scholarly journals Satellite Observations Are Needed to Understand Ocean Acidification and Multi-Stressor Impacts on Fish Stocks in a Changing Arctic Ocean

2021 ◽  
Vol 8 ◽  
Author(s):  
Hannah L. Green ◽  
Helen S. Findlay ◽  
Jamie D. Shutler ◽  
Peter E. Land ◽  
Richard G. J. Bellerby
Keyword(s):  
Ocean Acidification ◽  
Arctic Ocean ◽  
Management Strategies ◽  
Experimental Studies ◽  
Satellite Observations ◽  
The Arctic ◽  
Fish Stock ◽  
Stock Management ◽  
Fish Stocks ◽  
Space And Time

It is widely projected that under future climate scenarios the economic importance of Arctic Ocean fish stocks will increase. The Arctic Ocean is especially vulnerable to ocean acidification and already experiences low pH levels not projected to occur on a global scale until 2100. This paper outlines how ocean acidification must be considered with other potential stressors to accurately predict movement of fish stocks toward, and within, the Arctic and to inform future fish stock management strategies. First, we review the literature on ocean acidification impacts on fish, next we identify the main obstacles that currently preclude ocean acidification from Arctic fish stock projections. Finally, we provide a roadmap to describe how satellite observations can be used to address these gaps: improve knowledge, inform experimental studies, provide regional assessments of vulnerabilities, and implement appropriate management strategies. This roadmap sets out three inter-linked research priorities: (1) Establish organisms and ecosystem physiochemical baselines by increasing the coverage of Arctic physicochemical observations in both space and time; (2) Understand the variability of all stressors in space and time; (3) Map life histories and fish stocks against satellite-derived observations of stressors.

scholarly journals Model constraints on the anthropogenic carbon budget of the Arctic Ocean

2019 ◽  
Vol 16 (11) ◽  
pp. 2343-2367 ◽  
Author(s):  
Jens Terhaar ◽  
James C. Orr ◽  
Marion Gehlen ◽  
Christian Ethé ◽  
Laurent Bopp
Keyword(s):  
Ocean Acidification ◽  
Arctic Ocean ◽  
Lower Limit ◽  
Ocean Circulation ◽  
The Arctic ◽  
Model Resolution ◽  
Lateral Transport ◽  
The Arctic Ocean ◽  
Anthropogenic Carbon ◽  
The Difference

Abstract. The Arctic Ocean is projected to experience not only amplified climate change but also amplified ocean acidification. Modeling future acidification depends on our ability to simulate baseline conditions and changes over the industrial era. Such centennial-scale changes require a global model to account for exchange between the Arctic and surrounding regions. Yet the coarse resolution of typical global models may poorly resolve that exchange as well as critical features of Arctic Ocean circulation. Here we assess how simulations of Arctic Ocean storage of anthropogenic carbon (Cant), the main driver of open-ocean acidification, differ when moving from coarse to eddy-admitting resolution in a global ocean-circulation–biogeochemistry model (Nucleus for European Modeling of the Ocean, NEMO; Pelagic Interactions Scheme for Carbon and Ecosystem Studies, PISCES). The Arctic's regional storage of Cant is enhanced as model resolution increases. While the coarse-resolution model configuration ORCA2 (2∘) stores 2.0 Pg C in the Arctic Ocean between 1765 and 2005, the eddy-admitting versions ORCA05 and ORCA025 (1∕2∘ and 1∕4∘) store 2.4 and 2.6 Pg C. The difference in inventory between model resolutions that is accounted for is only from their divergence after 1958, when ORCA2 and ORCA025 were initialized with output from the intermediate-resolution configuration (ORCA05). The difference would have been larger had all model resolutions been initialized in 1765 as was ORCA05. The ORCA025 Arctic Cant storage estimate of 2.6 Pg C should be considered a lower limit because that model generally underestimates observed CFC-12 concentrations. It reinforces the lower limit from a previous data-based approach (2.5 to 3.3 Pg C). Independent of model resolution, there was roughly 3 times as much Cant that entered the Arctic Ocean through lateral transport than via the flux of CO2 across the air–sea interface. Wider comparison to nine earth system models that participated in the Coupled Model Intercomparison Project Phase 5 (CMIP5) reveals much larger diversity of stored Cant and lateral transport. Only the CMIP5 models with higher lateral transport obtain Cant inventories that are close to the data-based estimates. Increasing resolution also enhances acidification, e.g., with greater shoaling of the Arctic's average depth of the aragonite saturation horizon during 1960–2012, from 50 m in ORCA2 to 210 m in ORCA025. Even higher model resolution would likely further improve such estimates, but its prohibitive costs also call for other more practical avenues for improvement, e.g., through model nesting, addition of coastal processes, and refinement of subgrid-scale parameterizations.

scholarly journals Decorrelation scales for Arctic Ocean hydrography – Part I: Amerasian Basin

Ocean Science ◽  
2018 ◽  
Vol 14 (1) ◽  
pp. 161-185 ◽  
Author(s):  
Hiroshi Sumata ◽  
Frank Kauker ◽  
Michael Karcher ◽  
Benjamin Rabe ◽  
Mary-Louise Timmermans ◽  
...  
Keyword(s):  
Data Assimilation ◽  
Arctic Ocean ◽  
Autocorrelation Function ◽  
Gaussian Function ◽  
The Arctic ◽  
Depth Range ◽  
Space And Time ◽  
Amerasian Basin ◽  
Decorrelation Scale

Abstract. Any use of observational data for data assimilation requires adequate information of their representativeness in space and time. This is particularly important for sparse, non-synoptic data, which comprise the bulk of oceanic in situ observations in the Arctic. To quantify spatial and temporal scales of temperature and salinity variations, we estimate the autocorrelation function and associated decorrelation scales for the Amerasian Basin of the Arctic Ocean. For this purpose, we compile historical measurements from 1980 to 2015. Assuming spatial and temporal homogeneity of the decorrelation scale in the basin interior (abyssal plain area), we calculate autocorrelations as a function of spatial distance and temporal lag. The examination of the functional form of autocorrelation in each depth range reveals that the autocorrelation is well described by a Gaussian function in space and time. We derive decorrelation scales of 150–200 km in space and 100–300 days in time. These scales are directly applicable to quantify the representation error, which is essential for use of ocean in situ measurements in data assimilation. We also describe how the estimated autocorrelation function and decorrelation scale should be applied for cost function calculation in a data assimilation system.

INTAROS synthesis of gap analysis of the existing Arctic observing systems

2020 ◽  
Author(s):  
Roberta Pirazzini ◽  
Michael Tjernström ◽  
Stein Sandven ◽  
Hanne Sagen ◽  
Torill Hamre ◽  
...  
Keyword(s):  
Arctic Ocean ◽  
Gap Analysis ◽  
Satellite Observations ◽  
The Arctic ◽  
Reference Level ◽  
Data Handling ◽  
Network Concept ◽  
The Arctic Ocean ◽  
Observing Systems

<p>A comprehensive assessment of a substantial subset of Arctic observing systems, data collections and satellite products across scientific disciplines was carried out in INTAROS, also including data repositories and a brief scientific gap analysis. The assessments cover a multitude of aspects such as sustainability, technical maturity and data handling for the entire chain from observation to users, including metadata procedures and availability to data. Community based environment monitoring programs were surveyed and assessed separately; they do not form part of the present assessment.</p><p>The assessed observing systems were first ranked according to general sustainability and other aspects, were analyzed subsequently. While the range of sustainability is large, it was found that high scores on all other aspects, such as for data handling and technical maturity, are more likely for systems with high sustainability. Moreover, many systems with high sustainability, as well as advanced systems for data handling and availability in place, resulted from national commitments to international monitoring or infrastructure programs, several of which are not necessarily particular to the Arctic.</p><p>Traditionally, terrestrial and atmospheric observation network assessments build on the network concept with a “comprehensive” level including all observations, a “baseline” level of an agreed subset of sustained observations, and a “reference” level, with observations adhering to specific calibrations and traceability criteria. Examples from atmospheric observations are the “comprehensive” global GCOS radiosounding network, the “baseline” GUAN (GCOS Upper Air Network) and “reference” GRUAN (GCOS Reference Upper Air Network) networks. With the lack of in-situ observations especially from the Arctic Ocean and the logistical difficulties to deploy new stations, it was concluded that this concept does not work well in the Arctic.</p><p>In summary, we recommend that:</p><ul><li>advancement in Arctic observing should be done in international global or regional programs with well-established routines and procedures, rather than to invest in new Arctic-specific programs</li> <li>investments in new instruments and techniques be done at already established sites, to benefit interdisciplinary studies and optimize infrastructure costs</li> <li>more observations be based on ships of opportunity and that a subset of ocean, sea-ice and atmosphere observations always be made on all research expeditions, regardless of their scientific aim</li> <li>the funding structures for science expeditions is reviewed to maintain, and preferably increase, the number of expeditions and to safeguard funding for appropriate data handling and storage</li> <li>observing-network concept for the atmosphere over the Arctic Ocean is revised, so that coupled reanalyses represent the “comprehensive level”, satellite observations complemented with available in-situ data is the “baseline level”, while scientific expeditions is the “reference level”. This requires substantial improvements in reanalysis, better numerical models and data assimilation, better satellite observations and improved data handling and accessibility for scientific expeditions.</li> </ul>

scholarly journals Modelling stock–recruitment relationships to examine stock management policies

2007 ◽  
Vol 64 (5) ◽  
pp. 870-877 ◽  
Author(s):  
A. Kimoto ◽  
T. Mouri ◽  
T. Matsuishi
Keyword(s):  
Prediction Error ◽  
Management Strategies ◽  
Fish Stock ◽  
Data Sets ◽  
Stock Management ◽  
Spawning Stock ◽  
Stock Recruitment ◽  
Management Policies ◽  
Leave One Out ◽  
High Recruitment

Abstract Kimoto, A., Mouri, T., and Matsuishi, T. 2007. Modelling stock–recruitment relationships to examine stock management policies. – ICES Journal of Marine Science, 64: 870–877. Simulation studies are used widely for fish stock management. In such studies, forecasting future recruitment, which can vary greatly between years, has become an essential part of evaluating management strategies. We propose a new forecasting algorithm to predict recruitment for short- or medium-term stochastic projections, using a stock–recruitment relationship. We address cases in which the spawning stock has dropped below previously observed levels, or in which predicted recruitment is situated close to the maximum observed level. The relative prediction error of seven existing algorithms was compared with that of the new model using leave-one-out cross-validation for 61 data sets from ICES, the Japanese Fisheries Agency, and PICES. The new algorithm had the smallest prediction error for 49 of the data sets, but was slightly biased by the precautionary treatment of predictions of high recruitment.

scholarly journals Seasonal calcium carbonate undersaturation in shelf waters of the Western Arctic Ocean; how biological processes exacerbate the impact of ocean acidification

2012 ◽  
Vol 9 (10) ◽  
pp. 14255-14290 ◽  
Author(s):  
N. R. Bates ◽  
M. I. Orchowska ◽  
R. Garley ◽  
J. T. Mathis
Keyword(s):  
Calcium Carbonate ◽  
Ocean Acidification ◽  
Arctic Ocean ◽  
The Arctic ◽  
Biological Processes ◽  
Subsurface Waters ◽  
Bottom Waters ◽  
Western Arctic ◽  
The Impact ◽  
Surface And Subsurface Waters

Abstract. The Arctic Ocean accounts for only 4% of the global ocean area but it contributes significantly to the global carbon cycle. Recent observations of seawater carbonate chemistry in shelf waters of the Western Arctic from 2009 to 2011 indicate that extensive areas of the benthos are exposed to bottom waters that are seasonally undersaturated with respect to calcium carbonate (CaCO3) minerals, particularly aragonite. Our observations indicate seasonal reduction of saturation states (Ω) for calcite (Ωcalcite) and aragonite (Ωaragonite) in the subsurface in the Western Arctic by as much as 0.9 and 0.6, respectively. Such data indicates that bottom waters of the Western Arctic shelves are already potentially corrosive for biogenic and sedimentary CaCO3 for several months each year. Seasonal changes in Ω are imparted by a variety of factors such as phytoplankton photosynthesis, respiration/remineralization of organic matter and air-sea gas exchange of CO2 – combined these processes either increase or enhance Ω in surface and subsurface waters, respectively. These seasonal physical and biological processes also act to mitigate or enhance the impact of Anthropocene ocean acidification (OA) on Ω in surface and subsurface waters, respectively. Future monitoring of the Western Arctic shelves is warranted to assess the present and future impact on Ω values from ocean acidification and seasonal biological/physical processes on Arctic marine ecosystems.

scholarly journals Intercomparison of Salinity Products in the Beaufort Gyre and Arctic Ocean

2021 ◽  
Vol 14 (1) ◽  
pp. 71
Author(s):  
Sarah B. Hall ◽  
Bulusu Subrahmanyam ◽  
James H. Morison
Keyword(s):  
Soil Moisture ◽  
Arctic Ocean ◽  
Satellite Observations ◽  
Sea Surface ◽  
Sea Surface Salinity ◽  
The Arctic ◽  
Surface Salinity ◽  
Beaufort Gyre ◽  
The Arctic Ocean

Salinity is the primary determinant of the Arctic Ocean’s density structure. Freshwater accumulation and distribution in the Arctic Ocean have varied significantly in recent decades and certainly in the Beaufort Gyre (BG). In this study, we analyze salinity variations in the BG region between 2012 and 2017. We use in situ salinity observations from the Seasonal Ice Zone Reconnaissance Surveys (SIZRS), CTD casts from the Beaufort Gyre Exploration Project (BGP), and the EN4 data to validate and compare with satellite observations from Soil Moisture Active Passive (SMAP), Soil Moisture and Ocean Salinity (SMOS), and Aquarius Optimally Interpolated Sea Surface Salinity (OISSS), and Arctic Ocean models: ECCO, MIZMAS, HYCOM, ORAS5, and GLORYS12. Overall, satellite observations are restricted to ice-free regions in the BG area, and models tend to overestimate sea surface salinity (SSS). Freshwater Content (FWC), an important component of the BG, is computed for EN4 and most models. ORAS5 provides the strongest positive SSS correlation coefficient (0.612) and lowest bias to in situ observations compared to the other products. ORAS5 subsurface salinity and FWC compare well with the EN4 data. Discrepancies between models and SIZRS data are highest in GLORYS12 and ECCO. These comparisons identify dissimilarities between salinity products and extend challenges to observations applicable to other areas of the Arctic Ocean.

scholarly journals Monitoring and assessment of ocean acidification in the Arctic Ocean-A scoping paper

2010 ◽  
Author(s):  
Lisa L. Robbins ◽  
Kimberly K. Yates ◽  
Richard Feely ◽  
Victoria Fabry
Keyword(s):  
Ocean Acidification ◽  
Arctic Ocean ◽  
The Arctic ◽  
The Arctic Ocean

scholarly journals Decorrelation scales for Arctic Ocean Hydrography. Part I: Amerasian Basin

2017 ◽  
Author(s):  
Hiroshi Sumata ◽  
Frank Kauker ◽  
Michael Karcher ◽  
Benjamin Rabe ◽  
Mary-Louise Timmermans ◽  
...  
Keyword(s):  
Data Assimilation ◽  
Arctic Ocean ◽  
Autocorrelation Function ◽  
Gaussian Function ◽  
The Arctic ◽  
Depth Range ◽  
Space And Time ◽  
Amerasian Basin ◽  
Decorrelation Scale

Abstract. Abstract. Any use of observational data for data assimilation requires adequate information of their representativeness in space and time. This is particularly important for sparse, non-synoptic data, which comprise the bulk of oceanic in-situ observations in the Arctic. To quantify spatial and temporal scales of temperature and salinity variations, we estimate the autocorrelation function and associated decorrelation scales for the Amerasian Basin of the Arctic Ocean. For this purpose, we compile historical measurements from 1980 to 2015. Assuming spatial and temporal homogeneity of the decorrelation scale in the basin interior (abyssal plain area), we calculate autocorrelations as a function of spatial distance and temporal lag. The examination of the functional form of autocorrelation in each depth range reveals that the autocorrelation is well described by a Gaussian function in space and time. We derive decorrelation scales of 150~200 km in space and 100~300 days in time. These scales are directly applicable to quantify the representation error, which is essential for use of ocean in-situ measurements in data assimilation. We also describe how the estimated autocorrelation function and decorrelation scale should be applied for cost function calculation in a data assimilation system.

scholarly journals Macroalgae contribute to nested mosaics of pH variability in a subarctic fjord

2015 ◽  
Vol 12 (16) ◽  
pp. 4895-4911 ◽  
Author(s):  
D. Krause-Jensen ◽  
C. M. Duarte ◽  
I. E. Hendriks ◽  
L. Meire ◽  
M. E. Blicher ◽  
...  
Keyword(s):  
Ocean Acidification ◽  
Arctic Ocean ◽  
Boundary Layers ◽  
Total Alkalinity ◽  
The Arctic ◽  
Kelp Forests ◽  
Coastal Habitats ◽  
Saturation State ◽  
The Arctic Ocean ◽  
Diffusive Boundary

Abstract. The Arctic Ocean is considered the most vulnerable ecosystem to ocean acidification, and large-scale assessments of pH and the saturation state for aragonite (Ωarag) have led to the notion that the Arctic Ocean is already close to a corrosive state. In high-latitude coastal waters the regulation of pH and Ωarag is, however, far more complex than offshore because increased biological activity and input of glacial meltwater affect pH. Effects of ocean acidification on calcifiers and non-calcifying phototrophs occupying coastal habitats cannot be derived from extrapolation of current and forecasted offshore conditions, but they require an understanding of the regimes of pH and Ωarag in their coastal habitats. To increase knowledge of the natural variability in pH in the Arctic coastal zone and specifically to test the influence of benthic vegetated habitats, we quantified pH variability in a Greenland fjord in a nested-scale approach. A sensor array logging pH, O2, PAR, temperature and salinity was applied on spatial scales ranging from kilometre scale across the horizontal extension of the fjord; to 100 m scale vertically in the fjord, 10–100 m scale between subtidal habitats with and without kelp forests and between vegetated tidal pools and adjacent vegetated shores; and to centimetre to metre scale within kelp forests and millimetre scale across diffusive boundary layers of macrophyte tissue. In addition, we assessed the temporal variability in pH on diurnal and seasonal scales. Based on pH measurements combined with point samples of total alkalinity, dissolved inorganic carbon and relationships to salinity, we also estimated variability in Ωarag. Results show variability in pH and Ωarag of up to 0.2–0.3 units at several scales, i.e. along the horizontal and vertical extension of the fjord, between seasons and on a diel basis in benthic habitats and within 1 m3 of kelp forest. Vegetated intertidal pools exhibited extreme diel pH variability of > 1.5 units and macrophyte diffusive boundary layers a pH range of up to 0.8 units. Overall, pelagic and benthic metabolism was an important driver of pH and Ωarag producing mosaics of variability from low levels in the dark to peak levels at high irradiance generally appearing favourable for calcification. We suggest that productive coastal environments may form niches of high pH in a future acidified Arctic Ocean.

Some Icelandic Perspectives on the Agreement to Prevent Unregulated High Seas Fisheries in the Central Arctic Ocean

2021 ◽  
Vol 12 (1) ◽  
pp. 268-284
Author(s):  
Jóhann Sigurjónsson
Keyword(s):  
Arctic Ocean ◽  
The Arctic ◽  
Scientific Cooperation ◽  
Central Arctic Ocean ◽  
Fish Stocks ◽  
Management Measures ◽  
Interim Management ◽  
Ice Retreat ◽  
Sea Ice Retreat ◽  
High Seas

This paper reflects on several aspects of the Agreement to Prevent Unregulated High Seas Fisheries in the Central Arctic Ocean from the standpoint of Iceland, prior to, during and at the conclusion of the negotiations of the Agreement in late 2017. Particular reference is made to UNCLOS and coastal State interests, status of knowledge on the fish stocks and the importance of scientific cooperation which the Agreement facilitates. During the years 2008–2015, the so-called Arctic Five consulted on cooperation in Arctic matters including future management of fisheries in the central Arctic Ocean. These rather exclusive cooperative efforts were criticised by Iceland and other States that felt these matters were to be dealt with in a broader international context. It seems evident that Iceland’s desire to become a full participant in the process during the subsequent years was both based on legal arguments as well as fair and natural geopolitical reasons. Iceland became a participant in the negotiations in December 2015. The final version of the Agreement is a fully fledged platform for coordinating scientific research and it even allows for interim management measures until future regional management framework is in place. In essence, the Agreement can be taken as a regional fisheries management arrangement (RFMA), since most elements of relevance are incorporated in accordance with the 1995 UN Fish Stocks Agreement. The opening of the central Arctic Ocean for fishing is not likely to take place in the nearest future, although the development of sea ice retreat is currently faster than earlier anticipated. While the Agreement is today regarded as being historic due to its precautionary approach, future may prove that it was a timely arrangement in a fast-moving world with dramatic changes taking place in the Arctic Ocean.

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