Distribution patterns of<scp>P</scp>acific halibut (<i>Hippoglossus stenolepis</i>) in relation to environmental variables along the continental shelf waters of the<scp>US W</scp>est<scp>C</scp>oast and southern<scp>B</scp>ritish<scp>C</scp>olumbia

Sadorus, Lauri L.; Mantua, Nathan J.; Essington, Timothy E.; Hickey, Barbara M.; Hare, Steven R.

doi:10.1111/fog.12057

Cited by 18 publications

(20 citation statements)

References 64 publications

(89 reference statements)

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“…Observed range changes in non-hypoxia tolerant halibut, adds weight to the findings of AR5 (Sadorus et al, 2014). The work of Cheung et al (2014) supports the assertions of the AR5, finding high sensitivity in the larvae of benthic invertebrates.…”

Section: Updates To Ar5supporting

confidence: 60%

An updated synthesis of the observed and projected impacts of climate change on the chemical, physical and biological processes in the oceans

et al. 2015

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The 5th Assessment Report (AR5) of the Intergovernmental Panel on Climate Change (IPCC) states with very high certainty that anthropogenic emissions have caused measurable changes in the physical ocean environment. These changes are summarized with special focus on those that are predicted to have the strongest, most direct effects on ocean biological processes; namely, ocean warming and associated phenomena (including stratification and sea level rise) as well as deoxygenation and ocean acidification. The biological effects of these changes are then discussed for microbes (including phytoplankton), plants, animals, warm and cold-water corals, and ecosystems. The IPCC AR5 highlighted several areas related to both the physical and biological processes that required further research. As a rapidly developing field, there have been many pertinent studies published since the cut off dates for the AR5, which have increased our understanding of the processes at work. This study undertook an extensive review of recently published literature to update the findings of the AR5 and provide a synthesized review on the main issues facing future oceans. The level of detail provided in the AR5 and subsequent work provided a basis for constructing projections of the state of ocean ecosystems in 2100 under two the Representative Concentration Pathways RCP4.5 and 8.5. Finally the review highlights notable additions, clarifications and points of departure from AR5 provided by subsequent studies.

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Section: Updates To Ar5supporting

confidence: 60%

An updated synthesis of the observed and projected impacts of climate change on the chemical, physical and biological processes in the oceans

et al. 2015

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“…Sadorus et al. () found a significant relationship between dissolved oxygen and catch rates of Pacific halibut. Primary production (plankton) concentration and distribution and subsequent changes in secondary production levels have also been linked to groundfish abundance (Francis et al., ; McGowan, Cayan, & Dorman, ).…”

Section: Discussionmentioning

confidence: 99%

“…SST may also be a proxy for other environmental variables, such as oxygen levels, ocean mixing, and plankton availability, that may affect these groundfish to varying degrees. Sadorus et al (2014) found a significant relationship between dissolved oxygen and catch rates of Pacific halibut. Primary production (plankton) concentration and distribution and subsequent changes in secondary production levels have also been linked to groundfish abundance (Francis et al, 1998;McGowan, Cayan, & Dorman, 1998 Notes.…”

Section: Control Of Bayesian Parameter ϕ In Crossvalidationmentioning

confidence: 91%

“…The inclusion of SST in the A and A 1 models increases the absolute forecasting errors for all species. Covariates in the ARIMAX and Bayesian settings are incorporated linearly; however, the effect of winter SST on groundfish catch is likely to be nonlinear (Laurel, Hurst, Copeman, & Davis, 2008;Rooper & Martin, 2009;Sadorus, Mantua, Essington, Hickey, & Hare, 2014), which is apparent in Supporting Information Figure S3; therefore, the effect's nonlinear shape is not being taken into account in the A, A 1 , B, and B 1 forecasting methods.…”

Section: Control Of Bayesian Parameter ϕ In Crossvalidationmentioning

confidence: 99%

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Spatiotemporally explicit model averaging for forecasting of Alaskan groundfish catch

Correia

2018

Ecology and Evolution

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Fisheries management is dominated by the need to forecast catch and abundance of commercially and ecologically important species. The influence of spatial information and environmental factors on forecasting error is not often considered. I propose a forecasting method called spatiotemporally explicit model averaging (STEMA) to combine spatial and temporal information through model averaging. I examine the performance of STEMA against two popular forecasting models and a modern spatial prediction model: the autoregressive integrated moving averages with explanatory variables (ARIMAX) model, the Bayesian hierarchical model, and the varying coefficient model. I focus on applying the methods to four species of Alaskan groundfish for which catch data are available. My method reduces forecasting errors significantly for most of the tested models when compared to ARIMAX, Bayesian, and varying coefficient methods. I also consider the effect of sea surface temperature (SST) on the forecasting of catch, as multiple studies reveal a potential influence of water temperature on the survival and growth of juvenile groundfish. For most of the preferred models, inclusion of SST in the model improved forecasting of catch. It is advisable to consider both spatial information and relevant environmental factors in forecasting models to obtain more accurate projections of population abundance. The STEMA method is capable of accounting for spatial information in forecasting and can be applied to various types of data because of its flexible varying coefficient model structure. It is therefore a suitable forecasting method for application to many fields including ecology, epidemiology, and climatology.

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“…Ocean warming as a result of climate change, sometimes in combination with other drivers, can affect the distribution, abundance, species richness, and ecology of many of the organisms-both hosts and parasites-living in the oceans (Kaschner et al, 2011;Marcogliese, 2008;Sadorus et al, 2014). Of particular concern for foodborne parasites are the various vertebrates and invertebrates consumed by people.…”

Section: Direct Effects Of Climate Change During Productionmentioning

confidence: 99%

Foodborne parasites and climate change

Polley

2015

Foodborne Parasites in the Food Supply Web

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Distribution patterns ofPacific halibut (Hippoglossus stenolepis) in relation to environmental variables along the continental shelf waters of theUS WestCoast and southernBritishColumbia

Cited by 18 publications

References 64 publications

An updated synthesis of the observed and projected impacts of climate change on the chemical, physical and biological processes in the oceans

An updated synthesis of the observed and projected impacts of climate change on the chemical, physical and biological processes in the oceans

Spatiotemporally explicit model averaging for forecasting of Alaskan groundfish catch

Foodborne parasites and climate change

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