Projected future biophysical states of the Bering Sea

Hermann, Albert J.; Gibson, Georgina A.; Bond, Nicholas A.; Curchitser, Enrique N.; Hedstrom, Kate; Cheng, Wei; Wang, Muyin; Cokelet, Edward D.; Stabeno, Phyllis J.; Aydin, Kerim

doi:10.1016/j.dsr2.2015.11.001

Cited by 70 publications

(84 citation statements)

References 39 publications

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“…Refined resolution in global climate models has allowed them to better resolve coastal processes and, in some cases, to reduce regional model biases (Saba et al, 2016). Dynamical downscaling offers a second means of improving coastal process resolution (e.g., Hermann et al, 2016;Holt et al, 2016), but the underlying global climate models are still subject to biases that propagate through regional model boundaries (e.g., Meier et al, 2006). Lastly, climate variability, which present-day models suggest has limited predictability beyond a year for all but a few regions of the ocean (Meehl et al, 2014), will continue to contribute uncertainty to future climate states (e.g., Deser et al, 2012).…”

Section: Improving Marine Mammal Distribution Projectionsmentioning

confidence: 99%

Projecting Marine Mammal Distribution in a Changing Climate

et al. 2017

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Climate-related shifts in marine mammal range and distribution have been observed in some populations; however, the nature and magnitude of future responses are uncertain in novel environments projected under climate change. This poses a challenge for agencies charged with management and conservation of these species. Specialized diets, restricted ranges, or reliance on specific substrates or sites (e.g., for pupping) make many marine mammal populations particularly vulnerable to climate change. High-latitude, predominantly ice-obligate, species have experienced some of the largest changes in habitat and distribution and these are expected to continue. Efforts to predict and project marine mammal distributions to date have emphasized data-driven statistical habitat models. These have proven successful for short time-scale (e.g., seasonal) management activities, but confidence that such relationships will hold for multi-decade projections and novel environments is limited. Recent advances in mechanistic modeling of marine mammals (i.e., models that rely on robust physiological and ecological principles expected to hold under climate change) may address this limitation. The success of such approaches rests on continued advances in marine mammal ecology, behavior, and physiology together with improved regional climate projections. The broad scope of this challenge suggests initial priorities be placed on vulnerable species or populations (those already experiencing declines or projected to undergo ecological shifts resulting from climate Silber et al.Projecting Marine Mammal Distributions changes that are consistent across climate projections) and species or populations for which ample data already exist (with the hope that these may inform climate change sensitivities in less well observed species or populations elsewhere). The sustained monitoring networks, novel observations, and modeling advances required to more confidently project marine mammal distributions in a changing climate will ultimately benefit management decisions across time-scales, further promoting the resilience of marine mammal populations.

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Section: Improving Marine Mammal Distribution Projectionsmentioning

confidence: 99%

Projecting Marine Mammal Distribution in a Changing Climate

et al. 2017

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“…The EBS is influenced by strong tidal mixing that establishes biophysical domains and seasonal ice cover and the formation of a benthic “cold pool” in the summer. The increased spatial resolution of the downscaled physical models (Hermann et al, , ) was able to resolve the cold pool, whereas this feature was not resolved in the three IPCC global models that were downscaled. The downscaled models were also able to model processes such as tidal mixing, which resulted in a change in the scale of modeled temperature relative to the IPCC models (Hermann et al, ).…”

Section: Discussionmentioning

confidence: 99%

“…The increased spatial resolution of the downscaled physical models (Hermann et al, , ) was able to resolve the cold pool, whereas this feature was not resolved in the three IPCC global models that were downscaled. The downscaled models were also able to model processes such as tidal mixing, which resulted in a change in the scale of modeled temperature relative to the IPCC models (Hermann et al, ). An additional benefit of downscaling was that it facilitated connection to a biological NPZ model (Gibson & Spitz, ) which allowed projections of important biological features such as phytoplankton and zooplankton distribution and abundance.…”

Section: Discussionmentioning

confidence: 99%

“…Projected future values of most of the exposure factors were obtained from dynamic downscaling using the output of general circulation models (GCMs) as surface forcing, boundary, and initial conditions for regional physical/biological models (Hermann et al, 2013(Hermann et al, , 2016). The regional model used was a Regional Ocean Modeling System (ROMS; Hermann et al, 2016) coupled with a nutrient-phytoplankton-zooplankton (NPZ) model (Gibson & Spitz, 2011). The ROMS model is a descendent from Danielson, Curchitser, Hedstrom, Weingartner, and Stabeno (2011), and has a 10 km horizontal spatial resolution with 10 vertical layers.…”

Section: Me Thodsmentioning

confidence: 99%

“…Recent research is described in over 150 publications, many of which are contained in four special issues of the journal Deep Sea Research Part II (Ashjian et al, , , , ). Much of the existing scientific information has direct relevance to climate vulnerability assessments, such as spatial projections of future environmental conditions (Hermann et al, , ) and mechanistic and correlative studies relating environmental factors to population abundance and productivity that have often focused on highly valued stocks such as walleye pollock ( Gadus chalcogrammus , hereafter pollock; Heintz, Siddon, Farley, & Napp, ; Hunt et al, ; Mueter, Bond, Ianelli, & Hollowed, ), flatfish (Spencer, ; Wilderbuer et al, ; Wilderbuer, Stockhausen, & Bond, ), and crabs (Punt, Foy, Dalton, Long, & Swiney, ; Punt, Poljak, Dalton, & Foy, ). In contrast, information for many EBS stocks is much less detailed, resulting in a wide dispersity of climate vulnerability information.…”

Section: Introductionmentioning

confidence: 99%

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Trait‐based climate vulnerability assessments in data‐rich systems: An application to eastern Bering Sea fish and invertebrate stocks

Spencer

Hollowed

Sigler

et al. 2019

Global Change Biology

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Trait‐based climate vulnerability assessments based on expert evaluation have emerged as a rapid tool to assess biological vulnerability when detailed correlative or mechanistic studies are not feasible. Trait‐based assessments typically view vulnerability as a combination of sensitivity and exposure to climate change. However, in some locations, a substantial amount of information may exist on system productivity and environmental conditions (both current and projected), with potential disparities in the information available for data‐rich and data‐poor stocks. Incorporating this level of detailed information poses challenges when conducting, and communicating uncertainty from, rapid vulnerability assessments. We applied a trait‐based vulnerability assessment to 36 fish and invertebrate stocks in the eastern Bering Sea (EBS), a data‐rich ecosystem. In recent years, the living marine resources of the EBS and Aleutian Islands have supported fisheries worth more than US $1 billion of annual ex‐vessel value. Our vulnerability assessment uses projections (to 2039) from three downscaled climate models, and graphically characterizes the variation in climate projections between climate models and between seasons. Bootstrapping was used to characterize uncertainty in specific biological traits and environmental variables, and in the scores for sensitivity, exposure, and vulnerability. The sensitivity of EBS stocks to climate change ranged from “low” to “high,” but vulnerability ranged between “low” and “moderate” due to limited exposure to climate change. Comparison with more detailed studies reveals that water temperature is an important variable for projecting climate impacts on stocks such as walleye pollock (Gadus chalcogrammus), and sensitivity analyses revealed that modifying the rule for determining vulnerability increased the vulnerability scores. This study demonstrates the importance of considering several uncertainties (e.g., climate projections, biological, and model structure) when conducting climate vulnerability assessments, and can be extended in future research to consider the vulnerability of user groups dependent on these stocks.

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Simulated Impact of Glacial Runoff on CO₂ Uptake in the Gulf of Alaska

Pilcher

Siedlecki

Hermann

et al. 2018

Geophysical Research Letters

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The Gulf of Alaska (GOA) receives substantial summer freshwater runoff from glacial meltwater. The alkalinity of this runoff is highly dependent on the glacial source and can modify the coastal carbon cycle. We use a regional ocean biogeochemical model to simulate CO2 uptake in the GOA under different alkalinity‐loading scenarios. The GOA is identified as a current net sink of carbon, though low‐alkalinity tidewater glacial runoff suppresses summer coastal carbon uptake. Our model shows that increasing the alkalinity generates an increase in annual CO2 uptake of 1.9–2.7 TgC/yr. This transition is comparable to a projected change in glacial runoff composition (i.e., from tidewater to land‐terminating) due to continued climate warming. Our results demonstrate an important local carbon‐climate feedback that can significantly increase coastal carbon uptake via enhanced air‐sea exchange, with potential implications to the coastal ecosystems in glaciated areas around the world.

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Projected future biophysical states of the Bering Sea

Cited by 70 publications

References 39 publications

Projecting Marine Mammal Distribution in a Changing Climate

Projecting Marine Mammal Distribution in a Changing Climate

Trait‐based climate vulnerability assessments in data‐rich systems: An application to eastern Bering Sea fish and invertebrate stocks

Simulated Impact of Glacial Runoff on CO₂ Uptake in the Gulf of Alaska

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Projected future biophysical states of the Bering Sea

Cited by 70 publications

References 39 publications

Projecting Marine Mammal Distribution in a Changing Climate

Projecting Marine Mammal Distribution in a Changing Climate

Trait‐based climate vulnerability assessments in data‐rich systems: An application to eastern Bering Sea fish and invertebrate stocks

Simulated Impact of Glacial Runoff on CO2 Uptake in the Gulf of Alaska

Contact Info

Product

Resources

About

Simulated Impact of Glacial Runoff on CO₂ Uptake in the Gulf of Alaska