Data and code from: Phenotypic memory drives population growth and extinction risk in a noisy environment

Random environmental fluctuations pose major threats to wild populations. As patterns of environmental noise are themselves altered by global change, there is growing need to identify general mechanisms underlying their effects on population dynamics. This notably requires understanding and predicting population responses to the color of environmental noise, i.e. its temporal autocorrelation pattern. Here, we show experimentally that environmental autocorrelation has a large influence on population dynamics and extinction rates, which can be predicted accurately provided that a memory of past environment is accounted for. We exposed near to 1000 lines of the microalgae Dunaliella salina to randomly fluctuating salinity, with autocorrelation ranging from negative to highly positive. We found lower population growth, and twice as many extinctions, under lower autocorrelation. These responses closely matched predictions based on a tolerance curve with environmental memory, showing that non-genetic inheritance can be a major driver of population dynamics in randomly fluctuating environments.  

Methods
Six strains (or mix of two strains) of the green microalgae Dunaliella salina have been exposed to 164 independant, randomly fluctuating time series of salinity, with four autocorrelation treatments. Populations were transferred twice a week for 37 transfers, and population sizes were measured after each transfer by spectrometry (optical density and fluorescence), and once a week by flow cytometry.

Optical density, fluorescence and cytometer counts are used to analyse Dunaliela population dynamics in stochastic environment. All measurements are integrated into a state-space models, assuming logistic growth between each dilution and transfer, using the R package TMB (Template Model Builder). The provided code estimates:

- the parameters of the distribution of growth rates in autocorrelated environments

- the parameters of the function relating growth to current and previous salinity.