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Environmental effects and individual body condition drive seasonal fecundity of rabbits: identifying acute and lagged processes

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Abstract

The reproduction of many species is determined by seasonally-driven resource supply. But it is difficult to quantify whether the fecundity is sensitive to short- or long-term exposure to environmental conditions such as rainfall that drive resource supply. Using 25 years of data on individual fecundity of European female rabbits, Oryctolagus cuniculus, from semiarid Australia, we investigate the role of individual body condition, rainfall and temperature as drivers of seasonal and long-term and population-level changes in fecundity (breeding probability, ovulation rate, embryo survival). We built distributed lag models in a hierarchical Bayesian framework to account for both immediate and time-lagged effects of climate and other environmental drivers, and possible shifts in reproduction over consecutive seasons. We show that rainfall during summer, when rabbits typically breed only rarely, increased breeding probability immediately and with time lags of up to 10 weeks. However, an earlier onset of the yearly breeding period did not result in more overall reproductive output. Better body condition was associated with an earlier onset of breeding and higher embryo survival. Breeding probability in the main breeding season declined with increased breeding activity in the preceding season and only individuals in good body condition were able to breed late in the season. Higher temperatures reduce breeding success across seasons. We conclude that a better understanding of seasonal dynamics and plasticity (and their interplay) in reproduction will provide crucial insights into how lagomorphs are likely to respond and potentially adapt to the influence of future climate and other environmental change.

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Wells, K., O’Hara, R. B., Cooke, B. D., Mutze, G. J., Prowse, T. A. A., & Fordham, D. A. (2016). Environmental effects and individual body condition drive seasonal fecundity of rabbits: identifying acute and lagged processes. Oecologia, 181(3), 853–864. https://doi.org/10.1007/s00442-016-3617-2

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