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Spatial Analysis with QGIS

Author(s): Ryan Kerney1, Timothy Whitfeld2

1. Gettysburg College 2. Bell Museum, University of Minnesota

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Summary:
Map specimen data points using QGIS, connect them to form a polygon using the Concave Hull plugin, and calculate the range of a species to examine how it changes over time.

Licensed under CC Attribution-NonCommercial-ShareAlike 4.0 International according to these terms

Version 1.0 - published on 13 Oct 2021 doi:10.25334/2RNW-2K04 - cite this

Keywords

  1. natural history collections
  2. species distributions
  3. course-based research experiences (CUREs)
  4. spatial analysis
  5. digitized natural history collections
  6. QGIS

Alignments

  1. Resource Type
  2. Audience Level
  3. Activity Length
  4. Inclusive Pedagogy for Life Science Education
  5. Open Science and Education Practices Ontology
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Description

Abstract: Species distributions shift over time as populations move and respond to changes in their environment. This activity used digital natural history specimen data, QGIS, and Excel to analyze range distribution changes over time. QGIS is an open-source geographic information system that can be used not only to map specimens but also to conduct spatial analyses. By connecting specimen data points to form a polygon, we will calculate the range of a species and examine how it changes over time. Then, we will use Excel to create a table and graph to display how the area of a species distribution changes. 

Details: This activity builds on the related resource, Mapping Specimen Occurrence in QGIS (Bronson, C., 2021). These two activities can be used as a standalone resource or as part of the implementation of a BCEENET CURE. In this activity, students will learn to:

  • Create a map with overlapping polygons using the Concave Hull tool
  • Use the polygon map to measure the area of the species range at multiple time points
  • Create a spreadsheet showing the area of the range of a species over time

 

This content was created by members of BCEENET, Biological Collections in Ecology and Evolution Network, and funded by the National Science Foundation, under Grant No. 1920385 and Grant No. 2032158. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the National Science Foundation.

 

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