1 How do Various Iron Sources Fuel Phytoplankton Growth in the Southern Ocean? What Factors Control Phytoplankton Abundance in Coastal Polynyas? Kevin R. Arrigo Gert van Dijken Stanford University
2 Antarctic polynyas Areas of open water surrounded by sea ice Can be identified with SSM/I satellite data Based on days of ice cover Red = Max Blue = Min Polynyas are blue areas near coast
3 Antarctic polynyas 40 80 120 160 200 Hot spots of primary production (g C m -2 yr -1 )
4 Antarctic polynyas Hot spots of primary production (g C m -2 yr -1 ) Can support high densities of marine mammals and birds Adelie Penguins vs. Polynya Productivity Mean colony size (1000 pairs) Ann R 2 = 0.63 Annual production (mg C m -2 yr -1 ) Arrigo and Van Dijken (2003)
5 Antarctic polynyas Hot spots of primary production (g C m -2 yr -1 ) Can support high densities of marine mammals and birds Seal Pups vs. Polynya Productivity Weddell seal pups weaned R 2 = 0.75 Annual production (mg C m -2 yr -1 ) Paterson et al. (submitted)
6 Antarctic polynyas Hot spots of primary production (g C m -2 yr -1 ) CO 2 flux (g C m -2 yr -1 ) Can support high densities of marine mammals and birds Large sinks for atmospheric CO 2 Ross Sea Arrigo et al. (2008)
Question: What factors control phytoplankton abundance in Antarctic coastal polynyas? Factors investigated for each polynya: Area of open water Number of days of open water Mean daily PAR during growing season Sea surface temperature Continental shelf width Basal melt rate of nearby glaciers (Rignot et al. 2013) Photo: John Weller Phaeocystis antarctica 7
Approach SeaWiFS For 1998-2013: Used satellite data to identify polynyas, track changes in sea ice, measure SST and chlorophyll a concentration, and calculate primary AVHRR production SSM/I 8
9 8 9 7 6 5 4 3 Ocean Atlantic Ocean 10 2 17 18 13 141516 12 11 1 19 20 21 ANTARCTICA 46 45 44 43 42 41 40 22 23 24 2526 27 28 29 30 31 32 33 34 35 36 37 38 39 Indian Ocean
Annual mean phytoplankton abundance in 46 coastal polynyas 2.5 Atlantic Indian Chlorophyll a (mg m -3 ) 2.0 1.5 1.0 0.5 0.0 1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 Polynya number 10
Annual mean phytoplankton abundance in 46 coastal polynyas Related to annual mean sea surface temperature Warmer temperatures promote higher Chl a Strongest relationship in Atlantic sector 2.5 Atlantic Indian 0 Chlorophyll a (mg m -3 ) 2.0 1.5 1.0 0.5-0.2-0.4-0.6-0.8-1.0-1.2 Temperature ( C) 0.0 1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 Polynya number -1.4 11
Annual mean phytoplankton abundance in 46 coastal polynyas Chlorophyll a (mg m -3 ) 2.5 2.0 1.5 1.0 0.5 Atlantic Chlorophyll a (mg m -3 ) 2.5 2.0 1.5 1.0 0.5 0.0 Indian -1.5-1.0-0.5 0.0 Temperature ( C) R 2 = 0.41 p < 0.01 0-0.2-0.4-0.6-0.8-1.0-1.2 Temperature ( C) 0.0 1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 Polynya number -1.4 12
What other factors control phytoplankton abundance in coastal polynyas? 2.5 Atlantic Indian Chlorophyll a (mg m -3 ) 2.0 1.5 1.0 0.5 0.0 1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 Polynya number 13
14 What other factors control phytoplankton abundance in coastal polynyas? Related to width of local continental shelf Relationship about equally strong in all sectors 2.5 Atlantic Indian 700 Chlorophyll a (mg m -3 ) 2.0 1.5 1.0 0.5 600 500 400 300 200 100 Shelf width (km) 0.0 1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 Polynya number 0
15 What other factors control phytoplankton abundance in coastal polynyas? Chlorophyll a (mg m -3 ) 2.5 2.0 1.5 1.0 0.5 Atlantic Chlorophyll a (mg m -3 ) 2.5 2.0 1.5 1.0 0.5 0.0 Indian 0 200 400 600 Shelf width (km) R 2 = 0.40 p < 0.01 700 600 500 400 300 200 100 Shelf width (km) 0.0 1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 Polynya number 0
Why the relationship between phytoplankton abundance and continental shelf width? Highest seawater iron concentrations are on the shelf Wider shelves have larger iron inventory and permit greater entrainment of iron into surface waters (Bruland et al. 2005, Biller et al. 2013) More iron = higher phytoplankton biomass Blue = Low iron concentration Orange = High iron concentration visibleearth.nasa.gov 16
Why the relationship between phytoplankton abundance and continental shelf width? A B Best example is in Ross Sea Large continental shelf Depth (m) A B 0 200 400 600 800 0 200 400 600 800 Marsay et al. (2014) 164 E 168 E 172 E 176 E 180 E Longitude Gerringa et al. (submitted) Blue Low = Low Fe near iron concentration RIS Orange = High iron concentration Ross Ice Shelf Latitude visibleearth.nasa.gov 17 nm 2 1.5 1.0 0.5 0
What other factors control phytoplankton abundance in coastal polynyas? 18 2.5 Atlantic Indian Chlorophyll a (mg m -3 ) 2.0 1.5 1.0 0.5 0.0 1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 Polynya number
What other factors control phytoplankton abundance in coastal polynyas? 39 of 46 coastal polynyas are adjacent to melting ice shelves 19 2.5 Atlantic Indian Chlorophyll a (mg m -3 ) 2.0 1.5 1.0 0.5 0.0 1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 Polynya number
What other factors control phytoplankton abundance in coastal polynyas? 39 of 46 coastal polynyas are adjacent to melting ice shelves Phytoplankton abundance related to basal melt rate Relationship strongest in sector Chlorophyll a (mg m -3 ) 2.5 2.0 1.5 1.0 0.5 Atlantic Indian 180 160 140 120 100 80 60 40 20 0 Basal melt rate (Gt yr -1 ) 0.0 1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 Polynya number 20
What other factors control phytoplankton abundance in coastal polynyas? Chlorophyll a (mg m -3 ) 2.5 2.0 1.5 1.0 0.5 0.0 Atlantic Chlorophyll a (mg m -3 ) 0 50 100 150 200 100 Basal melt rate (Gt yr -1 ) 80 60 40 20 0 1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 2.5 2.0 1.5 1.0 0.5 0.0 Polynya number Indian Indian R 2 = 0.59 p < 0.01 180 160 140 120 Basal melt rate (Gt yr -1 ) 21
Why the relationship between phytoplankton abundance and basal melt rate of nearby ice shelves? Ice sheets grind up bedrock as they flow to sea Ice sheets accumulate Fe-containing dust Particulate and dissolved iron is released into seawater Facilitated by upwelling of warm CDW Iron taken up by growing phytoplankton 22 Phytoplankton bloom (CDW)
Why the relationship between phytoplankton abundance and basal melt rate of nearby ice shelves? Best example is in Amundsen Sea Most rapidly melting glaciers Large Fe flux at face of Pine Island Glacier Fe consumed by phytoplankton in surface waters 0 DynaLiFe Cruise Chlorophyll > 10 mg m -3 Dissolved iron (nm) 0.8 Depth (m) 100 200 Chlorophyll > 5 mg m -3 0.6 0.4 300 250 200 150 100 50 0 Distance from Pine Island Glacier (km) 0.2 0 Modified from Gerringa et al. (2012) 23
24 How much variance in chlorophyll a can be explained by environmental variables? Multiple regression model included: Shelf width SST Basal melt rate Open water area *Number of days of open water *Mean daily PAR *Removed because they had no effect on regression model
25 Some of the predictor variables were significantly but weakly correlated Predictor Predictor R 2 p-value Shelf width SST 0.19 p<0.01 SST Basal melt 0.16 p<0.01 Shelf width Basal melt 0.17 p<0.01 Shelf width Open water 0.20 p<0.01
Multiple linear regression: R 2 = 0.77 Parameter p-value VIF % of R 2 explained Basal melt rate <0.001 1.34 43.6% (Gt yr -1 ) Sea surface temp <0.01 1.42 24.5% ( C) Shelf width <0.01 1.67 19.1% (km) Mean open water <0.05 1.26 12.8% (km 2 ) VIF = Variance Inflation Factor (should be below 2.5) 26
27 CONCLUSIONS Even coastal Antarctic polynyas are iron-limited Light does not control phytoplankton productivity Higher SST increases phytoplankton abundance directly through increased growth rates but possibly also indirectly through increased glacial melting Wide shelves are more productive than narrow ones Greater resuspension of sediment iron Very productive polynyas require input of glacial meltwater Presumably because of additional iron supplies Future increases in glacial melt are likely to increase biological productivity of coastal ecosystems
THANK YOU! Ocean Biology and Biogeochemistry Cryosphere Science Program 28