Mosquito Vector Ecology of the East Coast using NEON
Author(s): Courtney Campany1, David Kang2
1. Shepherd University 2. Cornell University
1533 total view(s), 3808 download(s)
Summary:
This data module examines the relationship between mosquito vector ecology and climate across the east coast of the United States. The module is designed to merge core concepts in ecology with budding interests of the largely pre-heath student body.
Contents:
- mosquito_neon.html(HTML | 869 KB)
- Mosquito_NEON_student.docx(DOCX | 201 KB)
- Mosquito_NEON_Teachers_Notes.docx(DOCX | 20 KB)
- mosquito_pathogens.csv(CSV | 998 B )
- mosquito_taxonomy.csv(CSV | 3 KB)
- weather_summary.csv(CSV | 7 KB)
- Climate Central: A Science & News Organization
- WHO | World Health Organization
- CDC - Parasites - Malaria
- License terms
Description
This module is fully reproducible from a github repository (see Teacher's Notes). This allows modification of the module to fit time restrains of lecture or lab time slots, as well as adjusting content. The module (as-is) was given in a lecture time slot and students worked through the questions in small groups with one computer (Excel). If working with R, it is recommended that a lab time slot may be more appropriate.
The broad goals and learning objectives for the module are as follows:
Module Goals
- Explore any differences between pathogen status and mosquito populations along a latitudinal gradient of NEON field sites on the east coast of the United States.
- Gain a broad understanding the relationships between animal disease vectors and common environmental drivers.
- Gain awareness of the potential for NEON data to investigate disease ecology.
- Apply quantitative reasoning and critical thinking to explore future relationships between changing climates and vector ecology.
- Understand the important history of malaria-specific vector ecology in the United States and beyond.
Learning objectives
Upon completion of the module, students will be able to:
- download and wrangle NEON data
- visualize environmental data sets
- produce reproducible results (if using R)
- critically evaluate relationships between disease vectors, climate, habitat type and global change
Cite this work
Researchers should cite this work as follows:
- Campany, C., Kang, D. (2019). Mosquito Vector Ecology of the East Coast using NEON. NEON Faculty Mentoring Network, QUBES Educational Resources. doi:10.25334/25CW-6988