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<title>Rachel King</title>
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  <title>Digital Assets: Scrollytelling</title>
  <link>https://king0708.github.io/rkingecology/projects/dan_scrollytell/</link>
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<section id="scrollytelling-example" class="level1">
<h1>Scrollytelling example</h1>
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<p>See an example of using the <code>closereads</code> package to highlight the main findings from one of my recent projects, <a href="https://king0708.github.io/dan-scrollytell/"><strong>Digital Assets for Nature</strong></a>.</p>
<p>The dataset compiled for this project can be found at the <a href="https://doi.org/10.5063/F1VQ3157">Knowledge Network for Biocomplexity</a>.</p>
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<p><img src="https://king0708.github.io/rkingecology/projects/dan_scrollytell/DAN_logo2.png" class="img-fluid"></p>
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  <guid>https://king0708.github.io/rkingecology/projects/dan_scrollytell/</guid>
  <pubDate>Tue, 25 Mar 2025 00:00:00 GMT</pubDate>
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  <title>Tidy Tuesday</title>
  <link>https://king0708.github.io/rkingecology/projects/tidy_tuesday/</link>
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<h1>Tidy Tuesday</h1>
<p>See my data viz examples from the <a href="https://github.com/king0708/tidy-tuesday/tree/main">Tidy Tuesday</a> project in R.</p>
<p>When I get the chance, I use use the <code>tidytuesdayR</code> package to download the data, explore it, and create a visualization I post to my repository. In creating this repo, I followed <a href="https://nrennie.rbind.io/blog/script-templates-r/">this tutorial</a> by <a href="https://nrennie.rbind.io/">Nicola Rennie</a> to make a template for each week to streamline my workflow.</p>
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Figure&nbsp;1
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 ]]></description>
  <guid>https://king0708.github.io/rkingecology/projects/tidy_tuesday/</guid>
  <pubDate>Tue, 04 Mar 2025 00:00:00 GMT</pubDate>
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  <title>Visualizing Spatial Data</title>
  <link>https://king0708.github.io/rkingecology/projects/spatial_data_viz/</link>
  <description><![CDATA[ 




<section id="workshop-overview" class="level1">
<h1>Workshop Overview</h1>
<p>My first workshop for <a href="https://ecodatascience.github.io/">EcoDataScience</a> on <a href="https://king0708.github.io/spatial-data-viz/">visualizing spatial data</a>. I present an overview of the <code>sf</code> package in R, how to add a basemap with different packages, and some other tips and tricks for improving reproducibility and efficiency in map making.</p>
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Figure&nbsp;1: One of the maps created during the tutorial.
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 ]]></description>
  <guid>https://king0708.github.io/rkingecology/projects/spatial_data_viz/</guid>
  <pubDate>Wed, 06 Mar 2024 00:00:00 GMT</pubDate>
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  <title>Prey Distribution Mapping</title>
  <link>https://king0708.github.io/rkingecology/projects/prey_shiny_app/</link>
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<h1>Project Overview</h1>
<p>There are many threatened and endangered species within California drylands, and many active efforts to conserve and restore their populations. One important component of conservation for endangered consumers, such as the Blunt-nosed Leopard Lizard, is ensuring that they have adequate prey resources. In this project, we compiled a list of prey of endangered species in California drylands, downloaded occurrence records for the prey from the <a href="www.gbif.org">Global Biodiversity Information Facility</a>, and used these to create species distribution models for finding suitable prey habitat. These were stacked to identify hot-spots of potential prey species richness for different predators. These species distribution models, raw occurrence records, and other summary plots can be viewed interactively in the linked <a href="https://kingr.shinyapps.io/Prey_map_shiny/">shiny app</a>. The data for the app and associated paper (King et al., <em>submitted</em>) are availble on Zenodo: <a href="https://zenodo.org/records/10215172">https://zenodo.org/records/10215172</a>.</p>
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<p><img src="https://king0708.github.io/rkingecology/projects/prey_shiny_app/prey_distribution_map.png" class="img-fluid"></p>
<p>The first page of the Shiny application.</p>
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</section>

 ]]></description>
  <guid>https://king0708.github.io/rkingecology/projects/prey_shiny_app/</guid>
  <pubDate>Fri, 01 Sep 2023 00:00:00 GMT</pubDate>
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