Brenda L. Norcross

University of Alaska Fairbanks

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Franz J. Mueter

University of Alaska Fairbanks

Andrew C. Seitz

University of Alaska Fairbanks

Ron A. Heintz

Sitka Sound Science Center

Brenda A. Holladay

University of Alaska Fairbanks

Arny L. Blanchard

University of Alaska Fairbanks

Robert J. Foy

NOAA National Marine Fisheries Service

Kevin D. E. Stokesbury

University of Massachusetts Dartmouth

Kevin M. Boswell

Florida International University

Herbert M. Austin

William & Mary

Adam Moles

NOAA National Marine Fisheries Service

Cooperative Institutions

University of Alaska Fairbanks

National Oceanic and Atmospheric Administration

NOAA National Marine Fisheries Service

NOAA National Marine Fisheries Service Alaska Fisheries Science Center

United States Geological Survey

University of Washington

Consejo Superior de Investigaciones Científicas

Fisheries and Oceans Canada

United States Fish and Wildlife Service

Oceanography Society

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Habitats and Demersal Fish Communities in the Vicinity of Albatross Bank, Gulf of Alaska

Elsevier eBooks (2011)

Jennifer R. Reynolds Sean Charles Rooney Jonathan Heifetz H. Gary Greene Brenda L. Norcross

Albatross

Petroleum seep

Forearc

Demersal zone

Bedrock

Demersal fish

Accretionary wedge

10.1016/b978-0-12-385140-6.00038-4

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Citations (2)

Hypothetical Northern Spawning Limit and Larval Transport of Spot

Brenda L. Norcross Deborah A. Bodolus

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Citations (3)

Times Series Analyses as a Means of Examining Long Term Biological Data Sets

Oceans (1986)

Herbert M. Austin D. Evans Brenda L. Norcross

Biologists, and other environmental scientists have traditionally used central tendency statistical analyses (eg. correlative analysis) to describe and quantify the variance between two variables. These analyses are best suited for situations where the dependent and independent variables are a priori defined. In marine systems, where the causal relationship is not always clear, the chance for misinterpretation is introduced. This is particularly so for monitoring programs of resource stocks when investigating the causes of fluctuations or trends in abundance, be they natural (climate), man-made (pollution) or due to fishing pressure. While much can be learned from these data using the traditional statistical approaches, more may be extracted using time series analyses. Time series models are also better suited for forecasting as they identify and partition trends and cycles that are poorly reproduced in linear correlative statistics.

Correlative

10.1109/oceans.1986.1160383

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Citations (1)

Effects of oil-laden sediments on growth and health of juvenile flatfishes

Canadian Journal of Fisheries and Aquatic Sciences (1998)

Adam Moles Brenda L. Norcross

Juvenile yellowfin sole (Pleuronectes asper), rock sole (Pleuronectes bilineatus), and Pacific halibut (Hippoglossus stenolepis) had reduced growth following 30-90 days of exposure to sediments laden with Alaska North Slope crude oil. Changes in fish health bioindicators after 90 days, i.e., increases in fin erosion, liver lipidosis, gill hyperplasia, and gill parasites, coupled with decreases in macrophage aggregates, occurred at hydrocarbon concentrations (1600 µg/g) that reduced growth 34-56% among the flatfishes. Chronic hydrocarbon pollution of nearshore nursery sediments could alter growth and health of juvenile flatfishes. Recruitment of juveniles to the fishery may decline because of increased susceptibility to predation and slower growth.

Pleuronectes

Pleuronectidae

10.1139/cjfas-55-3-605

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Citations (14)

A Comparison of Fish and Invertebrate Catch from Two Small Demersal Beam Trawls in the Beaufort Sea

American Geophysical Union eBooks (2016)

Lorena E. Edenfield Katrin Iken Brenda L. Norcross

Demersal fish

Demersal zone

Beaufort sea

Beaufort scale