Geology topics

Kasey C. Pregler

Publications and source records attributed to Kasey C. Pregler.

3 recordsLinked to original sources

USGS2023

Spatial asynchrony and cross-scale climate interactions in populations of a coldwater stream fish

Climate change affects populations over broad geographic ranges due to spatially autocorrelated abiotic conditions known as the Moran effect. However, populations do not always respond to broad-scale environmental changes synchronously across a landscape. We combined multiple datasets for a retrospective analysis of time-series count data (5–28 annual samples per segment) at 144 stream segments dispersed over nearly 1,000 linear kilometers of range to characterize the population structure and scale of spatial synchrony across the southern native range of a coldwater stream fish (brook trout, Salvelinus fontinalis ), which is sensitive to stream temperature and flow variations. Spatial synchrony differed by life stage and geographic region: it was stronger in the juvenile life stage than in the adult life stage and in the northern sub-region than in the southern sub-region. Spatial synchrony of trout populations extended to 100–200 km but was much weaker than that of climate variables such as temperature, precipitation, and stream flow. Early life stage abundance changed over time due to annual variation in summer temperature and winter and spring stream flow conditions. Climate effects on abundance differed between sub-regions and among local populations within sub-regions, indicating multiple cross-scale interactions where climate interacted with local habitat to generate only a modest pattern of population synchrony over space. Overall, our analysis showed higher degrees of response heterogeneity of local populations to climate variation and consequently population asynchrony than previously shown based on analysis of individual, geographically restricted datasets. This response heterogeneity indicates that certain local segments characterized by population asynchrony and resistance to climate variation could represent unique populations of this iconic native coldwater fish that warrant targeted conservation. Advancing the conservation of this species can include actions that identify such priority populations and incorporate them into landscape-level conservation planning. Our approach is applicable to other widespread aquatic species sensitive to climate change.

Global Change Biology↗

USGS2019

State-space analysis of power to detect regional brook trout population trends over time

Threats to aquatic biodiversity are expressed at broad spatial scales, but identifying regional trends in abundance is challenging owing to variable sampling designs, and temporal and spatial variation in abundance. We compiled a regional dataset of brook trout Salvelinus fontinalis counts across their southern range representing 326 sites from eight states between 1982-2014, and conducted a statistical power analysis using Bayesian state-space models to evaluate the ability to detect temporal trends by characterizing posterior distributions with three approaches. A combination of monitoring periods, number of sites and electrofishing passes, decline magnitude and different revisit patterns were tested. Power increased with monitoring periods and decline magnitude. Trends in adults were better detected than young-of-the-year fish, which showed greater inter-annual variation in abundance. The addition of weather covariates to account for the temporal variation increased power only slightly. Single- and three-pass electrofishing methods were similar in power. Finally, power was higher for sampling designs with more frequent revisits over the duration of the monitoring program. Our results provide guidance for broad-scale monitoring designs for temporal trend detection.

Canadian Journal of Fisheries and Aquatic Sciences↗

USGS2015

Seasonal temperature and precipitation regulate brook trout young-of-the-year abundance and population dynamics

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.

Virginia↗