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The construction of National Industrial Relocation Demonstration Zones (NIRDZ) is important for China's industrial transfer, but its environmental influence cannot be neglected. This study explores the environmental effects of industrial transfers by studying China's NIRDZ. By employing panel data of 284 cities in China between 2005 and 2019, we compare environmental quality changes over time in areas with and without demonstration zones based on the staggered difference-in-differences (DD) technique. The results demonstrate a 0.032 increase in the environmental quality level of industrial receivers after the implementation of demonstration zones. The effect of demonstration zones on environmental improvement is moderated by natural resources, capital accumulation, and technological innovation capabilities. This impact is more fully realized in cities with resource-based, low-capital accumulation, and high-tech innovation but is not statistically significant difference at various levels of human resources. The environmental improvement effect of the NIRDZ is powerful in central cities and small- and medium-sized cities instead of western regions and large-scale cities. Additionally, mediation analysis is adopted to assess the potential mechanism between the association of NIRDZ and the environment. The demonstration area negatively affects environmental quality through the economic scale effect while improving environmental quality through the technological innovation effect. We provide empirical evidence that the NIRDZ is positively correlated with the environment and identify the technology effect as one underlying driver of this correlation to help developing countries address its detrimental impacts., (© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

The environment is the foundation for human existence, and the digital economy has exacerbated the impact of human beings on the environment. Based on data of 31 provinces in China from 2011 to 2020, we used the spatial Durbin model to research the impact of the digital economy on the environment and its spatiotemporal characteristics. We found that the digital economy has a significant positive impact on the environmental effects of the region, and also has a positive spatial overflow. This conclusion still holds after robustness test and endogenous treatment (changing the space weight matrix, applying the instrumental variables, and two-stage least-squares method). Second, we found that environmental effects of the digital economy have a time lag, and the lag decreases gradually over time. Third, we used geographically and temporally weighted regression model and K-means clustering, which shows that digital economy has a strong effect on the environment in western region. The western region may need to increase digital infrastructure construction to achieve better environmental effects. In addition, China needs to upgrade its industrial structure as soon as possible, accelerate technological innovation, and advocate a green lifestyle, so as to realize the coordinated development of human beings and nature., (© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Improving carbon productivity is an important measure to promote low-carbon development. Since high-speed rail (HSR) has both economic and environmental effects, it is particularly important to clarify the relationship between HSR development and carbon productivity. In this paper, 285 cities in China from 2007 to 2017 are used as a research sample, and the relationship between the opening of HSR and the city's carbon productivity is studied using the spatial difference-in-difference method (SDID). The result shows that due to the intermediary effect of technological innovation and industrial structure, the opening of HSR significantly increases urban carbon productivity. At the same time, this influence has a significant positive spatial spillover effect. On average, when a city opens HSR, the local carbon productivity increases by 5.18%, and the carbon productivity of its neighboring cities increases by 13.52%. Overall, the positive effect of HSR on carbon productivity is more pronounced in the middle and western regions. However, the spatial spillover effect in the eastern region is significantly negative. These findings help to accurately assess the social benefits of HSR network expansion and provide important decision-making references for climate governance in the HSR era., (© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Exploring the spatiotemporal variations of vegetation net primary productivity (NPP) and analyzing the relationships between NPP and its influencing factors are vital for ecological protection in the Beijing-Tianjin-Hebei (BTH) region. In this study, we employed the CASA model in conjunction with spatiotemporal analysis techniques to estimate and analyze the spatiotemporal variations of NPP in BTH and different ecological function sub-regions over the past two decades. Subsequently, we established three scenarios (actual, climate-driven and land cover-driven) to assess the influencing factors and quantify their relative contributions. The results indicated that the overall NPP in BTH exhibited a discernible upward trend from 2000 to 2020, with a growth rate of 3.83 gC·m -2 a -1 . Furthermore, all six sub-regions exhibited an increase. The Bashang Plateau Ecological Protection Zone (BP) exhibited the highest growth rate (5.03 gC·m -2 a -1 ), while the Low Plains Ecological Restoration Zone (LP) exhibited the lowest (2.07 gC·m -2 a -1 ). Geographically, the stability of NPP exhibited a spatial pattern of gradual increase from west to east. Climate and land cover changes collectively increased NPP by 0.04 TgC·a -1 and 0.07 TgC·a -1 , respectively, in the BTH region. Climate factors were found to have the greatest influence on NPP variations, contributing 40.49% across the BTH region. This influence exhibited a decreasing trend from northwest to southeast, with precipitation identified as the most influential climatic factor compared to temperature and solar radiation. Land cover change has profound effects on ecosystems, which is an important factor on NPP. From 2000 to 2020, 15.45% area of the BTH region underwent land cover type change, resulting in a total increase in NPP of 1.33 TgC. The conversion of grass into forest brought about the 0.89 TgC increase in NPP, which is the largest of all change types. In the area where land cover had undergone change, the land cover factor has been found to be the dominant factor influencing variations in NPP, with an average contribution of 49.37%. In contrast, in the south-central area where there has been no change in land cover, the residual factor has been identified as the most influential factor influencing variations in NPP. Our study highlights the important role of land cover change in influencing NPP variations in BTH. It also offers a novel approach to elucidating the influences of diverse factors on NPP, which is crucial for the scientific assessment of vegetation productivity and carbon sequestration capacity., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Understanding the spatial variability of ecosystem functions is an important step forward in predicting changes in ecosystems under global transformations. Plant functional traits are important drivers of ecosystem functions such as net primary productivity (NPP). Although trait-based approaches have advanced rapidly, the extent to which specific plant functional traits are linked to the spatial diversity of NPP at a regional scale remains uncertain. Here, we used structural equation models (SEMs) to disentangle the relative effects of abiotic variables (i.e., climate, soil, nitrogen deposition, and human footprint) and biotic variables (i.e., plant functional traits and community structure) on the spatial variation of NPP across China and its eight biomes. Additionally, we investigated the indirect influence of climate and soil on the spatial variation of NPP by directly affecting plant functional traits. Abiotic and biotic variables collectively explained 62.6 % of the spatial differences of NPP within China, and 28.0 %-69.4 % across the eight distinct biomes. The most important abiotic factors, temperature and precipitation, had positive effects for NPP spatial variation. Interestingly, plant functional traits associated with the size of plant organs (i.e., plant height, leaf area, seed mass, and wood density) were the primary biotic drivers, and their positive effects were independent of biome type. Incorporating plant functional traits improved predictions of NPP by 6.7 %-50.2 %, except for the alpine tundra on the Qinghai-Tibet Plateau. Our study identifies the principal factors regulating NPP spatial variation and highlights the importance of plant size traits in predictions of NPP variation at a large scale. These results provide new insights for involving plant size traits in carbon process models., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

China has implemented extensive ecological engineering projects (EEPs) during recent decades to restore and enhance ecosystem functioning. However, the effectiveness of these interventions can vary due to factors such as local climate and specific project objectives. Here, we used two independent satellite remote sensing datasets, including the Global Inventory Monitoring and Modeling System (GIMMS) Normalized Difference Vegetation Index (NDVI) and vegetation optical depth from Ku-band (Ku-VOD), to investigate the vegetation trends in two hotspot regions of EEPs characterized by different climate conditions, i.e., the xeric/semi-xeric Loess Plateau and mesic southwest China. We found diverging vegetation greenness/biomass trend shift patterns in these two regions as a result of the combined effects of EEPs and climate variations, as indicated by changes in the Standardized Precipitation Evapotranspiration Index (SPEI). In the Loess Plateau, where no significant climate variations were observed, NDVI/Ku-VOD increased continuously after the implementation of key EEPs in 2000. Conversely, southwest China has experienced persistent drying since 2000, and vegetation greenness/biomass showed an increasing trend during the initial stages of ecological engineering implementation but subsequently reversed towards a decline due to the continued dry climatic conditions. We used the residual trend method to separate the influence of EEPs from climate variations on vegetation trends and found a positive effect of the ecological management practices in the Loess Plateau, yet a predominantly negative effect in the southwest China region, which means that projects implemented in southwest China did not lead to a long-term improvement in vegetation growth under the given climate conditions in southwest China. This adverse impact suggests that ecological engineering practices could potentially increase the ecosystem's vulnerability to droughts, owing to the increased transpirational water demands introduced by ecological engineering interventions. Our study highlights the importance of considering the expected occurrence and magnitude of climatic variability when implementing large-scale EEPs., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Nowadays, frequent climate extremes exert a serious impact on agricultural production and social development, which is seldom studied in the previous literature. Production–Living–Ecological (PLE) is a useful analysis framework, and China is a suitable model for such study. This paper takes the Huai River Eco-Economic Belt (HREB), an important agricultural zone in China, to study the relationship among agricultural production (P), society (L), and climate change (E), which is referred to as APLE. This paper constructs a coupled coordination evaluation index system for the APLE system and uses coupling coordination degree models and geographic detector to study the spatial and temporal evolution of the coordinated development of 34 counties (cities) in the HREB from 2009 to 2018. The results show the following: (1) The development of the agricultural subsystem and the social subsystem formed a "scissors difference" from 2009 to 2014, and the three subsystems showed a slight upward trend during 2014–2018. (2) The coupling and coordinated development of the APLE system in the HREB was generally stable, and the coupling coordination degree was improved from low-grade and slightly uncoordinated to barely and primarily coordinated. Furthermore, the spatial differentiation of the coupling coordination degree shows a clear pattern of being high in the southeast and low in the northwest. (3) The main influencing factors are the drought and flood protection rate, the effective irrigation rate, the per capita electricity consumption in agriculture, the number of beds in healthcare facilities per 10,000 people, the per capita disposable income of urban residents, the annual average temperature, and the annual precipitation. (4) The spatial–temporal evolution of the coupling and coordinated development of the APLE system is the result of the comprehensive effect of internal driving forces such as food security, the consumption level of rural residents, and the development level of urbanization construction, and external driving forces such as government public welfare and natural conditions. [ABSTRACT FROM AUTHOR]

With global warming, cities are vulnerable to extreme weather, increasing the climate risk to cities worldwide. Although existing literature has examined the ex-post impacts of extreme weather, it is less clear how climate risk affects cites before extreme weather occur. To lower the risk of urban waterlogging, which is caused by extreme weather, and improve the ability of cities to adapt to extreme weather, China launched the Sponge City Project (SCP) in 2013 to manage the urban stormwater and waterlogging. Adopting the SCP pilot in China as a quasi-natural experiment, we examine the impact of the climate risk caused by urban stormwater and waterlogging on the house price with the difference-in-differences (DID) method. We find that after implementing the SCP pilot program, the house price in pilot cities increased significantly because of the improvement in cities' resilience to climate risk. Additionally, this effect was only demonstrated in cities with a high waterlogging risk. For SCP pilot cities with lower waterlogging risk, the house price is not significantly affected by SCP implementation. This indicates that the house price in China is sensitive to the climate risk caused by the urban stormwater and waterlogging. Our findings also contribute to the understanding of the significance of the climate risk management, and provided theoretical evidence for urban governance., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

The implementation of the Environmental Tax Law is a milestone in promoting China's green tax reform. However, the existence literature has lacked attention to whether it leads enterprises to invest in green environmental protection. To examine the Environmental Tax Law effects and mechanism on the environmental investment of heavy-polluted enterprises, this study used the data of heavy-polluted enterprises listed on the A-share market from 2012 to 2020 and regarded the Environmental Tax Law as a quasi-natural experiment to employ a difference-in-differences model. We found that environmental tax improves the green environmental investment of heavy-polluted enterprises, reflecting the guiding role of policy on enterprise investment allocation. Heterogeneity was found, and the promotion effect of environmental tax reform on enterprise environmental investment is more significant in non-nation-owned, central-western regions, and small-scale enterprises. Further analysis believed that market competition, as an external mechanism, helps strengthen environmental tax reform's implementation effect. The findings of this paper provide a new proof for a comprehensive understanding of the micro-effect of environmental tax reform and provide a reference for the implementation of green development strategies., (© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Achieving the ambitious Global Methane Pledge announced in the Glasgow Climate Pact requires collaborative efforts from both the signatory countries and China which serves as the world's largest emitter. Considering the heterogeneity of economic structures within China and the relocation of emissions between regions via the global economic network, it is vital to investigate how China's methane emissions at the subnational level are linked to global final consumption. In this paper, we mapped global methane footprint in China from 2007 to2015 at the subnational level, by nesting China's interprovincial input-output tables into global multiregional input-output accounts and upscaling grid-level methane emission data of the Edgar database to the provincial level. Our results suggested that global methane footprint in China shifted westward, and the United States, European Union, Japan, and Hong Kong were the main drivers of China's local methane emissions. By illustrating the international and interprovincial trade flows of methane emissions, this study demonstrated that southeast coastal provinces were the hotspots for global methane footprint while middle inland provinces were the emission hotspots for China's domestic demands. We also showed how China's methane emissions were distributed through the nested global economic network to different economic agents. Moreover, emission trends of key exporting sectors for China's eight economic zones were detailed discussed. The outcome of this study may be fully supportive for identifying the heterogeneous effects of global methane footprint in China and implicative for interprovincial and international collaborations towards methane emission mitigation., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Against the backdrop of low-carbon development, it is imperative to cultivate a modernized industrial system and new development model. Industrial collaborative agglomeration (ICA) between manufacturing and producer services may offer an opportunity to aid carbon reduction in this scenario. Using balanced panel data of China's 30 provinces and municipalities from 2008 to 2019, this paper attempts to investigate the influences of ICA on carbon emission efficiency (CEE), its heterogeneous effects, impact mechanisms, and spillover effects. Our main findings can be concluded as follows: (1) There is a U-shaped relationship between ICA and CEE; namely, ICA will inhibit first and then promote CEE. (2) The heterogeneity results further indicate that this U-shaped relationship is significant in the eastern area while there exists an inverted U-shaped relationship between ICA and CEE in the western area; however, the influence of ICA on CEE is not significant in the central area. (3) More deeply, the mechanism identification uncovers that industrial structure upgrading and green technological innovation are important channels through which ICA affects CEE. (4) Importantly, we unfold that ICA in the local area has spatial spillover effects; namely, it will influence CEE in neighboring areas, which also presents a U-shaped relationship. These findings provide not only new insights into understanding the environmental effects of ICA but also helpful inspiration for regional policymakers to scientifically formulate industrial development policies and effectively implement carbon emission control actions., (© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Under the increasingly severe environmental constraints, improving environmental total factor productivity (ETFP) is the fundamental way for the sustainable development of heavily polluting enterprises. Based on 3463 panel data of A-share listed companies in China from 2011 to 2019, this paper employs Porter's hypothesis (PH) framework to explore the impact of environmental tax (EN_T) on enterprise innovation and environmental total factor productivity for the heavily polluting manufacturing industry using the propensity score matching (PSM) method. The empirical results show the following. (i) Environmental taxes positively affect enterprise innovation (EI) and environmental total factor productivity (ETFP). (ii) Mechanism analysis verifies a partial mediating effect for EI between EN_T and ETFP. (iii) Regional heterogeneity analysis illustrates the differences in the impact of environmental taxes on innovation quality. (iv) Individual heterogeneity analysis shows that the "strong Porter hypothesis" is only valid for large-scale enterprises. The results are of great importance for both government and enterprises to improve the EN_T system and optimize the allocation of resources in realistic practice., (© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Nowadays, population ageing is a common social phenomenon that occurs worldwide. Rapid ageing may have profound socioeconomic impacts, and thus it may influence effects of climate policy. Nevertheless, very few previous researchers have evaluated climate policy in an ageing society. In this paper, we attempt to narrow the research gap by incorporating ageing impact in climate policy evaluation. Specifically, we have modeled ageing impacts on labor supply, household electricity consumption, and health expenditure. The core of the research framework in this paper is a dynamic recursive Computable General Equilibrium (CGE) model. The model results show that population ageing tends to decrease private health expenditure but increase governmental health expenditure. In contrast, Emission Trading Scheme (ETS) decreases both private and governmental health expenditure. Both population ageing and ETS decrease labor employment, employment rate, GDP, and carbon emissions. The results imply that population ageing lays heavy burdens on social healthcare system, whilst climate policy reduces governmental health expenditure. In ageing societies, mitigation targets can be achieved less costly and more easily through implementing ETS., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier B.V. All rights reserved.)

Many studies quantify the impact of climate change and human activities on runoff changes on an annual scale, but few studies have examined this on multiple time scales. This paper quantifies the contribution of different factors to the variability of Jinsha River runoff at multiple time scales (annual, seasonal and monthly). First, the trend analysis of Jinsha River runoff is carried out, and the Mann–Kendall mutation test was then applied to the runoff data for mutation analysis. According to the mutation year, the research period is divided into the base period and the mutation period. By constructing an ABCD hydrological model simulation and monthly scale Budyko model, the contribution rate of human and climate factors to the multitime-scale runoff of Jinsha River is calculated. The results showed that: (1) The sudden year of change in the Jinsha River runoff is 1978, and the Nash coefficients of the ABCD hydrological model in the base period and sudden change period were 0.85 and 0.86, respectively. (2) Climate factors were the dominant factor affecting annual runoff changes (98.62%), while human factors were the secondary factor affecting annual runoff changes (1.38%). (3) The contribution rates of climate factors in spring, summer, autumn, and winter to runoff were 91.68%, 74.08%, 95.30%, and 96.15%, respectively. The contribution rates of human factors in spring, summer, autumn, and winter to runoff were 8.32%, 25.92%, 4.70%, and 3.85%, respectively. (4) The contribution rates of climate factors to runoff in May, June, and July were 95.14%, 102.15%, and 87.79%, respectively. The contribution rates of human factors to runoff in May, June, and July were 4.86%, −2.15%, and 12.21%, respectively. [ABSTRACT FROM AUTHOR]

Leaf phenology is one of the most reliable indicators of global warming in temperate regions because it is highly sensitive to temperatures. Temperature sensitivity (S T ) is defined as the values of changed days of leaf flushing date (LUD) per degree increase in temperatures. Climate warming substantially advanced LUD in the temperate region, but its effect on S T of LUD is still not clear. We used spring phenological records of 12 woody plants in eastern China in the years of 1983-2014 to explore temporal and spatial changes of LUD and S T . Furthermore, we compared the difference of S T and preseason temperatures in two periods (1983-1997 and 2000-2014), and explored the main factors regulating S T . The results showed that the average LUD significantly advanced (-2.7 days per decade). The mean LUD over the period 1983-2014 was in day of the year (DOY) 87 ± 7 across sites and species for the early leaf flushing species (EFS), and mean DOY 102 ± 5 for the late leaf flushing species (LFS). LUD was earlier in low latitude than that in high latitude. S T of Armeniaca vulgaris was the most sensitive to temperature across all sites (-3.66 d °C -1 ), while Firmiana simplex was the most insensitive (-2.37 d °C -1 ). LUD of EFS was more sensitive to temperature warming than that of LFS. At the same site, LUD of EFS would advance more obviously than that of LFS under global warming. For all species, S T decreased significantly with shorter preseason length and warmer temperatures at the preseason end. Our results had demonstrated a strong relationship between S T and the preseason length (mean temperature at the preseason end)., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier B.V. All rights reserved.)

Revegetation has been conducted extensively to restore degraded ecosystems, thereby accelerating water consumption and affecting water availability for other human demands. Examining evapotranspiration (ET) can guide regional management to promote revegetation sustainability and address the contradiction in water demand. We characterised ET variation on China's Loess Plateau from 2003 to 2013, after the 'Grain for Green' revegetation programme implementation. Annual ET significantly increased, with an average trend of 4.87 mm yr -2 ; the highest increasing trends were in the southern part of the plateau. Combining zero-order correlation and partial correlation, we found that climate and crop production were the key factors influencing ET, while revegetation also had significant effects. We also explored how multiple influencing factors affected ET through partial least-squares path modelling. Revegetation and socioeconomic development were found to impose indirect effects on ET by promoting rural household income and altering agricultural production. The specified linkages and regulating pathways among revegetation and human needs including socioeconomic development and agricultural production should be considered in solving the conflicts between the ecosystem and human water use in water-limited regions., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier Ltd. All rights reserved.)

Optimizing the vertical environmental regulation (VER) effect of the central government and reducing the negative execution motivation of local governments have become the priority points to accelerate the green development of China. Based on the spatial Durbin model, this paper not only examines the influence of VER on green development efficiency (GDE), but also discusses the moderating effect of politically and economically motivated pollution dividend (PPD and EPD) on the relationship between them. The research results are as follows: (1) VER has a U-shaped effect on local GDE, the green governance effect of which began to appear when VER was higher than 1.561. VER has an inverted N-shaped effect on adjacent GDE. When the VER intensity lies in (0.138, 3.012), it has a positive spatial spillover effect. (2) PPD weakens the local green governance effect of VER, while EPD positively moderates it. Both of them have no significant moderating effect on it in neighboring areas. (3) Cross-regional cooperative governance moderates the short-term weakness and pollution transfer of VER, and generally facilitates the positive moderating effect of PPD and EPD. In China's two major economic belts, VER, PPD and EPD also have different performances. This study proves the important influence of local inter-governmental competition and promotion tournament on the central environmental regulation for the first time, which is of great significance for optimizing the top-level design of the central government and implementing the governance responsibility of local governments., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Du, Pan, Meng, Wang and Ren.)

Background: Although many studies have reported the mortality effect of temperature, there were few studies on the mortality risk of humidity, let alone the joint effect of temperature and humidity. This study aimed to investigate the joint and interaction effect of high temperature and relative humidity on mortality in China, which will deepen understanding the health risk of mixture climate exposure., Methods: The mortality and meteorological data were collected from 353 locations in China (2013-2017 in Jilin, Hunan, Guangdong and Yunnan provinces, 2009-2017 in Zhejiang province, and 2006-2011 in other Provinces). We defined location-specific daily mean temperature ≥ 75th percentile of distribution as high temperature, while minimum mortality relative humidity as the threshold of high relative humidity. A time-series model with a distributed lag non-linear model was first employed to estimate the location-specific associations between humid-hot events and mortality, then we conducted meta-analysis to pool the mortality effect of humid-hot events. Finally, an additive interaction model was used to examine the interactive effect between high temperature and relative humidity., Results: The excess rate (ER) of non-accidental mortality attributed to dry-hot events was 10.18% (95% confidence interval (CI): 8.93%, 11.45%), which was higher than that of wet-hot events (ER = 3.21%, 95% CI: 0.59%, 5.89%). The attributable fraction (AF) of mortality attributed to dry-hot events was 10.00% (95% CI: 9.50%, 10.72%) with higher burden for females, older people, central China, cardiovascular diseases and urban city. While for wet-hot events, AF was much lower (3.31%, 95% CI: 2.60%, 4.30%). We also found that high temperature and low relative humidity had synergistic additive interaction on mortality risk., Conclusion: Dry-hot events may have a higher risk of mortality than wet-hot events, and the joint effect of high temperature and low relative humidity may be greater than the sum of their individual effects., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Improving the environment and optimizing industrial structure are the primary tasks of resource-based cities in western China. This paper analyzes the impact mechanism and path of environmental effect on the industrial structure using the panel data of 37 prefecture-level resource-based cities in western China from 2008 to 2019. The results show that the environmental effect is beneficial for optimizing the industrial structure of resource-based cities in western China. The economic development and resource endowment amplify the positive impact of the environmental effect on industrial structure upgrades. In resource-based cities with different growth cycles, environmental effect has different impact on industrial structure upgrades. Technological innovation of enterprises and public awareness of environmental protection are effective paths for environmental effect to promote industrial structure upgrading. Therefore, it is really crucial to promote environmental protection, identify regional characteristics, and enhance departmental cooperation for resource-based cities in western China, realizing industrial structure upgrades and sustainable economic development., (© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Under the "carbon peaking and carbon neutrality goals", China's commercial banks are facing a severe climate transition risk. This paper proposes a climate transition risk measurement method for commercial banks, and investigates the impact of climate transition risk on bank performance based on the data of 490 commercial banks in China from 2008 to 2019. The empirical findings are as follows: firstly, the climate transition risk has an inhibitory effect on the performance of commercial banks, and the inhibitory effect weakens with the increase of bank size. Secondly, the signing of the Paris Agreement and the increase of the economic policy uncertainty in China have a positive moderating effect, which weakens the inhibitory effect of the climate transition risk. Finally, the climate transition risk inhibits the performance of commercial banks partly by reducing the scale of bank loans., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier Ltd. All rights reserved.)

The climate aridity since the mid-20th century has raised concerns about water resources on the Chinese Loess Plateau (CLP). A lack of extended observation-like precipitation records for the eastern CLP (ECLP) means that it remains unclear whether or not the current arid state of the CLP is unprecedented, and the spatial-temporal characteristics of hydroclimatic variability across the CLP over past centuries are not well understood. Here we present a regional hydrological-year precipitation reconstruction for the Heichashan Mountains, which successfully captures hydroclimate changes on the ECLP since 1773 CE. The reconstruction explains 48.72 % of the observed variance for 1957-2019 CE and reveals a wetting trend since the early 2000s and shows 2014-2020 CE to have been the second wettest period over the past 248 years. 1910-1932 CE was the longest and driest period over the past centuries. Furthermore, the 19th century was relatively wet, whereas the 20th century was dry. We demonstrate that droughts tend to occur in warm periods. Combining our new reconstruction with previously published hydroclimatic reconstructions, we find that hydroclimate has changed synchronously on the ECLP and the western CLP (WCLP) for most of the past two centuries. Some regional differences do exist, for example in the 1890s-1920s, when aridity gradually intensified across the ECLP, no similar drying is evident in records for the WCLP, although the 1920s megadrought occurred in both the ECLP and WCLP. Another difference is in the onset of the 20th-century aridity, which began in the 1950s on the ECLP, around 20 years later than it began on the WCLP. In addition to the known influences of the Asian Summer Monsoon and related large-scale circulations, this work highlights a major finding that the 1920s megadrought may be related to a regime shift in Northern Hemisphere temperature., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier B.V. All rights reserved.)

The social cost of carbon is a tool for assessing the appropriateness of emission reduction measures and climate policy, and is affected by socioeconomic and climatic factors. This study aimed to explore the impact of socioeconomic factors and climate on the social cost of carbon; to this end, this study considered Chinese provinces as the focus of research. This study constructed an integrated framework for carbon emissions considering socioeconomic and climatic factors, which consisted of shared socioeconomic pathways (SSPs) and representative concentration pathways (RCPs). Subsequently, social cost of the carbon estimation model was used to calculate the social cost of carbon for China's provinces from 2022 to 2100 under different carbon emission scenarios. The results show that: under most carbon emission scenarios, provinces with a high social cost of carbon are located in the eastern developed region. For instance, Jiangsu and Guangdong had the highest values of 6.31 $/tC. Second, SSPs that are highly dependent on fossil fuels have a high social cost of carbon, which is higher than 60 $/tC in 2022 in China. The social cost of carbon under other SSPs is at a fluctuating value of 40 $/tC. Third, in terms of RCPs, the social cost of carbon for the middle baseline emission scenario (RCP6.0) is considerably lower than that for the high baseline emission scenario (RCP8.0), and the difference between them is 3.7 times that of two medium emission scenarios (RCP6.0 and RCP4.5). Fourth, there is a substantial difference between the dynamic and fixed discount rates in the social cost of carbon in the same scenario. Studying the impact of socioeconomic and climatic factors on the social cost of carbon will help in its regulation and provide a scientific basis for Chinese provinces to optimize climate policies and emission reduction measures., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier Ltd. All rights reserved.)

Extreme climate-induced vegetation greenness decline significantly affects the stability of ecosystem function. Extreme climate events have occurred frequently in the recent 20 years and the possibility of climate anomalies is forecasted to increase in the future. But currently, the spatial and temporal response of episodic local vegetation decline to climate extremes at a global scale are still unclear. In this study, the detrend NDVI data was utilized as the indicator of vegetation growth, and a spatiotemporally contiguous recognition method was proposed to identify episodic large-scale vegetation decline events globally, subsequently, the spatiotemporal characteristics of these vegetation decline events and their interannual variation trends during 2000-2019 were explored. The results showed that (1) the spatiotemporally contiguous recognition method proposed by this paper was proven to be accurate in identifying the hotspot regions of large-scale vegetation decline. A total of 243 large-scale vegetation decline events were recognized globally during 2000-2019 drived by the method. (2) The global hotspots of large-scale vegetation decline were mainly distributed in the low-elevation areas at middle and low latitudes, especially at 15°S ~ 35°S, 15°N and 35°N, where covered north-western Africa, the Sahel, the Middle East, Central Asia, western India, the border of north-eastern China and Mongolia, western and south-central United States, northern Mexico, southern Africa, Australia, and southern and north-eastern South America. (3) Recent global episodic local vegetation decline has increased significantly since 2000, at the rate of 180,000 km 2 of vegetation decline areas increasing per year. Particular, the severity of vegetation decline grew significantly since 2010 at the regions where covered the latitudes of approximately 15°N, 30°N and 65°N. Additionally, the severity of vegetation decline ranging from 20°S to 30°S weakened significantly since 2010. These findings were expected to provide the valuable scientific understanding for global vegetation decline and ecosystem responses to frequent climate extremes., Competing Interests: Declaration of competing interest All authors declare that No conflict of interest exists., (Copyright © 2022. Published by Elsevier B.V.)

This paper estimates the impact of destination cities' temperature on the migration intentions of highly educated talents. Using a unique manually collected dataset of applicants for the Unified National Graduate Entrance Examination (UNGEE) of double first-class universities in China, we find that both hot (over 25 °C) and cold (below 5 °C) days in the previous 3 months before the registration date significantly decrease the number of applicants for the UNGEE of double first-class universities, relative to a moderate (20-25 °C) day. Heterogeneity analysis shows that such effects differ by destination universities' quality and climate regions. We also find that destination cities' income level can mitigate the negative effects of hot days and cold days on the number of applicants. These findings add to the existent literature by examining an understudied relationship between temperature and migration intention.

The development of rural tourism (RT) has great significance in reducing poverty and achieving rural vitalization. Qinghai-Tibetan Plateau (QTP) is a depressed area with rich RT resources due to its unspoiled nature and diverse culture. For future sustainable development of RT in QTP, this paper analyzes the spatial distribution characteristics and its influencing factors of RT villages using various spatial analysis methods, such as nearest neighbor index, kernel density estimation, vector buffer analysis, and geographic detectors. The results show the following. First, the RT villages present an agglomeration distribution tendency dense in the southeast and spare in the northwest. The inter-county imbalance distribution feature is obvious and four relatively high-density zones have been formed. Second, the RT villages have significant positive spatial autocorrelation, and the area of cold spots is larger and of hot spots is smaller. Third, the RT villages are mainly distributed with favorable topographic and climate conditions, near the road and water, around the city, and close to tourism resources. Fourth, the spatial distribution is the result of multifactor interactions. Socio-economic and tourism resource are the dominant factor in the mechanism network. Fifth, based on the above conclusions this study provides scientific suggestions for the sustainable development of the RT industry.

Under the context of global warming, compound dry and hot events (CDHEs) will increase and bring serious losses to society and the economy. The projection of CDHEs is of great significance for policy-making and risk assessment. In this paper, two large ensemble simulations, CanESM2-LE and CESM-LE, are used to estimate the risk of extreme CDHEs under different warming scenarios in China. First, the biases of the model in the simulation of the temperature and precipitation over the China region are corrected, and the index of CDHEs is established based on a copula function. The results show that extreme CDHEs will occur more often in China with the increase in global warming and the more severe extreme CDHEs are, the greater the risk will be in the future with higher uncertainties. Events that would be attained once every 50 and 100 years in the current climate from CESM-LE (CAanESM2-LE) will be 1.2/1.6 (1.1/1.5) times and 1.3/2.3 (1.5/2.0) times more likely to occur in a 1.5°C/2.0°C warmer climate, respectively. Northwestern China will experience the greatest increase in the risk of extreme CDHEs. Extreme CDHEs expected once every 100 years in the current period over NW China are expected to occur approximately every 5 and 4 years under a 4.0°C warmer world in CanESM2-LE and CESM-LE, respectively., Competing Interests: The authors have declared that no competing interests exist.

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The public demand for urban green growth (UGG) varies greatly due to climate conditions, resource endowments, geographical location; thus, understanding the coupling relationship between public demand and government supply is important to optimize government investment. This paper aims to evaluate the coupling coordination of UGG between public demand and government supply. An index system consisting of six aspects, including environment, society, economy, population, production and life, was used to evaluate the government supply. Meanwhile, citizens' demand was measured by the satisfaction for the six aspects. The coupling coordination degree model (CCDM) was established to analyze the government supply and public demand for UGG, and it was tested in the case of Shandong Peninsula urban agglomeration in China. The results indicated that citizens of Shandong Peninsula are basically satisfied, and the satisfaction for the environment, population and life is higher than the average value. From 2015 to 2019, the government supply level shows a trend of rising first and then declining, of which environment has been always at a high level for the five years. The coupling coordination degree of UGG shows the supply and demand in different cities of urban agglomerations is unbalanced, and the overall value of the eastern coast is higher than that of the western inland area. Moreover, the concept of relative satisfaction was put forwards, which is of great significance for regional policy. To improve UGG for a city, determining optimization objectives base on their evaluation results of coupling coordination degree and relative satisfaction is important, as well as the possible external reasons for the low coupling coordination degree., (Copyright © 2021 Elsevier Ltd. All rights reserved.)

A pneumonia outbreak was primarily reported in the fall of 2019 in Wuhan, Hubei province, China, with the identity SARS-CoV-2, a novel coronavirus. It quickly grew from a local epidemic to a global pandemic and was declared a public health emergency by the WHO. A total of three prominent waves were identified across the globe, with a slight temporal variability as per the geographical locations, and has impacted several sectors which connect the world. By March 2022, the coronavirus had infected 444.12 million people and claimed 6.01 million human lives worldwide, and these numbers have not yet stabilized. Our paper enlightens readers on the seven strains of human coronaviruses, with special emphasis on the three severe deadliest outbreaks (SARS-2002, MERS-2012, and COVID-19). This work attempts a comprehensive understanding of the coronavirus and its impact on the possible sectors that link the world through the economic chain, climate conditions, SDGs, recycling of the event, and mitigations. There are many points that are raised by the authors in the possible sectors, which are emerging or are as yet unnoticed and thus have not been taken into consideration. This comprehension will leave sets of new challenges and opportunities for the researchers in various streams, especially in earth sciences. Science-integrated research may help to prevent upcoming disasters as a by-product of (existing) epidemics in the form of coronavirus. [ABSTRACT FROM AUTHOR]

As a special socio-ecosystem, urban sustainability has been challenged by frequent human activities and natural disasters. Including climate into the socio-ecosystem evaluation framework, this paper constructed the climate, eco-environmental, and socio-economic evaluation index, respectively, to evaluate the core cities' socio-ecology in China's three economic circles. An improved entropy-TOPSIS method was subsequently employed to identify the contribution made by each indicator of the compound system, and a modified ternary Coupling Coordination Degree (CCD) model was developed to probe into the CCD levels among the three systems during the study. The results showed that: (1) The climate system's composite scores were characterized by inter-annual fluctuation without a time trend. However, the system's risk increased, manifesting in an increased probability of extreme weather events, especially in Shanghai. (2) The eco-environmental system witnessed an enormous stride, rising above the level of socio-economic development after 2007. Besides, the gap between the eco-environment and the socio-economy was gradually enlarged since 2014. (3) The eco-environment made the most contribution to the CCD's improvement, meaning enhancing the eco-environmental performance was of paramount significance. The findings can help the government formulate more effective measures to balance climate, eco-environment, and socio-economy to achieve sustainable urban development. [ABSTRACT FROM AUTHOR]

In recent years, moisture buffering materials for interior finishing have received much attention for their ability to regulate indoor humidity passively. It is necessary to investigate the potential of such materials' moisture buffering performance before application because the effect is highly climate and material dependent. However, existing studies in China lack a comprehensive overview of the moisture buffering potential of different interior finishing materials throughout the large country with a wide spectrum of climates. This paper aims to outline the moisture buffering potential for office buildings in various climates in China through numerical methods. Specifically, simulations in 15 representative Chinese cities are conducted with five interior finishing materials under two heating, ventilation, and air conditioning (HVAC) scenarios. The results show that the moisture buffering materials hold a general potential to regulate indoor humidity conditions and reduce buildings' HVAC load. Such benefits are evident in the mild climate but weak in humid areas. The moisture buffering effect also displays significant seasonal variations and could worsen indoor humidity conditions in some cases, indicating the importance of utilizing moisture buffering materials properly. In addition, although moisture buffering materials can reduce the HVAC load, the reduction is limited, within 3 kWh/m2, in most simulated cases. The energy-saving benefits of moisture buffering materials should thus not be over-emphasized. Finally, suggestions are put forward to instruct the choice of interior finishing material according to climate and buildings' HVAC scenarios. [ABSTRACT FROM AUTHOR]

Leaf senescence have shed light on its contribution to the recovery of nutrients and signaling of the transition from the active to the dormant stage in winter. The manner by which climatic and edaphic factors and plant phylogeny affect the senescent leaf economics spectrum (more mineral elements included) of different growth habits along elevational gradients in mountain ecosystems is highly uncertain. To fill this knowledge gap, we examined 15 representative subalpine forest species' senescent leaf functional traits (i.e., specific leaf area [SLA], leaf dry matter content [DMC], pH, carbon [C], nitrogen [N], phosphorus [P], potassium [K], calcium [Ca], sodium [Na], magnesium [Mg], manganese [Mn], aluminum [Al], iron [Fe], C:N, N:P, and C:P ratios) to determine the senescent leaf economics spectrum along elevational gradients in the Hengduan Mountains, China. Our results demonstrate that all the functional traits of senescent leaf showed strong correlations with one another, and K was observed as the hub for the leaf economics spectrum. Irrespective of the difference among growth habits (arbor vs. shrub), leaf habits (deciduous vs. evergreen), and leaf types (broad vs. needle), the variations in the two‐dimensional spectrum of the senescent leaf trait exhibited uniformly positive associations with elevation, primarily attributed to climatic drivers. However, the modulation of the senescent leaf economics spectrum by soil properties and plant phylogeny was surprisingly modest. Collectively, our results revealed that the resource trade‐off of senescent leaf showed a trend from acquisition to conservation along elevational gradients, which could broaden the plant economics spectrum to include senescent leaf. [ABSTRACT FROM AUTHOR]

Background: Abusive supervision by the nurse manager significantly influences nurses' withholding voice about patient safety. The role of impression management motivation and speak up-related climate is crucial in understanding their connection. This study aimed to explore the relationship between abusive supervision, impression management motivation, speak up-related climate, and withholding voice about patient safety. Methods: This cross-sectional study employed a convenience sampling method to recruit 419 clinical nurses from Taizhou Hospital, Zhejiang Province, China, between 1 November 2022 and 31 January 2023. The study adhered to the STROBE checklist. Abusive supervision and impression management motivation were assessed using the Chinese versions of the Abusive Supervision Scale and the Impression Management Motivation Scale, respectively. Withholding voice about patient safety and speak up-related climate were identified using the Chinese version of the Speaking Up about Patient Safety Questionnaire. Results: Nurse leaders' abusive supervision (β=0.40, p<0.01) and nurses' impression management motivation (β=0.10, p<0.01) significantly and positively influenced nurses' withholding voice about patient safety. We introduced impression management motivation as a mediating variable, and the effect of abusive supervision on nurses' withholding voice decreased (β from 0.40 to 0.38, p< 0.01). Nurses' speak up-related climate played a moderating role between abusive supervision and impression management motivation (β= 0.24, p<0.05). Conclusions: Abusive supervision by nursing leaders can result in nurses withholding voice about patient safety out of self-protective impression management motives. This phenomenon inhibits nurses' subjective initiative and undermines their proactive involvement in improving patient safety, and hinders the cultivation of a culture encouraging full participation in patient safety, which should warrant significant attention. [ABSTRACT FROM AUTHOR]

In China, struggling to balance environmental protection and economic growth is fundamental for the transformation of economic growth model in future. This research uses the dynamic DEA model and incorporates it into non-radial DDF. Then, the research estimates the provincial environmental performance in China during the observation period. Taking into account technological heterogeneity, in this study, the evaluated provinces are divided into two groups (temperate region and tropical and subtropical regions). The empirical findings reveal the following. (1) Most of the provinces have considerable room for enhancement in environmental performance. (2) The environmental performance of provinces in temperate regions is obviously worse than that of those in the tropical and subtropical regions. (3) Provinces in temperate region should improve environmental efficiency by reducing both their technology gap and managerial inefficiency compared to those in the tropical and subtropical regions. Considering in future that China's population will continue to shift from inland areas to coastal areas, especially large coastal cities, each province should take targeted policies to improve environmental performance according to their own situation. [ABSTRACT FROM AUTHOR]

It is essential to monitor the dynamics of vegetation at different scales in space and time to promote the sustainable development of terrestrial ecosystems. We used the Google Earth Engine (GEE) cloud platform to perform a comprehensive analysis of the changes in normalized difference vegetation index (NDVI) Mann-Kendall (MK) + Sen trend in the hinterland region of the Maowusu sandland in China over the last two decades. We performed bias-correlation studies using soil and climate data. Furthermore, we performed a partial Mantel test to analyze the spatial and temporal fluctuations of vegetation health-related indices. Additionally, we developed a logistic dual model of the phenology index using the Lenvenberg–Marquardt technique. The objective was to uncover the factors contributing to the regional shifts in vegetation dynamics. We provide a comprehensive analytic method designed to monitor vegetation over some time and forecast its future recovery. The findings indicate that over the past 20 years, more than 90% of the regional NDVI in the study area has exhibited a consistent and significant upward trend. This trend is primarily influenced by the adverse impact of temperature and the beneficial impact of precipitation. Additionally, long-term phenological indicators in the study area reveal that the vegetation's growth cycle commences on the 125th day of the year and concludes on the 267th day of the year. This suggests that the shorter duration of the vegetation's growth season may be attributed to the local climate and unfavorable groundwater depth conditions. levated temperatures throughout the next spring and autumn seasons would significantly affect the wellbeing of plants, with soil moisture being a crucial determinant of plant development in the examined region. This study presents a wide range of analytical tools for monitoring vegetation over a long period and predicting its future recovery. It considers factors such as vegetation health, phenology, and climatic influences. The study establishes a solid scientific foundation for understanding the reasons behind regional vegetation changes in the future. [ABSTRACT FROM AUTHOR]

Introduction: The diversity-productivity relationship is a central issue in maintaining the grassland ecosystem’s multifunctionality and supporting its sustainable management. Currently, the mainstream opinion on the diversity-productivity relationship recognizes that increases in species diversity promote ecosystem productivity.Methods: Here, we challenge this opinion by developing a generalized additive model-based framework to quantify the response rate of grassland productivity to plant species diversity using vegetation survey data we collected along a land-use intensity gradient in northern China.Results: Our results show that the grassland aboveground biomass responds significantly positively to the Shannon-Wiener diversity index at a rate of 46.8 g m-2 per unit increase of the Shannon-Wiener index in enclosure-managed grasslands, under the co-influence of climate and landscape factors. The aboveground biomass response rate stays positive at a magnitude of 47.1 g m-2 in forest understory grassland and 39.7 g m-2 in wetland grassland. Conversely, the response rate turns negative in heavily grazed grasslands at -55.8 g m-2, transiting via near-neutral rates of -7.0 and -7.3 g m-2 in mowing grassland and moderately grazed grassland, respectively.Discussion: These results suggest that the diversity-productivity relationship in temperate grasslands not only varies by magnitude but also switches directions under varying levels of land use intensity. This highlights the need to consider land use intensity as a more important ecological integrity indicator for future ecological conservation programs in temperate grasslands. [ABSTRACT FROM AUTHOR]

In this study, the Flexible Particle Dispersion Model (FLEXPART) is applied to analyze the moisture sources of Northeast China precipitation from March 1979 to February 2018. The results show that there is mainly one particle aggregation channel in winter, namely the eastern Europe–Siberia–Lake Baikal–Northeast Asia channel (the western channel). In comparison with winter, there are two extra channels in summer, namely the Indochina Peninsula–South China Sea–East China channel (the southern channel) and the Philippine Sea–Ryukyu Islands channel (the southeastern channel). From the long-term mean, the Siberia–Mongolia–Xinjiang region (SMX) is the most dominant moisture source of Northeast China precipitation in all seasons. As for the moisture contribution rate of each source region to Northeast China precipitation, there is a seesaw interannual relationship between SMX and other source regions. The moisture from Central and East China is critical to the interdecadal shift of Northeast China summer precipitation. This interdecadal shift is related to the moisture transport from low latitudes to Northeast China, which is modulated by the positive phase of the Pacific decadal oscillation and the negative phase of the Atlantic multidecadal oscillation. [ABSTRACT FROM AUTHOR]

[Display omitted] • A numerical model is proposed for seasonal thermal energy storage (STES) couple with solar collector. • The model is featured as relatively high computational speed and accuracy. • An analysis on technical planning and operational design for the STES is offered. • The key parameters for system design and control are investigated with instructive results. Seasonal thermal energy storage (STES) systems are a key component in expanding the share of renewables in energy programs because they provide schedulability and flexibility. However, such a large-scale system requires careful planning to avoid high investment costs. Therefore, numerical models are becoming increasingly important as an alternative. This paper develops a numerical model of STES coupled with solar collector. The model was verified based on the experimental data of the Huangdicheng Project in China. The results show that the relative error in the charging mode and discharging mode is only 1.57 % and 0.46 %, respectively. Then, the effects of different charging and discharging mode on the heat storage efficiency of the tank and the efficiency of solar collector systems in STES were studied. The study found that in the initial charging stage, the water temperature rise curve caused by different flow rates is very different. In the design of the collector-storage area ratio, the relatively economical collector-storage ratio of this model is around 3768 L/m2. The selection of different proportions of discharging energy in the discharge stage has a great impact on the heat storage efficiency of the system in the next year. Moreover, the influence of different depth-diameter ratios of the tank on the system heat storage efficiency is discussed in detail, which has important guiding significance for model application and system analysis. This paper provides some references for the scale design and operation optimization of cylindrical STES. [ABSTRACT FROM AUTHOR]

Amidst the compounded challenges posed by global climate change and urbanization on forest ecosystems, the integration of urbanization control measures within a climate-focused framework may offer an avenue for breakthroughs. This study delves into the impact of climate, specifically hydrothermal conditions, on the complex interplay between urbanization (Urb) and forest ecological function (Eco) in the Yellow River Basin (YRB) in China. Our findings reveal: (1) The application of a coupled coordination model reveals a stronger alignment between urbanization and forest ecological function in the warm and humid regions in the YRB. (2) Through the cross-sectional threshold regression model, we elucidate the diverse responses of Urb to Eco across varying climate gradients. Among them, annual precipitation shows a double-threshold effect at 532.34 mm and 694.18 mm. As precipitation increases, the impact of Urb shifts from negative to positive on Eco. Moreover, in regions with precipitation below 532.34 mm and above 694.18 mm, the absolute value of response coefficients of Eco to Urb is amplified. Annual average temperature displays a single-threshold effect at 10.11 °C, leading to a transition from negative to positive impact as temperature rises. This study establishes the climate-based threshold system that governs the urbanization–forest ecological function relationship. [ABSTRACT FROM AUTHOR]

Irrigation has excellent potential for altering surface characteristics and the local climate. Although studies using site observations or remote sensing data have demonstrated an irrigation cooling effect (ICE) on the air temperature (Tem) and land surface temperature (LST), it is difficult to eliminate other stress factors due to different backgrounds. We characterized the irrigation effect as the differences (Δ) of LST and DCT (DCT = LST − Tem) between irrigated and adjacent non-irrigated areas. An improved method was proposed to detect it over the North China Plain (NCP) based on satellite observations. We also investigated the effects of irrigation on Tem, precipitation, NDVI, and ET, and explored the relationships between them. The results show that irrigation induced a decrease in the daytime/nighttime LST and DCT (−0.13/−0.09 and −0.14/−0.07 °C yr−1), Tem (−0.023 °C in spring), and precipitation (−1.461 mm yr−1), and an increase in NDVI (0.03 in spring) and ET (0.289 mm yr−1) across the NCP. The effect on nighttime LST and NDVI increased by 0.04 °C 10 yr−1 and 0.003 10 yr−1, and that on ET weakened by 0.23 mm 10 yr−1 during 2000–2015. The ICE on the LST had evident spatiotemporal heterogeneity, which was greater in the daytime, in the spring, and in the northern area of the NCP (dry–hot conditions). The daytime ICE in the NCP and northern NCP was 0.37 and 0.50 °C during spring, respectively, with the strongest ICE of 0.60 °C in Henan; however, the ICE was less evident (<0.1 °C) in the southern NCP throughout the year. The ΔNDVI, ΔET, and ΔTem were the main factors driving ICE, explaining approximatively 22%, 45%, and 25% of the daytime ICE, respectively. For every unit of these measures that was increased, the daytime ICE increased by about 7.3, 4.6, and 1.5 °C, respectively. This study highlights the broad irrigation effect on LST, ET, NDVI, and the climate, and provides important information for predicting climate change in the future. The improved method is more suitable for regions with uneven terrain and a varying climate. [ABSTRACT FROM AUTHOR]

Climate plays a significant role in shaping ecosystem-level carbon sinks. Research on the mechanisms of climate impacts on carbon sinks can contribute to the achievement of carbon neutrality. Investigating the mechanisms by which climate impact on carbon sinks in ecological spaces in the Beijing–Tianjin–Hebei region, one of the most important urban clusters in China, is of great significance. This study employed spatial autocorrelation and econometric models to explore how various climatic factors impact net primary productivity (which is used to represent carbon sink capacity) on a spatial scale. We found an increasing trend in NPP across the Beijing–Tianjin–Hebei urban agglomeration from 2000 to 2020, with marked spatial clustering. Climatic factors exhibited the best fit with the spatial Durbin model, except for average annual precipitation. The remaining factors had significant effects on NPP, showing spatial spillover effects. Results also showed that the average annual temperature, evaporation, and relative humidity had positive impacts on NPP at a local scale but adverse effects at a regional scale. Average annual sunshine duration and the ground temperature had negative effects on NPP locally but promoted effects regionally. Furthermore, the average annual wind speed negatively impacted both local- and regional-scale NPP. This research provides insights into how climate affects carbon sinks on a small spatial scale, offering important references for making policy decisions and improving the accuracy of carbon cycling simulations. [ABSTRACT FROM AUTHOR]

Vegetation is an essential component of the Earth's surface system, and is a clear indicator to global climate changes. Understanding the long‐term characteristics of vegetation variations and their relationship to climate and human activities is important for regional sustainable development and ecological construction. In this study the ensemble empirical mode decomposition, the breaks for additive seasonal and trend algorithm and trend analysis were applied to obtain the spatiotemporal characteristics of the long‐term interannual normalized difference vegetation index in China. Partial least squares‐structural equation modeling and geographically weighted regression were used to separate the effects of climate and human activities on vegetation greening and achieve the partitioning of these driving forces. The results suggested that vegetation growth in China experienced an abrupt change in 1995, there was obvious vegetation 'browning' during 1990–1995, and noticeable vegetation recovery from 1996 to 2018 (slope = 0.129/yr, p = 0.009). Spatially, vegetation 'greening' was occurred in central and southern China, reflecting the positive effect of ecological restoration projects on vegetation growth. Climate was a directly main driving force for vegetation greening in China. It played a positive role in South China, but had a negative effect in Northwest China. Improving socio‐economic conditions had a slightly negative impact on vegetation greening, while afforestation played a direct and obvious role in promoting vegetation growth, especially in Northwest China. Furthermore, afforestation and socio‐economic conditions would also indirectly affect vegetation growth by directly influencing the local microclimate, and the indirect effect of them on vegetation growth was far greater than its direct impact in some cases; therefore, research attention should be paid to the indirect effects of these driving forces on vegetation growth. There was obvious spatial heterogeneity in the effects of different forces on vegetation greening in China, and the dominant driving force of vegetation change in each geographical region also differed. [ABSTRACT FROM AUTHOR]

Species diversity has been shown to be influenced by environmental factors, but the mechanism underlying their relationship remains unclear across spatial scales. Based on field investigation data collected from 3077 sample plots in temperate forest ecosystems, we compared tree species richness, evenness and dominance at 10 km × 10 km, 30 km × 30 km and 90 km × 90 km spatial scales. Then, we detected the scale dependence of changes in tree species composition on climate, topography and forest structure using variation partitioning and quantified their contribution to tree diversity with gradient–boosted models (GBMs) and fitted their relationships. The magnitude of tree richness, evenness and dominance significantly increased with spatial scale. Ecological factors jointly accounted for 24.3%, 26.5% and 38.5% of the variation in tree species composition at the three spatial scales, respectively. The annual mean temperature had a strong impact on tree richness, evenness and dominance and peaked at an intermediate scale. Tree evenness and dominance increased with the variation of temperature but had upper and lower limits. Tree richness obviously increased with annual precipitation on multiple scales and decreased with annual sunshine duration at large spatial scales. Tree richness, evenness and dominance obviously increased with the variation in elevation and diameter at breast height at large scales and small scales, respectively. Tree dominance decreased with tree height at a small scale. The dependence of tree diversity on ecological factors increased with spatial scales. Furthermore, different factors exert various controls on tree diversity at different spatial scales, representing a comprehensive mechanism regulating tree diversity. [ABSTRACT FROM AUTHOR]

Introduction: Salvia miltiorrhiza Bunge is an important medicinal herb, which is widely cultivated in most parts of China. It has attracted considerable attention because of its pharmacological properties and potential health benefits. Methods: We used a field experiment to determine the effects of different genotypes and climatic factors on the performance (plant biomass, morphological parameters), active ingredients, rhizosphere soil physicochemical properties and microbial composition of S. miltiorrhiza at five cultivation locations. Results: The results showed that these parameters were significantly different in the six different genotypes of S. miltiorrhiza from five producing areas. Genotype and soil physicochemical properties were the main factors affecting the growth traits of S. miltiorrhiza, while genotype, climate and soil physicochemical properties were the main factors affecting the content of active components of S. miltiorrhiza. Microbial phospholipid fatty acid analysis showed that the biomass of Gram-positive and Gram-negative bacteria was affected by the genotypes of S. miltiorrhiza plants, while the biomass of arbuscular mycorrhizal fungi, fungi, Gram-positive and Gram-negative bacteria was affected by climate factors. Discussion: Based on the main results, DS993 was the most suitable genotype for S. miltiorrhiza in the five producing areas from the perspective of comprehensive growth traits and medicinal components, while DS993 and DS2000 were suitable for planting in Shandong province from the perspective of origin. DS996 is not suitable for all of the above production areas. These results are helpful to understand the ecological adaptability of different genotypes of S. miltiorrhiza resources, and to select appropriate S. miltiorrhiza genotypes for specific planting areas, so as to maximize yield and quality. [ABSTRACT FROM AUTHOR]

A major goal of ecology and evolutionary biology is to explain geographic patterns of species richness. Richness is often correlated with climatic variables. However, the processes underlying these climate‐diversity relationships remain poorly understood. Two potential hypotheses to explain these relationships involve: (i) faster diversification rates (speciation minus extinction) in high‐richness climates and (ii) earlier colonization of high‐richness climates, allowing more time for speciation to build up richness. Few studies have tested these hypotheses directly, and most focused on animal clades with limited richness. In this study, we test these hypotheses in Chinese angiosperms, encompassing ~10% of Earth's plant species, using large‐scale phylogenetic, climatic, and distributional data including 26,977 species. We find that climatic zones that were colonized earlier have higher species richness. By contrast, relationships between diversification rates and richness of climatic zones are often nonsignificant or negative. Our study reveals that even when richness is strongly correlated with climate, the underlying explanation may still be rooted in phylogenetic history. Thus, climate may not be a competing explanation for richness patterns relative to colonization times and diversification rates. We also show that the timing of colonization can be crucial for explaining richness patterns. Yet, many recent studies have ignored this explanation and instead have focused solely on rates of speciation and diversification as drivers of diversity gradients. [ABSTRACT FROM AUTHOR]

Aboveground biomass (AGB) in managed grasslands can vary across a suite of environmental and management conditions; however, there lacks a quantitative assessment at the national scale of China. Although the potential effects of individual drivers (e.g., species, nutrient fertilization, and water management) have been examined in China's managed grasslands, no attempts have been made to comprehensively assess the effects of multiple variables on AGB. Using a meta-data analysis approach, we created a database composed of AGB and associated attributes of managed grasslands in China. The database was used to assess the responses of AGB to anthropogenic factors, in addition to a suite of natural variables including climate, soil, and topography. The average AGB in managed grasslands of China is approximately 630 g m−2 of dry matter, ranging from 55 to 2172 g m−2 (95% confidence interval). Medicago sativa is the most widely planted species in China's managed grasslands, followed by Elymus dahuricus and Bromus japonicus. The national average AGB of these three species was around 692, 530, and 856 g m−2, respectively. For each species, AGB shows a large discrepancy across different places. In general, grassland AGB depends substantially on species, environments, and management practices. The dependence can be well described by a linear mixed-effects regression in which a series of biotic and abiotic factors are used as predictors. We highlight that establishing managed grassland can potentially contribute to not only AGB enhancement, but also grassland restoration on degraded natural grasslands. [ABSTRACT FROM AUTHOR]

Subsoil (0.2–1 m) organic carbon (C) accounts for the majority of soil organic carbon (SOC), and SOC turnover time (τ, year) is an important index of soil C stability and sequestration capacity. However, the estimation of subsoil τ and the identification of its dominant environmental factors at a regional scale is lacking in regards to forest ecosystems. Therefore, we compiled a dataset with 630 observations to investigate subsoil τ and its influencing factors in forest ecosystems across China using the structural equation model (SEM). The results showed a large variability of subsoil τ from 2.3 to 896.2 years, with a mean (± standard deviation) subsoil τ of 72.4 ± 68.6 years; however, the results of one-way analysis of variance (ANOVA) showed that subsoil τ differed significantly with forest types (p = 0.01), with the slowest subsoil τ obtained in deciduous-broadleaf forests (82.9 ± 68.7 years), followed by evergreen-needleleaf forests (77.6 ± 60.8 years), deciduous-needleleaf forests (75.3 ± 78.6 years), and needleleaf and broadleaf mixed forests (71.3 ± 80.9 years), while the fastest subsoil τ appeared in evergreen-broadleaf forests (59.9 ± 40.7 years). Subsoil τ negatively correlated with the mean annul temperature, occurring about three years faster with a one degree increase in temperature, indicating a faster subsoil SOC turnover under a warming climate. Subsoil τ significantly and positively correlated with microbial activities (indicated by microbial C and nitrogen), highlighting the importance of microbial communities in regulating subsoil C dynamics. Climate, forest types, forest origins, vegetation, and soil variables explained 37% of the variations in subsoil τ, as indicated by the SEM, and the soil property was the most important factor affecting subsoil τ. This finding challenged previous perception that climate was the most important factor driving subsoil C dynamics, and that dominant drivers varied according to climate zones. Therefore, recognizing different dominant factors in predicting subsoil C dynamics across climate zones would improve our understanding and reduce the uncertainties regarding subsoil C dynamics in biogeochemical models under ongoing climate change. [ABSTRACT FROM AUTHOR]

Vegetation phenology is a sensitive indicator of climate change, and can help understand the response of vegetation cycles to climate, which is important for understanding the impact of global climate change on terrestrial ecosystems. In this study, based on the enhanced vegetation index (EVI) time-series data, derived from the moderate-resolution imaging spectroradiometer (MODIS) data, the climate parameters were extracted using the Savitzky–Golay (S–G) filtering method to explore the spatial and temporal variation characteristics of the vegetation phenology in an agro-pasture ecotone in China, from 2000 to 2020. In addition, the response characteristics of the vegetation phenology to the climate elements (temperature and precipitation) were also analyzed. The results showed the following: (1) The start of the growing season (SOS) was widely advanced, and that was caused by climate change. The end of the growing season (EOS) was delayed, and the length of the growing season (LOS) was gradually extended with a large interannual fluctuation in the SOS and the LOS in the region; (2) the SOS showed significant negative correlations with the air temperature and precipitation. Precipitation was mainly positively correlated with the EOS, but there was no significant difference in the correlation between temperature and the EOS. In general, pre-season precipitation is the main driver of the vegetation phenology, while the influence of temperature on the phenology is less obvious; (3) in the semi-arid area and arid area, the phenology was mainly influenced by precipitation. The response of the vegetation phenology to the temperatures in different temperature zones was found to be regular, showing high spatial differences. In general, the higher the cumulus temperature, the lower the negative effect of the temperature on both the SOS and EOS. These results may provide new reference to study the non-systematic changes of the vegetation phenology in response to climate change. [ABSTRACT FROM AUTHOR]