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相关概念视频

The Nitrogen Cycle01:49

The Nitrogen Cycle

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Nitrogen atoms, present in all proteins and DNA, are recycled between abiotic and biotic components of the ecosystem. However, the primary form of nitrogen on Earth is nitrogen gas, which cannot be used by most animals and plants. Thus, nitrogen gas must first be converted into a usable form by nitrogen-fixing bacteria before it can be cycled through other living organisms. The use of nitrogen-containing fertilizers and animal waste products in human agriculture has greatly influenced the...
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Selected Data About Geographic Locations01:25

Selected Data About Geographic Locations

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Geographic Information Systems (GIS) rely on two core types of data: spatial data and attribute data.Spatial DataSpatial data defines the physical location of features within a coordinate system, typically expressed in terms of latitude and longitude. It provides precise positioning for elements like roads, rivers, or buildings.Attribute DataAttribute data complements spatial data by adding descriptive information about these features. For example, a road's spatial data includes its start and...
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Inorganic Nitrogen Assimilation01:22

Inorganic Nitrogen Assimilation

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Nitrogen is an essential element in biological systems, forming a crucial component of proteins, nucleic acids, and other cellular constituents. Many bacteria and archaea acquire nitrogen in the form of nitrate (NO₃⁻) or ammonia (NH₃), which are then assimilated into biomolecules through specific enzymatic pathways.Assimilatory Nitrate ReductionWhen nitrate enters the cell, it undergoes a two-step reduction process known as assimilatory nitrate reduction. Initially, the enzyme...
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Overview of Nitrogen Metabolism01:20

Overview of Nitrogen Metabolism

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Nitrogen is a very important element for life because it is a major constituent of proteins and nucleic acids. It is a macronutrient, and in nature, it is recycled from organic compounds and stored in the form of  ammonia, ammonium ions, nitrate, nitrite, or  nitrogen gas by many metabolic processes. Many of these metabolic processes are carried out only by prokaryotes.
The largest pool of nitrogen available in the terrestrial ecosystem is gaseous nitrogen (N2) from the air, but this...
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Key Elements for Plant Nutrition

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Like all living organisms, plants require organic and inorganic nutrients to survive, reproduce, grow and maintain homeostasis. To identify nutrients that are essential for plant functioning, researchers have leveraged a technique called hydroponics. In hydroponic culture systems, plants are grown—without soil—in water-based solutions containing nutrients. At least 17 nutrients have been identified as essential elements required by plants. Plants acquire these elements from the...
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相关实验视频

Updated: Jul 18, 2025

Measurement of Greenhouse Gas Flux from Agricultural Soils Using Static Chambers
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Measurement of Greenhouse Gas Flux from Agricultural Soils Using Static Chambers

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全球年度土壤二氧化排放的数据驱动建模:空间模式和属性.

Jiaqiang Liao1, Yuanyuan Huang2, Zhaolei Li3

  • 1Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China; College of Resources and Environment, University of Chinese Academy of Sciences, Beijing, China.

The Science of the total environment
|August 25, 2023
PubMed
概括

这项研究使用现场数据绘制了全球土壤二氧化 (N2O) 排放的地图,显示出比以前的模型更低的排放率. 土壤的可用性,而不是气候,是N2O排放的关键驱动因素.

关键词:
农田是农作物种植的土地.数据驱动模型是基于数据的模型.森林的森林森林的森林.草原是一片草地.土壤的氧化氧化物.空间模式的空间模式

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Estimating Sediment Denitrification Rates Using Cores and N2O Microsensors
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Use of Principal Components for Scaling Up Topographic Models to Map Soil Redistribution and Soil Organic Carbon
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相关实验视频

Last Updated: Jul 18, 2025

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11:50

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Estimating Sediment Denitrification Rates Using Cores and N2O Microsensors
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Estimating Sediment Denitrification Rates Using Cores and N2O Microsensors

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科学领域:

  • 环境科学 环境科学
  • 土壤科学 土壤科学
  • 大气化学 大气化学

背景情况:

  • 以前的全球陆地土壤二氧化 (N2O) 排放估计是分歧的,观察数据不匹配.
  • 准确的N2O排放映射对于了解其在气候变化中的作用和制定减缓策略至关重要.

研究的目的:

  • 通过广泛的现场观测,生成地面土壤N2O排放的数据驱动全球地图.
  • 确定影响全球N2O排放变化的关键环境变量.
  • 将数据驱动的估计与以前基于模型的评估进行比较.

主要方法:

  • 利用了5549个全球实地观测土壤N2O排放的数据集.
  • 采用随机森林方法,创建每年土壤N2O排放率的空间显式地图.
  • 量化了各种因素的预测重要性,包括土壤基质 (酸盐,,肥料) 和气候变量 (温度,降水).

主要成果:

  • 全球平均土壤N2O排放率估计为0.059 ± 0.006 g N m−2年−1,低于之前的模型组合估计.
  • 土壤N2O排放量在北半球比南半球更高.
  • 耕地土壤的年平均N2O排放率比森林 (0.039 ± 0.004 g N m−2 年−1) 和草原 (0.045 ± 0.007 g N m−2 年−1) 高 (0.094 ± 0.009 g N m−2 年−1).
  • 土壤基 (酸盐,,肥料) 在预测N2O排放方面比年平均温度和降水更有影响.

结论:

  • 基于广泛现场观测的数据驱动模型提供了更可靠的估计全球土壤N2O排放.
  • 以往基于工艺的模型可能会高估N2O排放量,因为验证数据有限,假设简化.
  • 全球现场观测对于限制和改进基于过程的模型来准确预测N2O排放至关重要.