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Invasion, Restoration, and Response: Assessing changes in arthropod community assemblage using both parametric and non-parametric approaches

Author(s): Andrew Cameron

Virginia Commonwealth University

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Summary:
This lesson, which is based around a recently published paper in the Journal of Ecological Applications, introduces students to both parametric and non-parametric approaches to statistical analysis using R. Key concepts covered include Analysis of…

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This lesson, which is based around a recently published paper in the Journal of Ecological Applications, introduces students to both parametric and non-parametric approaches to statistical analysis using R. Key concepts covered include Analysis of Variance and Kruskal-Wallis tests, Shapiro-Wilk and Levene's testing, least significant difference post-hoc testing, and the Shannon Diversity Index. In addition to providing a detailed guide to these quantitative approaches, the lesson includes environmental background context and a section on the art of data wrangling to prepare raw data for analysis. The entire lesson is R-based, meaning that all parts of the lesson are intended to be viewed in RStudio, or some other Integrated Development Environment.
Contents:

Description

The lesson revolves are around a recently published study focused on saltmarsh restoration and the effects of non-native plant control on arthropod assemblages. The researchers conducted their research at wetland in coastal China that contains five different plant community types along an ecological gradient, ranging from native Phragmites to invasive Spartina monoculture and a restored Phragmites community. The study aims to determine whether removing invasive grass and restoring native plants can reverse the changes brought on by plant invasion.

The authors perform multiple statistical analyses as they try to answer several different research questions. We will focus our attention on the data and analyses related to arthropod diversity and abundance across the plant community gradient.

This lesson will guide you through the application of both parametric and non-parametric approaches to comparing means in order to determine whether or not there are statistically significant differences between groups with respect to a variable of interest. Along the way, you'll learn how to effectively explore and wrangle raw data and how to check that data conform to the expectations of parametric tests.Throughout the lesson there are opportunities for you to practice writing your own code, You'll learn about several ways that species diversity and abundance can be quantified, including the Shannon Diversity Index. You will also be introduced coding constructs and syntax that can be used to to more efficiently work with data, particularly when the same operation must be repeated over many columns in a table.

The lesson is divided into three parts, each contained in its own Markdown (.rmd) file:

  1. Environmental background and focal paper introduction

  2. Data wrangling

  3. Analysis

Notes

Added code to load conover.test package and fixed a minor typo in code.

Fixed typos and improved clarity in text.

Included `vegan` package description and code for installation, as needed.

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