The inclusion of immediate and lagged climate responses amplifies the effect of climate autocorrelation on long-term growth rate of populations

Climate variability will increase with climate change, and thus it is important for population ecologists to understand its consequences for population dynamics. Four components are known to mediate the consequences of climate variability: the magnitude of climate variability, the effect size of climate on vital rates, covariance between vital rates and autocorrelation in climate. Recent studies have pointed to a potential fifth component: vital rates responding to climate in different timeframes, with some responding more immediately and some having lagged responses. We use simulations to quantify how all five components modify the consequences of climatic variability on long-term population growth rates across a range of life histories defined by life expectancy and iteroparity. We use an established method to compose Matrix Population Models for 147 life histories. Our simulations show that including different timeframes for vital rates responses to climate can either reduce or amplify the negative influence of climate variability on long-term population growth rates. The negative effect of different timeframes for vital rates responses on population growth is amplified when climatic autocorrelations are negative, and when species are long-lived. Synthesis. The existing literature shows that vital rates often respond to climate in different timeframes, and that studies often ignore climate autocorrelation. Our results show that simultaneously including both of these factors can substantially increase or decrease a population's expected growth rate. Moreover, the relative magnitude of this change increases with the generation time of a life history. Our results are relevant to conservation, population forecasts and population modelling in general.