Random environmental fluctuations pose major threats to wild populations. As patterns of environmental noise are themselves altered by global change, there is a growing need to identify general mechanisms underlying their effects on population dynamics. This notably requires understanding and predicting population responses to the colour of environmental noise, in other words 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 nearly 1,000 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.

随机的环境波动对野生种群构成重大威胁。由于环境噪声的模式本身会因全球变化而改变，因此越来越需要确定其对人口动态影响的一般机制。这尤其需要理解和预测人口对环境噪声颜色的反应，换句话说，就是它的时间自相关模式。在这里，我们通过实验证明，环境自相关对种群动态和灭绝率有很大影响，只要考虑到过去环境的记忆，就可以准确预测。我们暴露了近 1000 株微藻杜氏盐藻随机波动的盐度，自相关范围从负到高度正。在较低的自相关性下，我们发现人口增长较低，灭绝数量增加了一倍。这些反应与基于耐受曲线的预测与环境记忆密切匹配，表明非遗传遗传可能是随机波动环境中种群动态的主要驱动力。