Sea ice biological communities and nutrient dynamics in the Canada Basin of the Arctic Ocean

Melnikov, I. A.; Kolosova, E. G.; Welch, H. E.; Житина, Л. С.

doi:10.1016/s0967-0637(02)00042-0

Cited by 140 publications

(105 citation statements)

References 26 publications

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“…In autumn, an increase in nutrient supply due to enhanced vertical mixing may trigger 3574 E. E. Popova et al: Control of primary production in the Arctic by nutrients and light a weaker phytoplankton bloom although observational evidence of ecosystem dynamics for this time of year do not exist. It has also been observed that an accumulation of plankton biomass can occur in the bottom 3-4 cm of the ice (Melnikov et al, 2002).…”

Section: Conceptual Models Of Arctic Ecosystemsmentioning

confidence: 95%

Control of primary production in the Arctic by nutrients and light: insights from a high resolution ocean general circulation model

et al. 2010

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Abstract. Until recently, the Arctic Basin was generally considered to be a low productivity area and was afforded little attention in global-or even basin-scale ecosystem modelling studies. Due to anthropogenic climate change however, the sea ice cover of the Arctic Ocean is undergoing an unexpectedly fast retreat, exposing increasingly large areas of the basin to sunlight. As indicated by existing Arctic phenomena such as ice-edge blooms, this decline in sea-ice is liable to encourage pronounced growth of phytoplankton in summer and poses pressing questions concerning the future of Arctic ecosystems. It thus provides a strong impetus to modelling of this region.The Arctic Ocean is an area where plankton productivity is heavily influenced by physical factors. As these factors are strongly responding to climate change, we analyse here the results from simulations of the 1/4 • resolution global ocean NEMO (Nucleus for European Modelling of the Ocean) model coupled with the MEDUSA (Model for Ecosystem Dynamics, carbon Utilisation, Sequestration and Acidification) biogeochemical model, with a particular focus on the Arctic basin. Simulated productivity is consistent with the limited observations for the Arctic, with significant production occurring both under the sea-ice and at the thermocline, locations that are difficult to sample in the field.Results also indicate that a substantial fraction of the variability in Arctic primary production can be explained by two key physical factors: (i) the maximum penetration of winter mixing, which determines the amount of nutrients available for summer primary production, and (ii) short-wave radiation at the ocean surface, which controls the magnitude of phytoplankton blooms. A strong empirical correlation was Correspondence to: E. E. Popova (ekp@noc.soton.ac.uk) found in the model output between primary production and these two factors, highlighting the importance of physical processes in the Arctic Ocean.

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Section: Conceptual Models Of Arctic Ecosystemsmentioning

confidence: 95%

Control of primary production in the Arctic by nutrients and light: insights from a high resolution ocean general circulation model

et al. 2010

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“…Thus, ice core sampling during ship-based campaigns is generally limited to <10 algal chl a biomass or NPP cores per ice station making it difficult to conduct spatial studies of sea ice algae (e.g., this study; Gosselin et al, 1997;Gradinger, 1999;Schünemann and Werner, 2005;Fernández-Méndez et al, 2015). Even during long term ship-based studies (e.g., Melnikov et al, 2002) ice core sampling was limited to a small number of cores for each sampling interval every 1-2 weeks.…”

Section: Chl a Biomassmentioning

confidence: 99%

Characterizing Spatial Variability of Ice Algal Chlorophyll a and Net Primary Production between Sea Ice Habitats Using Horizontal Profiling Platforms

et al. 2017

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Assessing the role of sea ice algal biomass and primary production for polar ecosystems remains challenging due to the strong spatio-temporal variability of sea ice algae. Therefore, the spatial representativeness of sea ice algal biomass and primary production sampling remains a key issue in large-scale models and climate change predictions of polar ecosystems. To address this issue, we presented two novel approaches to up-scale ice algal chl a biomass and net primary production (NPP) estimates based on profiles covering distances of 100 to 1,000 s of meters. This was accomplished by combining ice core-based methods with horizontal under-ice spectral radiation profiling conducted in the central Arctic Ocean during summer 2012. We conducted a multi-scale comparison of ice-core based ice algal chl a biomass with two profiling platforms: a remotely operated vehicle and surface and under ice trawl (SUIT). NPP estimates were compared between ice cores and remotely operated vehicle surveys. Our results showed that ice core-based estimates of ice algal chl a biomass and NPP do not representatively capture the spatial variability compared to the remotely operated vehicle-based estimates, implying considerable uncertainties for pan-Arctic estimates based on ice core observations alone. Grouping sea ice cores based on region or ice type improved the representativeness. With only a small sample size, however, a high risk of obtaining non-representative estimates remains. Sea ice algal chl a biomass estimates based on the dominant ice class alone showed a better agreement between ice core and remotely operated vehicle estimates. Grouping ice core measurements yielded no improvement in NPP estimates, highlighting the importance of accounting for the spatial variability of both the chl a biomass and bottom-ice light in order to get representative estimates. Profile-based measurements of ice algae chl a biomass identified sea ice ridges as an underappreciated component of the Arctic ecosystem Lange et al.Ice-Algal Biomass and NPP because chl a biomass was significantly greater in this unique habitat. Sea ice ridges are not easily captured with ice coring methods and thus require more attention in future studies. Based on our results, we provide recommendations for designing an efficient and effective sea ice algal sampling program for the summer season.

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“…In contrast, inflow, spraying, and flooding from surface sea water could likely increase nutrient availability and thus stimulate productivity. The algal community in the melt ponds can consist of fresh water species, such as Chlamydomonas nivalis and Meringosphaera mediterranea (Melnikov et al 2002), as well as marine species, which are mainly dominated by diatom genera such as Navicula sp., Nitzchia sp., Thalassiosira sp., Chaetoceros sp. and Melosira arctica (Bursa 1963;Melnikov et al 2002;Fernández-Méndez et al 2014).…”

Section: Introductionmentioning

confidence: 99%

Nutrient availability limits biological production in Arctic sea ice melt ponds

et al. 2017

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addition compared with their respective controls, with the largest increase occurring in the enclosures. Separate additions of PO 4 3− and NO 3 − in the enclosures led to intermediate increases in productivity, suggesting co-limitation of nutrients. Bacterial production and the biovolume of ciliates, which were the dominant grazers, were positively correlated with primary production, showing a tight coupling between primary production and both microbial activity and ciliate grazing. To our knowledge, this study is the first to ascertain nutrient limitation in melt ponds. We also document that the addition of nutrients, although at relative high concentrations, can stimulate biological productivity at several trophic levels. Given the projected increase in first-year ice, increased melt pond coverage during the Arctic spring and potential additional nutrient supply from, e.g. terrestrial sources imply that biological activity of melt ponds may become increasingly important for the sympagic carbon cycling in the future Arctic.

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Sea ice biological communities and nutrient dynamics in the Canada Basin of the Arctic Ocean

Cited by 140 publications

References 26 publications

Control of primary production in the Arctic by nutrients and light: insights from a high resolution ocean general circulation model

Control of primary production in the Arctic by nutrients and light: insights from a high resolution ocean general circulation model

Characterizing Spatial Variability of Ice Algal Chlorophyll a and Net Primary Production between Sea Ice Habitats Using Horizontal Profiling Platforms

Nutrient availability limits biological production in Arctic sea ice melt ponds

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