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

Theories of Dissolution: Diffusion Layer Model01:15

Theories of Dissolution: Diffusion Layer Model

Dissolution, the process by which drug particles dissolve in a solvent, is explained by the diffusion layer model, a theoretical framework that simulates the absorption of oral drugs and allows us to analyze experimental data.
This process starts with a thin layer, saturated with the drug, forming at the interface between the solid and liquid. The solute then diffuses from this layer into the main solution. The Noyes-Whitney equation suggests that the rate of dissolution relies on the diffusion...
Pharmacodynamic Models: Overview01:27

Pharmacodynamic Models: Overview

Pharmacodynamic (PD) responses describe the interaction between a drug and its biological target, culminating in a physiological effect. These responses can be classified into different types: continuous variables, such as blood glucose levels; categorical outcomes, like survival rates; and time-to-event metrics, such as disease progression. Understanding and modeling PD responses are critical for optimizing drug efficacy and safety.PD models describe the relationship between drug concentration...
Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving01:29

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving

Mechanistic models play a crucial role in algorithms for numerical problem-solving, particularly in nonlinear mixed effects modeling (NMEM). These models aim to minimize specific objective functions by evaluating various parameter estimates, leading to the development of systematic algorithms. In some cases, linearization techniques approximate the model using linear equations.
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...
Models of Health Promotion and Illness Prevention I01:25

Models of Health Promotion and Illness Prevention I

A model is a theoretical way to understand a concept or an idea. Models can overcome barriers to health regardless of diverse economic and cultural backgrounds. In addition, models make the task easier by providing different ways to approach complex issues. There are two major health promotion models: the health belief model and the health promotion model.
The health belief model (HBM) attempts to predict health-related behavior in specific belief patterns. According to the HBM, a person's...
Models, Theories, and Laws01:16

Models, Theories, and Laws

Scientists frequently use models to help them comprehend a specific collection of phenomena. In physics, a model is a condensed version of a physical system that is too complex to study thoroughly. One such example is the light wave model; unlike water waves, light waves are typically invisible to us. Nonetheless, it is helpful to think of light as being composed of waves, since investigations show that light behaves like water waves. Since it is impossible to visually see what is genuinely...
Mechanistic Models: Compartment Models in Individual and Population Analysis01:23

Mechanistic Models: Compartment Models in Individual and Population Analysis

Mechanistic models are utilized in individual analysis using single-source data, but imperfections arise due to data collection errors, preventing perfect prediction of observed data. The mathematical equation involves known values (Xi), observed concentrations (Ci), measurement errors (εi), model parameters (ϕj), and the related function (ƒi) for i number of values. Different least-squares metrics quantify differences between predicted and observed values. The ordinary least squares (OLS)...

You might also read

Related Articles

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

Sort by
Same author

Assessing the roles of nitrogen, biomass, and niche dimensionality as drivers of species loss in grassland communities.

Proceedings of the National Academy of Sciences of the United States of America·2022
Same author

An experimental test of the area-heterogeneity tradeoff.

Proceedings of the National Academy of Sciences of the United States of America·2020
Same author

Heterogeneity-diversity relationships in sessile organisms: a unified framework.

Ecology letters·2019
Same author

Mechanisms of seed mass variation along resource gradients.

Ecology letters·2018
Same author

Dispersal increases ecological selection by increasing effective community size.

Proceedings of the National Academy of Sciences of the United States of America·2018
Same author

Seed mass diversity along resource gradients: the role of allometric growth rate and size-asymmetric competition.

Ecology·2018

Related Experiment Video

Updated: Jun 19, 2026

The HoneyComb Paradigm for Research on Collective Human Behavior
06:48

The HoneyComb Paradigm for Research on Collective Human Behavior

Published on: January 19, 2019

A general framework for neutral models of community dynamics.

Omri Allouche1, Ronen Kadmon

  • 1Department of Evolution, Systematics and Ecology, Institute of Life Sciences, The Hebrew University of Jerusalem, Givat-Ram, Jerusalem 91904, Israel. omri.allouche@gmail.com

Ecology Letters
|October 23, 2009
PubMed
Summary

This study introduces a new framework for neutral models in community ecology, unifying existing theories and explaining diverse species diversity patterns. The dispersal-limited multinomial distribution robustly describes abundance, regardless of underlying dynamics.

More Related Videos

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

Experimental Protocol for Manipulating Plant-induced Soil Heterogeneity

Published on: March 13, 2014

Related Experiment Videos

Last Updated: Jun 19, 2026

The HoneyComb Paradigm for Research on Collective Human Behavior
06:48

The HoneyComb Paradigm for Research on Collective Human Behavior

Published on: January 19, 2019

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

Experimental Protocol for Manipulating Plant-induced Soil Heterogeneity

Published on: March 13, 2014

Area of Science:

  • Ecology
  • Theoretical Ecology
  • Community Dynamics

Background:

  • Neutral models are vital in ecology but limited to simple dynamics, ignoring ecosystem complexity.
  • Existing models fail to capture the full spectrum of ecological phenomena and empirical patterns.

Purpose of the Study:

  • To present a novel analytical framework for neutral models that unifies existing theories.
  • To extend the applicability of neutral models to a wider range of ecological phenomena and empirical patterns.
  • To investigate the robustness of the dispersal-limited multinomial distribution in ecological communities.

Main Methods:

  • Developed a new analytical framework extending the concept of neutrality to fitness equivalence.
  • Applied the framework to explain diverse empirical patterns of species diversity.
  • Analyzed abundance distributions across various ecological scenarios.

Main Results:

  • The new framework explains positive, negative, and unimodal productivity-diversity relationships.
  • It accounts for gradual and delayed species diversity declines with habitat loss.
  • It describes positive and negative species diversity responses to habitat heterogeneity.
  • The dispersal-limited multinomial distribution consistently describes abundance, irrespective of specific dynamics.

Conclusions:

  • Ecological communities may be regulated by a simpler set of fundamental mechanisms than previously assumed.
  • The dispersal-limited multinomial distribution is a robust descriptor of abundance, limiting its use for inferring specific community dynamics.
  • The enhanced neutral model framework offers a more comprehensive approach to understanding ecological complexity.