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Melting glaciers help fuel productivity hotspots around Antarctica

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Presentation on theme: "Melting glaciers help fuel productivity hotspots around Antarctica"— Presentation transcript:

1 Melting glaciers help fuel productivity hotspots around Antarctica
Kevin R. Arrigo Gert van Dijken Stanford University 1

2 Antarctic polynyas Areas of open water surrounded by sea ice
Can be identified with SSM/I satellite data Based on days of open water Red = Max Blue = Min Polynyas are blue areas near coast 2

3 Antarctic polynyas Hot spots of primary production (g C m-2 yr-1) 40
80 120 160 200 Hot spots of primary production (g C m-2 yr-1) 3

4 Antarctic polynyas Hot spots of primary production (g C m-2 yr-1)
Ann Adelie Penguins vs. Polynya Productivity Hot spots of primary production (g C m-2 yr-1) Can support high densities of marine mammals and birds Mean colony size (1000 pairs) R2 = 0.63 Annual production (mg C m-2 yr-1) Arrigo and Van Dijken (2003) 4

5 Anthropogenic CO2 flux (g C m-2 yr-1)
Antarctic polynyas Anthropogenic CO2 flux (g C m-2 yr-1) Hot spots of primary production (g C m-2 yr-1) Can support high densities of marine mammals and birds Large sinks for anthropogenic CO2 Ross Sea Arrigo et al. (2008) 5

6 Question: What controls phytoplankton abundance in Antarctic coastal polynyas? Phaeocystis antarctica Photo: John Weller 6

7 Approach SeaWiFS For : Used satellite data to identify polynyas, track changes in sea ice, measure chlorophyll a concentration, and calculate primary production (Arrigo et al. 2008) SSM/I AVHRR 7

8 Atlantic Ocean ANTARCTICA Indian Ocean Pacific Ocean 8

9 Annual mean phytoplankton abundance in 46 coastal polynyas
Pacific Atlantic Indian Pacific Chlorophyll a (mg m-3) Polynya number 9

10 Annual mean phytoplankton abundance in 46 coastal polynyas
Not controlled by light or temperature (p > 0.05) Pacific Atlantic Indian Pacific Chlorophyll a (mg m-3) Polynya number 10

11 Annual mean phytoplankton abundance in 46 coastal polynyas
Related to width of local continental shelf Pacific Atlantic Indian Pacific Chlorophyll a (mg m-3) Shelf width (km) Polynya number 11

12 Annual mean phytoplankton abundance in 46 coastal polynyas
Related to width of local continental shelf R2 = 0.40 p < 0.01 Pacific Atlantic Indian Pacific Chlorophyll a (mg m-3) Shelf width (km) Chlorophyll a (mg m-3) Shelf width (km) Polynya number 12

13 Highest seawater iron concentrations are on the shelf
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 13

14 What other factors control phytoplankton abundance in coastal polynyas?
Pacific Atlantic Indian Pacific Chlorophyll a (mg m-3) Polynya number 14

15 37 of 46 coastal polynyas are adjacent to melting ice shelves
What other factors control phytoplankton abundance in coastal polynyas? 37 of 46 coastal polynyas are adjacent to melting ice shelves Pacific Atlantic Indian Pacific Chlorophyll a (mg m-3) Polynya number 15

16 37 of 46 coastal polynyas are adjacent to melting ice shelves
What other factors control phytoplankton abundance in coastal polynyas? 37 of 46 coastal polynyas are adjacent to melting ice shelves Basal melt rates are now available (Rignot et al. 2013) Pacific Atlantic Indian Pacific Basal melt rate (Gt yr-1) Chlorophyll a (mg m-3) Polynya number 16

17 Basal melt rate (Gt yr-1)
What other factors control phytoplankton abundance in coastal polynyas? R2 = 0.59 p < 0.01 Pacific Atlantic Indian Pacific Chlorophyll a (mg m-3) Basal melt rate (Gt yr-1) Basal melt rate (Gt yr-1) Chlorophyll a (mg m-3) Polynya number 17

18 What about coastal polynyas not near ice shelves?
Pacific Atlantic Indian Pacific Basal melt rate (Gt yr-1) Chlorophyll a (mg m-3) Polynyas w/o ice shelf = 0.44±0.19 mg m-3 Polynya number 18

19 Basal melt rate (Gt yr-1)
What about coastal polynyas not near ice shelves? Pacific Atlantic Indian Pacific Chlorophyll a (mg m-3) y-intercept = 0.40 mg m-3 Basal melt rate (Gt yr-1) Basal melt rate (Gt yr-1) Chlorophyll a (mg m-3) Polynyas w/o ice shelf = 0.44±0.19 mg m-3 Polynya number 19

20 Basal melt rate (Gt yr-1)
What about coastal polynyas not near ice shelves? Very productive polynyas require input of glacial meltwater Pacific Atlantic Indian Pacific Chlorophyll a (mg m-3) y-intercept = 0.40 mg m-3 Basal melt rate (Gt yr-1) Basal melt rate (Gt yr-1) Chlorophyll a (mg m-3) Polynyas w/o ice shelf = 0.44±0.19 mg m-3 Polynya number 20

21 Ice sheets grind up bedrock as they flow to sea
Why the relationship between phytoplankton abundance and basal melt rate of nearby ice shelves? Ice sheets grind up bedrock as they flow to sea Particulate and dissolved iron is released into seawater Facilitated by upwelling of warm CDW Iron taken up by growing phytoplankton Phytoplankton bloom (CDW) 21

22 Ice sheets grind up bedrock as they flow to sea
Why the relationship between phytoplankton abundance and basal melt rate of nearby ice shelves? Ice sheets grind up bedrock as they flow to sea Particulate and dissolved iron is released into seawater Facilitated by upwelling of warm CDW Iron taken up by growing phytoplankton DynaLiFe Cruise Dissolved iron (nM) Chlorophyll > 10 mg m-3 0.8 Chlorophyll > 5 mg m-3 100 0.6 Depth (m) 0.4 200 0.2 300 250 200 150 100 50 Distance from Pine Island Glacier (km) Modified from Gerringa et al. (2012) 22

23 CONCLUSIONS Even coastal Antarctic polynyas are iron limited
Together, basal melt rate and continental shelf width explain 70% of variance in phytoplankton abundance in coastal polynyas Basal melt rate and shelf width are weakly correlated with each other (R2=0.19) Antarctic polynyas are a 0.2 Pg C yr-1 sink for anthropogenic CO2 Larger than entire high latitude Southern Ocean No interannual trends over 15 year time series However, if the rate of ice sheet melting accelerates, polynyas could become even more productive in the future 23

24 THANK YOU! Ocean Biology and Biogeochemistry
Cryosphere Science Program


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