This years chapter could not be updated. Satellite-based annual net primary production in the Barents Sea has shown an increasing trend with a doubling over the last twenty years, due to increased temperatures leading to reduced ice-coverage and prolonged open water period.
The phytoplankton development in the Barents Sea is typical for a high latitude region with a pronounced maximum in biomass and productivity during spring. During winter and early spring (January-March) both phytoplankton biomass and productivity are quite low. The spring bloom is initiated during mid-April to mid-May and may vary strongly from one year to another. The bloom duration is typically about 3-4 weeks and it is followed by a reduction of phytoplankton biomass mainly due to the exhaustion of nutrients and grazing by zooplankton. Later in the fall when the increasing winds start to mix the upper layer and bring nutrients to the surface, a short autumn bloom can be observed. However, the time development of this general description can vary geographically. The spring bloom in the Atlantic water domain without sea-ice is thermocline-driven, whereas in the Arctic domain with seasonal sea-ice, stability from ice-melt determines the bloom (Skjoldal and Rey 1989, Hunt et al. 2012). Thus, the spring bloom at the ice edge in the Barents Sea can sometimes take place earlier than in the southern regions due to early stratification from ice melting.
Remote sensing data having high spatial and temporal resolution were used in obtaining Chl a concentration (mg m-3) and mean daily NPP (g C m-2 day-1). Daily net primary production (NPP) and open water area (OWA) were calculated from satellite data as described in detail in Arrigo and Van Dijken (2015). Satellite-derived surface Chl a (Sat Chl a, Level 3, 8 days binned) was based on SeaWiFS and MODIS/Aqua sensors. SeaWiFS was used in 1998-2002, and MODIS/Aqua in 2003-2017. Data were updated using NASA's latest reprocessing - version R2018.0. For the years where data was available for both sensors (2003-2007), SeaWiFS Chl was consistently higher than MODIS/Aqua Chl. Therefore, we used a correction factor for SeaWiFS Chl to create a comparable 20-year time series. The values for the South-East and Pechora polygons were recalculated excluding the regions most influenced by river inflow (18% and 41% of the total area, respectively). The work done here is in collaboration with Professor Kevin Arrigo and Gert van Dijken from the Stanford University, USA. Validation of satellite Chl a using in situ data showed significant correlations between the two variables in the Barents Sea (Dalpadado et al. 2014, ICES/WGIBAR 2017, this study) and thus, the NPP model based on satellite data by Arrigo et al. (2015) gives reasonable results that compare well with sea ground truthing measurements. Also, estimates of new production from phytoplankton based on nitrogen consumption (seasonal draw-down of nitrate in the water column) for the Fugløya - Bear Island (FB) and Vardø-Nord (VN) sections, representing the western and central Barents Sea respectively, from March to June resulted in values comparable to satellite NPP estimates (Rey et al. in prep, pers. com.).
Spatial and temporal patterns of Chl a in spring
Remote sensing data, providing good spatial and temporal coverage, were used to explore the seasonal and interannual variability in Chl a distribution. Satellite data from the Barents Sea during 2016-2018 showed large interannual variability with the highest Chl a concentration generally observed in May (Fig. 18.104.22.168). There was much less sea ice in 2016, and north- and eastward expansion of the Chl a distribution. Furthermore, earlier blooming and higher concentrations in the eastern regions in April and May were observed in this year. 2017 was a colder year with more ice especially compared to 2016. Chl a was much lower during April to July in 2017 compared to the previous year. The ice cover was larger in April 2017 and 2018, than in 2016. Though the Chl a in April in 2018 was lower compared to 2016, high concentration was observed in May for both years.
Figure 22.214.171.124. Spatial distributions of Chl a (mg m-3) in April, May and June for 2016, 2017 and 2018. White areas indicate ice-coverage. The black areas indicate no data. The pink lines show the climatological (average 1981-2010) position of the ice edge.
Net Primary Production (NPP)
Although the NPP of the whole Barents Sea showed substantial interannual variability, there was a marked significant increase during the study period, 1998-2018 (Fig. 126.96.36.199, p = 0.001). Average NPP for the whole Barents Sea was much lower in years 1998-2008 than in the more recent decade 2009-2018 (64.8 and 93.8 Tg C, respectively). Though the NPP in the western and eastern regions of the Barents Sea increased significantly during the study period (p < 0.01), the increase in the northeastern region was up to 5 times larger compared to the south west region.
Figure 188.8.131.52. Annual net primary production (satellite based NPP) for the whole Barents Sea.