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Related Experiment Video

Updated: Jul 26, 2025

Author Spotlight: Exploring Bradysia coprophila's Unique Biology – A Guide to Laboratory Maintenance
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Amazonian Odonata Trait Bank.

Victor Rennan Santos Ferreira1, Bethânia Oliveira de Resende1, Rafael Costa Bastos1

  • 1Laboratório de Ecologia e Conservação (LABECO) Universidade Federal do Pará Belém Pará Brazil.

Ecology and Evolution
|June 19, 2023
PubMed
Summary

This study created the Amazonian Odonata Trait Bank (AMO-TB), a database of 68 functional traits for 218 Brazilian Amazon dragonfly species. This resource aids ecological research and conservation by standardizing data and identifying functional patterns.

Keywords:
bibliographydatabasefunctional traitsphenotyperaunkiæran shortfalls

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Area of Science:

  • Ecology
  • Evolutionary Biology
  • Biodiversity Science

Background:

  • Knowledge gaps exist regarding Odonata (dragonfly) biology, particularly in biodiverse regions like the Amazon Rainforest.
  • Standardizing functional traits is crucial for ecological and evolutionary hypotheses and for conservation planning under environmental change.

Purpose of the Study:

  • To create a comprehensive database of functional traits for Odonata species in the Brazilian Amazon.
  • To identify functional patterns and relationships between trait categories within Odonata suborders.

Main Methods:

  • Compiled data on 68 functional traits (behavior, habitat, thermoregulation, distribution) for 218 species from 419 literature sources.
  • Measured 22 morphological traits from ~2500 adults and categorized distributions using ~40,000 geographic records.

Main Results:

  • Developed a functional matrix for Brazilian Amazonian Odonata, revealing distinct functional patterns across suborders.
  • Identified strong relationships between different functional trait categories.
  • Highlighted literature gaps and suggested future research directions.

Conclusions:

  • The Amazonian Odonata Trait Bank (AMO-TB) provides a valuable resource for ecological and evolutionary studies.
  • Recommends selecting key traits to reduce sampling effort while capturing functional diversity.
  • Informs conservation and management strategies by understanding trait responses to environmental changes.