Jove
Visualize
联系我们
JoVE
x logofacebook logolinkedin logoyoutube logo
关于 JoVE
概览领导团队博客JoVE 帮助中心
作者
出版流程编辑委员会范围与政策同行评审常见问题投稿
图书馆员
用户评价订阅访问资源图书馆顾问委员会常见问题
研究
JoVE JournalMethods CollectionsJoVE Encyclopedia of Experiments存档
教育
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab Manual教师资源中心教师网站
使用条款与条件
隐私政策
政策

相关概念视频

Overview of Archaea01:29

Overview of Archaea

155
Archaea, named after the Archaean eon, represent a unique domain of life, distinct from bacteria and eukaryotes, with remarkable traits. Their cellular and molecular features, ecological adaptability, and industrial relevance highlight their importance in understanding life processes and leveraging biotechnology.Cellular and Molecular CharacteristicsA defining feature of archaea is their unique membrane composition. Archaeal membranes contain ether-linked isoprenoid lipids, which confer...
155
Adaptations that Reduce Water Loss01:57

Adaptations that Reduce Water Loss

26.4K
Though evaporation from plant leaves drives transpiration, it also results in loss of water. Because water is critical for photosynthetic reactions and other cellular processes, evolutionary pressures on plants in different environments have driven the acquisition of adaptations that reduce water loss.
26.4K
Green Algae01:21

Green Algae

219
Green algae, also referred to as chlorophytes, are different from red algae in having the chloroplasts containing chlorophylls a and b, which give them their distinct green hue. However, they lack phycobiliproteins, preventing them from developing the red or blue-green pigmentation seen in red algae. In terms of photosynthetic pigment composition, green algae closely resemble plants and share a close evolutionary relationship with them. Taxonomically Green algae belong to Phylum Chlorophyta in...
219
Bioremediation00:46

Bioremediation

20.2K
Bioremediation is the use of prokaryotes, fungi, or plants to remove pollutants from the environment. This process has been used to remove harmful toxins in groundwater as a byproduct of agricultural run-off and also to clean up oil spills.
20.2K
Global Climate Change01:50

Global Climate Change

24.8K
Throughout its ~4.5 billion year history, the Earth has experienced periods of warming and cooling. However, the current drastic increase in global temperatures is well outside of the Earth’s cyclic norms, and evidence for human-caused global climate change is compelling. Paleoclimatology, the study of ancient climate conditions, provides ample evidence for human-caused global climate change by comparing recent conditions with those in the past.
24.8K
Carbon-dioxide Fixation01:28

Carbon-dioxide Fixation

89
Carbon dioxide fixation in prokaryotes enables the assimilation of inorganic carbon into organic molecules, supporting biosynthetic pathways, sustaining ecosystems, and contributing to the global carbon cycle. It also has industrial applications in carbon capture and bioproduct synthesis. Autotrophic organisms rely on this process to utilize CO₂ as a carbon source in diverse environments.The Calvin CycleThe Calvin cycle is the most widespread carbon fixation mechanism, primarily used by...
89

您也可能阅读

相关文章

通过共同作者、期刊和引用图与本文相关的文章。

排序
Same author

Arbuscular mycorrhizal fungal interactions bridge the support of root-associated microbiota for slope multifunctionality in an erosion-prone ecosystem.

iMeta·2024
Same author

Coastal conversion alters topsoil carbon, nitrogen and phosphorus stocks and stoichiometric balances in subtropical coastal wetlands.

The Science of the total environment·2024
Same author

Ecosystem Microbiome Science.

mLife·2024
Same author

Global biogeography of microbes driving ocean ecological status under climate change.

Nature communications·2024
Same author

Variations and trade-offs in leaf and culm functional traits among 77 woody bamboo species.

BMC plant biology·2024
Same author

Assembly and succession of the phyllosphere microbiome and nutrient-cycling genes during plant community development in a glacier foreland.

Environment international·2024

相关实验视频

Updated: Sep 16, 2025

Visualizing Methane-Cycling Microbial Dynamics in Coastal Wetlands
07:26

Visualizing Methane-Cycling Microbial Dynamics in Coastal Wetlands

Published on: January 31, 2025

455

将植被变化与北极甲排放量联系起来.

Xiaoqi Zhou1, Wensheng Xiao1, Josep Peñuelas2

  • 1Zhejiang Tiantong Forest Ecosystem National Observation and Research Station, Zhejiang Zhoushan Island Ecosystem Observation and Research Station, Institute of Eco-Chongming, School of Ecological and Environmental Sciences, East China Normal University, Shanghai 200241, China.

Trends in plant science
|July 5, 2025
PubMed
概括

北极甲排放不确定,影响气候模型. 将植被数据与机器学习相结合,可以改善甲预测,从而改善气候政策.

关键词:
北极地区 北极地区 北极地区甲的外流流量甲过程模型模型植被类型 植物类型

更多相关视频

Measuring Dissolved Methane in Aquatic Ecosystems Using An Optical Spectroscopy Gas Analyzer
05:00

Measuring Dissolved Methane in Aquatic Ecosystems Using An Optical Spectroscopy Gas Analyzer

Published on: July 26, 2024

602
Design and Use of a Full Flow Sampling System FFS for the Quantification of Methane Emissions
08:18

Design and Use of a Full Flow Sampling System FFS for the Quantification of Methane Emissions

Published on: June 12, 2016

16.9K

相关实验视频

Last Updated: Sep 16, 2025

Visualizing Methane-Cycling Microbial Dynamics in Coastal Wetlands
07:26

Visualizing Methane-Cycling Microbial Dynamics in Coastal Wetlands

Published on: January 31, 2025

455
Measuring Dissolved Methane in Aquatic Ecosystems Using An Optical Spectroscopy Gas Analyzer
05:00

Measuring Dissolved Methane in Aquatic Ecosystems Using An Optical Spectroscopy Gas Analyzer

Published on: July 26, 2024

602
Design and Use of a Full Flow Sampling System FFS for the Quantification of Methane Emissions
08:18

Design and Use of a Full Flow Sampling System FFS for the Quantification of Methane Emissions

Published on: June 12, 2016

16.9K

科学领域:

  • 环境科学 环境科学
  • 气候科学 气候科学
  • 地球系统科学 地球系统科学

背景情况:

  • 北极甲排放是全球气候模型中不确定性的重要来源.
  • 准确预测这些排放对于理解和缓解气候变化至关重要.

研究的目的:

  • 为了提高北极甲排放预测的准确性.
  • 整合植被数据和机器学习以进行增强的基于过程的建模.

主要方法:

  • 利用机器学习算法来分析植被数据.
  • 开发了一种结合生态和计算方法的新方法,用于甲排放建模.

主要成果:

  • 与传统模型相比,拟议的方法在预测北极甲排放方面显示出更高的可靠性.
  • 更好地了解植被动态和北极甲释放之间的关系.

结论:

  • 结合植被数据和机器学习,为减少北极甲排放估计的不确定性提供了一个有希望的途径.
  • 这种方法可以提供更强大的科学见解,为有效的全球气候变化减缓政策提供信息.