| 1 | <p>This lesson demonstrates ways that society and scientists identify and use data to understand disturbance events by focusing on the 2013 Boulder County, Colorado flooding events. Further, it encourages students to think about why we need to quantify change and the different types of data needed to quantify landscape change after a disturbance event.</p>
| 1 | <p>In the spring of 2018 I participated in the National Ecological Observatory Network’s (NEON) Faculty Mentoring Network (FMN) hosted by QUBES (<a href="https://qubeshub.org/">https://qubeshub.org/</a>). As part of this community I implemented and adapted the interactive lesson “Quantifying the Drivers and Impacts of Natural Disturbance Events-The 2013 Colorado Floods” developed by Leah Wasser and Megan Jones (<a href="https://www.neonscience.org/tm-disturbance-events-co13flood">https://www.neonscience.org/tm-disturbance-events-co13flood</a>). This lesson uses natural disasters and subsequent ecological disturbance events as a tool to illustrate the complexity of environmental science. The Colorado flood lesson explores: 1) drought, 2) precipitation, and 3) stream discharge as factors leading up to the intense floods of 2013. In southern California we rarely experience floods as natural disasters; however threats from fires and severe drought conditions are real-world problems that students constantly confront. Two recent examples are: 1) the state of California was in an official drought from 2011-2017, and 2) in December 2017 the Thomas fire located in Santa Barbara County burned 281,893 acres from Dec 4<sup>th</sup> to January 12<sup>th</sup> and the Skirball fire located in Los Angeles County burned 422 acres from Dec 6<sup>th</sup> through the 15<sup>th</sup>. Students at Mount Saint Mary’s University Chalon campus had to be evacuated and finals were postponed. I used the California drought and fires as personal examples to frame a lesson investigating the multi-layered environmental drivers of natural disasters in an introductory environmental science class for non-science majors.</p> |
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| 3 | <p>This lesson focuses on flooding as a natural disturbance event with impacts on humans. While the drivers and impacts of flooding extend beyond the metrics used in this lesson, we use subsets of these public data repositories to elicit discussion surrounding how we can study flooding and how the event impacts humans:</p>
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| 5 | <ul>
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| 6 | <li>Palmer Drought Index: <a href="http://www7.ncdc.noaa.gov/CDO/CDODivisionalSelect.jsp" target="_blank">NOAA's Climate Divisional Database (nCLIMDIV)</a></li>
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| 7 | <li>Precipitation: <a href="http://www.ncdc.noaa.gov/cdo-web/search" target="_blank">National Climatic Data Center-NOAA</a></li>
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| 8 | <li>Stream Discharge: <a href="http://waterdata.usgs.gov/nwis" target="_blank">USGS stream gauges</a></li>
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| 9 | <li>Before/After Terrain Data: <a href="http://www.neonscience.org/science-design/collection-methods/airborne-remote-sensing" target="_blank">NEON AOP LiDAR-derived Elevation Models</a></li>
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| 10 | <li>Before/After Imagery: various sources, each image has source information</li>
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| 11 | </ul>
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| 13 | <p>All materials for this teaching resources are hosted on the <a href="http://www.neonscience.org/overview-disturbance-events-co13flood" target="_blank">NEON website</a> including interactive plots, video, explanatory text, R code, and pre-made datasets. </p>
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| 15 | <p>The R scripts that both build the lesson (.Rmd) and are available for download are hosted in the <a href="https://github.com/NEONScience/NEON-Data-Skills" target="_blank">NEON Data Skills GitHub repo</a> and can be directly forked or downloaded for edits. We encourage instructors who want to fork this lesson on QUBES and make changes to the optional coding lessons to also fork the GitHub repo and link to their updated code. </p> | | |
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