Code for: Triolena anisophylly data extraction
Data files
Dec 30, 2025 version files 19.68 KB
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canopy_cover.R
884 B
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ecoregion_analysis.R
4.95 KB
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pca_analysis.R
1.31 KB
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README.md
1.66 KB
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regression_analysis.R
8.15 KB
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spatial_thinning_WorldClim.R
1.46 KB
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WWF_ecoregions.R
1.27 KB
Abstract
Anisophylly is a peculiar leaf trait in some opposite-leaved taxa where opposing leaves are distinctly unequal. This study uses an expert-curated specimen dataset to explore relationships of canopy cover and climate with the presence and intraspecific variation of anisophylly in the genus Triolena. Canopy and climate conditions are investigated between species and within a single species through beta regression models. R code for canopy cover, climate, and ecoregion data are included here, as well as code for PCA and beta regression model analyses. No relationship was found between canopy cover and anisophylly. However, anisophylly is associated with conditions of high precipitation and high isothermality, which is evident across Triolena and within a single species. In addition, partitioned ecoregion analyses illustrate that different types of anisophyllous leaf states occur in distinct ranges of precipitation and isothermality. Results suggest that anisophylly is associated with climate in Triolena.
https://doi.org/10.5061/dryad.9kd51c5qx
Six R code files are included here. With our species occurrence dataset of coordinates, some of these files were used to extract data such as climate, canopy cover, and ecoregions. Others were used to run various analyses to understand relationships between anisophylly and the extracted data. Their specific uses are outlined below.
Description of the data and file structure
canopy_cover.R: Used to extract a value representing canopy cover from NASA Global 30 m Landsat Tree Canopy (Sexton et al. 2013). The earliest year in the dataset (2000) was used to minimize bias from deforestation.
ecoregion_analysis.R: Used to investigate climate variables via two-way ANOVA analyses ecoregions and anisophylly type as dependent variables.
pca_analysis.R: Used to run a principal component analysis of the 19 climatic variables across all Triolena species.
regression_analysis.R: Used to examine individual relationships via beta regression models between climate, canopy cover, and anisophylly.
spatial_thinning_WorldClim.R: Used to spatially thin species occurences at a threshold of 10 km.
WWF_ecoregions.R: Used to extract ecoregions for coordinates from WWF ecoregions (Olson et al. 2001) and WWF's Global 200 ecoregions (Olson and Dinerstein 2002).
Sharing/Access information
Data was derived from the following sources. Due to licensing compliance, we are unable to include these data here.
- GBIF (Global Biodiversity Information System).
- K (Kew Herbarium records)
Code/Software
All scripts were run in R.