scholarly journals Caveats with estimating natural mortality rates in stock assessment models using age aggregated catch data and abundance indices

2021 ◽  
Vol 243 ◽  
pp. 106071
Author(s):  
M. Aldrin ◽  
F.L. Aanes ◽  
I.F. Tvete ◽  
S. Aanes ◽  
S. Subbey
Keyword(s):  
Stock Assessment ◽  
Mortality Rates ◽  
Natural Mortality ◽  
Catch Data ◽  
Abundance Indices

scholarly journals An integrated tagging model to estimate mortality rates of Albemarle Sound – Roanoke River striped bass

2017 ◽  
Vol 74 (7) ◽  
pp. 1061-1076 ◽  
Author(s):  
Julianne E. Harris ◽  
Joseph E. Hightower
Keyword(s):  
Striped Bass ◽  
Stock Assessment ◽  
Mortality Rates ◽  
Natural Mortality ◽  
Fishing Mortality ◽  
Albemarle Sound ◽  
High Reward ◽  
Accuracy And Precision ◽  
Summer Mortality ◽  
Roanoke River

We developed an integrated tagging model to estimate mortality rates and run sizes of Albemarle Sound – Roanoke River striped bass (Morone saxatilis), including (i) a multistate component for telemetered fish with a high reward external tag; (ii) tag return components for fish with a low reward external or PIT tag; and (iii) catch-at-age data. Total annual instantaneous mortality was 1.08 for resident (458–899 mm total length, TL) and 0.45 for anadromous (≥900 mm TL) individuals. Annual instantaneous natural mortality was higher for resident (0.70) than for anadromous (0.21) fish due to high summer mortality in Albemarle Sound. Natural mortality for residents was substantially higher than currently assumed for stock assessment. Monthly fishing mortality from multiple sectors (including catch-and-release) corresponded to seasonal periods of legal harvest. Run size estimates were 499 000–715 000. Results and simulation suggest increasing sample size for the multistate component increases accuracy and precision of annual estimates and low reward tags are valuable for estimating monthly fishing mortality rates among sectors. Our results suggest that integrated tagging models can produce seasonal and annual mortality estimates needed for stock assessment and management.

Detecting mortality variation to enhance forage fish population assessments

2018 ◽  
Vol 76 (1) ◽  
pp. 124-135 ◽  
Author(s):  
Nis S Jacobsen ◽  
James T Thorson ◽  
Timothy E Essington
Keyword(s):  
Test Performance ◽  
Size Structure ◽  
Stock Assessment ◽  
Reference Points ◽  
Forage Fish ◽  
Natural Mortality ◽  
Time Varying ◽  
Fishing Mortality ◽  
Catch Data ◽  
Over Time

Abstract Contemporary stock assessment models used by fisheries management often assume that natural mortality rates are constant over time for exploited fish stocks. This assumption results in biased estimates of fishing mortality and reference points when mortality changes over time. However, it is difficult to distinguish changes in natural mortality from changes in fishing mortality, selectivity, and recruitment. Because changes in size structure can be indicate changes in mortality, one potential solution is to use population size-structure and fisheries catch data to simultaneously estimate time-varying natural and fishing mortality. Here we test that hypothesis, using a simulation experiment to test performance for four alternative estimation models that estimate natural and fishing mortality from size structure and catch data. We show that it is possible to estimate time-varying natural mortality in a size-based model, even when fishing mortality, recruitment, and selectivity are changing over time. Finally, we apply the model to North Sea sprat, and show that estimates of recruitment and natural mortality are similar to estimates from an alternative multispecies population model fitted to additional data sources. We recommend exploring potential trends in natural mortality in forage fish assessments using tools such as the one presented here.

Integrating catch-at-age and multiyear tagging data: a combined Brownie and Petersen estimation approach in a fishery context

2006 ◽  
Vol 63 (3) ◽  
pp. 534-548 ◽  
Author(s):  
Tom Polacheck ◽  
J Paige Eveson ◽  
Geoff M Laslett ◽  
Kenneth H Pollock ◽  
William S Hearn
Keyword(s):  
Mortality Rate ◽  
Population Size ◽  
Stock Assessment ◽  
Natural Mortality ◽  
Fishing Mortality ◽  
Catch Data ◽  
Coefficients Of Variation ◽  
Southern Bluefin Tuna ◽  
Catch Rates ◽  
Comprehensive Framework

A comprehensive framework for modelling data from multiyear tagging experiments in a fishery context is presented that incorporates catch data into the traditional Brownie tag–recapture model. Incorporation of catch data not only allows for improved estimation of natural and fishing mortality rates, but also for direct estimation of population size at the time of tagging. These are the primary quantities required to be estimated in stock assessments — having an approach for directly estimating them that does not require catch rates provides a potentially powerful alternative for augmenting traditional stock assessment methods. Simulations are used to demonstrate the value of directly incorporating catch data in the model. Results from the range of scenarios considered suggest that in addition to providing a precise estimate of population size (coefficients of variation ranging from ~15% to 30%), including catch data can decrease biases in the mortality rate estimates (natural mortality especially) and improve precision of fishing mortality rate estimates (by as much as 60% at age 1). The model is applied to southern bluefin tuna (Thunnus maccoyii) tag–recapture and catch data collected in the 1990s to provide estimates of natural mortality, fishing mortality, and abundance for five cohorts of fish.

scholarly journals Growth, maturation, and longevity of maturation cohorts of Norwegian spring-spawning herring

2004 ◽  
Vol 61 (2) ◽  
pp. 165-175 ◽  
Author(s):  
Raymond J.H. Beverton ◽  
Arvid Hylen ◽  
Ole-Johan Østvedt ◽  
John Alvsvaag ◽  
Terence C. Iles
Keyword(s):  
Mortality Rate ◽  
Small Proportion ◽  
Stock Assessment ◽  
Adult Life ◽  
Total Mortality ◽  
Mortality Rates ◽  
Natural Mortality ◽  
Marine Research ◽  
First Time ◽  
Age At Maturation

Abstract In 1907, the Bergen Institute of Marine Research started regular sampling of scales and lengths from landings of mature Norwegian spring-spawning herring. The actual age of each fish when caught was recorded, and from the early 1920s also the age at which it spawned for the first time. The present analyses concern biological samples secured during the fishing seasons 1940–1964. Herring in this stock do not all reach maturity at the same age. A small proportion of any one year class matures at 3 years. The majority matures from the age of 4–7 years, and a small proportion of some year classes at 8 and even 9 years of age. Subsequent age composition and growth of each maturation cohort were followed throughout mature life after spawning for the first time. The maximum age was found to increase with age at maturation, rising to an asymptote of about 22 years. The von Bertalanffy parameter L∞ shows an increasing trend with age at maturation, while K decreases. There is no strict length threshold at maturation and the curve joining the length at which each maturation cohort reaches maturity is less steep than the growth curve itself over the range of maturation ages. The data suggest that fish in this stock spawn, on average, eight times during a period of their life history in which the mortality rate is independent of age. After these eight spawnings, at an age referred to in this paper as the hinge age, the mortality rate increases sharply. Thus, the adult life is divided into two phases, called here pre-senescent and senescent. The total mortality rates in the pre-senescent phase are relatively stable for all maturation cohorts 3–9, but there is some evidence of a trend towards higher mortality rates during the senescent phase for the youngest maturing fish. This trend is caused mainly by a reduced natural mortality in the fish that mature when older. These findings have interesting demographic implications. Additional mortality due to fishing will change the relative contribution of young and old maturation cohorts in the senescent phase, thus making it appear that natural mortality is dependent on the intensity of fishing. Consequently, for stock assessment, analysis on a cohort basis seems advisable.

scholarly journals A state-space stock assessment model for northern cod, including under-reported catches and variable natural mortality rates

2016 ◽  
Vol 73 (2) ◽  
pp. 296-308 ◽  
Author(s):  
Noel G. Cadigan
Keyword(s):  
State Space ◽  
Gadus Morhua ◽  
Stock Assessment ◽  
Mortality Rates ◽  
Assessment Model ◽  
Data Sources ◽  
Natural Mortality ◽  
Similar Data ◽  
Subjective Data ◽  
Northern Cod

A state-space assessment model for the northern cod (Gadus morhua) stock off southern Labrador and eastern Newfoundland is developed here. The model utilizes information from offshore trawl surveys, inshore acoustic surveys, fishery catch age compositions, partial fishery landings, and tagging. This is done using an approach that avoids the use of subjective data-weighting. Estimates of fishing mortality rates (F) are usually conditional on assumptions about natural mortality rates (M) in stock assessment models. However, by integrating much of the information on northern cod, it is possible to estimate F and M separately. It is also possible to estimate a change in the offshore survey catchability by including inshore acoustic biomass estimates. The proposed model also accounts for biased total catch statistics, which is a common problem in stock assessments. The main goal of the model is to provide realistic projections of the impacts of various levels of future fishery catches on the recovery of this stock. The projections incorporate uncertainty about M and catch. This is vital information for successful future fisheries. The model has been developed for the specific data sources available for northern cod, but it could be adapted to other stocks with similar data sources.

Natural mortality rates in tropical tunas: size really does matter

2000 ◽  
Vol 57 (5) ◽  
pp. 1002-1010 ◽  
Author(s):  
John Hampton
Keyword(s):  
Stock Assessment ◽  
Mortality Rates ◽  
Yellowfin Tuna ◽  
Natural Mortality ◽  
Katsuwonus Pelamis ◽  
Size Classes ◽  
Age Related ◽  
Thunnus Obesus ◽  
Order Of Magnitude ◽  
Tropical Tuna

Important size-related variability in natural mortality rates has been revealed in populations of skipjack tuna (Katsuwonus pelamis), yellowfin tuna (Thunnus albacares), and bigeye tuna (Thunnus obesus) in the western tropical Pacific Ocean using a new, size-structured tagging model. The tagging data were classified into release groups by size at release, and a growth model was used to predict size at each time at liberty interval. Natural and fishing mortality rates were categorized by broad size-classes and estimated by maximum likelihood. The method incorporates a correction for incomplete mixing of new releases. For each population, the natural mortality rate declined by about an order of magnitude over the initial size-classes. For skipjack and yellowfin tuna, there was also evidence of elevated natural mortality for some of the larger size-classes. Size- or age-related variability in natural mortality is likely to have important implications for tropical tuna stock assessment in the western Pacific.

Natural mortality diagnostics for state-space stock assessment models

2021 ◽  
Vol 243 ◽  
pp. 106062
Author(s):  
Andrea M.J. Perreault ◽  
Noel G. Cadigan
Keyword(s):  
State Space ◽  
Stock Assessment ◽  
Natural Mortality

scholarly journals Integrating spatial synchrony/asynchrony of population distribution into stock assessment models: a spatial hierarchical Bayesian statistical catch-at-age approach

2016 ◽  
Vol 73 (7) ◽  
pp. 1725-1738 ◽  
Author(s):  
Yan Jiao ◽  
Rob O'Reilly ◽  
Eric Smith ◽  
Don Orth ◽  
Keyword(s):  
Relative Abundance ◽  
Bayesian Model ◽  
Population Distribution ◽  
Stock Assessment ◽  
Spatial Models ◽  
Reference Points ◽  
Hierarchical Bayesian ◽  
Hierarchical Bayesian Model ◽  
Spatial Synchrony ◽  
Abundance Indices

Abstract In many marine fisheries assessments, population abundance indices from surveys collected by different states and agencies do not always agree with each other. This phenomenon is often due to the spatial synchrony/asynchrony. Those indices that are asynchronous may result in discrepancies in the assessment of temporal trends. In addition, commonly employed stock assessment models, such as the statistical catch-at-age (SCA) models, do not account for spatial synchrony/asynchrony associated with spatial autocorrelation, dispersal, and environmental noise. This limits the value of statistical inference on key parameters associated with population dynamics and management reference points. To address this problem, a set of geospatial analyses of relative abundance indices is proposed to model the indices from different surveys using spatial hierarchical Bayesian models. This approach allows better integration of different surveys with spatial synchrony and asynchrony. We used Atlantic weakfish (Cynoscion regalis) as an example for which there are state-wide surveys and expansive coastal surveys. We further compared the performance of the proposed spatially structured hierarchical Bayesian SCA models with a commonly used Bayesian SCA model that assumes relative abundance indices are spatially independent. Three spatial models developed to mimic different potential spatial patterns were compared. The random effect spatially structured hierarchical Bayesian model was found to be better than the commonly used SCA model and the other two spatial models. A simulation study was conducted to evaluate the uncertainty resulting from model selection and the robustness of the recommended model. The spatially structured hierarchical Bayesian model was shown to be able to integrate different survey indices with/without spatial synchrony. It is suggested as a useful tool when there are surveys with different spatial characteristics that need to be combined in a fisheries stock assessment.

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