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Measuring aquatic ecosystem Measuring aquatic ecosystem metabolism - - PowerPoint PPT Presentation

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Measuring aquatic ecosystem Measuring aquatic ecosystem metabolism in the southern Everglades metabolism in the southern Everglades Gregory R. Koch 1 , Peter A. Sthr 2 , Evelyn E. Gaiser 1 and Daniel L. Childers 3 1 Department of Biological

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Measuring aquatic ecosystem Measuring aquatic ecosystem metabolism in the southern Everglades metabolism in the southern Everglades

Gregory R. Koch1, Peter A. Stæhr2, Evelyn E. Gaiser1 and Daniel L. Childers3

1Department of Biological Sciences, Florida International University Miami, FL, USA 2University of Copenhagen Hillerød, Denmark 3Global Institute of Sustainability, Arizona State University Tempe, AZ, USA

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SLIDE 2

Introduction Methods Results Analyses Conclusions

Everglades National Park

Taylor Slough Shark River Slough

Florida Bay Gulf of Mexico

Miami

http://fcelter.fiu.edu/data/GIS/interactive_map/

Historic Flow Current Flow Planned Flow

http://www.evergladesplan.org

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SLIDE 3

Florida Bay

Taylor Slough Miami Taylor River

Introduction Methods Results Analyses Conclusions

The Taylor Slough Watershed

Photos: http://fcelter.fiu.edu/about_us/photos/ Map: http://fcelter.fiu.edu/data/GIS/interactive_map/

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SLIDE 4

Introduction Methods Results Analyses Conclusions

Taylor River

http://fcelter.fiu.edu/about_us/photos/ Photo by Steven Davis http://fcelter.fiu.edu/data/GIS/interactive_map/

TS/Ph 6 TS/Ph 7 Study Sites

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SLIDE 5

http://fcelter.fiu.edu

Introduction Methods Results Analyses Conclusions

Taylor River Seasonality

TS/Ph6

10 20 30 40 50 60 May-98 Sep-98 Jan-99 May-99 Sep-99 Jan-00 May-00 Sep-00 Jan-01 May-01 Sep-01 Jan-02 May-02 Sep-02 Jan-03 May-03 Sep-03 Jan-04 May-04 Sep-04 Jan-05 May-05 Salinity (ppt)

Full-strength Seawater ~35ppt

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SLIDE 6

TS/Ph 6 5 10 15 20 25 30 35 40 45 50 J F M A M J J A S O N D

Salinity (ppt)

1998 1999 2000 2001 2002 2003 2004 2005

Blue – Oligohaline “Wet” Season – September to February Red – Euhaline “Dry” Season – March to August

Introduction Methods Results Analyses Conclusions

Taylor River Seasonality

http://fcelter.fiu.edu

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SLIDE 7

Introduction Methods Results Analyses Conclusions

Taylor River Seasonality

Nov Jan Mar May Jul Sep

Salinity (ppt)

10 20 30 40 50 FCE LTER Site TS/Ph 6 (Upstream) FCE LTER Site TS/Ph 7 (Downstream) 3-day Smoothed Average Average

2008 - 2009

“Wet” Season “Dry” Season

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SLIDE 8

What is ecosystem metabolism?

  • metabolism: the sum of all chemical changes in living cells by which

energy is provided for vital processes and activities and new material is assimilated (Merriam-Webster Dictionary)

  • In Ecosystems: the biological activity of all living organisms within the

ecosystem boundary; generally, primary production and respiration

Heterotrophs

Ecosystem Boundary

Autotrophs

Production Respiration consumption Light

Introduction Methods Results Analyses Conclusions

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SLIDE 9

The balance of carbon between the ecosystem and its surroundings:

Gross Primary Production (GPP) Ecosystem Respiration (R) NEP = GPP - R Net Ecosystem Production (NEP)

Introduction Methods Results Analyses Conclusions

What does ecosystem metabolism tell us?

Heterotrophs

Ecosystem Boundary

Autotrophs

Production Respiration consumption Light

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SLIDE 10

Oligohaline “Wet” Season Euhaline “Dry” Season

GPP R

GPP Re

GPP R

Introduction Methods Results Analyses Conclusions

How does metabolism change with time?

+ Low Salinity + Submerged Aquatic Vegetation (SAV) + High Water Depth + Low Sediment Depth = Higher GPP, Lower R + High Salinity + No SAV + Low Water Depth + High Sediment Depth = Lower GPP, Higher R

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SLIDE 11

Anemometer Dissolved Oxygen sensor Temperature and Light loggers

Floating Buoy Design Variables Measured % Dissolved Oxygen Wind Speed Water Temperature Underwater Light Surface Light

Introduction Methods Results Analyses Conclusions

Calculating Metabolism

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SLIDE 12

Introduction Methods Results Analyses Conclusions

Phytoplankton GPP R Phytoplankton, animals, bacteria Sediment Atmospheric exchange (F)

∆DO

GPP R R

Vind Wind

  • C

Summer Winter

Turbulent mixing Metalimnion Hypolimnion Epilimnion Advection

ΔO2 / Δt = GPP – R – Fatm

Calculating Metabolism

Staehr, P.A., C.E. Williamson, M.C. Van de Bogert, T.K. Kratz, G.R. Koch, P.C. Hanson, J.J. Cole, D.L. Bade. In Prep.

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Introduction Methods Results Analyses Conclusions

Fatm (gO2 m-2 h-1) = k (O2meas – O2sat) k600 (cm h-1) = 2.07 + 0.215(wind10m)1.7

Calculating Metabolism

Cole, J.J. and N.F. Caraco. 1998. Bioscience 38:764-769.

k (cm h-1) = k600(Sc/600)-0.5

Jähne, B., O. Münnich, R. Bösinger, A. Dutzi, W. Huber, and P. Libner. 1987. Journal of Geophysical Research 92: 1937-1949. Staehr, P.A., C.E. Williamson, M.C. Van de Bogert, T.K. Kratz, G.R. Koch, P.C. Hanson, J.J. Cole, D.L. Bade. In Prep.

wind10m = windZ (1.4125 (z-0.15))

Smith, S.V. 1985. Plant, Cell, and Environment 8: 387-398.

Sc = 0.0476(T)3 + 3.7818(T)2 - 120.1(T) + 1800.6

Wanninkhof, R. 1992. Journal of Geophysical Research 17: 721-735.

ΔO2 / Δt = GPP – R – Fatm

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SLIDE 14

Introduction Methods Results Analyses Conclusions

Pond 3

Feb Mar Apr May Jun Jul Aug

°C

10 15 20 25 30 35 40

P3 10cm P3 50cm P3 100cm Pond 4

Nov Jan Mar May Jul

°C

10 15 20 25 30 35 40

P4 10cm P4 50cm P4 100cm Pond 5

Jul Aug

°C

26 28 30 32 34 36

P5 10cm P5 50cm P5 100cm

Water Temperature Profiles

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SLIDE 15

Introduction Methods Results Analyses Conclusions

Pond 3

May Jun Jul Aug mmol O2 m3 d-1

  • 1000
  • 800
  • 600
  • 400
  • 200

200 400 600 800

P3 GPP P3 R P3 NEP Pond 4

Nov Dec Jan Feb Mar Apr May Jun mmol O2 m3 d-1

  • 1000
  • 800
  • 600
  • 400
  • 200

200 400 600 800

P4 GPP P4 R P4 NEP Pond 5

Feb Mar Apr May Jun Jul Aug mmol O2 m3 d-1

  • 1000
  • 800
  • 600
  • 400
  • 200

200 400 600 800

P5 GPP P5 R P5 NEP

Daily Metabolic Rates

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SLIDE 16

Introduction Methods Results Analyses Conclusions

P4 Wet GPP P4 Dry GPP P4 Wet R P4 Dry R P4 Wet NEP P4 Dry NEP

mmol O2 m-3 d-1

  • 1200
  • 1000
  • 800
  • 600
  • 400
  • 200

200 400 600 800 t = -8.8637 p < 0.0001 df = 188 t = 7.0392 p < 0.0001 df = 188 t = -0.6640 p = 0.5075 df = 188

Seasonal Differences

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SLIDE 17

Introduction Methods Results Analyses Conclusions

P3 GPP P4 GPP P5 GPP P3 R P4 R P5 R P3 NEP P4 NEP P5 NEP

mmol O2 m-3 d-1

  • 1200
  • 1000
  • 800
  • 600
  • 400
  • 200

200 400 600 800

Spatial Differences

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SLIDE 18

Introduction Methods Results Analyses Conclusions

0.517 p < 0.001 0.746 p < 0.001

  • 0.414

p < 0.001 N/A

  • 0.429

p < 0.052

  • 0.353

p = 0.107 0.314 p < 0.001 Pond 5 GPP 0.235 p = 0.001 0.572 p < 0.001 0.365 p < 0.001 0.007 p = 0.967

  • 0.099

p = 0.367 0.081 p = 0.409 0.595 p < 0.001 Pond 4 GPP

  • 0.010

p = 0.937 0.454 p < 0.001

  • 0.302

p = 0.015 N/A

  • 0.155

p = 0.221 0.201 p = 0.111 0.268 p = 0.032 Pond 3 GPP Wind Salinity Temp TP Kd 50cm Light Surface Light

Drivers of Aquatic Production

Green Cells = Significant Positive Correlation Red Cells = Significant Negative Correlation

α = 0.05

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SLIDE 19

Oligohaline “Wet” Season Euhaline “Dry” Season

GPP R

GPP Re

GPP R

Introduction Methods Results Analyses Conclusions

+ Low Salinity + Submerged Aquatic Vegetation (SAV) + High Water Depth + Low Sediment Depth = Higher GPP, Lower R + High Salinity + No SAV + Low Water Depth + High Sediment Depth = Lower GPP, Higher R

Our Predictions…

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SLIDE 20

Oligohaline “Wet” Season Euhaline “Dry” Season

GPP R

GPP Re

GPP R

Introduction Methods Results Analyses Conclusions

+ Low Salinity + Submerged Aquatic Vegetation (SAV) + High Water Depth + Low Sediment Depth = Lower GPP, Lower R + High Salinity + No SAV + Low Water Depth + High Sediment Depth = Higher GPP, Higher R

So, What Really Happened?

+ High TP??

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SLIDE 21
  • Expand spatial and temporal breadth of data
  • Explore the relationship between stimulated GPP and responses in R
  • additions of algal extracts onto pond sediments (“priming”)
  • Time series analysis to explore time lags
  • Investigate the meaning of metabolic throughput in terms of

ecosystem function

  • Floc transport rates between ponds
  • Carbon budgets and landscape metabolism estimates for Taylor

River

Introduction Methods Results Analyses Conclusions

Directions of New Research