Description

The assignment is developed for one laboratory session of 2.5 hours.The module was taught to sophomore students majoring in biology, with only basic knowledge of ecology and statistics. An additional laboratory session of 2.5 hours (can be assigned to be completed online at home) would be required prior to this module if students are unfamiliar with R. Please see the instructors notes for more details.

This module can be used in ecology classes to demonstrate basic community analysis, or compliment the course material letting students to explore one of the forest habitats, dead wood, and its decomposers - saproxylic fungi. It can be also used in beginners bioinformatics or biostatistics classes to introduce basics of ordination in R.

Learning objectives:

In this activity, students will:

• Discuss quantitative methods used in community ecology. Presentation slides are provided to guide this discussion.
• Use basics of statistical software R.
• Familiarize with the global biodiversity portals such as inaturalist.org or gbif.org and methods of storage and open sharing of data.
• Use open biodiversity dataset to perform NMDS ordination analysis in R (package vegan).
• Compare and contrast dead wood fungal communities in different types of forests (hardwood vs softwood).

Activity software:

Software used was: R / R-Studio; packages: dplyr and vegan.

Dataset used:

In this module, a modified version of an openly published dataset is used. Full dataset can accessed at gbif.org:

https://www.gbif.org/dataset/d1d59f9f-e130-4715-bc9b-8a25e7b62e89

Shumskaya M, Zambell C, Mishra S, Bell E, Blue S, Yearwood-Marut J, Marut W, Vindas-Cruz A, Jennings A, Hylton N, Burghardt J (2019). Survey of saproxylic fungi across parks of New Jersey. Kean University. Occurrence dataset https://doi.org/10.15468/ngpb5m

What is included in this module:

1. PowerPoint slides to introduce the activity. Slides contain a simple in-class exercise on Jaccard similarity calculation and free-hand ordination.

2. Student's handout to distribute in class.

3. Instructor's notes. Contains recommendations for instructors. Sample student answers are provided in a separated file.

4. Two scripts in R: one to distribute to students who will have to do some editing for the script to work, and one for instructors with completed commands to serve as an example of a working script.

5. The dataset csv file.

Notes

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