Management implications of shifting baselines in fish stock assessments

2021 ◽  
Author(s):  
Rebecca Schijns ◽  
Daniel Pauly
Keyword(s):  
Fish Stock ◽  
Management Implications ◽  
Shifting Baselines ◽  
Stock Assessments

How much evidence is required for acceptance of productivity regime shifts in fish stock assessments: Are we letting managers off the hook?

2015 ◽  
Vol 168 ◽  
pp. 49-55 ◽  
Author(s):  
Neil L. Klaer ◽  
Robert N. O’Boyle ◽  
Jonathan J. Deroba ◽  
Sally E. Wayte ◽  
L. Richard Little ◽  
...  
Keyword(s):  
Regime Shifts ◽  
Fish Stock ◽  
Stock Assessments

Accounting for marine reserves using spatial stock assessments

2015 ◽  
Vol 72 (2) ◽  
pp. 262-280 ◽  
Author(s):  
Carey R. McGilliard ◽  
André E. Punt ◽  
Richard D. Methot ◽  
Ray Hilborn
Keyword(s):  
Spatial Heterogeneity ◽  
Stock Assessment ◽  
Marine Reserves ◽  
Movement Patterns ◽  
Catch Rate ◽  
Fish Stock ◽  
Rate Data ◽  
Stock Assessments ◽  
Age Structured ◽  
Movement Parameters

Some fish stock assessments are conducted in regions that contain no-take marine reserves (NTMRs). NTMRs are expected to lead to spatial heterogeneity in fish biomass by allowing a buildup of biomass inside their borders while fishing pressure occurs outside. Stock assessments do not typically account for spatial heterogeneity caused by NTMRs, which may lead to biased estimates of biomass. Simulation modeling is used to analyze the ability of several stock assessment configurations to estimate current biomass after the implementation of a single, large NTMR. Age-structured spatial operating models with three patterns of ontogenetic movement are used to represent the “true” population dynamics. Results show that assessing populations as a single stock with use of fishery catch-rate data and without accounting for the NTMR results in severe underestimation of biomass for two of the movement patterns. Omitting fishery catch-rate data or allowing time-varying dome-shaped selectivity after NTMR implementation leads to improved estimates of current biomass, but severe bias in estimated trends in biomass over time. Performing separate assessments for fished areas and NTMRs leads to improved estimation performance in the absence of movement among assessment areas, but can severely overestimate biomass otherwise. Performing a spatial assessment with estimation of movement parameters among areas was found to be the best way to assess a species, even when movement patterns were unknown. However, future work should explore the performance of spatial assessments when catchability varies among areas.

Fish stock assessments in Lake Konnevesi

Hydrobiologia ◽  
1982 ◽  
Vol 86 (1-2) ◽  
pp. 219-222 ◽  
Author(s):  
J. Toivonen ◽  
H. Auvinen ◽  
P. Valkeaj�rvi
Keyword(s):  
Fish Stock ◽  
Stock Assessments

scholarly journals Importance of modelling heteroscedasticity of survey index data in fishery stock assessments

2014 ◽  
Vol 72 (1) ◽  
pp. 130-136 ◽  
Author(s):  
Saang-Yoon Hyun ◽  
Mark N. Maunder ◽  
Brian J. Rothschild
Keyword(s):  
Coefficient Of Variation ◽  
Likelihood Function ◽  
Error Model ◽  
Fish Stock ◽  
Additional Parameter ◽  
Traditional Practice ◽  
Multiplicative Error ◽  
Additive Error ◽  
Stochastic Error ◽  
Stock Assessments

Abstract Many fish stock assessments use a survey index and assume a stochastic error in the index on which a likelihood function of associated parameters is built and optimized for the parameter estimation. The purpose of this paper is to evaluate the assumption that the standard deviation for the difference in the log-transformed index is approximately equal to the coefficient of variation of the index, and also to examine the homo- and heteroscedasticity of the errors. The traditional practice is to assume a common variance of the index errors over time for estimation convenience. However, if additional information is available about year-to-year variability in the errors, such as year-to-year coefficient of variation, then we suggest that the heteroscedasticity assumption should be considered. We examined five methods with the assumption of a multiplicative error in the survey index and two methods with that of an additive error in the index: M1, homoscedasticity in the multiplicative error model; M2, heteroscedasticity in the multiplicative error model; M3, M2 with approximate weighting and an additional parameter for scaling variance; M4–M5, pragmatic practices; M6, homoscedasticity in the additive error model; M7, heteroscedasticity in the additive error model. M1–M2 and M6–M7 are strictly based on statistical theories, whereas M3–M5 are not. Heteroscedasticity methods M2, M3, and M7 consistently outperformed the other methods. However, we select M2 as the best method. M3 requires one more parameter than M2. M7 has problems arising from the use of the raw scale as opposed to the logarithm transformation. Furthermore, the fitted survey index in M7 can be negative although its domain is positive.

scholarly journals “The Elephant in the Room”: Exploring Natural Mortality Uncertainty in Statistical Catch at Age Models

2020 ◽  
Vol 7 ◽  
Author(s):  
Alessandro Mannini ◽  
Cecilia Pinto ◽  
Christoph Konrad ◽  
Paraskevas Vasilakopoulos ◽  
Henning Winker
Keyword(s):  
Stock Assessment ◽  
Assessment Process ◽  
Sensitivity Analyses ◽  
Fish Stock ◽  
Natural Mortality ◽  
Fishing Mortality ◽  
Food And Agriculture ◽  
Stock Assessments ◽  
The Mediterranean ◽  
The Impact

The natural mortality rate (M) of a fish stock is typically highly influential on the outcome of age-structured stock assessment models, but at the same time extremely difficult to estimate. In data-limited stock assessments, M usually relies on a range of empirically or theoretically derived M estimates, which can vary vastly. This article aims at evaluating the impact of this variability in M using seven Mediterranean stocks as case studies of statistical catch-at-age assessments for information-limited fisheries. The two main bodies carrying out stock assessments in the Mediterranean and Black Seas are European Union’s Scientific Technical Economic Committee for Fisheries (STECF) and Food and Agriculture Organization’s General Fisheries Commission for the Mediterranean (GFCM). Current advice in terms of fishing mortality levels is based on a single “best” M assumption which is agreed by stock assessment expert working groups, but uncertainty about M is not taken into consideration. Our results demonstrate that not accounting for the uncertainty surrounding M during the assessment process can lead to strong underestimation or overestimation of fishing mortality, potentially biasing the management process. We recommend carrying out relevant sensitivity analyses to improve stock assessment and fisheries management in data-limited areas such as the Mediterranean basin.

scholarly journals Fish stock assessments in the Mediterranean: state of the art

2003 ◽  
Vol 67 (S1) ◽  
pp. 37-49 ◽  
Author(s):  
Jordi Lleonart ◽  
Francesc Maynou
Keyword(s):  
State Of The Art ◽  
Fish Stock ◽  
Stock Assessments ◽  
The Mediterranean

scholarly journals Annual trends in catchability and fish stock assessments

2003 ◽  
Vol 67 (S1) ◽  
pp. 63-73 ◽  
Author(s):  
Marchal Paul ◽  
Ulrich Clara ◽  
Korsbrekke Knut ◽  
Pastoors Martin ◽  
Rackham Brian
Keyword(s):  
Fish Stock ◽  
Stock Assessments ◽  
Annual Trends
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