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https://github.com/lter/lterdatasampler

LTER data samples to teach environmental data science
https://github.com/lter/lterdatasampler

data-science ecology lter-science r r-package

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LTER data samples to teach environmental data science

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README 

        
---

output: github_document

editor_options: 

  markdown: 

    wrap: 72

---



```{r setup, include=FALSE}

knitr::opts_chunk$set(

  collapse = TRUE,

  comment = "#>",

  fig.path = "man/figures/README-",

  out.width = "75%",

  warning = FALSE,

  message = FALSE,

  fig.retina = 2,

  fig.align = 'center'

)



library(gt)

library(tidyverse)

```



[![Package

Site](https://github.com/lter/lterdatasampler/workflows/pkgdown/badge.svg)](https://github.com/lter/lterdatasampler/actions)

[![R-CMD-check](https://github.com/lter/lterdatasampler/workflows/R-CMD-check/badge.svg)](https://github.com/lter/lterdatasampler/actions)

[![CRAN status](https://www.r-pkg.org/badges/version/lterdatasampler)](https://cran.r-project.org/package=lterdatasampler)

[![CRAN RStudio mirror downloads](http://cranlogs.r-pkg.org/badges/lterdatasampler)](http://www.r-pkg.org/pkg/lterdatasampler)



# lterdatasampler 



The mission of the [Long Term Ecological Research program (LTER)

Network](https://lternet.edu/) is to “*provide the scientific community,

policy makers, and society with the knowledge and predictive

understanding necessary to conserve, protect, and manage the nation’s

ecosystems, their biodiversity, and the services they provide.*” A

specific goal of the LTER is [education and

training](https://lternet.edu/education-and-training/) - “*to promote

training, teaching, and learning about long-term ecological research and

the Earth’s ecosystems, and to educate a new generation of scientists.*”



The goal of this package is to provide a sampler to gather feedback from

the community of what will be a larger package containing 28 datasets -

one from each of the existing [US LTER

sites](https://lternet.edu/site/). Those datasets are subsets of the

original data and have been updated - sometimes substantially - from the

raw data. They are aimed to be useful for teaching and training in

environmental data science. **This content is thus not suitable for

research and should only be used for teaching purposes**.



We encourage you to explore existing LTER [teaching and training

initiatives](https://lternet.edu/education-and-training/), and the

**many** other available LTER datasets which can be accessed via the

[Environmental Data

Initiative](https://edirepository.org/). Please contact

cited researchers directly to discuss using data for research purposes

or in publication.



## Installation



You can install the CRAN version of `lterdatasampler` with:



``` r

install.packages("lterdatasampler")

```



You can install the development version of `lterdatasampler` from

GitHub with:



``` r

# install.packages("remotes")

remotes::install_github("lter/lterdatasampler")

```



## The dataset samples



Dataset samples currently included in the package are summarized below;

see individual Articles for data and source details. Note: the three

letter prefix for each dataset indicates the LTER site (see full list of

[site abbreviations](https://lternet.edu/site/)).



-   [`and_vertebrates`](https://lter.github.io/lterdatasampler/reference/and_vertebrates.html):

    Records for aquatic vertebrates (cutthroat trout and salamanders) in

    Mack Creek, Andrews Experimental Forest, Oregon (1987 - present)

-   [`arc_weather`](https://lter.github.io/lterdatasampler/reference/arc_weather.html):

    Daily meteorological (e.g. air temperature, precipitation) records

    from Toolik Field Station, Alaska (1988 - present)

-   [`hbr_maples`](https://lter.github.io/lterdatasampler/reference/hbr_maples.html):

    Sugar maple seedlings at Hubbard Brook Experimental Forest (New

    Hampshire) in calcium-treated and reference watersheds in August

    2003 and June 2004

-   [`knz_bison`](https://lter.github.io/lterdatasampler/reference/knz_bison.html):

    Bison masses recorded for the herd at Konza Prairie Biological

    Station LTER

-   [`luq_streamchem`](https://lter.github.io/lterdatasampler/reference/luq_streamchem.html):

    stream chemistry data for the Quebrada Sonadora (QS) location part of the Luqillo tropical

    forest LTER site

-   [`ntl_icecover`](https://lter.github.io/lterdatasampler/reference/ntl_icecover.html):

    Ice freeze and thaw dates for Madison, Wisconsin Area lakes (1853 -

    2019), North Temperate Lakes LTER

-   [`ntl_airtemp`](https://lter.github.io/lterdatasampler/reference/ntl_airtemp.html):

    Daily average air temperature data for Madison, Wisconsin (1869 -

    2019), North Temperate Lakes LTER

-   [`nwt_pikas`](https://lter.github.io/lterdatasampler/reference/nwt_pikas.html):

    Pika observations for habitat and stress analysis at Niwot Ridge

    LTER, Colorado

-   [`pie_crab`](https://lter.github.io/lterdatasampler/reference/pie_crab.html):

    Fiddler crab body size recorded summer 2016 in salt marshes from

    Florida to Massachusetts including Plum Island Ecosystem LTER,

    Virginia Coast LTER, and NOAA’s National Estuarine Research Reserve

    System



## Which data sample should I use?



These data samples are selected because they have features we feel are

commonly useful in introductory environmental data science and

statistics courses.



In the table below, we list some introductory methods / skills, then

share which data samples in this package we think are well-suited to use

when teaching or learning them! It is not comprehensive - there are

*many* different analyses & skills that these data samples would

facilitate. Here we highlight a few that we think would be commonly

useful



```{r, echo = FALSE}

# Create the table contents

table_contents <- tribble(

  ~method, ~datasample, ~data_description, ~link,

  "Linear relationships", "`pie_crab`", "Model the relationship between fiddler crab size and latitude using `pie_crab` , while learning about Bergmann's Rule!", "https://lter.github.io/lterdatasampler/articles/pie_crab_vignette.html",

  "Linear relationships", "`ntl_icecover`", "Investigate the relationship between winter temperatures and ice cover duration for Wisconsin lakes using `ntl_icecover`", "https://lter.github.io/lterdatasampler/articles/ntl_icecover_vignette.html",

  "Linear relationships", "`hbr_maples`", "Explore seedling height-mass relationships for sugar maples using `hbr_maples`", "https://lter.github.io/lterdatasampler/articles/hbr_maples_vignette.html",

  "Non-linear relationships", "`knz_bison`", "Model the relationship between bison age and mass for male and female bison using `knz_bison`, for example estimating parameters in the Gompertz model", "https://lter.github.io/lterdatasampler/articles/knz_bison_vignette.html",

  "Non-linear relationships", "`and_vertebrates`", "Model the length-mass relationships for cutthroat trout and salamanders in Mack Creek, Oregon", "https://lter.github.io/lterdatasampler/articles/and_vertebrates_vignette.html", 

  "Time series analysis", "`arc_weather`", "Explore seasonality, wrangling dates, or practice forecasting using daily meteorological records from Toolik Station, Alaska", "https://lter.github.io/lterdatasampler/articles/arc_weather_vignette.html", 

  "Time series analysis", "`luq_streamchem`", "Investigate the impact of a hurricane on stream water chemistry", "https://lter.github.io/lterdatasampler/articles/luq_streamchem_vignette.html",

  "Spatial data introduction", "`nwt_pikas`", "Introduce basics of spatial data (e.g. CRS, projections) and tools for working with spatial data by visualizing pika locations at Niwot Ridge in the Colorado Rockies", "https://lter.github.io/lterdatasampler/articles/nwt_pikas_vignette.html", 

  "Comparing groups", "`hbr_maples`", "Compare sugar maple seedling heights in previously calcium-treated versus untreated watersheds using `hbr_maples`, using the exercise as an opportunity to think about acid rain and soil acidification", "https://lter.github.io/lterdatasampler/articles/hbr_maples_vignette.html", 

  "Comparing groups", "`and_vertebrates`", "Explore differences in size and abundance of cutthroat trout and salamanders in old growth versus previously clear cut forest sections (2 groups) or in different conditions (> 2 groups, e.g. pool, cascade, riffle) of Mack Creek, Oregon", "https://lter.github.io/lterdatasampler/articles/and_vertebrates_vignette.html"

) %>% 

  mutate(full_link = sprintf('%s', link, datasample),

         full_link = map(full_link, gt::html))



table_contents %>% 

  select(method, full_link, data_description) %>% 

  gt(groupname_col = "method") %>% 

  tab_header(

    title = "Recommended data samples for introducing selected topics",

  ) %>% 

  cols_label(method = "Topic", full_link = "Data sample", data_description = "For example you could:") %>%

  tab_options(row_group.as_column = TRUE) %>% 

  tab_style(

    style = "vertical-align:middle",

    locations = cells_row_groups()

  ) 

  

```



## How to provide feedback



The best way to provide feedback on this package is to open an

[issue](https://github.com/lter/lterdatasampler/issues) and assign the

`feedback` label. Thank you!



## Acknowledgements



Thank you to the amazing students who contributed to this project: *Sam

Guo, Adhitya Logan, Lia Ran, Sophia Sternberg, Karen Zhao* as part of

their [UCSB Data Science capstone

project](https://ucsb-ds-capstone-2021.github.io/projects/nceas/update3.html).

Thank you also go to their Course Advisor Prof. Sang-yun Oh.



People / organizations who supported this project:



-   LTER Network Office

-   LTER Information Managers

-   LTER Education Committee

-   All the LTER Researchers and Site PIs

-   Cyber-infrastructures:

    [EDI](https://edirepository.org/) and

    [DataONE](https://www.dataone.org/)



We gratefully acknowledge all authors and contributors of the

[`roxygen2`](https://roxygen2.r-lib.org/),

[`usethis`](https://usethis.r-lib.org/),

[`pkgdown`](https://pkgdown.r-lib.org/),

[`devtools`](https://devtools.r-lib.org/),

[`tidyverse`](https://www.tidyverse.org/) and

[`metajam`](https://github.com/NCEAS/metajam/) packages. This website

relies heavily on themes created by Dr. Desirée DeLeon and Dr. Alison

Hill.