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

Global Climate Change

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.

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...

You might also read

Related Articles

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

Sort by

Same author

Synthetic ecology of coastal ecosystems.

Cell reports·2026

Same author

In Science Journals.

Science (New York, N.Y.)·2026

Same author

Local drivers in accelerating North American heat stress.

Nature communications·2026

Same author

Sexual dimorphism in the colonic microbiome and host's transcriptomics profiles of a murine model of multiple sclerosis.

Clinical immunology communications·2026

Same author

Managing microbial interactions in environmental biotechnology: can we scale interaction principles?

Trends in microbiology·2026

Same author

Radiation-induced lymphopenia is associated with survival in patients with hepatocellular carcinoma treated with stereotactic body radiotherapy.

JHEP reports : innovation in hepatology·2026

Search research articles

Related Experiment Video

Updated: May 29, 2026

Development of an Individual-Tree Basal Area Increment Model using a Linear Mixed-Effects Approach

Development of an Individual-Tree Basal Area Increment Model using a Linear Mixed-Effects Approach

Published on: July 3, 2020

Forecasting alpine vegetation change using repeat sampling and a novel modeling approach.

David R Johnson¹, Diane Ebert-May, Patrick J Webber

¹Department of Biology, University of Texas at El Paso, 79968-0519, USA. drjohnson2@utep.edu

|September 30, 2011

Summary

This summary is machine-generated.

Alpine plant communities are shifting due to global change. This study forecasts a decrease in snowbed vegetation and an increase in shrub tundra over 100 years, driven by temperature and nitrogen deposition.

More Related Videos

Watershed Planning within a Quantitative Scenario Analysis Framework

Watershed Planning within a Quantitative Scenario Analysis Framework

Published on: July 24, 2016

A Method of Trigonometric Modelling of Seasonal Variation Demonstrated with Multiple Sclerosis Relapse Data

A Method of Trigonometric Modelling of Seasonal Variation Demonstrated with Multiple Sclerosis Relapse Data

Published on: December 9, 2015

Related Experiment Videos

Last Updated: May 29, 2026

Development of an Individual-Tree Basal Area Increment Model using a Linear Mixed-Effects Approach

Development of an Individual-Tree Basal Area Increment Model using a Linear Mixed-Effects Approach

Published on: July 3, 2020

Watershed Planning within a Quantitative Scenario Analysis Framework

Watershed Planning within a Quantitative Scenario Analysis Framework

Published on: July 24, 2016

A Method of Trigonometric Modelling of Seasonal Variation Demonstrated with Multiple Sclerosis Relapse Data

A Method of Trigonometric Modelling of Seasonal Variation Demonstrated with Multiple Sclerosis Relapse Data

Published on: December 9, 2015

Area of Science:

Ecology
Climate Change Research
Vegetation Dynamics

Background:

Global change significantly impacts alpine ecosystems, altering plant distributions and community composition.
Forecasting alpine vegetation change is difficult due to limited long-term studies on fixed plots.
Decadal-scale data is crucial for understanding and predicting shifts in alpine plant communities.

Purpose of the Study:

To develop and apply a probabilistic modeling approach to forecast alpine vegetation change.
To predict vegetation shifts on Niwot Ridge, Colorado, over a 100-year period.
To identify key environmental drivers influencing observed and predicted plant community changes.

Main Methods:

Utilized plant abundance data from marked plots established in 1971 and resurveyed in 1991 and 2001.
Employed a probabilistic modeling approach to extrapolate vegetation change from 1971 onwards for 100 years.
Correlated plant community trends with time-series environmental data from 1971-2001.

Main Results:

Models predict a significant decrease in the extent of Snowbed vegetation by 2071.
Models forecast an increase in the extent of Shrub Tundra by 2071.
Mean annual maximum temperature and nitrogen deposition were identified as primary correlates of plant community change.

Conclusions:

The probabilistic modeling approach provides valuable hypotheses for future alpine vegetation change.
Long-term monitoring data is essential for validating and refining vegetation change predictions.
Understanding the impact of climate change and nitrogen deposition is critical for alpine ecosystem management.