American Society of Naturalists

A membership society whose goal is to advance and to diffuse knowledge of organic evolution and other broad biological principles so as to enhance the conceptual unification of the biological sciences.

2024 American Naturalist Student Paper Award

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Gregor-Fausto Siegmund
Gregor-Fausto Siegmund

The American Naturalist 2024 Student Paper Award is for work that was published in 2023 and that was performed primarily by the first author and primarily while she or he was an undergraduate or graduate student. The Editors of the journal, in consultation with Associate Editors, examine all student-authored papers in the journal to select an outstanding contribution that advances the journal’s goals of changing the way people think about organismal biology (including but not limited to ecology, evolution, and behavior) by providing new conceptual insights.


Gregor-Fausto Siegmund, David A. Moeller, Vincent M. Eckhart, and Monica A. Geber. 2023. “Bet Hedging Is Not Sufficient to Explain Germination Patterns of a Winter Annual Plant.” The American Naturalist 202:767–784.

In this paper, Gregor-Fausto Siegmund and colleagues test a classic bet-hedging hypothesis for delayed germination of seeds in the seed bank. This is a literal textbook example in ecology used to explain how species can deal with variable and unpredictable environments, but is bet-hedging enough to explain what is going on in the field? Utilizing an immense data set in Clarkia xantiana encompassing 20 populations and 15 years, Siegmund et al. estimate key life history parameters and the rate of germination that would maximize geometric mean fitness. The found that these optimal rates are often several times higher than observed rates, so something other than, or in addition to, bet-hedging seems to be in operation. The authors’ exploratory analyses suggest that the discrepancy can explain density dependence in germination and fruiting success.

This paper is a perfect example of integrating long-term data, experimental work, and theoretical modeling to “change the way people think” about a classic question and system. Both editors and reviewers of the paper were impressed by the meticulous quantification of vital rates that allowed robust quantitative predictions for optimal bet-hiding rates. The paper also illustrates the unique insights one can obtain from long-term population studies across multiple populations, which are increasingly important to understanding how species respond to changing conditions.

Honorable mention:

Noah S. B. Houpt and Rees Kassen. 2023. “On the de novo emergence of ecological interactions during evolutionary diversification: A conceptual framework and experimental test.” The American Naturalist 202:800–817.

In this paper, Noah Houpt and Rees Kassen tackle an extremely interesting question: how do novel ecological interactions evolve? We know from microbial experimental evolution that even a single strain of bacterium, when given enough time, can differentiate into strains or isolates that are ecologically distinct. But we don’t yet know the details of this process: what kind of ecological interactions evolve? Do different kinds of interactions evolve in different environments? These are the fundamental questions that Houpt and Kassen tackle. They use a microbial evolution experiment where an ancestral strain of Pseudomonas aeruginosa evolves in nutritionally simple or complex environments. They propose an intuitive new framework to classify the kind of ecological interactions that evolve based on how the evolved isolates perform by themselves versus their evolved communities in the evolved or non-evolved environments. They show that most lines evolve positive ecological interactions that make communities more fit than individual isolates. However, an ingenious dilution experiment shows unexpectedly that this seems to be driven at least in part by variants that evolved that don’t themselves reach high frequency. These results highlight that there is still much to be learned about how ecological diversity and interaction networks evolve even in “simple” systems.