2.5 per leaf area among the different tree species with different life forms (p &lt; 0.05), with the order of retention being shrub &gt; arbor (needle leaves) &gt; arbor (broad leaves). (3) Coniferous plants have a deep leaf surface texture, which is conducive to capturing more particles on their leaf surface, and (4) the long stomata diameter was significantly negatively correlated with PM retention, and the stomata density was significantly positively correlated with PM retention. However, the short diameter and small area of stomata demonstrated no significant correlation with PM retention (p &lt; 0.05). Considering the selection of suitable tree species for greening in urban air pollution control, we suggest that Osmanthus fragrans, Pseudolarix amabilis, Rosa saturata, and Rhododendron simsii be used more frequently in urban areas affected by severe air pollution.

Characterizing accumulation and negative effects of aerosol particles on the leaves of urban trees

Urban vegetation can alleviate particulate matter (PM) pollution. Many studies examined the PM retention efficiencies of different plant species, but the PM changes retained on leaf surfaces and their effects on plant leaves have rarely been explored. In this study, two common urban greening tree species of the Yangtze River Delta (i.e., Broussonetia papyrifera and Osmanthus fragrans) were selected to explore the compositions of retained PM and assess their adverse impacts on leaf functional traits. Compared with B. papyrifera, O. fragrans with higher wax content was more efficient in particle accumulation, specifically fine (Φ ≤ 2.5 μm) and coarse (2.5 < Φ ≤ 10 μm) particles. The number density and mass concentration of retained PM on plant leaves tended to increase during the accumulation period. Plant species and accumulation time were two major factors to influence particle retention efficiency. Interestingly, the accumulation of particle retention influenced leaf functional traits, such as photosynthesis rate, stomatal conductance, and transpiration rate. The microscopic observations of PM on leaves confirmed that the toxic components of the retained particles potentially caused leaf injury and stomatal damage. Therefore, the acclimation mechanisms of plants responding to the retained urban aerosols should be paid attention in highly polluted areas.

Traits coordination at leaf and branch level in response to the urban environment

The response of urban trees to the environment is the key content to explain the functional toughness of urban green space. However, how urban greening trees adapt to the dry and hot environment of the city remains unclear due to the single index and the limitations of the research area. We selected four representative cities in northern China with different regional dryness and measured 18 economic, hydraulic and anatomical traits of the common greening tree species (Fraxinus chinensis Roxb). The results show that there was generally a significant divergence in plant functional traits across urban dryness, and the traits have strong plasticity. As urban dryness increases, the number of leaf veins closed loops increases, forming a more complete network system of veins. While a significant decrease in the vessel vulnerability index further indicates the increased drought tolerance of urban trees to resist dry and hot environments. The increase of dryness leads to the decrease of vessel hydraulic diameter and area. The reduction in the vessel vulnerability index indicates an increase in the drought resistance of the twigs, which may be related to the input and distribution of resources in the branches and leaves. There was a strong correlation between plant economic-anatomical-hydrological traits. Under the stress of a dry urban environment, plants prefer to invest resources in the water sparing capacity of the stem, as well as in the construction of defence structures and nutrient storage capacity of the leaves.

Effect of optimal allocation of urban trees on the outdoor thermal environment in hot and humid areas: A case study of a university campus in Guangzhou, China

The process of urbanization in developing countries has had an ecological impact, destroying the outdoor thermal environment, especially in hot and humid areas where high summer temperatures are a nuisance for human outdoor activities. The role of urban greening in improving the regional microclimate has been confirmed by many studies. To improve the outdoor thermal environment, taking a university campus in Guangzhou as an example, the tree species and tree geometric parameters were analyzed, the ENVI-met model was established, and a simulation platform was calibrated based on the measured data, which improved the accuracy of the simulation platform. In this simulation platform, the maximum root mean square errors of air temperature and humidity were as low as 1.49 °C and 5.63 %, respectively. To reveal the influence of the physical morphology of tree species and their community characteristics on the outdoor thermal environment, six typical greening tree species and 37 green space configurations were established, and the influence of each tree species and their spatial configurations on the cooling effect of the outdoor environment was simulated. The results showed that the leaf area index, crown width, and tree height had a great influence on the ground temperature and sensible heat flux under the tree canopy, and the cooling effect of the tree group was improved when the height of the trees exceeded 10 m, with an ideal canopy coverage of 30 %. Optimizing the green space configuration reduced the temperature at pedestrian height (1.5 m) in the study area by up to 1.5 °C, and a reduction of 0.5 °C was observed over approximately 50 % of the green area during the peak summer temperatures (14:00–16:00), mitigating the microclimate heat environment. This study can enable urban planners to determine the type, quantity, and spatial allocation of green vegetation to improve the urban thermal environment.

Suitability Assessment of Six Tree Species through Combined Analysis of PM2.5 Capture Ability and Air Pollution Tolerance Index for Urban Green Belt

Increasing concentrations of atmospheric particulate matter (PM) can cause a serious threat to urban air quality and human health. To reduce PM pollution in urban environments, pragmatic screening and planting of tolerant tree species can be effective and sustainable ways. However, our understanding of the effects of the capture ability of PM2.5 on plant tolerance, and efforts to devise explicit assessment tools for suitability analysis for urban green belt plantations, are still inadequate. In this study, six common green tree species (Pinus tabuliformis, Abies holophylla, Juniperus chinensis, Salix babylonica, Robinia pseudoacacia, and Populus alba) from three pollution sites in Shenyang City, China, were collected in order to assess their PM2.5 capture ability, biochemical characteristics, leaf microstructures, and air pollution tolerance index (APTI). The results revealed that different sites and tested plant species can significantly affect the amount of PM2.5 retained by leaf surfaces. The PM2.5 retention amount of Abies holophylla was the highest at the SFH site and 1.41–8.89 times that of other tested species (p &lt; 0.05). Morphological plant attributes, such as leaf surface roughness (r = 0.52 **) and contact angle (r = −0.57 **), were strongly related to the PM2.5 retention amount. The PM2.5 retention amount per unit leaf area had the strongest and most significant negative influence on total chlorophyll content (r = −0.743 **), indicating that the accumulation of leaf PM2.5 reduced the photosynthetic efficiency of the plants. Among the tested plants, Robinia pseudoacacia had the highest APTI value and was identified as the most resilient plant at all three sites, whereas Juniperus chinensis had the lowest APTI at all study sites. However, the integration of PM2.5 capture ability with APTI showed Pinus tabuliformis to be the best species for the construction of urban green belts in Shenyang City.

Effect of urban pavement on nutrient strategies of common greening tree species in northern China

There are many factors that affect how urban tree species absorb and use nutrients, but little is known about the impact of pavement in urban areas. In this study, we selected four common urban tree species—Platanus x acerifolia, Metasequoia glyptostroboides, Robinia pseudoacacia, and Pinus thunbergii—and three pavement coverage categories—unpaved, semi-paved, and fully paved—in Qingdao, a typical city in northern China, to investigate changes in the leaf nutrient utilization strategies of tree species in paved environments. The nitrogen (N) resorption efficiency (NRE) and phosphorus (P) resorption efficiency (PRE) of R. pseudoacacia and the NRE of M. glyptostroboides increased in semi- and fully paved environments. Additionally, the N resorption proficiency of M. glyptostroboides increased significantly with pavement coverage, indicating that the biochemical limitation on N resorption was weakened. Similarly, the contents of N, P, and potassium (K) in R. pseudoacacia and N and K in M. glyptostroboides significantly increased with pavement coverage. This indicates that R. pseudoacacia, a nitrogen-fixing Fabaceae tree species, and M. glyptostroboides, a deciduous Cupressaceae tree species, can better adapt to pavement in urban settings, and even high pavement coverage levels can induce higher nutrient contents and resorption capacities. In addition, M. glyptostroboides showed potentially poor adaptability for N, P, and K uptake in the more stressful pavement environments, and P. x acerifolia showed relatively poor adaptability in P-limited environments. Robinia pseudoacacia associates with nodule-forming nitrogen-fixing bacteria, thus retaining more N in its leaves and showing a low NRE. These findings not only provide additional insight into tree growth at varying pavement coverages but also preliminary guidance for tree species selection to promote resilience in urban areas.

Synergy of different leaf traits determines the particulate matter retention capacity and its susceptibility to rain wash-off

Rainfall plays a crucial role in the removal of particulate matter (PM) from plant leaves, influencing PM retention and the environmental behaviour of harmful substances that accumulate in PM. This study examined the PM retention capacity, particle size distributions, and wash-off rates of leaf surface PM from three common green tree species in northern China during two natural rainfall events (light rain: 8.3 mm; heavy rain: 54.2 mm), to investigate the relationship between the leaf traits, PM retention capacity, and PM wash-off process. Our results found that leaf morphometric characteristics, such as leaf size, length, width, and aspect ratio (length-to-width), had a negative and significant correlations with the PM retention capacity, but had no significant correlation with the leaf surface PM wash-off rate. Smaller leaves with low aspect ratios exhibited greater stability under external disturbances than large leaves with high aspect ratios, resulting in a higher PM retention capacity and lower wash-off rate. Ridges and grooves enhanced the PM retention capacity by increasing the leaf roughness. Rainfall could wash off all particle size ranges of leaf surface PM without altering their mechanical composition. Larger particles were more easily washed off. Euonymus japonicus, with its small leaf size and low aspect ratio, exhibited the highest PM retention capacity. Its curled leaf shape also hindered light rain from washing off leaf surface PM. Forsythia suspensa, with denser grooves and ridges compared with Prunus serrulata, exhibited a rougher leaf surface and higher PM retention capacity. However, this roughness may reduce wettability, making it easier for runoff to form on the leaf surface and dislodge leaf surface PM, resulting in F. suspensa having the highest wash-off rate. Our results highlight the synergy of different leaf traits on PM retention capacity and the PM stability after rainfall.

Variation in the Ability of Various Tree Species to Capture Particulate Matter in Industrial and Urban Areas

There are several short- and long-term negative effects on human health caused by the well-known pollutant known as particulate matter (PM), which also significantly contributes to urban air pollution. Trees can act as a sustainable air purifying filter by adsorbing and absorbing tiny airborne dust. Their effectiveness is influenced by a number of variables, including particulate matter concentration and leaf features of tree species. In this study, the particulate matter capturing capacity of commonly grown 20 tree species were compared and the best tree species were chosen for the urban plantation to reduce particulate matter pollution. In this study, Ficus bengalensis (0.67 mg/cm2), Mangifera indica (0.61 mg/cm2), Polyalthia longifolia (0.57 mg/cm2), Tectona grandis (0.66 mg/cm2) and Terminalia catappa (0.63 mg/cm2) were found to be the best tree species among the 20 tree species and also it was confirmed that morphological characteristics of tree leaves plays an important role in capturing the particulate matter from the atmosphere. In conclusion, our findings may help in the selection of greening tree species with strong particulate matter purifying capacities for both industrial and urban areas.

Potential Carbon Sequestration and Economic Value Assessment of the Relict Plant Ginkgo biloba L. Based on the Maximum Entropy Model

As global warming intensifies, plant carbon sequestration is becoming increasingly important. Studies have shown that Ginkgo biloba L. is a kind of tree with a high carbon sequestration capacity and is one of the dominant tree species suitable for urban ecosystems. Predicting the changes in the potential suitable areas, carbon sequestration amount and carbon sink value of G. biloba under current and future climate change will provide some references for the resource utilization of urban green tree species and the realization of carbon sink value. In this study, we used ‘kuenm’, an R package that uses MaxEnt, as a modeling algorithm to predict the potential suitable areas of G. biloba under nine climate scenarios, and the carbon sequestration and the carbon sink values under the fair-value measurement model were calculated. We found that: (1) the optimized MaxEnt model improved the prediction accuracy (AUC = 0.97 ± 0.004) significantly. (2) The total current potential suitable area of G. biloba was 175.11 × 104-km2, representing 21.63% of China’s total territorial area, and the highly suitable area was 26.86 × 104-km2, accounting for 2.83% of China’s total territorial area, concentrated primarily in the regions of Sichuan and Chongqing, southern Jiangsu, and Zhejiang Province. (3) The eight future climate scenarios predict that the suitable area of G. biloba will initially decrease and then increase, and the newly expanded area will be distributed primarily in the middle and upper reaches of the Yangtze River as well as near the estuary of the Yangtze River, while the region suffering losses will move from Sichuan and Chongqing to Hunan, Jiangxi and Zhejiang Province as well. Hf and bio2 are the major factors affecting the distribution of G. biloba. (4) The total annual carbon sequestration of G. biloba was 1.60 × 106-t, 1.50 × 106-t and 1.57 × 106-t under different environmental conditions in the present, the 2050s and the 2090s, respectively. Over these three time periods, we obtained total carbon sequestration values of 5.63 × 107 CNY, 5.28 × 107 CNY and 5.53 × 107 CNY.

PagMYB151 facilitates proline accumulation to enhance salt tolerance of poplar

Poplar is one of the main urban and rural greening and shade tree species in the northern hemisphere, but its growth and development is always restricted by salt stress. R2R3-MYB transcription factor family is commonly involved in many biological processes during plant growth and stress endurance. In this study, PagMYB151 (Potri.014G035100) one of R2R3-MYB members related to salt stress and expressed in both nucleus and cell membrane was cloned from Populus alba × P. glandulosa to perfect the salt tolerance mechanism. Morphological and physiological indexes regulated by PagMYB151 were detected using the PagMYB151 overexpression (OX) and RNA interference (RNAi) transgenic poplar lines. Under salt stress conditions, compared with RNAi and the non-transgenic wild-type (WT) plants, the plant height, both aboveground and underground part fresh weight of OX was significantly increased. In addition, OX has a longer and finer root structure and a larger root surface area. The root activity of OX was also enhanced, which was significantly different from RNAi but not from WT under salt treatment. Under normal conditions, the stomatal aperture of OX was larger than WT, whereas this phenotype was not obvious after salt stress treatment. In terms of physiological indices, OX enhanced the accumulation of proline but reduced the toxicity of malondialdehyde to plants under salt stress. Combing with the transcriptome sequencing data, 6 transcription factors induced by salt stress and co-expressed with PagMYB151 were identified that may cooperate with PagMYB151 to function in salt stress responding process. This study provides a basis for further exploring the molecular mechanism of poplar PagMYB151 transcription factor under abiotic stress.

Nitrogen addition and drought affect nitrogen uptake patterns and biomass production of four urban greening tree species in North China

Nitrogen (N) is an essential nutrient element limiting plant growth and production, and plant N uptake capacity varies with environmental change. Recently, global climate changes such as N deposition and drought have important impacts on the terrestrial ecosystems, especially for urban greening trees. However, it's still unclear how N deposition and drought affect plant N uptake and biomass production and the underlying relationship between them. Therefore, we conducted a 15N isotope labeling experiment on four common tree species of urban green spaces in North China, including Pinus tabulaeformnis, Fraxinus chinensis, Juniperus chinensis, and Rhus typhina in pots. Three N addition treatments (0, 3.5, and 10.5 gN m −2 year −1; “no”, “low”, and “high” N treatments, respectively) and two water addition treatments (300 and 600 mm year−1; “drought” and “normal water”, respectively) were set up in a greenhouse. Our results showed that N and drought significantly affected tree biomass production and N uptake rates, and the relationship between them depended on the species specificity. Trees could transform their N uptake preference to adapt to the changing environment, from ammonium to nitrate or vice versa, which was also reflected in total biomass. Furthermore, the variation of N uptake patterns was also related to distinct functional traits, including aboveground (specific leaf area and leaf dry matter content) or belowground (specific root length, specific root area, and root tissue density) traits. There was a transformation of plant resource acquisitive strategy in a high N and drought environment. In general, there were tight connections among N uptake rates, functional traits, and biomass production of each target species. This finding comes up with a new strategy that tree species can modify their functional traits and plasticity of the N uptake forms for survival and growth in the context of high N deposition and drought.

Sensitivity of isoprene emission rate to ozone in greening trees is concurrently determined by isoprene synthesis capacity and stomatal conductance

The sensitivity of isoprene emission rate (ISOrate) to ozone (O3) in plant suggests potentially large changes in future isoprene emissions, which will have important consequences for atmospheric chemistry. However, the interspecific variation of ISOrate sensitivity to O3 and its key drivers remain largely unknown. In this study, four urban greening tree species were exposed to two O3 treatments (charcoal-filtered air, CF; and non-filtered ambient air plus 60 ppb extra O3, EO3) in open-top chambers for one growing season. We aimed to compare the interspecific variation in O3 inhibitory effect on ISOrate and explore its physiological mechanism. EO3 decreased the ISOrate by on average 42.5 % across species. According to absolute effect size ranking, the highest ISOrate sensitivity to EO3 was observed in Salix matsudana, followed by Sophora japonica and hybrid poplar clone ‘546’, while Quercus mongolica ISOrate was the least sensitive. Leaf anatomical structures differed in tree species but did not respond to EO3. Furthermore, the ISOrate sensitivity to O3 was driven by the concurrent effects of O3 on ISO synthesis ability (i.e., dimethylallyl diphosphate and isoprene synthase contents) and stomatal conductance. Overall, the mechanistic understanding grained from this study may promote the integrity of O3 effect into process-based ISO emission models.

The image recognition of urban greening tree species based on deep learning and CAMP-MKNet model

The information of urban tree species resources is of vital significance to the planning and design of urban green spaces. Tree organs, such as the bark are used as the primary features of identifying tree species. However, traditional tree identification methods need to consume a lot of manpower and time costs. In addition, the application of machine image recognition technology to tree species recognition still has problems such as heavy data preprocessing workload, small number of tree species images, uneven distribution of categories, and low recognition accuracy. In order to promote the intelligent management of urban forestry and solve the above problems, it is necessary to establish an automatic image recognition model for urban greening tree species. We captured bark images of 21 urban afforestation tree species in their natural environment and constructed a dataset that was divided into a train set, validation set, and test set in the ratio of 7:1:2. Combining Channel Attention Module (CAM) with algorithms such as Spatial Pyramid Pooling (SPP) and Mixed Depthwise Dilated Convolutional Kernels. The core algorithm is Mixed Convolution Kernel (MK), and a CAMP-MKNet Convolutional Neural Network (CNN) is constructed as a bark image classification model for urban greening tree species. The overall accuracy of the generic models ranged from 41.06% to 82.03%, whereas the overall accuracy of the experimental CAMP-MKNet model was 84.25%, with lower prediction cost. Our study shows that the CAMP-MKNet CNN model with better prediction performance and computational cost and can provide crucial insights and technical support for developing automated urban tree species image recognition systems.

Relationship between the amount of black carbon particles deposited on the leaf surface and leaf surface traits in nine urban greening tree species

To select urban greening tree species suitable for the purification of the atmosphere polluted by black carbon (BC) particles, it is necessary to clarify the determinants of the amount of BC particles deposited on the tree leaves. In the present study, we investigated the relationship between the amount of BC particles that were deposited from the atmosphere and firmly adhered to the leaf epicuticular wax, and leaf surface traits in seedlings of nine tree species grown for two years under natural conditions (Fuchu, Tokyo, Japan). There was a significant interspecific difference in the maximum amount of BC particles deposited on the leaf surface, and the order was as follows: Ilex rotunda > Cornus florida > Osmanthus fragrans > Cornus kousa > Quercus glauca ≒ Quercus myrsinifolia > Magnolia kobus ≒ Zelkova serrata ≒ Styrax japonicus. In the nine tree species, significant highly positive correlations were observed between the amount of BC particles deposited on the leaf surface, and the hydrophobicity of leaf epicuticular wax determined by its chemical composition. Therefore, we concluded that the hydrophobicity of leaf epicuticular wax is an important determinant of the amount of BC particles deposited on the leaf surface of urban greening tree species.