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相关概念视频

Global Climate Change01:50

Global Climate Change

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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.
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What is Climate?01:16

What is Climate?

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Climate refers to the prevailing weather conditions in a specific area over an extended period. As the saying goes, “Climate is what you expect. Weather is what you get.” Climate is influenced by geographic factors, such as latitude, terrain, and proximity to bodies of water.
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Biological Clocks and Seasonal Responses02:45

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The circadian—or biological—clock is an intrinsic, timekeeping, molecular mechanism that allows plants to coordinate physiological activities over 24-hour cycles called circadian rhythms. Photoperiodism is a collective term for the biological responses of plants to variations in the relative lengths of dark and light periods. The period of light-exposure is called the photoperiod.
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Light Acquisition

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In order to produce glucose, plants need to capture sufficient light energy. Many modern plants have evolved leaves specialized for light acquisition. Leaves can be only millimeters in width or tens of meters wide, depending on the environment. Due to competition for sunlight, evolution has driven the evolution of increasingly larger leaves and taller plants, to avoid shading by their neighbors with contaminant elaboration of root architecture and mechanisms to transport water and nutrients.
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Every organism has an optimum temperature range within which healthy growth and physiological functioning can occur. At the ends of this range, there will be a minimum and maximum temperature that interrupt biological processes.
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相关实验视频

Updated: Jul 11, 2025

Using Generative Art to Convey Past and Future Climate Transitions
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在未来气候变化下,变暖增加了春季现象学模型之间的差异.

Yunhua Mo1, Xiran Li2, Yahui Guo2

  • 1College of Water Sciences, Beijing Normal University, Beijing, China.

Frontiers in plant science
|November 8, 2023
PubMed
概括

在气候变化下预测植物现象学至关重要. 这项研究评估了13个模型,发现M1模型 (光周期和温度) 的表现最好,在各种场景中预测不同.

关键词:
在PEP72525中,我们可以使用PEP725单一服务平台场景 单一服务平台场景气候变化 气候变化 气候变化未来的预测 未来的预测春季现象学模型 春季现象学模型

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科学领域:

  • 植物科学 植物科学
  • 生态生态学 生态生态学
  • 气候变化研究研究 气候变化研究

背景情况:

  • 现象学模型可以预测植物对环境因素的反应.
  • 了解气候变化对现象学的影响至关重要.
  • 不同气候场景中的模型性能仍未得到充分研究.

研究的目的:

  • 在两个对比的气候变化场景 (SSP126和SSP585) 下评估13个春季现象学模型的预测性能.
  • 为了比较休眠阶段和驱动因素对模型准确性的影响.
  • 预测德国从2021年到2100年的春季现象学变化.

主要方法:

  • 使用观测和气象数据对13个春季现象学模型 (六个单相,七个双相) 的参数化.
  • 使用SSP126和SSP585情景的气候数据预测春季现象 (生长季节开始 - SOS).
  • 模型性能的比较,包括休眠影响和驱动因素的影响.

主要成果:

  • 所有模型的表现都优于NULL模型,平均SOS预测相关性>0.72.
  • 由光周期和强迫温度驱动的M1模型显示出跨物种的最佳性能.
  • 在SSP126下,SOS最初前进,然后延迟;在SSP585下,SOS前进了~0.14天/年.
  • 模型预测变化 (标准偏差) 显著增加,特别是在本世纪晚些时候的双相和仅温度模型中.

结论:

  • 在气候变化下,M1模型为春季现象学提供了可靠的预测.
  • 未来的现象学模型应该包含内臭释放机制,以提高准确性.
  • 休眠阶段和驱动因素在不同的气候场景下显著影响模型性能.