Ocean & Climate Atmospheric CO 2, DMS, … Ocean/Atmosphere Circulation Dust-Iron Influx, pH Ocean Nutrient Fields Ecosystem State Biomass Primary Productivity.

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Presentation transcript:

Ocean & Climate Atmospheric CO 2, DMS, … Ocean/Atmosphere Circulation Dust-Iron Influx, pH Ocean Nutrient Fields Ecosystem State Biomass Primary Productivity Net Production/Export Community Structure Marine Ecosystem Modeling & Genomics Scott Doney, WHOI Biological Dynamics Environmental Genomics Physiology Population Ecology

D. Karl (2004) -Regulation of atm. CO 2 & other radiative gases -Responses & feedbacks to warming, dust, … -Predictions require mechanistic understanding

-Aggregate into trophic levels/functional groups -Rates/processes from limited culture/field studies -Many aspects empirically based -Data poor for validation (rates, grazing, loss terms) “State of the Art” Model

Marine Genomic Revolution -Leverage advances in Biotech & Human Genome -rapid gene sequencing -O(10) => O(100) marine microbial genomes -“microarrays” => simultaneous samples -Environmental genomics: -sample whole communities; -“cultivation independent” techniques Prochlorococcus Genome map Rocap et al. (2003)

DNA Brief Genomic Tutorial -Proteomics -Physiological rates Proteins/ Enzymes mRNA -Gene expression -Response to environmental forcing -Phylogeny -Diversity (DNA, rRNA) -Metabolic pathways -Phylogeny -Diversity (DNA, rRNA) -Metabolic pathways -Gene expression -Response to environmental forcing

-dominance of uncultured microbes -large number of species/taxa -new metabolic pathways -deeper genetic “potential” (genotype) often unexpressed Recent Findings Light-driven proton pump Photosynthesis

Sargasso Sea “Shotgun” Analysis (C. Venter) -filter 2000 liters -collect genome fragments -assemble in silico ~1.2M genes ~1800 new “species” Venter et al. 2004

Bridging Genomics & Ecosystem Modeling -New processes/dynamics -Data for model evaluation species composition metabolic rates -Adapt current models expand predicted variables increase species diversity (more boxes) model cellular metabolism (more complex boxes)

Molecular Detection of Trichodesmium Phosphorus Stress +P -P Assay development: Cultures grown with (+P) or without (-P) phosphorus. St nM PO 4 3- St nM PO nM PO 4 3- Dyhrman et al. 2002

Genomics & Modeling New model paradigms -multi-scale models (e.g., individual based models; continuous distributions) (more flexible “boxes”) nesting; SGS parameterization -simulate ecological functions, not species “genotype” => “phenotype” (abandon boxes) -ecological/evolutionary rules for ecosystem assembly (e.g., resiliance; optimal energy/mass flow)

Ocean & Climate Atmospheric CO 2, DMS, … Ocean/Atmosphere Circulation Dust-Iron Influx, pH Ocean Nutrient Fields Ecosystem State Biomass Primary Productivity Net Production/Export Community Structure Biological Dynamics Environmental Genomics Physiology Population Ecology How do we build a credible model? How much complexity is enough? Do we know the key processes for climate change? Genomic data will help to quantify processes & environmental sensitivity

Phylogentic Tree for nifH (N 2 fixation) gene Chesapeake Bay Jenkins et al. (2004)

Molecular Detection of Trichodesmium Phosphorus Stress +P -P Assay development: Cultures grown with (+P) or without (-P) phosphorus. St nM PO 4 3- St nM PO 4 3- Dyhrman et al nM PO 4 3- Species Heterogeneity

Prochlorococcus genome Rocap et al. (2003) Genome Sequences -novel metabolic pathways -

Environmental Controls on Plankton Species Distributions: An Example for Coccolithophores SeaWiFS Model estimate (probability distribution) Universal distribution => local selection Step 1: Satellite mapping of coccolithophorid blooms Step 2: Compare with modern physical variables (SST, nutrients, light, mixing depth) Step 3: Develop “conditional probability function” Step 4: Project future using results of climate models Future ( ) Iglesias-Rodreguiz (2002)

SA 11 NZ BA Distinct genetic populations of Emiliania huxleyia in Northern and Southern Hemisphere blooms => different physiological responses to environmental forcing Amplified Fragment Length Polymorphism (AFLP)

DNA Proteins/ Enzymes mRNA -Phylogeny (evolutionary relationships): dominance of uncultured microbes Archea (new Domain of life) -Diversity large number species/taxa, many unidentified relative number of organisms -Metabolic pathways new functions or unexpected capabilities deeper genetic “potential” (genotype) mRNA Proteins/ Enzymes Genes to Physiology

DNA Proteins/ Enzymes mRNA Proteins/ Enzymes Genes to Physiology -Gene expression -Responses to environmental forcing (physcial, chemical, biological)

DNA Brief Genomic Tutorial -Proteomics -Physiological Rates -“Phenotype” Proteins/ Enzymes mRNA -Gene Expression -Response to environmental forcing -Diversity (DNA, rRNA) -Metabolic pathways -Genetic potential “genotype” -Diversity (DNA, rRNA) -Metabolic pathways -Genetic potential “genotype” -Gene Expression -Response to environmental forcing

Molecular/genomic data -validation -new metabolism -why are some pathways turned on -improved

Current generation models -many aspects empirically based -aggregate trophic levels -geochemical functional groups Increased biological complexity -biological “sub-grid-scale” parameterization Molecular/genomic data -validation -new metabolism -why are some pathways turned on -improved

-Microbes dominate marine ecology/biogeochem. -Regulation of atm. CO 2 & other radiative gases -Responses & feedbacks to warming, dust, … -Predictions require mechanistic understanding

Boyd and Doney (2002) Regional changes in ecosystem boundaries, productivity & community structure Warming & stratification  Increased N 2 fixation Reduced dust??  Increased N 2 fixation

Phytoplankton Fixed C/N/P, Variable Fe/C, Chl/C, Si/C Diatoms (C, Chl, Fe, Si) Diazotrophs (C, Chl, Fe) Picoplankton / Coccolithophores (C, Chl, Fe, CaCO3) Zooplankton (C) Nutrients Ammonium Nitrate Phosphate Silicate Iron Dissolved Organic Material (C, N, P, Fe) Sinking Particulate Material (C, (N, P), Fe, Si, CaCO3, Dust) ECO-C3 Marine Ecosystem Component

Ecosystem Modeling -Population dynamics based -Multiple limiting nutrients -Plankton community structure (size, geochemical functionality) -Embed in full global 3-D physics model

DNA Brief Genomic Tutorial -Proteomics -Physiological Rates -“Phenotype” Proteins/ Enzymes mRNA -Gene Expression -Response to environmental forcing -Diversity (DNA, rRNA) -Metabolic pathways -Genetic potential “genotype” -Diversity (DNA, rRNA) -Metabolic pathways -Genetic potential “genotype” -Gene Expression -Response to environmental forcing