Diapause is not selected as a bet-hedging strategy in insects: a meta-analysis of reaction norm shapes
Cite this dataset
Joschinski, Jens; Bonte, Dries (2020). Diapause is not selected as a bet-hedging strategy in insects: a meta-analysis of reaction norm shapes [Dataset]. Dryad. https://doi.org/10.5061/dryad.9kd51c5d1
Many organisms escape from lethal climatological conditions by entering a resistant resting stage called diapause, and it is essential that this strategy remains optimally timed with seasonal change. Climate change therefore exerts selection pressure on phenology, which is expected to cause the evolution of mean diapause timing, but also phenotypic plasticity and bet-hedging strategies. Especially the latter as a strategy to cope with unpredictability is so far little considered in the context of climate change, and it is unknown whether it can readily evolve.
Contemporary patterns of phenological strategies across a geographic range may provide information about their evolvability. We thus extracted 458 diapause reaction norms from 60 studies. First, we correlated mean diapause timing with mean winter onset. Then we partitioned the reaction norm variance into a temporal component (phenotypic plasticity) and among-offspring variance (diversified bet-hedging) and correlated this variance composition with predictability of winter onset. Contrary to our expectation, mean diapause timing correlated only weakly with mean winter onset, as populations at high latitudes failed to track early onsets. Variance among offspring was also limited and correlated only weakly with environmental predictability, indicating little scope for bet-hedging. We conclude that constraints may limit the evolution of phenology in a rapidly changing climate.
This dataset includes literature search results, data extraction procedures and analysis scripts for a meta-analysis, in addition scripts and outputs of a climate data analysis. All methods can be found in the accompanying manuscript (see references), and further information can be also found in the readme files in the subfolders of the dataset.
The climate data analysis requires the GHCN-Daily dataset from the NOAA server. The dataset has to be extracted in the correct subfolder, as indicated in the script in subfolder "clim_read"
Deutsche Forschungsgemeinschaft, Award: 398170603
Research Foundation - Flanders, Award: G018017N