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commecometrics: an R package for trait-environment modelling at the community level
María A Hurtado-Materon1, Leila Siciliano-Martina2, Rachel A Short3
1Ecology and Evolutionary Biology Program, Texas A&M University. Department of Ecology and Conservation Biology, Texas A&M University, College Station, United States of America Ecology and Evolutionary Biology Program, Texas A&M University. Department of Ecology and Conservation Biology, Texas A&M University College Station United States of America.
The commecometrics R package models trait-environment links using community data. It reconstructs past environments and predicts future ecological changes, aiding biodiversity analysis.
Area of Science:
- Ecology
- Paleontology
- Bioinformatics
Background:
- Functional trait analysis is crucial for understanding ecological dynamics.
- Existing tools often lack integration with paleontological data or are taxon-specific.
- Ecometrics links community trait distributions to environmental variables for ecological inference.
Purpose of the Study:
- Introduce the R package `commecometrics` as a novel framework.
- Provide tools for accessible modeling of trait-environment relationships.
- Enable reconstruction of past environments and prediction of future community responses.
Main Methods:
- The `commecometrics` package offers functions for summarizing trait distributions.
- It facilitates the construction and visualization of ecometric models.
- Model robustness is assessed, and environmental conditions are reconstructed.
Main Results:
- The package integrates modern and ancient species trait data.
- It demonstrates broad applicability across ecological and palaeoecological studies.
- A worked example using carnivoran mammals (relative blade length) showcases its utility.
Conclusions:
- `commecometrics` provides an accessible, open-access tool for trait-based biodiversity analysis.
- The package bridges gaps in functional trait analysis by incorporating paleontological data.
- It enhances our ability to analyze trait-environment dynamics across space and time.
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