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A Hidden-Process Model for Estimating Prespawn Mortality Using Carcass Survey Data.

Authors :
DeWeber, J. Tyrell
Peterson, James T.
Sharpe, Cameron
Kent, Michael L.
Colvin, Michael E.
Schreck, Carl B.
Source :
North American Journal of Fisheries Management; Feb2017, Vol. 37 Issue 1, p162-175, 14p
Publication Year :
2017

Abstract

After returning to spawning areas, adult Pacific salmonOncorhynchusspp. often die without spawning successfully, which is commonly referred to as prespawn mortality. Prespawn mortality reduces reproductive success and can thereby hamper conservation, restoration, and reintroduction efforts. The primary source of information used to estimate prespawn mortality is collected through carcass surveys, but estimation can be difficult with these data due to imperfect detection and carcasses with unknown spawning status. To facilitate unbiased estimation of prespawn mortality and associated uncertainty, we developed a hidden-process mark–recovery model to estimate prespawn mortality rates from carcass survey data while accounting for imperfect detection and unknown spawning success. We then used the model to estimate prespawn mortality and identify potential associated factors for 3,352 adult spring Chinook SalmonO. tshawytschathat were transported above Foster Dam on the South Santiam River (Willamette River basin, Oregon) from 2009 to 2013. Estimated prespawn mortality was relatively low (≤13%) in most years (interannual mean = 28%) but was especially high (74%) in 2013. Variation in prespawn mortality estimates among outplanted groups of fish within each year was also very high, and some of this variation was explained by a trend toward lower prespawn mortality among fish that were outplanted later in the year. Numerous efforts are being made to monitor and, when possible, minimize prespawn mortality in salmon populations; this model can be used to provide unbiased estimates of spawning success that account for unknown fate and imperfect detection, which are common to carcass survey data. Received April 11, 2016; accepted October 2, 2016Published online January 9, 2017 [ABSTRACT FROM PUBLISHER]

Details

Language :
English
ISSN :
02755947
Volume :
37
Issue :
1
Database :
Supplemental Index
Journal :
North American Journal of Fisheries Management
Publication Type :
Academic Journal
Accession number :
121393226
Full Text :
https://doi.org/10.1080/02755947.2016.1245223