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 are Estimates?01:06

What are Estimates?

8.9K
It isn't easy to measure a parameter such as the mean height or the mean weight of a population. So, we draw samples from the population and calculate the mean height or mean weight of the individuals in the sample. This sample data acts as a representative measure of the population parameter. These sample statistics are known as estimates. 
The estimate for the mean of a sample is denoted by ͞x, whereas the mean of the population is designated as μ. Further, parameters such...
8.9K
Frequency-dependent Selection01:21

Frequency-dependent Selection

24.2K
When the fitness of a trait is influenced by how common it is (i.e., its frequency) relative to different traits within a population, this is referred to as frequency-dependent selection. Frequency-dependent selection may occur between species or within a single species. This type of selection can either be positive—with more common phenotypes having higher fitness—or negative, with rarer phenotypes conferring increased fitness.
24.2K
Estimation of k and VD of Aminoglycosides01:20

Estimation of k and VD of Aminoglycosides

253
Aminoglycosides are a class of antibiotics used to treat various bacterial infections. Clinicians must determine the elimination rate constant (k) and volume of distribution (VD) to optimize therapeutic efficacy and minimize toxicity. The k value represents the rate at which the drug is removed from the body, and the VD reflects the degree to which the drug distributes into body tissues. Accurately estimating these parameters allows healthcare professionals to tailor drug dosing to individual...
253
What is a Frequency Distribution00:51

What is a Frequency Distribution

27.8K
A frequency is the number of times a value of the data occurs. The sum of all the frequency values represents the total number of students included in the sample. It is commonly used to group data of quantitative types. Frequency distributions can be displayed in a table, histogram, line graph, dot plot, or pie chart, just to name a few. A histogram is a graphical representation of tabulated frequencies, shown as adjacent rectangles, erected over discrete intervals (bins), with an area equal to...
27.8K
Mean From a Frequency Distribution01:11

Mean From a Frequency Distribution

23.1K
Sometimes, data gathered from an experiment on a large sample or population are organized into concise tables. In such cases, the frequency of the quantitative data set is plotted in the form of a table. Or else, the data values are grouped into the quantity’s intervals, which form classes, and their respective frequencies are known. That is, the data values are distributed over different categories or classes. This is known as frequency distribution.
When such a data set is encountered,...
23.1K
How Data are Classified: Categorical Data01:11

How Data are Classified: Categorical Data

45.2K
A variable, usually notated by capital letters such as X and Y, is a characteristic or measurement that can be determined for each member of a population. Data are the actual values of variables. They may be numbers, or they may be words. Datum is a single value.
Data are classified based on whether they are measurable or not. Categorical data cannot be measured; instead, it can be divided into categories. For example, if Y denotes a person's party affiliation, some examples of Y include...
45.2K

You might also read

Related Articles

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

Sort by
Same author

Vertebrate biodiversity via eDNA at the air-water interface.

iScience·2026
Same author

Assessing morphological, developmental, and genetic responses of Hydropsychid caddisflies to Cry1Ab exposure.

Environmental entomology·2026
Same author

Mapping the marine distribution of eulachon (Thaleichthys pacificus) in the Northeast Pacific using environmental DNA.

Communications biology·2026
Same author

Understanding practical barriers to the global adoption of environmental DNA (eDNA) methods, tools, and standards.

BMC research notes·2026
Same author

Fast, Flexible, Feasible: A Transparent Framework for Evaluating eDNA Workflow Trade-Offs in Resource-Limited Settings.

Molecular ecology resources·2026
Same author

eDNA reveals spatial differences in species composition of protected rockfishes.

PloS one·2025

Related Experiment Video

Updated: Feb 14, 2026

Chromatin Immunoprecipitation ChIP Protocol for Low-abundance Embryonic Samples
12:47

Chromatin Immunoprecipitation ChIP Protocol for Low-abundance Embryonic Samples

Published on: August 29, 2017

16.4K

Estimating Organism Abundance Using Within-Sample Haplotype Frequencies of eDNA Data.

Pedro F P Brandão-Dias1, Gledis Guri1, Megan R Shaffer1

  • 1School of Marine and Environmental Affairs, University of Washington, Seattle, WA, USA.

Molecular Ecology Resources
|February 13, 2026
PubMed
Summary
This summary is machine-generated.

Environmental DNA (eDNA) analysis can now estimate species abundance. By comparing haplotype frequencies within samples to population frequencies, researchers can infer the number of individuals contributing to eDNA samples.

Keywords:
allelesindividualslikelihoodmetabarcodingpopulation genetics

More Related Videos

Electrochemical Impedance Spectroscopy as a Tool for Electrochemical Rate Constant Estimation
08:41

Electrochemical Impedance Spectroscopy as a Tool for Electrochemical Rate Constant Estimation

Published on: October 10, 2018

25.9K
Purification of Low-abundant Cells in the Drosophila Visual System
07:09

Purification of Low-abundant Cells in the Drosophila Visual System

Published on: September 26, 2018

6.7K

Related Experiment Videos

Last Updated: Feb 14, 2026

Chromatin Immunoprecipitation ChIP Protocol for Low-abundance Embryonic Samples
12:47

Chromatin Immunoprecipitation ChIP Protocol for Low-abundance Embryonic Samples

Published on: August 29, 2017

16.4K
Electrochemical Impedance Spectroscopy as a Tool for Electrochemical Rate Constant Estimation
08:41

Electrochemical Impedance Spectroscopy as a Tool for Electrochemical Rate Constant Estimation

Published on: October 10, 2018

25.9K
Purification of Low-abundant Cells in the Drosophila Visual System
07:09

Purification of Low-abundant Cells in the Drosophila Visual System

Published on: September 26, 2018

6.7K

Area of Science:

  • Ecology
  • Genetics
  • Molecular Biology

Background:

  • Environmental DNA (eDNA) is valuable for detecting species and community composition.
  • Current eDNA methods struggle to accurately quantify species abundance or population structure.

Purpose of the Study:

  • To develop a method for estimating the number of individual contributors to eDNA samples.
  • To bridge population genetics theory with eDNA analysis for abundance estimation.

Main Methods:

  • Established a theoretical framework to approximate population haplotype frequencies from eDNA data.
  • Developed a maximum likelihood estimator to infer the number of contributors.
  • Validated the method using simulations with varying haplotype frequencies and noise levels.

Main Results:

  • The deviation between within-sample and population-level haplotype frequencies can estimate the number of individuals.
  • Accurate estimates are achievable with variable haplotypes, well-characterized population frequencies, and sufficient sample size.
  • The method allows for population frequency approximation without tissue-derived references.

Conclusions:

  • This novel method offers a new approach to quantifying species abundance using eDNA metabarcoding.
  • It complements existing molecular techniques by integrating population genetic principles.
  • The findings advance the utility of eDNA for ecological monitoring and biodiversity assessment.