Socio-economic relevance and policy implications Variability of the ocean circulation and the water mass distribution in the Nordic Seas lead to changes in the volume, heat and freshwater fluxes between the Arctic Ocean and North Atlantic. Changes in these fluxes can have a strong influence on the role of the ocean in the climate system which includes the potential of abrupt climate changes.
The climate variability in particular in the northern North Atlantic has a strong impact on the living conditions in Northwest Europe. This includes energy consumption, sea traffic and marine living resources. Therefore a reliable prediction system is of high value to maintain the present living conditions. Prediction requires understanding and modelling of the relevant processes and monitoring key parameters to validate and constrain the models.
Since variability of the relevant time scales can be only studied on the base of the long-term time series, ASOF-N aimed to pave the way towards an observing system consisting of a cost effective array of instruments in the key areas for the exchanges between the North Atlantic and Arctic Ocean. The results of ASOF-N will help to design such a system, to give advice for its implementation and consequently contribute to maintain the quality of life in Northwest Europe.
Conclusion The evaluation of the available historical data together with the results of the ASOF-N field measurements and modelling results revealed a significant warming of the Atlantic Water propagating through the ASOF-N region and an increased heat flux into the Arctic Ocean. The data indicate that variations of the fluxes between the North Atlantic and the Arctic Ocean occur on a wide range of time scales and are interlinked between the main passages.
The volume and heat fluxes are also controlled by local and remote atmospheric forcing. Both in the Barents Sea Opening and Fram Strait variability of temperature is independent of the variations in the volume flux. The former is dominated by advective processes and depends mostly on the upstream conditions while the latter is related to the local atmospheric forcing. All these changes occur over long time scales and only quasi-continuous measurements over a decade and more give a chance to identify the nature of these fluctuations.
Lacking spatial resolution is a problem in spite of the fact that the major parts of the transports occur in relatively narrow boundary currents. Technical problems with the present day equipment lead to redundancy of equipment. This includes tidal forcing.
airtec.gr/images/localizador-movil/1006-ubicacion-de-personas.php The large-scale model runs with a total of eight tidal components based on data from the TPXO 7. The ecosystem module is formulated in an Eulerian framework and includes state variables for nutrients nitrate - NO 3 , ammonium - NH 4 , and silicate - SiO 4 , the microbial loop, heterotrophic nanoflagellates, diatoms and autotrophic flagellates, ciliates and two key mesozooplankters: the Atlantic C.
For details of the biological model, see Wassmann et al. The model contains additional compartments for sinking detritus fast and slow , dissolved organic carbon and the sediment. The SINMOD model was found to be one of the best models to estimate primary production in the Arctic Ocean during an inter-comparison among ocean biogeochemical coupled models and Earth system models Lee et al.
In each grid cell, phytoplankton are modeled in the 50 m surface layer of the water as:. The model output is in units of Nitrogen, converted to carbon using a constant C:N ratio of 7. Sinking is only related to phytoplankton cells, a slow export of organic carbon from the surface layer. On the other hand, Export of organic matter Figure 2 comprises mostly the sedimentation of zooplankton fecal pellets and molts, considered to be a fast export. The model does include a module on the microbial loop where bacteria consume DOC from phytoplankton excretion and are predated upon by nanoflagellates.
The model does not consider viruses as a separate compartment or cell lysis as a separate process Wassmann et al. Figure 2.
Input terms are in green, as g C m —2 d —1 and loss terms in red, with the same units. All model output is expressed in units of phytoplankton carbon. Model results are for the year , a year of minimum sea ice extent in the Arctic Ocean Figure 1b ; Stroeve and Notz, , maximizing ice-free primary production in the West and NSv Archipelago.
These rates are calculated for a 6-month period during the growth season, from April to September, and are considered representative of yearly estimates Wassmann et al. Several experiments were performed to determine the contribution of a phytoplankton biomass advection to local primary production, b phytoplankton growth parameters, c the relative importance of phytoplankton biomass advection on in situ phytoplankton production at each grid cell, and d the balance between sources and sinks of biomass as a function of advection.
Results are shown as maps in units of phytoplankton carbon and as tables with discrete values at fixed points along the AWI. The remaining data are shown to give context to the phytoplankton dynamics observed in the AWI. Gross Primary Production relates to the total amount of organic carbon newly incorporated by photosynthesis, thus an index of production.
As this process is based on the existing phytoplankton biomass, it depends on the physiological response of high-latitude microalgae to irradiance, temperature and inorganic nutrients within the surface mixed layer. These GPP annual rates are within estimates extrapolated from field samples with low March production and high June production Vernet et al.
Figure 3. Range of values from 0. This is a difficult parameter to measure in the field, as phytoplankton biomass in units of carbon is often contaminated by bacteria and other heterotrophs. The modeled rates are within the range expected for seasonal ly averaged field samples in high-latitude environments, e.
For the 6-month productive period Figure 3b and Supplementary Table S2 , between April and September, average growth rates varied from 0. In the field, assessments of in situ primary production concurrent to advection estimates of primary production are challenging. This variable is sensitive to the model grid cell size, thus, this experiment provides only relative comparisons among locations. Within the flow, phytoplankton is carried north relatively fast and the Residence Time is limited to 0. These numbers compare favorably with transport from a WSC current speed of 0.
Comparing this Residence Time map to the distribution of GPP in Figure 3a , it suggests that the low Residence Time in the currents is mainly due to high advection of phytoplankton biomass as in situ GPP changes only by a factor of 2 or 3. Figure 4. Phytoplankton residence time mean over 6 months, April-September. An alternative to estimating the effect of advection on phytoplankton processes along the AWI is to turn off GPP at a certain location and observe the downstream distribution of phytoplankton biomass B. The extent of phytoplankton biomass loss after GPP was turned off is shown for three locations in Figure 5.
Notably, phytoplankton biomass along the AWI reaches longer distances than elsewhere in the study domain. However, there is spatial variability: phytoplankton biomass persists longer i. Such dispersal distances are typical for larval transport of benthic, sessile organisms and a variety of fish 50— km with large ocean currents being major pathways of larval dispersal Cowen et al. Figure 5.
The three locations are depicted with the vertical red lines see also orange transect lines in Figure 1b. This unitless ratio indicates what proportion of the biomass in any given location originated from advection mg C m —2 d —1 and how much from local photosynthesis mg C m —2 d —1. When the spatial distribution of the ratio in each model grid cell is mapped, the values are always positive, indicating advection of phytoplankton is greater than, or equal to, in situ GPP in our region of interest Figure 6.
For the growth season, the ratio, that is the contribution of biomass by advection, is maximum along the currents on average, with ratios of up to 40 indicating a much larger contribution of advected phytoplankton compared to contribution of carbon by in situ primary production. Figure 6. Low contribution of advection blue to high red from 0 to 50 times higher Phytoplankton Advection than local GPP. The relative balance between advected and locally produced biomass at each location has a strong seasonality Supplementary Figure S2.
When GPP is low, as in the beginning and end of the growth season, the ratio is intermediate 10 — 20 , as presumably advected biomass is also low. Advection of biomass becomes more important as local productivity lessens later in the summer. In the NSv, the importance of advected biomass is highest also late in the growth season, in August and September.
The two-way oceanic exchanges that connect the Arctic and Atlantic oceans through subarctic seas are of fundamental importance to climate. The two-way oceanic exchanges that connect the Arctic and Atlantic oceans through subarctic seas are of fundamental importance to climate. Change may.
If phytoplankton biomass is being advected along the AWI current, how much carbon is being transported at any given location? The transport of phytoplankton carbon biomass and water through sections along the advective pathway was calculated Advection-OUT for biomass, Figure 2 and integrated for the growth period from April to September. We defined four sections along the AWI to examine potential changes in transport occurring from south to north Figure 1b.
These sections have variable lengths as they were set to be representative of all northward transport that varies along the current due to topography Hansen et al. As there is no objective measure of water and carbon flow, these transects are meant to give a semi-quantitative estimate of south-to-north changes in fluxes. A decrease in phytoplankton biomass transport was observed from the NAC to the NSv that can be considered a net loss of biomass toward the north Table 1 and Supplementary Table S3.
In northern Norway the southernmost section , the flow carries 2. As the current flows northward, 0. Transport of carbon decreases to 0.
Thus, we expect a fraction of phytoplankton carbon to enter this westerly recirculation, in agreement with the decrease of phytoplankton carbon from NW Svalbard to north of Barents Sea, from 0. The high seasonal variability in carbon flux in any region is attributed in part to the seasonal variability in water transport within the AWI, with summer water transport half that in winter 0.
Furthermore, copepod grazing in the NAC is highest at the time of reproduction in early spring, affecting carbon export out of this region. Table 1. Due to the variability of advected and in situ production of biomass at any given location Figure 6 and Supplementary Figure S2 , what is the net carbon balance between phytoplankton production and loss rates at each location along the AWI? A positive carbon balance between these processes would indicate a net accumulation of phytoplankton biomass due to in situ processes while a negative one relates to net loss.
By the end of the summer season, the whole region has become dominated by net carbon losses, indicating higher consumption than production. The overall seasonal signal west of Svalbard Figure 7 is positive due to the high NCP in May and June that is not compensated by in situ losses later in the season. Figure 7. Net carbon production NCP , calculated as the balance between in situ production GPP and in situ carbon losses respiration, DOC excretion, sinking and grazing , calculated for each grid cell and mapped.
A major question in the Arctic region concerns the changes in the Arctic Seas and their effect on the connectivity with the Central Arctic Ocean. The most active of these connections is the AWI from the North Atlantic to the Nansen Basin, an eastern boundary current well known for bringing heat and nutrients to high latitudes e.
Water masses and their biological and chemical constituents advected in eastern boundary currents such as the AWI are subject to transformation along their transit from temperate to polar waters Saloranta and Haugan, ; Longhurst, We can expect local biological processes to take place at every location, through photosynthesis bottom-up processes and the interactions of the food web components top-down processes.
The series of experiments performed with the SINMOD model in this study provides insights into the transformation of the phytoplankton biomass from Northern Norway to the entrance to the Arctic Ocean and the role of advection for phytoplankton productivity and ecosystem processes along this pathway.
The year was ideal to perform the model experiments for two main reasons: first, it was a year of unusually low sea-ice extent in the Arctic Ocean, providing a glimpse of future conditions as sea ice extent continues to decline Polyakov et al. Second, there is interest in understanding ecological processes in the NSv area, at the entrance of the AWI into the Arctic Ocean, particularly with respect to the potential development of cod fisheries in this region Haug et al. Conditions observed in reflected the open-water fraction of this northern region, particularly during springtime when sea ice drift normally covers the northern Fram Strait Lind et al.
In this study, we address the central question: how are primary production processes affected by advection of phytoplankton carbon in the AWI and what are the consequences for the pelagic ecosystem? As all variables and processes from the model are in units of phytoplankton carbon, we can infer answers to these questions. At the entrance of the Arctic Ocean, and in most Arctic Seas, sea ice edge blooms are considered critical to annual productivity e. As the transport of phytoplankton arrives to the ice edge in the WSC or NSv, it is expected to enhance the ice-edge blooms as well.
Known standing stocks of available nitrogen in the Arctic are not enough to support the annual Arctic Ocean production Tremblay et al. Diffusion of nitrate from deep waters through the pycnocline has recently been estimated at 0.