Estimating Mortality from Mean Length Data in Nonequilibrium Situations, with Application to the Assessment of Goosefish

Gedamke, Todd; Hoenig, John M.

doi:10.1577/t05-153.1

Cited by 58 publications

(93 citation statements)

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“…The base model used in this analysis was derived by Gedamke and Hoenig (2006), and consists of a transitional form of a mean length mortality estimator for application in non-equilibrium conditions. The Beverton and Holt mortality estimator (1956,1957):…”

Section: Mortality Estimationmentioning

confidence: 99%

“…, the so-called length of first capture (smallest size at which animals are fully vulnerable to the fishery and to the sampling gear), L c , and the mean length ( " L) of the animals above L c . Unlike the Holt (1956, 1957) mortality estimator and earlier modifications (such as in Ehrhardt and Ault 1992), the restrictive assumption of equilibrium conditions (i.e., mortality rate has been constant for a long enough time period that the observed mean length reflects the current mortality rate) is not a requirement of the Gedamke and Hoenig (2006) approach.…”

Section: Mortality Estimationmentioning

confidence: 99%

“…The methodology and a practical application are described in detail in Gedamke and Hoenig (2006), and the method will only be described briefly here. The nonequilibrium formulation was derived by including multiple integrals to account for the different mortality histories experienced by fish of different ages.…”

Section: Mortality Estimationmentioning

confidence: 99%

“…Assuming one change in mortality has occurred, for example, one integral represents fish recruited to the population after a change in mortality (i.e., these animals have experienced only the most recent mortality rate), and a second integral represents animals recruited before the change in mortality (i.e., these fish have experienced both the old and new mortality rates). After integration and simplification (see Appendix 1 in Gedamke and Hoenig 2006), an equation results in which the mean length in a population can be calculated d years after a single permanent change in total mortality from Z 1 to Z 2 year -1 :…”

Section: Mortality Estimationmentioning

confidence: 99%

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Fishing through time: population dynamics of plaice (Pleuronectes platessa) in the Kattegat–Skagerrak over a century

et al. 2009

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Over the past century, advances in technology and historical events such as climate change have resulted in significant changes in the exploitation pattern, population sizes and the potential yield of fish stocks. These variations provide contrast in the data that improves our knowledge on population dynamics and our ability to develop management strategies for long-term sustainable exploitation. In this study, we use a standardized scientific trawl survey to obtain a historical time series of relative abundance, recruitment and size structure for plaice in the Kattegat-Skagerrak. Our work extends the available time series by more than 80 years so that the evaluation of trends is more informative than is possible from the current assessment. We show that the current adult biomass is approximately 40% of the maximum observed at the beginning of the century and during the 1960s. The average maximum individual length has been reduced by 10 cm over the studied time period. An analysis of trends in mean length indicates that fishing mortality was variable during the first half of the century and has increased steadily over the past 20 years. Recruitment has been the highest on record during recent years, suggesting that the alleged link between coastal environmental degradation and juvenile survival is of low importance. The overall findings of our work will provide managers with a historical perspective on the population dynamics of the stock, which will support the long-term management of plaice in the Kattegat-Skagerrak.

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Section: Mortality Estimationmentioning

confidence: 99%

Section: Mortality Estimationmentioning

confidence: 99%

Section: Mortality Estimationmentioning

confidence: 99%

Section: Mortality Estimationmentioning

confidence: 99%

See 2 more Smart Citations

Fishing through time: population dynamics of plaice (Pleuronectes platessa) in the Kattegat–Skagerrak over a century

et al. 2009

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“…Although data from baited jigs (the fishing technique used by the prehistoric Aleut) were not available, modern longline-obtained cod are likely to be most comparable with fish taken by prehistoric jigging practices. The mean length recorded for the 2005 longline survey, which occurs as frequencies in size bins, was calculated using procedures in Gedamke and Hoenig (2006). Figure 9 displays a time series of average Pacific cod lengths spanning the preindustrial (prehistoric) to recent period.…”

Section: Faunal Studiesmentioning

confidence: 99%

An Introduction to the Biocomplexity of Sanak Island, Western Gulf of Alaska

et al. 2009

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The Sanak Biocomplexity Project is a transdisciplinary research effort focused on a small island archipelago 50 km south of the Alaska Peninsula in the western Gulf of Alaska. This team of archaeologists, terrestrial ecologists, social anthropologists, intertidal ecologists, geologists, oceanographers, paleoecologists, and modelers is seeking to understanding the role of the ancient, historic, and modern Aleut in the structure and functioning of local and regional ecosystems. Using techniques ranging from systematic surveys to stable isotope chemistry, long-term shifts in social dynamics and ecosystem structure are present in the context of changing climatic regimes and human impacts. This paper presents a summary of a range of our preliminary findings.

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Comparative Performance of Three Length‐Based Mortality Estimators

et al. 2018

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Length-based methods provide alternatives for estimating the instantaneous total mortality rate (Z) in exploited marine populations when data are not available for age-based methods. We compared the performance of three equilibrium length-based methods: the length-converted catch curve (LCCC), the Beverton-Holt equation (BHE), and the length-based spawning potential ratio (LB-SPR) method. The LCCC and BHE are two historically common procedures that use length as a proxy for age. From a truncated length-frequency distribution of fully selected animals, the LCCC estimates Z with a regression of the logarithm of catch at length by the midpoint of the length-bins, while the BHE estimates Z as a function of the mean length. The LB-SPR method is a likelihood-based population dynamics model, which-unlike the LCCC and BHE-does not require data truncation. Using Monte Carlo simulations across a range of scenarios with varying mortality and life history characteristics, our study showed that neither the LCCC nor the BHE was uniformly superior in terms of bias or root mean square error across simulations, but these estimators performed better than LB-SPR, which had the largest bias in most cases. Generally, if the ratio of natural mortality (M) to the von Bertalanffy growth rate parameter (K) is low, then the BHE is most preferred, although there is likely to be high bias and low precision. If M/K is high, then the LCCC and BHE performed better and similarly to each other. Differences in performance among commonly used truncation methods for the LCCC and BHE were small. The LB-SPR method did not perform as well as the classical methods but may still be of interest because it provides estimates of a logistic selectivity curve. The M/K ratio provided the most contrast in the performance of the three methods, suggesting that it should be considered for predicting the likely performance of length-based mortality estimators.

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Estimating Mortality from Mean Length Data in Nonequilibrium Situations, with Application to the Assessment of Goosefish

Cited by 58 publications

References 1 publication

Fishing through time: population dynamics of plaice (Pleuronectes platessa) in the Kattegat–Skagerrak over a century

Fishing through time: population dynamics of plaice (Pleuronectes platessa) in the Kattegat–Skagerrak over a century

An Introduction to the Biocomplexity of Sanak Island, Western Gulf of Alaska

Comparative Performance of Three Length‐Based Mortality Estimators

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