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Seasonal streamflow extremes are key drivers of Brook Trout young‐of‐the‐year abundance

August 1, 2018

To manage ecosystems in the context of climate change, we need to understand the relationship between extreme events and population dynamics. Floods and droughts are projected to occur more frequently, but how aquatic species will respond to these extreme events remains uncertain. Based on counts of Brook Trout (Salvelinus fontinalis) collected over 28 yr at 115 sites in Shenandoah National Park, we developed mixed‐effects models to (1) assess how well extreme streamflow, as compared to mean flows and total precipitation, can explain young‐of‐the‐year (YOY) abundance, (2) identify potential nonlinear relationships between seasonal environmental covariates and abundance using nonlinear generalized additive mixed models, and (3) explore likely impacts of expected future weather and streamflow conditions. We found that (1) using covariates of streamflow extremes improved prediction of YOY abundance compared to use of mean seasonal flow values or precipitation as a proxy, (2) warmer maximum daily spring temperatures were associated with increased YOY abundance up to about 1.5 standard deviations, above which abundance declined, and (3) a strong negative effect of extreme winter streamflow, unlikely to be offset by possibly positive effects from other seasons, is expected to have a detrimental impact on Brook Trout populations given predicted increases in winter precipitation. Because YOY abundance is a strong determinant of population dynamics for these short‐lived species, extreme events will have the potential to exert a strong influence on population persistence of Brook Trout in a changing climate. Management actions that maximize resiliency of populations in response to extreme events, such as restoration of habitat connectivity, should be prioritized to buffer negative impacts.

Citation Information

Publication Year 2018
Title Seasonal streamflow extremes are key drivers of Brook Trout young‐of‐the‐year abundance
DOI 10.1002/ecs2.2356
Authors Annalise G. Blum, Yoichiro Kanno, Benjamin H. Letcher
Publication Type Article
Publication Subtype Journal Article
Series Title Ecosphere
Series Number
Index ID 70200933
Record Source USGS Publications Warehouse
USGS Organization Leetown Science Center