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Exploring links between climatic predictability and the evolution of within- and transgenerational plasticity

Cite this dataset

Halali, Sridhar; Saastamoinen, Marjo (2022). Exploring links between climatic predictability and the evolution of within- and transgenerational plasticity [Dataset]. Dryad. https://doi.org/10.5061/dryad.9ghx3ffmz

Abstract

In variable environments, phenotypic plasticity can increase fitness by providing tight environment-phenotype matching. However, adaptive plasticity is expected to evolve only when the future selective environment can be predicted based on the prevailing conditions. That is, the juvenile environment should be predictive of the adult environment (within-generation plasticity) or the parental environment should be predictive of the offspring environment (transgenerational plasticity). Moreover, environmental predictability can also shape transient responses such as stress responses in an adaptive direction. Here, we test links between environmental predictability and the evolution of adaptive plasticity by combining time series analyses and a common garden experiment using temperature as a stressor in a temperate butterfly (Melitaea cinxia). Time series analyses revealed that across-season fluctuations in temperature over 48 years are overall predictable. However, within the growing season, temperature fluctuations showed high heterogeneity across years with low autocorrelations and the timing of temperature peaks was asynchronous. Most life-history traits showed strong within-generation plasticity for temperature and traits such as body size and growth rate broke the temperature-size rule. Evidence for transgenerational plasticity, however, was weak and detected for only two traits each in an adaptive and non-adaptive direction. We suggest that the low predictability of temperature fluctuations within the growing season likely disfavours the evolution of adaptive transgenerational plasticity but instead favours strong within-generation plasticity.

Methods

Two approaches were used for data collection: (1) we used freely available time series data for temperature from 1974 to 2020 (https://en.ilmatieteenlaitos.fi/download-observations#!/) for carrying out time series analyses, and (2) we carried out a common garden experiment to quantify the extent of within- and transgenerational in life-history traits using the Glanville Fritillary butterfly (Melitaea cinxia) as the model system. All the raw data is provided here in .csv format and statistical analyses was performed using the R programming language.  

Usage notes

All provided datasets are in .csv format and do not need any special programs for opening the files. 

Funding

Helsinki Institute of Life Sciences