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.

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.

In what direction should the fishing mortality target change when natural mortality increases within an assessment?

2016 ◽  
Vol 73 (3) ◽  
pp. 349-357 ◽  
Author(s):  
Christopher M. Legault ◽  
Michael C. Palmer
Keyword(s):  
Mortality Rate ◽  
Empirical Evidence ◽  
Gadus Morhua ◽  
Atlantic Cod ◽  
Stock Assessment ◽  
Total Mortality ◽  
Natural Mortality ◽  
Fishing Mortality ◽  
Limanda Ferruginea ◽  
Trade Offs

Traditionally, the natural mortality rate (M) in a stock assessment is assumed to be constant. When M increases within an assessment, the question arises how to change the fishing mortality rate target (FTarget). Per recruit considerations lead to an increase in FTarget, while limiting total mortality leads to a decrease in FTarget. Application of either approach can result in nonsensical results. Short-term gains in yield associated with high FTarget values should be considered in light of potential losses in future yield if the high total mortality rate leads to a decrease in recruitment. Examples using yellowtail flounder (Limanda ferruginea) and Atlantic cod (Gadus morhua) are used to demonstrate that FTarget can change when M increases within an assessment and to illustrate the consequences of different FTarget values. When a change in M within an assessment is contemplated, first consider the amount and strength of empirical evidence to support the change. When the empirical evidence is not strong, we recommend using a constant M. If strong empirical evidence exists, we recommend estimating FTarget for a range of stock–recruitment relationships and evaluating the trade-offs between risk of overfishing and forgone yield.

A Generalization of the Murphy Catch Equation

1970 ◽  
Vol 27 (4) ◽  
pp. 821-825 ◽  
Author(s):  
Patrick K. Tomlinson
Keyword(s):  
Mortality Rate ◽  
Population Size ◽  
Generalized Equation ◽  
Time Interval ◽  
Natural Mortality ◽  
Fishing Mortality ◽  
Time Intervals

Given catches, by time intervals, from a known cohort of fish with known natural mortality rate and known fishing mortality rate for either the first or last time interval, the population size at the beginning of each interval and the fishing mortality rate during each interval may be estimated using a generalized Murphy catch equation. The generalized equation is constructed from the ratio of catches in successive intervals and depends on the assumption of simple exponential mortality within the intervals. The intervals may vary in length and have zero catches. The estimates may be badly biased depending on the nature of the catch sequence and the independent estimates of natural mortality and fishing mortality used to start the procedure.

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

Movement, Growth and natural mortality rate of the Red Spot King Prawn, Penaeus longistylus Kubo, from the Great Barrier Reef Lagoon

1990 ◽  
Vol 41 (3) ◽  
pp. 399 ◽  
Author(s):  
MCL Dredge
Keyword(s):  
Growth Rate ◽  
Mortality Rate ◽  
Great Barrier Reef ◽  
Annual Variation ◽  
Growth Parameters ◽  
Natural Mortality ◽  
Barrier Reef ◽  
Fishing Mortality ◽  
Nursery Areas ◽  
Reef Lagoon

Movement, growth and natural mortality rate of the red spot king prawn, Penaeus longistylus, occurring in waters of the Great Barrier Reef off Townsville, Queensland, were investigated in a series of tagging experiments. Adult P. longistylus did not migrate after leaving nursery areas. Their growth rate was slower than that of the conspecific species P. plebejus, and significant inter-annual variation in growth parameters was observed. The natural mortality rate, assessed by sequential tagging experiments that eliminated the possibility of confounding with the rate of fishing mortality, was estimated to be 0.072 (week-1).

Influence of errors in natural mortality estimates in cohort analysis

1997 ◽  
Vol 54 (7) ◽  
pp. 1608-1612 ◽  
Author(s):  
G Mertz ◽  
R A Myers
Keyword(s):  
Mortality Rate ◽  
Similar Pattern ◽  
Cohort Analysis ◽  
Transient Behavior ◽  
Natural Mortality ◽  
Exact Formulation ◽  
Fishing Mortality ◽  
Bias Factor ◽  
Special Case ◽  
Mortality Estimates

The accuracy of the estimation of cohort strength from catch data may be greatly degraded if a poor estimate of the natural mortality rate is entered into the calculation. A straightforward, exact formulation for the error in cohort reconstruction due to a misspecified natural mortality rate is presented. The special case of constant fishing mortality is particularly transparent, allowing the error to be segmented into easily interpreted terms. A change in the fishing mortality may result in a distinct hump in the transient behavior of the bias factor, rather than a simple monotonic adjustment. This implies a similar pattern in estimated cohort strength.

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.

scholarly journals POPULATION DYNAMICS OF MALAYAN LEAF FISH (Pristolepisgrooti Blkr.) IN RANAU LAKE, SOUTH SUMATRA

2018 ◽  
Vol 24 (2) ◽  
pp. 125
Author(s):  
Sevi Sawetri ◽  
Subagdja Subagdja ◽  
Dina Muthmainnah
Keyword(s):  
Mortality Rate ◽  
Growth Parameters ◽  
Total Mortality ◽  
Natural Mortality ◽  
Fishing Mortality ◽  
Frequency Data ◽  
Length Frequency ◽  
Lake Ecosystems ◽  
Exploitation Rate ◽  
Length Frequency Data

The Malayan leaf fish or locally named as kepor (Pristolepis grooti) is one of important biotic components in Ranau Lake ecosystems. This study aimed to estimate population dynamic and exploitation rate of kepor in Ranau Lake, South Sumatera. The population parameters are estimated based on length frequency data which were collected in March to October 2013. Growth parameters and fishing mortality rates were calculated using FiSAT software package. The results showed that kepor’s growth was negative allometric, which tended to gain length faster than weight. Kepor population was dominated (42%) by individual length of 10.0 to 11.0 cm. Predicted length infinity (L) was 17.28 cm with high value of growth rates (K) of 1.4 year-1. The natural mortality rate (M) is 2.57 year-1, the fishing mortality rate (F) is 5.36 year-1 and total mortality rate (Z) is 7.93 year-1. The exploitation rate of Malayan leaf fish in Ranau Lake (E = 0.68 year-1) has passed the optimum score.  

scholarly journals Time-varying natural mortality in fisheries stock assessment models: identifying a default approach

2014 ◽  
Vol 72 (1) ◽  
pp. 137-150 ◽  
Author(s):  
Kelli F. Johnson ◽  
Cole C. Monnahan ◽  
Carey R. McGilliard ◽  
Katyana A. Vert-pre ◽  
Sean C. Anderson ◽  
...  
Keyword(s):  
Stock Assessment ◽  
Assessment Method ◽  
Reference Points ◽  
Natural Mortality ◽  
Time Varying ◽  
Fishing Mortality ◽  
Total Allowable Catch ◽  
Robust Approach ◽  
Structured Population Models ◽  
Trade Offs

Abstract A typical assumption used in most fishery stock assessments is that natural mortality (M) is constant across time and age. However, M is rarely constant in reality as a result of the combined impacts of exploitation history, predation, environmental factors, and physiological trade-offs. Misspecification or poor estimation of M can lead to bias in quantities estimated using stock assessment methods, potentially resulting in biased estimates of fishery reference points and catch limits, with the magnitude of bias being influenced by life history and trends in fishing mortality. Monte Carlo simulations were used to evaluate the ability of statistical age-structured population models to estimate spawning-stock biomass, fishing mortality, and total allowable catch when the true M was age-invariant, but time-varying. Configurations of the stock assessment method, implemented in Stock Synthesis, included a single age- and time-invariant M parameter, specified at one of the three levels (high, medium, and low) or an estimated M. The min–max (i.e. most robust) approach to specifying M when it is thought to vary across time was to estimate M. The least robust approach for most scenarios examined was to fix M at a high value, suggesting that the consequences of misspecifying M are asymmetric.

scholarly journals SPAM (Sex-Structured Pandalus Assessment Model): a stock assessment model for Pandalus stocks

2012 ◽  
Vol 69 (4) ◽  
pp. 770-783 ◽  
Author(s):  
Hilaire Drouineau ◽  
Louise Savard ◽  
Mathieu Desgagnés ◽  
Daniel Duplisea
Keyword(s):  
Stock Assessment ◽  
Sex Change ◽  
Assessment Model ◽  
Natural Mortality ◽  
The Novel ◽  
Fishing Mortality ◽  
Novel Structure ◽  
Shrimp Fisheries ◽  
Analytical Tools ◽  
Mortality Estimates

Despite the economic importance of Pandalus shrimp fisheries, few analytical tools have been developed to assess their stocks, and traditional stock assessment models are not appropriate because of biological specificities of Pandalus species. In this context, we propose SPAM (Sex-Structured Pandalus Assessment Model), a model dedicated to protandric hermaphrodite pandalids stock assessment. Pandalids are difficult to assess because the cues affecting sex change, size at recruitment, and mortality variability are not well understood or characterized. The novel structure of the model makes it possible to adequately describe variability in natural mortality by stage and in time, as well as variability in size at sex change and recruitment. The model provides traditional stock assessment outputs, such as fishing mortality estimates and numbers of individuals, and provides in addition yearly natural mortality estimates. The model is applied to the exploited shrimp stock of Pandalus borealis in Sept-Îles (Québec, Canada) as an illustrative example of the utility of the approach.

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