RT Journal Article
SR Electronic
T1 Evaluating the consequences of common assumptions in run reconstructions on Pacific-salmon biological status assessments
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 868927
DO 10.1101/868927
A1 Stephanie J. Peacock
A1 Eric Hertz
A1 Carrie A. Holt
A1 Brendan Connors
A1 Cameron Freshwater
A1 Katrina Connors
YR 2020
UL http://biorxiv.org/content/early/2020/04/16/868927.abstract
AB Information on biological status is essential for designing, implementing, and evaluating management strategies and recovery plans for threatened or exploited species. However, the data required to quantify status are often limited, and it is important to understand how assessments of status may be biased by assumptions in data analysis. For Pacific salmon, biological status assessments based on spawner abundances and spawner-recruitment (SR) analyses often involve “run reconstructions” that impute missing spawner data, expand observed spawner abundance to account for unmonitored streams, assign catch to individual stocks, and quantify age-at-return. Using a stochastic simulation approach, we quantified how common assumptions in run reconstructions biased assessments of biological status based on spawner abundance. We found that status assessments were robust to most common assumptions in run reconstructions, even in the face of declining monitoring coverage, but that overestimating catch tended to increase rates of status misclassification. Our results lend confidence to biological status assessments based on spawner abundances and SR analyses, even in the face of incomplete data.Competing Interest StatementThe authors have declared no competing interest.