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Summary Abundance of the young‐of‐the‐year (YOY) fish can vary greatly among years and it may be driven by several key biological processes (i.e. adult spawning, egg survival and fry survival) that span several months. However, the relative influence of seasonal weather patterns on YOY abundance is poorly understood. We assessed the importance of seasonal air temperature (a surrogate for stream temperature) and precipitation (a surrogate for stream flow) on brook trout (Salvelinus fontinalis) YOY summer abundance using a 29‐year data set from 115 sites in Shenandoah National Park, Virginia, U.S.A. We used a Bayesian hierarchical model that allowed the effect of seasonal weather covariates to vary among sites and accounted for imperfect detection of individuals. Summer YOY abundance was affected by preceding seasonal air temperature and precipitation, and these regional‐scale drivers led to spatial synchrony in YOY abundance dynamics across the 170‐km‐long study area. Mean winter precipitation had the greatest effect on YOY abundance and the relationship was negative. Mean autumn precipitation, and winter and spring temperature had significantly positive effects on YOY abundance, and mean autumn temperature had a significant negative effect. In addition, the effect of summer precipitation differed along a latitudinal gradient, with YOY abundance at more northern sites being more responsive to inter‐annual variation in summer precipitation. Strong YOY years resulted in high abundance of adults (>age 1 + fish) in the subsequent year at more than half of sites. However, higher adult abundance did not result in higher YOY abundance in the subsequent year at any of the study sites (i.e. no positive stock–recruitment relationship). Our results indicate that YOY abundance is a key driver of brook trout population dynamics that is mediated by seasonal weather patterns. A reliable assessment of climate change impacts on brook trout needs to account for how alternations in seasonal weather patterns impact YOY abundance and how such relationships may differ across the range of brook trout distribution.

Numerous studies have documented the decline of amphibians following timber harvest. However, direct evidence concerning the mechanisms of population decline is lacking and hinders attempts to develop conservation or recovery plans and solutions for forest species. We summarized the mechanisms by which abundance of amphibians may initially decline following timber harvest into three testable hypotheses: (1) mortality, (2) retreat, and (3) evacuation. Here, we tested the evacuation hypothesis within a large-scale, replicated experiment. We used drift fences with pitfall traps to capture pond-breeding amphibians moving out of experimental clearcut quadrants and into control quadrants at four replicate arrays located within the Daniel Boone Conservation Area on the upper Ozark Plateau in Warren County, Missouri, USA. During the preharvest year of 2004, only 51.6% of the 312 individuals captured were moving out of pre-clearcut quadrants, and movement did not differ from random. In contrast, during both postharvest years of 2005 and 2006, the number of captures along the quadrant edge increased, and a higher proportion of individuals (59.9% and 56.6%, respectively, by year) were moving out of clearcut quadrants than entering. Salamanders moved out of clearcuts in large percentages (Ambystoma annulatum, 78.2% in 2005, 78.2% in 2006; A. maculatum, 64.0% in 2005, 57.1% in 2006). Frogs and toads also moved out of clearcut quadrants, but in lower percentages (Bufo americanus, 59.6% in 2005, 53.3% in 2006; Rana clamitans, 52.7% in 2006). Salamanders moved out of clearcuts with low-wood treatments more than out of clearcuts with high-wood treatments. Movement of salamanders out of clearcuts was independent of sex. Estimated movement out of clearcuts represented between 8.7% and 35.0% of the total breeding adults captured for two species of salamanders. Although we recognize that some portion of the amphibian population may retreat underground for short periods and others may not survive the effects of timber harvest, these data are the first direct evidence showing that individuals are capable of leaving clearcuts and shifting habitat use.

Water temperature is a primary driver of stream ecosystems and commonly forms the basis of stream classifications. Robust models of stream temperature are critical as the climate changes, but estimating daily stream temperature poses several important challenges. We developed a statistical model that accounts for many challenges that can make stream temperature estimation difficult. Our model identifies the yearly period when air and water temperature are synchronized, accommodates hysteresis, incorporates time lags, deals with missing data and autocorrelation and can include external drivers. In a small stream network, the model performed well (RMSE = 0.59°C), identified a clear warming trend (0.63 °C decade−1) and a widening of the synchronized period (29 d decade−1). We also carefully evaluated how missing data influenced predictions. Missing data within a year had a small effect on performance (∼0.05% average drop in RMSE with 10% fewer days with data). Missing all data for a year decreased performance (∼0.6 °C jump in RMSE), but this decrease was moderated when data were available from other streams in the network.

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