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---
title: "Chris @ Evolution 2024"
format:
html:
toc: true
toc-depth: 4
css: cv.css
---
{fig-align="center"}
# Presentations
- **Poster: Saturday, July 27th**
- 5:45pm-8:15pm, Room 220DE, Poster Board F20 – Poster Session 1
- [View the poster here!](evolution2024poster.html)
- **Talk: Tuesday, July 30th**
- 3:00pm-3:15pm, Room 523AB – Ecology III
- View the slides here!
# Supplemental information
#### **Q1**: How was the **floral color** data collected?
**A**: A **k-means clustering** algorithm, hand-trained for each species using a custom GUI, ran on up to 100 research-grade images from iNaturalist. Coded in Python, and adapted from [Perez-Udell et al., 2019](https://doi.org/10.1002/aps3.11505). Find the GUI and algorithm on my GitHub [here](https://github.com/chris-a-talbot/pyflocolor). Floral color data is initially calculated as the average color value in HSV space for the most common floral color of a given species.
#### **Q2**: How was the **range** data collected?
**A**: **GBIF** occurrences, 1960 and later, isolated to North America, and filtered to exclude erroneous occurrences of various sorts. Representing North America as a raster of 10km^2^ cells, cells were populated with presence data based on the existence of an occurrence within that cell. This range format exhibits similar accuracy to convex hulls and buffered points, while offering higher computational speeds.
#### **Q3**: Where is the **phylogeny** from?
**A**: [Smith & Brown, 2018](https://doi.org/10.1002/ajb2.1019)
#### **Q4:** How was floral **color (dis)similarity** calculated?
**A**: Floral color for each species was transformed into HSL space. Floral color dissimilarity was calculated as the **Euclidean distance** between colors in **HSL** space:
``` r
color_dis <- dist(hsl_data, method = "euclidean")
```
Floral color similarity was calculated for each pair of species $(a,b)$ as:
$$
similarity_{a,b} = max(color\_dis) - color\_dis_{a,b}
$$
#### **Q5**: What about **pollinator vision**? The UV spectrum?
**A**: Floral color data is restricted to **camera color vision** due to the number of species for which color data was required. Exploring this pattern at such large scales using spectral data would be an exciting avenue for future research.
*\[Coming soon: figures on relatedness\~overlap, and any other relationships that may be of interest from the current data\]*
# Fun figures
*\[Coming soon: GIF of floral color across range through time\]*
# Contact info
View my CV [here!](CV.html)
- **Email**: [chtalbot\@umich.edu](chtalbot@umich.edu)
- **GitHub**: [\@chris-a-talbot](https://github.com/chris-a-talbot)
Social media:
- **Twitter**: [\@chris\_\_talbot](https://twitter.com/chris__talbot)
- **LinkedIn**: [\@chris-talbot](https://www.linkedin.com/in/chris-talbot/)
- **BlueSky**: [\@chtalbot](https://bsky.app/profile/chtalbot.bsky.social)