Sea-ice arches structure Arctic primary production hotspots at the Last Ice Area gateway

Sea-ice arches structure Arctic primary production hotspots at the Last Ice Area gateway | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Sea-ice arches structure Arctic primary production hotspots at the Last Ice Area gateway Foucaut Tachon, Karen Nieto, Philippe Massicotte, Philippe Archambault, and 5 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7827911/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted You are reading this latest preprint version Abstract Nares Strait, located at the southern edge of the Last Ice Area, is a significant ecological zone where seasonal sea-ice arches influence regional ice dynamics, air–sea exchange and ecosystem productivity. By modulating ice export, stratification, and light penetration, these arches determine the timing, location, and intensity of phytoplankton blooms. Based on two decades (2003–2023) of satellite sea-ice observations and depth-resolved primary production estimates, we found a pronounced increase in production, particularly in northern regions where earlier ice retreat and longer open-water seasons promoted phytoplankton growth. Two recurrent productivity hotspots were identified. The first is a variable northern hotspot in Kennedy Channel, which only emerged under specific ice-arch configurations and bathymetric conditions, highlighting the structural role of arches in regulating bloom dynamics. In contrast, the second hotspot, located in the North Water Polynya ( Pikialasorsuaq ), sustained consistently high production across all sea ice conditions. This stability, in contrast to previously reported declines, highlights the North Water Polynya as an ecologically and culturally significant marine area. Our findings identify sea-ice arches as ecosystem constitutive features within the Last Ice Area and emphasize the critical role of the North Water Polynya for biodiversity conservation and subsistence of Indigenous under continued Arctic warming. Biological sciences/Ecology/Ecological modelling Earth and environmental sciences/Ocean sciences/Marine biology Earth and environmental sciences/Climate sciences/Ocean sciences/Marine biology Figures Figure 1 Figure 2 Figure 3 Figure 4 Key Points Seasonal sea-ice arches act as fundamental ecosystem constitutive features, shaping bloom dynamics at the southern gateway of the Last Ice Area (LIA). Two recurrent productive hotspots are identified in Nares Strait (NS), with contrasting sensitivity to ice-arch regimes and topography. Primary production (PP) in the North Water Polynya (NOW, Pikialasorsuaq ) remains high and stable despite shifting sea-ice dynamics. Earlier ice retreat has increased light availability, driving a long-term rise in Arctic PP. Introduction Arctic sea ice is undergoing rapid decline in both thickness and extent, driven by accelerated polar warming (Stroeve et al., 2018; Ardyna & Arrigo, 2020 ; Heuzé et al., 2024). These changes fundamentally alter the balance between light availability and nutrient supply, two key drivers of primary production (PP) in polar marine ecosystems. Thinner and more mobile ice favors earlier phytoplankton blooms, sometimes even beneath the ice cover (Arrigo et al., 2014 ; Ardyna & Arrigo, 2020 ). Conversely, enhanced stratification resulting from freshwater inputs and surface warming inhibits vertical nutrient replenishment, ultimately limiting bloom magnitude (Tremblay & Gagnon, 2009 ; Slagstad et al., 2015 ). Whether Arctic ecosystems will transition toward higher or lower productivity under continued warming remains an open question and is likely to vary regionally. This uncertainty is particularly pronounced in poorly studied outflow shelf systems of the Arctic Ocean, where changes in sea-ice dynamics propagate downstream and influence local biogeochemical conditions (Carmack & Wassmann, 2006 ). Nares Strait (NS), a narrow (~ 30 km) channel between Canada’s Ellesmere Island and Greenland, is one of the five major gateways through which sea ice is exported from the Arctic Ocean (Kwok, 2005 , see Fig. 1 a). Unlike the broader Fram Strait, ice export through NS is dominated by multi-year ice (MYI) (Kwok et al., 2010 ), and is strongly regulated by the seasonal formation of two ice arches in Robeson Channel and Smith Sound (Vincent, 2019 ; Kirillov et al., 2021 ; Moore et al., 2023 ). These ice arches are large consolidated packs of ice laterally anchored on the coast of narrow passages where the circulation (here southward) stabilizes them. These arches can block ice transport for extended periods, effectively shielding the Last Ice Area (LIA), identified as the region expected to lose its perennial ice cover last, from the seasonally ice-free waters of northern Baffin Bay. It has been hypothesized that ice arches act as ecosystem constitutive features, influencing phytoplankton bloom dynamics at the southern boundary of the LIA by modulating ice export, stratification, and light penetration (Marchese et al., 2017 ; Moore et al., 2021 ). However, this ecological role has yet to be demonstrated directly, leaving a critical gap in our understanding of how physical processes shape marine productivity in this region. The North Water Polynya (NOW, Pikialasorsuaq ) has long been recognized as one of the most productive polynyas in the Arctic, supporting large phytoplankton blooms and sustaining high biomass (Tremblay et al., 2002 ). However, recent studies indicate ecological shifts, including a decline in PP (Bélanger et al., 2013 ) and a reduced contribution of diatoms to the phytoplankton community (Blais et al., 2017 ). Several mechanisms have been proposed to explain these trends: increased stratification limiting vertical nutrient replenishment, enhanced ice export reducing light availability, and upstream nutrient drawdown associated with earlier ice retreat and longer open-water periods in NS and farther north (Carmack et al., 2006 ; Carmack and Wassman, 2006; Tremblay and Gagnon, 2009 ). These changes have significant implications for regional ecosystems and the ecosystem services they support, from maintaining one of the Arctic’s richest food webs to sustaining the cultural and subsistence practices of Inuit communities. These concerns have generated strong interest in better understanding the future trajectory of NOW, both in terms of Arctic marine ecosystems functioning and the livelihoods of the communities that depend on them. Contrary to previous observations of decline, our results show that the annual PP in the NOW has remained relatively stable over the past two decades, despite notable changes in sea-ice dynamics. To reconcile this apparent paradox, we integrate two decades (2003–2023) of satellite-derived sea-ice data with depth-resolved PP estimates. This approach enables us to identify persistent productivity hotspots, assess their contrasting sensitivities to ice-arch dynamics and bathymetric settings, and, for the first time, demonstrate the role of sea-ice arches as ecosystem constitutive features at the southern gateway of the Last Ice Area. Data and Methods 2.1. Satellite data The Santa Barbara DISORT Atmospheric Radiative Transfer model (SBDART; Ricchiazi et al., 1998) was used following Bélanger et al. ( 2013 ) for the generation of look-up tables (LUTs, courtesy of Simon Bélanger) in order to retrieve the incident spectral downwelling irradiance Ed (0 + , λ, t) at the sea surface (0 + ), with a 5 nm spectral resolution (λ) at 3 h timesteps (t). The model inputs were solar zenith angle (θ s ) and values of, cloud fraction (CF) and total ozone concentration (O₃) from MODIS (MYD08, https://ladsweb.modaps.eosdis.nasa.gov ). Surface chlorophyll a concentration (Chl, mg m⁻³) was derived from remote sensing reflectance using the Arctic-optimized version of the semi-analytical Garver–Siegel–Maritorena algorithm (GSM) from Li et al. ( 2023 ). We used the Level-3 binned daily reflectance (Rrs) from the Ocean Colour Climate Change Initiative sinusoidal version 6 product (OC-CCI v6.0, https://climate.esa.int/en/projects/ocean-colour/ ; Sathyendranath et al., 2023). As this study is based on Bélanger et al.’s ( 2013 ) PP model, which in turn was based on MODIS spectral bands, the OC-CCI v6.0 Rrs (MERIS bands) have been adjusted in this upgraded version. This involved shifting the 490, 560, and 665 nm Rrs to 488, 555, and 667 nm, respectively, without significant impacts on inherent optical property (IOP) results (Lee et al., 2009 ). A linear interpolation between 510 and 560 nm bands have been applied to generate Rrs(531). 2.2. TAKUVIK-UQAR primary production Model Primary Production (PP) was estimated with a depth- and wavelength-resolved model upgraded from Bélanger et al. ( 2013 ), as applied in Li (2024) and maintained by Takuvik & UQAR (2025). The upgraded version incorporates improved spatial resolution of atmospheric inputs, and a resolution of the vertical Chl profile following Ardyna et al. ( 2013 ), which captures the typical subsurface chlorophyll maximum (SCM) found in Arctic, and of IOP profiles. The carbon fixation rate was calculated daily with the photosynthesis–irradiance model of Platt et al. (1980): where Chl(z) is chlorophyll a concentration at depth z (mg m − 3 ), P B max is the light-saturated Chl-normalized carbon fixation rate (mgC.mgChl-1.h-1) set to 2 based on field measurements in Arctic waters (Harrison and Platt, 1986 ; Huot et al., 2013 ), Ek(z) is the saturation irradiance modelled here as a function of PUR (z,t) (derived from the LUTs; in µmol photon m − 2 s − 1 ), and PUR(z) is the photosynthetically usable radiation (µmol photon m − 2 s − 1 ) is estimated as a function of PUR following Huot et al. ( 2013 ) calculated for each optical depth at a 3 h time interval following Arrigo et al. ( 1998 ). The calculated PP, integrated to a maximum depth of 100 m constrained by local bathymetry, was linearly interpolated in time with a maximum 8-day sliding window. Pixels with out-of-range values for the phytoplankton Chl-specific absorption coefficient, spectral decay constant for coloured detrital material absorption (aCDM) and power-law exponent for the particulate backscattering spectra from GSM were classified invalid and filtered out following Li (2023). Years 2004 and 2014 were excluded due to cloudiness covering more than 50% of the ice-free pixels during both spring and summer (Fig. S1 in the online resource). 2.3 Sea-ice concentration and arches Daily sea-ice concentration (SIC) at 12.5 km resolution for the period 2003–2023 was obtained from SSM/I data (CERSAT/Ifremer; Ezraty et al., 2007 ) using the ARTIST algorithm (Kaleschke et al., 2001 ). Values outside the physical range (0–100%) were removed (Andersen et al., 2007 ), and a 15% SIC threshold was applied to minimize contamination in ocean-colour retrievals near the ice edge (Bélanger et al., 2007 ; Marchese et al., 2017 ). Freeze-up and break-up were defined as periods in autumn and summer, of at least 21 consecutive days with SIC rising above or decreasing below 35%, respectively (Marchese et al., 2017 , see S6). Ice-arch configurations were classified following Vincent ( 2019 ) and Moore et al. ( 2023 ) into three scenarios: a southern arch, when the arch consolidated in Smith Sound; a northern arch, when it formed in Robeson Channel; and no arch, when neither structure developed during winter. These scenarios capture the primary modes of interannual variability in ice dynamics that modulate sea-ice export through Nares Strait. 2.4 Identification of productivity hotspots The k -means clustering method (Hartigan & Wong, 1979), which has been previously applied in the Amundsen Sea (Feng et al., 2022 ), was applied on the maximum primary production value per pixel subset. This unsupervised classification algorithm partitions pixels into groups based on the similarity of their feature values, here defined as the maximum annual primary production across the time series. Because pixels are assigned according to their distance from mean-based centroids, outliers can strongly influence the clustering. To avoid abrupt pixel-to-pixel variations, we first applied a 7 × 7 median filter to the climatological PP maps to smooth the data and remove outliers before clustering. We used the Sentinels Application Platform (SNAP) k -means cluster analysis algorithm and the number of clusters from 2 to 11. The default parameters for the random seed ( rs = 31415) and number of iterations ( i = 30) were used to group pixels with similar production. Based on our observations, we selected k = 6 for the clustering, as this configuration clearly highlights the two highly productive areas consistently observed across the time series, with a cluster mean primary production of 61.2 ± 5.0 gC m − 2 y − 1 . Using k = 5 produces a very similar outcome, while increasing the number of clusters beyond 6 does not alter the representation of the two productive regions and offers little additional insight. A more exhaustive analysis of the clustering procedure, including sensitivity tests for k , is provided in the Supplementary Information. Results and Discussion 3.1 Ice-arch dynamics drives primary production variability Recent pan-Arctic studies report a 30–50% increase in net primary production (PP) over recent decades, primarily attributed to longer open-water seasons and improved light availability as sea ice retreats (Arrigo & van Dijken, 2015 ; Ardyna & Arrigo, 2020 ; Lewis et al., 2020 ). Yet this apparent coherence conceals strong regional contrasts, where multiple environmental drivers shape PP. Nutrient replenishment from Pacific and Atlantic inflows (Oziel et al., 2019 ; Tremblay et al., 2015 ), lateral exchanges across shelves (Carmack & Wassmann, 2006 ), and upwelling along shelf breaks (Ardyna et al., 2017 ; Michel et al., 2015 ) all contribute to the spatial mosaic of productivity across the Arctic. Outflow shelves such as NS remain especially underexplored, despite their central role in exporting sea ice, freshwater, and biogeochemical properties from the Last Ice Area (LIA) into Baffin Bay. Our analysis of the NS–Baffin Bay system between 2003 and 2023 highlights a marked spatial heterogeneity in annual PP, spanning more than two orders of magnitude (Fig. 1 b). In the LIA area, values remain below 0.1 gC m⁻² y⁻¹, whereas recurrently ice-free waters in the NOW sustain rates exceeding 60 gC m⁻² y⁻¹ (Fig. 1 a, 2 a). This variability underscores the tight coupling between PP, sea-ice retreat (see S6), and season length, consistent with pan-Arctic trends (Arrigo & van Dijken, 2015 ; Ardyna & Arrigo, 2020 ; Lewis et al., 2020 ), but here accentuated by local constraints (Fig. 2 a). The juxtaposition of perennial ice cover to the north with the highly productive NOW downstream amplifies environmental gradients, locking northern sectors into light-limited regimes while southern regions transition rapidly toward nutrient limitation. Beyond ice dynamics, lateral forcing from outlet glaciers and the complex bathymetry of Kane Basin and Kennedy Channel further modulate circulation and stratification, shaping nutrient availability and reinforcing sharp contrasts in PP across this outflow shelf system (Michel et al., 2006 ; Münchow et al., 2007 ). Both the climatological mean map (Fig. 1 b) and the Hovmöller diagrams (Fig. 2 a) highlights two recurrent hotspots of elevated PP. The Southern Hotspot (SH), located near Smith Sound at the entrance of the NOW, sustains the highest mean productivity (61.7 ± 0.2 gC m⁻² y⁻¹; see Fig. 1 a, b). This persistence suggests favorable local conditions, including recurring thin-ice zones and stratification that reliably trigger bloom initiation (Barber et al., 2001 ). In contrast, the Northern Hotspot (NH) in Kennedy Channel near Cape Jackson exhibits lower average productivity (38.5 ± 0.2 gC m⁻² y⁻¹; see Fig. 1 a, 1 b) but pronounced interannual variability. This northern feature is tightly linked to local bathymetric constraints and the recurrent formation of heat polynyas (Kirillov et al., 2022 ), which intermittently generate windows of favorable light and nutrient conditions for bloom development. Together, these two regions exemplify how the interplay of sea ice, stratification, and bathymetry structure PP at the gateway of the LIA. Temporal Hovmöller diagrams (Fig. 2 a) further reveal the regulatory role of ice arches on hotspot dynamics. When the northern arch consolidates in Robeson Channel, downstream ice flux is suppressed, leading to prolonged open-water conditions in Kennedy Channel and promoting the development of the NH, as observed in 2009, 2010, 2017, and 2019. Conversely, the collapse of the southern arch in Smith Sound triggers earlier and more extensive openings in Kane Basin, producing anomalously warm conditions such as the + 5°C sea-surface temperature (SST) anomaly documented in 2009 (Vincent, 2013 ). In years with a stable southern arch, the NH is absent or strongly suppressed due to persistent sea ice cover, while the SH maintains relatively stable PP. These patterns confirm that ice arches act not only as mechanical barriers to ice floes but also regulate bloom timing, intensity, and spatial distribution across the system. Annual PP correlates significantly with the number of open-water pixels during the productive season but not with the timing of break-up, here defined as opening day (April–October; Kendall’s τ = 0.54, p = 0.004; Fig. 2 b). Yet the absence of a long-term trend in PP (Kendall’s τ = 0.135, p = 0.441, see S4) may suggest that productivity trajectories at the LIA gateway are not determined by monotonic sea-ice retreat alone, but by the shifting interplay of ice-arch stability, regional hydrography, and bathymetric setting. 3.2 Stability of the North Water Polynya productivity NOW has long been recognized as the most productive polynya of the Northern Hemisphere, sustaining intense phytoplankton blooms and supporting one of the richest Arctic food webs (Barber et al., 2001 ; Tremblay et al., 2002 ). Due to its ecological and cultural significance, it has been the focus of numerous studies examining phytoplankton dynamics and ecosystem responses (e.g., Bergeron & Tremblay, 2014 ; Blais et al., 2017 ; Marchese et al., 2017 ; Olivier et al., 2020 ; Moore et al., 2023 ). Several of these analyses reported either a decline in net community production (NCP) or primary production (PP) (Bergeron & Tremblay, 2014 ; Blais et al., 2017 ), or a reduction in bloom magnitude despite earlier and longer bloom seasons (Marchese et al., 2017 ). Unlike studies relying solely on surface chlorophyll from satellite ocean colour, our approach integrates depth-resolved PP, explicitly accounting for the subsurface chlorophyll maximum (SCM), which recurrently contributes to total production in Arctic systems (Ardyna et al., 2013 ). This methodological refinement partly explains the contrast with earlier findings of decline. This discrepancy may reflect a sampling bias, particularly the underestimation of PP occurring deeper in the water column. Another study by Blais et al. ( 2017 ) based their conclusions on in situ PP measurements made during CCGS Amundsen expeditions between 2006 and 2011, but their dataset excluded the productive year 2009, when PP reached unusually high values (Fig. 2 b, S3). Similarly, Bergeron & Tremblay ( 2014 ) used a nutrient drawdown time series (1997–2011) that pointed to decreasing NCP. When considering the longer 2003–2023 satellite-derived record, however, annual PP in the NOW shows stability, with a slight positive trend of about + 0.1 TgC per decade (Fig. S3). This stability is consistent with recent observations of rising nutrient concentrations in Arctic waters (Barut, in prep.), which may help sustain production despite ongoing sea-ice change. Moore et al. ( 2023 ) further demonstrated that ice-arch scenarios (southern, northern, or none) exert little influence on ice opening and biomass within the NOW itself. However, their findings were based on surface chlorophyll averages and not on integrated PP. Our results confirm the broader stability of the system: PP remains consistently high, regardless of arch configuration, with average values of 62.1 ± 0.2 gC m⁻² y⁻¹, 63.8 ± 0.2, and 60.6 ± 0.2 for no-arch years, northern-arch, and southern-arch, respectively (Fig. 3 a, 3 b, 3 c). This stability contrasts with the dependence of Kennedy Channel productivity to arch dynamics and highlights the NOW as a resilient system within the LIA. Although the NOW as a whole generally shows stable PP over time (Fig. 3 d, Table 1 ), spatial heterogeneity exists. An area of recurrent elevated production is observed in its northern sector, near Cape Alexander (Fig. 1 a), consistent with local characteristics with a possible island effect features and recurring thin-ice conditions. This localized signal complements the broader picture of system-wide stability and points to the coexistence of resilient background production with finer-scale variability in bloom timing and amplitude. Taken together, these findings emphasize that while the NOW is shaped by the larger-scale dynamics of Nares Strait, its capacity to sustain consistently high PP across shifting ice regimes makes it an ecological and cultural stronghold within the Arctic (Fig. 3 d, S3). Table 1 Annual PP of the Total Area, the Northern Hotspot and the Southern Hotspot (in TgC.y − 1 ) and their contributions to the total PP (in %). Year Southern Hotspot (TgC.y-1) Northern Hotspot (TgC.y-1) Total Area (TgC.y-1) 2003 1.083(41%) 0.007(0%) 2.620 2005 0.958(47%) 0.062(3%) 2.047 2006 1.116(44%) 0.023(1%) 2.520 2007 0.921(35%) 0.230(9%) 2.624 2008 0.923(41%) 0.060(3%) 2.267 2009 1.432(30%) 0.428(9%) 4.752 2010 0.753(33%) 0.175(8%) 2.274 2011 0.910(42%) 0.101(5%) 2.158 2012 1.212(43%) 0.035(1%) 2.826 2013 1.238(47%) 0.011(0%) 2.646 2015 1.029(41%) 0.004(0%) 2.499 2016 1.492(37%) 0.090(2%) 4.033 2017 1.017(31%) 0.319(10%) 3.291 2018 1.043(43%) 0.006(0%) 2.413 2019 0.884(27%) 0.219(7%) 3.259 2020 1.361(36%) 0.163(4%) 3.746 2021 0.993(35%) 0.084(3%) 2.836 2022 0.799(35%) 0.102(5%) 2.265 2023 0.849(37%) 0.022(1%) 2.296 3.3 Ice-arch control of productivity hotspots and bloom phenology While the NOW exhibits remarkable stability in its annual PP (Fig. 3 d, S3), finer-scale patterns reveal strong sensitivities to ice-arch dynamics farther upstream in Kane Basin and Kennedy Channel (see Fig. 1 a). Clustering analysis distinguished two contrasting regions: the SH, observed consistently across all years with a stable PP, and the NH, which occurs intermittently depending on ice-arch configuration. The presence or absence of arches influences the timing and intensity of NH blooms (Marchese et al., 2017 ). When the southern arch fails to consolidate, open-water conditions extend northward by early spring, leading to earlier ice breakup in Kane Basin and Kennedy Channel. This favors the initiation of the NH bloom as early as May, advancing the season by nearly two months compared to years when the southern arch persists (Vincent, 2019 ; Moore et al., 2023 ). A consolidated northern arch in Robeson Channel reduces the downstream flux of MYI and also contributes to prolonge open-water conditions downstream and further enhance NH productivity. In this configuration, annual PP in the NH can increase up to 74.4 ± 0.2 gC m − 2 y − 1 , nearly triple that observed in years without arches (Fig. 4 a-b). By contrast, the SH demonstrates greater robustness. Even in years when nutrient drawdown might be expected upstream, local conditions such as recurring thin-ice zones, stable stratification, and predictable light penetration (Barber et al., 2001 ) support relatively consistent bloom initiation and magnitude. One might expect intensified and earlier NH blooms to trigger cascading effects downstream, with nutrient depletion and advective transport reducing PP in the SH. Yet our results indicate otherwise: despite high SIC variability upstream, SH productivity remains confined within a narrow range across ice-arch scenarios, in sharp contrast to the high SIC interannual variability of the NH (Fig. 4 c–d). This stability suggests that local conditions damp the SH against upstream forcing, decoupling its dynamics from northern variability. Years of high productivity (i.e. 2007, 2009, 2016, 2017, 2019, 2020) were found to be linked to distinct environmental forcing patterns. For instance, the 2009 season, characterized by a long-lived northern arch and the early collapse of the southern arch, produced anomalously warm conditions (+ 5°C SST anomaly; Vincent, 2013 ) and sustained open water that favored prolonged NH blooms. In contrast, the 2017 season combined thin ice and early collapse with unusual atmospheric forcing linked to the breakdown of the Beaufort High (Moore et al., 2018 ), leading to exceptional bloom conditions in the NH. Beyond affecting the magnitude of PP, ice-arch dynamics also alter the phenology of NH blooms by shifting their timing, duration, and seasonal intensity, with potential consequences for food-web coupling and carbon fluxes. Taken together, these results confirm that sea-ice arches act both as passive mechanical barriers and ecosystem constitutive features that determine not only where hotspots emerge, but also when and how long they persist. While the SH near the NOW remains consistently productive, the NH in Kennedy Channel is more transient and opportunistic, with its presence, magnitude, and phenology depending on the shifting interplay of ice-arch stability and episodic environmental forcing. 3.4 Ice-arch dynamics and ecosystem resilience at the Last Ice Area gateway Our findings reveal that sea-ice arches are more than passive physical barriers: they act as ecosystem constitutive features that regulate the timing, intensity, and spatial distribution of PP at the southern gateway of the LIA. By shaping the duration of open-water seasons and the advection of MYI, arch stability drives the emergence of contrasting hotspots. The NH is a dynamic feature, with its phenology and magnitude varying according to arch persistence and bathymetric setting. By contrast, the SH, embedded in the NOW, demonstrates remarkable stability, sustaining stable PP across ice-arch scenarios thanks to recurrent thin-ice zones and reliable stratification. These results illustrate how the interplay of ice dynamics structures the productivity of an underexplored Arctic outflow shelf system. Despite earlier predictions of declining productivity in the NOW, our model suggests that annual PP has remained relatively stable, supporting one of the Arctic’s richest food webs and sustaining a cultural way of life for Inuit communities. Yet this stability is not guaranteed: accelerating MYI loss and the potential destabilization of ice arches could undermine the system’s long-term stability. Our results emphasize the need to recognize NOW not only as a productivity hotspot, but as a keystone ecosystem whose biodiversity and cultural importance make it central to the functioning of the rapidly changing Arctic and whose protection should be prioritized through marine protected area initiatives and Indigenous stewardship. Declarations 4. Acknowledgments The primary production model used in this study was developed thanks to support from the Canada Excellence Research Chair on Remote Sensing of Canada's new Arctic Frontier and from the Sentinel North project. The Refuge-Arctic project was conducted using the Canadian research icebreaker CCGS Amundsen with the support of the Amundsen Science program funded by the Canada Foundation for Innovation (CFI) Major Science Initiatives (MSI) Fund. We wish to thank the officers and crew of the CCGS Amundsen and the entire TAKUVIK laboratory team for planning the field work, and all other scientists and technicians involved in the Refuge-Arctic campaigns for their contribution to field work and data collection. The project was conducted under the scientific coordination of Centre national de la recherche scientifique CNRS/Université Laval Takuvik Joint International Laboratory (IRL3376). We also thank Québec-Océan and the Polar Continental Shelf Program for their in-kind contribution in terms of polar logistics and scientific equipment. The Refuge-Arctic project is funded by the following French and Canadian programs and agencies: Amundsen Science, ArcticNet, BNP Paribas Foundation, Centre National d’études spatiales (CNES) and the CNES-TOSCA “Alg-O-Nord", Centre National de la Recherche Scientifique (CNRS), Crown-Indigenous Relations and Northern Affairs Canada (RCAANC), European Research Council (ERC), Flotte Océanographique française (FOF), Fonds de recherche du Québec - Nature et technologies (FRQNT), Institut Nordique du Québec (INQ), Institut français de recherche pour l’exploitation de la mer (IFREMER), Institut Polaire français Paul-Émile Victor (IPEV), Les Enveloppes Fluides et l’Environnement (LEFE), Mission pour les Initiatives Transverses et Interdisciplinaires (MITI), Natural Sciences and Engineering Research Council of Canada (NSERC), Fisheries and Oceans Canada (DFO), Transforming Climate Action (TCA), Sentinelle Nord and Université Laval. We also wish to thank the Denmark's Independent Research Fund (Grant No. 2064-00021B) and the Polar Ocean Mitigation Potential project (Horizon Europe, Grant No. 101136875). 5. Data Availability The original datasets used to reproduce the findings of this study are publicly available on Zenodo for the primary production at https://doi.org/10.5281/zenodo.14715624. Sea-ice concentration data (12.5 km resolution grids of sea ice concentration from the 85 Ghz channel of SSM/I) are available from IFREMER FTP servers at ftp://ftp.ifremer.fr/ifremer/cersat/products/gridded/psi-concentration/data/arctic. 6. Computer code The analysis of the model output was done using the open-source software Python. Post-processing scripts will be provided upon request to the corresponding author. References Andersen, S., Tonboe, R., Kaleschke, L., Heygster, G. & Pedersen, L. T. Intercomparison of passive microwave sea-ice concentration retrievals over the high-concentration Arctic sea ice. J. Geophys. Res. 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Remote Sens. 12, 2712 (2020). Wang, M. & Overland, J. E. A sea-ice-free summer Arctic within 30 years? Geophys. Res. Lett. 36, L07502 (2009). Additional Declarations There is NO Competing Interest. Supplementary Files TachonNatureCEEsm.docx Supplementary information for Cite Share Download PDF Status: Under Review Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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1","display":"","copyAsset":false,"role":"figure","size":1527516,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eBathymetry of the Nares Strait – Baffin Bay system \u003c/strong\u003e(a). Abbreviations represent locations along the system: Lincoln Sea (LS); Robeson Channel (RC); Kennedy Channel (KC); Kane Basin (KB); Smith Sound (SS); \u0026nbsp;Cape Alexander (CA); North Water Polynya (NOW); Baffin Bay (BB). \u003cstrong\u003eAnnual climatology (2003–2023) of primary production across the Nares Strait system, extending from the Lincoln Sea to the North Water Polynya.\u003c/strong\u003e (b) Latitudinal grid used for the Hovmöller plots (see Figure 2).\u003c/p\u003e","description":"","filename":"image1.png","url":"https://assets-eu.researchsquare.com/files/rs-7827911/v1/84be3c1ad7d5a415968c9dc2.png"},{"id":94583727,"identity":"d18714a5-9e1a-488e-81c4-1c7feab3d7e3","added_by":"auto","created_at":"2025-10-28 18:14:27","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":3178262,"visible":true,"origin":"","legend":"\u003cp\u003e(a) Monthly means of net primary production (PP, top panel) and sea-ice concentration (SIC, bottom panel) along latitude grid (Fig. 1b). (b) Relationship between annual PP and the number of open-water pixels cumulated during the growing season (April–October), with marker colour indicating the Opening Day (OD) when the SIC \u0026lt; 0.15 defined using Kahru (2016) methodology.\u003c/p\u003e","description":"","filename":"image2.png","url":"https://assets-eu.researchsquare.com/files/rs-7827911/v1/78c823d3c6ae6af1fd02951d.png"},{"id":94583611,"identity":"1e575525-ceb4-4331-b54a-ecca2e106795","added_by":"auto","created_at":"2025-10-28 18:14:15","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":1385242,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eClimatological annual PP maps for years with contrasting ice-arch scenarios.\u003c/strong\u003e (a) Open years with no ice-arch formation in the Nares Strait–Baffin Bay system (2007, 2022). (b) Years with a persistent northern arch in Robeson Channel (2009, 2010, 2017, 2019). (c) Closed years with a persistent southern arch in Smith Sound (2003, 2005, 2006, 2008, 2011, 2012, 2013, 2015, 2016, 2018, 2020, 2021, 2023). White dashed polygons delineate the northern and southern hotspots identified using k-means clustering. The contribution of each hotspot to annual PP is shown (light blue = NH; light pink = SH). Ice-arch scenarios are classified following Moore (2023) and Vincent (2019).\u003c/p\u003e","description":"","filename":"image3.png","url":"https://assets-eu.researchsquare.com/files/rs-7827911/v1/b5ca0389f90ef195ac44a3a5.png"},{"id":94583299,"identity":"eb847f6c-92a9-493d-9827-dad4ece2a8d1","added_by":"auto","created_at":"2025-10-28 18:13:57","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":1758382,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eDaily time series of PP (a, b) and SIC (c, d) in the northern hotspot (NH) and southern hotspot (SH).\u003c/strong\u003e Years with a consolidated southern ice arch are shown in blue, and years without are shown in red. Bold lines represent the mean for each scenario.\u003c/p\u003e","description":"","filename":"image4.png","url":"https://assets-eu.researchsquare.com/files/rs-7827911/v1/6410710dd990e61fe0525391.png"},{"id":94598449,"identity":"ab3b345e-ad5f-44f7-8681-ba3cf7de76a7","added_by":"auto","created_at":"2025-10-28 18:53:18","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":8187229,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7827911/v1/0b0bf452-ebe7-4ff9-97c7-e4366c7445ac.pdf"},{"id":94583858,"identity":"04d1afc3-76ea-40bf-a5fb-cbc2be45649f","added_by":"auto","created_at":"2025-10-28 18:14:43","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":19519751,"visible":true,"origin":"","legend":"Supplementary information for","description":"","filename":"TachonNatureCEEsm.docx","url":"https://assets-eu.researchsquare.com/files/rs-7827911/v1/af4cf5e67f0035b6e4981e52.docx"}],"financialInterests":"There is \u003cb\u003eNO\u003c/b\u003e Competing Interest.","formattedTitle":"Sea-ice arches structure Arctic primary production hotspots at the Last Ice Area gateway","fulltext":[{"header":"Key Points","content":"\u003cul\u003e\n \u003cli\u003eSeasonal sea-ice arches act as fundamental ecosystem constitutive features, shaping bloom dynamics at the southern gateway of the Last Ice Area (LIA).\u003c/li\u003e\n \u003cli\u003eTwo recurrent productive hotspots are identified in Nares Strait (NS), with contrasting sensitivity to ice-arch regimes and topography.\u003c/li\u003e\n \u003cli\u003ePrimary production (PP) in the North Water Polynya (NOW, \u003cem\u003ePikialasorsuaq\u003c/em\u003e) remains high and stable despite shifting sea-ice dynamics.\u003c/li\u003e\n \u003cli\u003eEarlier ice retreat has increased light availability, driving a long-term rise in Arctic PP.\u003c/li\u003e\n\u003c/ul\u003e"},{"header":"Introduction","content":"\u003cp\u003eArctic sea ice is undergoing rapid decline in both thickness and extent, driven by accelerated polar warming (Stroeve et al., 2018; Ardyna \u0026amp; Arrigo, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Heuz\u0026eacute; et al., 2024). These changes fundamentally alter the balance between light availability and nutrient supply, two key drivers of primary production (PP) in polar marine ecosystems. Thinner and more mobile ice favors earlier phytoplankton blooms, sometimes even beneath the ice cover (Arrigo et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Ardyna \u0026amp; Arrigo, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Conversely, enhanced stratification resulting from freshwater inputs and surface warming inhibits vertical nutrient replenishment, ultimately limiting bloom magnitude (Tremblay \u0026amp; Gagnon, \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e2009\u003c/span\u003e; Slagstad et al., \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). Whether Arctic ecosystems will transition toward higher or lower productivity under continued warming remains an open question and is likely to vary regionally. This uncertainty is particularly pronounced in poorly studied outflow shelf systems of the Arctic Ocean, where changes in sea-ice dynamics propagate downstream and influence local biogeochemical conditions (Carmack \u0026amp; Wassmann, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2006\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eNares Strait (NS), a narrow (~\u0026thinsp;30 km) channel between Canada\u0026rsquo;s Ellesmere Island and Greenland, is one of the five major gateways through which sea ice is exported from the Arctic Ocean (Kwok, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2005\u003c/span\u003e, see Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ea). Unlike the broader Fram Strait, ice export through NS is dominated by multi-year ice (MYI) (Kwok et al., \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2010\u003c/span\u003e), and is strongly regulated by the seasonal formation of two ice arches in Robeson Channel and Smith Sound (Vincent, \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Kirillov et al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Moore et al., \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). These ice arches are large consolidated packs of ice laterally anchored on the coast of narrow passages where the circulation (here southward) stabilizes them. These arches can block ice transport for extended periods, effectively shielding the Last Ice Area (LIA), identified as the region expected to lose its perennial ice cover last, from the seasonally ice-free waters of northern Baffin Bay. It has been hypothesized that ice arches act as ecosystem constitutive features, influencing phytoplankton bloom dynamics at the southern boundary of the LIA by modulating ice export, stratification, and light penetration (Marchese et al., \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Moore et al., \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). However, this ecological role has yet to be demonstrated directly, leaving a critical gap in our understanding of how physical processes shape marine productivity in this region.\u003c/p\u003e\u003cp\u003eThe North Water Polynya (NOW, \u003cem\u003ePikialasorsuaq\u003c/em\u003e) has long been recognized as one of the most productive polynyas in the Arctic, supporting large phytoplankton blooms and sustaining high biomass (Tremblay et al., \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e2002\u003c/span\u003e). However, recent studies indicate ecological shifts, including a decline in PP (B\u0026eacute;langer et al., \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2013\u003c/span\u003e) and a reduced contribution of diatoms to the phytoplankton community (Blais et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Several mechanisms have been proposed to explain these trends: increased stratification limiting vertical nutrient replenishment, enhanced ice export reducing light availability, and upstream nutrient drawdown associated with earlier ice retreat and longer open-water periods in NS and farther north (Carmack et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2006\u003c/span\u003e; Carmack and Wassman, 2006; Tremblay and Gagnon, \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e2009\u003c/span\u003e). These changes have significant implications for regional ecosystems and the ecosystem services they support, from maintaining one of the Arctic\u0026rsquo;s richest food webs to sustaining the cultural and subsistence practices of Inuit communities. These concerns have generated strong interest in better understanding the future trajectory of NOW, both in terms of Arctic marine ecosystems functioning and the livelihoods of the communities that depend on them.\u003c/p\u003e\u003cp\u003eContrary to previous observations of decline, our results show that the annual PP in the NOW has remained relatively stable over the past two decades, despite notable changes in sea-ice dynamics. To reconcile this apparent paradox, we integrate two decades (2003\u0026ndash;2023) of satellite-derived sea-ice data with depth-resolved PP estimates. This approach enables us to identify persistent productivity hotspots, assess their contrasting sensitivities to ice-arch dynamics and bathymetric settings, and, for the first time, demonstrate the role of sea-ice arches as ecosystem constitutive features at the southern gateway of the Last Ice Area.\u003c/p\u003e"},{"header":"Data and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003e2.1. Satellite data\u003c/h2\u003e\u003cp\u003eThe Santa Barbara DISORT Atmospheric Radiative Transfer model (SBDART; Ricchiazi et al., 1998) was used following B\u0026eacute;langer et al. (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2013\u003c/span\u003e) for the generation of look-up tables (LUTs, courtesy of Simon B\u0026eacute;langer) in order to retrieve the incident spectral downwelling irradiance Ed (0\u003csup\u003e+\u003c/sup\u003e, λ, t) at the sea surface (0\u003csup\u003e+\u003c/sup\u003e), with a 5 nm spectral resolution (λ) at 3 h timesteps (t). The model inputs were solar zenith angle (θ\u003csub\u003es\u003c/sub\u003e) and values of, cloud fraction (CF) and total ozone concentration (O₃) from MODIS (MYD08, \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://ladsweb.modaps.eosdis.nasa.gov\u003c/span\u003e\u003cspan address=\"https://ladsweb.modaps.eosdis.nasa.gov\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). Surface chlorophyll \u003cem\u003ea\u003c/em\u003e concentration (Chl, mg m⁻\u0026sup3;) was derived from remote sensing reflectance using the Arctic-optimized version of the semi-analytical Garver\u0026ndash;Siegel\u0026ndash;Maritorena algorithm (GSM) from Li et al. (\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eWe used the Level-3 binned daily reflectance (Rrs) from the Ocean Colour Climate Change Initiative sinusoidal version 6 product (OC-CCI v6.0, \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://climate.esa.int/en/projects/ocean-colour/\u003c/span\u003e\u003cspan address=\"https://climate.esa.int/en/projects/ocean-colour/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e; Sathyendranath et al., 2023). As this study is based on B\u0026eacute;langer et al.\u0026rsquo;s (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2013\u003c/span\u003e) PP model, which in turn was based on MODIS spectral bands, the OC-CCI v6.0 Rrs (MERIS bands) have been adjusted in this upgraded version. This involved shifting the 490, 560, and 665 nm Rrs to 488, 555, and 667 nm, respectively, without significant impacts on inherent optical property (IOP) results (Lee et al., \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2009\u003c/span\u003e). A linear interpolation between 510 and 560 nm bands have been applied to generate Rrs(531).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\u003ch2\u003e2.2. TAKUVIK-UQAR primary production Model\u003c/h2\u003e\u003cp\u003ePrimary Production (PP) was estimated with a depth- and wavelength-resolved model upgraded from B\u0026eacute;langer et al. (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2013\u003c/span\u003e), as applied in Li (2024) and maintained by Takuvik \u0026amp; UQAR (2025). The upgraded version incorporates improved spatial resolution of atmospheric inputs, and a resolution of the vertical Chl profile following Ardyna et al. (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2013\u003c/span\u003e), which captures the typical subsurface chlorophyll maximum (SCM) found in Arctic, and of IOP profiles. The carbon fixation rate was calculated daily with the photosynthesis\u0026ndash;irradiance model of Platt et al. (1980):\u003c/p\u003e\u003cp\u003ewhere Chl(z) is chlorophyll a concentration at depth z (mg m\u003csup\u003e\u0026minus;\u0026thinsp;3\u003c/sup\u003e), P\u003csub\u003eB\u003c/sub\u003e\u003csup\u003emax\u003c/sup\u003e is the light-saturated Chl-normalized carbon fixation rate (mgC.mgChl-1.h-1) set to 2 based on field measurements in Arctic waters (Harrison and Platt, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e1986\u003c/span\u003e; Huot et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2013\u003c/span\u003e), Ek(z) is the saturation irradiance modelled here as a function of PUR (z,t) (derived from the LUTs; in \u0026micro;mol photon m\u003csup\u003e\u0026minus;\u0026thinsp;2\u003c/sup\u003e s\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e), and PUR(z) is the photosynthetically usable radiation (\u0026micro;mol photon m\u003csup\u003e\u0026minus;\u0026thinsp;2\u003c/sup\u003e s\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) is estimated as a function of PUR following Huot et al. (\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2013\u003c/span\u003e) calculated for each optical depth at a 3 h time interval following Arrigo et al. (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e1998\u003c/span\u003e). The calculated PP, integrated to a maximum depth of 100 m constrained by local bathymetry, was linearly interpolated in time with a maximum 8-day sliding window. Pixels with out-of-range values for the phytoplankton Chl-specific absorption coefficient, spectral decay constant for coloured detrital material absorption (aCDM) and power-law exponent for the particulate backscattering spectra from GSM were classified invalid and filtered out following Li (2023). Years 2004 and 2014 were excluded due to cloudiness covering more than 50% of the ice-free pixels during both spring and summer (Fig. \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e in the online resource).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\u003ch2\u003e2.3 \u003cb\u003eSea-ice concentration and arches\u003c/b\u003e\u003c/h2\u003e\u003cp\u003eDaily sea-ice concentration (SIC) at 12.5 km resolution for the period 2003\u0026ndash;2023 was obtained from SSM/I data (CERSAT/Ifremer; Ezraty et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2007\u003c/span\u003e) using the ARTIST algorithm (Kaleschke et al., \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2001\u003c/span\u003e). Values outside the physical range (0\u0026ndash;100%) were removed (Andersen et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2007\u003c/span\u003e), and a 15% SIC threshold was applied to minimize contamination in ocean-colour retrievals near the ice edge (B\u0026eacute;langer et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; Marchese et al., \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Freeze-up and break-up were defined as periods in autumn and summer, of at least 21 consecutive days with SIC rising above or decreasing below 35%, respectively (Marchese et al., \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2017\u003c/span\u003e, see S6). Ice-arch configurations were classified following Vincent (\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) and Moore et al. (\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) into three scenarios: a southern arch, when the arch consolidated in Smith Sound; a northern arch, when it formed in Robeson Channel; and no arch, when neither structure developed during winter. These scenarios capture the primary modes of interannual variability in ice dynamics that modulate sea-ice export through Nares Strait.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\u003ch2\u003e2.4 \u003cb\u003eIdentification of productivity hotspots\u003c/b\u003e\u003c/h2\u003e\u003cp\u003eThe \u003cem\u003ek\u003c/em\u003e-means clustering method (Hartigan \u0026amp; Wong, 1979), which has been previously applied in the Amundsen Sea (Feng et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), was applied on the maximum primary production value per pixel subset. This unsupervised classification algorithm partitions pixels into groups based on the similarity of their feature values, here defined as the maximum annual primary production across the time series. Because pixels are assigned according to their distance from mean-based centroids, outliers can strongly influence the clustering. To avoid abrupt pixel-to-pixel variations, we first applied a 7 \u0026times; 7 median filter to the climatological PP maps to smooth the data and remove outliers before clustering.\u003c/p\u003e\u003cp\u003eWe used the Sentinels Application Platform (SNAP) \u003cem\u003ek\u003c/em\u003e-means cluster analysis algorithm and the number of clusters from 2 to 11. The default parameters for the random seed (\u003cem\u003ers\u003c/em\u003e\u0026thinsp;=\u0026thinsp;31415) and number of iterations (\u003cem\u003ei\u003c/em\u003e\u0026thinsp;=\u0026thinsp;30) were used to group pixels with similar production. Based on our observations, we selected \u003cem\u003ek\u003c/em\u003e\u0026thinsp;=\u0026thinsp;6 for the clustering, as this configuration clearly highlights the two highly productive areas consistently observed across the time series, with a cluster mean primary production of 61.2\u0026thinsp;\u0026plusmn;\u0026thinsp;5.0 gC m\u003csup\u003e\u0026minus;\u0026thinsp;2\u003c/sup\u003e y\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e. Using \u003cem\u003ek\u003c/em\u003e\u0026thinsp;=\u0026thinsp;5 produces a very similar outcome, while increasing the number of clusters beyond 6 does not alter the representation of the two productive regions and offers little additional insight. A more exhaustive analysis of the clustering procedure, including sensitivity tests for \u003cem\u003ek\u003c/em\u003e, is provided in the Supplementary Information.\u003c/p\u003e\u003c/div\u003e"},{"header":"Results and Discussion","content":"\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003e3.1 \u003cb\u003eIce-arch dynamics drives primary production variability\u003c/b\u003e\u003c/h2\u003e\u003cp\u003eRecent pan-Arctic studies report a 30\u0026ndash;50% increase in net primary production (PP) over recent decades, primarily attributed to longer open-water seasons and improved light availability as sea ice retreats (Arrigo \u0026amp; van Dijken, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Ardyna \u0026amp; Arrigo, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Lewis et al., \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Yet this apparent coherence conceals strong regional contrasts, where multiple environmental drivers shape PP. Nutrient replenishment from Pacific and Atlantic inflows (Oziel et al., \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Tremblay et al., \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e2015\u003c/span\u003e), lateral exchanges across shelves (Carmack \u0026amp; Wassmann, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2006\u003c/span\u003e), and upwelling along shelf breaks (Ardyna et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Michel et al., \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2015\u003c/span\u003e) all contribute to the spatial mosaic of productivity across the Arctic. Outflow shelves such as NS remain especially underexplored, despite their central role in exporting sea ice, freshwater, and biogeochemical properties from the Last Ice Area (LIA) into Baffin Bay.\u003c/p\u003e\u003cp\u003eOur analysis of the NS\u0026ndash;Baffin Bay system between 2003 and 2023 highlights a marked spatial heterogeneity in annual PP, spanning more than two orders of magnitude (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eb). In the LIA area, values remain below 0.1 gC m⁻\u0026sup2; y⁻\u0026sup1;, whereas recurrently ice-free waters in the NOW sustain rates exceeding 60 gC m⁻\u0026sup2; y⁻\u0026sup1; (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ea, \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ea). This variability underscores the tight coupling between PP, sea-ice retreat (see S6), and season length, consistent with pan-Arctic trends (Arrigo \u0026amp; van Dijken, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Ardyna \u0026amp; Arrigo, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Lewis et al., \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), but here accentuated by local constraints (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ea). The juxtaposition of perennial ice cover to the north with the highly productive NOW downstream amplifies environmental gradients, locking northern sectors into light-limited regimes while southern regions transition rapidly toward nutrient limitation. Beyond ice dynamics, lateral forcing from outlet glaciers and the complex bathymetry of Kane Basin and Kennedy Channel further modulate circulation and stratification, shaping nutrient availability and reinforcing sharp contrasts in PP across this outflow shelf system (Michel et al., \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2006\u003c/span\u003e; M\u0026uuml;nchow et al., \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2007\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eBoth the climatological mean map (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eb) and the Hovm\u0026ouml;ller diagrams (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ea) highlights two recurrent hotspots of elevated PP. The Southern Hotspot (SH), located near Smith Sound at the entrance of the NOW, sustains the highest mean productivity (61.7\u0026thinsp;\u0026plusmn;\u0026thinsp;0.2 gC m⁻\u0026sup2; y⁻\u0026sup1;; see Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ea, b). This persistence suggests favorable local conditions, including recurring thin-ice zones and stratification that reliably trigger bloom initiation (Barber et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2001\u003c/span\u003e). In contrast, the Northern Hotspot (NH) in Kennedy Channel near Cape Jackson exhibits lower average productivity (38.5\u0026thinsp;\u0026plusmn;\u0026thinsp;0.2 gC m⁻\u0026sup2; y⁻\u0026sup1;; see Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ea, \u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eb) but pronounced interannual variability. This northern feature is tightly linked to local bathymetric constraints and the recurrent formation of heat polynyas (Kirillov et al., \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), which intermittently generate windows of favorable light and nutrient conditions for bloom development. Together, these two regions exemplify how the interplay of sea ice, stratification, and bathymetry structure PP at the gateway of the LIA.\u003c/p\u003e\u003cp\u003eTemporal Hovm\u0026ouml;ller diagrams (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ea) further reveal the regulatory role of ice arches on hotspot dynamics. When the northern arch consolidates in Robeson Channel, downstream ice flux is suppressed, leading to prolonged open-water conditions in Kennedy Channel and promoting the development of the NH, as observed in 2009, 2010, 2017, and 2019. Conversely, the collapse of the southern arch in Smith Sound triggers earlier and more extensive openings in Kane Basin, producing anomalously warm conditions such as the +\u0026thinsp;5\u0026deg;C sea-surface temperature (SST) anomaly documented in 2009 (Vincent, \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). In years with a stable southern arch, the NH is absent or strongly suppressed due to persistent sea ice cover, while the SH maintains relatively stable PP. These patterns confirm that ice arches act not only as mechanical barriers to ice floes but also regulate bloom timing, intensity, and spatial distribution across the system. Annual PP correlates significantly with the number of open-water pixels during the productive season but not with the timing of break-up, here defined as opening day (April\u0026ndash;October; Kendall\u0026rsquo;s τ\u0026thinsp;=\u0026thinsp;0.54, p\u0026thinsp;=\u0026thinsp;0.004; Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eb). Yet the absence of a long-term trend in PP (Kendall\u0026rsquo;s τ\u0026thinsp;=\u0026thinsp;0.135, p\u0026thinsp;=\u0026thinsp;0.441, see S4) may suggest that productivity trajectories at the LIA gateway are not determined by monotonic sea-ice retreat alone, but by the shifting interplay of ice-arch stability, regional hydrography, and bathymetric setting.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e\u003ch2\u003e3.2 \u003cb\u003eStability of the North Water Polynya productivity\u003c/b\u003e\u003c/h2\u003e\u003cp\u003eNOW has long been recognized as the most productive polynya of the Northern Hemisphere, sustaining intense phytoplankton blooms and supporting one of the richest Arctic food webs (Barber et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2001\u003c/span\u003e; Tremblay et al., \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e2002\u003c/span\u003e). Due to its ecological and cultural significance, it has been the focus of numerous studies examining phytoplankton dynamics and ecosystem responses (e.g., Bergeron \u0026amp; Tremblay, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Blais et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Marchese et al., \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Olivier et al., \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Moore et al., \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Several of these analyses reported either a decline in net community production (NCP) or primary production (PP) (Bergeron \u0026amp; Tremblay, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Blais et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2017\u003c/span\u003e), or a reduction in bloom magnitude despite earlier and longer bloom seasons (Marchese et al., \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2017\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eUnlike studies relying solely on surface chlorophyll from satellite ocean colour, our approach integrates depth-resolved PP, explicitly accounting for the subsurface chlorophyll maximum (SCM), which recurrently contributes to total production in Arctic systems (Ardyna et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). This methodological refinement partly explains the contrast with earlier findings of decline. This discrepancy may reflect a sampling bias, particularly the underestimation of PP occurring deeper in the water column. Another study by Blais et al. (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2017\u003c/span\u003e) based their conclusions on in situ PP measurements made during CCGS Amundsen expeditions between 2006 and 2011, but their dataset excluded the productive year 2009, when PP reached unusually high values (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eb, S3). Similarly, Bergeron \u0026amp; Tremblay (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2014\u003c/span\u003e) used a nutrient drawdown time series (1997\u0026ndash;2011) that pointed to decreasing NCP. When considering the longer 2003\u0026ndash;2023 satellite-derived record, however, annual PP in the NOW shows stability, with a slight positive trend of about\u0026thinsp;+\u0026thinsp;0.1 TgC per decade (Fig. S3). This stability is consistent with recent observations of rising nutrient concentrations in Arctic waters (Barut, in prep.), which may help sustain production despite ongoing sea-ice change.\u003c/p\u003e\u003cp\u003eMoore et al. (\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) further demonstrated that ice-arch scenarios (southern, northern, or none) exert little influence on ice opening and biomass within the NOW itself. However, their findings were based on surface chlorophyll averages and not on integrated PP. Our results confirm the broader stability of the system: PP remains consistently high, regardless of arch configuration, with average values of 62.1\u0026thinsp;\u0026plusmn;\u0026thinsp;0.2 gC m⁻\u0026sup2; y⁻\u0026sup1;, 63.8\u0026thinsp;\u0026plusmn;\u0026thinsp;0.2, and 60.6\u0026thinsp;\u0026plusmn;\u0026thinsp;0.2 for no-arch years, northern-arch, and southern-arch, respectively (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ea, \u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eb, \u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ec). This stability contrasts with the dependence of Kennedy Channel productivity to arch dynamics and highlights the NOW as a resilient system within the LIA.\u003c/p\u003e\u003cp\u003eAlthough the NOW as a whole generally shows stable PP over time (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ed, Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e), spatial heterogeneity exists. An area of recurrent elevated production is observed in its northern sector, near Cape Alexander (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ea), consistent with local characteristics with a possible island effect features and recurring thin-ice conditions. This localized signal complements the broader picture of system-wide stability and points to the coexistence of resilient background production with finer-scale variability in bloom timing and amplitude. Taken together, these findings emphasize that while the NOW is shaped by the larger-scale dynamics of Nares Strait, its capacity to sustain consistently high PP across shifting ice regimes makes it an ecological and cultural stronghold within the Arctic (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ed, S3).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eAnnual PP of the Total Area, the Northern Hotspot and the Southern Hotspot (in TgC.y\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) and their contributions to the total PP (in %).\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eYear\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSouthern Hotspot\u003c/p\u003e\u003cp\u003e(TgC.y-1)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eNorthern Hotspot\u003c/p\u003e\u003cp\u003e(TgC.y-1)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eTotal Area\u003c/p\u003e\u003cp\u003e(TgC.y-1)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2003\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.083(41%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.007(0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e2.620\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2005\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.958(47%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.062(3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e2.047\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2006\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.116(44%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.023(1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e2.520\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2007\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.921(35%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.230(9%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e2.624\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2008\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.923(41%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.060(3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e2.267\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2009\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.432(30%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.428(9%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e4.752\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2010\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.753(33%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.175(8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e2.274\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2011\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.910(42%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.101(5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e2.158\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2012\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.212(43%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.035(1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e2.826\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2013\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.238(47%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.011(0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e2.646\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2015\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.029(41%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.004(0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e2.499\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2016\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.492(37%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.090(2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e4.033\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2017\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.017(31%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.319(10%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e3.291\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2018\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.043(43%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.006(0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e2.413\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2019\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.884(27%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.219(7%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e3.259\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2020\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.361(36%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.163(4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e3.746\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2021\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.993(35%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.084(3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e2.836\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2022\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.799(35%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.102(5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e2.265\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2023\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.849(37%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.022(1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e2.296\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e\u003ch2\u003e3.3 Ice-arch control of productivity hotspots and bloom phenology\u003c/h2\u003e\u003cp\u003eWhile the NOW exhibits remarkable stability in its annual PP (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ed, S3), finer-scale patterns reveal strong sensitivities to ice-arch dynamics farther upstream in Kane Basin and Kennedy Channel (see Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ea). Clustering analysis distinguished two contrasting regions: the SH, observed consistently across all years with a stable PP, and the NH, which occurs intermittently depending on ice-arch configuration.\u003c/p\u003e\u003cp\u003eThe presence or absence of arches influences the timing and intensity of NH blooms (Marchese et al., \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). When the southern arch fails to consolidate, open-water conditions extend northward by early spring, leading to earlier ice breakup in Kane Basin and Kennedy Channel. This favors the initiation of the NH bloom as early as May, advancing the season by nearly two months compared to years when the southern arch persists (Vincent, \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Moore et al., \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). A consolidated northern arch in Robeson Channel reduces the downstream flux of MYI and also contributes to prolonge open-water conditions downstream and further enhance NH productivity. In this configuration, annual PP in the NH can increase up to 74.4\u0026thinsp;\u0026plusmn;\u0026thinsp;0.2 gC m\u003csup\u003e\u0026minus;\u0026thinsp;2\u003c/sup\u003e y\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, nearly triple that observed in years without arches (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ea-b).\u003c/p\u003e\u003cp\u003eBy contrast, the SH demonstrates greater robustness. Even in years when nutrient drawdown might be expected upstream, local conditions such as recurring thin-ice zones, stable stratification, and predictable light penetration (Barber et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2001\u003c/span\u003e) support relatively consistent bloom initiation and magnitude. One might expect intensified and earlier NH blooms to trigger cascading effects downstream, with nutrient depletion and advective transport reducing PP in the SH. Yet our results indicate otherwise: despite high SIC variability upstream, SH productivity remains confined within a narrow range across ice-arch scenarios, in sharp contrast to the high SIC interannual variability of the NH (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ec\u0026ndash;d). This stability suggests that local conditions damp the SH against upstream forcing, decoupling its dynamics from northern variability.\u003c/p\u003e\u003cp\u003eYears of high productivity (i.e. 2007, 2009, 2016, 2017, 2019, 2020) were found to be linked to distinct environmental forcing patterns. For instance, the 2009 season, characterized by a long-lived northern arch and the early collapse of the southern arch, produced anomalously warm conditions (+\u0026thinsp;5\u0026deg;C SST anomaly; Vincent, \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e2013\u003c/span\u003e) and sustained open water that favored prolonged NH blooms. In contrast, the 2017 season combined thin ice and early collapse with unusual atmospheric forcing linked to the breakdown of the Beaufort High (Moore et al., \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2018\u003c/span\u003e), leading to exceptional bloom conditions in the NH. Beyond affecting the magnitude of PP, ice-arch dynamics also alter the phenology of NH blooms by shifting their timing, duration, and seasonal intensity, with potential consequences for food-web coupling and carbon fluxes. Taken together, these results confirm that sea-ice arches act both as passive mechanical barriers and ecosystem constitutive features that determine not only where hotspots emerge, but also when and how long they persist. While the SH near the NOW remains consistently productive, the NH in Kennedy Channel is more transient and opportunistic, with its presence, magnitude, and phenology depending on the shifting interplay of ice-arch stability and episodic environmental forcing.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003e3.4 Ice-arch dynamics and ecosystem resilience at the Last Ice Area gateway\u003c/h2\u003e\u003cp\u003eOur findings reveal that sea-ice arches are more than passive physical barriers: they act as ecosystem constitutive features that regulate the timing, intensity, and spatial distribution of PP at the southern gateway of the LIA. By shaping the duration of open-water seasons and the advection of MYI, arch stability drives the emergence of contrasting hotspots. The NH is a dynamic feature, with its phenology and magnitude varying according to arch persistence and bathymetric setting. By contrast, the SH, embedded in the NOW, demonstrates remarkable stability, sustaining stable PP across ice-arch scenarios thanks to recurrent thin-ice zones and reliable stratification. These results illustrate how the interplay of ice dynamics structures the productivity of an underexplored Arctic outflow shelf system.\u003c/p\u003e\u003cp\u003eDespite earlier predictions of declining productivity in the NOW, our model suggests that annual PP has remained relatively stable, supporting one of the Arctic\u0026rsquo;s richest food webs and sustaining a cultural way of life for Inuit communities. Yet this stability is not guaranteed: accelerating MYI loss and the potential destabilization of ice arches could undermine the system\u0026rsquo;s long-term stability. Our results emphasize the need to recognize NOW not only as a productivity hotspot, but as a keystone ecosystem whose biodiversity and cultural importance make it central to the functioning of the rapidly changing Arctic and whose protection should be prioritized through marine protected area initiatives and Indigenous stewardship.\u003c/p\u003e\u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003e4. Acknowledgments\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe primary production model used in this study was developed thanks to support from the Canada Excellence Research Chair on Remote Sensing of Canada's new Arctic Frontier and from the Sentinel North project. The Refuge-Arctic project was conducted using the Canadian research icebreaker CCGS Amundsen with the support of the Amundsen Science program funded by the Canada Foundation for Innovation (CFI) Major Science Initiatives (MSI) Fund. We wish to thank the officers and crew of the CCGS Amundsen and the entire TAKUVIK laboratory team for planning the field work, and all other scientists and technicians involved in the Refuge-Arctic campaigns for their contribution to field work and data collection. The project was conducted under the scientific coordination of Centre national de la recherche scientifique CNRS/Université Laval Takuvik Joint International Laboratory (IRL3376). We also thank Québec-Océan and the Polar Continental Shelf Program for their in-kind contribution in terms of polar logistics and scientific equipment. The Refuge-Arctic project is funded by the following French and Canadian programs and agencies: Amundsen Science, ArcticNet, BNP Paribas Foundation, Centre National d’études spatiales (CNES) and the CNES-TOSCA “Alg-O-Nord\", Centre National de la Recherche Scientifique (CNRS), Crown-Indigenous Relations and Northern Affairs Canada (RCAANC), European Research Council (ERC), Flotte Océanographique française (FOF), Fonds de recherche du Québec - Nature et technologies (FRQNT), Institut Nordique du Québec (INQ), Institut français de recherche pour l’exploitation de la mer (IFREMER), Institut Polaire français Paul-Émile Victor (IPEV), Les Enveloppes Fluides et l’Environnement (LEFE), Mission pour les Initiatives Transverses et Interdisciplinaires (MITI), Natural Sciences and Engineering Research Council of Canada (NSERC), \u0026nbsp;Fisheries and Oceans Canada (DFO), Transforming Climate Action (TCA), Sentinelle Nord and Université Laval. We also wish to thank the Denmark's Independent Research Fund (Grant No. 2064-00021B) and the Polar Ocean Mitigation Potential project (Horizon Europe, Grant No. 101136875).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e5. Data Availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe original datasets used to reproduce the findings of this study are publicly available on Zenodo for the primary production at\u0026nbsp;https://doi.org/10.5281/zenodo.14715624. Sea-ice concentration data (12.5\u0026nbsp;km resolution grids of sea ice concentration from the 85 Ghz channel of SSM/I) are available from IFREMER FTP servers at ftp://ftp.ifremer.fr/ifremer/cersat/products/gridded/psi-concentration/data/arctic.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e6. Computer code\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe analysis of the model output was done using the open-source software Python. Post-processing scripts will be provided upon request to the corresponding author.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAndersen, S., Tonboe, R., Kaleschke, L., Heygster, G. \u0026amp; Pedersen, L. T. Intercomparison of passive microwave sea-ice concentration retrievals over the high-concentration Arctic sea ice. \u003cem\u003eJ. Geophys. Res. Oceans\u003c/em\u003e 112, C8 (2007).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eArdyna, M., Gosselin, M., Michel, C., Poulin, M. \u0026amp; Tremblay, J. \u0026Eacute;. Environmental forcing of phytoplankton community structure and function in the Canadian High Arctic: contrasting oligotrophic and eutrophic regions. \u003cem\u003eMar. Ecol. Prog. 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Lett.\u003c/em\u003e 36, L07502 (2009).\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"nature-portfolio","isNatureJournal":true,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"","title":"Nature Portfolio","twitterHandle":"","acdcEnabled":false,"dfaEnabled":false,"editorialSystem":"ejp","reportingPortfolio":"","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-7827911/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7827911/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eNares Strait, located at the southern edge of the Last Ice Area, is a significant ecological zone where seasonal sea-ice arches influence regional ice dynamics, air–sea exchange and ecosystem productivity. By modulating ice export, stratification, and light penetration, these arches determine the timing, location, and intensity of phytoplankton blooms. Based on two decades (2003–2023) of satellite sea-ice observations and depth-resolved primary production estimates, we found a pronounced increase in production, particularly in northern regions where earlier ice retreat and longer open-water seasons promoted phytoplankton growth. Two recurrent productivity hotspots were identified. The first is a variable northern hotspot in Kennedy Channel, which only emerged under specific ice-arch configurations and bathymetric conditions, highlighting the structural role of arches in regulating bloom dynamics. In contrast, the second hotspot, located in the North Water Polynya (\u003cem\u003ePikialasorsuaq\u003c/em\u003e), sustained consistently high production across all sea ice conditions. This stability, in contrast to previously reported declines, highlights the North Water Polynya as an ecologically and culturally significant marine area. Our findings identify sea-ice arches as ecosystem constitutive features within the Last Ice Area and emphasize the critical role of the North Water Polynya for biodiversity conservation and subsistence of Indigenous under continued Arctic warming.\u003c/p\u003e","manuscriptTitle":"Sea-ice arches structure Arctic primary production hotspots at the Last Ice Area gateway","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-10-28 16:28:15","doi":"10.21203/rs.3.rs-7827911/v1","editorialEvents":[],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"communications-earth-and-environment","isNatureJournal":true,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"commsenv","sideBox":"Learn more about [Communications Earth and Environment](https://www.nature.com/commsenv/)","snPcode":"","submissionUrl":"","title":"Communications Earth \u0026 Environment","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"ejp","reportingPortfolio":"Communications Series","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"35504982-fb40-4967-96bc-37dadb2050b8","owner":[],"postedDate":"October 28th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[{"id":56265442,"name":"Biological sciences/Ecology/Ecological modelling"},{"id":56265443,"name":"Earth and environmental sciences/Ocean sciences/Marine biology"},{"id":56265444,"name":"Earth and environmental sciences/Climate sciences/Ocean sciences/Marine biology"}],"tags":[],"updatedAt":"2026-04-18T21:35:14+00:00","versionOfRecord":[],"versionCreatedAt":"2025-10-28 16:28:15","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7827911","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7827911","identity":"rs-7827911","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}