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Vegetation has a well-known potential for mitigating urban overheating. This work aims to explore the effects of enhancing urban greenery in Melbourne (Australia) through a configuration of the Weather Research and Forecasting (WRF) model including the Building Effect Parameterization and the Local Climate Zones and presents novelties in: i) covering two-months and ii) focusing on air circulation and buildings cooling energy demand through the ventilation coefficient (VC) and the cooling degree hours (CDHs). A control case and two "what-if" scenarios with a growing green coverage equal to 35 % (control case), 50 % (modest increase) and 60 % (robust increase) have been designed and then simulated for January and February 2019. Outcomes reveal a maximum drop in 2 m temperature of approximately 0.4 °C and 0.8 °C at 14:00 LT for the modest and robust green increase scenario, respectively. The urban-rural energy surplus for cooling buildings is reduced and even counterbalanced. Peak CDHs decrease from 143 °C·h of the control case to 135 °C·h (modest increase) and 126 °C·h (robust increase), while they measure 137 °C·h in the non-urban areas. Average wind speed increases by 0.8 m/s (equal to 22 % with respect to the control case). Furthermore, adding urban greenery has an unfavorable implication on VC (maximum reduction of 500 m2s-1) with a consequent deterioration of the transport and dispersion of pollutants. Middle- and high-density classes are touched more than low-density by the VC reduction. In addition, the benefits of enhancing urban greenery concern physiologically and psychologically the quality of life of the dwellers.

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Canopy imaging offers a non-destructive, efficient way to objectively measure canopy size, detect stress symptoms, and assess pigment concentrations. While it is faster and easier than traditional destructive methods, manual image analysis, including segmentation and evaluation, can be time-consuming. To make imaging more widely accessible, it's essential to reduce the cost of imaging systems and automate the analysis process. We developed a low-cost imaging system with automated analysis using an embedded microcomputer equipped with a monochrome camera and a filter for a total hardware cost of ~USD 500. Our imaging system takes images under blue, green, red, and infrared light, as well as chlorophyll fluorescence. The system uses a Python-based program to collect and analyze images automatically. The multi-spectral imaging system separates plants from the background using a chlorophyll fluorescence image, which is also used to quantify canopy size. The system then generates normalized difference vegetation index (NDVI, "greenness") images and histograms, providing quantitative, spatially resolved information. We verified that these indices correlate with leaf chlorophyll content and can easily add other indices by installing light sources with the desired spectrums. The low cost of the system can make this imaging technology widely available.

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In a production environment, delayed stress recognition can impact yield. Imaging can rapidly and effectively quantify stress symptoms using indexes such as normalized difference vegetation index (NDVI). Commercial systems are effective but cannot be easily customized for specific applications, particularly post-processing. We developed a low-cost customizable imaging system and validated the code to analyze images. Our objective was to verify the image analysis code and custom system could successfully quantify the changes in plant canopy reflectance. 'Supercascade Red', 'Wave© Purple', and 'Carpet Blue' Petunias (Petunia × hybridia) were transplanted individually and subjected to increasing fertilizer treatments and increasing substrate pH in a greenhouse. Treatments for the first trial were the addition of a controlled release fertilizer at six different rates (0, 0.5, 1, 2, 4, and 8 g/pot), and for the second trial, fertilizer solution with four pHs (4, 5.5, 7, and 8.5), with eight replications with one plant each. Plants were imaged twice a week using a commercial imaging system for fertilizer and thrice a week with the custom system for pH. The collected images were analyzed using an in-house program that calculated the indices for each pixel of the plant area. All cultivars showed a significant effect of fertilizer on the projected canopy size and dry weight of the above-substrate biomass and the fertilizer rate treatments (p < 0.01). Plant tissue nitrogen concentration as a function of the applied fertilizer rate showed a significant positive response for all three cultivars (p < 0.001). We verified that the image analysis code successfully quantified the changes in plant canopy reflectance as induced by increasing fertilizer application rate. There was no relationship between the pH and NDVI values for the cultivars tested (p > 0.05). Manganese and phosphorus had no significance with chlorophyll fluorescence for 'Carpet Blue' and 'Wave© Purple' (p > 0.05), though 'Supercascade Red' was found to have significance (p < 0.01). pH did not affect plant canopy size. Chlorophyll fluorescence pixel intensity against the projected canopy size had no significance except in 'Wave© Purple' (p = 0.005). NDVI as a function of the projected canopy size had no statistical significance. We verified the ability of the imaging system with integrated analysis to quantify nutrient deficiency-induced variability in plant canopies by increasing pH levels.

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The arid region of northwest China (ARNC) is the most ecologically fragile region in China, and is characterized by harsh natural conditions, severe soil erosion, and poor soil fertility. Understanding long-term vegetation changes in this region is critical for effective environmental monitoring and climate change adaptation. Fractional vegetation coverage (FVC) is a key parameter for characterizing the ecological conditions of the ARNC. However, the reliance on low-resolution FVC and NDVI data due to the lack of medium-resolution data has limited our understanding of the environmental dynamics in this region. Therefore, this study addressed this gap by utilizing Landsat data to generate FVC data, enabling a detailed investigation of the spatial-temporal variations and driving factors of vegetation in the ARNC from 2000 to 2020. The results indicated the following: (1) The FVC was generally low, with an average of 0.191. The FVC was greater in the northwest and lower in the southeast in terms of spatial distribution features. The trend of FVC change in ARNC showed significant spatial variability, with degradation outweighing improvement. (2) The coefficient of variation of FVC was 0.377, indicating significant temporal fluctuations, with more stable conditions in the northwest than in the southeast. (3) The spatial differentiation of the FVC in ARNC was primarily driven by land cover types, evapotranspiration, and precipitation, with explanatory powers exceeding 30 % each. This study is significant because it provides a comprehensive understanding of vegetation dynamics in one of China's most vulnerable regions, offering critical insights for ecological restoration, desertification control, and sustainable development. The findings underscore the importance of targeted ecological governance to address the challenges posed by environmental degradation in the ARNC.

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Tropical regions have provided new insights into how ecological communities are assembled. In dry coastal communities, water stress has been hypothesized to determine plant assembly structure by favoring preadapted lineages from neighboring ecosystems, consistent with functional clustering. However, it is unclear whether this hypothesis is sufficient to explain how coastal communities in tropical ecosystems are assembled. Here, we test whether water stress or other factors drive community assembly in woody plant communities across the coastal zone of Brazil, a tropical ecosystem. We characterized functional and phylogenetic structures of these communities and determined the underlying environmental factors (e.g., water stress, historical climate stability, edaphic constraints, and habitat heterogeneity) that drive their community assembly. Assemblages of coastal woody species show geographically varied patterns, including stochastic arrangements, clustering, and overdispersion of species relative to their traits and phylogenetic relatedness. Topographic complexity, water vapor pressure, and soil nutrient availability best explained the gradient in the functional structure. Water deficit, water vapor pressure, and soil organic carbon were the best predictors of variation in phylogenetic structure. Our results support the water-stress conservatism hypothesis on functional and phylogenetic structure, as well as the effect of habitat heterogeneity on functional structure and edaphic constraints on functional and phylogenetic structure. These effects are associated with increased phenotypic and phylogenetic divergence of woody plant assemblages, which is likely mediated by abiotic filtering and niche opportunities, suggesting a complex pattern of ecological assembly.

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In this work, radioactivity investigations of soil samples from neutral and agricultural sites in Punjab (India) have been carried out to study the impact of land use patterns. Analyzing soil samples radiological, mineralogical, and physicochemical attributes has employed state-of-the-art techniques. The mean activity concentration of 238U/226Ra, 232Th, 40K, 235U, and 137Cs, measured using a carbon fiber endcap p-type HPGe detector, in neutral land was observed as 58.03, 83.95, 445.18, 2.83, and 1.16 Bq kg-1, respectively. However, in vegetation land, it was found to be 40.07, 64.68, 596.74, 2.26, and 1.90 Bq kg-1, respectively. In the detailed activity analysis, radium equivalent (Raeq) radioactivity is in the safe prescribed limit of 370 Bq kg-1 for all investigated soil samples. However, the dosimetric investigations revealed that the outdoor absorbed gamma dose rate (96.08 nGy h-1) and consequent annual effective dose rate (0.12 mSv y-1) for neutral land and the gamma dose rate (82.46 nGy h-1) and subsequent annual effective dose rate (0.10 mSv y-1) for vegetation land marginally exceeded the global average. The soil's physicochemical parameters (pH, EC, and porosity) from both sites were measured, and their correlations with radionuclides were analyzed. Various heavy metals of health concern, namely, chromium (Cr), arsenic (As), copper (Cu), cobalt (Co), cadmium (Cd), lead (Pb), mercury (Hg), selenium (Se), and zinc (Zn), were also evaluated in soil samples using Inductively Coupled Plasma-Mass Spectroscopy (ICP-MS). Pollution Load Index (PLI) and Ecological Risk Index (RI) revealed that vegetation land was more anthropogenically contaminated than neutral land, with maximum contamination from Hg and As.

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The Palmer Drought Severity Index (scPDSI) and the Standardized Precipitation Evapotranspiration Index (SPEI) are two of the most commonly used drought indices. However, scPDSI and SPEI at a specific scale are often used interchangeably to characterize meteorological drought, agricultural drought, or terrestrial water availability, leading to potential inaccuracies in research outcomes. This study thus presents a global-scale assessment of the applications of scPDSI and SPEI at various timescales (SPEIs) in these contexts. Our findings indicate that scPDSI is more suitable for monitoring agricultural drought than meteorological drought, and highlight the effectiveness of SPEI at one month scale (SPEI01) for meteorological drought. Additionally, SPEI at nine months scale (SPEI09) is more appropriate for agricultural drought. Regarding their relationship with vegetation water stress, scPDSI and SPEI09 are more closely associated with root-zone soil moisture, while SPEI01 is most closely linked to vapor pressure deficit. Furthermore, we evaluate the capability of scPDSI and SPEI in representing terrestrial water availability by analyzing the responses of diverse vegetation indicators to them, including the Normalized Difference Vegetation Index (NDVI), Leaf Area Index (LAI), Solar-Induced Chlorophyll Fluorescence (SIF), and Gross Primary Productivity (GPP). All four vegetation indicators show the highest sensitivity of negative response to SPEI01 in cold climate regions, suggesting SPEI01 is most applicable in these regions. In drylands, vegetation indicators exhibit higher sensitivity of positive responses to SPEI at six months scale (SPEI06) and SPEI09, indicating SPEI06 and SPEI09 effectively characterize water availability in such areas. These findings enhance the understanding of scPDSI and SPEI, providing clearer guidelines for their global-scale applications in meteorological drought, agricultural drought, and terrestrial water availability.

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Vegetation restoration is an effective measure to cope with global climate change and promote soil carbon sequestration. However, during vegetation restoration, the turnover and properties of carbon within various aggregates change. The effects of plant source carbon input on surface soil and subsurface soil may be different. Thus, the characteristics of carbon components in aggregates are affected. Therefore, the research object of this study is the Robinia pseudoacacia forest located in 16-47a of the Loess Plateau, and compared with farmland. The change characteristics of organic carbon functional groups in 0-20 cm, 20-40 cm, and 40-60 cm soil layers were analyzed by Fourier near infrared spectroscopy, and the relationship between the chemical structure of organic carbon and the content of organic carbon components in soil aggregates was clarified, and the mechanism affecting the distribution of organic carbon components in soil aggregates was revealed in the process of vegetation restoration. The results show the following: (1) The stability of surface aggregates is sensitive, while that of deep aggregates is weak. Vegetation restoration increased the surface soil organic carbon content by 1.97~3.78 g·kg-1. (2) After vegetation restoration, the relative contents of polysaccharide functional groups in >0.25 mm aggregates were significantly reduced, while the relative contents of aromatic and aliphatic functional groups of organic carbon were significantly increased. The opposite is true for aggregates smaller than 0.25 mm. (3) With the increase in soil depth, the effect of litter on organic carbon gradually decreased, while the effect of root input on the accumulation of inert carbon in deep soil was more lasting.

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Urban vegetation plays a crucial role in meeting the challenges posed by rapid urbanization and climate change. The presence of plants and green spaces in urban areas provides a variety of environmental, social, and economic benefits. Understanding how users perceive ornamental plants in public green spaces and what their preferences are for certain vegetation elements is extremely important for planning and designing functional and aesthetically interesting urban landscapes. Although landscape experts sometimes use their creativity to create new trends, it is important not to ignore the attitudes and preferences of the public, who sometimes have a different opinion from that of the experts. The aim of the study was to determine the perceptions and preferences of the public and landscape experts for different vegetation elements and the differences in attitudes between these two groups. The study was conducted in Croatia in April 2012 using an online survey (n = 348). The results showed that trees were the most preferred vegetation element and that the public preferred flower beds and lawns to a greater extent than the professionals. All respondents perceived vegetation elements as volumes (trees, shrubs, and hedges) and plains (flower beds and lawns). In addition, respondents perceived two basic types of flower beds according to the features that characterize them: conventional and sustainable. The results show that users perceive the functional and spatial characteristics of the different vegetation elements, which is very important for the design of functional and sustainable urban green spaces.

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To scientifically evaluate the sustainability of tree planting and afforestation in the Alxa Desert region, this study, grounded in the principles of water balance within the natural water cycle, employed multi-source remote sensing products and ground-based measurements to construct a quantitative response relationship model. This model links evapotranspiration (ET) with meteorological variables and the Enhanced Vegetation Index (EVI). Furthermore, the study estimated the recovery thresholds and potential of forest and grassland vegetation coverage in the Alxa Desert region under various precipitation scenarios. The findings reveal that ET exhibited an increasing trend in 84.17% of the Alxa Desert region, with a significant increase observed in 61.53% of the area, indicating positive outcomes from the implementation of the Three-North Shelterbelt Forest Program. Notably, however, ET in the southeastern plain region demonstrated a decreasing trend, which is strongly associated with human activities. The response relationship model demonstrated that linear relationship areas constituted 47.52%, while nonlinear relationship areas accounted for 45.51% of the total. The overall model exhibited an R2 value of 0.69, indicating a high level of predictive accuracy. Analysis of forest and grassland coverage revealed that, under wet year scenarios, the vegetation coverage showed a significant trend of recovery, with an average recovery threshold of (75.4 ± 12.5)% and an average recovery potential of (8.5 ± 3.6)%. It is noteworthy that the vegetation coverage in 31.25% of the area had already surpassed the recovery threshold. The outcomes of this study provide a theoretical foundation for the formulation of more scientifically rigorous ecological restoration strategies in the future.

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Background: Transesophageal echocardiography (TEE) is mandatory before transvenous lead extraction (TLE), but its usefulness remains underestimated. This study aims to describe the broad range of TEE findings in TLE candidates, as well as their influence on procedure complexity, major complications (MCs) and long-term survival. Methods: Preoperative TEE was performed in 1191 patients undergoing TLE. Results: Lead thickening (OR = 1.536; p = 0.007), lead adhesion to heart structures (OR = 2.531; p < 0.001) and abnormally long lead loops (OR = 1.632; p = 0.006) increased the complexity of TLE. Vegetation-like masses on the lead (OR = 4.080; p = 0.44), lead thickening (OR = 2.389; p = 0.049) and lead adhesion to heart structures (OR = 6.341; p < 0.001) increased the rate of MCs. The presence of vegetations (HR = 7.254; p < 0.001) was the strongest predictor of death during a 1-year follow-up period. Conclusions: TEE before TLE provides a lot of important information for the operator. Apart from the visualization of possible vegetations, it can also detect various forms of lead-related scar tissue. Build-up of scar tissue and the presence of long lead loops are associated with increased complexity of the procedure and risk of MCs. Preoperative TEE performed outside the operating room may have an impact on the clinical decision-making process, such as transferring potentially more difficult patients to a more experienced center or having the procedure performed by the most experienced operator. Moreover, the presence of masses or vegetations on the leads significantly increases 1-year and all-cause mortality.

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Vegetation restoration is an effective and important measure for controlling soil erosion in arid and -arid regions. Both its aboveground and underground parts play a crucial role in controlling surface runoff and soil detachment on slopes. But how much the parts of vegetation contribute to the runoff and sediment reducing benefits of rill erosion on slopes is unclear. We used grassland slopes at four successional stages for simulated scouring experiments to observe how successional vegetation community structures, root characteristics, and soil structures contribute to erosion and sand production. Initial flow production time increased, and total runoff decreased. Under the scour intensities, the 11-year slope had the lowest flood peak and volume and the greatest runoff reduction benefit. The 25-year slope had the lowest sand peak and volume and the greatest sediment reduction benefit. As scour intensity increased, runoff reduction effect of vegetation at the successional stages decreased; the sediment reduction benefit remained high. PLS-PM analysis showed that the indirect effects of the aboveground and underground parts of vegetation on sand production were -0.364 and -0.439, respectively. Aboveground parts mainly embodied the regulation of runoff, in which stem count, humus mass, and biomass were the main factors affecting runoff and sand production. Underground parts mainly reflected their soil structure improvement, in which root volume density, root surface area density, and root mass density are the main explanatory variables. The direct effects of runoff and soil structure on slope rill erosion were 0.330 and -0.616, respectively, suggesting the stability of soil structure is the primary factor affecting the sand production, not erosion energy. The results provide a reference for scientific assessment of the key role of natural vegetation restoration in regional soil erosion control and the development of biological measures for soil and water conservation on the slopes of the Loess Plateau.

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One reason arid and semi-arid environments have been used to store waste is due to low groundwater recharge, presumably limiting the potential for meteoric water to mobilize and transport contaminants into groundwater. The U.S. Department of Energy Office of Legacy Management (LM) is evaluating selected uranium mill tailings disposal cell covers to be managed as evapotranspiration (ET) covers, where vegetation is used to naturally remove water from the cover profile via transpiration, further reducing deep percolation. An important parameter in monitoring the performance of ET covers is soil moisture (SM). If SM is too high, water may drain into tailings material, potentially transporting contaminants into groundwater; if SM is too low, radon flux may increase through the cover. However, monitoring SM via traditional instrumentation is invasive, expensive, and may fail to account for spatial heterogeneity, especially over vegetated disposal cells. Here we investigated the potential for non-invasive SM monitoring using radar remote sensing and other geospatial data to see if this approach could provide a practical, accurate, and spatially comprehensive tool to monitor SM. We used theoretical simulations to analyze the sensitivity of multi-frequency radar backscatter to SM at different depths of a field-scale (3 ha) drainage lysimeter embedded within an in-service LM disposal cell. We then evaluated a shallow and deep form of machine learning (ML) using Google Earth Engine to integrate multi-source observations and estimate the SM profile across six soil layers from depths of 0-2 m. The ML models were trained using in situ SM measurements from 2019 and validated using data from 2014 to 2018 and 2020-2021. Model predictors included backscatter observations from satellite synthetic aperture radar, vegetation, temperature products from optical infrared sensors, and accumulated, gridded rainfall data. The radar simulations confirmed that the lower frequencies (L- and P-band) and smaller incidence angles show better sensitivity to deeper soil layers and an overall larger SM dynamic range relative to the higher frequencies (C- and X-band). The ML models produced accurate SM estimates throughout the soil profile (r values from 0.75 to 0.94; RMSE = 0.003-0.017 cm3/cm3; bias = 0.00 cm3/cm3), with the simpler shallow-learning approach outperforming a selected deep-learning model. The ML models we developed provide an accurate, cost-effective tool for monitoring SM within ET covers that could be applied to other vegetated disposal cell covers, potentially including those with rock-armored covers.

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Following soil disturbances, establishing healthy roadside vegetation can reduce surface water runoff, improve soil quality, decrease erosion, and enhance landscape aesthetics. This study explores the use of organic soil amendments (OAs) as alternatives to conventional vegetation growth approaches, aiming to provide optimal compost mixing ratios for poor soils, and clarify guidelines for OAs' use in roadside projects. Three sandy loam soils and one loam soil were chosen for the study. Organic amendments included yard waste (Y), food waste (F), turkey litter and green waste-based (T) composts, and wood-derived biochar (B). Treatment applications targeted specific increases in the organic matter (OM) percentage of the soils. A selection of seven native species (grasses and forbs) in a total of 156 pots (4 control soils + 4 soils x 4 OAs x 3 application rates, all prepared in triplicates) was used for the pot study experiment. A significant correlation between electrical conductivity (soluble salts) in soil-OA blends and corresponding percent green coverage (%GC) was found. High salts from the T compost either delayed or curtailed growth. Notably, 3 out of the 4 soils amended with biochar exhibited rapid vegetation coverage during initial growth stages compared to other soil-OA blends but reduced the nitrogen (N) uptake and leaf area in black-eyed Susan (BES) plants. In contrast, N uptake was higher in the BES plants emerging from composts T, F, and Y compared to biochar. It is recommended to minimize concentrated manure-based (e.g., turkey litter) composts for roadside projects as an OM source, and alternatively, enriching wood-based biochar with nutrients when used as a soil amendment. Within the current study, composts such as F and Y were well-suited to establish healthy and long-lasting vegetation.

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Mountainous regions are vital biodiversity hotspots with high heterogeneity, providing essential refugia for vegetation. However, climate change threatens this diversity with the potential homogenization of the distinct environmental conditions at different elevations. Here, we used a time-series (1985-2023) of Normalized Difference Vegetation Index (NDVI) from Landsat archives (30 m) to quantify vegetation changes across an elevation gradient on Himalaya Mountain. Our analysis revealed that over the past 40 years, the Himalayas have experienced widespread greening, accompanied by homogenization of vegetation across elevations. This homogenization, characterized by a reduction in the differences between high and low elevations, can be attributed to two main factors: (1) increased warming and a higher snowmelt rate at high elevations, facilitating rapid changes in high-elevation vegetation activities; and (2) higher anthropogenic disturbance at low and mid elevations, thus inhibiting low-elevation vegetation. These factors have resulted in a reduction of habitat differentiation along the mountain slopes, homogenizing vegetation and potentially threatening the unique biodiversity adapted to specific elevational zones. Our findings emphasize the urgent need for conservation strategies that prioritize the protection of heterogeneous mountain habitats to preserve their rich biodiversity in the face of climate change.

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While large-scale vegetation greening in China has substantially influenced global vegetation dynamics, the specific impact of this restoration on water use efficiency (WUE) remained inadequately understood. This study employed both the Geodetector and structural equation modeling (SEM) methods, utilizing the Lund-Potsdam-Jena (LPJ) Global Dynamic Vegetation Model, to explore the contributions of various driving factors to China's potential vegetation WUE from 1982 to 2019. The results indicated: (1) there existed considerable further potential for vegetation recovery nationwide. Among them, the Loess Plateau, Inner Mongolia Plateau, and northern Xinjiang had relatively high potential for vegetation recovery. This potential was further amplified by the significant prospects for enhancing WUE in these areas; (2) The application of the Geodetector method revealed that the normalized difference vegetation index (NDVI) explained over 40 % of the variation in potential vegetation WUE in China, exerting a greater influence than climatic factors. In arid/semi-arid regions, precipitation (PRE), NDVI, and vapor pressure deficit (VPD) significantly influenced WUE. Temperature (TEM) was the dominant factor affecting WUE in humid and humid/semi-humid regions; (3) Utilizing the SEM analysis method, it was evident that NDVI exerted the most substantial direct positive influence on potential vegetation WUE in China, whereas VPD and PRE had notable negative impacts. In arid/semi-arid regions, PRE emerged as the primary determinant of WUE. Conversely, in regions where water resources were not limiting, TEM and VPD exerted a more pronounced influence on potential vegetation WUE. This indicated that while vegetation restoration generally enhanced potential vegetation WUE, other factors such as PRE, TEM, and VPD played critical roles in different climatic zones, shaping the regional variations in WUE.

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Greenspaces are important components of our living environment and have been linked to various human health. However, the mechanisms underlying the linkages remain unclear. Enriching microbiota has emerged as a novel mechanism, but the corresponding evidence is still limited. We collected soil samples from forest land, grassland, and barren land in Zunyi City, southwestern China and prepared soil solutions. A total of 40 BALB/c mice were evenly divided into normal control group, model control group, forest soil group, grassland soil group, and barren land soil group. After establishing the pseudo germ-free mouse model, different soil solutions were administered through gavage, lasting for seven weeks. Fecal samples were collected and a 16S rRNA high-throughput sequencing analysis was performed. Then, alpha- and beta-diversity were calculated and employed to estimate the effects of soil exposures on mice gut microbial diversity and composition. Further, Linear Discriminant Analysis Effect Size (LEfSe) analysis was carried out to evaluate the effects of soil exposures on gut microbiota specific genera abundances and functional pathways. Compared to mice exposed to barren land soils, those exposed to soils sourced from forest land showed an increase of 0.43 and 70.63 units in the Shannon index and the Observed ASVs, respectively. In addition, exposure to soils sourced from forest land and grassland resulted in healthier changes (i.e., more short-chain fatty acids (SCFAs)-producing bacteria) in gut microbiota than those from barren land. Furthermore, mice exposed to forest soil and grassland soil showed enrichment in 5 and 3 pathways (e.g., butanoate metabolism) compared to those exposed to barren land soil, respectively. In conclusion, exposure to various greenspaces soils may modify the gut microbial communities of mice, potentially fostering a more beneficial microbiota profile. Further better-designed studies are needed to validate the current findings and to explore the effects of greenspace related gut microbiota on human health.

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In Mexico, land use changes have significantly impacted the diversity of amphibians and reptiles in a negative way. In light of this, we evaluate the alpha and beta components of the taxonomic diversity of amphibians and reptiles in a heterogeneous landscape in west-central Mexico. Additionally, we provide a checklist of amphibian and reptile species recorded over nine years of observations within the studied landscape and surrounding areas. The land cover/use types with the highest species richness and alpha taxonomic diversity differed between amphibians and reptiles. Overall beta taxonomic diversity was high for both groups, but slightly higher in reptiles. This taxonomic differentiation mainly corresponded to a difference in the turnover component and was greater in pristine habitats compared to disturbed ones. The checklist records 20 species of amphibians (ten of which are endemic) and 48 of reptiles (30 endemics). Additionally, the study expands the known geographical distribution range of one species of frog and three species of snakes. Our findings suggest that heterogeneous landscapes with diverse land cover/use types can provide essential habitats for the conservation of amphibian and reptile species.

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Introduction: Understory removal is frequently used to relieve the renewal pressure on trees and promote the growth capability of trees for maintaining community stability, while the lack of previous study on temperate forests limits our assessment of the effectiveness of this essential management measurement. Methods: In this study, we calculated the niche characteristics and interspecific association of main understory species and community stability in temperate forests [original broad-leaved Korean pine forest (BKF), Betula platyphylla secondary forest (BF), and Larix gmelinii plantation (LF)] after understory removal for characterizing the resource utilization capacity of the regeneration trees. Results: During the restoration stage, the niche breadth of understory plants with similar habits varied across stands and layers; regeneration tree species with heliophile and semishade occupied a larger niche in BKF and LF, while it was the opposite in LF. Niche overlap among heliophile regeneration trees increased in both BKF and BF, but not in LF. The interspecific association among main species revealed that the distribution of each species was independent and the interspecific association was loose and it varied in different forests and different light-demanding species with regeneration trees. The stability of shrub communities in BF and LF improved whereas that of BKF declined, while that of the herb communities of corresponding forests showed the opposite state. Discussion: Our study demonstrated that the effectiveness of understory removal depends on species' ecological habits, which enhances the renewal and resource utilization capacity of regeneration tree species in temperate forests and shrub community stability in BF and LF.

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The coastal regions of India, particularly the Bay of Bengal, are highly vulnerable to the severe weather conditions induced by tropical cyclones. This study presents a comprehensive analysis of the changes in vegetation cover, shoreline dynamics, and meteorological variations resulting from Cyclone Michaung and subsequent post-monsoon events along the coastal zones of Andhra Pradesh and Tamil Nadu, India. A suite of vegetation indices, including the Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), Modified Vegetation Condition Index (mVCI), and Disaster Vegetation Damage Index (DVDI), were employed to assess changes in vegetation cover. The Digital Shoreline Assessment System (DSAS) was utilized to evaluate shoreline changes, and a range of meteorological variables were analyzed to assess the impacts of Cyclone Michaung and post-monsoon events. The findings reveal significant ecological impacts, with a notable decrease in Very Healthy Vegetation from 5.71% to 1.30%. The mean value of mVCI shifted from -0.2 to -0.16, indicating vegetation stress. DVDI analysis showed that 56.49% of the area experienced moderate damage, while 40.24% suffered severe vegetation damage. Additionally, erosion was observed along 79.46% of the shoreline transects in the study area. These insights are critical for assisting coastal managers in developing resilient coastal systems. Remarkably, a significant change in rainfall was recorded between the pre-cyclone period and the landfall day, with maximum rainfall intensifying from 13.93 mm/h on December 3rd to 164.26 mm/h on December 4th, and subsequently decreasing to 144.39 mm/h on December 5th.