Arctic amplification-induced decline in West and South Asia dust warrants stronger antidesertification toward carbon neutrality.

Dust loading in West and South Asia has been a major environmental issue due to its negative effects on air quality, food security, energy supply and public health, as well as on regional and global weather and climate. Yet a robust understanding of its recent changes and future projection remains unclear. On the basis of several high-quality remote sensing products, we detect a consistently decreasing trend of dust loading in West and South Asia over the last two decades. In contrast to previous studies emphasizing the role of local land use changes, here, we attribute the regional dust decline to the continuous intensification of Arctic amplification driven by anthropogenic global warming. Arctic amplification results in anomalous mid-latitude atmospheric circulation, particularly a deepened trough stretching from West Siberia to Northeast India, which inhibits both dust emissions and their downstream transports. Large ensemble climate model simulations further support the dominant role of greenhouse gases induced Arctic amplification in modulating dust loading over West and South Asia. Future projections under different emission scenarios imply potential adverse effects of carbon neutrality in leading to higher regional dust loading and thus highlight the importance of stronger anti-desertification counter-actions such as reforestation and irrigation management.

Satellite mapping of urban built-up heights reveals extreme infrastructure gaps and inequalities in the Global South.

Information on urban built-up infrastructure is essential to understand the role of cities in shaping environmental, economic, and social outcomes. The lack of data on built-up heights over large areas has limited our ability to characterize urban infrastructure and its spatial variations across the world. Here, we developed a global atlas of urban built-up heights circa 2015 at 500-m resolution from the Sentinel-1 Ground Range Detected satellite data. Results show extreme gaps in per capita urban built-up infrastructure in the Global South compared with the global average, and even larger gaps compared with the average levels in the Global North. Per capita urban built-up infrastructures in some countries in the Global North are more than 30 times higher than those in the Global South. The results also show that the built-up infrastructure in 45 countries in the Global North combined, with ∼16% of the global population, is roughly equivalent to that of 114 countries in the Global South, with ∼74% of the global population. The inequality in urban built-up infrastructure, as measured by an inequality index, is large in most countries, but the largest in the Global South compared with the Global North. Our analysis reveals the scale of infrastructure demand in the Global South that is required in order to meet sustainable development goals.

Construction of Hierarchical Conductive Networks for LiNi0.8Mn0.1Co0.1O2 Cathode toward Stable Cycling at High Areal Mass Loadings.

Realizing high-performance thick electrodes is considered as a practical strategy to promote the energy density of lithium-ion batteries. However, establishing effective transport pathways for both lithium-ions and electrons in a thick electrode is very challenging. This study develops a hierarchical conductive network structure for constructing high-performance NMC811 (LiNi0.8Mn0.1Co0.1O2) cathode toward stable cycling at high areal mass loadings. The hierarchical conductive networks are composed of a Li+/e- mixed conducting interface (lithium polyacrylate/hydroxyl-functionalized multiwalled carbon nanotubes) on NMC811 particles, and a segregated network of single-walled carbon nanotubes in the electrode, without any additional binders or carbon black. Such strategy endows the NMC811 cathode (up to 250 µm and 50 mg cm-2) with low porosity/tortuosity, ultrahigh Li+/e- conductivities and excellent mechanical property at low carbon nanotube content (1.8 wt%). It significantly improves the electrochemical reaction homogeneity along the electrode depth, meanwhile effectively inhibits the side reactions at the electrode/electrolyte interface and cracks in the NMC particles during cycling. This work emphasizes the crucial role of the electronic/ionic cooperative transportation in the performance deterioration of thick cathodes, and provide guidance for architecture optimization and performance improvement of thick electrodes toward practical applications, not just for the NMC811 cathode.

Impact of heat on all-cause and cause-specific mortality: A multi-city study in Texas.

BACKGROUND: Studies on the health effects of heat are particularly limited in Texas, a U.S. state in the top 10 highest number of annual heat-related deaths per capita from 2018 to 2020. This study assessed the effects of heat on all-cause and cause-specific mortality in 12 metropolitan statistical areas (MSAs) across Texas from 1990 to 2011. METHODS: First, we determined the heat thresholds for each MSA above which the relation between temperature and mortality is linear. We then conducted a distributed lag non-linear model for each MSA, followed by a random effects meta-analysis to estimate the pooled effects for all MSAs. We repeated this process for each mortality cause and age group to achieve the effect estimates. RESULTS: We found a 1 °C temperature increase above the heat threshold is associated with an increase in the relative risk of all-cause mortality of 0.60% (95%CI [0.39%, 0.82%]) and 1.10% (95%CI [0.65%, 1.56%]) for adults older than 75. For each MSA, the relative risk of mortality for a 1 °C temperature increase above the heat threshold ranges from 0.10% (95%CI [0.09%, 0.10%]) to 1.29% (95%CI [1.26%, 1.32%]). Moreover, elevated temperatures showed a slight decrease in cardiovascular mortality (0.37%, 95%CI [-0.35%, 1.09%]) and respiratory disease (1.97%, 95%CI [-0.11%, 4.08%]), however this effect was not considered statistically significant.. CONCLUSION: Our study found that high temperatures can significantly impact all-cause mortality in Texas, and effect estimates differ by MSA, age group, and cause of death. Our findings generate critical information on the impact of heat on mortality in Texas, providing insights for policymakers on resource allocation and strategic intervention to reduce heat-related health effects.

Urban warming advances spring phenology but reduces the response of phenology to temperature in the conterminous United States.

Urbanization has caused environmental changes, such as urban heat islands (UHIs), that affect terrestrial ecosystems. However, how and to what extent urbanization affects plant phenology remains relatively unexplored. Here, we investigated the changes in the satellite-derived start of season (SOS) and the covariation between SOS and temperature (RT ) in 85 large cities across the conterminous United States for the period 2001-2014. We found that 1) the SOS came significantly earlier (6.1 ± 6.3 d) in 74 cities and RT was significantly weaker (0.03 ± 0.07) in 43 cities when compared with their surrounding rural areas (P < 0.05); 2) the decreased magnitude in RT mainly occurred in cities in relatively cold regions with an annual mean temperature <17.3 °C (e.g., Minnesota, Michigan, and Pennsylvania); and 3) the magnitude of urban-rural difference in both SOS and RT was primarily correlated with the intensity of UHI. Simulations of two phenology models further suggested that more and faster heat accumulation contributed to the earlier SOS, while a decrease in required chilling led to a decline in RT magnitude in urban areas. These findings provide observational evidence of a reduced covariation between temperature and SOS in major US cities, implying the response of spring phenology to warming conditions in nonurban environments may decline in the warming future.

Satellite-based phenology products and in-situ pollen dynamics: A comparative assessment.

Ongoing climate variability and change is impacting pollen exposure dynamics among sensitive populations. However, pollen data that can provide beneficial information to allergy experts and patients alike remains elusive. The lack of high spatial resolution pollen data has resulted in a growing interest in using phenology information that is derived using satellite observations to infer key pollen events including start of pollen season (SPS), timing of peak pollen season (PPS), and length of pollen season (LPS). However, it remains unclear if the agreement between satellite-based phenology information (e.g. start of season: SOS) and the in-situ pollen dynamics vary based on the type of satellite product itself or the processing methods used. To address this, we investigated the relationship between vegetation phenology indicator (SOS) derived from two separate sensor/satellite observations (MODIS, Landsat), and two different processing methods (double logistic regression (DLM) vs hybrid piecewise logistic regression (HPLM)) with in-situ pollen season dynamics (SPS, PPS, LPS) for three dominant allergenic tree pollen species (birch, oak, and poplar) that dominate the springtime allergy season in North America. Our results showed that irrespective of the data processing method (i.e. DLM vs HPLM), the MODIS-based SOS to be more closely aligned with the in-situ SPS, and PPS while upscaled Landsat based SOS had a better precision. The data products obtained using DLM processing methods tended to perform better than the HPLM based methods. We further showed that MODIS based phenology information along with temperature and latitude can be used to infer in-situ pollen dynamic for tree pollen during spring time. Our findings suggest that satellite-based phenology information may be useful in the development of early warning systems for allergic diseases.

Biological differentiation of traditional Chinese medicine from excessive to deficient syndromes in AIDS: Comparative microRNA microarray profiling and syndrome-specific biomarker identification.

Traditional Chinese medicine (TCM) has been widely applied as a supplementary therapy of human immunodeficiency virus infection and acquired immunodeficiency syndrome (HIV/AIDS) in China. TCM has a positive effect on improving the quality of life, prolonging life, and ameliorating the symptoms of HIV/AIDS patients. Yang deficiency of spleen and kidney (YDSK) syndrome is a typical deficient TCM syndrome in AIDS patients, and accumulation of heat-toxicity (AHT) syndrome is a common excessive syndrome in the earlier stage of AIDS. Thus, accurate diagnosis of these two syndromes can improve the targeted treatment effect, and predict the prognosis of the disease. However, the scientific basis of TCM syndromes remains lacking, greatly hindering the accuracy of diagnosis and effectiveness of treatment. In this research, microRNA (miRNA) microarray and quantitative real-time polymerase chain reaction combined with bioinformatics were used for comparative analysis between YDSK and AHT patients. Significantly differential expressed miRNAs (SDE-miRNAs) of each TCM syndrome were identified, including hsa-miR-766-3p and hsa-miR-1260a and so on, as well hsa-miR-6124, hsa-let-7g-5p and so on, for YDSK and AHT, respectively. Biological differences were found between their SDE-miRNAs based on bioinformatics analyses, for example, ErbB signaling pathway mainly linked to AHT, while focal adhesion dominated in YDSK. Syndrome-specific SDE-miRNAs were further identified as potential biomarkers, including hsa-miR-30e-5p, hsa-miR-144-5p for YDSK and hsa-let-7g-5p, hsa-miR-126-3p for AHT, respectively. All of them have laid biological and clinical bases for TCM diagnosis and treatment of AIDS syndrome at the miRNA level, offering potential diagnostic indicators of immune reconstitution.

Photoperiod decelerates the advance of spring phenology of six deciduous tree species under climate warming.

Vegetation phenology in spring has substantially advanced under climate warming, consequently shifting the seasonality of ecosystem process and altering biosphere-atmosphere feedbacks. However, whether and to what extent photoperiod (i.e., daylength) affects the phenological advancement is unclear, leading to large uncertainties in projecting future phenological changes. Here we examined the photoperiod effect on spring phenology at a regional scale using in situ observation of six deciduous tree species from the Pan European Phenological Network during 1980-2016. We disentangled the photoperiod effect from the temperature effect (i.e., forcing and chilling) by utilizing the unique topography of the northern Alps of Europe (i.e., varying daylength but uniform temperature distribution across latitudes) and examining phenological changes across latitudes. We found prominent photoperiod-induced shifts in spring leaf-out across latitudes (up to 1.7 days per latitudinal degree). Photoperiod regulates spring phenology by delaying early leaf-out and advancing late leaf-out caused by temperature variations. Based on these findings, we proposed two phenological models that consider the photoperiod effect through different mechanisms and compared them with a chilling model. We found that photoperiod regulation would slow down the advance in spring leaf-out under projected climate warming and thus mitigate the increasing frost risk in spring that deciduous forests will face in the future. Our findings identify photoperiod as a critical but understudied factor influencing spring phenology, suggesting that the responses of terrestrial ecosystem processes to climate warming are likely to be overestimated without adequately considering the photoperiod effect.

Global scenarios of urban density and its impacts on building energy use through 2050.

Although the scale of impending urbanization is well-acknowledged, we have a limited understanding of how urban forms will change and what their impact will be on building energy use. Using both top-down and bottom-up approaches and scenarios, we examine building energy use for heating and cooling. Globally, the energy use for heating and cooling by the middle of the century will be between 45 and 59 exajoules per year (corresponding to an increase of 7-40% since 2010). Most of this variability is due to the uncertainty in future urban densities of rapidly growing cities in Asia and particularly China. Dense urban development leads to less urban energy use overall. Waiting to retrofit the existing built environment until markets are ready in about 5 years to widely deploy the most advanced renovation technologies leads to more savings in building energy use. Potential for savings in energy use is greatest in China when coupled with efficiency gains. Advanced efficiency makes the least difference compared with the business-as-usual scenario in South Asia and Sub-Saharan Africa but significantly contributes to energy savings in North America and Europe. Systemic efforts that focus on both urban form, of which urban density is an indicator, and energy-efficient technologies, but that also account for potential co-benefits and trade-offs with human well-being can contribute to both local and global sustainability. Particularly in growing cities in the developing world, such efforts can improve the well-being of billions of urban residents and contribute to mitigating climate change by reducing energy use in urban areas.

Global urban signatures of phenotypic change in animal and plant populations.

Humans challenge the phenotypic, genetic, and cultural makeup of species by affecting the fitness landscapes on which they evolve. Recent studies show that cities might play a major role in contemporary evolution by accelerating phenotypic changes in wildlife, including animals, plants, fungi, and other organisms. Many studies of ecoevolutionary change have focused on anthropogenic drivers, but none of these studies has specifically examined the role that urbanization plays in ecoevolution or explicitly examined its mechanisms. This paper presents evidence on the mechanisms linking urban development patterns to rapid evolutionary changes for species that play important functional roles in communities and ecosystems. Through a metaanalysis of experimental and observational studies reporting more than 1,600 phenotypic changes in species across multiple regions, we ask whether we can discriminate an urban signature of phenotypic change beyond the established natural baselines and other anthropogenic signals. We then assess the relative impact of five types of urban disturbances including habitat modifications, biotic interactions, habitat heterogeneity, novel disturbances, and social interactions. Our study shows a clear urban signal; rates of phenotypic change are greater in urbanizing systems compared with natural and nonurban anthropogenic systems. By explicitly linking urban development to traits that affect ecosystem function, we can map potential ecoevolutionary implications of emerging patterns of urban agglomerations and uncover insights for maintaining key ecosystem functions upon which the sustainability of human well-being depends.

Integrating LiDAR data and multi-temporal aerial imagery to map wetland inundation dynamics using Google Earth Engine.

The Prairie Pothole Region of North America is characterized by millions of depressional wetlands, which provide critical habitats for globally significant populations of migratory waterfowl and other wildlife species. Due to their relatively small size and shallow depth, these wetlands are highly sensitive to climate variability and anthropogenic changes, exhibiting inter- and intra-annual inundation dynamics. Moderate-resolution satellite imagery (e.g., Landsat, Sentinel) alone cannot be used to effectively delineate these small depressional wetlands. By integrating fine spatial resolution Light Detection and Ranging (LiDAR) data and multi-temporal (2009-2017) aerial images, we developed a fully automated approach to delineate wetland inundation extent at watershed scales using Google Earth Engine. Machine learning algorithms were used to classify aerial imagery with additional spectral indices to extract potential wetland inundation areas, which were further refined using LiDAR-derived landform depressions. The wetland delineation results were then compared to the U.S. Fish and Wildlife Service National Wetlands Inventory (NWI) geospatial dataset and existing global-scale surface water products to evaluate the performance of the proposed method. We tested the workflow on 26 watersheds with a total area of 16,576 km2 in the Prairie Pothole Region. The results showed that the proposed method can not only delineate current wetland inundation status but also demonstrate wetland hydrological dynamics, such as wetland coalescence through fill-spill hydrological processes. Our automated algorithm provides a practical, reproducible, and scalable framework, which can be easily adapted to delineate wetland inundation dynamics at broad geographic scales.

The role of protected areas in land use/land cover change and the carbon cycle in the conterminous United States.

Protected areas (PAs) cover about 22% of the conterminous United States. Understanding their role on historical land use and land cover change (LULCC) and on the carbon cycle is essential to provide guidance for environmental policies. In this study, we compiled historical LULCC and PAs data to explore these interactions within the terrestrial ecosystem model (TEM). We found that intensive LULCC occurred in the conterminous United States from 1700 to 2005. More than 3 million km2 of forest, grassland and shrublands were converted into agricultural lands, which caused 10,607 Tg C release from land ecosystems to atmosphere. PAs had experienced little LULCC as they were generally established in the 20th century after most of the agricultural expansion had occurred. PAs initially acted as a carbon source due to land use legacies, but their accumulated carbon budget switched to a carbon sink in the 1960s, sequestering an estimated 1,642 Tg C over 1700-2005, or 13.4% of carbon losses in non-PAs. We also find that PAs maintain larger carbon stocks and continue sequestering carbon in recent years (2001-2005), but at a lower rate due to increased heterotrophic respiration as well as lower productivity associated to aging ecosystems. It is essential to continue efforts to maintain resilient, biodiverse ecosystems and avoid large-scale disturbances that would release large amounts of carbon in PAs.

21st century United States emissions mitigation could increase water stress more than the climate change it is mitigating.

There is evidence that warming leads to greater evapotranspiration and surface drying, thus contributing to increasing intensity and duration of drought and implying that mitigation would reduce water stresses. However, understanding the overall impact of climate change mitigation on water resources requires accounting for the second part of the equation, i.e., the impact of mitigation-induced changes in water demands from human activities. By using integrated, high-resolution models of human and natural system processes to understand potential synergies and/or constraints within the climate-energy-water nexus, we show that in the United States, over the course of the 21st century and under one set of consistent socioeconomics, the reductions in water stress from slower rates of climate change resulting from emission mitigation are overwhelmed by the increased water stress from the emissions mitigation itself. The finding that the human dimension outpaces the benefits from mitigating climate change is contradictory to the general perception that climate change mitigation improves water conditions. This research shows the potential for unintended and negative consequences of climate change mitigation.

Response of vegetation phenology to urbanization in the conterminous United States.

The influence of urbanization on vegetation phenology is gaining considerable attention due to its implications for human health, cycling of carbon and other nutrients in Earth system. In this study, we examined the relationship between change in vegetation phenology and urban size, an indicator of urbanization, for the conterminous United States. We studied more than 4500 urban clusters of varying size to determine the impact of urbanization on plant phenology, with the aids of remotely sensed observations since 2003-2012. We found that phenology cycle (changes in vegetation greenness) in urban areas starts earlier (start of season, SOS) and ends later (end of season, EOS), resulting in a longer growing season length (GSL), when compared to the respective surrounding urban areas. The average difference of GSL between urban and rural areas over all vegetation types, considered in this study, is about 9 days. Also, the extended GSL in urban area is consistent among different climate zones in the United States, whereas their magnitudes are varying across regions. We found that a tenfold increase in urban size could result in an earlier SOS of about 1.3 days and a later EOS of around 2.4 days. As a result, the GSL could be extended by approximately 3.6 days with a range of 1.6-6.5 days for 25th ~ 75th quantiles, with a median value of about 2.1 days. For different vegetation types, the phenology response to urbanization, as defined by GSL, ranges from 1 to 4 days. The quantitative relationship between phenology and urbanization is of great use for developing improved models of vegetation phenology dynamics under future urbanization, and for developing change indicators to assess the impacts of urbanization on vegetation phenology.

Fine-Tuned Gene Expression Elements from Hybrid Promoter Libraries in Pichia pastoris.

As a desirable microbial cell factory, Pichia pastoris has garnered extensive utilization in metabolic engineering. Nevertheless, the lack of fine-tuned gene expression components has significantly constrained the potential scope of applications. Here, a gradient strength promoter library was constructed by random hybridization and high-throughput screening. The hybrid promoter, phy47, performed best with 2.93-fold higher GFP expression levels than GAP. The broad applicability of the novel hybrid promoter variants in biotechnological production was further validated in the biosynthesis of pinene and rHuPH20 with higher titers. The upstream regulatory sequences (UASE and URSD) were identified and applied to promoters GAP and ENO1, resulting in a 34 and 43% increase and an 18 and 37% decrease in the expression level, respectively. Yeast one-hybrid analysis showed that transcription factor HAP2 activates the hybrid promoter through a direct interaction with the crucial regulatory region UASH. Furthermore, a short segment of tunable activation sequence (20 bp) was also screened, and artificial promoters were constructed in tandem with the addition of regulatory sequence, resulting in a 61% expansion of the expression range. This study provides a molecular tool and regulatory elements for further synthetic biology research in P. pastoris.

The effect of the interaction of sleep onset latency and age on ischemic stroke severity via inflammatory chemokines.

Objective: Prolonged sleep onset latency (PSOL) and age have been linked to ischemic stroke (IS) severity and the production of chemokines and inflammation, both of which contribute to IS development. This study aimed to explore the relationship between chemokines, inflammation, and the interplay between sleep onset latency (SOL) and age in influencing stroke severity. Methods: A cohort of 281 participants with mild to moderate IS was enrolled. Stroke severity was assessed using the National Institutes of Health Stroke Scale (NIHSS), and SOL was recorded. Serum levels of macrophage inflammatory protein-1alpha (MIP-1α), macrophage inflammatory protein-1beta (MIP-1ß), monocyte chemoattractant protein-1 (MCP-1), interleukin-6 (IL-6), and tumor necrosis factor-alpha (TNF-α) were measured. Results: NIHSS scores of middle-aged participants with PSOL were significantly higher than those with normal sleep onset latency (NSOL) (p = 0.046). This difference was also observed when compared to both the elderly with NSOL (p = 0.022), and PSOL (p < 0.001). Among middle-aged adults with PSOL, MIP-1ß exhibited a protective effect on NIHSS scores (ß = -0.01, t = -2.11, p = 0.039, R2 = 0.13). MIP-1α demonstrated a protective effect on NIHSS scores in the elderly with NSOL (ß = -0.03, t = -2.27, p = 0.027, R2 = 0.12). Conclusion: This study reveals a hitherto undocumented association between PSOL and IS severity, along with the potential protective effects of MIP-1ß in mitigating stroke severity, especially among middle-aged patients.

Spatially explicit downscaling and projection of population in mainland China.

Spatially explicit population data is critical to investigating human-nature interactions, identifying at-risk populations, and informing sustainable management and policy decisions. Most long-term global population data have three main limitations: 1) they were estimated with simple scaling or trend extrapolation methods which are not able to capture detailed population variation spatially and temporally; 2) the rate of urbanization and the spatial patterns of settlement changes were not fully considered; and 3) the spatial resolution is generally coarse. To address these limitations, we proposed a framework for large-scale spatially explicit downscaling of populations from census data and projecting future population distributions under different Shared Socio-economic Pathways (SSP) scenarios with the consideration of distinctive changes in urban extent. We downscaled urban and rural population separately and considered urban spatial sprawl in downscaling and projection. Treating urban and rural populations as distinct but interconnected entities, we constructed a random forest model to downscale historical populations and designed a gravity-based population potential model to project future population changes at the grid level. This work built a new capacity for understanding spatially explicit demographic change with a combination of temporal, spatial, and SSP scenario dimensions, paving the way for cross-disciplinary studies on long-term socio-environmental interactions.

Genome-wide identification of SIMILAR to RCD ONE (SRO) gene family in rapeseed (Brassica napus L.) reveals their role in drought stress response.

Rapeseed (Brassica napus L.) is an important oilseed crop widely cultivated worldwide, and drought is the main environmental factor limiting its yield enhancement and the expansion of planted areas. SIMILAR TO RCD ONE (SRO) is a plant-specific small gene family that plays a crucial role in plant growth, development, and responses to abiotic stresses such as drought. However, the functional role of SROs in rapeseed remains poorly understood. In this study, 19 BnaSROs were identified from the rapeseed genome, with 9, 10, 10, 18, and 20 members identified from the genomes of Brassica rapa, Brassica nigra, Brassica oleracea, Brassica juncea, and Brassica carinata, respectively. We then analyzed their sequence characteristics, phylogenetic relationships, gene structures, and conserved domains, and explored the collinearity relationships of the SRO members in Brassica napus and Brassica juncea. Next, we focused on the analysis of tissue expression and stress-responsive expression patterns of rapeseed SRO members and examined their expression profiles under ABA, MeJA and water-deficit drought treatments using qPCR. Transcriptome data analysis and qPCR detection indicated that BnaSROs exhibit multiple stress-responsive expression patterns. BnaSRO1 and BnaSRO11, which are likely to function through interactions with NAC transcription factors, were screened as major drought-regulated members. Our results provide a solid foundation for functional analysis of the role of the SRO gene family in abiotic stress responses, especially drought stress responses, in rapeseed.

Enhancing vegetation formation classification: Integrating coarse-scale traditional mapping knowledge and advanced machine learning.

Mapping vegetation formation types in large areas is crucial for ecological and environmental studies. However, this is still challenging to distinguish similar vegetation formation types using existing predictive vegetation mapping methods, based on commonly used environmental variables and remote sensing spectral data, especially when there are not enough training samples. To solve this issue, we proposed a predictive vegetation mapping method by integrating an advanced machine learning algorithm and knowledge in an early coarse-scale vegetation map (VMK). First, we implemented classification using the random forest algorithm by integrating the early vegetation map as an auxiliary feature (VMF). Then, we determined the rationality of classified vegetation types and distinguished the confusing types, respectively, based on the knowledge of the spatial distributions and hierarchies of vegetation. Finally, we replaced each recognized unreasonable vegetation type with its corresponding reasonable vegetation type. We implemented the new method in upstream of the Yellow River based on GaoFen-1 satellite images and other environmental variables (i.e., topographical and climate variables). Results showed that the overall accuracy using the VMK method ranged from 67.7 % to 76.8 %, which was 10.9 % to 13.4 % and 3.2 % to 6.6 %, respectively, higher than that of the method without the early vegetation map (NVM) and the VMF method, based on cross-validation with 20 % to 60 % random training samples. The spatial details of the vegetation map using the VMK method were also more reasonable compared to the NVM and VMF methods. These results indicated that the VMK method can distinctly improve the mapping accuracy at the vegetation formation level by integrating knowledge of existing vegetation maps. The proposed method can largely reduce the requirements on the number of field samples, which is especially important for alpine mountains and arctic region, where collecting training samples is more difficult due to the harsh natural environment.

Thermal, water, and land cover factors led to contrasting urban and rural vegetation resilience to extreme hot months.

With continuing global warming and urbanization, it is increasingly important to understand the resilience of urban vegetation to extreme high temperatures, but few studies have examined urban vegetation at large scale or both concurrent and delayed responses. In this study, we performed an urban-rural comparison using the Enhanced Vegetation Index and months that exceed the historical 90th percentile in mean temperature (referred to as "hot months") across 85 major cities in the contiguous United States. We found that hot months initially enhanced vegetation greenness but could cause a decline afterwards, especially for persistent (≥4 months) and intense (≥+2 °C) episodes in summer. The urban responses were more positive than rural in the western United States or in winter, but more negative during spring-autumn in the eastern United States. The east-west difference can be attributed to the higher optimal growth temperatures and lower water stress levels of the western urban vegetation than the rural. The urban responses also had smaller magnitudes than the rural responses, especially in deciduous forest biomes, and least in evergreen forest biomes. Within each biome, analysis at 1 km pixel level showed that impervious fraction and vegetation cover, local urban heat island intensity, and water stress were the key drivers of urban-rural differences. These findings advance our understanding of how prolonged exposure to warm extremes, particularly within urban environments, affects vegetation greenness and vitality. Urban planners and ecosystem managers should prioritize the long and intense events and the key drivers in fostering urban vegetation resilience to heat waves.