Microbial food web structure in a changing Arctic

Transcription

1 Microbial food web structure in a changing Arctic Tatiana M Tsagaraki, Jorun K Egge, Gunnar Bratbak, Øystein Leikness, T. Frede Thingstad, Lise Øvreås, Ruth-Anne Sandaa, Elzbieta A. Petelenz-Kurdziel, Maria L. Paulsen, Colin A. Stedmon, Svein Norland, Mikal Heldal and Aud Larsen

2 The microbial food web as seen by the minimum model utilises enough parameters to reproduce FW interactions Who wins the competition for mineral nutrients? Thingstad et al, J.Mar.Sys., 2007

3 3 pathways for nutrients entrance 3 limitation types Organic carbon limitation Affects bacteria Mineral nutrient limitation Affects all Silicate limitation- Affects diatoms Undestanding the food web: nutrient pathways

4 Model predicts pathways according to nutrient availability Does competition between groups work according to model? Challenge model with data

5 Who wins the competition for nutrients? Source:biology.kenyon.edu/ Model: With glucose present HB win Experiment : Combining high glucose and Si diatoms win Model: lots of HF grazers to control bacteria necessary (Results in Havskum et al. 2003)

6 Map source: Norwegian Polar Institute Ny Ålesund, Svalbard 2007, 2008, 2015 Map source: unis.no

7 This time we ask: How are resources allocated & consumed? Same set up- Ny Ålesund August 2007 Ciliates Model: With glucose present HB win Experiment : HB won But no large diatoms appeared Model: Ciliates feed on small diatoms present (Thingstad et al, 2008)

8 So let s make bacteria and diatoms compete Same location, intention to stimulate both bacterial and small/ large diatom pathway- Ny Ålesund 2008 Model: Bacteria vs Small diatoms (HB win) Bacteria vs Large diatoms (diatoms win) Experiment : Small flagellates win. Always. Model: High mesozoo inhibited diatoms HF inhibited bacteria Data in: Larsen et al., 2015

9 What made the difference? PAME I (2007) & PAME II (2008) Low initial mesozoo High initial mesozoo Next question: How do predators control resource allocation?

10 Factors inducing changes in predators and resources in the Arctic Mesozoo. changes due to: Advection Migration patterns Temperature Food availability Predation Spring bloom timing C and nutrient supply due to: Riverine input Meltwater Temperature Light availability Ice cover Spring bloom timing

11 Why is it important? Export Drives the biological and microbial pumps (Carbon storage) Production New biomass & transfers energy to harvestable resources (Fisheries)

12 Ny Ålesund How do predators control resources? Low grazing: Copepods removed Daily addition of dissolved Si, N, P Carbon added daily as glucose Even numbers, odd numbers High grazing: 5x C. glacialis & hyperboreus/ L -1 added Daily addition of dissolved Si, N, P Carbon added daily as glucose

13 Expectation in low zooplankton removes predators of diatoms and bacteria Ciliates increase Bacteria win when OC supply is high Diatoms win when OC supply is low Microbes respond to C (ab. & div.) Working hypothesis: Bacterial consumption of organic carbon is strongly dependent on copepod/ciliate standing stocks

14 : predators of diatoms and bacteria removed Modelled response Ciliates ml -1 Ciliates increase Ciliates/ L Much more ciliates in Most between 20-40μm ESD No correlation with C NB: Even numbers, odd numbers

15 : predators of diatoms and bacteria removed Modelled response Diat Chla µgl -1 Diatoms win when OC supply is low Chla> 10μm in μg/ L Almost no diatoms observed Preliminary diversity data show some diatoms towards the end (B. Edvardsen and E. Egge, UiO)

16 : predators of diatoms and bacteria removed Modelled response 18 x 106 Bact ml Bacteria win when OC supply is high C gradient Bacteria/ml No clear response to C gradient Bacteria in increase also Even numbers, odd numbers

17 : predators of diatoms and bacteria removed 0C Modelled response (not shown) Diversity changes with C addition and time 1C Microbial communities respond to C (ab. & div.) 3C Day 0 Day 11 SAR11 Flavobacteriaceae Porticoccaceae Oceanospirillaceae Psychromonadaceae

18 Expectation in high zooplankton Bacteria abundance is kept low by HF Heterotrophic flagellates(hf) increase Working hypothesis: Bacterial consumption of organic carbon is strongly dependent on copepod/ciliate standing stocks AF win because of low bacteria ab. Community becomes mineral nutrient limited removes diatoms & ciliates

19 removes diatoms & ciliates Modelled response HF ml -1 Heterotrophic flagellates increase High initial mesozoo Heterotrophic nanoflagellates/ L HF start increasing before bacteria NB: Even numbers, odd numbers

20 removes diatoms & ciliates Modelled response 18 x 106 Bact ml Bacteria ab. kept low C gradient Bacteria/ml No C response Increase in last days NB: Even numbers, odd numbers

21 removes diatoms & ciliates Modelled response Chla µgl -1 AF win because of low bacteria ab Chla mg/l 0C More copepods= More Chla Highest Chla in 0C Most Chla in μm fraction

22 removes diatoms & ciliates Modelled response (not shown) Microbial communities are nutrient limited Pearson correlation for particulate elements Correlations shown significant (p <0.01) Coefficient> 0.7 highlighted Tighter correlation in indicates Nutrients are utilised Potential limitation since elements are «locked» in biomass

23 And just when we thought all was figured out TEM Mg/Na ratio increases in C limitation Bacteria become C limited at the end More llimited in Limitation even in the highest C BUT Mg/Na indicates community in dormancy/ repair mode

24 Bacterial activity lower where ab. is high BP per cell is less where bacteria are more Fits with Mg/Na & dormancy Bacteria/ml

25 C N Can it be viruses? Higher virus diversity in Virus composition changes as C increases Size (kb) D-1 1-D1 1-D3 1-D5 1-D7 1-D91-D112-D1 2-D3 2-D5 2-D7 2-D92-D11 1C N More viruses in Size (kb) D1 5-D3 5-D5 5-D7 5-D9 5-D11 6-D1 6-D3 6-D5 6-D7 6-D9 6-D11 3C N Size (kb) Day No 9-D1 9-D3 9-D5 9-D7 9-D9 9-D1110-D110-D310-D510-D710-D910-D11 Sampling day

26 Is it a different community? 0C 1C 3C Diversity changes similar in both In Psychromonads appear earlier and dominate faster Day 0 Day 11 SAR11 Psychromonadaceae

27 Competition and trade- offs in bacterial communities What are the triggers? Bacteria have more predators Abundance is lower Community response to C faster More small autotrophs demand resources Bacteria abundance is high Low activity per cell Communty response to C slower Virus diversity is high More Mg uptake Is there higher competition in? Is the community in in defense mode?

28 Summary of food web implications Nutrient through classic food chain Fewer steps = less energy lost Higher harvestable stock Nutrients to DOM More steps = more energy lost Lower harvestable stock Does reflect what happens if we get a mismatch between occurrence of phytoplankton bloom and copepods? A different story with diatoms? - probably YES!

29 What we learned so far Copepods- Increased production Export to BP Overview Ciliates- Increased Degradation- Export to MCP C addition affects community structure C gradient affects competition and defense strategies New challenges: What are the potential trade offs in microbes? What happens if observed changes persist? How do predators respond? What triggers for changes in strategy? 2 3 What does the flow of elements tell us?

30 Lots of people measured lots of things

31 And some just there for fun UN secretary general Ban Ki-moon visits us in NÅ

32 Bacterial consumption of OC strongly depends on top predator standing stocks Consumption patterns affect both production and export

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