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Data from: Food-limited mothers favor offspring quality over offspring number: a principal components approach

Cite this dataset

Stahlschmidt, Zachary R.; Adamo, Shelley A. (2015). Data from: Food-limited mothers favor offspring quality over offspring number: a principal components approach [Dataset]. Dryad.


Mothers are expected to balance the tradeoff between the number and quality of offspring, and many theoretical studies describe how the maternal environment might influence the evolution of the number-quality tradeoff. However, few empirical studies attempt to test these theories (and their assumptions) by measuring the fitness consequences of variation in investment per offspring. Part of the problem is that measuring offspring fitness is difficult, which frequently leads experimenters to measure several proxies of offspring fitness in place of a comprehensive fitness assay. This strategy tends to result in multiple univariate analyses that involve different offspring fitness proxies, and these tests can have low power and may produce conflicting conclusions. Here, we demonstrate the benefits of integrating maternal fecundity and proxies of offspring size and fitness into multivariate analyses to elucidate variation in reproductive allocation strategies. In a 2×2 factorial experiment, we manipulated the quality of maternal environment (food availability) throughout early and late adulthood (acute and chronic exposure to the maternal environment) in a field cricket. We developed a multivariate index of reproductive allocation by incorporating maternal fecundity and the performance of offspring in low- and high-food environments into a principle components analysis. This index of reproductive allocation indicated that females decreased fecundity and increased offspring quality after chronic exposure to low-food environments, thereby providing evidence of adaptive plasticity in investment per offspring. In contrast, few treatment effects were observed using univariate analyses. The present study demonstrates that multivariate analysis can increase our ability to assess the adaptive significance of reproductive strategies, particularly in situations when offspring size and fitness are difficult to measure with accuracy. Such an approach might ultimately help assess the adaptive significance of reproductive allocation across a wider range of taxa, thereby providing broader insight into the evolution of reproductive strategies.

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