Search

The concept of low carbon education is one solution to provide knowledge to students related to low carbon behavior. The purpose of this paper is providing an extensive bibliometric literature review on 'low carbon education'. Articles found by Publishing or Perish (PoP) software with the Google Scholar database. There were 55 out of 97 articles found from Google Scholar data base ranging from 2014 to 2019 analyzed in this study. The chosen references were then managed using a referencing manager software namely Zotero. After managing the database, this study classified and visualized it using VOSviewer software. Overall, this review provides an appropriate reference point for further research on 'low carbon education'.

Climate change is not local; it is global. This means that many environmental issues related to climate change are not geographically limited and hence concern humans in more than one location. There is a growing body of research indicating that today's increased climate change is caused by human activities and our modern lifestyle. Consequently, climate change awareness and attention from the entire world's population needs to be a global priority and we need to work collaboratively to attain a sustainable future. A powerful tool in this process is to develop an understanding of climate change through education. Recognizing this, climate change has been included in many science curricula as a part of science education in schools. However, teaching such a complex and global topic as climate change is not easy. The research in this paper has been driven by this challenge. In this paper, we will present our online science module called Global Climate Exchange, designed with inquiry activities for international peer collaboration to teach climate change. In this study, we engaged 157 students from four countries (Canada, China, Sweden, and Norway) to collaborate in Global Climate Exchange. To explore the opportunities that international peer collaboration in Global Climate Exchange gives, we have analyzed how students develop their explanations about climate change issues over time. Our analysis showed that the students increased the proportion of relevant scientific concepts in relation to the total number of words in their explanations and that they improved the quality of links between concepts over a six-week period. The analysis also revealed that the students explained more perspectives relating to climate change issues over time. The outcomes indicate that international peer collaboration, if successfully supported, can be an effective approach to climate change education.

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.)

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.)

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.)

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]

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.)

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 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.)

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.

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]

The deterioration of water quality has become a primary environmental concern worldwide. Understanding the status of water quality and identifying the influencing factors are important for water resources management. However, reported analyses have mostly been conducted in small and focused areas. It is still unclear if factors driving spatial variation in water quality would be different in extended spatial scales. In this paper, we analyzed spatial pattern of inland surface water quality in China using a dataset with four water quality parameters (i.e., pH, DO, NH4+-N and CODMn) and the water quality level. We tested the effects of anthropogenic (i.e., land use and socio-economic) and natural (i.e., climatic and topographic) factors on spatial variation in water quality. The study concluded that the overall inland surface water quality in China was at level III (fair). Water quality level was strongly correlated with CODMn and NH4+-N concentration. In contrast to reported studies that suggested land use patterns were the determinants of inland surface water quality, this study revealed that both anthropogenic and natural factors played important roles in explaining spatial variation of inland surface water quality in China. Among the tested explanatory variables, mean elevation within watershed appeared as the best predictor for pH, while annual precipitation and mean air temperature were the most important explanatory variables for CODMn and DO, respectively. NH4+-N concentration and water quality level were most strongly correlated with the percent of forest cover in watershed. Compared to studies at smaller spatial scales, this study found different influencing factors of surface water quality, suggesting that factors may play different roles at different spatial scales of consideration. Therefore management policies and measures in water quality control must be established and implemented accordingly. Since currently adopted parameters for monitoring of inland surface water quality in China are largely influenced by natural variables, additional physicochemical and biological indicators are needed for a robust assessment of human impacts on water quality., Competing Interests: The authors have declared that no competing interests exist.

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]

[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]

Regression analysis is applied to quantitatively analyze the impact of different ambient temperature characteristics on the transformer life at different locations of Chinese mainland. 200 typical locations in Chinese mainland are selected for the study. They are specially divided into six regions so that the subsequent analysis can be done in a regional context. For each region, the local historical ambient temperature and load data are provided as inputs variables of the life consumption model in IEEE Std. C57.91-1995 to estimate the transformer life at every location. Five ambient temperature indicators related to the transformer life are involved into the partial least squares regression to describe their impact on the transformer life. According to a contribution measurement criterion of partial least squares regression, three indicators are conclusively found to be the most important factors influencing the transformer life, and an explicit expression is provided to describe the relationship between the indicators and the transformer life for every region. The analysis result is applicable to the area where the temperature characteristics are similar to Chinese mainland, and the expressions obtained can be applied to the other locations that are not included in this paper if these three indicators are known.

Based on SPOT-VGT images and meteorological data, this paper applied an integrated method to investigate the vegetation dynamic and its response to climate factors during 1998-2008 in Northeast China Transect, one of 15 ecological transects listed in the International Geosphere-Biosphere Programme. The main findings are as follows: (1) The NDVI time series presented nonlinear patterns that vary with timescales. The series fluctuated greatly at the smallest timescale (20 days), showing no salient trend, whereas a trend manifested itself more and more with the increase of time scale and finally stabilized at the 320-day scale. Little difference was found between vegetation types about the NDVI periodicity, as they occurred on either a 280-day or a 290-day cycle. (2) NDVI exhibited a significant correlation with temperature, precipitation, and sunshine hours. Overall, the correlation between NDVI and temperature was the highest, followed by precipitation, sunshine hours, and relative humidity. For different vegetation types, the correlations between NDVI and climate variables diversified, increasing from desert steppe to typical steppe, meadow steppe, and forest. (3) The periodicity of temperature and precipitation occurred in either a 280-day or 290-day cycle, which was approximately coincident with that of NDVI. This further supported the significant relationship between NDVI and these two climate factors. (4) At all the time scales under examination, NDVI and temperature and precipitation are significantly, positively correlated, especially at the 160-day scale, which can be regarded as the most suitable time scale for investigating the responses of vegetation dynamics to climate factors at most stations.

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]

Net primary productivity (NPP) is a key component of energy and matter transformation in the terrestrial ecosystem, and the responses of NPP to global change locally and regionally have been one of the most important aspects in climate-vegetation relationship studies. In order to isolate causal climatic factors, it is very important to assess the response of seasonal variation of NPP to climate. In this paper, NPP in Xinjiang was estimated by NOAA/AVHRR Normalized Difference Vegetation Index (NDVI) data and geographic information system (GIS) techniques. The impact of climatic factors (air temperature, precipitation and sunshine percentage) on seasonal variations of NPP was studied by time lag and serial correlation ageing analysis. The results showed that the NPP for different land cover types have a similar correlation with any one of the three climatic factors, and precipitation is the major climatic factor influencing the seasonal variation of NPP in Xinjiang. It was found that the positive correlation at 0 lag appeared between NPP and precipitation and the serial correlation ageing was 0 d in most areas of Xinjiang, which indicated that the response of NPP to precipitation was immediate. However, NPP of different land cover types showed significant positive correlation at 2 month lag with air temperature, and the impact of which could persist 1 month as a whole. No correlation was found between NPP and sunshine percentage.

In the framework of an EU project on sustainable village development in China (SUCCESS), the natural climate resource was evaluated. Climate is seen as a potential for sustainability, an improvement of social life, agricultural production and reduction of air pollution problems. In this respect, thermal comfort conditions, microclimates and ventilation patterns were studied in seven Chinese villages and climate maps were drawn. Following planning recommendations, they can be transferred to decision-makers for their village development. In this framework, the paper presents a general methodology of urban climate mapping, carried out in China, applicable to all countries and climates.

This paper investigates the sandy desertification change between 1986 and 2000 in the western Jilin province, North China. Land use and land cover data were obtained from Landsat TM data by using a supervised classification approach. We summarized the total area of desertified land by each county, as well as the area for each of the four categories of desertified land. The changes of different types of land use and land cover between 1986 and 2000 were calculated and analyzed. Taking Tongyu and Qianan as examples, both human and natural driving forces of the sandy desertification were analyzed. Our analyses indicate that the material sources and windy, warm and dry climate are the immanent causes of potential land desertification, while the irrational human activities, such as deforestation, reclaiming and grazing in the grassland, are the external causes of potential land desertification. However, rational human activities, such as planting trees and restoring grassland can reverse the land desertification process. Furthermore, the countermeasures and suggestions for the sustainable development in ecotone between agriculture and animal husbandry in North China are put forward.

Climate and tectonism are both particularly intense in the Yarlung Zangbo (Tsangpo) Great Canyon in the eastern Himalayan syntaxis, which is characterized by the most rapid landscape evolution of anywhere in the world. Thus, the eastern Himalayan syntaxis is one of the best locations to study the interactions between climate and tectonics. This paper investigates the cooling ages of the Doxong La-Baibung profile using apatite fission track (AFT) dating on 11 bedrock samples at elevations ranging from 4210 to 710 m. There are topographic, climatic, metamorphic, and thermochronological gradients in the profile, providing good conditions to study interactions between climate and tectonics. AFT ages ranged from 4.6±0.6 Ma to 1.7±0.3 Ma, and the mean fission track lengths ranged from 11.0 to 12.4 µm. It was found that the cooling rates revealed by AFT ages increased with decreasing elevation. However, the tendency of the cooling rates revealed by the 40Ar-39Ar ages was different from that indicated by the AFT ages. Moreover, for most districts of the eastern Himalayan syntaxis, the compiled AFT age distribution correlates well with the annual average precipitation, indicating the coupling of the cooling and erosion rates of the near-surface rock and precipitation. The geothermal history modeling results indicate an obvious increase in the cooling and erosion rate between 1.0 and 0.5 Ma. This age is consistent with other research findings for this time, when the vapor channel of the Yarlung Zangbo Great Canyon began to take effect. These evidences suggest that climate, especially precipitation, has acting as a key factor influencing the rapid cooling and erosion in the Yarlung Zangbo Great Canyon since 1-0.5 Ma. [ABSTRACT FROM AUTHOR]

Expansion of irrigated land can cause local cooling of daytime temperatures by up to several degrees Celsius. Here the authors compare the expected cooling associated with rates of irrigation expansion in developing countries for historical (1961–2000) and future (2000–30) periods with climate model predictions of temperature changes from other forcings, most notably increased atmospheric greenhouse gas levels, over the same periods. Indirect effects of irrigation on climate, via methane production in paddy rice systems, were not considered. In regions of rapid irrigation growth over the past 40 yr, such as northwestern India and northeastern China, irrigation’s expected cooling effects have been similar in magnitude to climate model predictions of warming from greenhouse gases. A masking effect of irrigation can therefore explain the lack of significant increases in observed growing season maximum temperatures in these regions and the apparent discrepancy between observations and climate model simulations. Projections of irrigation for 2000–30 indicate a slowing of expansion rates, and therefore cooling from irrigation expansion over this time period will very likely be smaller than in recent decades. At the same time, warming from greenhouse gases will likely accelerate, and irrigation will play a relatively smaller role in agricultural climate trends. In many irrigated regions, therefore, temperature projections from climate models, which generally ignore irrigation, may be more accurate in predicting future temperature trends than their performance in reproducing past observed trends in irrigated regions would suggest. [ABSTRACT FROM AUTHOR]

• Background and Aims A central goal of biogeography and ecology is to uncover and understand distributional patterns of organisms. China has long been a focus of attention because of its rich biota, especially with respect to plants. Using 290 floras from across China, this paper quantitatively characterizes the composition of floristic elements at multiple scales (i.e. national, provincial and local), and explores the extent to which climatic and geographical factors associated with each flora can jointly and independently explain the variation in floristic elements in local floras.• Methods A study was made of 261 local floras, 28 province-level floras and one national-level flora across China. Genera of seed plants in each flora were assigned to 14 floristic elements according to their worldwide geographical distributions. The composition of floristic elements was related to climatic and geographical factors.• Key Results and Conclusions Variations in percentages of cosmopolitan, tropical and temperate genera among local floras tend to be greater at higher latitudes than at lower latitudes. Latitude is strongly correlated with the proportions of 13 of the 14 floristic elements. Correlations of the proportions of floristic elements with longitude are much weaker than those with latitude. Climate represented by the first principal component of a principal component analysis was strongly correlated with the proportions of floristic elements in local floras (|r| = 0·75 ± 0·18). Geographical coordinates independently explained about four times as much variation in floristic elements as did climate. Further research is necessary to examine the roles of water–energy dynamics, geology, soils, biotic interactions, and historical factors such as land connections between continents in the past and at present in creating observed floristic patterns. [ABSTRACT FROM AUTHOR]

In Asia, especially in China, our knowledge of the distribution of testate amoebae is still limited. In this paper, the geographical distribution of testate amoebae in Tibetan Plateau and northwestern Yunnan Plateau, southwest China and their relationships with the climatic factors have been studied. We found testate amoebae shifted in the most dominant species and increased in species (or genus) richness from northwest to southeast. Further, the linear regression analyses revealed that both species richness and genus richness have higher positive correlations with the mean temperature of the warmest month and annual mean precipitation as contrasted with the mean altitude, which showed weak negative correlation. This indicates that the temperature and precipitation are more significant influences on the richness than the altitude. The cluster analysis based on the community structure, defined by Sørenson’s coefficient matrix, suggested four groups from the 10 physiographical regions. This geographical distribution pattern was also closely related with the climatic regionalization. The present climatic regionalization pattern of the study area originated from the uplift of Tibetan Plateau and mainly occurred in or after the late Pleistocene. Therefore, the geographical distribution of testate amoebae in our study area may have experienced complicated and drastic changes corresponding to the variation of the climate caused by the geological events. [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]

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]

As one of the most intensively eroded regions worldwide, soil erosion assessment is currently gaining further momentum in the Loess Plateau (LP), China. However, there exist very few review studies that assess soil erosion in relation to land use and land cover (LULC), climate, and ecosystem services (ESs) at multiple temporal and spatial scales in the LP. Thus, this review provides a comprehensive review of the interactions among soil erosion assessment, climate change, LULC change, and ESs at different scales. We focused on the academic literature published in the English language and analyzed the coverage of soil erosion across 109 publications. Our results highlighted three aspects: (1) studies dealing with the effects of LULC change on soil erosion are abundant. A recent surge in research interest is to explore a threshold of vegetation cover to support a sustainable eco-hydrological environment in the LP. However, the impacts of multiple stressors on soil erosion have received limited attention. (2) The short-term soil erosion assessment dominated the published studies. Cross-spatial-scale and long-term erosion assessments have received little attention. (3) 43% of reviewed papers used a field measurement method to assess soil erosion with the validation of measurement methods. 41% of reviewed papers used empirical models to assess soil erosion, but the modeling validation remains an unsolved problem. Then, three recommendations are listed as follows: (1) the combined impacts of LULC and climate change on soil erosion need to be further examined. (2) Long-term and cross-spatial-scale soil erosion assessments need to be established. (3) Soil erosion modeling accuracy on a large scale needs to be developed. • The assessment of multiple stressors on soil erosion has received limited attention. • Poor coverage of multi-spatial scale and long-term soil erosion assessment. • Large scale soil erosion modeling validation remains an unsolved problem. • A recent surge in academic interest is to explore thresholds of vegetation cover in the Loess Plateau. [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]

Mineral-associated organic carbon (MOC), that is stabilized by fine soil particles (i.e., silt plus clay, <53 μm), is important for soil organic carbon (SOC) persistence and sequestration, due to its large contribution to total SOC (TSOC) and long turnover time. Our objectives were to investigate how climate, soil type, soil texture, and agricultural managements affect MOC contributions to TSOC in China. We created a dataset from 103 published papers, including 1106 data points pairing MOC and TSOC across three major land use types: cropland, grassland, and forest. Overall, the MOC/TSOC ratio ranged from 0.27 to 0.80 and varied significantly among soil groups in cropland, grassland, and forest. Croplands and forest exhibited significantly higher median MOC/TSOC ratios than in grassland. Moreover, forest and grassland soils in temperate regions had higher MOC/TSOC ratios than in subtropical regions. Furthermore, the MOC/TSOC ratio was much higher in ultisol, compared with the other soil types. Both the MOC content and MOC/TSOC ratio were positively correlated with the amount of fine fraction (silt plus clay) in soil, highlighting the importance of soil texture in stabilizing organic carbon across various climate zones. In cropland, different fertilization practices and land uses (e.g., upland, paddy, and upland-paddy rotation) significantly altered MOC/TSOC ratios, but not in cropping systems (e.g., mono- and double-cropping) characterized by climatic differences. This study demonstrates that the MOC/TSOC ratio is mainly driven by soil texture, soil types, and related climate and land uses, and thus the variations in MOC/TSOC ratios should be taken into account when quantitatively estimating soil C sequestration potential of silt plus clay particles on a large scale. [ABSTRACT FROM AUTHOR]

In this paper, we present a δ13C record that covers the past 750 years at a resolution of 2 - 3 years which was preserved in a precisely dated stalagmite (DY-1) obtained from the Dayu Cave on the south flank of the Qinling Mountains in central China. Between 1249 AD and 1800 AD, climate-induced vegetation changes appear to have been the primary control on δ13C values at a centennial scale. Variations in precipitation amounts control the residence time of seepage water and may have affected the dissolution of bedrock, prior carbonate precipitation in the unsaturated zone above the cave, and the degassing of CO2 within the cave. These hydrogeochemical processes are likely to have been the most important controls on δ13C levels over annual to decadal scales, and may also have influenced centennial-scale variations. The reduced δ13C value of atmospheric CO2 since the Industrial Revolution may have caused the decreasing trend in δ13C values seen in stalagmite DY-1 after 1800 AD. Increased visitor numbers in the unventilated Dayu Cave over time produced a large amount of CO2, and maintained a raised level of pCO2 in the cave air. This artificially enhanced pCO2 may have decreased the fraction of CO2 degassing, and hence carbonate precipitation, which could partly cause the decreasing trend in the stalagmite δ13C seen over the past 200 years. [ABSTRACT FROM AUTHOR]