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Related Experiment Video

Updated: May 5, 2026

Quantifying Corticolous Arthropods Using Sticky Traps

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Published on: January 19, 2020

Traits Explain Canopy Tree Occurrence Along Regional Environmental Gradients: A Subset Combine to Be Useful.

Peter A Vesk¹, Saras M Windecker¹, Rachael V Gallagher²

¹School of Agriculture, Food and Ecosystem Sciences The University of Melbourne Parkville Victoria Australia.

Ecology and Evolution

|May 4, 2026

Summary

Trait-Species Distribution Models (trait-SDMs) predict species occurrence using plant traits. Key traits like stem density and bark thickness influence eucalypt distribution across environmental gradients, aiding ecological understanding and restoration efforts.

Keywords:

eucalypt joint species distribution models multi‐level model trait‐SDM trait‐environment associations

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Last Updated: May 5, 2026

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Published on: January 19, 2020

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Published on: October 20, 2019

Relating Stomatal Conductance to Leaf Functional Traits

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Published on: October 12, 2015

Area of Science:

Ecology
Biogeography
Trait-based ecology

Background:

Trait-Species Distribution Models (trait-SDMs) are crucial for understanding plant strategies and predicting species distributions.
Inconsistencies in published trait-environment associations necessitate robust, region-scale modeling approaches.
Region-scale models offer advantages in species, trait, and climatic gradient data over local or global scales.

Purpose of the Study:

To fit trait-SDMs for over 90 eucalypt tree taxa using multilevel models.
To identify influential plant traits driving species distributions along environmental gradients.
To test trait-based theory regarding realized niches and inform ecological predictions.

Main Methods:

Utilized multilevel models to fit trait-SDMs for eucalypt trees across a 120,000 km² region.
Modeled species presence-absence in 1 km² grid cells along temperature and precipitation gradients.
Incorporated six key plant traits: stem sapwood density, bark thickness, seed mass, maximum height, specific leaf area, and leaf size.

Main Results:

Stem sapwood density, bark thickness, seed mass, and maximum height were the most influential traits in predicting environmental responses.
These traits collectively explained 9%-19% of the variance in species' environmental responses.
Species with dense stems favored drier climates, thicker bark favored warmer climates, larger seeds and thinner bark occurred in shallow soils, and taller species preferred warmer, wetter sites.

Conclusions:

Trait-SDMs provide valuable insights into trait-environment associations and the testing of trait-based ecological theories.
Multi-trait models better represent integrated phenotypes responding to multidimensional niches compared to single-trait models.
Trait-SDMs offer predictive capabilities for species occurrence and restoration planning, while acknowledging uncertainties in species-specific identification.