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Island biogeography, spatial ecology, and macroinvertebrate species diversity in Richmond’s rock pools

Author(s): Nadia Bukach1, Todd Lookingbill1, Andrew Davidson2, James R Vonesh2, Kristine Grayson1

1. University of Richmond 2. Virginia Commonwealth University

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Students investigate questions of community ecology and biogeography using data from an urban rock pool ecosystem. Using ArcGIS 10, students learn to create effective maps, calculate landscape attributes, and perform introductory spatial analysis.

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

Version 1.0 - published on 22 Feb 2019 doi:10.25334/Q43F14 - cite this


In the heart of Richmond, VA a series of depressions dot the banks of the James River. These rock pools were created by years of water and debris boring into the underlying bedrock. Exposed by an upriver dam, the rock pools are a patchwork of aquatic habitats dynamically interconnected by seasonal flooding that have been carefully mapped using photography from Unmanned Arial Vehicles (UAVs). In this lab, students use spatial biodiversity data from these pools to investigate principles of island biogeography.

This lesson teaches students introductory level concepts for working with spatial data and producing effective maps. Students use ArcGIS 10 to calculate spatial attributes and perform basic spatial analysis to conceptualize species distribution, measures of pool biodiversity, pool isolation and distance of pools to sources of biodiversity. This module has been used an introductory ecology and geography course. It is designed to introduce students with no background in ArcGIS to spatial analysis while teaching fundamental ecological concepts.


  1. Assignment Instructions
  2. Zip file containing ArcGIS spatial data
    • Map document
    •  Geodatabase with spatial data
  3. Supplemental Educator Materials
    • Completed maps
    • Example statistical analysis assignment

Geography Learning Objectives

  • Introduce basics of ArcMap functionality
  • Understand and navigate spatial data in ArcMap
  • Develop effective maps using critical map elements and symbology
  • Understand and calculate spatial attributes from existing data
  • Perform basic spatial analysis using spatial statistical models in ArcMap

Statistics Learning Objectives

  • Export spatial attributes for statistical analysis
  • Use T-tests, ANOVA, and linear regression to test relationships between species diversity and spatial attributes

Ecology Learning Objectives

  • Understand metrics of species diversity such richness and evenness
  • Apply principles of island bigeography theory based on size and pool isolation

Acknowledgements: This work was funded by NSF DEB-1556686 (Vonesh) and an ROA supplement (Grayson), as well as the MSI: Richmond program funded by Altria. The data used in this module was collected as part of a collaborative education project between VCU and UR. We are grateful for the data collection efforts of Ryland Stunkle, Emily Betts, Anne Wright, and students from Richmond City Public Schools, VCU Biology and Life Sciences, and UR Biology and Geography. Drone imagery provided by Will Shuart. We also thank David Kitchen, Taylor Holden, Kim Browne, Chtaura Jackson, and Johanna Kraus. River photo by James Vonesh.

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