A field lab designed to guide student research from sweepnet to statistical analysis


Erin A. McKenney and Ana M. Meza-Salazar

Department of Applied Ecology, North Carolina State University, Raleigh, NC 27695

Corresponding author: Erin A. McKenney (


Students are generally excited to learn hands-on field methods. However, the nuanced logistics required to curate collaborative datasets are considered more tedious; and many students find data analysis and code intimidating. We designed a 3-week lab to address these challenges by empowering students to design experiments to characterize and compare arthropod communities across different habitats. We structured assignments, activities, and assessments to support team building through methods practice, project development, data collection, statistical analysis, visualization and interpretation. This extended lab is completed at the beginning of the semester to coach students through every stage of place-based research and lays the groundwork for subsequent collaborative research projects.


  • Core Ecological Concepts:
    • Communities
    • Landscapes
  • Ecology Practices:
    • Natural history
    • Fieldwork
    • Quantitative reasoning and computational thinking
    • Designing and critiquing investigations
    • Working collaboratively
    • Communicating and applying ecology
  • Human-Environment Interactions:
    • How humans shape and manage ecosystems
  • Cross-cutting Themes:
    • Spatial and Temporal Scales


MULTIWEEK - three 4.5-hour lab sessions and two 75-minute lectures


8.5-14 hours - Students read an article (1-2 hours) to discuss during the initial field lab, that will inform their question and methods development; complete 5 R for Data Science modules (0.5-1 hour per module) to learn coding basics and get familiar with the R environment; identify arthropods and enter species count data into a shared spreadsheet (1-3 hours); and work with group members to write up the results and interpretations of data analysis (4 hours).


Students create a shared Google Sheet where they curate arthropod data collected in the field. Students then adapt provided base code to analyze the class data in RStudio, creating figures to visualize the data and selecting appropriate statistical approaches to test their group's hypotheses (10 points each for figures and R script). Each group turns in a collaborative write-up in Google Doc to present and interpret their results in the context of the literature (100 points). In addition, students earn credit for completing the preparatory reading (5 points for 5 annotations in and R for Data Science modules 1-5 (5 points each), and for recording arthropod data in their field notebook (5 points).


The field work can be completed in any habitat with enough space to plot multiple 5-meter transects for sweet net sampling, ideally from at least two different conditions (e.g., vegetation height, size of patch, etc.) Sweep net sampling cannot be conducted during precipitation or when vegetation is wet. Students analyze class data using R in the following week(s).


Field Ecology and Methods (AEC 460) exposes senior students to the diverse field approaches used to address ecological questions. The course considers and implements a variety of field approaches to characterize communities of interest, from microcosm experiments to forest systems. The course comprises a single lecture + lab section with enrollment capped at 25, and we complete this lab first to lay a foundation for collaborative project development, data curation and analysis that will be practiced across the remainder of the semester. We collected data at the North Carolina Museum of Art (NCMA) park, though we refer to "field site" in the Detailed Description of the Experiment for Students below.


This experiment can be readily scaled across class sizes and adapted for majors, non-majors, intro or upper division courses. The comparative premise also translates readily across geographic regions or to urban environments, though the method requires dry conditions and temperatures warm enough to support arthropod activity. The field site can be selected to support students of varying abilities, and the methods and data analysis activities can be adapted for a variety of pre-college environments. We ask students to complete 5 R for Data Science Modules that are curated by NC State University Libraries and only available to NC State affiliates via Shibboleth-protected access. However, we have identified a free Data Analysis with R on Coursera that covers similar concepts.


Description of other Resource Files:

  • Arthropod lab overview [docx][pdf]
  • Arthropod lab guide [docx][pdf]
  • Data visualization presentation [pptx]
  • 2022 Sample data [xlsx]
  • 2023 Sample data [xlsx]


Madison Polera helped Erin develop the original methods and base code for this experiment in fall 2019 during their first semester teaching AEC 460 at NC State University. Madison also refined the base code in fall 2021 when we adapted the sweep net experiment to compare arthropod diversity on Western Boulevard medians in fall 2021. Those materials and experiences provided a strong foundation for the experiment and code we present here.


Erin A. McKenney and Ana M. Meza-Salazar. February 2024. A field lab designed to guide student research from sweepnet to statistical analysis. Teaching Issues and Experiments in Ecology, Vol. 20: Experiment #1.

Field Ecology students compare arthropod communities associated with adjacent cut (lawn) and uncut (meadow) vegetation. Arthropods are sampled using sweep nets along 5m transects and identified using iNaturalist and printed field guides. Data are curated in Google Sheets and analyzed in R. (Photo credit: Michelle Jewell)