Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

What is Variation?01:14

What is Variation?

12.9K
Apart from the measures of central tendency, distribution, outliers, and the changing characteristics of data with time, an important characteristic of any data set is its variation or spread. In some data sets, the data values are concentrated closely near the mean; in others, the data values are more widely spread out from the mean.
The range, standard deviation, standard error, and variance are the different measures of variation.
Range: The range is the difference between its maximum and...
12.9K
Genetic Variation01:25

Genetic Variation

1.7K
Genetic variation is the diversity in DNA sequences found among individuals of the same species. This diversity is crucial for a species' survival because it helps organisms adapt to environmental changes. Genetic variation begins with fertilization, where an egg and sperm cell merge. Each of these cells carries 23 chromosomes, up to 46 in the fertilized egg. Chromosomes are long DNA strands that contain genes, the basic units of heredity.
Genes exist in different versions called alleles,...
1.7K
Variability: Analysis01:11

Variability: Analysis

1.1K
Measures of variability are statistical metrics that reveal the dispersion pattern within a dataset. They are pivotal in biostatistics, providing insights into the heterogeneity within health and biological data. Variability signifies the degree to which data points diverge from one another, helping researchers understand the potential range of values and associated uncertainty within the data.
The range is a simple measure of variability, indicating the difference between the highest and...
1.1K
Variation of Atmospheric Pressure01:18

Variation of Atmospheric Pressure

3.7K
Change in atmospheric pressure with height is particularly interesting. The decrease in atmospheric pressure with increasing altitude is due to the decreasing gravitational force per unit area as we move away from the surface of the earth.
Assuming the air temperature is constant at a given altitude and that the ideal gas law of thermodynamics describes the atmosphere to a good approximation, one can find the variation of atmospheric pressure with height.
Let p(y) be the atmospheric pressure at...
3.7K
Variation: Normal Distribution, Range, and Standard Deviation02:32

Variation: Normal Distribution, Range, and Standard Deviation

24.9K
In the field of psychology, there are several ways to organize measurements of a trait, feature, or characteristic (i.e., variables). Qualitative data, such as ethnicity, can be tabulated into a frequency count to provide information about the proportion, as well as the variety of groups in a sample or population. On the other hand, researchers can perform a wider set of calculations on quantitative data. The mean, mode, and median, for instance, are central tendency measures to identify a...
24.9K
Variation in Acceleration due to Gravity near the Earth's Surface01:20

Variation in Acceleration due to Gravity near the Earth's Surface

2.0K
An object's apparent weight is its weight measured by a spring balance at its location. It is different from its true weight, the force with which the Earth pulls it, because of the Earth's rotation. Mathematically, an object's apparent weight equals its true weight minus the centripetal force that keeps it in a circular motion along with the Earth's surface every 24 hours.
The difference between the true and apparent weights is proportional to the square of the Earth's...
2.0K

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

A Digital Twin Framework for Proactive Enterprise Management: Research on Operational Decision-making Integrating IoT Data and Computational Modeling.

Journal of visualized experiments : JoVE·2026
Same author

Comparative Evaluation of Germination Methods on the Nutritional and Sensory Profile of <i>Coix</i>.

Foods (Basel, Switzerland)·2026
Same author

PLANeT: Understanding and leveraging the genome of land plants for a sustainable future.

Cell·2026
Same author

A generative AI framework unifies human multi-omics to model aging, metabolic health, and intervention response.

Cell metabolism·2026
Same author

Electrochemical Oxy-Carbofunctionalization of Alkenes with Alcohols and 1,3-Dicarbonyl Compounds.

The Journal of organic chemistry·2026
Same author

China's National Botanical Gardens: An innovative model to support global biodiversity conservation and sustainable development.

Plant diversity·2026

Related Experiment Video

Updated: May 6, 2026

Measuring and Mapping Patterns of Soil Erosion and Deposition Related to Soil Carbonate Concentrations Under Agricultural Management
08:09

Measuring and Mapping Patterns of Soil Erosion and Deposition Related to Soil Carbonate Concentrations Under Agricultural Management

Published on: September 12, 2017

11.1K

Global variation in elevational diversity patterns.

Qinfeng Guo1, Douglas A Kelt, Zhongyu Sun

  • 1USDA FS, Eastern Forest Environmental Threat Assessment Center, Asheville, NC 28804, USA.

Scientific Reports
|October 26, 2013
PubMed
Summary
This summary is machine-generated.

Vertical biodiversity gradients, particularly along elevational gradients, show complex patterns. Most diversity peaks occur below mid-elevation, influenced by hemisphere, latitude, and mountain extent.

More Related Videos

Isolation and Analysis of Microbial Communities in Soil, Rhizosphere, and Roots in Perennial Grass Experiments
10:31

Isolation and Analysis of Microbial Communities in Soil, Rhizosphere, and Roots in Perennial Grass Experiments

Published on: July 24, 2018

58.3K
Experimental Protocol for Manipulating Plant-induced Soil Heterogeneity
08:16

Experimental Protocol for Manipulating Plant-induced Soil Heterogeneity

Published on: March 13, 2014

17.7K

Related Experiment Videos

Last Updated: May 6, 2026

Measuring and Mapping Patterns of Soil Erosion and Deposition Related to Soil Carbonate Concentrations Under Agricultural Management
08:09

Measuring and Mapping Patterns of Soil Erosion and Deposition Related to Soil Carbonate Concentrations Under Agricultural Management

Published on: September 12, 2017

11.1K
Isolation and Analysis of Microbial Communities in Soil, Rhizosphere, and Roots in Perennial Grass Experiments
10:31

Isolation and Analysis of Microbial Communities in Soil, Rhizosphere, and Roots in Perennial Grass Experiments

Published on: July 24, 2018

58.3K
Experimental Protocol for Manipulating Plant-induced Soil Heterogeneity
08:16

Experimental Protocol for Manipulating Plant-induced Soil Heterogeneity

Published on: March 13, 2014

17.7K

Area of Science:

  • Ecology
  • Biodiversity Science
  • Biogeography

Background:

  • Horizontal biodiversity gradients are well-studied.
  • Vertical diversity gradients (elevation, water depth) are gaining research interest.

Purpose of the Study:

  • Investigate elevational diversity patterns globally.
  • Compare patterns between Northern and Southern hemispheres and across latitudes.
  • Analyze factors influencing diversity peaks.

Main Methods:

  • Compiled data from 443 elevational gradients worldwide.
  • Analyzed diversity curves across diverse organisms.
  • Examined relationships between peak diversity elevation and gradient limits.

Main Results:

  • Most elevational diversity curves are positively skewed (peak diversity below mid-gradient).
  • Peak diversity elevation increases with lower sampling limits and, to a lesser extent, upper limits.
  • Hemispheric differences and variations across taxonomic groups were observed.

Conclusions:

  • Elevational diversity patterns exhibit global similarities and regional differences.
  • Mountain extent and taxonomic group inclusiveness influence pattern shapes.
  • Physical and physiological constraints likely drive varying diversity peaks among taxa.