Ocean sensors, the information explosion and biological oceanography
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1 Supported by NSERC, ONR, NOPP, CFCAS Ocean sensors, the information explosion and biological oceanography John J. Cullen Dalhousie University University of Hawaiʼi June 28, 2008
2 20th century oceanography: observations were scarce
3 In retrospect, physical charts of temperature, salinity, nutrients, and currents were so unrealistic that they could not possibly have been of any use to the biologists. Similarly, scientists could find experimental support for their favorite theory no matter what the theory claimed. Walter Munk, 2002
4 But insight went a very long way Sverdrup s (1955) map of productivity based on vertical convection, upwelling and turbulent diffusion Global productivity estimated from remote sensing (Falkowski et al. 1998). As presented by John McGowan (Oceanography Mag., 2004)
5 Technical approach: Thinking R.W. Eppley
6 Products of 20th century oceanography: New Production UNDERSTANDING and KNOWLEDGE Producers: John Martin, Wally Broecker, Dick Dugdale, Dick Eppley Conveyor Belt
7 The bar has been raised We need: PREDICTIVE CAPABILITY HABs Topics/AlgalBlooms/alg_p1.jpg Decline of fish stocks since 1960 Global CO 2 since 900 A.D. (IPCC TAR) Myers and Worm Nature 2003
8 Marine Environmental Prediction DISCOVER! EXPLORE! & EXPERIMENT with PREDICTION OBSERVE DESCRIBE EXPLAIN GOAL: PREDICTION WITH MEASURABLE SKILL Needs: Technology for observations Integration of knowledge Insight (opportunity to think)
9 Requirements for quantitative marine environmental prediction Resolve mesoscale variability Ocean surface Ocean interior (highly resolved vertically) Take bio-optics beyond biomass Describe biodiversity and understand its significance Integrate observations and knowledge in interdisciplinary data assimilative ecological and biogeochemical models
10 Remote sensing is revolutionary NASA/GSFC
11 Capabilities are Awesome From a presentation by Mark Abbott
12 Capabilities are Awesome Results are Important! Decline of the El Niño From a presentation by Mark Abbott
13 Remote sensing permits integrated, interdisciplinary analyses on the scales that matter Vector Winds and Sea Surface Temperature: 2-4 Sept 1999 From a presentation by Mark Abbott
14 New technology describes mesoscale variability in the ocean interior Ken Johnson MBARI
15 Years of records now possible Boss et al., EOS 2008
16 Continuous measures of optics reveal rates see
17 Ultimate Goal: An Interdisciplinary, Coupled, and Data Assimilating Observation and Modeling System Bays to Basins
18 And also: To understand how physically forced oceanographic variability is integrated by marine ecosystems in space and time to result in the biogeochemical state of the ocean. Katja Fennel K. Johnson - MBARI
19 New capabilities were developed through interdisciplinary research Ocean Observing Systems Biological Oceanography Hydrological & Atmospheric Optics Process Studies Models Theory
20 Where does molecular ecology and genomics fit in?
21 What have advances in molecular ecology and genomics contributed? What can be contributed? DISCOVER! EXPLORE! & EXPERIMENT with PREDICTION OBSERVE DESCRIBE EXPLAIN GOAL: PREDICTION WITH MEASURABLE SKILL Needs: Technology for observations Integration of knowledge Insight (opportunity to think) Answers: a) Lots. b) Lots more!
22 Distributions of functional groups distinguishable no other way
23 Metabolic function related to oceanographic stratum The DeLong Tartan
24 The critical ingredient: ENVIRONMENTAL CONTEXT Genetic variability related quantitatively to well defined ecological regimes John Cullen: Agouron Science, Symposium
25 Explicit consideration of oceanographic processes and measurements
26 The challenge: Get to this sooner rather than later Ocean Observing Systems Genomics & the other omics Integrated interdisciplinary sensor systems Physical Chemical & Biological Oceanography Assimilative biogeochemical models Hydrological & Atmospheric Optics [+Acoustics] Process Studies Theory / Models Physiological Ecology Including Gene Expression
27 A Tool for Making Sense of Microbial Diversity in the Marine Environment: Margalef s s Mandala
28 The Genomics Mandala? Venter et al., Science, 2004
29
30 Jargon of vocabulary? Oceanography Turbulence Closure Scheme Shear Instability N-star Hydrostatic model Net westward intensification PDO Mode water eddy Rossby wave Triple isotope oxygen Bio-Optics Apparent Optical Properties Volume Scattering Function Packaging effect Inelastic scatter Normalized water leaving radiance Average cosine of downwelling irradiance Semi-analytic model Hyperspectral absorption - attenuation Nonphotochemical quenching Genomics Fosmids TBLASTX high-scoring sequence pair bitscores KEGG and COG annotated bins ORFs BAC contigs synteny distinctly nonpunctate scaffold
31 The challenge: Get to this sooner rather than later Ocean Observing Systems Genomics & the other omics Integrated interdisciplinary sensor systems Physical Chemical & Biological Oceanography Assimilative biogeochemical models Hydrological & Atmospheric Optics [+Acoustics] Process Studies Theory / Models Physiological Ecology Including Gene Expression
32 We will need Sense-Making Tools in a world of Too Much Information DISCOVER EXPLORE & EXPERIMENT with PREDICTION after Paul Saffo Institute for the Future OBSERVE DESCRIBE EXPLAIN Research Education Knowledge Insight for Education Outreach Management
33 The VISION Portal Virtual-reality Information System and Integrated Ocean-observing Network Virtual reality access to all ocean environments Fully 4-dimensional Scalable from global to mm and smaller Physical, chemical, biological Direct access to oceanographic data Integrated with the Global Ocean Observing System DATA MODELS Contextual hyperlinks to scientific literature and databases Multiple levels of interaction Entertainment, education, exploration, research, prediction
34 The Lunenburg Project : Interdisciplinary Marine Environmental Prediction in the Atlantic Coastal Region
35 Models within models within models
36 Google Earth Access
37 Remote sensing of temperature and chlorophyll
38 Easy access to real-time and archived data
39 Probe the Ocean Depths Brandon Sackmann, University of Maine
40 Switch to layers for all ocean information systems
41 Layers for All Ocean Knowledge Weather Hazards History Currents Shipwrecks Surf Report Minerals Ecosystems Pollution Forecasts Climate models Bottom type Genomics Sea Life
42 The VISION Portal Virtual-reality Information System and Integrated Ocean-observing Network Virtual reality access to all ocean environments Fully 4-dimensional Scalable from global to mm and smaller Physical, chemical, biological Direct access to oceanographic data Integrated with the Global Ocean Observing System DATA MODELS Contextual hyperlinks to scientific literature and databases Multiple levels of interaction Entertainment, education, exploration, research, prediction
43 The VISION Portal Information to Knowledge through Thinking Mahalo!
44
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