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

Conservation of Declining Populations

Conservation of Declining Populations

Conservation of declining population focuses on ways of detecting, diagnosing, and halting a population decline. The approach uses methods to prevent populations from going extinct.

Survival Tree

Survival Tree

Survival trees are a non-parametric method used in survival analysis to model the relationship between a set of covariates and the time until an event of interest occurs, often referred to as the "time-to-event" or "survival time." This method is particularly useful when dealing with censored data, where the event has not occurred for some individuals by the end of the study period, or when the exact time of the event is unknown.
Building a Survival Tree
Constructing a...

Threats to Biodiversity

Threats to Biodiversity

There have been five major extinction events throughout geological history, resulting in the elimination of biodiversity, followed by a rebound of species that adapted to the new conditions. In the current geological epoch, the Holocene, there is a sixth extinction event in progress. This mass extinction has been attributed to human activities and is thus provisionally called the Anthropocene. In 2019 the human population reached 7.7 billion people and is projected to comprise 10 billion by...

Evolutionary Relationships through Genome Comparisons

Evolutionary Relationships through Genome Comparisons

Genome comparison is one of the excellent ways to interpret the evolutionary relationships between organisms. The basic principle of genome comparison is that if two species share a common feature, it is likely encoded by the DNA sequence conserved between both species. The advent of genome sequencing technologies in the late 20th century enabled scientists to understand the concept of conservation of domains between species and helped them to deduce evolutionary relationships across diverse...

Introduction to Plant Diversity

Introduction to Plant Diversity

From Water to Land

Gene Evolution - Fast or Slow?

Gene Evolution - Fast or Slow?

The genomes of eukaryotes are punctuated by long stretches of sequence which do not code for proteins or RNAs. Although some of these regions do contain crucial regulatory sequences, the vast majority of this DNA serves no known function. Typically, these regions of the genome are the ones in which the fastest change, in evolutionary terms, is observed, because there is typically little to no selection pressure acting on these regions to preserve their sequences.
In contrast, regions which code...

You might also read

Related Articles

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

Sort by

Same author

The digital biodiversity revolution.

The New phytologist·2026

Same author

Geospatial Access to Pediatric Cardiac and Cardiac-Surgical Services by Neighborhood-Level Determinants of Health.

Journal of the American Heart Association·2026

Same author

The danger zone: The joint trap of incomplete lineage sorting and long-branch attraction in resolving the Gondwanan origin of Rafflesiaceae and Apodanthaceae.

American journal of botany·2026

Same author

Climate mediates phenological and phylogenetic differentiation in plant invasions.

Proceedings of the National Academy of Sciences of the United States of America·2026

Same author

Using large language models to address the bottleneck of georeferencing natural history collections.

Nature plants·2025

Same author

Shifts in Phenology and Species Ranges Synergistically Alter the Timing and Species Composition of the Flowering Season.

Global change biology·2025

Search research articles

Related Experiment Video

Updated: Dec 23, 2025

Author Spotlight: UAV Remote Sensing for Efficient Invasive Plant Biomass Estimation

Author Spotlight: UAV Remote Sensing for Efficient Invasive Plant Biomass Estimation

Published on: February 9, 2024

Machine learning predicts large scale declines in native plant phylogenetic diversity.

Daniel S Park¹, Charles G Willis², Zhenxiang Xi³

¹Department of Organismic and Evolutionary Biology and Harvard University Herbaria, Harvard University, Cambridge, MA, 02138, USA.

The New Phytologist

|April 28, 2020

Summary

Global climate change threatens plant diversity. Machine learning predicts native phylogenetic diversity will decline despite rising species richness, highlighting the need for advanced predictive tools.

Keywords:

artificial intelligence biodiversity climate change machine learning phylogenetic diversity vascular plants

More Related Videos

Author Spotlight: Leaf Trait Analysis for Climate and Ecology Reconstruction in Modern and Ancient Plant Communities

Author Spotlight: Leaf Trait Analysis for Climate and Ecology Reconstruction in Modern and Ancient Plant Communities

Published on: October 25, 2024

A Bioinformatics Pipeline to Accurately and Efficiently Analyze the MicroRNA Transcriptomes in Plants

A Bioinformatics Pipeline to Accurately and Efficiently Analyze the MicroRNA Transcriptomes in Plants

Published on: January 21, 2020

Related Experiment Videos

Last Updated: Dec 23, 2025

Author Spotlight: UAV Remote Sensing for Efficient Invasive Plant Biomass Estimation

Author Spotlight: UAV Remote Sensing for Efficient Invasive Plant Biomass Estimation

Published on: February 9, 2024

Author Spotlight: Leaf Trait Analysis for Climate and Ecology Reconstruction in Modern and Ancient Plant Communities

Author Spotlight: Leaf Trait Analysis for Climate and Ecology Reconstruction in Modern and Ancient Plant Communities

Published on: October 25, 2024

A Bioinformatics Pipeline to Accurately and Efficiently Analyze the MicroRNA Transcriptomes in Plants

A Bioinformatics Pipeline to Accurately and Efficiently Analyze the MicroRNA Transcriptomes in Plants

Published on: January 21, 2020

Area of Science:

Ecology
Biodiversity Science
Computational Biology

Background:

Predicting climate change impacts on biodiversity is crucial but limited by taxon-specific data.
Existing studies often focus narrowly on species richness, neglecting other diversity metrics.

Purpose of the Study:

To apply machine learning to predict regional plant taxonomic and phylogenetic diversity under climate change.
To differentiate drivers and patterns of native versus non-native plant biodiversity.
To assess the congruence between taxonomic and phylogenetic diversity patterns.

Main Methods:

Utilized a comprehensive vascular plant database for the United States.
Employed machine learning approaches to generate predictive models.
Incorporated a wide range of environmental variables into the models.

Main Results:

Predicted native phylogenetic diversity is likely to decrease over the next 50 years, contrasting with potential increases in species richness.
Identified incongruence between predicted patterns of taxonomic and phylogenetic diversity.
Demonstrated varying drivers of native and non-native biodiversity under changing environmental conditions.

Conclusions:

Machine learning significantly enhances the ability to predict future plant diversity patterns.
Climate change will alter macro-environmental factors, leading to varied impacts on regional diversity.
Future biodiversity assessments must consider both taxonomic and phylogenetic diversity metrics for comprehensive understanding.