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Title: Growth–defense trade-offs shape population genetic composition in an iconic forest tree species

All organisms experience fundamental conflicts between divergent metabolic processes. In plants, a pivotal conflict occurs between allocation to growth, which accelerates resource acquisition, and to defense, which protects existing tissue against herbivory. Trade-offs between growth and defense traits are not universally observed, and a central prediction of plant evolutionary ecology is that context-dependence of these trade-offs contributes to the maintenance of intraspecific variation in defense [Züst and Agrawal,Annu. Rev. Plant Biol., 68, 513–534 (2017)]. This prediction has rarely been tested, however, and the evolutionary consequences of growth–defense trade-offs in different environments are poorly understood, especially in long-lived species [Cipolliniet al.,Annual Plant Reviews(Wiley, 2014), pp. 263–307]. Here we show that intraspecific trait trade-offs, even when fixed across divergent environments, interact with competition to drive natural selection of tree genotypes corresponding to their growth–defense phenotypes. Our results show that a functional trait trade-off, when coupled with environmental variation, causes real-time divergence in the genetic architecture of tree populations in an experimental setting. Specifically, competitive selection for faster growth resulted in dominance by fast-growing tree genotypes that were poorly defended against natural enemies. This outcome is a signature example of eco-evolutionary dynamics: Competitive interactions affected microevolutionary trajectories on a timescale relevant to subsequent ecological interactions [Brunneret al.,Funct. Ecol.33, 7–12 (2019)]. Eco-evolutionary drivers of tree growth and defense are thus critical to stand-level trait variation, which structures communities and ecosystems over expansive spatiotemporal scales.

 
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NSF-PAR ID:
10305838
Author(s) / Creator(s):
; ; ;
Publisher / Repository:
Proceedings of the National Academy of Sciences
Date Published:
Journal Name:
Proceedings of the National Academy of Sciences
Volume:
118
Issue:
37
ISSN:
0027-8424
Page Range / eLocation ID:
Article No. e2103162118
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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