Resource Image

Pesticide-Driven Bee Mortality: An Introduction to Survival Analysis in R

Author(s): Megan Black

Virginia Commonwealth University

1101 total view(s), 531 download(s)

0 comment(s) (Post a comment)

Summary:
In this lesson, students will receive an introduction to survival analysis in R utilizing data on bee mortality caused by pesticide exposure. In their code, students will assess survivability, recreate survival plots, and analyze the results from…

more

In this lesson, students will receive an introduction to survival analysis in R utilizing data on bee mortality caused by pesticide exposure. In their code, students will assess survivability, recreate survival plots, and analyze the results from chi-square tests.

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

Version 2.0 - published on 26 Jan 2023 doi:10.25334/GSJN-4N68 - cite this

Description

Using the focal paper, "Roundup causes high levels of mortality following contact exposure in bumble bees", students will learn about the ecological effects of pesticides and the concept of surfactant co-formulants. This lesson also provides a background on survival analysis before walking students through a provided code example step by step. Students will be expected to recreate this code, in which they assess and model survivability, for two additional experiments on their own. After completing their analyses, students will be able to assess whether the active ingredient in Roundup is to blame for pollinator mortality. 

Cite this work

Researchers should cite this work as follows: