Students use small mammal data from the National Ecological Observatory Network to understand necessary steps of data management from data collection to data analysis by estimating small mammal population sizes using the Lincoln-Peterson model.
Megan A. Jones, Lee F. Stanish, Natalie Robinson, Katherine D. Jones, Cody Flagg
This module series covers how to import, manipulate, format and plot time series data stored in .csv format in R. Originally designed to teach researchers to use NEON plant phenology and air temperature data; has been used in undergraduate classrooms.
This lesson focuses on ways that scientists identify and use data to understand ecological disturbance events using data from five public datasets. The main lesson focused on interpretation of figures, while optional coding extensions teach R skills.
This is the third lab in an Introductory Physical Geography/Environmental Studies course. It introduces students to different data types (qualitative vs quantitative), basic statistical analyses (correlation analysis s, t-test), and graphing techniques.
Students build on fundamental concepts of spatial patterns and combine this knowledge with the open-data from the National Ecological Observatory Network to quantify spatial autocorrelation and complexity.
Concepts of remote sensing and data logistics, and NEON remote sensing data are introduced. Students learn how to apply spatial data processing and visualization skills using R coding program to process NEON airborne data to address scientific questions.
This module assesses the role of wildfire in the eastern US and its impact on bird communities using NEON bird survey data from pre- and post- a major wildfire in the Great Smoky Mountains National Park (GRSM) in November 2016.
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.
Natural disasters and subsequent ecological disturbance events illustrate the complexity of problems in ecology and environmental science, and can be used as effective teaching tools. Unpacking the diverse real-world factors leading up to events offers op
Christopher Gough, Cindee Giffen, Thomas W Woodward
Students build on fundamental concepts of ecosystem production and carbon cycling, combining this knowledge with open long-term data from ecological and meteorological networks to uncover the environmental drivers of carbon fluxes.
This adaptation introduces students to R and the NEON OS & IS data – Plant Phenology & Temperature tutorial. A planned extension will prompt students to develop a testable hypothesis, based on their tutorial insights, that could be investigated locally.
This adaptation consists of three exercises that introduce students to 1) format spreadsheet data tables, 2) carry out spreadsheet quality control, and 3) count/sort/filter data of interest in order to conduct a pilot analysis on NEON small mammal data.
Danielle Garneau, Matthew Joshua Heard, Mary Beth Kolozsvary
This project makes use of publicly-available datasets on lichen presence and abundance and wet deposition, paired with geospatial data on air quality, tree canopy cover, and locally collected field data, to better understand how lichens respond to changes
Students observe insect pollinators and other floral visitors in their backyards, or campus, or nearby natural areas to describe plant-pollinator networks and assess how the assemblages from their sites compare to those in a range of landscapes.
A project to compare effects of a continuum of landscape alteration intensities on plant diversity, biomass, and ecosystem services, and to explore human socioeconomic connections to plants in the environment.