The Hawaii Ocean Time-series (HOT): Highlights and perspectives from two decades of ocean observations MATTHEW CHURCH UNIVERSITY OF HAWAII OCB SCOPING WORKSHOP SEPTEMBER 2010
A Dedicated HOT Team NSF
What s HOT? Program objectives: Quantify time-dependent variability in key physical, biogeochemical, and ecological properties and processes Define relationships between plankton community structure and biogeochemical dynamics Quantify physical and biological processes controlling oceanic carbon uptake, transformation, and sequestration
The Hawaii Ocean Time-series i (HOT) Near monthly cruises to Station ALOHA since October 1988 Deep ocean (~4800 m) observatory Shipboard and remote measurements of ocean biogeochemistry, physics, and plankton ecology 4-day cruises, intensive sampling to 1000 m
Time, water, and change The value of HOT observations continues to increase with time. HOT provides some of the best and only records of biogeochemical and physical variability in the open ocean waters of the Pacific across multiple time scales: episodic, seasonal, interannual, and multidecadal. ALOHA Knowledge gained from HOT furthers our understanding of global-scale ocean change.
Ongoing projects supported by HOT: If you build it, they will come Ocean Carbon System Variability, NSF; A. Dickson (P.I.), 1988-present WHOI Hawaii Ocean Time Series Station (WHOTS), NOAA-NSF; NSF; R. Weller (P.I.), 2004-present CFC and SF 6 Water Mass Tracers, NOAA; J. Bullister (P.I.), 2004-present Microbial Oceanography: Genomes to Biomes Summer training course, NSF-Agouron Institute-Gordon and Betty Moore Foundation; D. Karl (P.I.), 2006- present Marine Microbiology Initiative, Gordon and Betty Moore Foundation; D. Karl (P.I.), 2005-present Center for Microbial Oceanography: Research and Education (C-MORE), NSF; D. Karl (P.I.), 2006-present Si Cycling and Dynamics, NSF; M. Brzezinski (P.I.), 2007-present ALOHA Cabled Observatory, NSF; B. Howe (P.I.), 2007-present Diazotrophy in a High CO 2 World, NSF; M. Church (P.I.),2009-present Profiling Floats for Ocean Biogeochemistry, NSF-NOPP; NOPP; K. Johnson, 2007- present Subsurface Moored Profiler, NSF; M. Alford (P.I.), 2009-present Taxon-specific Variability of Organic Matter Production and Remineralization, NSF; A. White (P.I.), 2009-present Primary Productivity as a Function of Absorption, Pigment-based Phytoplankton Diversity, and Particle Size Distributions, NASA; A. White (P.I.), 2009-present
From the Predictable to the Unexpected: Highlights on 3 interlinked themes in ocean biogeochemistry Ocean carbon cycling Plankton productivity and the importance of community structure New production and export
HOT carbon reservoirs and fluxes Carbon reservoirs: Carbonate system: DIC, total t alkalinity, li it ph, pco 2 Coulometry (DIC), potentiometric titration (total alkalinity), spectrophotometric (ph), shipboard (KM) pco 2 equilibrator (SOEST), and moored pco 2 sensor (C. Sabine-PMEL) Total organic carbon (TOC) High temperature combustion Particulate carbon (POC and PIC) High temperature combustion (POC); acidification/ IR detection (PIC) Carbon fluxes: Biological carbon production (POC and DOC) 14 C-bicarbonate assimilation (primary production), changes in carbon and oxygen Particulate carbon export Sediment trap particle collections
Air trend: +1.70 atm yr -1 Rising CO 2, Falling ph Ocean trend: +1.92 atm yr -1 ph trend -0.0018 yr -1 Dore et al. (2009)
Temporal variability in mixed layer inorganic carbon DIC ol C L -1 ) 2020 2000 1980 Interannual variations in DIC concentrations closely coincident with changes to upper ocean salinity. ( m 1960 1940 88 90 92 94 96 98 00 02 04 06 08 10 Year 35.55 35.0 34.5 Salinity Dore et al. (2003)
Interannual variability in inorganic carbon pools Annual accumulation (0-150 m) of ndic ~ 0.1 mol C m -2 yr -1 Interannual variations in the E-P balance and mixing important controls on carbon inventories Winn et al. 1994, Dore et al. 2003, 2009
Processes influencing carbon cycling in the upper ocean at Station ALOHA CO 2 ATMOSPHERE Gas exchange E-P balance Diffusion DIC DIC Net community production Entrainment Organic Carbon (DOC, POC) Diffusion MIXED LAYER Mixed layer boundary THERMOCLINE Adapted from Keeling et al. (2004) Particle export
What is the biological contribution to ocean carbon flux at ALOHA? Photosynthesis + O 2, -CO 2 Respiration -O 2, + CO 2
The upper ocean habitat PAR ( mol quanta m -2 s -1 ) -2-1 ) 14 10 0 10 1 10 2 10 3 0 0 PAR 14 C-PP ( mol C L -1 d -1 ) 0.0 0.1 0.2 0.3 0.4 0.5 0.6 14 C-PP 50 MLD 50 De epth (m) 100 100 1% Chl a 150 150 0.1% N+N 200 200 0 1 2 3 4 5 00 0.0 02 0.2 04 0.4 06 0.6 08 0.8 Nitrate + Nitrite ( mol N L -1 ) Chlorophyll a ( g L -1 )
Light is an important habitat control Seasonal changes in light appear to drive productivity in both the near surface waters and deep chlorophyll maximum 125 m 5 m 0-75 m 125 m
Polov vina et al. (200 08) -2 ) 0-125 m Chl a (mg m - 35 Corno et al. (2007), Saba et al. (2010), Luo et al. Chl a increasing 0.22 mg m -2 yr -1 80 14 C-PP (mmol C m -2 d -1 ) Boyce et al. (2010) 30 HOT 25 observations 20 indicate both 15 chlorophyll and 10 primary 5 production are 100 14 C-PP increasing 0.33 mmol C m increasing. yr -1 Prominent 89 91 93 95 97 99 01 03 05 07 09 Year 60 increases occurring 40 below the 20 depth of satellite detection.
Material transfer through the food web 3.0 Mesozoop plankton dry weight (g m -2 ) 2.5 2.0 1.5 1.0 0.5 0.0 94 95 97 99 01 03 05 07 09 Year Zooplankton dry weight (0-150 m) increasing at 37 mg m -2 per year Sheridan and Landry (2004)
Measurements and models of primary production at Station ALOHA Carbon production 14 C-bicarbonate assimilation (daylight incubation period ~12 hours) DIC, TOC, and PC variability Oxygen production In vitro O 2 bottle incubations In situ O 2 dynamics: gliders, floats, moorings, and ships 18 O 2 production from H 2 18 O 16 O, 17 O, 18 O Triple O 2 isotopes Bio-optics and satellites Bio-optical optical approaches Satellite remote sensing
In vitro O 2 dynamics at Station ALOHA GPP, NCP, and R ( mol O 2 L -1 d -1 ) -0.4-0.2 0.0 0.2 0.4 0.6 0.8 1.0 0 4 years of measurements (2001, 2005-2007) Net N t Community Production:-4.2 to -7.4 mol C m -2 yr -1 Gross Primary Production: 11.9-14.0 mol C m -2 yr -1 Respiration: p 17-21 mol C m -2 yr -1 Conclusion: Net heterotrophy due to incubation conditions and/or under sampling GPP, R, NCP (mmol O m -2 d -1 2 ) 100 50 0-50 -100 Dep pth (m) 25 50 75 100 125 150 100 200 300 Day of year GPP R NCP e.g. Williams et al. (2004)
Mixed layer O 2 is in equilibrium with the atmosphere Rate of subsurface O 2 Rate of subsurface O 2 accumulation provides information on NCP
In situ O 2 dynamics at Station ALOHA 75 m >6+ 6 years of in situ measurements (2003-05, 2008- present) Net Community Production: 1.1-1.7 mol C m -2 yr -1 Riser and Johnson (2008)
Net Community Production at Station ALOHA Method Mixed Layer O 2 + Ar budgets Rate mol C m -2 yr -1 Period of measurements References 1.4-3.7 (± 1.0) 1992 2008 Emerson et al. (1997); Hamme and Emerson (2006); Juanek and Quay (2005); Quay et al. (2010) DIC + DI 13 C budgets 2.7-2.8 (± 1.4) 1988 2002 Quay and Stutsman (2003); Keeling et al. (2004) Mooring O 2 4.1 (± 1.8) 2005 Emerson et al. (2008) Sub-mixed layer float profiles Sub-mixed layer glider surveys 1.1-1.7 (±0.2) 2003-2010 Riser and Johnson (2008) 0.9 (± 0.1) 2005 Nicholson et al. (2008) Sediment traps 0.9 (± 0.3) 1989 2009 HOT core data In vitro O 2 incubations -6.1 (± 4.6) 2001, 2005-2007 Williams et al. (2004) NCP appears constrained to ~2 fold variability NCP appears constrained to ~2-fold variability GPP estimated ~20-fold greater than NCP
What controls variability in nutrient supply supporting net community production? N 2 fixation 2 NH 4 + Organic matter Organic matter NH 4 + NO - NO - 3 2 NO 3 - NO 2 - NH 4 + Organic matter
Annual cycle of productivity and export 60 35 3.5 150 m Carbon export (mmol C m -2 d -1 ) 3.0 50 2.5 40 im. prod. C m -2 d -1 ) 2.0 30 (mmol 14 C-pri 1.5 0-150 m 20 Silica Export ( mol Si m -2 d -1 ) 100 80 60 40 20 4000 m 4000 m 500 400 300 200 100 Carbon Export ( mol C m -2 d -1 ) Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Jan Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Jan Month Month Plankton community structure plays a key role in carbon flux to the deep sea
Controls on nitrogen supply to the upper ocean Physical: Mixing, upwelling, diffusion, advection NO 3- supported new production Biological: i l N 2 fixation (N 2 NH 3 ) N 2 supported new production
Physical supply of nutrients: Mixing -2 ) N+N (mm mol N m - 30 0 0-100 00 m 25 25 20 15 10 5 0 150 89 90 91 92 93 94 95 96 97 98 99 00 01 02 03 04 05 06 07 08 09 10 Year 50 75 100 125 MLD (m) Winter mixing increases upper ocean nitrate concentrations
Mesoscale variability at Station ALOHA Temper rature ( o C) 24 22 20 18 140 m 1/05 1/06 1/07 SSHa (cm) 20 10 0-10 -20 SSHa (cm) Dep pth (m) 75 24.6 kg m -3 100 125 150 175 200 Y = 2.2 + 136, R 2 = 0.47-20 -10 0 10 20 SSHa (cm)
Biological supply of nutrients: N 2 fixation N 2 fix xation ( mol N m -2 d -1 ) 200 150 100 50 0 Jan FebMar Apr May June July Month Aug Sept Oct Nov Dec Rates of N 2 fixation are variable, but generally Rates of N 2 fixation are variable, but generally increase in the spring and summer
) ALOHA July 19-26, 2005 Tempe erature ( o C 28 26 24 22 20 18 16 01 03 05 07 09 11 01 03 05 2005 2006 ALOHA C. Sabine, PMEL
January 2005 April 2005 July 2005 Depth (m) 0 50 100 150 p July 2005 typical profile 200 Fong et al. (2007) 0.0 0.2 0.4 0.6 0.8 1.0 Chloropigment ( g L -1 )
Whole Seawater Time series measurements of near-surface ocean N 2 fixation at Station ALOHA erature ( o C) Temp 28 26 24 22 20-15 -10-5 0 5 10 15 20 Episodic increases in N 2 fixation by diazotrophs >10 m appear associated with mesoscale (anticyclonic) eddies. Te emperatur re ( o C) 28 26 24 22 <10 m Seawater 20-15 -10-5 0 5 10 15 20 SSHa (cm) Church et al. (2009) 10 5 2 1 nmol N L -1 d -1 0.5 0.2
NO 3- based new production N 2 fixation based new production 1 2 NO 3-, PO 3-4, Si, CO 2 1 2 NO 3-, PO 4 3-, Si, CO 2 Both appear to support new production, but for different reasons
HOT insights Biological and physical processes interact to control time-variability in ocean carbon inventories and fluxes. The complexity of ocean ecosystem change demands interdisciplinary studies. HOT measurements indicate we need to study carbon cycle processes at a range of scales, from decadal to seasonal to episodic. The value of HOT continues to increase with time.
Facing Future The complexity of ecosystem dynamics, even in this stable ecosystem, demands sustained observations. The shipboard time series program continues to enrich our understanding of the NPSG, and help direct application of remote and autonomous sensing technologies. These multi-decadal time series programs are some of our best (and only) barometers of ocean ecosystem change.