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Patrick J. Sullivan

Researcher at Cornell University

Publications -  88
Citations -  2648

Patrick J. Sullivan is an academic researcher from Cornell University. The author has contributed to research in topics: Population & Rainbow smelt. The author has an hindex of 28, co-authored 87 publications receiving 2364 citations. Previous affiliations of Patrick J. Sullivan include University of Wisconsin-Madison & National Marine Fisheries Service.

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Decadal changes in growth and recruitment of Pacific halibut (Hippoglossus stenolepis)

TL;DR: The recent sustained high level of recruitment at high levels of spawning biomass has erased the previous appearance of strong density dependence in the stock-recruitment relationship and prompted a reduction in the target full- Recruitment harvest rate from 30-35 to 20-25%.
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Breeding dispersal and philopatry in the tree swallow

TL;DR: The spatial scale in which swallows gather and process information appears to be much larger than for passerines that defend all-purpose territories that defienden territorios de uso múltiple.
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When can efforts to control nuisance and invasive species backfire

TL;DR: A general population model with juvenile and adult stages is developed to help determine the conditions under which control harvest efforts can produce unintended outcomes and suggests species with high per capita fecundity, short juvenile stages, and fairly constant survivorship rates are most likely to respond undesirably to harvest.
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The effect of dams on river transport of microplastic pollution.

TL;DR: The results show that the sediment collecting behind dams is one sink for microplastics in river systems at long timescales, indicating that accounting for dams may be important when modeling global riverine microplastic transport.
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Predicting stream temperatures: geostatistical model comparison using alternative distance metrics

TL;DR: Stream temperatures were recorded over time throughout the Beaverkill Watershed and were used to identify thermal refugia and areas of thermal stress, and three geostatistical metrics for predicting temperature were constructed and evaluated.