Related Experiment Video

Updated: Apr 22, 2026

The Use of High-resolution Infrared Thermography HRIT for the Study of Ice Nucleation and Ice Propagation in Plants
09:36

The Use of High-resolution Infrared Thermography HRIT for the Study of Ice Nucleation and Ice Propagation in Plants

Published on: May 8, 2015

8.9K

Evidence for a weakening relationship between interannual temperature variability and northern vegetation activity

Shilong Piao1, Huijuan Nan2, Chris Huntingford3

  • 11] Key Laboratory of Alpine Ecology and Biodiversity, Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing 100085, China [2] Sino-French Institute for Earth System Science, College of Urban and Environmental Sciences, Peking University, Beijing 100871, China [3] CAS Center for Excellence in Tibetan Plateau Earth Sciences,Chinese Academy of Sciences, Beijing 100085, China.

Nature Communications
|October 17, 2014
PubMed

More Related Videos

Simulating Temperature in a Soil Incubation Experiment08:39

Simulating Temperature in a Soil Incubation Experiment

Published on: October 28, 2022

5.1K
Author Spotlight: Leaf Trait Analysis for Climate and Ecology Reconstruction in Modern and Ancient Plant Communities10:14

Author Spotlight: Leaf Trait Analysis for Climate and Ecology Reconstruction in Modern and Ancient Plant Communities

Published on: October 25, 2024

3.2K

Related Concept Videos

Global Climate Change01:50

Global Climate Change

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.
24.3K
Responses to Heat and Cold Stress02:45

Responses to Heat and Cold Stress

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.
13.4K
Threats to Biodiversity01:50

Threats to Biodiversity

There have been five major extinction events throughout geological history, resulting in the elimination of biodiversity, followed by a rebound of species that adapted to the new conditions. In the current geological epoch, the Holocene, there is a sixth extinction event in progress. This mass extinction has been attributed to human activities and is thus provisionally called the Anthropocene. In 2019 the human population reached 7.7 billion people and is projected to comprise 10 billion by...
21.6K
Adaptations that Reduce Water Loss01:57

Adaptations that Reduce Water Loss

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.
24.2K
Microbes and Climate Change01:27

Microbes and Climate Change

Microorganisms are pivotal agents in Earth's biogeochemical cycles, significantly influencing climate dynamics through their metabolic activities. These microbes modulate the levels of key greenhouse gases by both contributing to and helping mitigate climate change.Microbial Contributions to Greenhouse Gas EmissionsRising global temperatures accelerate microbial metabolism, which, in turn, speeds up the decomposition of organic matter. This process releases carbon dioxide (CO₂) through...
81
Calculating and Interpreting the Linear Correlation Coefficient01:11

Calculating and Interpreting the Linear Correlation Coefficient

The correlation coefficient, r, developed by Karl Pearson in the early 1900s, is numerical and provides a measure of strength and direction of the linear association between the independent variable, x, and the dependent variable, y. Hence, it is also known as the Pearson product-moment correlation coefficient. It can be calculated using the following equation:
6.4K