R for Ornithologists: How R can benefit the study of Ornithology

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### Symposium

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# R pour ornithologue

### .rblue[Points de vue des utilisateuRs et programmeuRs]

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# R for Ornithologists

### .rblue[Perspectives from useRs to programmeRs (to birdeRs)]

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**10:30-14:15**  Salle des Plaines II

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.footer[SCO-SOC 2019]

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Ornithologists “in the era of new technologies” have access to ever increasing
sources of data, which in turn leads to large quantities of data. This wealth of
data is exciting, but sometimes overwhelming, and with new technologies for
collecting data, we need new technologies for processing and analyzing data. One
such technology is the free and open source programming language, R. R is a
powerful (and economical) tool that is highly extensible through ‘packages’ for
performing specific tasks. Because there are so many packages, many
ornithologists are not aware of the many ways in which R can be useful, or which
packages are available for purposes beyond statistical analysis. However, there
are numerous packages which have been developed for specific scientific, or even
ornithological applications. Such examples include those for accessing relevant
online data sources (e.g., climate data, eBird, population data, etc.), genomic
analyses, bioacoustic analyses, analyses of animal movements, reproducible
research workflow, and dissemination (e.g., graphs, maps, and interactive
visualizations). This presentation will introduce ornithologists to these tools
which make ornithological research quicker, easier, more affordable, and
stronger.

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.hanging[
### Stefanie E. LaZerte]

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# R for Ornithologists
### How R can benefit the study of Ornithology

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![:img left: 150px, bottom: 100px, 200px, , ](./Figures/R_bird.png)

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# What is R?

## A statistical programming language and environment
(free and open source!)

## R uses packages

- Packages extend R (i.e. `nlme` and `lme4` add mixed modeling)
- Packages can be written by anyone

- Some are ok, some are good, some are AMAZING
- .rblue[Base R] is R without any extra packages (also good)

> There are 1000's of packages!

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# R is hard

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# Impost**R** Syndrome

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# Impost**R** Syndrome

![:img left: 25px, bottom: 170px, 60%, , David Whittaker](./Figures/imposter.jpg)

![:box 50%, 80%, 75%](<strong>Moral of the story?</strong><br>Make friends, code in groups, learn together and don't beat yourself up)

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# Impost**R** Syndrome
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**Using R in the undergraduate biology classroom**: Hurdles, hints, and aha moments  
(.rblue[Here @ 1:45pm])

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# Ornithologists and R

## What I **am not** going to do

- Teach you R
- Talk about statistics

## What I **am** going to do

- Explain how R can benefit ornithologists
- Showcase useful packages
- Give you resources to get started

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- Inspire you to take your .rblue[R] to the next level!

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- What??!?!! Can you have a presentation about R without these two things?
- The goal of this presentation is not to explain how to use R, but rather

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# Why ornithologists should use R

## R is powerful!

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# Why ornithologists should use R
## R is powerful!

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**The blessing and curse of automated data collection:**  
  R and dealing with big data in a modern age  
  (.rblue[Here @ 10:45am])

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**Super-computing with R:**  
  Harnessing the power of the cloud to analyze big-bird-data, or just run your simulations, models, and cross-validations faster  
(.rblue[Here @ 11:15am])

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# Why ornithologists should use R
## Reproducible Science

- Scripts are records of your work

```r
m <- lm(mpg ~ cyl, data = mtcars)
summary(m)
```

- Scripts can be compiled into pdf/html reports with [**`rmarkdown`**](https://rmarkdown.rstudio.com/) and [**`knitr`**](https://yihui.name/knitr/)  
  (In RStudio: `File > Compile Report`)

![:img right: 250px, bottom: 50px, 15%, , ](./Figures/rmarkdown_logo.png)
![:img right: 50px, bottom: 50px, 15%, , ](./Figures/knitr_logo.png)

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# Why ornithologists should use R
## Reproducible Science

- Keep track of code AND output
![:img right: 0px, top: 100px, 60%, , ](./Figures/repro1.png)

- Keep track of data
![:img right: 0px, top: 100px, 60%, , ](./Figures/repro2.png)

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- Keep track of software
![:img right: 0px, top: 100px, 60%, , ](./Figures/repro3.png)

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# Why ornithologists should use R

## Find Data!

- Many online data sources are accessible through R
- Reproducible science includes data sources!

### Packages
- Observations from [ebird](https://ebird.org) with [**`auk`**](https://github.com/CornellLabofOrnithology/auk)
![:img right: 300px, top: 120px, 15%, , ](./Figures/auk_logo.png)

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- Observations from [NatureCounts](https://naturecounts.ca) with [**`naturecounts`**](https://github.com/birdstudiescanada/naturecounts) (.rblue[Here @ 11:00am])

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- Recordings of vocalizations from [xeno-canto](https://www.xeno-canto.org/) with [**`warbleR`**](https://github.com/maRce10/warbleR)
![:img right: 30px, top: 200px, 20%, , ](./Figures/warbleR_logo.png)

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- Weather data from [Environment and Climate Change Canada](http://climate.weather.gc.ca/) with [**`weathercan`**](https://github.com/ropensci/weathercan)
![:img right: 25px, top: 275px, 15%, , ](./Figures/weathercan_logo.png)

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- DNA Sequences from [GenBank](https://www.ncbi.nlm.nih.gov/genbank/) with [**`phylotaR`**](https://github.com/ropensci/phylotaR)
![:img right: 100px, top: 470px, 16%, , ](./Figures/phylotaR_logo.png)

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- Taxonomic data with [**`taxize`**](https://github.com/ropensci/taxize)

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- IUCN Red Lists with [**`rredlist`**](https://github.com/ropensci/rredlist)

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- brranching: Includes methods for fetching 'phylogenies' from a variety of sources, including the 'Phylomatic' web service (<http://phylodiversity.net/phylomatic>), and 'Phylocom' (<https://github.com/phylocom/phylocom/>).
- Data published on [dryad](https://datadryad.org/) with [**`rdryad`**](https://github.com/ropensci/rdryad)

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# Why ornithologists should use R
## Dealing with Data

![:img center, bottom: 25px, 85%, , <a href = "https://www.forbes.com/sites/gilpress/2016/03/23/data-preparation-most-time-consuming-least-enjoyable-data-science-task-survey-says/">Forbes.com</a>](./Figures/forbes_cleaning.jpg)

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# Why ornithologists should use R

.columnl[
## Dealing with Data
- Reproducible!
- Cleaning
  - Fix typos
  - Fix/explore odd/missing values
- Filtering
- Summarizing
- Transforming
- Exploring
]

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## Packages to Use
- Base R (i.e. no special packages)
- [`data.table`](http://r-datatable.com) (<http://r-datatable.com>)
- [`tidyverse`](http://tidyverse.org) (<http://tidyverse.org>)
  - Suite of packages
  - Learn more: [R for Data Science](https://r4ds.had.co.nz/)

]

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I don't know about you, but I've never come back from the field and thought, great, my data is perfectly ready for analysis.
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# Why ornithologists should use R

## 100's of Specialized packages

### For example...

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- Phylogenetic comparative analyses [**`adephylo`**](https://github.com/thibautjombart/adephylo)

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- Bioacoustic analyses with [**`seewave`**](http://rug.mnhn.fr/seewave/)
![:img left: 50px, bottom: 75px, 35%, , ](./Figures/seewave_logo.png)

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- Automatic detection of vocalizations with [**`monitoR`**](http://www.uvm.edu/rsenr/vtcfwru/R/?Page=monitoR/monitoR.htm)

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- Animal home ranges with [**`adehabitatHR`**](https://cran.r-project.org/web/packages/adehabitatHR/)

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- Hierarchical Bayesian modelling of Breeding Bird Survey data with [**`bbsBayes`**](https://github.com/BrandonEdwards/bbsBayes)  (.rblue[Here @ 11:30am])
![:img left: 575px, bottom: 5px, 14%, , ](./Figures/bbsBayes_logo.png)

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- Systematic reviews with [**`litsearchr`**](https://elizagrames.github.io/litsearchr/) (.rblue[Here @ 1:30pm])
![:img right: 150px, bottom: 5px, 14%, , ](./Figures/litsearchr_logo.png)

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- Animal movements detected by RFID with [**`feedr`**](https://github.com/animalnexus/feedr)

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# Why ornithologists should use R

## Dissemination and Visualizations

- Beautiful plots with [**`ggplot2`**](https://ggplot2.tidyverse.org/)
![:img left: 75px, bottom: 160px, 15%, , ](./Figures/ggplot2_logo.png)
![:img right: 25px, bottom: 75px, 50%, , ](./Figures/ggplot2-1.png)

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- Complex maps with [**`sf`**](https://r-spatial.github.io/sf/), [**`tmap`**](https://github.com/mtennekes/tmap)
![:img left: 260px, bottom: 162px, 17%, , ](./Figures/sf_logo.gif)
![:img right: 25px, bottom: 75px, 50%, , ](./Figures/tmap.png)

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- Interactive visualizations with [**`shiny`**](https://shiny.rstudio.com/)

![:img right: 25px, bottom: 25px, 55%, ,Finch movements](./Figures/shiny_feedr.png)
![:img left: 175px, bottom: 5px, 15%, , ](./Figures/shiny_logo.png)

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# Why ornithologists should use R
## Find More Packages!

- Not an exhaustive list!
- Check out package collections
   - [metaverse](https://rmetaverse.github.io/) (<https://rmetaverse.github.io/>)
   - [ropensci](https://ropensci.org/) (<https://ropensci.org/>)
   - [tidyverse](https://tidyverse.org/) (<https://tidyverse.org/>)
- Look in journals, i.e. Methods in Ecology and Evolution
- Look in methods sections of articles

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> Always cite packages and package versions!

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# **Symposium:** R for Ornithologists

### Stay tuned for 6 more .rblue[R]-related presentations
### 2:00pm Round-Table Discussion on Ornithological perspectives on R

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## .rblue[Thank you!]

**Thanks to Denis LePage for help on the French version**

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.footer-right[Compiled on 2019-08-28]

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Presentation Available: <https://steffilazerte.github.io/Presentations/>  
Slides created with the R package [xaringan](https://github.com/yihui/xaringan), using [remark.js](https://remarkjs.com), [knitr](http://yihui.name/knitr), and [R Markdown](https://rmarkdown.rstudio.com)]