Predicting density-dependent somatic growth in Norwegian spring-spawning herring

Stenevik, Erling Kåre; Hølleland, Sondre; Enberg, Katja; Høines, Åge S.; Salthaug, Are; Slotte, Aril; Vatnehol, Sindre; Aanes, Sondre

doi:10.1093/icesjms/fsac057

Cited by 6 publications

(3 citation statements)

References 44 publications

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“…This model provides dynamic description about the strength of density dependence with respect to environmental variations. In addition, our model embodies the density dependence of a combination of biological traits, including growth, fecundity and post‐recruitment mortality, which have been demonstrated separately by previous studies (Achord et al, 2003; Crozier et al, 2010; Raid et al, 2010; Stenevik et al, 2022; Wakiya et al, 2022). The density‐dependent effects presented by our mechanistic model were comparable to relevant field observations.…”

Section: Discussionmentioning

confidence: 95%

Coupling dynamic energy budget and population dynamic models to inform stock enhancement in fisheries management

et al. 2023

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Extensive applications of fishery stock enhancement worldwide bring up broad concerns about its negative effects, creating a pivotal need for science‐based assessment and planning of enhancement strategies. However, the lack of mechanistic understanding of enhanced population dynamics, particularly the density‐dependent processes, leads to compromise in model development and limits the capacity in predicting enhancement effects. Here, we developed an individual‐based model based on dynamic energy budget theory and full life‐history processes, to understand the mechanism of density dependence in population dynamics that emerge from individual‐level processes. We demonstrated the utility of the model framework by applying it to an extensively enhanced species, Chinese prawn (Fenneropenaeus chinensis, Penaeidae). The model could yield projections reflecting the observed trajectory of population biomass and yields. The model also delineated the key effects of density dependence on the vital rates of growth, fecundity and starvation mortality. Regarding the manifold effects of stock enhancement, we demonstrated a dampened shape in population biomass and yields with increasing magnitude of enhancement, and trade‐offs between the ecological and economic objectives, that is, pursuing high benefit might compromise the wild population without proper management. Furthermore, we illustrated the possibility of combining stock enhancement and harvest regulation in promoting population recovery while maintaining fisheries yields. We highlight the potential of the proposed model for understanding density dependence in enhancement programme, and for designing integrated management strategies. The approach developed herein may serve as a general approach to assess the population dynamics in stock enhancement and inform enhancement management.

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Section: Discussionmentioning

confidence: 95%

Coupling dynamic energy budget and population dynamic models to inform stock enhancement in fisheries management

et al. 2023

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“…The factors affecting fish somatic growth can arise from both environmental factors [31] and population dynamics through density dependence [32]. In Norwegian spring spawning herring, Stenevik et al [33] found a significant negative correlation between estimated asymptotic length and fish density. Investigating 70 fish populations from the northeast Atlantic, Zimmerman et al [34] found evidence for density dependence in both recruitment and growth.…”

Section: Discussionmentioning

confidence: 99%

Temporal Variation in Von Bertalanffy Growth Curves and Generation Time of Southern Gulf of St. Lawrence Spring and Fall Spawning Atlantic Herring (Clupea harengus)

Burbank

McDermid

Turcotte

et al. 2023

Fishes

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Examining temporal changes in the growth and generation time of fish species can be valuable for understanding population responses to different management measures and environmental conditions. Atlantic herring (Clupea harengus) is an ecologically and commercially important pelagic forage fish species that occupies the southern Gulf of St. Lawrence. Here, we developed von Bertalanffy growth curves and estimated yearly values of generation time for NAFO Division 4TVn Atlantic herring for the years from 1988 to 2021. The results indicate a temporal reduction in the growth and generation time of both spring and fall spawning herring. Over the time series, the generation time of spring and fall spawners reduced by approximately 1 and 2 years, respectively. Furthermore, the average generation time of spring spawners across the time series (6.23 years (95% CI: 5.78–6.85 years)) was approximately 1 year lower than that of fall spawners (7.52 years (6.82–8.34 years)). Overall, the findings of this study can be used to better inform stock assessments and rebuilding plans for 4TVn spring and fall spawning Atlantic herring and highlight the importance of examining temporal trends in growth and generation time for more effective management of fish stocks.

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“…For the long‐term investigation on NSS herring, the full recruitment (at age 2 years) time series covered the period from 1907 to 2017 (Stenevik et al., 2022). These data, however, did not include any estimation of uncertainty, in contrast with those from the ICES assessment outputs (1988–2021) (Table S1).…”

Section: Methodsmentioning

confidence: 99%

Recruitment regime shifts and nonstationarity are widespread phenomena in harvestable stocks experiencing pronounced climate fluctuations

Ma,

Huse,

Ono

et al. 2023

Fish and Fisheries

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Methods to reliably identify jump discontinuities in biological time series and to assess the specific contribution of various covariates are rapidly progressing. Here, we took advantage of these statistical improvements as well as those seen in complementary, down‐scaled climate and biogeochemical models to investigate causes of the substantial interannual variability observed in recruitment strength in hindcast analyses. This systematic meta‐analysis included 23 data‐rich, commercially valuable, warm‐ and cold‐temperate stocks in the North, Norwegian and Barents Seas. Since this study focuses on recruitment strength variability, we have used the term “recruitment regime shift” to distinguish from the concept of ecosystem regime shift. The breakpoint analysis revealed that the former criterion applied to more than half of the time series, mainly with respect to North Sea stocks but also to those in the Norwegian Sea. The exploratory analysis using vcGAM indicated that 1–3 shifts per stock were real, when using five drivers spanning spawning stock biomass to large‐scale climatic processes. Thus, non‐stationary relationships were extensively prevalent, indicating that each stock is uniquely adapted to its locally varying conditions. Outputs from the stationary GAM resembled those from the vcGAM but not after the threshold year. In‐depth case studies showed that the proxy of a given driver for the process which was to be included should be critically considered in a spatiotemporal context. Furthermore, the stock‐specific uncertainty associated with the given recruitment figures as such should also be an in‐built component of the model construct and thereby in the evaluation of the output.

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Predicting density-dependent somatic growth in Norwegian spring-spawning herring

Cited by 6 publications

References 44 publications

Coupling dynamic energy budget and population dynamic models to inform stock enhancement in fisheries management

Coupling dynamic energy budget and population dynamic models to inform stock enhancement in fisheries management

Temporal Variation in Von Bertalanffy Growth Curves and Generation Time of Southern Gulf of St. Lawrence Spring and Fall Spawning Atlantic Herring (Clupea harengus)

Recruitment regime shifts and nonstationarity are widespread phenomena in harvestable stocks experiencing pronounced climate fluctuations

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