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  • 1
    Online Resource
    Online Resource
    Climate to fish: Synthesizing field work, data and models in a 39-year retrospective analysis of seasonal processes on the eastern Bering Sea shelf and slope
    Elsevier BV ; 2016
    In:  Deep Sea Research Part II: Topical Studies in Oceanography Vol. 134 ( 2016-12), p. 390-412
    Details
    In: Deep Sea Research Part II: Topical Studies in Oceanography, Elsevier BV, Vol. 134 ( 2016-12), p. 390-412
    Type of Medium: Online Resource
    ISSN: 0967-0645
    URL: Article
    DOI: 10.1016/j.dsr2.2016.07.009
    Language: English
    Publisher: Elsevier BV
    Publication Date: 2016
    detail.hit.zdb_id: 1141627-0
    detail.hit.zdb_id: 1500312-7
    SSG: 14
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  • 2
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    The estimated impact of changes to otolith field-sampling and ageing effort on stock assessment inputs, outputs, and catch advice
    Canadian Science Publishing ; 2023
    In:  Canadian Journal of Fisheries and Aquatic Sciences Vol. 80, No. 1 ( 2023-01-01), p. 115-131
    Details
    In: Canadian Journal of Fisheries and Aquatic Sciences, Canadian Science Publishing, Vol. 80, No. 1 ( 2023-01-01), p. 115-131
    Abstract: Generating accurate data for stock assessments is resource-demanding, necessitating periodic evaluation of survey sampling designs and potential impacts on stock assessments. We developed a framework for bootstrapped resampling of survey age data and calculation of input sample sizes as a function of among-bootstrap variance in age compositions. Data from this bootstrap estimator were then used to evaluate the influence of alternative sampling rates and methods on uncertainty in estimates of the overfishing limit (OFL) calculated using stock assessment models. For dusky rockfish ( Sebastes variabilis) and Pacific ocean perch ( Sebastes alutus), a 10% decrease in the number of tows sampled upon led to a predicted 5%–6% increase in the CV of OFL (log–log slope = −0.576 to −0.486), which was greater than the 0%–2% increase from a 10% decrease in otoliths-per-tow (log–log slope = −0.238 to −0.029). Application of this approach across all stocks monitored in the survey of interest is required to identify which stocks ( i) benefit the most from increased sampling of ageing structures or ( ii) cost the least in terms of OFL uncertainty owing to reduced sampling.
    Type of Medium: Online Resource
    ISSN: 0706-652X , 1205-7533
    URL: Article
    DOI: 10.1139/cjfas-2022-0050
    Language: English
    Publisher: Canadian Science Publishing
    Publication Date: 2023
    detail.hit.zdb_id: 7966-2
    detail.hit.zdb_id: 1473089-3
    SSG: 21,3
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  • 3
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    Adapting to climate‐driven distribution shifts using model‐based indices and age composition from multiple surveys in the walleye pollock ( Gadus chalcogrammus ) stock assessment
    Wiley ; 2020
    In:  Fisheries Oceanography Vol. 29, No. 6 ( 2020-11), p. 541-557
    Details
    In: Fisheries Oceanography, Wiley, Vol. 29, No. 6 ( 2020-11), p. 541-557
    Abstract: The northern Bering Sea is transitioning from an Arctic to subarctic fish community as climate warms. Scientists and managers aim to understand how these changing conditions are influencing fish biomass and spatial distribution in this region, as both are used to inform stock assessments and fisheries management advice. Here, we use a spatio‐temporal model for walleye pollock ( Gadus chalcogrammus ) to provide two inputs to its stock assessment model: (a) an alternative model‐based biomass index and (b) alternative model‐based age compositions. Both inputs were derived from multiple fishery‐independent data that span different regions of space and time. We developed an assessment model that utilizes both the standard and model‐based inputs from multiple surveys despite inconsistencies in spatial and temporal coverage, and we found that using these data provide an improved spatial and temporal scope of total pollock biomass. Age composition information indicated that pollock density is increasing and moving farther north, particularly for older pollock. We found that including an index of cold pool extent could be used to extrapolate pollock densities in the northern Bering Sea in unsampled years. Stock assessment parameter estimates were similar for standard and model‐based input. This study demonstrates that spatio‐temporal model‐based estimates of a biomass index and age composition can facilitate rapid changes in stock assessment structure in response to climate‐driven shifts in spatial distribution. We conclude that assimilating data from regions neighboring standard survey areas, such as the Chukchi Sea and western Bering Sea, would improve understanding and management efforts as fish distributions change under a warming climate.
    Type of Medium: Online Resource
    ISSN: 1054-6006 , 1365-2419
    URL: Issue
    URL: Article
    DOI: 10.1111/fog.v29.6
    DOI: 10.1111/fog.12494
    Language: English
    Publisher: Wiley
    Publication Date: 2020
    detail.hit.zdb_id: 1214985-8
    detail.hit.zdb_id: 2020300-7
    SSG: 21,3
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  • 4
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    Characterizing dominant patterns of spatiotemporal variation for a transboundary groundfish assemblage
    Wiley ; 2023
    In:  Fisheries Oceanography Vol. 32, No. 6 ( 2023-11), p. 541-558
    Details
    In: Fisheries Oceanography, Wiley, Vol. 32, No. 6 ( 2023-11), p. 541-558
    Abstract: Many mobile marine taxa are changing their distributions in response to climate change. Such movements pose a challenge to fisheries monitoring and management, particularly in systems where climate‐adaptive and ecosystem‐based management objectives are emphasized. While shifts in species distributions can be discerned from long‐term fisheries‐independent monitoring data, distilling coherent patterns across space and time from such datasets can be challenging, particularly for transboundary stocks. One approach for identifying dominant patterns of spatiotemporal variation that has been widely used in physical atmospheric and oceanographic studies is empirical orthogonal function (EOF) analysis, wherein spatiotemporal variation is separated into time‐series of annual factor loadings and spatial response maps. Here, we apply an extension of EOF analysis that has been modified for compatibility with biological sampling data to a combined US–Russian fisheries‐independent survey dataset that spans the eastern (United States) and western (Russia) Bering Sea shelf to estimate dominant patterns of spatiotemporal variation for 10 groundfish species at a shelf‐wide scale. EOF identified one axis of variability that was coherent with the extent of cold (≤0°C) near‐bottom waters (the cold pool) previously shown to be a key influence on species distributions and ecosystem structure for the Bering Sea. However, the leading axis of variability identified by our EOF analysis was characterized by low frequency changes in the distributions of several species over longer time scales. Our analysis has important implications for predicting variation in species distributions over time and demonstrates a widely applicable method for leveraging combined fisheries‐independent survey datasets to characterize community‐level responses to ecosystem change at basin‐wide scales.
    Type of Medium: Online Resource
    ISSN: 1054-6006 , 1365-2419
    URL: Issue
    URL: Article
    DOI: 10.1111/fog.v32.6
    DOI: 10.1111/fog.12651
    Language: English
    Publisher: Wiley
    Publication Date: 2023
    detail.hit.zdb_id: 1214985-8
    detail.hit.zdb_id: 2020300-7
    SSG: 21,3
    SSG: 12
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  • 5
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    The relative influence of temperature and size‐structure on fish distribution shifts: A case‐study on Walleye pollock in the Bering Sea
    Wiley ; 2017
    In:  Fish and Fisheries Vol. 18, No. 6 ( 2017-11), p. 1073-1084
    Details
    In: Fish and Fisheries, Wiley, Vol. 18, No. 6 ( 2017-11), p. 1073-1084
    Abstract: Research has estimated associations between water temperature and the spatial distribution of marine fishes based upon correlations between temperature and the centroid of fish distribution (centre of gravity, COG ). Analysts have then projected future water temperatures to forecast shifts in COG , but often neglected to demonstrate that temperature explains a substantial portion of historical distribution shifts. We argue that estimating the proportion of observed distributional shifts that can be attributed to temperature vs. other factors is a critical first step in forecasting future changes. We illustrate this approach using Gadus chalcogrammus (Walleye pollock) in the Eastern Bering Sea, and use a vector‐autoregressive spatiotemporal model to attribute variation in COG from 1982 to 2015 to three factors: local or regional changes in surface and bottom temperature (“temperature effects”), fluctuations in size‐structure that cause COG to be skewed towards juvenile or adult habitats (“size‐structured effects”) or otherwise unexplained spatiotemporal variation in distribution (“unexplained effects”). We find that the majority of variation in COG (including the north‐west trend since 1982) is largely unexplained by temperature or size‐structured effects. Temperature alone generates a small portion of primarily north–south variation in COG , while size‐structured effects generate a small portion of east–west variation. We therefore conclude that projections of future distribution based on temperature alone are likely to miss a substantial portion of both the interannual variation and interdecadal trends in COG for this species. More generally, we suggest that decomposing variation in COG into multiple causal factors is a vital first step for projecting likely impacts of temperature change.
    Type of Medium: Online Resource
    ISSN: 1467-2960 , 1467-2979
    URL: Issue
    URL: Article
    DOI: 10.1111/faf.2017.18.issue-6
    DOI: 10.1111/faf.12225
    Language: English
    Publisher: Wiley
    Publication Date: 2017
    detail.hit.zdb_id: 2024569-5
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  • 6
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    Joint dynamic species distribution models: a tool for community ordination and spatio‐temporal monitoring
    Wiley ; 2016
    In:  Global Ecology and Biogeography Vol. 25, No. 9 ( 2016-09), p. 1144-1158
    Details
    In: Global Ecology and Biogeography, Wiley, Vol. 25, No. 9 ( 2016-09), p. 1144-1158
    Abstract: Spatial analysis of the distribution and density of species is of continuing interest within theoretical and applied ecology. Species distribution models (SDMs) are being increasingly used to analyse count, presence–absence and presence‐only data sets. There is a growing literature on dynamic SDMs (which incorporate temporal variation in species distribution), joint SDMs (which simultaneously analyse the correlated distribution of multiple species) and geostatistical models (which account for similarity between nearby sites caused by unobserved covariates). However, no previous study has combined all three attributes within a single framework. Innovation We develop spatial dynamic factor analysis for use as a ‘joint, dynamic SDM’ (JDSDM), which uses geostatistical methods to account for spatial similarity when estimating one or more ‘factors’. Each factor evolves over time following a density‐dependent (Gompertz) process, and the log‐density of each species is approximated as a linear combination of different factors. We demonstrate a JDSDM using two multispecies case studies (an annual survey of bottom‐associated species in the Bering Sea and a seasonal survey of butterfly density in the continental USA), and also provide our code publicly as an R package. Main conclusions Case study applications show that that JDSDMs can be used for species ordination, i.e. showing that dynamics for butterfly species within the same genus are significantly more correlated than for species from different genera. We also demonstrate how JDSDMs can rapidly identify dominant patterns in community dynamics, including the decline and recovery of several Bering Sea fishes since 2008, and the ‘flight curves’ typical of early or late‐emerging butterflies. We conclude by suggesting future research that could incorporate phylogenetic relatedness or functional similarity, and propose that our approach could be used to monitor community dynamics at large spatial and temporal scales.
    Type of Medium: Online Resource
    ISSN: 1466-822X , 1466-8238
    URL: Issue
    URL: Article
    DOI: 10.1111/geb.2016.25.issue-9
    DOI: 10.1111/geb.12464
    Language: English
    Publisher: Wiley
    Publication Date: 2016
    detail.hit.zdb_id: 1479787-2
    detail.hit.zdb_id: 2021283-5
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  • 7
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    Spatial delay-difference models for estimating spatiotemporal variation in juvenile production and population abundance
    Canadian Science Publishing ; 2015
    In:  Canadian Journal of Fisheries and Aquatic Sciences Vol. 72, No. 12 ( 2015-12), p. 1897-1915
    Details
    In: Canadian Journal of Fisheries and Aquatic Sciences, Canadian Science Publishing, Vol. 72, No. 12 ( 2015-12), p. 1897-1915
    Abstract: Many important ecological questions require accounting for spatial variation in demographic rates (e.g., survival) and population variables (e.g., abundance per unit area). However, ecologists have few spatial modelling approaches that (i) fit directly to spatially referenced data, (ii) represent population dynamics explicitly and mechanistically, and (iii) estimate parameters using rigorous statistical methods. We therefore demonstrate a new and computationally efficient approach to spatial modelling that uses random fields in place of the random variables typically used in spatially aggregated models. We adapt this approach to delay-difference dynamics to estimate the impact of fishing and natural mortality, recruitment, and individual growth on spatial population dynamics for a fish population. In particular, we develop this approach to estimate spatial variation in average production of juvenile fishes (termed recruitment), as well as annual variation in the spatial distribution of recruitment. We first use a simulation experiment to demonstrate that the spatial delay-difference model can, in some cases, explain over 50% of spatial variance in recruitment. We also apply the spatial delay-difference model to data for rex sole (Glyptocephalus zachirus) in the Gulf of Alaska and show that average recruitment (across all years) is greatest near Kodiak Island but that some years show greatest recruitment in Southeast Alaska or the western Gulf of Alaska. Using model developments and software advances presented here, we argue that future research can develop models to approximate adult movement, incorporate spatial covariates to explain annual variation in recruitment, and evaluate management procedures that use spatially explicit estimates of population abundance.
    Type of Medium: Online Resource
    ISSN: 0706-652X , 1205-7533
    URL: Article
    DOI: 10.1139/cjfas-2014-0543
    Language: English
    Publisher: Canadian Science Publishing
    Publication Date: 2015
    detail.hit.zdb_id: 7966-2
    detail.hit.zdb_id: 1473089-3
    SSG: 21,3
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  • 8
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    Unlocking the triad of age, year, and cohort effects for stock assessment: Demonstration of a computationally efficient and reproducible framework using weight-at-age
    Elsevier BV ; 2023
    In:  Fisheries Research Vol. 266 ( 2023-10), p. 106755-
    Details
    In: Fisheries Research, Elsevier BV, Vol. 266 ( 2023-10), p. 106755-
    Type of Medium: Online Resource
    ISSN: 0165-7836
    URL: Article
    DOI: 10.1016/j.fishres.2023.106755
    Language: English
    Publisher: Elsevier BV
    Publication Date: 2023
    detail.hit.zdb_id: 406532-3
    detail.hit.zdb_id: 1497860-X
    SSG: 21,3
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  • 9
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    Understanding transboundary stocks’ availability by combining multiple fisheries-independent surveys and oceanographic conditions in spatiotemporal models
    Oxford University Press (OUP) ; 2022
    In:  ICES Journal of Marine Science Vol. 79, No. 4 ( 2022-05-23), p. 1063-1074
    Details
    In: ICES Journal of Marine Science, Oxford University Press (OUP), Vol. 79, No. 4 ( 2022-05-23), p. 1063-1074
    Abstract: Shifts in the distribution of groundfish species as oceans warm can complicate management efforts if species distributions expand beyond the extent of existing scientific surveys, changing the proportion of groundfish available to any one survey each year. We developed the first-ever model-based biomass estimates for three Bering Sea groundfishes (walleye pollock (Gadus chalcogrammus), Pacific cod (Gadus macrocephalus), and Alaska plaice (Pleuronectes quadrituberculatus)) by combining fishery-independent bottom trawl data from the U.S. and Russia in a spatiotemporal framework using Vector Autoregressive Spatio-Temporal (VAST) models. We estimated a fishing-power correction to calibrate disparate data sets and the effect of an annual oceanographic index to explain variation in groundfish spatiotemporal density. Groundfish densities shifted northward relative to historical densities, and high-density areas spanned the international border, particularly in years warmer than the long-term average. In the final year of comprehensive survey data (2017), 49%, 65%, 47% of biomass was in the western and northern Bering Sea for pollock, cod, and plaice, respectively, suggesting that availability of groundfish to the more regular eastern Bering Sea survey is declining. We conclude that international partnerships to combine past data and coordinate future data collection are necessary to track fish as they shift beyond historical survey areas.
    Type of Medium: Online Resource
    ISSN: 1054-3139 , 1095-9289
    URL: Article
    DOI: 10.1093/icesjms/fsac046
    Language: English
    Publisher: Oxford University Press (OUP)
    Publication Date: 2022
    detail.hit.zdb_id: 2463178-4
    detail.hit.zdb_id: 1468003-8
    detail.hit.zdb_id: 29056-7
    SSG: 12
    SSG: 21,3
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  • 10
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    Incorporating vertical distribution in index standardization accounts for spatiotemporal availability to acoustic and bottom trawl gear for semi-pelagic species
    Oxford University Press (OUP) ; 2021
    In:  ICES Journal of Marine Science Vol. 78, No. 5 ( 2021-09-07), p. 1826-1839
    Details
    In: ICES Journal of Marine Science, Oxford University Press (OUP), Vol. 78, No. 5 ( 2021-09-07), p. 1826-1839
    Abstract: Abundance indices from scientific surveys are key stock assessment inputs, but when the availability of fish varies in space and time, the estimated indices and associated uncertainties do not accurately reflect changes in population abundance. For example, indices for many semi-pelagic species rely on acoustic and bottom trawl gear that differ in water column coverage, and so spatiotemporal trends in fish vertical distribution affect the availability of fish to each gear type. The gears together cover the whole water column, and so in principle allow estimation of more accurate, combined indices of the whole population. Here, we extend previous methods and develop a vertically integrated index, which accounts for spatiotemporal correlation and works with data unbalanced spatially or unpaired from distinct surveys. Using eastern Bering Sea walleye pollock (Gadus chalcogrammus) as an example, we identified clear spatial and temporal patterns in vertical distribution and gear availability from 2007 to 2018. Estimated acoustic annual vertical availability ranged from 0.339 to 0.888 among years, and from 0.588 to 0.911 for the bottom trawl survey. Our results highlight the importance of accounting for the spatiotemporal and vertical distribution of semi-pelagic fish to estimate more accurate indices, and provide important context for gear availability.
    Type of Medium: Online Resource
    ISSN: 1054-3139 , 1095-9289
    URL: Article
    DOI: 10.1093/icesjms/fsab085
    Language: English
    Publisher: Oxford University Press (OUP)
    Publication Date: 2021
    detail.hit.zdb_id: 2463178-4
    detail.hit.zdb_id: 1468003-8
    detail.hit.zdb_id: 29056-7
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    SSG: 21,3
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