Dongxiang wild rice rhizomicrobiomes inhibit photosynthetic methanogenic microbes: a potential solution for reducing methane emissions in northeastern China DOI Creative Commons

Yingnan Pang,

Jingjing Chang,

Zongmu Yao

и другие.

Research Square (Research Square), Год журнала: 2024, Номер unknown

Опубликована: Дек. 11, 2024

Abstract Background Reducing greenhouse gas (GHG) emissions from agriculture is a crucial aspect of global environmental governance. In particular, reducing methane (CH4) rice fields top priority for ensuring the sustainable development agricultural ecosystems. Methane paddies reflect balance between production and degradation, wild may be an advantageous resource modulating both processes. Results this study, we used shotgun metagenomic sequencing, 16S rRNA analysis, chromatographic determination to demonstrate that are significantly influenced by soil type domestication The abundances genes related metabolism were lower in rhizosphere than cultivated under controlled field conditions. Notably, found photoautotrophic microorganisms contributed paddies. Wild suspension validation tests confirmed rich diverse microbial resources effectively inhibited methanogens reduce rice. Conclusions On basis our results, propose harnessing strain novel feasible strategy GHG black agriculture. This approach could make significant contribution towards achieving "carbon peak carbon neutrality" goals.

Язык: Английский

Changes in Compound Extreme Events and Their Impacts on Cropland Productivity in China, 1985–2019 DOI Creative Commons
Zejin Liu,

Limin Jiao,

Xihong Lian

и другие.

Earth s Future, Год журнала: 2025, Номер 13(3)

Опубликована: Март 1, 2025

Abstract While the influence of compound extreme events is gaining attention with advancing climate research, variations in their impacts on regional crop production require further exploration. Here, we primarily analyze changes hot‐dry and hot‐wet China from 1985 to 2019, based meteorological observations 686 stations. Then, contributions losses cropland net primary productivity (CNPP) are identified using gradient boosting Shapley additive explanations models. Results indicate that have become increasingly frequent, persistent, severe over past 35 years. With increasing risks events, greater CNPP observed northern regions compared southern regions. Throughout growing season, caused by initially increase, peak summer, then gradually decrease. influenced events. From north south, dominating shift sequentially daytime hot dry day‐night finally nighttime This study explores threats posed provides new insights into China, supporting climate‐adaptive agricultural development.

Язык: Английский

Процитировано

0
Soil moisture deficits triggered by increasing compound drought and heat events during the growing season in Arid Central Asia DOI
Qian Wang, Changchun Xu, Jin Long

и другие.

Journal of Hydrology, Год журнала: 2025, Номер 660, С. 133397 - 133397

Опубликована: Апрель 29, 2025

Язык: Английский

Процитировано

0
Strategies for combating climate extremes in a semi-arid region in Austria DOI Creative Commons
Hermine Mitter, Bernadette Kropf

Journal of Environmental Management, Год журнала: 2025, Номер 386, С. 125821 - 125821

Опубликована: Май 15, 2025

Язык: Английский

Процитировано

0
Global aging exacerbates heat exposure risk across diverse socioeconomic pathways DOI Creative Commons
Xiaohong Chen, Song Leng, Zhaowu Yu

и другие.

Geography and sustainability, Год журнала: 2025, Номер unknown, С. 100318 - 100318

Опубликована: Май 1, 2025

Язык: Английский

Процитировано

0
Assessment of the spatial and temporal dynamics of food system resilience and its response to natural hazards DOI

Xinjun He,

Yiping Fang, Baosheng Wang

и другие.

International Journal of Disaster Risk Reduction, Год журнала: 2024, Номер 112, С. 104781 - 104781

Опубликована: Авг. 24, 2024

Язык: Английский

Процитировано

3
Assessing the impacts of temperature extremes on agriculture yield and projecting future extremes using machine learning and deep learning approaches with CMIP6 data DOI Creative Commons
Firdos Khan, Yuei‐An Liou, Gunter Spöck

и другие.

International Journal of Applied Earth Observation and Geoinformation, Год журнала: 2024, Номер 132, С. 104071 - 104071

Опубликована: Авг. 1, 2024

Climate change, particularly extreme weather events, has significantly affected various sectors, including agriculture, human health, water resources, sea levels, and ecosystems. It is anticipated that the intensity, duration, frequency of these extremes will escalate in future. This study aims to discover association between temperature agricultural yield project using machine learning (ML) deep (DL) models with CMIP6 (Coupled Model Intercomparison Project Phase 6) data under two SSPs (Shared Socioeconomic Pathways). A bi-wavelet coherence technique employed investigate association, providing detailed information both time domains for period 1980–2014. Various ML DL are trained tested periods 1985–2004 2005–2014, respectively, gradient boosting chosen projecting based on its superior performance. Mann-Kendall test used trend analysis projected extremes. The results indicate strong negative positive associations TN10p (Cold nights) TN90p (Warm nights), wheat production. Additionally, there a long-term CSDI Spell Duration Indicator) WSDI rice yield. Projected show an increase decrease SSP2-4.5 SSP5-8.5, DTR (Diurnal Temperature Range) at most stations. future stations, exceptions such as Muree station where it decreases during 2025–2049 then increases SSPs. Projections TXn (annual or monthly minimum value daily maximum temp) future, exhibiting lowest close zero, while average around 20 °C Khanpur station. Trend reveals increasing TR20 (Tropical decreasing durations These findings hold implications policymakers stakeholders departments, resources management.

Язык: Английский

Процитировано

2
Ground Urban Heat Island: Strengthening the Connection Between Spaceborne Thermal Observations and Urban Heat Risk Management DOI Creative Commons
Leiqiu Hu, Christopher K. Uejio

GeoHealth, Год журнала: 2024, Номер 8(7)

Опубликована: Июль 1, 2024

As urbanization progresses under a changing climate, urban populations face increasing threats from chronically higher heat exposures and more frequent extreme events. Understanding the complex thermal exposure patterns becomes crucial for effective risk management. The spatial advantage of satellite observations positions surface islands (SUHI) as primary measure such applications at city scale. However, satellite-inherent biases pose considerable uncertainties. To improve representation human-relevant exposure, this study proposes simple but satellite-based measure- ground island (GUHI), focusing solely on radiant temperatures elements. Leveraging ECOSTRESS land temperature product radiation-based statistical downscaling, diurnally representative GUHIs were evaluated over NYC. findings reveal that overall GUHI is consistently warmer than SUHI diurnally. exhibits contrasts with SUHI, primarily influenced by vegetation coverage. Various indicators associated structures materials examined, showing important dissimilar roles in shaping dynamics SUHI. This highlights value compared to air while addressing uncertainties widely adopted practices using them. By improving depiction human-related Earth observations, research offers valuable insight reliable measures address urgent requirements management globally.

Язык: Английский

Процитировано

1
Ground Urban Heat Island: Strengthening the Connection between Spaceborne Thermal Observations and Urban Heat Managemen DOI
Leiqiu Hu, Christopher K. Uejio

Опубликована: Янв. 1, 2024

Download This Paper Open PDF in Browser Share: Permalink Using these links will ensure access to this page indefinitely Copy URL DOI

Язык: Английский

Процитировано

0
Projections of urban land exposure to drought and flood in China DOI
Huiqing Han, Jie Zhao,

Ying Cong

и другие.

Environmental Monitoring and Assessment, Год журнала: 2024, Номер 197(1)

Опубликована: Дек. 6, 2024

Язык: Английский

Процитировано

0
Observed Changes and Projected Risks of Hot–Dry/Hot–Wet Compound Events in China DOI Creative Commons

Yifan Zou,

Xiaomeng Song

Remote Sensing, Год журнала: 2024, Номер 16(22), С. 4208 - 4208

Опубликована: Ноя. 12, 2024

Compound extreme events can cause serious impacts on both the natural environment and human beings. This work aimed to explore changes in compound drought–heatwave heatwave–extreme precipitation (i.e., CDHEs CHPEs) across China using daily-scale gauge-based meteorological observations, examine their future projections potential risks Coupled Model Intercomparison Project (CMIP6) under shared socioeconomic pathway (SSP) scenarios SSP1-2.6, SSP2-4.5, SSP5-8.5). The results show following: (1) frequencies of CHPEs showed a significant increasing trend from 1961 2020, with contrasting trends between first half second period decrease 1990 an increase 1991 2020). Similar were observed for four intensity levels mild, moderate, severe, extreme) CHPEs. (2) All three SSP will trends, especially higher emission scenarios. Moreover, projected intensities gradually increase, levels. (3) exposure population (POP) Gross Domestic Product (GDP) be concentrated mainly China’s coastal areas. GDP exposures reach highest values SSP5-8.5, while POP peak SSP2-4.5 respectively. Our findings offer scientific technological support actively mitigate climate change risks.

Язык: Английский

Процитировано

0