A Note on Determining Parameter Redundancy in Age-Dependent Tag Return Models for Estimating Fishing Mortality, Natural Mortality and Selectivity

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).

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Influence of errors in natural mortality estimates in cohort analysis

Canadian Journal of Fisheries and Aquatic Sciences ◽

10.1139/f97-067 ◽

1997 ◽

Vol 54 (7) ◽

pp. 1608-1612 ◽

Cited By ~ 15

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.

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

Canadian Journal of Fisheries and Aquatic Sciences ◽

10.1139/cjfas-2016-0141 ◽

2017 ◽

Vol 74 (7) ◽

pp. 1061-1076 ◽

Cited By ~ 6

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.

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

Indonesian Fisheries Research Journal ◽

10.15578/ifrj.24.2.2018.125-131 ◽

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.

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Estimation of the parameters of fish stock dynamics from catch-at-age data and indices of abundance: can natural and fishing mortality be separated?

Canadian Journal of Fisheries and Aquatic Sciences ◽

10.1139/f07-074 ◽

2007 ◽

Vol 64 (8) ◽

pp. 1130-1142 ◽

Cited By ~ 26

Author(s):

Sondre Aanes ◽

Steinar Engen ◽

Bernt-Erik Sæther ◽

Ronny Aanes

Keyword(s):

Gadus Morhua ◽

State Space Model ◽

Population Projections ◽

Quality Data ◽

Fish Stock ◽

Natural Mortality ◽

Fishing Mortality ◽

Absolute Size ◽

Data Set ◽

Long Time

Models for fluctuations in size of fish stocks must include parameters that describe expected dynamics, as well as stochastic influences. In addition, reliable population projections also require assessments about the uncertainties in estimates of vital parameters. Here we develop an age-structured model of population dynamics based on catch-at-age data and indices of abundance in which the natural and fishing mortality are separated in a Bayesian state–space model. Markov chain Monte Carlo methods are used to fit the model to the data. The model is fitted to a data set of 19 years for Northeast Arctic cod (Gadus morhua). By simulations of the fitted model we show that the model captures the dynamical pattern of natural mortality adequately, whereas the absolute size of natural mortality is difficult to estimate. Access to long time series of high-quality data are necessary for obtaining precise estimates of all the parameters in the model, but some parameters cannot be estimated without including some prior information. Nevertheless, our model demonstrates that temporal variability in natural mortality strongly affects perceived variability in stock sizes. Thus, using estimation procedures that neglect temporal fluctuations in natural mortality may therefore give biased estimates of fluctuations in fish stock sizes.

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Detecting mortality variation to enhance forage fish population assessments

ICES Journal of Marine Science ◽

10.1093/icesjms/fsy160 ◽

2018 ◽

Vol 76 (1) ◽

pp. 124-135 ◽

Cited By ~ 1

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.

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

ICES Journal of Marine Science ◽

10.1093/icesjms/fsu055 ◽

2014 ◽

Vol 72 (1) ◽

pp. 137-150 ◽

Cited By ~ 43

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.

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

Canadian Journal of Fisheries and Aquatic Sciences ◽

10.1139/f05-232 ◽

2006 ◽

Vol 63 (3) ◽

pp. 534-548 ◽

Cited By ~ 34

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 tagrecapture 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) tagrecapture and catch data collected in the 1990s to provide estimates of natural mortality, fishing mortality, and abundance for five cohorts of fish.

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Differences in predicted catch composition between two widely used catch equation formulations

Canadian Journal of Fisheries and Aquatic Sciences ◽

10.1139/f08-196 ◽

2009 ◽

Vol 66 (1) ◽

pp. 126-132 ◽

Cited By ~ 11

Author(s):

Trevor A. Branch

Keyword(s):

Age Groups ◽

Correct Choice ◽

Fishing Gear ◽

Natural Mortality ◽

Fishing Mortality ◽

Gear Selectivity ◽

Different Types ◽

Catch Composition ◽

Continuous Formulation ◽

Discrete Formulation

Fishing gear selectivity varies among different types of fish (e.g., species, age, sex, or length groups), but their relative catch composition also depends on the fishing process. The continuous (Baranov) formulation assumes that fishing mortality and natural mortality occur together during the fishing season and that there are multiple encounters between fish and fishing gear. For this formulation, predicted catch composition depends on fishing mortality, and at high fishing mortality levels the entire population can be caught provided the selectivity is nonzero for all age groups. In contrast, the discrete formulation assumes that fishing mortality occurs separately from natural mortality and that fish encounter at most only one set of fishing gear. The discrete formulation is easier to compute, but the predicted catch composition is independent of fishing mortality, and some of the population remains unexploitable. The correct choice of equations depends on the particular fishery and fishing mortality levels; at low fishing mortality levels the predictions differ little, but at high fishing mortality levels where multiple gear encounters could occur, the continuous formulation is preferable.

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