11 results on '"M. Ardyna"'
Search Results
2. Green Edge ice camp campaigns: understanding the processes controlling the under-ice Arctic phytoplankton spring bloom
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P. Massicotte, R. Amiraux, M.-P. Amyot, P. Archambault, M. Ardyna, L. Arnaud, L. Artigue, C. Aubry, P. Ayotte, G. Bécu, S. Bélanger, R. Benner, H. C. Bittig, A. Bricaud, É. Brossier, F. Bruyant, L. Chauvaud, D. Christiansen-Stowe, H. Claustre, V. Cornet-Barthaux, P. Coupel, C. Cox, A. Delaforge, T. Dezutter, C. Dimier, F. Domine, F. Dufour, C. Dufresne, D. Dumont, J. Ehn, B. Else, J. Ferland, M.-H. Forget, L. Fortier, M. Galí, V. Galindo, M. Gallinari, N. Garcia, C. Gérikas Ribeiro, M. Gourdal, P. Gourvil, C. Goyens, P.-L. Grondin, P. Guillot, C. Guilmette, M.-N. Houssais, F. Joux, L. Lacour, T. Lacour, A. Lafond, J. Lagunas, C. Lalande, J. Laliberté, S. Lambert-Girard, J. Larivière, J. Lavaud, A. LeBaron, K. Leblanc, F. Le Gall, J. Legras, M. Lemire, M. Levasseur, E. Leymarie, A. Leynaert, A. Lopes dos Santos, A. Lourenço, D. Mah, C. Marec, D. Marie, N. Martin, C. Marty, S. Marty, G. Massé, A. Matsuoka, L. Matthes, B. Moriceau, P.-E. Muller, C.-J. Mundy, G. Neukermans, L. Oziel, C. Panagiotopoulos, J.-J. Pangrazi, G. Picard, M. Picheral, F. Pinczon du Sel, N. Pogorzelec, I. Probert, B. Quéguiner, P. Raimbault, J. Ras, E. Rehm, E. Reimer, J.-F. Rontani, S. Rysgaard, B. Saint-Béat, M. Sampei, J. Sansoulet, C. Schmechtig, S. Schmidt, R. Sempéré, C. Sévigny, Y. Shen, M. Tragin, J.-É. Tremblay, D. Vaulot, G. Verin, F. Vivier, A. Vladoiu, J. Whitehead, and M. Babin
- Subjects
Environmental sciences ,GE1-350 ,Geology ,QE1-996.5 - Abstract
The Green Edge initiative was developed to investigate the processes controlling the primary productivity and fate of organic matter produced during the Arctic phytoplankton spring bloom (PSB) and to determine its role in the ecosystem. Two field campaigns were conducted in 2015 and 2016 at an ice camp located on landfast sea ice southeast of Qikiqtarjuaq Island in Baffin Bay (67.4797∘ N, 63.7895∘ W). During both expeditions, a large suite of physical, chemical and biological variables was measured beneath a consolidated sea-ice cover from the surface to the bottom (at 360 m depth) to better understand the factors driving the PSB. Key variables, such as conservative temperature, absolute salinity, radiance, irradiance, nutrient concentrations, chlorophyll a concentration, bacteria, phytoplankton and zooplankton abundance and taxonomy, and carbon stocks and fluxes were routinely measured at the ice camp. Meteorological and snow-relevant variables were also monitored. Here, we present the results of a joint effort to tidy and standardize the collected datasets, which will facilitate their reuse in other Arctic studies. The dataset is available at https://doi.org/10.17882/59892 (Massicotte et al., 2019a).
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- 2020
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3. Parameterization of vertical chlorophyll a in the Arctic Ocean: impact of the subsurface chlorophyll maximum on regional, seasonal, and annual primary production estimates
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M. Ardyna, M. Babin, M. Gosselin, E. Devred, S. Bélanger, A. Matsuoka, and J.-É. Tremblay
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Ecology ,QH540-549.5 ,Life ,QH501-531 ,Geology ,QE1-996.5 - Abstract
Predicting water-column phytoplankton biomass from near-surface measurements is a common approach in biological oceanography, particularly since the advent of satellite remote sensing of ocean color (OC). In the Arctic Ocean, deep subsurface chlorophyll maxima (SCMs) that significantly contribute to primary production (PP) are often observed. These are neither detected by ocean color sensors nor accounted for in the primary production models applied to the Arctic Ocean. Here, we assemble a large database of pan-Arctic observations (i.e., 5206 stations) and develop an empirical model to estimate vertical chlorophyll a (Chl a) according to (1) the shelf–offshore gradient delimited by the 50 m isobath, (2) seasonal variability along pre-bloom, post-bloom, and winter periods, and (3) regional differences across ten sub-Arctic and Arctic seas. Our detailed analysis of the dataset shows that, for the pre-bloom and winter periods, as well as for high surface Chl a concentration (Chl asurf; 0.7–30 mg m−3) throughout the open water period, the Chl a maximum is mainly located at or near the surface. Deep SCMs occur chiefly during the post-bloom period when Chl asurf is low (0–0.5 mg m−3). By applying our empirical model to annual Chl asurf time series, instead of the conventional method assuming vertically homogenous Chl a, we produce novel pan-Arctic PP estimates and associated uncertainties. Our results show that vertical variations in Chl a have a limited impact on annual depth-integrated PP. Small overestimates found when SCMs are shallow (i.e., pre-bloom, post-bloom > 0.7 mg m−3, and the winter period) somehow compensate for the underestimates found when SCMs are deep (i.e., post-bloom < 0.5 mg m−3). SCMs are, however, important seasonal features with a substantial impact on depth-integrated PP estimates, especially when surface nitrate is exhausted in the Arctic Ocean and where highly stratified and oligotrophic conditions prevail.
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- 2013
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4. Springtime Export of Arctic Sea Ice Influences Phytoplankton Production in the Greenland Sea
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N. Mayot, P. A. Matrai, A. Arjona, S. Bélanger, C. Marchese, T. Jaegler, M. Ardyna, and M. Steele
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- 2020
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5. Seafloor primary production in a changing Arctic Ocean.
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Attard K, Singh RK, Gattuso JP, Filbee-Dexter K, Krause-Jensen D, Kühl M, Sejr MK, Archambault P, Babin M, Bélanger S, Berg P, Glud RN, Hancke K, Jänicke S, Qin J, Rysgaard S, Sørensen EB, Tachon F, Wenzhöfer F, and Ardyna M
- Subjects
- Ecosystem, Budgets, Carbon, Climate Change, Ice Cover, Phytoplankton, Microalgae, Seaweed
- Abstract
Phytoplankton and sea ice algae are traditionally considered to be the main primary producers in the Arctic Ocean. In this Perspective, we explore the importance of benthic primary producers (BPPs) encompassing microalgae, macroalgae, and seagrasses, which represent a poorly quantified source of Arctic marine primary production. Despite scarce observations, models predict that BPPs are widespread, colonizing ~3 million km
2 of the extensive Arctic coastal and shelf seas. Using a synthesis of published data and a novel model, we estimate that BPPs currently contribute ~77 Tg C y-1 of primary production to the Arctic, equivalent to ~20 to 35% of annual phytoplankton production. Macroalgae contribute ~43 Tg C y-1 , seagrasses contribute ~23 Tg C y-1 , and microalgae-dominated shelf habitats contribute ~11 to 16 Tg C y-1 . Since 2003, the Arctic seafloor area exposed to sunlight has increased by ~47,000 km2 y-1 , expanding the realm of BPPs in a warming Arctic. Increased macrophyte abundance and productivity is expected along Arctic coastlines with continued ocean warming and sea ice loss. However, microalgal benthic primary production has increased in only a few shelf regions despite substantial sea ice loss over the past 20 y, as higher solar irradiance in the ice-free ocean is counterbalanced by reduced water transparency. This suggests complex impacts of climate change on Arctic light availability and marine primary production. Despite significant knowledge gaps on Arctic BPPs, their widespread presence and obvious contribution to coastal and shelf ecosystem production call for further investigation and for their inclusion in Arctic ecosystem models and carbon budgets., Competing Interests: Competing interests statement:The authors declare no competing interest.- Published
- 2024
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6. Environmental vulnerability of the global ocean epipelagic plankton community interactome.
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Chaffron S, Delage E, Budinich M, Vintache D, Henry N, Nef C, Ardyna M, Zayed AA, Junger PC, Galand PE, Lovejoy C, Murray AE, Sarmento H, Acinas SG, Babin M, Iudicone D, Jaillon O, Karsenti E, Wincker P, Karp-Boss L, Sullivan MB, Bowler C, de Vargas C, and Eveillard D
- Abstract
Marine plankton form complex communities of interacting organisms at the base of the food web, which sustain oceanic biogeochemical cycles and help regulate climate. Although global surveys are starting to reveal ecological drivers underlying planktonic community structure and predicted climate change responses, it is unclear how community-scale species interactions will be affected by climate change. Here, we leveraged Tara Oceans sampling to infer a global ocean cross-domain plankton co-occurrence network-the community interactome-and used niche modeling to assess its vulnerabilities to environmental change. Globally, this revealed a plankton interactome self-organized latitudinally into marine biomes (Trades, Westerlies, Polar) and more connected poleward. Integrated niche modeling revealed biome-specific community interactome responses to environmental change and forecasted the most affected lineages for each community. These results provide baseline approaches to assess community structure and organismal interactions under climate scenarios while identifying plausible plankton bioindicators for ocean monitoring of climate change., (Copyright © 2021 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works. Distributed under a Creative Commons Attribution License 4.0 (CC BY).)
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- 2021
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7. Marine snow morphology illuminates the evolution of phytoplankton blooms and determines their subsequent vertical export.
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Trudnowska E, Lacour L, Ardyna M, Rogge A, Irisson JO, Waite AM, Babin M, and Stemmann L
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- Animals, Arctic Regions, Carbon Cycle, Ecosystem, Eutrophication, Food Chain, Oceans and Seas, Particle Size, Seawater chemistry, Spatio-Temporal Analysis, Zooplankton growth & development, Zooplankton metabolism, Geologic Sediments chemistry, Phytoplankton growth & development, Phytoplankton metabolism
- Abstract
The organic carbon produced in the ocean's surface by phytoplankton is either passed through the food web or exported to the ocean interior as marine snow. The rate and efficiency of such vertical export strongly depend on the size, structure and shape of individual particles, but apart from size, other morphological properties are still not quantitatively monitored. With the growing number of in situ imaging technologies, there is now a great possibility to analyze the morphology of individual marine snow. Thus, automated methods for their classification are urgently needed. Consequently, here we present a simple, objective categorization method of marine snow into a few ecologically meaningful functional morphotypes using field data from successive phases of the Arctic phytoplankton bloom. The proposed approach is a promising tool for future studies aiming to integrate the diversity, composition and morphology of marine snow into our understanding of the biological carbon pump.
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- 2021
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8. Hydrothermal vents trigger massive phytoplankton blooms in the Southern Ocean.
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Ardyna M, Lacour L, Sergi S, d'Ovidio F, Sallée JB, Rembauville M, Blain S, Tagliabue A, Schlitzer R, Jeandel C, Arrigo KR, and Claustre H
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- Antarctic Regions, Carbon Dioxide, Carbon Sequestration, Iron, Eutrophication, Hydrothermal Vents, Oceans and Seas, Phytoplankton
- Abstract
Hydrothermal activity is significant in regulating the dynamics of trace elements in the ocean. Biogeochemical models suggest that hydrothermal iron might play an important role in the iron-depleted Southern Ocean by enhancing the biological pump. However, the ability of this mechanism to affect large-scale biogeochemistry and the pathways by which hydrothermal iron reach the surface layer have not been observationally constrained. Here we present the first observational evidence of upwelled hydrothermally influenced deep waters stimulating massive phytoplankton blooms in the Southern Ocean. Captured by profiling floats, two blooms were observed in the vicinity of the Antarctic Circumpolar Current, downstream of active hydrothermal vents along the Southwest Indian Ridge. These hotspots of biological activity are supported by mixing of hydrothermally sourced iron stimulated by flow-topography interactions. Such findings reveal the important role of hydrothermal vents on surface biogeochemistry, potentially fueling local hotspot sinks for atmospheric CO
2 by enhancing the biological pump.- Published
- 2019
- Full Text
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9. Marine DNA Viral Macro- and Microdiversity from Pole to Pole.
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Gregory AC, Zayed AA, Conceição-Neto N, Temperton B, Bolduc B, Alberti A, Ardyna M, Arkhipova K, Carmichael M, Cruaud C, Dimier C, Domínguez-Huerta G, Ferland J, Kandels S, Liu Y, Marec C, Pesant S, Picheral M, Pisarev S, Poulain J, Tremblay JÉ, Vik D, Babin M, Bowler C, Culley AI, de Vargas C, Dutilh BE, Iudicone D, Karp-Boss L, Roux S, Sunagawa S, Wincker P, and Sullivan MB
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- Aquatic Organisms genetics, Biodiversity, DNA Viruses genetics, DNA, Viral genetics, Metagenome, Water Microbiology
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Microbes drive most ecosystems and are modulated by viruses that impact their lifespan, gene flow, and metabolic outputs. However, ecosystem-level impacts of viral community diversity remain difficult to assess due to classification issues and few reference genomes. Here, we establish an ∼12-fold expanded global ocean DNA virome dataset of 195,728 viral populations, now including the Arctic Ocean, and validate that these populations form discrete genotypic clusters. Meta-community analyses revealed five ecological zones throughout the global ocean, including two distinct Arctic regions. Across the zones, local and global patterns and drivers in viral community diversity were established for both macrodiversity (inter-population diversity) and microdiversity (intra-population genetic variation). These patterns sometimes, but not always, paralleled those from macro-organisms and revealed temperate and tropical surface waters and the Arctic as biodiversity hotspots and mechanistic hypotheses to explain them. Such further understanding of ocean viruses is critical for broader inclusion in ecosystem models., (Copyright © 2019 Elsevier Inc. All rights reserved.)
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- 2019
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10. Need for focus on microbial species following ice melt and changing freshwater regimes in a Janus Arctic Gateway.
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Joli N, Gosselin M, Ardyna M, Babin M, Onda DF, Tremblay JÉ, and Lovejoy C
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- Arctic Regions, Climate Change, Greenland, Phytoplankton genetics, Phytoplankton isolation & purification, Fresh Water microbiology, Seawater microbiology
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Oceanic gateways are sensitive to climate driven processes. By connecting oceans, they have a global influence on marine biological production and biogeochemical cycles. The furthest north of these gateways is Nares Strait at the top of the North Water between Greenland and Ellesmere Island (Canada). This gateway is globally beneficial, first by supporting high local mammal and bird populations and second with the outflow of phosphate-rich Arctic waters fueling the North Atlantic spring bloom. Both sides of the North Water are hydrologically distinct with counter currents that make this Arctic portal a Janus gateway, after Janus, the Roman god of duality. We examined oceanographic properties and differences in phytoplankton and other protist communities from the eastern and western sides of the North Water (latitude 76.5°N) and found that species differed markedly due to salinity stratification regimes and local hydrography. Typical Arctic communities were associated with south flowing currents along the Canadian side, while potentially noxious Pseudo-nitzschia spp. were dominant on the Greenland side and associated with greater surface freshening from ice melt. This susceptibility of the Greenland side to Pseudo-nitzschia spp. blooms suggest that monitoring species responses to climate mediated changes is needed.
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- 2018
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11. An assessment of phytoplankton primary productivity in the Arctic Ocean from satellite ocean color/in situ chlorophyll- a based models.
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Lee YJ, Matrai PA, Friedrichs MA, Saba VS, Antoine D, Ardyna M, Asanuma I, Babin M, Bélanger S, Benoît-Gagné M, Devred E, Fernández-Méndez M, Gentili B, Hirawake T, Kang SH, Kameda T, Katlein C, Lee SH, Lee Z, Mélin F, Scardi M, Smyth TJ, Tang S, Turpie KR, Waters KJ, and Westberry TK
- Abstract
We investigated 32 net primary productivity (NPP) models by assessing skills to reproduce integrated NPP in the Arctic Ocean. The models were provided with two sources each of surface chlorophyll- a concentration (chlorophyll), photosynthetically available radiation (PAR), sea surface temperature (SST), and mixed-layer depth (MLD). The models were most sensitive to uncertainties in surface chlorophyll, generally performing better with in situ chlorophyll than with satellite-derived values. They were much less sensitive to uncertainties in PAR, SST, and MLD, possibly due to relatively narrow ranges of input data and/or relatively little difference between input data sources. Regardless of type or complexity, most of the models were not able to fully reproduce the variability of in situ NPP, whereas some of them exhibited almost no bias (i.e., reproduced the mean of in situ NPP). The models performed relatively well in low-productivity seasons as well as in sea ice-covered/deep-water regions. Depth-resolved models correlated more with in situ NPP than other model types, but had a greater tendency to overestimate mean NPP whereas absorption-based models exhibited the lowest bias associated with weaker correlation. The models performed better when a subsurface chlorophyll- a maximum (SCM) was absent. As a group, the models overestimated mean NPP, however this was partly offset by some models underestimating NPP when a SCM was present. Our study suggests that NPP models need to be carefully tuned for the Arctic Ocean because most of the models performing relatively well were those that used Arctic-relevant parameters.
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- 2015
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