How Do We Measure Biodiversity: Exploring Biodiversity Metrics Using Avian Communities

Jeffrey Brown, La Salle University

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Initial Publication Date: July 21, 2023

Summary

This activity is designed to illustrate various ways that biodiversity can be measured and to highlight what we can learn about an ecological community from different metrics. Students will explore biodiversity metrics (i.e., species richness and Shannon diversity) using point count data on birds collected from the Central Arizona-Phoenix Long Term Ecological Research program. Specifically, students will investigate how bird richness and abundance have changed over time and create figures to compare abundance across landscapes and time.

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Learning Goals

  • Work with R to learn how to organize and manage datasets. Students will reshape data and select only species of interest from larger data sets.
  • Calculate species diversity metrics: By the end of this module, students will be able to calculate total abundance, species richness, and the Shannon diversity of birds at sites across the CAP LTER study site.
  • Explore how communities change across time and space. Specifically, students will investigate how avian communities change from 2000 to 2010 in the Phoenix Metropolitan Area. Additionally, students will explore how land cover (e.g., potential habitat) shapes avian communities.
  • (Optional) Conduct non-metric multiple dimensional scaling (NDMS) and learn about this metric for visualizing and comparing data: Students will conduct an NMDS to compare avian communities across sites and between years. Students will learn what NMDS represents and how we can use NMDS to explore and compare communities. Additionally, students will learn about wide and long data formats and structure their data so that it can be analyzed appropriately for different tests.

Core Questions:

  • What can we learn about an ecological community by measuring richness and Shannon Diversity, and exploring community composition (through non-metric multi-dimensional scaling | NMDS)?
  • How does urbanization and patterns of land-use change influence biotic communities?

Dataset(s)

  • CAP LTER Long Term Bird Monitoring Data from Warren et al. (2020)
  • Visualization of land-use/ land-cover data from the CAP LTER study site

Context for Use

This module is designed for an upper-level environmental analysis methods course. It can be completed in 3 hours, but two shorter sessions may also be appropriate. Students may work in small groups, but it will be most beneficial for all students to have access to a computer so they can complete the work on their own. Students should be familiar with R/RStudio, and be able to load data into R. If not, they will require more attention and support using the module. Students should be familiar with statistics, or additional statistical background may be needed. The module includes background information about community diversity metrics.

How Instructors Have Used This Module

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Using the Project EDDIE 'How Does Avian Biodiversity Vary Temporarily and Spatially?' Module in BIO 411: Quantitative Methods for Ecology and Conservation
Jeffrey Brown, Arizona State University at the Tempe Campus
This model allows students to explore how biodiversity metrics vary across landscapes using long term point-count data.

Description and Teaching Materials

Quick overview of the activities in this module

  • Background / Pre-Work: Students who are unfamiliar with abundance, richness, and Shannon diversity explore the supplemental background files to ensure an understanding of diversity metrics.
  • Activity A: Students will load data into R and explore the data while answering questions about species richness and species abundance. Students will explore how species ranges and conservation status relates to the abundance of species seen at the study site.
  • Activity B: Students will hypothesize how avian communities may differ across time and explore their hypotheses using various diversity metrics.
  • Activity C: Students will compare communities across space, specifically incorporating land use and land cover elements in their community comparisons, and create visualizations to illustrate how communities differ.
  • Activity D (optional extension): Students will compare communities using Non-metric Multidimensional Scaling (NMDS) to visually represent differences in community compositions.

Activity Description and Materials

Background/Pre-Work

Begin by watching the following introductory video (MP4 Video 269.9MB Feb1 22) and use the Introductory PowerPoint (PowerPoint 2007 (.pptx) 6MB Dec14 22) to learn more about the Central Arizona-Phoenix Long-Term Ecological Research Project (CAPLTER).

  • Background Activities (Optional):
    • Instructors can use the mini-assessment to ensure students understand the key terms and calculations involved in calculating diversity metrics.
      • Student Background Assessment 1 (Microsoft Word 2007 (.docx) 88kB Dec14 22)
    • Students can break into groups and brainstorm the pros and cons of the different metrics discussed in the video.
      • Students should discuss the following questions related to species richness and Shannon diversity.
        • Student Background Assessment 2 (Microsoft Word 2007 (.docx) 15kB Dec14 22)
  • Pre-Module Activity: Students should review Warren et al. 2019, paying particular attention to the "Bird surveys" section in the methods (pages 3-5). After reviewing this paper, students should take some time to explore the CAP LTER Bird Monitoring Data Portal (data page | meta-data). Students should calculate species Richness and Shannon's Diversity for the three sites (AD-10, U-13, and X-8) from the "Data for Background Assessment" below. If students are already familiar with how to calculate these metrics, this step can be skipped.

Activity A:

  • Students should open RStudio and load the CAP LTER bird Monitoring data into R. Students will follow the instructions in the assessment to explore species abundance in the data set and familiarize themselves with the data.

Activity B: 

  • Students will take a closer look at the data to try and identify if species are driving patterns in diversity metrics. Students will also link the data to land-use and land cover data to investigate how land use and land cover may shape community diversity metrics
  • Students will learn about the vegan package which is used to calculate many community diversity metrics in R. Students will use this package to quickly calculate Shannon's diversity for multiple sites across multiple years. Students will also work on creating new data frames by combing information from multiple data frames

Activity C:

  • Students will explore how diversity metrics vary across different land-uses.
  • Students will visualize differences in diversity metrics by land-use and investigate how diversity patterns change across sites. 

Activity D:

  • Video Intro: A brief explanation of comparing communities across space - NMDS Background (MP4 Video 6.9MB Dec14 22) Students will conduct NMDS and affiliated tests to ensure the NMDS accurately captures patterns in the data. Lastly, students will create figures to visually show the results of their NMDS with clusters for both year and land-use land-cover. Lastly, students will explore how particular species influence the overall composition of ecological communities and investigate how removing or sub-setting data differently impact the results of the NMDS.

Teaching Materials

Assignment, Instructions, Data, and Answer Key:

PowerPoints:

Videos:

Supplemental Files:

Teaching Notes and Tips

  • This module works best if students are familiar with biodiversity metrics, including richness and Shannon diversity.
  • This module will likely work best if students have access to their own computers but can work together in groups.
  • Familiarity working with R is recommended.

Assessment

Student success can be measured by considering the following:

  • Determining students' understanding of species richness and Shannon's Diversity
  • Assessing whether students understood how abundance varied over time for bird species
  • Were students able to produce figures that explored species diversity across different landscapes?
  • Did students answer all questions associated with the assigned student handout.

References and Resources

Brown, J. A., Lockwood, J. L., Avery, J. D., Burkhalter, J. C., Aagaard, K., & Fenn, K. H. 2019. Evaluating the long-term effectiveness of terrestrial protected areas: a 40-year look at forest bird diversity. Biodiversity and Conservation, 28(4), 811-826.
https://link.springer.com/article/10.1007/s10531-018-01693-5

Warren, P. S., S. B. Lerman, R. Andrade, K. L. Larson, and H. L. Bateman. 2019. The more things change: species
losses detected in Phoenix despite stability in bird–socioeconomic relationships. Ecosphere 10(3):e02624. 10.1002/ecs2.2624
https://esajournals.onlinelibrary.wiley.com/doi/10.1002/ecs2.2624

Warren, P. S., S. B. Lerman, H. L. Bateman, M. Katti, E. Shochat. 2020.Point-count bird censusing: long-term monitoring of bird abundance and diversity in central Arizona-PHoenix, ongoing since 2000.
https://sustainability-innovation.asu.edu/caplter/data/view/knb-lter-cap.46/

Zhang, Y. and X. Li 2017. Land cover classification for the CAP LTER study area at five-year intervals from 1985 to 2010 using Landsat imagery. 
https://sustainability-innovation.asu.edu/caplter/data/view/knb-lter-cap.650.1/