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Shannon White

Publications and source records attributed to Shannon White.

2 recordsLinked to original sources

Behavior at short temporal scales drives dispersal dynamics and survival in a metapopulation of brook trout (Salvelinus fontinalis)

1) Movement has been studied extensively in stream salmonids, and most data suggest that population-level behavior is best described by a leptokurtic distribution. This distribution emphasizes the large proportion of sedentary individuals in a population, which can implicitly lead to assumptions of low population connectivity and overlook the ecological significance of rare individuals with more mobile phenotypes. 2) We report findings of a multi-season radio telemetry study conducted on four adjacent populations of wild brook trout ( Salvelinus fontinalis ) connected by Loyalsock Creek in northcentral Pennsylvania. We used these data to investigate temporal and spatial patterns in movement and fitness tradeoffs associated with behavioral phenotype. 3) Similar to previous studies, we found that 59 of the 120 radio-tagged individuals (49%) were sedentary and moved less than 200 m. Only 18% of individuals dispersed more than 1 km, but the maximum distanced moved exceeded 13 km. We also found that mobile individuals had significantly higher summer and fall survival than did sedentary fish, which could indicate that there are fitness benefits associated with vagility. 4) Most long-distance movements were the result of fish migrating from small tributaries into a larger mainstem river in the days after spawning. Therefore, even though mobility was only expressed for a short duration and by relatively few individuals in the population, the behavior appears to maintain metapopulation connectivity throughout the watershed. 5) Our study highlights the ecological significance of rare phenotypes for population demography across large spatial scales and the need to understand movement across multiple temporal and spatial scales to ensure adequate conservation of critical forms of cryptic life history diversity.

Pennsylvania

Predicting fish species richness and habitat relationships using Bayesian hierarchical multispecies occupancy models

Understanding how stream fishes respond to changes in habitat availability is complicated by low occurrence rates of many species, which in turn reduces the ability to quantify species–habitat relationships and account for imperfect detection in estimates of species richness. Multispecies occupancy models have been used sparingly in the analysis of fisheries data, but address the aforementioned deficiencies by allowing information to be shared among ecologically similar species, thereby enabling species–habitat relationships to be estimated for entire fish communities, including rare species. Here, we highlight the utility of hierarchical multispecies occupancy models for the analysis of fish community data and demonstrate the modeling framework on a stream fish community dataset collected in the Delaware Water Gap National Recreation Area, USA. In particular, we demonstrate the ability of the modeling framework to make inferences at the species-, guild-, and community-levels, thereby making it a powerful tool for understanding and predicting how environmental variables influence species occupancy probabilities and structure fish assemblages.

New York New Jersey, Pennsylvania