Intermingling of two Pseudocalanus species on Georges Bank D.J. McGillicuddy, Jr. Woods Hole Oceanographic Institution A. Bucklin University of New Hampshire.

Slides:



Advertisements
Similar presentations
Individual-based Models Three Examples
Advertisements

Printed by An Update of Primary Productivity and Chlorophyll, a Twenty Year Database Analysis Jennifer L. Sheldon, David M. Wolgast,
Effect of Rain Scavenging on Altitudinal Distribution of Soluble Gaseous Pollutants in the Atmosphere B. Krasovitov, T. Elperin, A. Fominykh Department.
Plankton changes and cod recruitment in the North Sea Plankton changes and cod recruitment in the North Sea Grégory Beaugrand 1,3*, Keith M. Brander 2,
Erin Meyer-Gutbrod - Cornell University Dr. Andrew Pershing – Gulf of Maine Research Institute Dr. Charles Greene - Cornell University
Use of Headcount Surveys to Estimate the Relative Abundance of Diamondback Terrapins (Malaclemys terrapin centrata) at Masonboro Island, North Carolina.
Potential Approaches Empirical downscaling: Ecosystem indicators for stock projection models are projected from IPCC global climate model simulations.
Change in Ocean Surface Thermal Habitat in a Continental Shelf Marine Ecosystem and Its Affect on Lower Trophic Level Organisms Kevin Friedland, Joe Kane,
Zooplankton processes Puget Sound Oceanography Jan. 28, 2011.
A SCALING TOOL TO ACCOUNT FOR INHERENT STOCHASTICITY IN LARVAL DISPERSAL Mitarai S., Siegel D. A., Warner R.R., Kendall B.E., Gaines S.D., Costello C.J.
Integration schemes for biochemical systems unconditional positivity and mass conservation Jorn Bruggeman Hans Burchard, Bob Kooi, Ben Sommeijer Theoretical.
A Variational Carbon Data Assimilation System (CDAS-4DVar)
The Ocean as a Microbial Habitat Matthew Church Marine Microplankton Ecology OCN 626/Fall 2008.
Scaling of Larval Transport in the Coastal Ocean Satoshi Mitarai, Dave Siegel, Kraig Winters Postdoctoral Researcher University of California, Santa Barbara.
Experimental System for Predicting Shelf-Slope Optics (ESPreSSO): Assimilating ocean color data using an iterative ensemble smoother: skill assessment.
BIOPLUME II Introduction to Solution Methods and Model Mechanics.
Ecology and Populations. What is ecology? Ecology is the scientific study of interactions between organisms and their environment. Ecology is the scientific.
Global Carbon Cycle Feedbacks: From pattern to process Dave Schimel NEON inc.
US-GLOBEC NW Atlantic Georges Bank Program Broadscale cruises (Jan-June) Process cruised 1995, 97 and 99 (Mar-May) Growth rate of
So you want to study marine biology?. Introduction to Marine Biology Physical Oceanography – Waves, Tides, Ocean Circulation, Seawater, and Surfing?
The Physical Modulation of Seasonal Hypoxia in Chesapeake Bay Malcolm Scully Outline: 1)Background and Motivation 2)Role of Physical Forcing 3)Simplified.
US GLOBEC Fundamental Discoveries and Surprises David Mountain.
Keith Brander IMBER-GODAE 12 June 2007 Variability and shifts in marine ecosytems Keith Brander ICES/GLOBEC Coordinator.
Ecology and Oceanography in the Gulf of Mexico
A Nutrient Climatology for the Gulf of Maine − Georges Bank Region June 23, 2008 David Townsend Nathan Rebuck Maura Thomas.
Nearshore fish communities response to habitat variability Terril P. Efird School of Fisheries and Ocean Sciences University of Alaska Fairbanks.
Development of the Lipid Accumulation Window hypothesis to explain Calanus finmarchicus dormancy Jeffrey Runge School of Marine Sciences, University of.
Spatial Fisheries Values in the Gulf of Alaska Matthew Berman Institute of Social and Economic Research University of Alaska Anchorage Ed Gregr Ryan Coatta.
An adjoint data assimilation approach Physical and Biological Controls on Calanus finmarchicus in the Georges Bank Region GlOBEC broad-scale surveysAcadia.
Our Backyard Waterways: Predicting a Phytoplankton Bloom.
Spatial and Temporal Variability of Zooplankton on Georges Bank: Results from the GLOBEC Study Edward Durbin, Maria Casas Graduate School of Oceanography,
Vertical distribution of ontogenetically migrating copepods in the Western Subarctic Gyre T. Kobari 1, D. K. Steinberg 2, S. Wilson 2, K. Buesseler 3,
Globec Legacy- the SSC ideas A.Philosophy B.Body of Knowledge C.Innovative Methodologies D.Management and information transfer E.Education/Outreach.
Definition and assessment of a regional Mediterranean Sea ocean colour algorithm for surface chlorophyll Gianluca Volpe National Oceanography Centre, Southampton.
Figure. Seasonally migrating copepods appeared at Station K2. We can identify two groups of the copepods by the life cycle. Red: surface spawning species,
Yvette H. Spitz Oregon State University, CEOAS Carin J. Ashjian (1), Robert G. Campbell (2), Michael Steele (3) and Jinlun Zhang (3) (1) Woods Hole Oceanographic.
GLOBEC-01: Zooplankton population dynamics on Georges Bank: model and data synthesis Peter Franks (SIO), Changsheng Chen (UMassD), James Pringle, Jeff.
2:00-3:00 Plenary - GLOBEC NWA Finale Summary of key findings Summary of key findings Prog Oce Volume 2010 Prog Oce Volume 2010 Final GLOBEC symposium,
Hydrodynamic Connectivity in Marine Population Dynamics Satoshi Mitarai 1, David A. Siegel 1, Bruce E. Kendall 1, Robert R. Warner 1, Steven D. Gaines.
Jo King: Mechanisms relating the ocean-scale distribution of Calanus finmarchicus to environmental heterogeneity Douglas Speirs Acknowledgments: Bill Gurney.
Collaborative Research: Copepods in a Warming Climate: A Pan-Regional Model of Arctic and Northwest Atlantic Systems coPIs: Davis, Ji, Beardsley, Chen.
One float case study The Argo float ( ) floating in the middle region of Indian Ocean was chosen for this study. In Figure 5, the MLD (red line),
Ocean-scale modelling of Calanus finmarchicus
Physical-biological interactions: regional to basin scales I. Pseudocalanus spp.: MARMAP data II. P. moultoni and P. newmani: U.S. Globec Georges.
Climate forcing of C. finmarchicus populations of the North Atlantic WHOI PIs: D. McGillicuddy and P. Wiebe UConn PI: A. Bucklin Rutgers PIs: D. Haidvogel.
Dynamics of the Gulf of Maine
US GLOBEC NWA Program Phase 4B Synthesis Workshop 10/2-3/2006 – 507 Clark Laboratory, WHOI Logistics Logistics – Continental breakfast today & tomorrow.
The principal objective of this project is to utilize the very comprehensive U.S GLOBEC broad-scale data sets that now exist to address two overarching.
Atlantic Herring Conservation Lauren Keyes Yu Kawakami Brigette Jones.
Copepods in a warming climate: A pan-regional model of Arctic and Northwest Atlantic systems PIs: Davis, Ji, Beardsley, Chen Goal: To better understand.
OEAS 604: Final Exam Tuesday, 8 December 8:30 – 11:30 pm Room 3200, Research Innovation Building I Exam is cumulative Questions similar to quizzes with.
GLOBEC NWA Program: Phase 4B Synthesis FVCOM-NPZD- Copepod Dynamics Calanus Diapause Larval Fish Dynamics Basin-scale Calanus IBM Data/model synthesis.
Sources of Synoptic CO2 Variability in North America Nick Parazoo Atmospheric Science Colorado State University ChEAS, June 5, 2006 Acknowledgments: Scott.
The 2009 Alexandrium bloom Donald M. Anderson- Woods Hole Oceanographic Institution Scott Libby - Battelle, Brunswick, ME.
Primary production & DOM OUTLINE: What makes the PP levels too low? 1- run Boundary conditions not seen (nudging time) - Phytoplankton parameter:
GLOBEC Phase IV. Broad-scale Synthesis of the Bank-wide patterns of Pseudocalanus distribution and abundance Ann Bucklin 1, Meredith A. Bailey 1, and Dennis.
The effect of tides on the hydrophysical fields in the NEMO-shelf Arctic Ocean model. Maria Luneva National Oceanography Centre, Liverpool 2011 AOMIP meeting.
Biological structure of Fisheries Resources In Space And Time.
Tracking life history of each particle Particles could be divided into three groups (Fig. 7) The red group’s period of copepodite stage shortened when.
Linking seasonal migratory patterns with prey availability in Steller sea lions Jamie N. Womble 1, Michael F. Sigler 2, Mary F. Willson 3 1 National Park.
Example #2: Northwest Pacific Zooplankton
Carbon Cycle Data Assimilation with a Variational Approach (“4-D Var”) David Baker CGD/TSS with Scott Doney, Dave Schimel, Britt Stephens, and Roger Dargaville.
FISHERIES POSTER SESSION
Population growth: determined by three factors:
Meghan Hartwick, Cheryl Whistler, Erin Urquhart
Comparison of modeled and observed bed erodibility in the York River estuary, Virginia, over varying time scales Danielle Tarpley, Courtney K. Harris,
Davis, Beardsley, Chen, Ji, Durbin, Townsend, Runge, Flagg
Invertebrate Predators
Marine Bacterioplankton Seasonal Succession Dynamics
Typology and classification of coastal waters in Estonia
Presentation transcript:

Intermingling of two Pseudocalanus species on Georges Bank D.J. McGillicuddy, Jr. Woods Hole Oceanographic Institution A. Bucklin University of New Hampshire Journal of Marine Research 60, pp , 2002.

P. moultoni P. newmani 1997 Broadscale Survey Data Species-specific PCR (Bucklin et al., 2001)

The forward model: an advection-diffusion-reaction equation C concentration v velocity K diffusivity Advection Tendency Diffusion Reaction (biological sources and sinks) C obs (t 0 ) C obs (t 1 ) time The forward problem

Observations: P. Moultoni Models Observations: P. newmani

Are the inverse solutions ecologically realistic? R(x,y,t) bounded by –100 to +100 individuals m -3 day -1 [most fall between -10 to +10] C 5 moulting potential: Mean C 5 abundance 2500 individuals m -3 (Incze pump samples: April 1997, May 1997, June 1995) Stage duration in GB conditions: 5 days (McLaren et al., 1989) Implied moulting flux of 500 individuals m -3 day -1

Are the inverse solutions ecologically realistic? Predation potential: Model predicted rates of 3-10% day -1 Bollens et al. specific rates of predation on C. finmarchicus and Pseudocalanus spp. copepodites based on observed predator abundance and feeding rates

Inverse method results in convergent solutions Geographically specific regions of growth/mortality These vary seasonally according to animal abundance patterns, the circulation, and their orientation Two main balances: –Tendency / source (weak currents or aligned gradients) –Tendency / source / advection Conclusions (I)

Resulting biological sources and sinks ecologically realistic -- R(x,y,t) bounded by independent rate estimates C 5 moulting flux Predation by invertebrates and vertebrates Emerging conceptual model: -- Distinct source regions in late winter P. moultoni on NW flank P. newmani on NE peak and Browns Bank -- During the growing season, GB circulation blends these reproducing (not interbreeding) populations such that their distributions overlap by early summer. Conclusions (II)

Physics -- errors in the circulation -- vertical shear Biology -- density dependence vs. “geographic” formulation -- multistage models, behavior, etc. Observational limitations -- only adults -- upper 40m Caveats

Are the inverse solutions ecologically realistic? R(x,y,t) bounded by –100 to +100 individuals m -3 day -1 [most fall between -10 to +10] C 5 moulting potential: Mean C 5 abundance 2500 individuals m -3 (Incze pump samples) Stage duration in GB conditions: 5 days (McLaren et al., 1989) Implied moulting flux of 500 individuals m -3 day -1 Predation potential: Hydroid ingestion rate: 0.25 cop. hydr -1 day -1 (Madin et al., 1996) Characteristic abundance: 10,000 hydranths m -3 Potential consumption rate: 2500 copepods m -3 day -1 Pseudocalanus adults ~15% of total postlarvae (Davis, 1987) Hydroid predation on Pseudocalanus: 200 individuals m -3 day -1

Pseudocalanus spp. MARMAP Concentration (# m -3 ) Two population centers: Western Gulf of Maine Georges Bank Davis (1984) hypothesis: Western Gulf of Maine is a source region for the Georges Bank population

General circulation during the stratified season Beardsley et al. (1997)

A first attempt to simulate the data…

Derivation of the adjoint model (1) Problem: Given observations C 0 (t 0 ) and C 1 (t 1 ), find R(x,y) that minimizes J Define a cost function J: Where λ=λ(x,y,t) are Lagrange multipliers

Derivation of the adjoint model (2) Adjoint model: We require R at the minimum of (and therefore J) where It can be shown that:

Convergence of the iterative procedure

Example results: Mar-Apr to May-Jun Red: source Blue: sink

Term-by-Term Diagnosis Observations Biological Source/Sink Advection Diffusion Tendency JF-MA MA-MJ MJ-JA

Chlorophyll-a MARMAP O’Reilly and Zetlin (1996) Jan-Feb Mar-Apr May-JunJul-Aug Sep-Oct Nov-Dec Davis (1984) Cutoff for food limitation 0.6 – 1.2 μg Chl l -1 Cutoff range

Chaetognaths MARMAP Sullivan and Meise (1996) Jan-FebMar-Apr May-JunJul-Aug Sep-OctNov-Dec

ECOHAB-GOM Observations Townsend et al. (2001) 1)Gulf-wide distribution 2) Association with coastal current 3) Center of mass shifts west-to-east as season progresses

Some thoughts on model design for HAB applications Forward models Inverse approaches McG et al. (1998) Fisheries Oceanography, 7(3/4), McG and Bucklin (2002) Journal of Marine Research, 60,

END

Term-by-Term Diagnosis Continued… Observations Biological Source/Sink Advection Diffusion Tendency JA-SO SO-ND ND-JF

Pseudocalanus spp. MARMAP Concentration (# m -3 )

Term-by-Term Diagnosis Obs Src Adv Dif Ten JF-MA MA-MJ MJ-JA JA-SO SO-ND ND-JF

Term-by-Term Diagnosis Obs Src Adv Dif Ten JF-MA MA-MJ MJ-JA JA-SO SO-ND ND-JF

A first attempt to simulate the data…

Term-by-term diagnosis Red: source Blue: sink

Observations: P. Moultoni Models Observations: P. newmani