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Data from: Individual variation in plasticity dulls transgenerational responses to stress

Citation

Gillis, Michael K.; Walsh, Matthew R. (2019), Data from: Individual variation in plasticity dulls transgenerational responses to stress, Dryad, Dataset, https://doi.org/10.5061/dryad.h09hj3b

Abstract

1. Much research has shown that environmental stress can induce adaptive and maladaptive phenotypic changes in organisms that persist for multiple generations. Such transgenerational phenotypic plasticity shrouds our understanding of the long-term consequences of ongoing anthropogenic pressures. 2. Here, we evaluated within- and transgenerational phenotypic responses to food stress in the freshwater crustacean, Daphnia. We reared 45 clones of Daphnia pulicaria each on high-quality Scenedesmus and low-quality (but also non-toxic) cyanobacteria (generation 1). Offspring produced by generation 1 adults were then reared on Scenedesmus (generation 2) and life history traits were measured across both generations. 3. The results show that Daphnia in generation 1 exhibited reduced fitness (i.e. delayed maturation, lower reproductive output, increased clutch interval) when reared in the presence of cyanobacteria as opposed to high-quality food. However, maternal stress had no clear influence on the fitness of offspring. That is, Daphnia in the second experimental generation had similar mean trait values, irrespective of whether their mothers were reared on cyanobacteria or high-quality food. 4. Signals of transgenerational life history effects were obscured, in part, by extensive clonal variation among Daphnia in the direction of transgenerational responses to cyanobacteria (i.e. adaptive and maladaptive plasticity). Further analyses demonstrated that such individual variance in plasticity might be open to selection and potentially offer a means of contemporary adaptation to cyanobacteria. Taken together, our results denote a link between the overall strength of transgenerational responses to the environment and the potential for rapid evolution in populations.

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Funding

National Science Foundation, Award: DEB-1544356, IOS-1651613