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Larger workers outperform smaller workers across resource environments: an evaluation of demographic data using functional linear models
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  • Natalie Kerr,
  • Rosemary Malfi,
  • Neal Williams,
  • Elizabeth Crone
Natalie Kerr
Duke University

Corresponding Author:[email protected]

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Rosemary Malfi
University of Massachusetts Amherst
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Neal Williams
University of California, Davis
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Elizabeth Crone
Tufts University
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1. Behavior and organization of social groups is thought to be vital to the functioning of societies, yet the contributions of various roles within social groups towards population growth and dynamics have been difficult to quantify. A common approach to quantifying these role-based contributions is evaluating the number of individuals conducting certain roles, which ignores how behavior might scale up to effects at the population-level. Manipulative experiments are another common approach to determine population-level effects, but they often ignore potential feedbacks associated with these various roles. 2. Here, we evaluate the effects of worker size distribution in bumblebee colonies on worker production in 24 observational colonies across three environments, using functional linear models. Functional linear models are an underused correlative technique that has been used to assess lag effects of environmental drivers on plant performance. We demonstrate potential applications of this technique for exploring high-dimensional ecological systems, such as the contributions of individuals with different traits to colony dynamics. 3. We found that more larger workers had mostly positive effects and more smaller workers had negative effects on worker production. Most of these effects were only detected under low or fluctuating resource environments suggesting that the advantage of colonies with larger-bodied workers becomes more apparent under stressful conditions. 4. We also demonstrate the wider ecological application of functional linear models. We highlight the advantages and limitations when considering these models, and how they are a valuable complement to many of these performance-based and manipulative experiments.
18 Nov 2020Submitted to Ecology and Evolution
21 Nov 2020Submission Checks Completed
21 Nov 2020Assigned to Editor
23 Nov 2020Review(s) Completed, Editorial Evaluation Pending
08 Jan 2021Editorial Decision: Accept