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You are here: Home / Resources / Climate Science Documents / Seasonal weather patterns drive population vital rates and persistence in a stream fish

Seasonal weather patterns drive population vital rates and persistence in a stream fish

Here, we investigated effects of seasonal air temperature and precipitation (fall, winter, and spring) on survival and recruitment of brook trout (Salvelinus fontinalis) at a broad spatial scale using a novel stage-structured population model. The data were a 15-year record of brook trout abundance from 72 sites distributed across a 170-km-long mountain range in Shenandoah National Park, Virginia, USA. Population vital rates responded differently to weather and site-specific conditions. Specifically, young-of-year survival was most strongly affected by spring temperature, adult survival by elevation and per-capita recruitment by winter precipitation. Low fall precipitation and high winter precipitation, the latter of which is predicted to increase under climate change for the study region, had the strongest negative effects on trout populations. Simulations show that trout abundance could be greatly reduced under constant high winter precipitation, consistent with the expected effects of gravel-scouring flows on eggs and newly hatched individuals. However, high-elevation sites would be less vulnerable to local extinction because they supported higher adult survival. Furthermore, the majority of brook trout populations are projected to persist if high winter precipitation occurs only intermittently (≤3 of 5 years) due to density-dependent recruitment. Variable drivers of vital rates should be commonly found in animal populations characterized by ontogenetic changes in habitat, and such stage-structured effects may increase population persistence to changing climate by not affecting all life stages simultaneously. Yet, our results also demonstrate that weather patterns during seemingly less consequential seasons (e.g., winter precipitation) can have major impacts on animal population dynamics.

Publication Date: 2015

Credits: Global Change Biology (2015) 21, 1856–1870, doi: 10.1111/gcb.12837

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