Nutrient- vs. Energy-Limitation in the Sea:

Transcription

1 Nutrient- vs. Energy-Limitation in the Sea: The Red Sea and the Antarctic Ocean as Extreme Case Studies Max M. Tilzer University of Constance, Germany ISEEQS-Meeting, 29 May 1 June 2005 Katsushika Hokusai: The Great Wave Off Kanagawa

2 Why study biological productivity?

3 Reason I: To assess the availability of food for the growing human population The world population increases by 83 million annually 800 million people are undernourished only 12 % of the world s food are currently produced in the water Can the sea produce the needed additional food?

4 CO 2 Reason II: To assess the possible role of the biosphere as a global CO 2 -sink Pre-industrial: Current: Current atmospheric CO 2 levels are the highest since at least 5 million years 280 ppm 367 ppm

5 Questions asked in my talk: (1) Why are the oceans less productive than the continents? (2) Implications for food production and the global carbon cycle The Red Sea and the Southern Ocean will be used as extreme case-studies of marine productivity control

6 Questions asked in my talk: (1) Why are the oceans less productive than the continents? (2) Implications for food production and the global carbon cycle The Red Sea and the Southern Ocean will be used as extreme case-studies of marine productivity control

7 Questions asked in my talk: (1) Why are the oceans less productive than the continents? (2) Implications for food production and the global carbon cycle The Red Sea and the Southern Ocean will be used as extreme case-studies of marine productivity control

8 The Law of the Minimum The resource in shortest supply (minimum factor) controls the biological responses The biological responses to shortage of resources can be either diminished growth yields or slowed growth rates In most cases, nutrients control growth yields, whereas energy controls growth rates In cases of extreme energy shortage, growth yields can be limited by energy

9 The Law of the Minimum The resource in shortest supply (minimum factor) controls the biological responses The biological responses to shortage of resources can be either diminished growth yields or slowed growth rates In most cases, nutrients control growth yields, whereas energy controls growth rates In cases of extreme energy shortage, growth yields can be limited by energy

10 The Law of the Minimum The resource in shortest supply (minimum factor) controls the biological responses The biological responses to shortage of resources can be either diminished growth yields or slowed growth rates In most cases, nutrients control growth yields, whereas energy controls growth rates In cases of extreme energy shortage, growth yields can be limited by energy

11 The Law of the Minimum The resource in shortest supply (minimum factor) controls the biological responses The biological responses to shortage of resources can be either diminished growth yields or slowed growth rates In most cases, nutrients control growth yields, whereas energy controls growth rates In cases of extreme energy shortage, growth yields can be limited by energy

12 Constraints of biological productivity in aquatic habitats...

13 ...or, why are the continents more productive than the sea? Jacob van Ruysdael

14 Resource utilization in the water Part I: Nutrient salt utilization Cells have to overcome two major probelms in the water when taking up dissolved nutrient salts: Problem 1: Slow molecular diffusion in water The diffusion problem is partly overcome by sinking and small body size (enhanced surface-to-volume ratio)

15 Resource utilization in the water I. Nutrient salt utilization (cont d) Problem 2: Extremely low ambient nutrient concentrations Michaelis-Menten uptake kinetics Monod growth kinetics The concentration problem is partly overcome by active transport and nutrient storage

16 By contrast, on land, plants can sequester nutrients at high concentrations from soils

17 however, their problem often is the availability of water

18 Resource utilization in the water Part II: Energy utilization is highly restricted

19 Problem 1: Spectral mismatch: 1. Spectral light absorption by phytoplankton is highly selective Tilzer et al., 1994 phytoplankton light absorption cross-sections

20 Problem 1:: Spectral mismatch (cont d) 2. The spectral components that are required for photosynthesis are rapidly attenuated in the water Sta. 117: low chl. a Sta. 135; high chl. a comparison of ocean background light attenuation with pure water Tilzer et al., 1994 red light is rapidly attenuated in pure water Tilzer et al., 1994 blue light is rapidly attenuated by DOM, even in extremely clear ocean water

21 Problem 2: Small fractional light absorption Tilzer et al., 1985 Productivity per area is a function of fractional light absorption and reaches a saturation plateau at high biomass due to self-shading

22 Problem 3: Mean water column light level decreases with mixing depth If the mixing depth equals the euphotic depth, the average light level within the mixed layer is 21.5 % of the surface value If the mixing depth equals 5 times the euphotic depth, the average light level within the mixed layer is 4.3 % of the surface value. Under such conditions phytoplankton receives insufficient energy for growth From Tilzer 1990 after Riley, 1953 The deeper the mixing, the lower den average light level the phytoplankton is exposed to

23 By contrast, on land, virtually all light impinging onto the Earth s surface is absorbed by photosynthetic tissue

24 The Antarctic Ocean The Red Sea The Red Sea Case-studies Case-studies The Antarctic Ocean

25 The Red Sea: Case-study for a nutrient-limited system

26 The control of primary productivity in the Red Sea 1. Identification of the limiting nutrient species 2. The role of vertical mixing in controlling productivity

27 The control of primary productivity in the Red Sea 1. Identification of the limiting nutrient species 2. The role of vertical mixing in controlling productivity

28 The Role of Nutrients

29 Ambient N vs. P - concentrations Al Qutob et al., in press Ambient N : P ratios throughout the year are close to the Redfield Ratio

30 Nutrient-Stimulation Bioassays Al Qutob et al., in prep Only the combined addition of N and P had a stimulatory effect on phytoplankton growth

31 Possible explanation for co-limitation by N and P: Intense nitrogen fixation by Trichodesmium, which might be supported by high radiant energy availability

32 The Role of Mixing

33 Vertical water column mixing and phytoplankton productivity 1.The greater the mixing depth, the more nutrients are imported into the euphotic zone 2. However, the greater the mixing depth, the smaller the average light within the mixed layer Which factor is more important?

34 Vertical water column mixing and phytoplankton productivity 1.The greater the mixing depth, the more nutrients are imported into the euphotic zone 2. However, the greater the mixing depth, the smaller the average light within the mixed layer Which factor is more important?

35 Vertical water column mixing and phytoplankton productivity 1.The greater the mixing depth, the more nutrients are imported into the euphotic zone 2. However, the greater the mixing depth, the smaller the average light within the mixed layer Question: Which factor is more important?

36 Answer: It depends.

37 Nitrate Profiles Nitrate profiles (top) and Thermal stratification (bottom) mixing depth Temperature Profiles Al Qutob et al., in prep Nitrate in the mixed layer is completely depleted at mixing depths > 300 m?

38 Mixing depth and maximum phytoplankton biomass Interannual variability of chlorophyll no biomass growth if mixing exceeds 450 m Haese et al. in prep. 92 % of the variability of euphotic phytoplankton biomass can be explained by the variability in water column mixing depths

39 At mixing depth under 450 m, nutrient inputs due to vertical mixing will enhance productivity At mixing depth over 450 m, production will no longer rise due to nutrient inputs, as a consequence of yield limitation by energy supply

40 The Antarctic Ocean: Case-study for a predominantly energy-limited system

41

42 Characteristics of the Antarctic Ocean Water temperatures are consistently low (< 2 C) Unstable water column stratification (upper mixed layer > 50 m) Nutrient contrations (nitrate, phosphate, silicate) are high throughout the year. Except during spring ice out and in frontal regions, phytoplankton biomass is consistently low. Iron concetrations are extremely low. The Southern Ocen is the largest HNLC-region of the world ocean.

43 Characteristics of the Antarctic Ocean Water temperatures are consistently low (< 2 C) Unstable water column stratification persists throughout the year (upper mixed layer > 50 m) Nutrient contrations (nitrate, phosphate, silicate) are high throughout the year. Except during spring ice out and in frontal regions, phytoplankton biomass is consistently low. Iron concetrations are extremely low. The Southern Ocen is the largest HNLC-region of the world ocean.

44 Characteristics of the Antarctic Ocean Water temperatures are consistently low (< 2 C) Unstable water column stratification persists throughout the year (upper mixed layer > 50 m) Nutrient concentrations (nitrate, phosphate, silicate) are high throughout the year. Except during spring ice out and in frontal regions, phytoplankton biomass is consistently low. Iron concetrations are extremely low. The Southern Ocen is the largest HNLC-region of the world ocean.

45 Characteristics of the Antarctic Ocean Water temperatures are consistently low (< 2 C) Unstable water column stratification persists throughout the year (upper mixed layer > 50 m) Nutrient concentrations (nitrate, phosphate, silicate) are high throughout the year. Except during spring ice out and in frontal regions, phytoplankton biomass is consistently low. Iron concetrations are extremely low. The Southern Ocen is the largest HNLC-region of the world ocean.

46 Characteristics of the Antarctic Ocean Water temperatures are consistently low (< 2 C) Unstable water column stratification persists throughout the year (upper mixed layer > 50 m) Nutrient concentrations (nitrate, phosphate, silicate) are high throughout the year. Except during spring ice out and in frontal regions, phytoplankton biomass is consistently low. Iron concetrations are extremely low. The Southern Ocen is the largest HNLC-region of the world ocean.

47 Characteristics of the Antarctic Ocean Water temperatures are consistently low (< 2 C) Unstable water column stratification persists throughout the year (upper mixed layer > 50 m) Nutrient concentrations (nitrate, phosphate, silicate) are high throughout the year. Except during spring ice out and in frontal regions, phytoplankton biomass is consistently low. Iron concetrations are extremely low. The Southern Ocen is the largest HNLC-region of the world ocean.

48 Hypotheses explaining HNLCcharacteristics of the Southern Ocean Energy-Hypothesis: Energy supply is short due to deep mixing and brief growing season. Growth hypothesis: Slow phytoplankton growth is due to low temperatures. Grazing hypothesis: Effective grazing, mainly by Euphausia superba keeps phytoplankton biomass low. Iron hypothesis: Phytoplankton growth is slowed by severe iron defficiency.

49 Hypotheses explaining HNLCcharacteristics of the Southern Ocean Energy-Hypothesis: Energy supply is short due to deep mixing and brief growing season. Growth hypothesis: Slow phytoplankton growth is due to low temperatures. Grazing hypothesis: Effective grazing, mainly by Euphausia superba keeps phytoplankton biomass low. Iron hypothesis: Phytoplankton growth is slowed by severe iron defficiency.

50 Hypotheses explaining HNLCcharacteristics of the Southern Ocean Energy-Hypothesis: Energy supply is short due to deep mixing and brief growing season. Growth hypothesis: Slow phytoplankton growth is due to low temperatures. Grazing hypothesis: Effective grazing, mainly by Euphausia superba keeps phytoplankton biomass low. Iron hypothesis: Phytoplankton growth is slowed by severe iron defficiency.

51 Hypotheses explaining HNLCcharacteristics of the Southern Ocean Energy-Hypothesis: Energy supply is short due to deep mixing and brief growing season. Growth hypothesis: Slow phytoplankton growth is due to low temperatures. Grazing hypothesis: Effective grazing, mainly by Euphausia superba keeps phytoplankton biomass low. Iron hypothesis: Phytoplankton growth is slowed by severe iron defficiency.

52 Evidence supporting the Energy Hypothesis

53 The Southern Ocean is the largest upwelling region of the world ocean G. Jacques after Lutjeharms 1981

54 Supporting evidence for the Energy Hypothesis I Frontal enhancement Nitrate Chlorophyll Surface Temp. Phytoplankton biomass is consistently enhanced in oceanic fronts and at the ice margin where water column mixing is diminished. Lutjeharms et al., 1985

55 Supporting evidence for the Energy Hypothesis II Tilzer et al., 1986 In Southern Ocean phytoplankton, both light-saturated and light-limited photosynthesis appear to be temperature-sensitive

56 No supporting evidence for the Growth Hypothesis Growth is the net result of photosynthesis minus respiration photosynthesis growth rate respiration Especially during short days diminished night respiration at low temperatures leads to comparatively high growth rates Respiration is more temperature sensitive than photosynthesis Tilzer & Dubinsky, 1987

57 No supporting evidence for the grazing hypothesis Euphausia superba is an extremely efficient grazer. However, only by dense krill swarms phytoplankton density is significantly affected

58 Supporting evidence for the Iron Hypothesis SeaWifs image of phytoplankton patch Generated by in situ iron fertilization Growth of the diatom Fragialariopsis kerguelensis was stimulated by iron addition Source: Goddard DAAC

59 The control of Antarctic Productivity Summary Energy shortage is the dominant factor controlling Antarctic productivity Iron stimulation of algal photosynthesis and growth has been well documented. However, experiments were performed at rather low latitudes. No increased settling export fluxes after iron fertilization were observed. Excessive zooplankton (krill) grazing only has local effects Growth rates of phytoplankton are not significantly affected by low temperatures

60 The control of Antarctic Productivity Summary Energy shortage is the dominant factor controlling Antarctic productivity Iron stimulation of algal photosynthesis and growth has been well documented. However, experiments were performed at rather low latitudes. No increased settling export fluxes after iron fertilization were observed. Excessive zooplankton (krill) grazing only has local effects Growth rates of phytoplankton are not significantly affected by low temperatures

61 The control of Antarctic Productivity Summary Energy shortage is the dominant factor controlling Antarctic productivity Iron stimulation of algal photosynthesis and growth has been well documented. However, experiments were performed at rather low latitudes. No increased settling export fluxes after iron fertilization were observed. Excessive zooplankton (krill) grazing only has local effects Growth rates of phytoplankton are not significantly affected by low temperatures

62 The control of Antarctic Productivity Summary Energy shortage is the dominant factor controlling Antarctic productivity Iron stimulation of algal photosynthesis and growth has been well documented. However, experiments were performed at rather low latitudes. No increased settling export fluxes after iron fertilization were observed. Excessive zooplankton (krill) grazing only has local effects Growth rates of phytoplankton are not significantly affected by low temperatures

63 Conclusions and outlook

64 The world ocean is less productive than the continents (1) Poor nutrient supply: Slow molecular diffusion relative to air Low ambient concentrations as compared to soils (2) Energy shortage Low fractional light absorption by photosynthetic pigments (spectral mismatch, high background absorption) Self shading Water column mixing Sea-ice cover

65 The world ocean is less productive than the continents (1) Poor nutrient supply: Slow molecular diffusion relative to air Low ambient concentrations as compared to soils (2) Energy shortage Low fractional light absorption by photosynthetic pigments (spectral mismatch, high background absorption) Self shading Water column mixing Sea-ice cover

66 The world ocean is less productive than the continents (1) Poor nutrient supply: Slow molecular diffusion relative to air Low ambient concentrations as compared to soils (2) Energy shortage Low fractional light absorption by photosynthetic pigments (spectral mismatch, high background absorption) Self shading Water column mixing Sea-ice cover

67 The world ocean is less productive than the continents (1) Poor nutrient supply: Slow molecular diffusion relative to air Low ambient concentrations as compared to soils (2) Energy shortage Low fractional light absorption by photosynthetic pigments (spectral mismatch, high background absorption) Self shading Water column mixing Sea-ice cover

68 The world ocean is less productive than the continents (1) Poor nutrient supply: Slow molecular diffusion relative to air Low ambient concentrations as compared to soils (2) Energy shortage Low fractional light absorption by photosynthetic pigments (spectral mismatch, high background absorption) Self shading Water column mixing Sea-ice cover

69 The world ocean is less productive than the continents (1) Poor nutrient supply: Slow molecular diffusion relative to air Low ambient concentrations as compared to soils (2) Energy shortage Low fractional light absorption by photosynthetic pigments (spectral mismatch, high background absorption) Self shading Water column mixing Sea-ice cover

70 The world ocean is less productive than the continents (1) Poor nutrient supply: Slow molecular diffusion relative to air Low ambient concentrations as compared to soils (2) Energy shortage Low fractional light absorption by photosynthetic pigments (spectral mismatch, high background absorption) Self shading Water column mixing Sea-ice cover

71 The world ocean is less productive than the continents (1) Poor nutrient supply: Slow molecular diffusion relative to air Low ambient concentrations as compared to soils (2) Energy shortage Low fractional light absorption by photosynthetic pigments (spectral mismatch, high background absorption) Self shading Water column mixing Sea-ice cover at high latitudes

72 Implications of our results I: Food production for the growing human population Dueto itscomparativelylow productivity, increasing food demands cannot be met by expanding ocean fisheries. However, aquaculture can serve as a supplementary protein source..however, this should not discourage us from enjoying seafood!

73 Implications of our results II: The role of the ocean in the global carbon cycle and the climate Atmospheric CO 2 levels varied with temperature during the glacial-interglacial cycles causing a positive climate feedback

74 One possible hypothesis: Enhanced oceanic productivity during glaciations is leading to increased CO 2 -drawdown Two possible explanations.

75 One possible hypothesis: Enhanced oceanic productivity during glaciations is leading to increased CO 2 -drawdown Two possible explanations.

76 The Mixing Depth Hypothesis: During glacial periods water column stability is less, causing more nutrients to enter the euphotic zone during winter mixing, thus allowing enhanced primary productivity by macronutrient fertilization: The Red Sea Paradigm The Iron Dust Hypothesis: During glacial periods precipitation is less, causing dust storms which would increase aeolian drift of iron into the ocean, thus allowing enhanced primary productivity by iron fertilization: The Antarctic Ocean Paradigm

77 The Mixing Depth Hypothesis: During glacial periods water column stability is less, causing more nutrients to enter the euphotic zone during winter mixing, thus allowing enhanced primary productivity by macronutrient fertilization: The Red Sea Paradigm The Iron Dust Hypothesis: During glacial periods precipitation is less, causing dust storms which would increase aeolian drift of iron into the ocean, thus allowing enhanced primary productivity by iron fertilization: The Antarctic Ocean Paradigm

78 Acknowledgements I am grateful for financial and logistic support: Deutsche Forschungsgemeinschaft (Antarctic research) Federal Ministry of Education and Research (Red Sea Program) Alfred Wegener Institute for Polar and Marine Research (logistic support in the Southern Ocean) and for fruitful scientific collaboration and discussion over many years: Zvy Dubinsky, Bar Ilan University, Israel Bärbel Beese, University of Constance, Germany Clivia Haese, GKSS, Geesthacht, Germany Astrid Bracher, Bremen University Urich Sommer, IfM Kiel, Germany Boaz Lazar, The Hebrew University of Jerusalem, Israel Sayed S. Z. El Sayed, Texas A&M University, USA Mutaz Al Qutob, Al Quds University, Palestinian Authority and many, many more!

79 Thank you for your attention!