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#347, v2.1 Published:
#2215, v1.0 Published:

Title

Old VersionNew Version
1Data Management using National Ecological Observatory Network's (NEON) Small Mammal Data with Accompanying Lesson on Mark Recapture Analysis 1Data Management in Excel and R using National Ecological Observatory Network's (NEON) Small Mammal Data

Authors

Old VersionNew Version
1Jim McNeil (George Mason University; Smithsonian-Mason School of Conservation) 1Marguerite Mauritz ()
2Megan A. Jones (National Ecological Observatory Network) 2Sarah McCord (USDA ARS Jornada Experimental Range)
3Megan A. Jones (National Ecological Observatory Network) 3Marguerite Mauritz ()

Description

Old VersionNew Version
1<p>This version of this teaching module was published in Teaching Issues and Experiments in Ecology:&nbsp;</p>  1<p><strong>Background</strong></p>
2  2  
3<p>Jim McNeil and Megan A. Jones. April 2018, posting date. Data Management using National Ecological Observatory Network&rsquo;s (NEON) Small Mammal Data with Accompanying Lesson on Mark Recapture Analysis.&nbsp;<cite>Teaching Issues and Experiments in Ecology</cite>, Vol. 13: Practice #9 [online].&nbsp;<a href="http://tiee.esa.org/vol/v13/issues/data_sets/mcneil/abstract.html">http://tiee.esa.org/vol/v13/issues/data_sets/mcneil/abstract.html</a></p>  3<p>Undergraduate STEM students are graduating into professions that require them to manage and work with data at many points of a data management life cycle. Within ecology, students are presented not only with many opportunities to collect data themselves, but increasingly to access and use public data collected by others. This activity introduces the basic concept of data management, spreadsheet management, and metadata to allow meaningful&nbsp;data analysis. The accompanying presentation materials mention the importance of considering long-term data storage and data analysis using public data.</p>
4  4  
5<p>*** *** ***&nbsp;</p>  5<p>This data set is a subset of small mammal trapping data from the National Ecological Observatory Network (NEON). The accompanying lesson introduces students to proper data management practices including how data moves from collection to analysis. Students will do some manual preparation of messy spreadsheets with small datasets to prepare data in an R-compatible format. Students will then import data to R and do some preliminary data checks and a basic visualization.&nbsp;</p>
6  6  
7<p>Undergraduate STEM students are graduating into professions that require them to manage and work with data at many points of a data management life cycle. Within ecology, students are presented not only with many opportunities to collect data themselves, but increasingly to access and use public data collected by others. This activity introduces the basic concept of data management from the field through to data analysis. The accompanying presentation materials mention the importance of considering long-term data storage and data analysis using public data.</p>  7<p>Students then use a much larger NEON dataset and metadata sheets to understand small mammal capturing methods. Students use the field protocol and metadata to navigate the data structure and then import the data to R for some data-checks and visualizations.&nbsp;</p>
8  8  
9<p>This data set is a subset of small mammal trapping data from the National Ecological Observatory Network (NEON). The accompanying lesson introduces students to proper data management practices including how data moves from collection to analysis. Students perform basic spreadsheet tasks to complete a Lincoln-Peterson mark-recapture calculation to estimate population size for a species of small mammal. Pairs of students will work on different sections of the datasets allowing for comparison between seasons or, if instructors download additional data, between sites and years. Data from six months at NEON&rsquo;s Smithsonian Conservation Biology Institute (SCBI) field site are included in the materials download. Data from other years or locations can be downloaded directly from the NEON data portal to tailor the activity to a specific location or ecological topic.</p>  9<p>&nbsp;Data from six months at NEON&rsquo;s Smithsonian Conservation Biology Institute (SCBI) field site are included in the materials download. Data from other years or locations can be downloaded directly from the NEON data portal to tailor the activity to a specific location or ecological topic.</p>
10  10  
11<p>In this activity, students will:</p>  11<p><strong>Teaching notes:</strong></p>
   12
   13<p>I taught this module asynchronously in Fall 2020. Students received a background document for the lab, a brief video lecture covering the basic principles of good spreadsheet management, and had the option to work with extensively scripted helper R code or a minimal R code framework to complete the activity. I also provided a video in which I walked through and completed&nbsp;some components of the R code.&nbsp;Students worked in groups of 2-4 in their own time and were given 1 week to complete the lab.&nbsp;</p>
   14
   15<p><strong>In this activity, students will:</strong></p>
12  16  
13<ul>  17<ul>  
14   <li>discuss data management practices with the faculty. Presentation slides are provided to guide this discussion.</li>  14   <li>reflect on data management practices themselves and in teams.&nbsp;Presentation slides are provided to guide this discussion.</li>
15   <li>view field collection data sheets to understand how organized data sheets can be constructed.</li>  19   <li>view field collection data sheets to understand how organized data sheets can be constructed.</li>  
16   <li>design a spreadsheet data table for transcription of field collected data using good data management practices.</li>  20   <li>design a spreadsheet data table for transcription of field collected data using good data management practices.</li>  
17   <li>view NEON small mammal trapping data to a) see a standardized spreadsheet data table and b) see what data are collected during NEON small mammal trapping.</li>  21   <li>view NEON small mammal trapping data to a) see a standardized spreadsheet data table and b) see what data are collected during NEON small mammal trapping.</li>  
18   <li>use Microsoft Excel or Google Sheets to conduct a simple Lincoln-Peterson Mark-Recapture analysis to estimate plot level species population abundance.</li>  18   <li>use R to read and analyze patterns in spatial and seasonal small mammal abundance</li>
19</ul>  23</ul>  
20  24  
21<p>Please note that this lesson was developed while the NEON project was still in construction. There may be future changes to the format of collected and downloaded data. If using data directly from the NEON Data Portal instead of using the data sets accompanying this lesson, we recommend testing out the data each year prior to implementing this lesson in the classroom.</p>  21<p><strong>R skills</strong></p>
22  26  
23<p>This module was originally taught starting with a field component where students accompanied NEON technicians during the small mammal trapping. As this is not a possibility for most courses, the initial part of the lesson has been modified to include optional videos that instructors can use to show how small mammal trapping is conducted. Instructors are also encouraged to bring small mammal traps and small mammal specimens into the classroom where available.</p>  27<ul>
   28   <li>basic familiarity with R markdown, ggplot2, and dplyr packages</li>
   29   <li>I provide helper code (most of the code is pre-written with prompts for where to enter variables) and minimal code (code is initiated and students write the rest)</li>
   30   <li>students can choose which code they use to allow greater accessibility and the ability to explore&nbsp;more independent coding</li>
   31</ul>
24  32  
25<p><strong>The Data Sets</strong></p>  33<p><strong>The Data Sets</strong></p>  
26  34  
  
28  36  
29<p>The following datasets are posted for educational purposes only. Data for research purposes should be obtained directly from the National Ecological Observatory Network (www.neonscience.org).</p>  37<p>The following datasets are posted for educational purposes only. Data for research purposes should be obtained directly from the National Ecological Observatory Network (www.neonscience.org).</p>  
30  38  
31<p>Data Citation: National Ecological Observatory Network. 2017. Data Product: NEON.DP1.10072.001. Provisional data downloaded from <a href="http://data.neonscience.org/">http://data.neonscience.org</a>. Battelle, Boulder, CO, USA</p> 39<p>Data Citation: National Ecological Observatory Network. 2017. Data Product: NEON.DP1.10072.001. Provisional data downloaded from <a href="http://data.neonscience.org/">http://data.neonscience.org</a>. Battelle, Boulder, CO, USA</p>
   40
   41<p><strong>Adaptation Notes</strong></p>
   42
   43<p>This version was adapted by blending ideas from two other Qubes resources:&nbsp;</p>
   44
   45<ol>
   46   <li id="fn1">
   47   <p>McNeil, J., Jones, M. A. (2018). Data Management using NEON Small Mammal Data with Accompanying Lesson on Mark Recapture Analysis. NEON - National Ecological Observatory Network, QUBES.&nbsp;<a href="doi:10.25334/Q4XH5S">doi:10.25334/Q4XH5S</a><a href="file:///Users/memauritz/Desktop/R/R_programs/Teaching/EcosystemEcology_UTEP/Lab6_DataManagement_SmallMammals/Lab6_Description.html#fnref1">↩</a></p>
   48   </li>
   49   <li id="fn3">
   50   <p>Hern&aacute;ndez-Pacheco, R. H. (2018). More In Depth Spreadsheet Management Adaptation of Data Management using NEON Small Mammal Data. NEON Faculty Mentoring Network, QUBES Educational Resources.&nbsp;<a href="doi:10.25334/Q44X4D">doi:10.25334/Q44X4D</a><a href="file:///Users/memauritz/Desktop/R/R_programs/Teaching/EcosystemEcology_UTEP/Lab6_DataManagement_SmallMammals/Lab6_Description.html#fnref3">↩</a></p>
   51   </li>
   52</ol>

Attachments

1 file — ./Small Mammal Data Teaching Module/McNeilJones_TIEE_DataManagementSlides.pptx 1 file — Lab6_SmallMammals/Abbreviated NEON Small Mammal Trapping Protocols.docx
2 file — ./Small Mammal Data Teaching Module/McNeilJones_TIEE_NEONSmallMammalDataAbundanceWorkbook.xlsx 2 file — Lab6_SmallMammals/formatted_small_mammal_comm-1707.xlsx
3 file — ./Small Mammal Data Teaching Module/NEONTeachingModule_SmallMammalDataManagement_TeachingDataSubset.zip 3 file — Lab6_SmallMammals/Lab6_DataManagement.pptx
4 file — ./Small Mammal Data Teaching Module/NEONTeachingModule_Student_DataManagementwWithNEONSmallMammalDataAndMarkRecapture.docx 4 file — Lab6_SmallMammals/Lab6_Description.html
5 file — ./Small Mammal Data Teaching Module/NEONTeachingModule_Teacher_DataManagementwWithNEONSmallMammalDataAndMarkRecapture.docx 5 file — Lab6_SmallMammals/NEON.D02.SCBI.DP1.10072.001.mam_pertrapnight.072014to052015.csv
6 file — ./Small Mammal Data Teaching Module/NEON_Fieldtech7.jpg 6 file — Lab6_SmallMammals/NEON.D02.SCBI.DP1.10072.001.variables.csv
7 file — Lab6_SmallMammals/NEON.DP1.10072.001_readme.txt
8 file — Lab6_SmallMammals/RmdCodes/Lab6_Description.Rmd
9 file — Lab6_SmallMammals/RmdCodes/Lab6_Working.Rmd
10 file — Lab6_SmallMammals/small_mammal_community.xls
11 link — QA&amp;QC - YouTube
12 link — Monitoring: The Conversation - Talking Data Quality with Sarah McCord | Free Podcasts | Podomatic"
13 file — Lab6_SmallMammals/pics/Pic_21CenturyData.png
14 file — Lab6_SmallMammals/pics/Pic_Data.png
15 file — Lab6_SmallMammals/pics/Pic_DataIdeal.png
16 file — Lab6_SmallMammals/pics/Pic_FieldData.png
17 file — Lab6_SmallMammals/pics/Pic_McCord_DataCycle.png
18 file — Lab6_SmallMammals/pics/Pic_Spreadsheet.png