Factors affecting inferences on natural mortality and associated environmental effects in state-space age-structured assessment models

Treatment of natural mortality is a major consideration in assessment models and state-space approaches allow estimation of temporal variation in this mortality rate as well as effects of specific covariates. However, there has been no investigation of the reliability of inferences made from state-space assessment models when there is process error or covariate effects on natural mortality. We conducted a large-scale simulation study with operating models simulating data assuming alternative levels of observation error, types and magnitude of process error, and magnitude of covariate effects on natural mortality. We fit estimating models to the simulated data with alternative assumptions regarding the inclusion of covariate effects, estimation of the median natural mortality rate, and type of process error. We found estimating covariate effects on natural mortality required ideal scenarios with lower observation uncertainty, contrast in fishing pressure, and higher covariate variability, but the source of process error could be mis-specified. Estimating annual natural mortality rates as random effects was also challenging, but spawning stock biomass and fishing mortality was reliable in a wide range of scenarios.

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Publication Details

Journal
Canadian Journal of Fisheries and Aquatic Sciences
Published
2026-06-08
DOI
https://doi.org/10.1139/cjfas-2025-0206
Primary Topic
Marine and fisheries research
Type
article
Field-Weighted Citation Impact
0.00
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article

Factors affecting inferences on natural mortality and associated environmental effects in state-space age-structured assessment models

Gavin Fay, Christopher M. Legault, Alexander C. Hansell, Elizabeth N. Brooks et al.
Canadian Journal of Fisheries and Aquatic Sciences
Marine and fisheries research
article

Factors affecting inferences on natural mortality and associated environmental effects in state-space age-structured assessment models

Gavin Fay, Christopher M. Legault, Alexander C. Hansell, Elizabeth N. Brooks, Brandon Muffley, Gregory Britten, John Wiedenmann, Timothy J. Miller
article en

Abstract

Treatment of natural mortality is a major consideration in assessment models and state-space approaches allow estimation of temporal variation in this mortality rate as well as effects of specific covariates. However, there has been no investigation of the reliability of inferences made from state-space assessment models when there is process error or covariate effects on natural mortality. We conducted a large-scale simulation study with operating models simulating data assuming alternative levels of observation error, types and magnitude of process error, and magnitude of covariate effects on natural mortality. We fit estimating models to the simulated data with alternative assumptions regarding the inclusion of covariate effects, estimation of the median natural mortality rate, and type of process error. We found estimating covariate effects on natural mortality required ideal scenarios with lower observation uncertainty, contrast in fishing pressure, and higher covariate variability, but the source of process error could be mis-specified. Estimating annual natural mortality rates as random effects was also challenging, but spawning stock biomass and fishing mortality was reliable in a wide range of scenarios.

Canadian Journal of Fisheries and Aquatic Sciences
University of Massachusetts Dartmouth (US), Rutgers, The State University of New Jersey (US), Bedford Institute of Oceanography (CA), Mid Atlantic Fishery Management Council (US), NOAA National Marine Fisheries Service Northeast Fisheries Science Center (US), Woods Hole Oceanographic Institution (US)
Openalex Percentile: Top 7%
Marine and fisheries research
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