
@article {160485,
	title = {Founders predict trait evolution and population performance after evolutionary rescue in the red flour beetle.},
	journal = {Proc Natl Acad Sci U S A},
	volume = {122},
	year = {2025},
	month = {2025 Sep 09},
	pages = {e2506244122},
	abstract = {<p>Evolutionary rescue helps populations survive environmental change, but the phenotypic and demographic factors associated with rescue dynamics and its long-term effects remain unclear. We experimentally evolved 10 wild-collected populations of flour beetles from across India in a suboptimal corn resource for 70 generations (\&gt;5 y), collecting \&gt;10,000 population census points book-ended by measurements of fitness-related traits for 30 experimental lines. Despite clear ancestral trait differences, all lines showed highly parallel evolutionary rescue within 20 generations. Long-term average population size varied across source populations and was positively correlated with ancestral development rate, which increased convergently across populations and emerged as the single best predictor of population performance during and after evolutionary rescue. Notably, specific demographic events during rescue (such as the rate of population decline and recovery) were uncorrelated both with ancestral trait distributions and post-rescue adaptation. Our results support prior work showing founder traits as key predictors of adaptation, and highlight their role in long-term adaptation and trait evolution following evolutionary rescue.</p>
},
	keywords = {Adaptation, Physiological, Animals, Biological Evolution, Coleoptera, India, Phenotype, Population Density, Population Dynamics},
	issn = {1091-6490},
	doi = {10.1073/pnas.2506244122},
	author = {Ravi Kumar, Vrinda and Buddh, Shyamsunder and Singhal, Shivansh and Prakash, Arun and Agashe, Deepa}
}
@article {123070,
	title = {Fitness landscapes reveal context-dependent benefits of oviposition behavior.},
	journal = {Evolution},
	volume = {77},
	year = {2023},
	month = {2022 Dec 08},
	pages = {550-561},
	abstract = {<p>Resource choice behavior has enormous fitness consequences and can drive niche expansion. However, individual behavioral choices are often mediated by context, determined by past experience. Do such context-dependent behaviors reflect maladaptive variation or are they locally adaptive? Using Tribolium castaneum (the red flour beetle), we demonstrate that context-dependent oviposition behavior reflects distinct, context-specific local fitness peaks. We measured offspring fitness to generate fitness landscapes as a function of all possible oviposition behaviors (i.e., combinations of fecundity and resource preference) in a habitat containing optimal and suboptimal resource patches. We did this by experimentally manipulating egg allocation across patches, which allowed us to assess behaviors not typically observed in the laboratory. We found that females from different age and competition contexts exhibit distinct behaviors which optimize different fitness components, linked in a tradeoff. With prior exposure to strong competition and increasing age, females produce few but fast-developing offspring that are advantageous under high resource competition. In contrast, young na{\"\i}ve females produce significantly more (but slower developing) offspring, which is beneficial under weak competition. Systematically mapping complete context-dependent fitness landscapes is thus critical to infer behavioral optimality and offers predictive power in novel contexts.</p>
},
	issn = {1558-5646},
	doi = {10.1093/evolut/qpac035},
	author = {Ravi Kumar, Vrinda and Agavekar, Gaurav and Agashe, Deepa}
}
