Near real-time forecasting of recruitment from larval surveys: application to Alaska pollock

Bailey, Kevin M.; Zhang, Tianyang; Chan, Kung‐Sik; Porter, Steven M.; Dougherty, Annette B.

doi:10.3354/meps09614

Cited by 15 publications

(8 citation statements)

References 27 publications

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“…However, year‐class strength of EBS pollock has previously been associated with total energetic reserves acquired by juvenile fish before the first winter, as measured by the product of energy density and body size; thus, body size alone may not be sufficient for high survival (Heintz, Siddon, Farley, & Napp, ). One possible explanation for the lack of association for GOA pollock is a long‐term increase in predation rates by a growing predator population (arrowtooth flounder), which has had a major impact on juvenile survival (Bailey et al, ), and may have masked any patterns of size‐dependent survival. Hence, lack of detected association in our study does not necessarily imply lack of a biologically significant relationship, as it was not feasible in our study to control for effects of environmental changes on survival that potentially dominated over the effects of intra‐population factors.…”

Section: Discussionmentioning

confidence: 99%

“…The time series data have often been collected to get an early indication of yearclass strength to inform fisheries management (e.g. Dragesund, Hylen, Olsen, & Nakken, 2008, Bailey, Zhang, Chan, Porter, & Dougherty, 2012, McClatchie et al, 2014, Megrey, Hollowed, Hare, Maclin, & Stabeno, 1996. Analyses of such time series have shown that reasonable predictions of recruitment can sometimes be obtained as early as the egg stage (Helle et al, 2000;Mukhina, Marshall, & Yaragina, 2003), although processes at later ages also come into play (Bogstad, Yaragina, & Nash, 2016;Stige, Hunsicker, Bailey, Yaragina, & Hunt, 2013).…”

Section: Introductionmentioning

confidence: 99%

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Density‐ and size‐dependent mortality in fish early life stages

et al. 2019

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The importance of survival and growth variations early in life for population dynamics depends on the degrees of compensatory density dependence and size dependence in survival at later life stages. Quantifying density‐ and size‐dependent mortality at different juvenile stages is therefore important to understand and potentially predict the recruitment to the population. We applied a statistical state‐space modelling approach to analyse time series of abundance and mean body size of larval and juvenile fish. The focus was to identify the importance of abundance and body size for growth and survival through successive larval and juvenile age intervals, and to quantify how the dynamics propagate through the early life to influence recruitment. We thus identified both relevant ages and mechanisms (i.e. density dependence and size dependence in survival and growth) linking recruitment variability to early life dynamics. The analysis was conducted on six economically and ecologically important fish populations from cold temperate and sub‐arctic marine ecosystems. Our results underscore the importance of size for survival early in life. The comparative analysis suggests that size‐dependent mortality and density‐dependent growth frequently occur at a transition from pelagic to demersal habitats, which may be linked to competition for suitable habitat. The generality of this hypothesis warrants testing in future research.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Density‐ and size‐dependent mortality in fish early life stages

et al. 2019

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“…A shift in dominance between flounder and pollock is not unprecedented. Flounder replaced pollock as the dominant groundfish species in the Gulf of Alaska ecosystem in the early 1990s, and now controls pollock recruitment there [38]. Previous studies indicate that heavy exploitation coupled with increased predation by flounder exacerbated the decline of Gulf of Alaska pollock [39], [40].…”

Section: Discussionmentioning

confidence: 99%

Climate and Demography Dictate the Strength of Predator-Prey Overlap in a Subarctic Marine Ecosystem

et al. 2013

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There is growing evidence that climate and anthropogenic influences on marine ecosystems are largely manifested by changes in species spatial dynamics. However, less is known about how shifts in species distributions might alter predator-prey overlap and the dynamics of prey populations. We developed a general approach to quantify species spatial overlap and identify the biotic and abiotic variables that dictate the strength of overlap. We used this method to test the hypothesis that population abundance and temperature have a synergistic effect on the spatial overlap of arrowtooth flounder (predator) and juvenile Alaska walleye pollock (prey, age-1) in the eastern Bering Sea. Our analyses indicate that (1) flounder abundance and temperature are key variables dictating the strength of flounder and pollock overlap, (2) changes in the magnitude of overlap may be largely driven by density-dependent habitat selection of flounder, and (3) species overlap is negatively correlated to juvenile pollock recruitment when flounder biomass is high. Overall, our findings suggest that continued increases in flounder abundance coupled with the predicted long-term warming of ocean temperatures could have important implications for the predator-prey dynamics of arrowtooth flounder and juvenile pollock. The approach used in this study is valuable for identifying potential consequences of climate variability and exploitation on species spatial dynamics and interactions in many marine ecosystems.

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“…6h) is consistent with a direct, ongoing influence of fishing pressure on community structure. In particular, awareness has been growing for several years that increases in arrowtooth flounder populations in the Gulf of Alaska and Bering Sea may reflect the lower exploitation pressure on this species relative to other groundfish, with a positive feedback created by increased arrowtooth flounder predation on other groundfishes (Bailey, 2000;Zador et al, 2011;Bailey et al, 2012).…”

Section: (L)mentioning

confidence: 99%

Reassessing regime shifts in the North Pacific: incremental climate change and commercial fishing are necessary for explaining decadal‐scale biological variability

Litzow

Mueter

Hobday

2013

Global Change Biology

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In areas of the North Pacific that are largely free of overfishing, climate regime shifts - abrupt changes in modes of low-frequency climate variability - are seen as the dominant drivers of decadal-scale ecological variability. We assessed the ability of leading modes of climate variability [Pacific Decadal Oscillation (PDO), North Pacific Gyre Oscillation (NPGO), Arctic Oscillation (AO), Pacific-North American Pattern (PNA), North Pacific Index (NPI), El Niño-Southern Oscillation (ENSO)] to explain decadal-scale (1965-2008) patterns of climatic and biological variability across two North Pacific ecosystems (Gulf of Alaska and Bering Sea). Our response variables were the first principle component (PC1) of four regional climate parameters [sea surface temperature (SST), sea level pressure (SLP), freshwater input, ice cover], and PCs 1-2 of 36 biological time series [production or abundance for populations of salmon (Oncorhynchus spp.), groundfish, herring (Clupea pallasii), shrimp, and jellyfish]. We found that the climate modes alone could not explain ecological variability in the study region. Both linear models (for climate PC1) and generalized additive models (for biology PC1-2) invoking only the climate modes produced residuals with significant temporal trends, indicating that the models failed to capture coherent patterns of ecological variability. However, when the residual climate trend and a time series of commercial fishery catches were used as additional candidate variables, resulting models of biology PC1-2 satisfied assumptions of independent residuals and out-performed models constructed from the climate modes alone in terms of predictive power. As measured by effect size and Akaike weights, the residual climate trend was the most important variable for explaining biology PC1 variability, and commercial catch the most important variable for biology PC2. Patterns of climate sensitivity and exploitation history for taxa strongly associated with biology PC1-2 suggest plausible mechanistic explanations for these modeling results. Our findings suggest that, even in the absence of overfishing and in areas strongly influenced by internal climate variability, climate regime shift effects can only be understood in the context of other ecosystem perturbations.

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Near real-time forecasting of recruitment from larval surveys: application to Alaska pollock

Cited by 15 publications

References 27 publications

Density‐ and size‐dependent mortality in fish early life stages

Density‐ and size‐dependent mortality in fish early life stages

Climate and Demography Dictate the Strength of Predator-Prey Overlap in a Subarctic Marine Ecosystem

Reassessing regime shifts in the North Pacific: incremental climate change and commercial fishing are necessary for explaining decadal‐scale biological variability

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