Title
Understanding Drivers of Variation and Predicting Variability Across Levels of Biological Organization
Document Type
Article
Publication Date
12-2021
Abstract
Differences within a biological system are ubiquitous, creating variation in nature. Variation underlies all evolutionary processes and allows persistence and resilience in changing environments; thus, uncovering the drivers of variation is critical. The growing recognition that variation is central to biology presents a timely opportunity for determining unifying principles that drive variation across biological levels of organization. Currently, most studies that consider variation are focused at a single biological level and not integrated into a broader perspective. Here we explain what variation is and how it can be measured. We then discuss the importance of variation in natural systems, and briefly describe the biological research that has focused on variation. We outline some of the barriers and solutions to studying variation and its drivers in biological systems. Finally, we detail the challenges and opportunities that may arise when studying the drivers of variation due to the multi-level nature of biological systems. Examining the drivers of variation will lead to a reintegration of biology. It will further forge interdisciplinary collaborations and open opportunities for training diverse quantitative biologists. We anticipate that these insights will inspire new questions and new analytic tools to study the fundamental questions of what drives variation in biological systems and how variation has shaped life.
Identifier
PMID: 34259842
DOI
10.1093/icb/icab160
Publisher
Oxford University Press
Repository Citation
McEntire, K. D., Gage, M., Gawne, R., Hadfield, M. G., Hulshof, C., Johnson, M. A., Levesque, D. L., ... & Pinter-Wollman, N. (2021). Understanding drivers of variation and predicting variability across levels of biological organization. Integrative & Comparative Biology, 61(6), 2119-2131. https://doi.org/10.1093/icb/icab160
Publication Information
Integrative & Comparative Biology