scholarly journals Running the gauntlet: Connectivity between spawning and nursery areas for arrowtooth flounder (Atheresthes stomias) in the Gulf of Alaska, as inferred from a biophysical individual-based model

2019 ◽  
Vol 165 ◽  
pp. 127-139 ◽  
Author(s):  
William T. Stockhausen ◽  
Kenneth O. Coyle ◽  
Albert J. Hermann ◽  
Deborah Blood ◽  
Miriam J. Doyle ◽  
...  
2019 ◽  
Author(s):  
James J. Ruzicka ◽  
Stephen Kasperski ◽  
Stephani Zador ◽  
Amber Himes‐Cornell

2018 ◽  
Vol 142 ◽  
pp. 28-51 ◽  
Author(s):  
Miriam J. Doyle ◽  
Casey Debenham ◽  
Steven J. Barbeaux ◽  
Troy W. Buckley ◽  
Jodi L. Pirtle ◽  
...  

2019 ◽  
Vol 165 ◽  
pp. 113-126 ◽  
Author(s):  
S. Hinckley ◽  
W.T. Stockhausen ◽  
K.O. Coyle ◽  
B.J. Laurel ◽  
G.A. Gibson ◽  
...  

2010 ◽  
Vol 67 (7) ◽  
pp. 1135-1148 ◽  
Author(s):  
Kray F. Van Kirk ◽  
Terrance J. Quinn ◽  
Jeremy S. Collie

Predation is the largest source of mortality for marine fish and may be an important process in regulating population size. Recent population models have attempted to quantify predation separately from other sources of natural mortality. Building upon such work, a multispecies age-structured assessment model (MSASA) for the Gulf of Alaska was developed, which included arrowtooth flounder ( Atheresthes stomias ), Pacific cod ( Gadus macrocephalus ), and walleye pollock ( Theragra chalcogramma ). Predation mortality was a flexible function of predator and prey abundances that was fitted to stomach-content data. A proof of concept illustration is presented here, assessing model outputs against a set of single-species models. The MSASA model was able to successfully estimate predation between species and integrate it into total mortality. Significant predation occurred on younger pollock and flounder. Results indicate a significant change in predation over time on pollock as a function of increased arrowtooth flounder abundance. Estimating mortality and other parameters for three species simultaneously is complex, and the advantage of greater biological realism of MSASA comes at the expense of greater uncertainty in parameter estimation.


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