Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Population Growth

Population Growth

Population size is dynamic, increasing with birth rates and immigration, and decreasing with death rates and emigration. In ideal conditions with unlimited resources, populations can increase exponentially, which plots as a J-shaped growth rate curve of population size against time. This type of curve is characteristic of newly-introduced invasive species, or populations that have suffered catastrophic declines and are rebounding.

Applications of Life Tables

Applications of Life Tables

Life tables are versatile across various fields, providing a quantitative basis for analyzing mortality and survival rates. Whether used by demographers, actuaries, epidemiologists, or sociologists, life tables offer valuable insights into the dynamics of life and death, facilitating informed decisions in public health, insurance, conservation, and beyond. Their broad applicability highlights the interconnectedness of demographic data with practical outcomes in everyday life and strategic...

Modeling with Differential Equations

Modeling with Differential Equations

Population dynamics can be described mathematically by considering the population size P(t) as a function of time. The rate of change of the population is then represented by the derivative of P(t). A simple assumption is that the rate of growth is proportional to the size of the population itself. This leads to an exponential growth model, where the population increases rapidly without bound. While this is a useful first approximation, it does not reflect realistic long-term...

Exponential Equations for Modeling Growth

Exponential Equations for Modeling Growth

Exponential models are essential for describing rapid, multiplicative changes in natural systems, such as population growth. When a population doubles at regular intervals, the process can be modeled using a suitable base. For instance, a bacterial culture that doubles every three hours follows the model n(t)=n0⋅2t/3, where n(t) is the population at the time t.A more general model uses the natural base e, especially for continuous growth. This takes the form n(t)=n0⋅ert, where r is the relative...

Energy Budgets

Energy Budgets

Organisms must balance energy intake with the energy required for growth, maintenance and reproduction. These trade-offs result in a variety of survivorship and reproductive strategies, including semelparity and iteroparity. Semelparous species, like annual plants, have only one reproductive episode in their lifetimes and consequently have short lifespans. Iteroparous species, by contrast, have many reproductive events during their lifetimes but have relatively few offspring. These two...

Life Histories

Life Histories

You might also read

Related Articles

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

Sort by

Same author

Laparoscopic versus open appendicectomy performed by adult general surgeons in pre-teenage years children: a single-centre experience.

Annals of the Royal College of Surgeons of England·2024

Same author

Analysing open birth interval distributions.

Population studies·2011

Same author

Estimating infant mortality trends from child survivorship data.

Population studies·2011

Same author

Accelerating India's fertility decline: the role of temporary contraceptive methods.

National Family Health Survey bulletin·2002

Same author

One and a half centuries of demographic transition in Nepal.

Journal of health, population, and nutrition·2002

Same author

The p107 tumor suppressor induces stable E2F DNA binding to repress target promoters.

Oncogene·2001

Same journal

Reconstructing birth histories using linked household data and the 1911 Census fertility survey.

Population studies·2026

Same journal

Perceptions of infertility: The roles of age, knowledge, and motivated reasoning.

Population studies·2026

Same journal

The impact of education misreporting on education-specific mortality and educational inequalities in mortality: A scenario-based study.

Population studies·2026

Same journal

Social parenting and childlessness in Norway: Associations by sex and economic uncertainty.

Population studies·2026

Same journal

A review and evaluation of internal migration forecasting models.

Population studies·2026

Same journal

The generational health drift: A systematic review of evidence from the British birth cohort studies.

Population studies·2026

See all related articles

Search research articles

Related Experiment Video

Updated: May 27, 2026

Predicting the Effectiveness of Population Replacement Strategy Using Mathematical Modeling

Predicting the Effectiveness of Population Replacement Strategy Using Mathematical Modeling

Published on: July 4, 2007

Population dynamics based on birth intervals and parity progression.

¹a East-West Center , East-West Population Institute , Honolulu , Hawaii , U.S.A.

Population Studies

|November 15, 2011

Summary

This summary is machine-generated.

This study introduces a new population dynamics model based on birth intervals and parity progression, offering an alternative to stable population theory. The model effectively addresses challenges in analyzing birth interval and parity data.

More Related Videos

Optimized Staining and Proliferation Modeling Methods for Cell Division Monitoring using Cell Tracking Dyes

Optimized Staining and Proliferation Modeling Methods for Cell Division Monitoring using Cell Tracking Dyes

Published on: December 13, 2012

Related Experiment Videos

Last Updated: May 27, 2026

Predicting the Effectiveness of Population Replacement Strategy Using Mathematical Modeling

Predicting the Effectiveness of Population Replacement Strategy Using Mathematical Modeling

Published on: July 4, 2007

Optimized Staining and Proliferation Modeling Methods for Cell Division Monitoring using Cell Tracking Dyes

Optimized Staining and Proliferation Modeling Methods for Cell Division Monitoring using Cell Tracking Dyes

Published on: December 13, 2012

Area of Science:

Demography
Population Studies
Mathematical Biology

Background:

The 'later-longer-fewer' Chinese population policy emphasizes birth intervals and parity.
Existing population models like Lotka's stable population theory primarily focus on age structure.

Purpose of the Study:

To propose a novel formulation of population dynamics using birth intervals and parity progression.
To develop an alternative to Lotka's stable population theory by replacing age with parity and interval since last birth.
To analyze the effectiveness of this new approach in population projections and data analysis.

Main Methods:

Formulating population dynamics based on birth interval distributions and parity progression ratios.
Developing an alternative stable population model where age is replaced by parity and interval since last birth.
Conducting a numerical comparison between the proposed model and Lotka's model.

Main Results:

The proposed model provides population projections based on birth interval and parity data.
A numerical comparison revealed similarities and differences between the new model and Lotka's stable population theory.
The formulation offers a method to analyze birth interval and parity progression statistics, solving censoring and selection issues.

Conclusions:

The 'later-longer-fewer' policy can be modeled using birth intervals and parity progression.
The proposed parity-based model offers a valuable alternative to age-based stable population theory.
This approach enhances the analysis of demographic data, particularly concerning birth patterns and fertility.