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Keywords:

  • Arctic;
  • primary production;
  • satellite;
  • sea ice

Abstract

  1. Top of page
  2. Abstract
  3. 1. Introduction
  4. 2. Methods
  5. 3. Results
  6. 4. Discussion
  7. Acknowledgments
  8. References
  9. Supporting Information

[1] A satellite-based study was conducted to document daily changes in net primary production (NPP) by phytoplankton in the Arctic Ocean from 1998 to 2009 using fields of sea ice extent, sea surface temperature, and chlorophyll a concentrations. Total annual NPP over the Arctic Ocean exhibited a statistically significant 20% increase between 1998 and 2009 (range = 441–585 Tg C yr−1), due mainly to secular increases in both the extent of open water (+27%) and the duration of the open water season (+45 days). Increases in NPP over the 12 year study period were largest in the eastern Arctic Ocean, most notably in the Kara (+70%) and Siberian (+135%) sectors. NPP per unit area for the Arctic Ocean averaged 101 g C m−2 yr−1 with no significant change over the study period. In the western sectors, NPP ranged from 71.3 ± 11.0 g C m−2 yr−1 in the Beaufort to 96.9 ± 7.4 g C m−2 yr−1 in the Chukchi, while in the more productive eastern Arctic, annual NPP between 1998 and 2009 ranged from 101 ± 15.8 in the Siberian sector to 121 ± 20.2 in the Laptev. Results of a statistical analysis suggest that between 1979 and 1998 (prior to the launch of SeaWiFS and MODIS), total Arctic NPP likely averaged 438 ± 21.5 Tg C yr−1. Moreover, when summer minimum ice cover drops to zero sometime during the first half of this century, annual NPP in the Arctic Ocean could reach ∼730 Tg C yr−1. Nutrient fluxes into Arctic surface waters need to be better understood to determine if these projected increases are sustainable.

1. Introduction

  1. Top of page
  2. Abstract
  3. 1. Introduction
  4. 2. Methods
  5. 3. Results
  6. 4. Discussion
  7. Acknowledgments
  8. References
  9. Supporting Information

[2] The Arctic Ocean is undergoing unprecedented change with respect to its sea ice cover. Sea ice concentrations have dropped by approximately 9% per decade over the last three decades and have been accompanied by reductions in sea ice thickness, concentration, and duration [Perovich and Richter-Menge, 2009]. Causes of this decline in sea ice cover have been attributed to a number of factors, including increased Arctic air temperatures due to higher atmospheric greenhouse gas content [Rothrock and Zhang, 2005; Lindsay and Zhang, 2005; Zhang and Walsh, 2006; Stroeve et al., 2007], atmospheric circulation patterns that favor advection of sea ice out of the Arctic Ocean through Fram Strait [Rigor and Wallace, 2004; Liu et al., 2007; Maslanik et al., 2007; Serreze et al., 2007], and increased advection of warm water into the Arctic Ocean, both from the Atlantic through the eastern Fram Strait and the Barents Sea [Steele and Boyd, 1998; Dickson et al., 2000] and from the Pacific in the form of relatively warm Pacific Surface Water [Maslowski et al., 2001; Shimada et al., 2006; Woodgate et al., 2006]. The net result is an ice pack that contains a larger proportion of first year ice that is more easily melted, either by surface heating or advection of warm waters into the Arctic Ocean. Reduction in sea ice extent decreases surface albedo, allowing more shortwave radiation to penetrate the ocean surface, contributing to additional ocean heat content and thus creating a positive feedback mechanism that inhibits ice growth in winter and accelerates its loss in spring and summer [Perovich et al., 2007].

[3] Reduced sea ice cover increases the transmission of light to the surface ocean. Consequently, the Arctic Ocean in recent years has been characterized by increased open water area, a longer growing season, and increased annual net primary production (NPP) by phytoplankton [Arrigo et al., 2008a; Pabi et al., 2008]. Increases in NPP were particularly large on the continental shelves of the Beaufort, Chukchi, East Siberian, Laptev, and Kara seas. These results were based on a relatively short time series of satellite ocean color data and, unlike the 30+ year trend in sea ice, observed secular increases in annual NPP were not statistically significant.

[4] In the present study, we have extended the NPP time series using the newly reprocessed SeaWiFS and MODIS Aqua ocean color data. Prior to reprocessing, chlorophyll a (Chl a) retrievals by SeaWiFS were approximately 15% higher than those of MODIS Aqua in the Arctic Ocean and it was not possible to construct a coherent time series by combining these two data sets. Reprocessed SeaWiFS and MODIS Aqua imagery now agree to within 2% in oligotrophic and mesotrophic waters of the global ocean (http://oceancolor.gsfc.nasa.gov/REPROCESSING/R2009/validation/). This increased level of agreement between the two data products is important because SeaWiFS has not provided a continuous data record since 2007. Therefore, a long-term ocean color record will have to include data from both satellite sensors.

[5] The resulting 12 year time series of combined SeaWiFS/MODIS Aqua Chl a was used as input to a NPP algorithm developed for the Arctic Ocean [Pabi et al., 2008]. This algorithm calculates rates of daily NPP at each pixel location across the Arctic Ocean from satellite fields of Chl a, sea surface temperature, and sea ice extent, and from climatological mixed layer depths. The resulting maps of depth-integrated NPP are used to quantify both spatial and temporal (seasonal and interannual) variability in productivity and relate this variability to measured environmental changes.

2. Methods

  1. Top of page
  2. Abstract
  3. 1. Introduction
  4. 2. Methods
  5. 3. Results
  6. 4. Discussion
  7. Acknowledgments
  8. References
  9. Supporting Information

2.1. Net Primary Production by Geographic Sector

[6] Daily maps of NPP for the Arctic Ocean (all waters north of the Arctic Circle) were produced from satellite derived Chl a, sea surface temperature, and sea ice cover using the algorithm of Arrigo et al. [2008b] as modified by Pabi et al. [2008].

[7] For the purpose of characterizing spatial differences, we divided the Arctic Ocean into eight geographic sectors and four open water ecological regimes, as described by Pabi et al. [2008]. The geographic sectors were demarcated by longitude (Figure 1) and include the Chukchi (180° to 160°W), Beaufort (160°W to 100°W), Baffin (100°W to 45°W), Greenland (45°W to 15°E), Barents (15°E to 55°E), Kara (55°E to 105°E), Laptev (105°E to 150°E), and Siberian (150°E to 180°) sectors.

image

Figure 1. Map of the study region showing the locations of the eight geographic sectors referred to in the text.

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2.2. Algorithm Input Data

2.2.1. Chlorophyll a

[8] For the years 1998 through 2007, surface Chl a concentrations were determined from Level 3 (8 day binned, 9 km resolution) of the most recently reprocessed SeaWiFS ocean color data (Reprocessing R2009.1) using the OC4v6 algorithm (http://oceancolor.gsfc.nasa.gov/REPROCESSING/R2009/ocv6/), a modified version of the OC4v4 algorithm [O'Reilly et al., 1998]. For the years 2008 and 2009, surface Chl a concentrations were determined from Level 3 MODIS Aqua ocean color data (Reprocessing R2009.1) using the OC3Mv6 algorithm [O'Reilly et al., 2000]. Despite the recent reprocessing of both SeaWiFS and MODIS ocean color data, which brought the global mean Chl a retrieval from the two sensors much closer together, an analysis of mean Chl a concentrations in Arctic waters between 2003 and 2007 (for which both SeaWiFS and MODIS Aqua data are available) show that SeaWiFS-derived Chl a concentrations still exceed those from MODIS Aqua by approximately 2.6%. Furthermore, rates of NPP computed for Arctic waters using SeaWiFS Chl a exceed those from MODIS Aqua by an average of 3.6%, depending on year and geographic sector (Table 1). Therefore, to construct a 12 year time series of NPP that was based on both SeaWiFS and MODIS Aqua data, we calculated daily NPP using SeaWiFS Chl a data for the years 1998 through 2007. Then for 2008 and 2009 (for which limited SeaWiFS data are available), we used MODIS Aqua Chl a data as algorithm input, but adjusted the resulting NPP estimates using the mean correction factors shown in Table 1.

Table 1. Correction Factors Used to Adjust Primary Productivity Estimates Made Using MODIS Aqua Chl a
 YearMeanSD
20032004200520062007
Greenland1.1151.0041.0751.1061.0351.0670.047
Barents1.1121.0251.1081.0901.0181.0710.046
Kara1.0670.8970.9720.9830.9650.9770.061
Laptev1.1270.9681.0620.9971.0241.0350.062
Siberian0.9520.8930.9360.7670.9470.8990.077
Chukchi0.9980.8890.9950.9810.9410.9610.046
Beaufort1.0531.0061.0300.9951.0211.0210.023
Baffin1.0801.0591.0741.0901.1021.0810.016
Arctic1.0870.9831.0521.0501.0081.0360.041

[9] Nearshore Chl a pixels suspected of being contaminated by sediment or CDOM from river discharge, as identified by their anomalously high Chl a concentration (compared to coastal pixels not influenced by rivers) or high remote sensing reflectance in the red and near-infrared wavelengths, were removed, which reduced the pan-Arctic NPP by less than 10%.

2.2.2. Sea Surface Temperature

[10] Daily sea surface temperature (SST) is based on the Reynolds Optimally Interpolated SST (OISST) Version 2 product [Reynolds et al., 2002] obtained from NOAA (http://www.emc.ncep.noaa.gov/research/cmb/sst_analysis/).

2.2.3. Sea Ice Cover

[11] Sea ice cover was estimated from Special Sensor Microwave Imager (SSM/I) 37 and 85 GHz bands using the Polynya Signature Simulation Method (PSSM) algorithm [Markus and Burns, 1995], which allows determination of sea ice presence/absence at 6.25 km resolution. According to this algorithm, a given pixel is defined as being ice covered wherever the sea ice concentration is greater than approximately 10%.

[12] The date of sea ice retreat was defined as the date when open water area in a given region of interest (e.g., the Arctic or one of its geographic sectors) first exceeded 50% of the average annual amplitude for that region. For example, in the Arctic Ocean, open water area ranges seasonally from an average low of 2 × 106 km2 in February-March to an average peak of about 8 × 106 km2 in September. Therefore, the date of sea ice retreat would be the date when open water first exceeded 5 × 106 km2 (i.e., 2 × 106 + 0.5 (8 × 106 − 2 × 106)). Similarly, the date of sea ice advance would be defined as the date when total sea ice area in the Arctic Ocean first fell below 5 × 106 km2. Thresholds defining sea ice retreat and advance having values of 4 × 106 km2, 5 × 106 km2, and 6 × 106 km2 are shown in Figure 2. As will be seen, these different threshold values, which range from 25 to 65% of the annual amplitude in open water area, yield similar trends in sea ice retreat over the 12 year time series.

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Figure 2. Annual cycle of open water area in the Arctic Ocean (all waters north of the Arctic Circle) for the years 1998–2009. Thin horizontal lines show the three different threshold values used to estimate dates of sea ice retreat and sea ice advance shown in Figure 7.

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[13] The length of the open water season (or phytoplankton growing season) is defined as the number of days elapsed between the date of sea ice retreat and the date of sea ice advance.

2.3. Impact of High CDOM and Subsurface Chlorophyll Maxima on Estimated NPP

[14] Matsuoka et al. [2007, 2011] noted that the optical properties of Arctic waters differ from the rest of the global ocean, due to both higher pigment packaging by phytoplankton and elevated CDOM concentrations. As a result, the standard OC4v4 algorithm of SeaWiFS overestimates surface Chl a concentrations in Arctic waters, exhibiting a root mean square error (RMSE) of 0.21 mg m−3 when compared to in situ data. This error is likely to be smaller for the OC4v6 algorithm used in the most recent reprocessing (and used here), which shows improved agreement with in situ values in coastal waters. However, because surface Chl a is an important input parameter to our NPP algorithm, we quantified the impact that a 0.21 mg m−3 overestimate of Chl a by SeaWiFS, resulting from higher pigment packaging and elevated CDOM concentrations, would have on calculated NPP (see below).

[15] Furthermore, because the upwelling radiance received by satellite ocean color sensors originates almost exclusively from the upper optical depth of the ocean, features deeper in the water column cannot be resolved. Therefore, depth-integrated rates of NPP calculated from satellite-based measurements of Chl a will be underestimated in regions of the Arctic Ocean that have a well-developed subsurface chlorophyll maximum (SCM). To date, the impact of ignoring the SCM when estimating depth-integrated NPP from surface Chl a has not been explicitly quantified, although Hill and Zimmerman [2010] did examine the impact of vertical distribution of Chl a on the performance of a satellite-based primary production model using in situ measurements.

[16] To investigate the impact that both overestimates in Chl a concentration by the OC4v6 and OC3Mv6 algorithms and omission of the SCM from vertical profiles of Chl a have on estimates of depth-integrated NPP in the Arctic Ocean, we used in situ data from the ARCSS-PP database (see Matrai et al. [2011] for details) to characterize vertical distributions of Chl a and primary production for the eight geographic sectors of the Arctic Ocean used in our analysis. The database consisted of 9484 Chl a stations and 1931 primary production stations. Both data types were binned monthly (e.g., January, February, March…), seasonally (January-March, April-June…), and annually (January-December, Figure 3) for each geographic sector.

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Figure 3. Annual mean vertical profiles of in situ Chl a for the Arctic Ocean from the ARCSS-PP database. Note that the vertical profile for the Laptev Sea is based on only two in situ samples.

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[17] The mean vertical profile of Chl a from the ARCSS-PP database for each time bin was then used as input to our NPP algorithm. This was done using three different approaches. First, we used the mean vertical profile for each time bin with the SCM intact (Figure 4a, solid line). NPP was then calculated using our algorithm [Arrigo et al., 2008b; Pabi et al., 2008] at each depth for which Chl a data were available and these depth-dependent values were integrated vertically to calculate total water column NPP. Second, we increased vertical profiles of Chl a by an amount equivalent to the RMSE of SeaWiFS for Arctic waters (0.21 mg m−3) to mimic the effect overestimating surface Chl a by SeaWiFS and MODIS. The difference in NPP estimated by our algorithm using in situ Chl a and in situ Chl a + 0.21 mg m−3 as input provides an estimate of the error in NPP for each time bin and in each geographic location resulting from our use of satellite-based surface Chl a, rather than in situ data. Third, we applied the surface Chl a concentration from the ARCSS-PP database to the entire mixed layer (Figure 4a, dashed line), essentially removing the SCM, and recalculated total water column NPP using the new vertical Chl a profile as input. The difference in vertically integrated NPP between this and the approach where we kept the SCM intact reflects the amount of NPP associated with the SCM and was used to estimate the degree to which our algorithm underestimates vertically integrated NPP for each time bin and in each geographic location as a consequence of SeaWiFS missing the SCM.

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Figure 4. Example vertical profiles of (a) Chl a and (b) NPP with the SCM and SPM intact and with them removed. To remove subsurface maxima, any depth where the Chl a or NPP value exceeded the surface value was replaced by the surface value.

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2.3.1. Use of SeaWiFS and MODIS Versus in Situ Chl a

[18] The impact on NPP of increasing in situ Chl a concentrations by 0.21 mg m−3 throughout the Arctic (to simulate errors in satellite-derived Chl a) varied seasonally and by region. Not surprisingly, estimated errors in NPP were largest for those months and locations where Chl a concentrations (and NPP) were low and an absolute increase of 0.21 mg Chl a m−3 represented a large percentage change. For example, increasing Chl a by the RMSE in the Barents Sea in February resulted in a 25-fold overestimate of NPP. This was by far the most extreme case, and was based on relatively few in situ data. Nevertheless, NPP over the entire Arctic Ocean was still overestimated by 44% in March when in situ Chl a was increased by an amount equivalent to the RMSE of SeaWiFS. Overestimates of NPP were even larger in November (61%). However, errors in all other months were much smaller, ranging from only 4.5% to 19.6%. Furthermore, during the most productive months of May-August, errors in NPP for the Arctic Ocean resulting from likely overestimates of surface Chl a by satellites ranged from only 4.5–5.8%. Consequently, errors in annual NPP for the entire Arctic Ocean resulting from the use of SeaWiFS Chl a are only on the order of 6.1%, although within specific geographic sectors, errors were as large as 15.4% (Barents sector).

2.3.2. Omission of the SCM

[19] Results of this analysis show that neglecting the SCM results in a 7.6% underestimate of annual primary production by our algorithm when averaged over the entire Arctic Ocean. Errors are largest in the Chukchi (7.6%) and the Beaufort (11.7%) seas and are negligible (<1%) in the Kara, Siberian, and Laptev seas. As also shown by Pabi et al. [2008], errors in NPP due to missing the SCM were larger in summer than they were in spring. It should be noted, however, that despite the large amount of data in the ARCSS database, some geographic regions still suffer from a lack of data during parts of the year. Nevertheless, existing data suggest that while our algorithm underestimates NPP due to its inability to resolve the SCM, particularly in the western Arctic, this effect never exceeds 11.7% for any geographic region and is usually far smaller.

[20] We performed a similar analysis using vertical profiles of primary production from the ARCSS-PP database. For any time bin exhibiting a subsurface productivity maximum (SPM), we replaced elevated production values in the SPM with the lower surface productivity values, just as we did with the SCM (Figure 4b), and calculated the change in vertically integrated primary production resulting from the removal of the SCM. Surprisingly, results of this analysis indicate that omission of the SPM has an even smaller impact on estimates of annual NPP than the removal of the SCM. Seasonally averaged data (Figure 5) indicate that SPM are only present in July-September (Figure 5b), and only in the Beaufort, Barents, and Siberian sectors. Surprisingly, when all data are averaged over the entire year, no SPM is apparent (Figure 5d). Based on the seasonally averaged data shown in Figure 5, primary production between April and December is approximately 202 g C m−2 when the SPM is left intact. When the SPM is removed from all vertical profiles and primary production is recalculated, the value for April to December drops to 196 g C m−2, a decline of only 2.9%, further demonstrating that while satellite-based estimates of NPP will underestimate production in waters with a SPM, the magnitude of the error is relatively small.

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Figure 5. Mean vertical profiles of in situ primary production for the Arctic Ocean from the ARCSS-PP database averaged for (a) spring, (b) summer, (c), autumn, and (d) annually.

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[21] The presence of relatively high CDOM and phytoplankton pigment packaging causes satellite-based approaches to overestimate surface Chl a, resulting in estimates of NPP for the Arctic Ocean that are 6.1% too high. Conversely, satellites also miss the SCM, which results in estimates of NPP for the Arctic Ocean that are 7.6% too low. Therefore, the combined effects of these two processes virtually offset each other. The net effect of using satellite-based surface Chl a values as input to the NPP model is likely to be a small underestimate in annual NPP (<2%). It must be noted, however, that the eastern Arctic is not well represented in the ARCSS database and as more data become available, estimated errors associated with omission of the SCM and use of SeaWiFS Chl a as model input may change.

3. Results

  1. Top of page
  2. Abstract
  3. 1. Introduction
  4. 2. Methods
  5. 3. Results
  6. 4. Discussion
  7. Acknowledgments
  8. References
  9. Supporting Information

3.1. Pan-Arctic Ocean

3.1.1. Open Water Area

[22] The annual cycle of open water area in the Arctic Ocean exhibits a relatively long annual minimum period that lasts from January through the beginning of April (Figure 2). Minimum open water area at that time ranges interannually from approximately 2 × 106 km2 in 1998 to 3 × 106 km2 in 2007. Open water area increases exponentially between April and August, reaching its annual peak sometime in September. In contrast to the annual minimum, the annual peak in open water area is much more short-lived, lasting only about a month and usually centered around September 10 (±7 days) (Table 2). Interannual differences in peak open water area are larger than differences in the annual minimum, ranging from 7.3 × 106 km2 in 2001 to 9.5 × 106 km2 in 2007. After September, sea ice advances at a faster rate than its retreat, resulting in a rapid drop in open water area in the autumn.

Table 2. Mean Productivity Metrics by Geographic Sector in the Arctic Ocean for 1998–2009a
 Bloom Length (Days)Open Water Season (Days)Productivity Peak (Date)Open Water Peak (Date)Annual Primary Production (g C m−2 yr−1)Annual Primary Production (Tg C yr−1)
MeanSDMeanSDMeanSDMeanSDMeanSDMeanSD
  • a

    Bold indicates significant negative secular trend between 1998 and 2009 (p < 0.05). An asterisk indicates significant secular trend between 1998 and 2009 (p < 0.05).

Greenland73.813.213329.5June 1112.7Aug 2710.386.06.514810.8
Barents108*21.5212*63.3May 2411.4Sep 1416.01108.613218.0
Kara11421.2103*27.1July 823.5Sep 1513.511317.856.8*15.1
Laptev10823.872.323.5July 2128.4Sep 810.712120.242.613.3
Siberian10719.863.4*30.9July 9*13.0Sep 811.410115.826.0*10.4
Chukchi11916.1105*25.2June 1024.7Sep 59.896.97.429.1*5.3
Beaufort61.215.896.630.6July 515.3Sep 69.471.311.024.17.3
Baffin48.521.2127*14.0May 26*13.0Sep 1011.173.74.934.33.8
Arctic1079.65100*12.4May 239.2Sep 106.81014.8493*41.7

[23] Mean annual open water area in the Arctic Ocean averaged 4.31 ± 0.34 × 106 km2 between 1998 and 2009. During that time, mean annual open water area increased by an average of 84,000 km2 each year (Figure 6a), for a total increase of 27% over the 12 year time series (R2 = 0.75, p < 0.001). Mean annual open water area was at its peak in 2007, dipping somewhat thereafter, with the last five years exhibiting the highest open water area of the 30 year satellite record.

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Figure 6. Yearly trends in (a) mean open water area and (b) total annual net primary production for the Arctic Ocean.

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3.1.2. Length of Open Water Season

[24] Associated with the secular increase in mean annual open water area has been an increase in the length of the open water season (the time between the start dates of ice retreat and ice advance), which averaged 100 ± 12.4 days between 1998 and 2009 (Table 2). The start of sea ice retreat in the Arctic Ocean, defined here as the date when open water area first exceeded 5 × 106 km2, ranged from June 30 to July 24 and began an average of 2.4 days earlier each year between 1998 and 2009 (Figure 7a). In aggregate, sea ice retreated a total of 28 days earlier at the end than at the beginning of our 12 year study period. In addition, sea ice advanced an average of 1.4 days later each year between 1998 and 2009 (Figure 7b), resulting in a 17 day delay in the timing of ice advance over the same 12 year period. Taking into account changes in the timing of both sea ice advance and retreat, the length of the open water season in the Arctic Ocean increased by an average of 3.8 days each year between 1998 and 2009 (Figure 7c), resulting in a 45 day increase in the length of the open water season over the 12 year period.

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Figure 7. Yearly trends in (a) the day of the year of initial sea ice retreat, (b) the day of the year of initial sea ice advance, and (c) the length of the open water season (defined as the difference between Figures 7a and 7b) for the Arctic Ocean. The three sets of values shown in Figures 7a and 7b were determined using thresholds of either 4 × 106 km2, 5 × 106 km2, or 6 × 106 km2, which are shown in Figure 2.

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3.1.3. Net Primary Production
3.1.3.1. Annual Cycle

[25] Because of low solar insolation, rates of daily NPP in open waters of the Arctic Ocean remain low until early March (Figure 8). At that time, NPP begins to increase despite the fact that open water area is still at its annual minimum. This early increase in NPP is due to increased solar insolation in the Greenland and Barents sectors, which contain a large amount of open water throughout the year (see below) and are able to support substantial early rates of phytoplankton productivity. As sea ice retreats in the other geographic sectors, exposing surface waters to increased solar insolation in April, mean rates of daily NPP for the Arctic Ocean begin to accelerate, eventually reaching their annual peak of ∼850 mg C m−2 d−1 around May 23 (±9.2 days) (Table 2). The value for mean annual peak NPP exhibits substantial interannual variability (Figure 8), ranging from 786 mg C m−2 d−1 in 2009 to 1240 mg C m−2 d−1 in 2003. Rates of daily NPP remain relatively high throughout June and July (600–700 mg C m−2 d−1), during which time the sea ice begins to retreat more rapidly. In August, daily NPP begins to decline, reaching ∼425 mg C m−2 d−1 by the end of the month and falling to ∼100 mg C m−2 d−1 by the end of September, as the sea ice begins to advance again (Figure 8). In general, the phytoplankton bloom (defined as the period when mean daily NPP exceeds 500 mg C m−2 d−1) in the Arctic Ocean lasted an average of 107 ± 9.7 days and exhibited no significant secular trend over the 12 year study period (Table 2).

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Figure 8. Annual cycle of mean open water area (thin black line) and mean daily net primary production (thick black line) for the Arctic Ocean averaged for the years 1998–2009. Also shown for reference are the net primary production time series for the 12 different years (thin gray lines).

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3.1.3.2. Annual NPP per Unit Area

[26] Annual NPP per unit area in the Arctic Ocean averaged a surprisingly uniform 101 ± 4.8 g C m−2 yr−1 between 1998 and 2009 (Table 2). There was no statistically significant secular trend in annual NPP per unit area during this 12 year period and productivity per unit area was not significantly correlated with either the mean annual open water area (R2 = 0.08, p = 0.360) or the length of the open water season (R2 = 0.02, p = 0.659) (Table 3).

Table 3. R2 Values for Regression Analysis of Annual Primary Production Against Year, Mean Open Water Area (106 km2), and Length of Growing Season (Days) by Geographic Sector for 1998–2009a
 Annual Primary Production (g C m−2 yr−1)Annual Primary Production (Tg C yr−1)
YearOpen Water AreaOpen Water SeasonYearOpen Water AreaOpen Water Season
  • a

    Bold indicates significant negative secular trend between 1998 and 2009. Asterisks indicate significant secular trend between 1998 and 2009 (*, p < 0.05; **, p < 0.01; ***, p < 0.001).

Greenland0.46*0.040.120.41*0.020.00
Barents0.000.020.000.210.57**0.40*
Kara0.000.010.020.40*0.66***0.64**
Laptev0.000.170.040.140.77***0.61**
Siberian0.010.110.040.43*0.91***0.71***
Chukchi0.030.000.000.49*0.76***0.69***
Beaufort0.110.010.030.030.90***0.80***
Baffin0.290.000.000.060.310.13
Arctic0.160.080.020.49*0.77***0.73***
3.1.3.3. Total Annual NPP

[27] Annual phytoplankton NPP integrated over the entire Arctic Ocean averaged 493 ± 41.7 Tg C yr−1 between 1998 and 2009. This value should be considered conservative since it does not include productivity under the sea ice, which can be substantial [Lee et al., 2010]. The high degree of interannual variability was marked by a statistically significant 20% secular increase in annual NPP over that 12 year time period (Figure 6b), with the lowest rate measured in 1999 (441 Tg C yr−1) and the highest in 2007 (585 Tg C yr−1). On average, annual NPP increased by 8.1 Tg C each year between 1998 and 2009 and, although the increase was not temporally uniform, the last four years exhibited the highest rates of annual NPP of the 12 year record. As noted previously by Pabi et al. [2008] and Arrigo et al. [2008a], annual rates of pan-Arctic Ocean NPP are highly correlated with the mean annual open water area (Figure 9a) and the length of the open water season (Figure 9b).

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Figure 9. Relationship between total annual net primary production and (a) mean open water area and (b) length of the growing season for the years 1998–2009.

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3.2. Spatial Variability

3.2.1. Open Water Area

[28] Not surprisingly, since the boundaries defined for the eight geographic sectors resulted in them all being different sizes, the amount of open water area in each sector varied as well. Nevertheless, some important spatial differences in sea ice dynamics were discernable, both between sectors and between years within a given sector. The most striking differences in open water area were between the two Atlantic-dominated sectors (Greenland and Barents), both of which contained a high proportion of open water year-round, and the other six sectors, which were much more heavily dominated by sea ice (Figure 10). Despite large differences in the proportion of open water area in the eight geographic sectors, the timing of peak open water area was surprisingly uniform (Table 2), ranging from August 27 (±10.3 days) in the Greenland sector to September 15 (±13.5 days) in the Kara sector (by contrast, the date of peak NPP varied by 60 days between sectors).

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Figure 10. Annual cycle of mean open water area (thin black line) and mean daily net primary production (thick gray line) for the eight geographic sectors of the Arctic Ocean averaged for the years 1998–2009. Boundaries of the geographic sectors are shown in Figure 1.

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[29] Secular trends in mean annual open water area differed markedly by geographic sector (Figure 11). While the entire Arctic Ocean exhibited a significant secular increase in annual mean open water area, this was not true of all geographic sectors. The Greenland (Figure 11a), Laptev (Figure 11d), Beaufort (Figure 11g), and Baffin (Figure 11h) sectors exhibited no significant trend in mean annual open water area between 1998 and 2009, either because of very low interannual variability (Greenland and Baffin) or very high interannual variability (Beaufort and Laptev). Of those sectors that exhibited significant secular increases in mean annual open water area (Kara, Barents, Siberian, and Chukchi), the Siberian sector (Figure 11e) exhibited the largest percent increase between 1998 and 2009 (∼400%) and the Barents (Figure 11b) the smallest (∼20%).

image

Figure 11. Yearly trends in mean open water area for the eight geographic sectors of the Arctic Ocean shown in Figure 1. Trends were significant for the Barents, Kara, Siberian, and Chukchi sectors.

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3.2.2. Length of Open Water Season

[30] The length of the open water season (as defined in section 2.2.3) varied widely by geographic sector, ranging from 63.4 ± 30.9 days in the Siberian sector to 212 ± 63.3 days in the Barents (Table 2), as compared to 100 ± 12.4 days for the entire Arctic. Open water season was longest in the Greenland and Barents sectors, owing to their high proportion of persistently open water, and lowest in the Siberian and Laptev. Five of the eight geographic sectors exhibited statistically significant secular increases in the length of the open water season between 1998 and 2009 (Table 2). The largest such increase was observed in the Barents sector, where the length of the open water season rose by an average of 12.5 days each year between 1998 and 2009. The Siberian, Kara, and Chukchi sectors also experienced large secular increases in the length of the open water season (6.4, 5.5, and 4.5 days per year, respectively). The secular increase in the Baffin sector was much smaller (2.5 days per year), but still statistically significant.

3.2.3. Net Primary Production
3.2.3.1. Annual Cycle

[31] As described briefly in section 3.1.3, phytoplankton blooms in the Arctic Ocean begin first in the permanently ice-free regions of the Greenland (Figure 10a), Barents (Figure 10b), and to a much lesser extent, Baffin (Figure 10h) sectors, with rates of NPP increasing sharply in early March. NPP in the other sectors remains low until about a month later. In all sectors, rates of NPP per unit area continue to increase throughout the spring before reaching their annual maximum, although both the peak rate of NPP and the date when this peak is reached varies widely between sectors. In general, the peak daily NPP attained during the phytoplankton bloom was lowest in the western Arctic (Baffin, Greenland, Beaufort, and Chukchi sectors) and highest in the east (Kara, Barents, Siberian, and Laptev sectors), ranging from 780 to 999 mg C m−2 d−1 and 1143–1463 mg C m−2 d−1, respectively (Figure 10). In addition, four of the eight sectors (Greenland, Barents, Chukchi, and Baffin) reached their productivity peak relatively early in the year, almost always during a 2 week period from May 24 to June 11 (Table 2 and Figure 10). In contrast, the phytoplankton bloom in the other four sectors (Kara, Laptev, Siberian, and Beaufort) reached its peak about a month and a half later, during a 2 week window from July 5 to July 21.

[32] Not surprisingly, the length of the phytoplankton bloom, defined here as the number of days that mean daily NPP exceeded 500 mg C m−2 d−1 (Figure 10) also varied markedly by geographic sector, ranging from a mere 48.5 ± 21.2 days in the Baffin to 119 ± 16.1 days in the Chukchi (Table 2). In general, sectors in the western Arctic Ocean (Greenland, Baffin, and Beaufort) had much shorter blooms than those in the east. Interestingly, only the Greenland and Barents sectors exhibited statistically significant secular changes in the length of the phytoplankton bloom between 1998 and 2009, with the bloom lasting progressively longer in the Barents and shorter in the Greenland.

[33] Based on the timing of the open water peak and NPP peak (Figure 10), the Arctic can be divided into early blooming and late blooming regions. The early bloomers include the Barents, Greenland, Baffin, and Chukchi Sectors, where the peak in phytoplankton production preceded the peak in open water area by 81–120 days. In contrast, the late bloomers, which included the Siberian, Beaufort, Kara, and Laptev sectors, exhibited rates of phytoplankton productivity that peaked within 36–60 days of the peak in open water area. While the existence of these two distinct temporal patterns is interesting, we were unable to determine its cause. The pattern was driven mainly by regional differences in the timing of peak daily NPP, since the peak in open water area was relatively consistent across regions. However, the timing of this peak was not correlated to shelf area, sea ice cover, annual NPP, mean Chl a, or any other metric we tested.

3.2.3.2. Annual NPP per Unit Area

[34] The western Arctic Ocean (Baffin, Greenland, Beaufort, and Chukchi sectors) exhibited the lowest rates of annual NPP per unit area averaged over the 1998–2009 time period (Table 2), following the same pattern as the annual peak daily NPP (Figure 10). Annual NPP in these western sectors ranged from 71.3 ± 11.0 g C m−2 yr−1 in the Beaufort sector to 96.9 ± 7.4 g C m−2 yr−1 in the Chukchi. In the more productive eastern Arctic Ocean, mean rates of annual NPP between 1998 and 2009 ranged from 101 ± 15.8 in the Siberian sector to 121 ± 20.2 in the Laptev. Although rates of annual NPP for the Siberian and Laptev sectors are much higher than those reported by Sakshaug [2003] based on in situ data, it should be noted that very little in situ data are available for either the East Siberian or the Laptev Seas [Matrai et al., 2011].

[35] Only the Greenland sector exhibited a statistically significant secular trend in annual NPP per unit area between 1998 and 2009, dropping by about 15% over the course of the 12 year time series. With the exception of this secular decrease in the Greenland sector, there was no statistically significant relationship between annual NPP per unit area and any other variable investigated, including the amount of open water area and the length of the open water season (Table 3).

3.2.3.3. Total Annual NPP

[36] Because it is calculated from both the area of open water and NPP per unit area, total annual NPP in the Arctic Ocean was by far the highest in the Greenland and Barents sectors (Table 2), the two sectors with the most open water (Figure 10). With rates of total annual NPP of 148 ± 10.8 Tg C yr−1 and 132 ± 18.0 Tg C yr−1, respectively, these two sectors accounted for 57% of total annual NPP in the Arctic Ocean between 1998 and 2009. The remaining sectors more closely followed the spatial pattern displayed by annual NPP per unit area, with the most productive of those sectors (Kara and Laptev) being located in the eastern Arctic. Although the Siberian sector (the other eastern Arctic sector) had relatively high NPP per unit area, it also had the least amount of open water of any of the geographic sectors, which accounted for its low rate of total annual NPP. Because of its low rate of NPP per unit area, the Beaufort sector had the lowest rate of total annual NPP (24.1 ± 7.3 Tg C yr−1) of any geographic sector, despite its relatively large amount of open water (Table 2).

[37] Total annual NPP was significantly correlated with both open water area and the length of the open water season in all geographic sectors except for Greenland and Baffin (Table 3), illustrating the importance of the amount of open water in determining rates of total NPP in Arctic waters. This does not mean, however, that secular changes in total annual NPP over time (Figure 12) are controlled solely by interannual changes in sea ice cover. For example, the Barents sector exhibited a statistically significant increase in open water area between 1998 and 2009, but these changes explained only 31% of the variance in total annual NPP. Alternatively, Greenland exhibited a significant decline in annual NPP with no corresponding changes in sea ice cover. However, of the four geographic sectors that exhibited statistically significant increases in open water area (Barents, Kara, Siberian, Chukchi), three also exhibited significant changes in total annual NPP (Kara, Siberian, Chukchi). Furthermore, of the four geographic sectors that exhibited no statistically significant change in open water area (Greenland, Laptev, Beaufort, and Baffin), three also exhibited no significant changes in total annual NPP (Laptev, Beaufort, and Baffin).

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Figure 12. Yearly trends in total annual net primary production for the eight geographic sectors of the Arctic Ocean shown in Figure 1. Trends were significant for the Greenland, Kara, Siberian, and Chukchi sectors.

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[38] Of those sectors that exhibited significant secular trends in total annual NPP, the largest absolute secular increase was measured in the Kara sector, where annual NPP increased by an average of 2.7 Tg C yr−1 each year between 1998 and 2009, representing a total increase of 70% over the 12 year time series. On a percentage basis, the largest secular increase was in the Siberian sector, where the average annual increase in NPP of 1.9 Tg C yr−1 amounted to a net change of 135% over the 12 year time series. The secular increase in NPP was smallest in the Greenland sector, which exhibited a 1.9 Tg C yr−1 drop in total annual NPP each year, for a net decline of 13% between 1998 and 2009.

4. Discussion

  1. Top of page
  2. Abstract
  3. 1. Introduction
  4. 2. Methods
  5. 3. Results
  6. 4. Discussion
  7. Acknowledgments
  8. References
  9. Supporting Information

[39] Although Pabi et al. [2008] and Arrigo et al. [2008a] presented data for the Arctic Ocean suggesting that annual NPP has been increasing over time, both studies spanned too short of a time period for the patterns they observed to have statistical significance. Furthermore, these two studies used SeaWiFS data from reprocessing 5.2 (R2007), which suffered from an instrument calibration artifact that was removed in the latest reprocessing (R2009.1). This artifact resulted in Chl a anomalies that grew increasingly worse throughout the SeaWiFS mission. Reprocessing R2009.1 eliminated these anomalies and as a result, all anomalous trends in the data have been removed. Despite this change, estimates of annual NPP made using the newly reprocessed SeaWiFS data are still within 10% of the previous estimates made by Pabi et al. [2008] and Arrigo et al. [2008a]. Moreover, now that the newly reprocessed ocean color time series has reached a length of 12 years, we are able to report for the first time that there has been a statistically significant 20% increase in NPP between 1998 and 2009. Secular increases during this time period were largest on the continental shelves of the Chukchi, East Siberian, Laptev, and Kara Seas, as had been shown previously by Arrigo et al. [2008a].

[40] Furthermore, we found that this 20% increase in annual NPP between 1998 and 2009 was accompanied by a 45 day (51%) increase in the length of the open water season, driven largely by earlier sea ice retreat in the spring. Given the high correlation between total annual primary production for a given year and both its mean annual open water area (R = 0.88) and length of the open water season (R = 0.85), we conclude that increases in total productivity of the Arctic Ocean over the last 12 years were driven largely by reductions in the persistence and extent of sea ice cover. This is consistent with a predominantly light-limited system, as had been proposed for the Arctic Ocean by Walsh et al. [2005]. This conclusion is further supported by our observation that rates of NPP per unit area in the Arctic Ocean have not changed during this same period (except for the small decline observed in the Greenland sector). Thus, as the amount of open water has increased both in extent and duration since 1998, total primary production has increased proportionally, with rates of NPP per unit area remaining virtually unchanged.

[41] We can take advantage of the strong relationship between sea ice cover and total annual NPP to infer rates of annual NPP both in the past when sea ice cover was greater, and in the future, as sea ice continues to decline. A convenient sea ice cover metric to use for this purpose is the summer minimum sea ice extent, which is widely used to characterize the state of the Arctic ice pack, is strongly correlated to total annual NPP (R = 0.82), and has been predicted to disappear as early as the first half of this century [Wang and Overland, 2009]. Over the last three decades, the summer minimum sea ice cover has decreased 40%, from approximately 7.5 × 106 km2 to 4.5 × 106 km2 (Figure 13a). Moreover, the annual rate of decline between 1995 and 2009 was about fourfold greater than rate of decline during the earlier part of the time series. By combining these data on summer minimum sea ice extent from 1979 to 2009 with the statistical relationship between total annual NPP in the Arctic Ocean and summer minimum sea ice extent from 1998 to 2009 (Figure 13b), we can estimate levels of NPP during years prior to the availability of SeaWiFS and MODIS data (open squares in Figure 13c).

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Figure 13. Changes in (a) the summer minimum sea ice cover for the Arctic Ocean between 1979 and 2009 and (b) total annual net primary production as a function of summer minimum sea ice cover for the Arctic Ocean between 1998 and 2009. (c) Estimates of annual net primary production made both prior to the launch of SeaWiFS (open squares) by combining Figures 13a and 13b and after the launch of SeaWiFS and MODIS Aqua using the primary production algorithm of Arrigo et al. [2008b] (closed squares).

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[42] Results of this analysis suggest that between 1979 and 1998, total Arctic NPP likely averaged 438 ± 21.5 Tg C yr−1, and although the secular trend during this time was positive (Figure 13c), increasing at a rate of ∼1.5 Tg C yr−1 due to the corresponding decline in minimum summer sea ice extent (Figure 13a), the trend was not statistically significant (R2 = 0.15, p = 0.097). This estimated rate of increase in annual NPP during the 20 year period between 1979 and 1998 was only ∼20% of the measured secular increase measured between 1998 and 2009 (Figure 13c). Thus, both the magnitude of interannual variability in annual Arctic NPP and its secular rate of increase have been dramatically higher over the last 12 years than they likely were in years prior to 1998.

[43] Our results show that as the rate of sea ice decline has increased in recent years, annual NPP has increased at an even faster rate. This suggests that if sea ice extent continues to decline in the future as predicted, annual NPP in the Arctic Ocean is likely to rise even further. To gain some understanding about how large an increase we might expect, we can extrapolate forward in time using the relationship between annual NPP and summer minimum ice cover shown in Figure 13b. This slope of the regression indicates that for every 106 km2 reduction in summer minimum ice cover between 1998 and 2009, annual NPP increased by ∼41 Tg C yr−1. Furthermore, the intercept of the regression shows that once summer minimum ice cover drops to zero, probably sometime during the first half this century [Wang and Overland, 2009], annual NPP in the Arctic Ocean can be expected to reach ∼730 Tg C yr−1. This value is even higher than the 673 Tg C yr−1 estimated by Arrigo et al. [2008a] using a similar approach. The difference between the two values stems from fact that rates of annual NPP have remained high since 2007 (the last year used in the Arrigo et al. [2008a] analysis), resulting in a steeper slope to the regression of annual NPP against summer minimum ice cover. Thus, current annual rates of NPP for the Arctic Ocean are already 26% higher than they were in 1979 and may increase by an additional 37% over current levels by the middle of this century. This rate of increase in annual NPP is much higher than the 6% increase predicted for the Canadian Beaufort Sea for the time period between 1975 and 1992 and 2042–2059 using a global climate model [Lavoie et al., 2010].

[44] It is not clear whether the inferred 26% increase in annual NPP in the Arctic Ocean since 1979 would have required additional nutrient inputs into Arctic surface waters in association with the reduction in sea ice cover or whether the phytoplankton blooms could persist for a longer period of time using a combination of existing inventories and recycled nutrients. The fact that annual NPP did not increase significantly between 1998 and 2009 indicates that no additional nutrients would have been required to support the 20% increase in NPP during that time period. However, this might not be the case for the larger 26% increase in annual NPP between 1979 and 2009. The distinction between the use of new or recycled nutrient sources is important because while the former will support additional higher trophic level production, the latter will not.

[45] In support of the former scenario, Arrigo et al. [2008a] showed that the largest recent increases in annual NPP were associated with the productive continental shelves on the Pacific side of the Arctic Ocean, shallow areas that may be more conducive to additional nutrient loading through episodic advection and vertical mixing events [Tremblay et al., 2008]. More importantly, Lalande et al. [2009] measured rates of organic matter export over the continental slope of the Laptev Sea that were twice as high in 2007 (the year of highest NPP) as in 2005–2006. These authors concluded that increased productivity associated with decreased Arctic sea ice extent could sustain additional export fluxes. Assuming that export is a reasonable proxy for new production, these higher export fluxes suggest that more nitrate is being consumed by phytoplankton in Arctic surface waters during years of reduced sea ice cover. Therefore, elevated rates of NPP in recent years may also represent an increase in annual new production, potentially supporting more robust pelagic and benthic ecosystems.

[46] Future increases in annual NPP, such as those calculated above, may require that additional nutrients be added to Arctic surface waters [Walsh et al., 2005]. There are a number of ways that this could happen. As sea ice continues to recede and the incidence of storms intensifies [Yang et al., 2004], upwelling events at the shelf break may increase in frequency and intensity [Carmack and Chapman, 2003], eroding the halocline and bringing nutrient-rich deeper waters nearer the surface where they can be consumed by phytoplankton. Pickart et al. [2009] has shown that in the Beaufort Sea, these upwelling events are capable of moving Atlantic waters from the deeper basins up onto the continental shelf. If these processes continue to erode the halocline as the sea ice retreats further from the shelf break, large subhalocline nutrient reservoirs could be tapped, potentially supporting even larger increases in annual NPP in the Arctic.

[47] Another potential source of nutrients to the increasingly productive Pacific sector of the Arctic Ocean is via increased flow through the Bering Strait. Using a series of year-round moorings, Woodgate et al. [2006] reported that the annual mean northward current velocity from the Bering Sea into the Arctic Ocean rose from ∼13 cm s−1 in 2001 to ∼23 cm s−1 in 2004, corresponding to an increase in flow from 0.7 to 1.0 Sv (assuming homogeneous barotropic flow across the strait). Although nutrient concentrations were not measured during that study, most of this flow was composed of nutrient-rich Anadyr Water (the low nutrient Alaska Coastal Current accounted for only 10% of the annual mean volume flux), suggesting that the flux of nutrients into the Pacific sector of the Arctic Ocean would have increased between 2001 and 2004. Perhaps significantly, annual NPP in the Pacific sectors of the Arctic Ocean nearest the strait (Chukchi, Beaufort and Siberian sectors) also increased between 2001 and 2004. At this time, it is not possible to determine if increased nutrient flux played a role in elevating NPP in these waters, particularly since open water area increased during this time as well (Figure 11). It is noteworthy, however, that total annual NPP in the Beaufort Sea increased between 2003 and 2004, despite a decline in open water area, suggesting that increased nutrient flux may have played a role.

[48] The secular increase in annual NPP in the Arctic Ocean over the last 12 years is surprisingly large and suggests that the system is being altered in ways that we do not yet understand. In particular, processes that could potentially bring new nutrients into Arctic surface waters, either through advection from adjacent seas or via erosion of the halocline, need to be better characterized. Efforts are currently underway to provide a more quantitative estimate of nutrient fluxes through the Bering Strait, notably through the Russian-American Long-term Census of the Arctic (RUSALCA) program (http://www.arctic.noaa.gov/aro/russian-american/). Once a longer time series on flows and their associated nutrient inventories becomes available, it will be possible to relate longer-term trends in nutrient fluxes from the Bering Sea to the Arctic Ocean to changes in annual NPP like those reported here. In addition, the Pacific Arctic Group (PAG) (http://pag.arcticportal.org/) has identified a number of Distributed Biological Observatories (DBO) in the Pacific sector of the Arctic Ocean that in the coming years will be sampled repeatedly each year, including for hydrography and nutrients. This international program (U.S., Canada, China, Japan, Korea) began its pilot phase with two sites sampled approximately 10 times each between June 15 and September 23, 2010, one in the southern Chukchi Sea (67°40.2 N, 168°57.6 W) and one in Barrow Canyon (71°24.8 N, 157°29.9 W). Programs such as these will provide improved understanding of the critical processes that control biological productivity in the Arctic Ocean both on seasonal and interannual timescales. Once this is achieved, we will be much better equipped to assess how ecosystems are being affected by ongoing changes in the environment, including decreased sea ice cover and increased NPP, and predict the trajectory and impact of these changes in the future.

Acknowledgments

  1. Top of page
  2. Abstract
  3. 1. Introduction
  4. 2. Methods
  5. 3. Results
  6. 4. Discussion
  7. Acknowledgments
  8. References
  9. Supporting Information

[49] This research was supported by NASA grants NNG05GC92G and NNX10AF42G and NSF grant ARC-0731524 to K. Arrigo. We thank P. Matrai for access to the ARCSS-PP database.

References

  1. Top of page
  2. Abstract
  3. 1. Introduction
  4. 2. Methods
  5. 3. Results
  6. 4. Discussion
  7. Acknowledgments
  8. References
  9. Supporting Information

Supporting Information

  1. Top of page
  2. Abstract
  3. 1. Introduction
  4. 2. Methods
  5. 3. Results
  6. 4. Discussion
  7. Acknowledgments
  8. References
  9. Supporting Information
FilenameFormatSizeDescription
jgrc12141-sup-0001-t01.txtplain text document1KTab-delimited Table 1.
jgrc12141-sup-0002-t02.txtplain text document1KTab-delimited Table 2.
jgrc12141-sup-0003-t03.txtplain text document1KTab-delimited Table 3.

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