Related Experiment Video
Updated: Feb 6, 2026

A Practical Guide to Phylogenetics for Nonexperts
Published on: February 5, 2014
Assessing biodiversity and endemism using phylogenetic methods across multiple taxonomic groups
Carlos E González-Orozco1, Brent D Mishler2, Joseph T Miller3,4
1Institute for Applied Ecology and Collaborative Research Network for Murray-Darling Basin Futures University of Canberra Canberra Australian Capital Territory 2601 Australia.
Abstract:
Identifying geographical areas with the greatest representation of the tree of life is an important goal for the management and conservation of biodiversity. While there are methods available for using a single phylogenetic tree to assess spatial patterns of biodiversity, there has been limited exploration of how separate phylogenies from multiple taxonomic groups can be used jointly to map diversity and endemism. Here, we demonstrate how to apply different phylogenetic approaches to assess biodiversity across multiple taxonomic groups. We map spatial patterns of phylogenetic diversity/endemism to identify concordant areas with the greatest representation of biodiversity across multiple taxa and demonstrate the approach by applying it to the Murray-Darling basin region of southeastern Australia. The areas with significant centers of phylogenetic diversity and endemism were distributed differently for the five taxonomic groups studied (plant genera, fish, tree frogs, acacias, and eucalypts); no strong shared patterns across all five groups emerged. However, congruence was apparent between some groups in some parts of the basin. The northern region of the basin emerges from the analysis as a priority area for future conservation initiatives focused on eucalypts and tree frogs. The southern region is particularly important for conservation of the evolutionary heritage of plants and fishes.
Related Concept Videos
What is Biodiversity?
Threats to Biodiversity
Biodiversity and Human Values
Phylogenetic Trees
Multiple Allele Traits
Multiple Regression
Farmers can use multiple regression to determine the crop yield based on more than one factor, such as water availability, fertilizer, soil properties, etc. Here, the crop yield is the response or dependent variable as it depends on the other independent variables. The analysis requires the construction of a scatter plot...

