Xuan Chen1, Daijiang Li2
1Department of Biological Sciences, Salisbury University, Salisbury, MD 21801
2Department of Biological Sciences, Louisiana State University, Baton Rouge, LA 70803
Corresponding author: Xuan Chen (XXCHEN@salisbury.edu)
THE ECOLOGICAL QUESTIONs
How does species richness change across large spatial scales? How does biodiversity in one place change over time? How does human disturbance affect biodiversity?
FOUR DIMENSIONAL ECOLOGY EDUCATION (4DEE) FRAMEWORK
- Core Ecological Concepts:
- Species diversity - Biodiversity
- Ecology Practices:
- Quantitative reasoning and computational thinking
- Data skills - inputting and data-mining /data visualization
- Computer skills: spreadsheets, "R"
- Human-Environment Interactions:
- Human accelerated environmental change
- Anthropogenic impacts
- Cross-cutting Themes:
- Spatial & Temporal
WHAT STUDENTS DO
Use R and an open biodiversity dataset to explore ecological questions related to the effects of space, time, and human disturbance on biodiversity
In this module, two to four students work collaboratively in a group to complete assignments. The module incorporates mostly open-ended questions, which can be challenging to answer due to the overwhelming amount of information available on the internet. Additionally, writing R code as an undergraduate can be a daunting task due to the complexity of the coding process and lack of experience. Collaborative learning can help to reduce the stress and anxiety associated with these challenges and create a more supportive learning environment. The assignments are uniform across all groups, with each group submitting one answer sheet to the instructor.
Answer sheet including questions’ answers of each activity, R scripts (demonstrating how students manipulate the code for the formative and summative assessments), figures and tables related to analysis results.
This module was designed to let students finish the exercises within two 3-hour labs: Lab 1: Activity 1 -> Introduce R -> Activity 2 Lab 2: Activity 3 -> Activity 4 -> Summative assessment
upper-level courses (e.g., General Ecology, Community Ecology, Conservation Biology) in Biology and related majors (e.g., Environmental Science). The best time to introduce this module is during the second half of a course when students have learned the concept of species, diversity, resilience etc.
Ellison, A. (2021). Ant Assemblages in Hemlock Removal Experiment at Harvard Forest since 2003 (Reformatted to the ecocomDP Design Pattern) ver 5. Environmental Data Initiative. https://doi.org/10.6073/pasta/cd33e1651c73841976049a5730504ad1
Gaynor, S. (2020). Introduction to R with Biodiversity Data. Biodiversity Literacy in Undergraduate Education, QUBES Educational Resources. https://doi.org/10.25334/84FC-TE88
Li, D., S. Record, E.R. Sokol, M.E. Bitters, M.Y. Chen, A.Y. Chung, M.R. Helmus, et al. (2022). Standardized NEON Organismal Data for Biodiversity Research. Ecosphere 13(7): e4141. https://doi.org/10.1002/ecs2.4141
Rabalais, N. (2016). Above ground plant biomass, canopy height and estimated percent cover supporting marsh and subtidal benthic community and marsh invertebrate distribution studies in paired oiled/unoiled sites in coastal Louisiana in Spring and Fall 2013. Distributed by: Gulf of Mexico Research Initiative Information and Data Cooperative (GRIIDC), Harte Research Institute, Texas A&M University–Corpus Christi. https://doi.org/10.7266/N7X34VD2
Description of Resource Files:
- NEON.R: R script for download and analysis of NEON data.
- EDI.R: R script for download and analysis of EDI data.
- GoMRI.R: R script for analysis of GoMRI data.
- GoMRI_RabalaisPlantData.xlsx: Data for GoMRI analysis.
This study was funded by National Science Foundation (DBI-1730526 RCN-UBE: Biodiversity Literacy in Undergraduate Education - Data Initiative and DBI-2120678 RCN-UBE: Transforming Ecology Education to Four Dimensional Network). We would like to thank Anna Monfils and Luanna Prevost for their help in developing the module. We also thank reviewer and editor for their insightful comments.
Xuan Chen and Daijiang Li. May 2023. Playing with open biodiversity datasets: case studies using data from NEON, EDI, and GoMRI. Teaching Issues and Experiments in Ecology, Vol. 19: Practice #1. https://tiee.esa.org/vol/v19/issues/data_sets/chen/abstract.html