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Developing a flexible learning activity on biodiversity and spatial scale concepts using open-access vegetation datasets from the National Ecological Observatory Network.

Authors :
Styers DM
Schafer JL
Kolozsvary MB
Brubaker KM
Scanga SE
Anderson LJ
Mitchell JJ
Barnett D
Source :
Ecology and evolution [Ecol Evol] 2021 Mar 21; Vol. 11 (9), pp. 3660-3671. Date of Electronic Publication: 2021 Mar 21 (Print Publication: 2021).
Publication Year :
2021

Abstract

Biodiversity is a complex, yet essential, concept for undergraduate students in ecology and other natural sciences to grasp. As beginner scientists, students must learn to recognize, describe, and interpret patterns of biodiversity across various spatial scales and understand their relationships with ecological processes and human influences. It is also increasingly important for undergraduate programs in ecology and related disciplines to provide students with experiences working with large ecological datasets to develop students' data science skills and their ability to consider how ecological processes that operate at broader spatial scales (macroscale) affect local ecosystems. To support the goals of improving student understanding of macroscale ecology and biodiversity at multiple spatial scales, we formed an interdisciplinary team that included grant personnel, scientists, and faculty from ecology and spatial sciences to design a flexible learning activity to teach macroscale biodiversity concepts using large datasets from the National Ecological Observatory Network (NEON). We piloted this learning activity in six courses enrolling a total of 109 students, ranging from midlevel ecology and GIS/remote sensing courses, to upper-level conservation biology. Using our classroom experiences and a pre/postassessment framework, we evaluated whether our learning activity resulted in increased student understanding of macroscale ecology and biodiversity concepts and increased familiarity with analysis techniques, software programs, and large spatio-ecological datasets. Overall, results suggest that our learning activity improved student understanding of biological diversity, biodiversity metrics, and patterns of biodiversity across several spatial scales. Participating faculty reflected on what went well and what would benefit from changes, and we offer suggestions for implementation of the learning activity based on this feedback. This learning activity introduced students to macroscale ecology and built student skills in working with big data (i.e., large datasets) and performing basic quantitative analyses, skills that are essential for the next generation of ecologists.<br />Competing Interests: The authors declare no conflicts of interest.<br /> (© 2021 The Authors. Ecology and Evolution published by John Wiley & Sons Ltd.)

Details

Language :
English
ISSN :
2045-7758
Volume :
11
Issue :
9
Database :
MEDLINE
Journal :
Ecology and evolution
Publication Type :
Academic Journal
Accession number :
33976765
Full Text :
https://doi.org/10.1002/ece3.7385