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Oceans of plenty? Challenges, advancements, and future directions for the provision of evidence-based fisheries management advice.
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- Reviews in Fish Biology & Fisheries, 2023, v. 33, n. 2, p. 375, doi. 10.1007/s11160-022-09726-7
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Monitoring programs of the U.S. Gulf of Mexico: inventory, development and use of a large monitoring database to map fish and invertebrate spatial distributions.
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- Reviews in Fish Biology & Fisheries, 2018, v. 28, n. 4, p. 667, doi. 10.1007/s11160-018-9525-2
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Spatial variation buffers temporal fluctuations in early juvenile survival for an endangered Pacific salmon.
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- Journal of Animal Ecology, 2014, v. 83, n. 1, p. 157, doi. 10.1111/1365-2656.12117
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Multispecies estimation of Bayesian priors for catchability trends and density dependence in the US Gulf of Mexico.
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- Canadian Journal of Fisheries & Aquatic Sciences, 2010, v. 67, n. 6, p. 936, doi. 10.1139/F10-040
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- Article
The multivariate-Tweedie: a self-weighting likelihood for age and length composition data arising from hierarchical sampling designs.
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- ICES Journal of Marine Science / Journal du Conseil, 2023, v. 80, n. 10, p. 2630, doi. 10.1093/icesjms/fsac159
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Modelling time-varying growth in state-space stock assessments.
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- ICES Journal of Marine Science / Journal du Conseil, 2023, v. 80, n. 7, p. 2036, doi. 10.1093/icesjms/fsad133
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Understanding transboundary stocks' availability by combining multiple fisheries-independent surveys and oceanographic conditions in spatiotemporal models.
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- ICES Journal of Marine Science / Journal du Conseil, 2022, v. 79, n. 4, p. 1063, doi. 10.1093/icesjms/fsac046
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Combining scientific survey and commercial catch data to map fish distribution.
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- ICES Journal of Marine Science / Journal du Conseil, 2022, v. 79, n. 4, p. 1133, doi. 10.1093/icesjms/fsac032
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Identifying species complexes based on spatial and temporal clustering from joint dynamic species distribution models.
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- ICES Journal of Marine Science / Journal du Conseil, 2022, v. 79, n. 3, p. 677, doi. 10.1093/icesjms/fsac015
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spatial statistical approach for identifying population structuring of marine fish species: European sprat as a case study.
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- ICES Journal of Marine Science / Journal du Conseil, 2022, v. 79, n. 2, p. 423, doi. 10.1093/icesjms/fsac007
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Development and simulation testing for a new approach to density dependence in species distribution models.
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- ICES Journal of Marine Science / Journal du Conseil, 2022, v. 79, n. 1, p. 117, doi. 10.1093/icesjms/fsab247
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Grand challenge for habitat science: stage-structured responses, nonlocal drivers, and mechanistic associations among habitat variables affecting fishery productivity.
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- ICES Journal of Marine Science / Journal du Conseil, 2021, v. 78, n. 6, p. 1956, doi. 10.1093/icesjms/fsaa236
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Incorporating vertical distribution in index standardization accounts for spatiotemporal availability to acoustic and bottom trawl gear for semi-pelagic species.
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- ICES Journal of Marine Science / Journal du Conseil, 2021, v. 78, n. 5, p. 1826, doi. 10.1093/icesjms/fsab085
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Seasonal and interannual variation in spatio-temporal models for index standardization and phenology studies.
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- ICES Journal of Marine Science / Journal du Conseil, 2020, v. 77, n. 5, p. 1879, doi. 10.1093/icesjms/fsaa074
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Simulation testing a new multi-stage process to measure the effect of increased sampling effort on effective sample size for age and length data.
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- ICES Journal of Marine Science / Journal du Conseil, 2020, v. 77, n. 5, p. 1728, doi. 10.1093/icesjms/fsaa036
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Comparison of multiple approaches to calculate time-varying biological reference points in climate-linked population-dynamics models.
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- ICES Journal of Marine Science / Journal du Conseil, 2020, v. 77, n. 3, p. 930, doi. 10.1093/icesjms/fsz215
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Coupled changes in biomass and distribution drive trends in availability of fish stocks to US West Coast ports.
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- ICES Journal of Marine Science / Journal du Conseil, 2020, v. 77, n. 1, p. 188, doi. 10.1093/icesjms/fsz211
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Developing spatio-temporal models using multiple data types for evaluating population trends and habitat usage.
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- ICES Journal of Marine Science / Journal du Conseil, 2019, v. 76, n. 6, p. 1748, doi. 10.1093/icesjms/fsz075
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Overcoming long Bayesian run times in integrated fisheries stock assessments.
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- ICES Journal of Marine Science / Journal du Conseil, 2019, v. 76, n. 6, p. 1477, doi. 10.1093/icesjms/fsz059
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Ensemble models for data-poor assessment: accounting for uncertainty in life-history information.
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- ICES Journal of Marine Science / Journal du Conseil, 2019, v. 76, n. 4, p. 870, doi. 10.1093/icesjms/fsz012
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The ocean's movescape: fisheries management in the bio-logging decade (2018–2028).
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- ICES Journal of Marine Science / Journal du Conseil, 2019, v. 76, n. 2, p. 477, doi. 10.1093/icesjms/fsy211
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utility of spatial model-based estimators of unobserved bycatch.
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- ICES Journal of Marine Science / Journal du Conseil, 2019, v. 76, n. 1, p. 255, doi. 10.1093/icesjms/fsy153
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Detecting mortality variation to enhance forage fish population assessments.
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- ICES Journal of Marine Science / Journal du Conseil, 2019, v. 76, n. 1, p. 124, doi. 10.1093/icesjms/fsy160
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The benefits and risks of incorporating climate-driven growth variation into stock assessment models, with application to Splitnose Rockfish (Sebastes diploproa).
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- ICES Journal of Marine Science / Journal du Conseil, 2018, v. 75, n. 1, p. 245, doi. 10.1093/icesjms/fsx147
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Producing distribution maps for informing ecosystem-based fisheries management using a comprehensive survey database and spatio-temporal models.
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- ICES Journal of Marine Science / Journal du Conseil, 2018, v. 75, n. 1, p. 158, doi. 10.1093/icesjms/fsx120
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Comparing estimates of abundance trends and distribution shifts using single- and multispecies models of fishes and biogenic habitat.
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- ICES Journal of Marine Science / Journal du Conseil, 2017, v. 74, n. 5, p. 1311, doi. 10.1093/icesjms/fsw193
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Geostatistical delta-generalized linear mixed models improve precision for estimated abundance indices for West Coast groundfishes.
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- ICES Journal of Marine Science / Journal du Conseil, 2015, v. 72, n. 5, p. 1297, doi. 10.1093/icesjms/fsu243
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Mixed effects: a unifying framework for statistical modelling in fisheries biology.
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- ICES Journal of Marine Science / Journal du Conseil, 2015, v. 72, n. 5, p. 1245, doi. 10.1093/icesjms/fsu213
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The determination of data-poor catch limits in the United States: is there a better way?
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- ICES Journal of Marine Science / Journal du Conseil, 2015, v. 72, n. 1, p. 237, doi. 10.1093/icesjms/fsu085
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Random effect estimation of time-varying factors in Stock Synthesis.
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- ICES Journal of Marine Science / Journal du Conseil, 2015, v. 72, n. 1, p. 178, doi. 10.1093/icesjms/fst211
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Standardizing compositional data for stock assessment.
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- ICES Journal of Marine Science / Journal du Conseil, 2014, v. 71, n. 5, p. 1117, doi. 10.1093/icesjms/fst224
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Development and application of an agent-based model to evaluate methods for estimating relative abundance indices for shoaling fish such as Pacific rockfish (Sebastes spp.).
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- ICES Journal of Marine Science / Journal du Conseil, 2012, v. 69, n. 4, p. 635, doi. 10.1093/icesjms/fss003
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Auxiliary and focal assessment models: a proof-of-concept involving time-varying catchability and fishery stock-status evaluation.
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- ICES Journal of Marine Science / Journal du Conseil, 2011, v. 68, n. 10, p. 2264, doi. 10.1093/icesjms/fsr160
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A review of methods for quantifying spatial predator–prey overlap.
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- Global Ecology & Biogeography, 2019, v. 28, n. 11, p. 1561, doi. 10.1111/geb.12984
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Joint dynamic species distribution models: a tool for community ordination and spatio-temporal monitoring.
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- Global Ecology & Biogeography, 2016, v. 25, n. 9, p. 1144, doi. 10.1111/geb.12464
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Thirteen novel ideas and underutilised resources to support progress towards a range‐wide American eel stock assessment.
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- Fisheries Management & Ecology, 2022, v. 29, n. 5, p. 516, doi. 10.1111/fme.12572
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Trees for fishes: The neglected role for phylogenetic comparative methods in fisheries science.
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- Fish & Fisheries, 2024, v. 25, n. 1, p. 168, doi. 10.1111/faf.12800
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Measuring complexity for hierarchical models using effective degrees of freedom.
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- Ecology, 2024, v. 105, n. 7, p. 1, doi. 10.1002/ecy.4327
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Diet analysis using generalized linear models derived from foraging processes using R package mvtweedie.
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- Ecology, 2022, v. 103, n. 5, p. 1, doi. 10.1002/ecy.3637
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Spatially varying coefficients can improve parsimony and descriptive power for species distribution models.
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- Ecography, 2023, v. 2023, n. 5, p. 1, doi. 10.1111/ecog.06510
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Climate‐informed models benefit hindcasting but present challenges when forecasting species–habitat associations.
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- Ecography, 2022, v. 2022, n. 10, p. 1, doi. 10.1111/ecog.06189
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Shifting fish distributions impact predation intensity in a sub‐Arctic ecosystem.
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- Ecography, 2022, v. 2022, n. 9, p. 1, doi. 10.1111/ecog.06084
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Forecasting community reassembly using climate‐linked spatio‐temporal ecosystem models.
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- Ecography, 2021, v. 44, n. 4, p. 612, doi. 10.1111/ecog.05471
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Improving estimates of the state of global fisheries depends on better data.
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- Fish & Fisheries, 2021, v. 22, n. 6, p. 1377, doi. 10.1111/faf.12593
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Estimating fine‐scale movement rates and habitat preferences using multiple data sources.
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- Fish & Fisheries, 2021, v. 22, n. 6, p. 1359, doi. 10.1111/faf.12592
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Spatio‐temporal analyses of marine predator diets from data‐rich and data‐limited systems.
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- Fish & Fisheries, 2020, v. 21, n. 4, p. 718, doi. 10.1111/faf.12457
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A novel spatiotemporal stock assessment framework to better address fine‐scale species distributions: Development and simulation testing.
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- Fish & Fisheries, 2020, v. 21, n. 2, p. 350, doi. 10.1111/faf.12433
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Predicting recruitment density dependence and intrinsic growth rate for all fishes worldwide using a data‐integrated life‐history model.
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- Fish & Fisheries, 2020, v. 21, n. 2, p. 237, doi. 10.1111/faf.12427
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Spatio‐temporal models of intermediate complexity for ecosystem assessments: A new tool for spatial fisheries management.
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- Fish & Fisheries, 2019, v. 20, n. 6, p. 1083, doi. 10.1111/faf.12398
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Realizing the potential of trait‐based approaches to advance fisheries science.
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- Fish & Fisheries, 2019, v. 20, n. 5, p. 1034, doi. 10.1111/faf.12395
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