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To quantitatively reflect the relationship between dust and plant spectral reflectance. Dust from different sources in the city were selected to simulate the spectral characteristics of leaf dust. Taking Euonymus japonicus as the research object. Prediction model of leaf dust deposition was established based on spectral parameters. Results showed that among the three different dust pollutants, the reflection spectrum has 6 main reflection peaks and 7 main absorption valleys in 350–2500 nm. A steep reflection platform appears in the 692–763 nm band. In 760–1400 nm, the spectral reflectance gradually decreases with the increase of leaf dust coverage, and the variation range was coal dust > cement dust > pure soil dust. The spectral reflectance in 680–740 nm gradually decreases with the increase of leaf dust coverage. In the near infrared band, the fluctuation amplitude and slope of its first derivative spectrum gradually decrease with the increase of leaf dust. The biggest amplitude of variation was cement dust. With the increase of dust retention, the red edge position generally moves towards short wave direction, and the red edge slope generally decreases. The blue edge position moved to the short wave direction first and then to the long side direction, while the blue edge slope generally shows a decreasing trend. The yellow edge position moved to the long wave direction first and then to the short wave direction (coal dust, cement dust), and generally moved to the long side direction (pure soil dust). The yellow edge slope increases first and then decreases. The R2 values of the determination coefficients of the dust deposition prediction model have reached significant levels, which indicated that there was a relatively stable correlation between the spectral reflectance and dust deposition. The best prediction model of leaf dust deposition was leaf water content index model (y = 1.5019x − 1.4791, R2 = 0.7091, RMSE = 0.9725).

Urban plants can improve several environmental pollution problems in cities, especially dust prevention, noise reduction, purification of the atmosphere, etc. To explore the influence of dust deposition on the spectral characteristics of the leaf, a foliar dust deposition prediction model based on high-spectrum data was established. Taking Euonymus japonicus L., the common greening tree species in Beijing, as the research object, high (T1), medium (T2), and low (T3) dust pollution gradients were set and hyperspectral data were collected. Results showed that: (1) in the dust-contaminated environment with different concentrations, the trend of the reflectance curve of the leaves of Euonymus japonicus L. was generally consistent. The spectral reflectance of the leaf surface was positively correlated with the amount of leaf dust. (2) There were five obvious reflection peaks and five main absorption valleys with the same positions and ranges in the 350-2500 nm range. (3) The spectral reflectance of leaf flour dust particles of Euonymus japonicus L. was significantly different before and after dusting, and its size was generally clean leaves > dust-depositing leaves. The sensitive range of its spectral response was 695-1400 nm. (4) The overall trend of the first derivative spectrum was basically the same. The red edge slope and the blue edge slope appeared as T3 > T2 > T1, the red edge position and the blue edge position appeared as T1 < T2 < T3. The red edge position of the leaf surface after dust deposition had an obvious "blueshift", and the moving distance increases with the increase of dust retention on leaf surface. (5) The leaf water index (y = - 1.18x2 + 0.5424x + 0.9917, R2 = 0.8030, RMSE = 0.187) had the highest accuracy in the regression model of leaf surface dust deposition using spectral parameters. The test showed that the R2 reached 0.9019, which indicated that the model has a good fitting effect. This prediction model can effectively estimate the dust deposition of the leaf surface of Euonymus japonicus L.

BackgroundUnderstanding the ecological strategies of urban trees to the urban environment is crucial to the selection and management of urban trees. However, it is still unclear whether urban tree pit cover will affect plant functional traits. Here, we study the response of urban trees to different tree pit covers, analyzed the effects of different cover types on soil properties and their trade-off strategies based on leaf functional traits.ResultsWe found that there were obvious differences in the physical properties of the soil in different tree pit covers. Under the different tree pit cover types, soil bulk density and soil porosity reached the maximum under cement cover and turf cover, respectively. We found that tree pit cover significantly affected the leaf properties of urban trees. Leaf thickness, chlorophyll content index and stomatal density were mainly affected by soil bulk density and non-capillary porosity in a positive direction, and were affected by soil total porosity and capillary porosity in a negative direction. Leaf dry matter content and stomata area were mainly negatively affected by soil bulk density and non-capillary porosity, and positively affected by soil total porosity and capillary porosity. Covering materials of tree pits promoted the functional adjustment of plants and form the best combination of functions.ConclusionUnder the influence of tree pit cover, plant have low specific leaf area, stomata density, high leaf thickness, chlorophyll content index, leaf dry matter content, leaf tissue density and stomata area, which belong to “quick investment-return” type in the leaf economics spectrum.

Background How to quickly predict and evaluate urban dust deposition is the key to the control of urban atmospheric environment. Here, we focus on changes of plant reflectance and plant functional traits due to dust deposition, and develop a prediction model of dust deposition based on these traits. Results The results showed that (1) The average dust deposition per unit area of Ligustrum quihoui leaves was significantly different among urban environments (street (18.1001 g/m2), community (14.5597 g/m2) and park (9.7661 g/m2)). Among different urban environments, leaf reflectance curves tends to be consistent, but there were significant differences in leaf reflectance values (park (0.052–0.585) > community (0.028–0.477) > street (0.025–0.203)). (2) There were five major reflection peaks and five major absorption valleys. (3) The spectral reflectances before and after dust removal were significantly different (clean leaves > dust-stagnant leaves). 695 ~ 1400 nm was the sensitive range of spectral response. (4) Dust deposition has significant influence on slope and position of red edge. Red edge slope was park > community > street. After dust deposition, the red edge position has obviously “blue shift”. The moving distance of the red edge position increases with the increase of dust deposition. The forecast model of dust deposition amount established by simple ratio index (y = 2.517x + 0.381, R2 = 0.787, RMSE (root-mean-square error) = 0.187. In the model, y refers to dust retention, x refers to simple ratio index.) has an average accuracy of 99.98%. (5) With the increase of dust deposition, the specific leaf area and chlorophyll content index decreased gradually. The leaf dry matter content, leaf tissue density and leaf thickness increased gradually. Conclusion In the dust-polluted environment, L. quihoui generally presents a combination of characters with lower specific leaf area, chlorophyll content index, and higher leaf dry matter content, leaf tissue density and leaf thickness. Leaf reflectance spectroscopy and functional traits have been proved to be effective in evaluating the changes of urban dust deposition.

Background Functional trait-based ecological research has been instrumental in advancing our understanding of environmental changes. It is still, however, unclear how the functional traits of urban plants respond to atmospheric particulate matter, and which trade-off strategies are shown. In order to explore the variation of plant functional traits with the gradient of urban atmospheric particulate matter, we divided atmospheric particulate matter into three levels according to road distance, and measured the variation of six essential leaf functional traits and their trade-off strategies. Results Here, we show that the functional traits of plants can be used as predictors of plant response to urban atmospheric particulate matter. Within the study, leaf thickness, leaf dry matter content, leaf tissue density, stomatal density were positively correlated with atmospheric particulate matter. On the contrary, chlorophyll content index and specific leaf area were negatively correlated with atmospheric particulate matter. Plants can improve the efficiency of gas exchange by optimizing the spatial distribution of leaf stomata. Under the atmospheric particulate matter environment, urban plants show a trade-off relationship of economics spectrum traits at the intraspecific level. Conclusion Under the influence of urban atmospheric particulate matter, urban plant shows a “slow investment-return” type in the leaf economics spectrum at the intraspecific level, with lower specific leaf area, lower chlorophyll content index, ticker leaves, higher leaf dry matter content, higher leaf tissue density and higher stomatal density. This finding provides a new perspective for understanding the resource trades-off strategy of plants adapting to atmospheric particulate matter.

Background: The visual forms of individual trees in peri-urban forests are driven by a complex array of simultaneous cause-and-effect relationships. Materials and Methods: Structural Equation Modeling (SEM), as a specialized analytical technique, was used to model and understand the complex interactions. It was applied to find out responses of visual forms to neighboring competition in a peri-urban forest dominated by Cotinus coggygria var. cinerea Engl. in Beijing, China. Research Highlights: Light interception and space extrusion have substantial effects on visual forms, expressed as crown forms and foliage forms. The structural model in SEM tested hypothetical correlations among latent variables, namely neighboring competition, crown forms, and foliage forms. Results: The fitted model suggested a direct negative effect of neighboring competition on crown forms and an insignificant negative direct effect on foliage forms. Moreover, an indirect positive effect on foliage forms mediated by crown forms was revealed. Conclusions: The fitted SEM and associated findings should facilitate peri-urban forest landscape management by providing insight into causal mechanisms of visual forms of individual trees and thereby assisting in the visual quality promotion.

Background: Functional trait-based ecological research has been instrumental in advancing our understanding of understanding of environmental changes. It is still, however, unclear how the functional traits of urban plants respond to atmospheric particulate pollution, and what trade-off strategies are shown. In order to explore the variation of plant functional traits with urban atmospheric particulate pollution gradient, we divided atmospheric particulate pollution into three levels according to road distance, and measured the variation of six key leaf functional traits and their trade-off strategies. Results: Here, we show that the functional traits of plants can be used as predictors or indicators of the response of plant to urban atmospheric particulate pollution. Within studies, there was a positive correlation between leaf thickness, leaf dry matter content, leaf tissue density, stomata density and leaf dust deposition. While chlorophyll content index and specific leaf area were negatively correlated with the leaf dust deposition. Plants improve the efficiency of gas exchange by optimizing the spatial distribution of stomata of leaves. Dust deposition promotes the regular distribution of stomata. Due to the pressure of atmospheric particles, urban plant shows a trade-off relationship of economics spectrum traits at the leaf level. Taken together, these results indicate that urban atmospheric particulate pollution is the main factor causing the variation of plant functional traits. Conclusion：Under the influence of urban atmospheric particulate matter, plant show a "slow investment-return" type in the global leaf economics spectrum, with lower specific leaf area, lower chlorophyll content, larger leaf thickness, higher leaf dry matter content, higher leaf tissue density and higher stomatal density. This finding provides a new perspective for understanding the resource trades-off strategy of plants adapting to air pollution environment.

Urban green space is an important element of well-being. It is still, however, lacking of research on green space demand analyzing based on social platform data. This research uses social platform data to evaluate people's demand for urban green space under the background of the global COVID-19 pneumonia. Using the micro-blog database of geographical markers and keywords, this research quantified the sentiment expressed inside and outside the parks by means of manual interpretation of characters, pictures and expressions. It addresses the following problems: dose COVID-19 pneumonia reduced people’s demand for green space? Our results showed that despite the restriction of epidemic situation, people still have a great demand for external green space. Older people have less negative sentiment, while younger people (under 18 years) have more negative sentiment. There were significant differences in emotional scores between inside and outside the park. During the period of pneumonia in COVID-19, tourists in Beijing Park generated more positive microblogs inside the park. Landscape and plants are the main elements of people's expression of positive emotions. The emotional scores inside and outside the park are negatively correlated with the new confirmed cases, existing confirmed cases and new deaths.

Studies on the influence of parasitism on plants based on hyperspectral analysis have not been reported so far. To fully understand the variation characteristics and laws of leaf reflectance spectrum and functional traits after the urban plant parasitized by Cuscuta japonica Choisy. Osmanthus fragrans (Thunb.) Lour. was taken as the research object to analyze the spectral reflectance and functional traits characteristics at different parasitical stages. Results showed that the spectral reflectance was higher than those being parasitized in the visible and near-infrared range. The spectral reflectance in 750~1400 nm was the sensitive range of spectral response of host plant to parasitic infection, which is universal at different parasitic stages. We established a chlorophyll inversion model (y = −65913.323x + 9.783, R2 = 0.6888) based on the reflectance of red valley, which can be used for chlorophyll content of the parasitic Osmanthus fragrans. There was a significant correlation between spectral parameters and chlorophyll content index. Through the change of spectral parameters, we can predict the chlorophyll content of Osmanthus fragrans under different parasitic degrees. After being parasitized, the leaf functional traits of host plant were generally characterized by large leaf thickness, small leaf area, small specific leaf area, low relative chlorophyll content, high leaf dry matter content and high leaf tissue density. These findings indicate that the host plant have adopted a certain trade-off strategy to maintain their growth in the invasion environment of parasitic plants. Therefore, we suspect that the leaf economics spectrum may also exist in the parasitic environment, and there was a general trend toward the “slow investment-return” type in the global leaf economics spectrum.

Background: Studies on the influence of parasitism on plants based on hyperspectral analysis have not been reported so far. To fully understand the variation characteristics and laws of leaf reflectance spectrum and functional traits after the urban plant parasitized by Cuscuta japonica Choisy. Osmanthus fragrans (Thunb.) Lour. was taken as the research object to analyze the spectral reflectance and functional traits characteristics at different parasitical stages. Results: Results showed that the spectral reflectance was higher than the parasitic reflectance in the visible light and near infrared. The spectral reflectance in 750 ~ 1400 nm was the sensitive range of spectral response of host plants to parasitic infection, which is universal at different parasitic stages. We established a chlorophyll inversion model (y=-65913.323x+9.783, R2=0.6888) based on the reflectance of red valley (minimum band reflectance in the range of 640 ~ 700 nm), which can be used for chlorophyll content of the parasitic Osmanthus fragrans. There was a significant correlation between spectral characteristic parameters and chlorophyll content index. Through the change of spectral parameters, we can predict the chlorophyll content of Osmanthus fragrans under different parasitism degrees.Conclusion: After the host plant was invaded by parasitic plants, its leaf functional traits are generally characterized by thick leaf, small leaf area, small specific leaf area, low relative chlorophyll content, high dry matter content and high leaf tissue density. These findings indicate that the host plant have taken certain trade-off strategy to maintain their growth in the environment invaded by parasitic plants. Therefore, we suspect that there may be leaf economics spectrum in the parasitic environment, and there was a general trend toward "slow investment-return" in the global leaf economics spectrum.

Quercus aquifolioides is one of the most representative broad-leaved plants in Qinghai-Tibet Plateau with important ecological status. So far, understanding how to quickly estimate the chlorophyll content of plants in plateau areas is still an urgent problem. Field Spec 3 spectrometer was used to measure hyperspectral reflectance data of Quercus aquifolioides leaves at different altitudes, and CCI (chlorophyll relative content) of corresponding leaves was measured by a chlorophyll meter. The correlation and univariate linear fitting analysis techniques were used to establish their relationship models. The results showed that: (1) Chlorophyll relative content of Quercus aquifolioides, under different altitude gradients, were significantly different. From 2905 m to 3500 m, chlorophyll relative content increased first and then decreased. Altitude 3300 m was the most suitable growth area. (2) In 350~550 nm, the spectral reflectance was 3500 m &gt, 3300 m &gt, 2905 m. In 750~1100 nm, the spectral reflectivity was 2905 m &gt, 3500 m &gt, 3300 m. (3) There were 4 main reflection peaks and 5 main absorption valleys in the leaf surface spectral reflection curve. While, 750~1400 nm was the sensitive range of leaf spectral response of Quercus aquifolioides. (4) The red edge position and red valley position moved to short wave direction with the increase of altitude, while the yellow edge position and green peak position moved to long wave direction first and then to short wave direction. (5) The correlation curve between the original spectrum and the CCI value was the best between the wavelengths 509~650 nm. The correlation between the first derivative spectrum and CCI value was the best and most stable at 450~500 nm. The green peak reflectance was most sensitive to the relative chlorophyll content of Quercus aquifolioides. The estimation model R2 of green peak reflectance was the highest (y = 206.98e&minus, 10.85x, R2 = 0.8523), and the prediction accuracy was 95.85%. The research results can provide some technical and theoretical support for the protection of natural Quercus aquifolioides forests in Tibet.

BackgroundResponse and adaptation strategies of plants to the environment have always been the core issues in ecological research. So far, relatively little study exists on its functional traits responses to warming, especially in an urban environment. This information is the key to help understand plant responses and trade-off strategy to urban warming.ResultsWe chose the common greening trees of mature age in Beijing (Fraxinus pennsylvanica, Koelreuteria paniculata, and Sophora japonica) as the research subjects, and used infrared heaters to simulate warming for three gradients of natural temperature (CK), moderate warming (T1) and severe warming (T2). Results showed that:(1) Leaf dry matter content (LDMC), chlorophyll content (CHL), leaf tissue density (LTD), and stomatal density (SD) all increased with temperature warming. Specific leaf area (SLA), stomatal size (SS), and stomatal aperture (SA) decreased with simulated warming. (2) SLA was extremely significantly negatively correlated with CHL, LDMC, LTD and SD (P P P P P R2and slope among the leaf traits were higher than CK, and the significance was also enhanced. The correlation between leaf traits was strengthened in this warming environment. Conversely, it will weaken the correlation between leaf traits under the T2 treatment.ConclusionOur study demonstrated that there was a strong trade-off between leaf functional traits in the urban warming environment. Plants in the warming environment have adopted relatively consistent trade-offs and adaptation strategies. Moderate warming was more conducive to strengthening their trade-off potential. It is further verified that the global leaf economics spectrum also exists in urban ecosystems, which is generally tend to a quick-investment return type with the characteristics of thick leaves, strong photosynthetic capacity, low transpiration efficiency and long life in urban environments.

Rapidly determining leaf vein network patterns and vein densities is biologically important and technically challenging. Current methods, however, are limited to vein contour extraction. Further image processing is difficult, and some leaf vein traits of interest therefore cannot be quantified. In this study, we proposed a novel method for the fast and accurate determination of leaf vein network patterns and vein density. Nine tree species with different leaf characteristics and vein types were applied to verify this method. To overcome the image processing difficulties at the microscopic scale, we adopted the remote object-oriented classification method applied comprehensively in the field of remote sensing research. The key to this approach is to determine the universally applicable leaf vein extraction threshold values (scale parameter, shape parameter, compactness parameter, brightness feature, spectral feature and geometric feature). Based on our analysis, the following recommended threshold values were determined: the scale parameter was 250, the shape parameter was 0.7, the compactness parameter was 0.3, the brightness feature value was 230∼280, the spectral feature value was 180∼230, and the geometric feature value was less than 2. With the optimal extraction parameters applied, the extraction precision was above 96.40% on average for the nine species studied. The leaf vein density calculation rate increased by more than 87.3% compared to that of the traditional methods. The results showed that this method is accurate, fast, flexible and complementary to existing technologies. It is an effective tool for the fast extraction of vein networks and the exploration of leaf vein characteristics, particularly for large-scale studies in plant vein physiology.

Nocturnal sap flow is an important part of plant sap flow, while it is usually regarded as negligible. Consequently, the aim of this study was to measure nocturnal stem sap flow of Acer truncatum and to determine its driving force in an urban green space. Stomatal aperture was measured using surface impression method in a typical clear day of August. Sap flux density was monitored by a thermal diffusive probe system from July to October. Meanwhile, wind speed (WS), relative humidity, air temperature, precipitation and total solar radiation were monitored by an automatic weather station. We found nocturnal stomatal aperture was about 32% of mid-morning, and nocturnal sap flux density was significantly and positively affected by WS and vapor pressure deficit (VPD) (P

Leaf stomata are important structures used for exchanging matter between plants and the environment, and they are very sensitive to environmental changes. The method of efficiently extracting stomata, as well as measuring stomatal density and area, still lacks established techniques. This study focused on the leaves of Fraxinus pennsylvanica Marshall, Ailanthus altissima (Mill.) Swingle, and Sophora japonica (L.) Schott grown on different underlying surfaces and carried out an analysis of stomatal information using multiscale segmentation and classification recognition as well as microscopy images of leaf stomata via eCognition Developer 64 software (Munich, Germany). Using this method, we further analyzed the ecological significance of stomata. The results were as follows: (1) The best parameters of stomatal division and automatic extraction rules were scale parameter 120&ndash, 125 + shape parameter 0.7 + compactness parameter 0.9 + brightness value 160&ndash, 220 + red light band &gt, 95 + shape&ndash, density index 1.5&ndash, 2.2, the accuracy of stomatal density and stomatal area using this method were 98.2% and 95.4%, respectively. (2) There was a very significant correlation among stomatal density, stomatal area, and stomatal shape index under different growing environments. When the stomatal density increased, the stomatal area lowered remarkably and the stomatal shape tended to be flat, suggesting that the plants had adopted some regulatory behavior at the stomatal level that might be an ecological trade-off strategy for plants to adapt to a particular growing environment. These findings provide a new approach and applicable parameters for stomata extraction, which can further calculate the stomatal density and stomatal area and deepen our understanding of the relationship between stomata and the environment. The study provides useful information for urban planners on the breeding and introduction of high-temperature-resistant urban plants.

Urban forests affect the filtration and absorption of airborne particulate matter, which can minimize the harmful effects to human health caused by airborne particulate pollution. Evergreen plants in urban forests play a major role in absorbing dust and purifying the air, especially in winter. Studying the spatial distribution of leaf dust and exploring the dust retention effect of evergreen shrubs are important for scientifically guiding urban forest construction and improving the living environment of cities in winter. The purpose of this study was to establish a dust inversion model by correlation analysis of spectral reflectance and the amount of dust absorption (ADA) of vegetation, using Sentinel-2 satellite remote-sensing images to obtain the dust distribution of the evergreen vegetation (mainly Euonymus japonicus Thunb.) in the Beijing urban area, and to determine the effect of the spatial pattern of E. japonicus woodland on ADA intensity. The result showed that the red band and near-infrared band are most sensitive to dust. The normalized difference phenology index (NDPI) is more suitable for building an inversion model, where the determination coefficient (R2) of the inversion model constructed by the ratio of the NDPI (RNDPI) was 0.879. The inversion results show that the mean ADA in the enclosed area is smaller than that in semi-enclosed and open areas, and the regional distribution of high ADA in the urban area of Beijing was higher in the south with a tendency of the ADA to decrease from city center to the surrounding area. The size, shape, and percentage of landscape (PLAND) of E. japonicus woodland have a significant effect on ADA intensity. We found that, in the study area, when the PLAND of E. japonicus woodland is higher than 40%, its ADA intensity remains basically unchanged. When the vegetation coverage is fixed, the landscape shape index is negatively correlated with ADA intensity, and reduction of the overall shape complexity of forestland can enhance its dust retention effect and improve the air environment of the surrounding areas. The results of this study can be used as a reference for urban planners and landscape architects when building urban forests, providing a scientific basis for controlling and reducing air particulate pollution in Beijing&rsquo, s winter and improving the living environment.