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www.pol.ac.uk
3-Dimensional Ecosystem Modelling for Shelf SeasOr
Putting the small-scale into the large-scale
Roger Proctor, Jason Holt (POL)Icarus Allen, Jerry Blackford (PML)
Tom Anderson, Boris Kelly-Gerreyn (SOC)Mike Ashworth (CCLRC)
(with thanks to others at PML, CEFAS, SAHFOS, Met Office, MBA, DARDNI)
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The marine ecosystem
Six-year composite of annual primary production
SeaWifs composite, courtesy Goddard
Why shelf seas are important
Though the world ocean covers 70% of the earth's surface, it accounts for only 46% of all primary production (Field et al., 1998).
While shelf seas and estuaries constitute only a small proportion (8%) of the area of the global ocean, they account for ~20% of ocean primary production (Liu et al., 2000).
Shelf seas are productive. By comparison, the open ocean is virtually a biological desert.
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Shelf Seas: a different approachThe processes active in shelf seas (e.g. tidal stirring, land-ocean interaction) require a different approach to the open ocean in order to resolve their impact on biogeochemical exchanges.
European shelf seas are connected to the open ocean and thus affected by the variability in the NE Atlantic. Rivers discharge into the coastal zones bringing buoyancy flux, nutrients, SPM (terrigenous and anthropogenic) and contaminants.
Tidal and wind-wave stirring in the shallow regions (< 50m depth), about 50% of the European shelf seas, causes re-suspension and transport of SPM, affecting the optical and biogeochemical water properties and surface and bed boundary exchanges.
There is recycling and exchange of nutrients between sea bed and water column.
The CONTROLLING bio-physical interactions, governed by water column structure, mixing, and turbulence, are variable both spatially and temporally with tidal mixing fronts playing a key role.
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Shelf Seas: a different approachThe processes active in shelf seas (e.g. tidal stirring, land-ocean interaction) require a different approach to the open ocean in order to resolve their impact on biogeochemical exchanges.
European shelf seas are connected to the open ocean and thus affected by the variability in the NE Atlantic. Rivers discharge into the coastal zones bringing buoyancy flux, nutrients, SPM (terrigenous and anthropogenic) and contaminants.
Tidal and wind-wave stirring in the shallow regions (< 50m depth), about 50% of the European shelf seas, causes re-suspension and transport of SPM, affecting the optical and biogeochemical water properties and surface and bed boundary exchanges.
There is recycling and exchange of nutrients between sea bed and water column.
The CONTROLLING bio-physical interactions, governed by water column structure, mixing, and turbulence, are variable both spatially and temporally with tidal mixing fronts playing a key role.
Pelagic AND benthic components
must be included
in any shelf sea biogeochemical study
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Why models?
Conceptual models are derived from empirical data
Numerical models are constructed using the conceptual framework and parameterised from empirical data
These are embedded into existing marine system models to scale processes up in space and time.
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Ecosystem Modelling
THREE COMPLEMENTARY PURPOSES
Heuristic: to test our understanding of ecological processes.
Application development: Ecosystem models that span eutrophic - oligotrophic, spatial and temporal trends.
Prediction: Forecast and field estimation capability.
There is a strong interdependency between each of these roles
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The Marine Ecosystem
A marine ecosystem is a natural unit of biotic and non biotic components which interact to form a stable system in which a cyclic interchange of materials takes place between biotic and non biotic units.
The biota are subdivided into three primary functional roles
• Producers (e.g. Phytoplankton)• Consumers (e.g. Zooplankton, Fish)• Decomposers (e.g. Bacteria)
The non biotic components consist of
• Inorganic Nutrients• Dissolved Organic Matter• Particulate Organic Matter
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Model type
Bulk Biomass Functional Group Models (FGM’s)
FGM’s divide the ecosystem into aggregated groups representing basic functional roles (production, consumption and decomposition). Here we have producers (phytoplankton), consumers (zooplankton and zoobenthos) and decomposers (pelagic and benthic bacteria).
These are often then subdivided into size classes to create a foodweb.
Physiological processes and population dynamics are described by fluxes of carbon or nutrients between functional groups.
It is assumed that whatever compositional changes occur within each pool over time, they are not large enough to cause substantial and persistent errors in the prediction of pool scale rate processes.
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A case study:
The western Irish Sea
A small region of sea which thermally stratifies in summer separated from well-mixed seas by a tidal front
Why this region?Semi-enclosed, manageable boundariesDisplays most shelf sea processesContains some data – area is a Nephrops fishery
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western Irish Sea
stratified
Well-mixed
The ‘Gyre’
Stratified site (90m depth).
Well mixed site(20m depth).
Study sites
Measurements collected
By Richard Gowen, DARDNI
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The Coupled Model
S,T,u,v,w,
SPM, Kh, Kv
ERSEM
In NERC Marine Productivity, we used 2 different FGM’s:
Anderson/Kelly-Gerreyn; ERSEM (European Regional Seas Ecosystem Model)
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Phytoplankton
Zooplankton
Pico-p Flagellates Diatoms
Dissolved
Particulates
Micro-z Meso-zHetero-trophs
Small Cells Large Cells
Si
NH4
NO3
PO4
CO2
Organics
Nutrients
Dino-f
BacteriaDMS+DOC
BacteriaDMSP+DOC
BacteriaDOC
ERSEM Pelagic component
Producers
Consumers
Decomposers
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ERSEM Benthic pelagic coupling
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ERSEM Benthic pelagic coupling
A summary of benthic pelagic coupling
Input from the pelagic system, either phytoplankton or detritus, is converted to benthic detritus on reaching the seabed.
The nutrients contained within these detrital pools are either remineralised by biological activity or undergo dissolution to be released into the pore waters of the benthic sediment.
Porewater nutrient profiles and bio-irrigation effects determine the diffusive fluxes across the benthic pelagic interface.
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The Model Domains
Hierarchies of nest models from ~12k to ~1.8km
12km 1.8km1-d
POLCOMS: POL Coastal Ocean Modelling System
www.pol.ac.uk/home/research/polcoms
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Setting the physical environment
Temperature structure in the Gyre
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Below Thermocline Heating
Average for July 1995Advective and diffusive terms in Temperature Equation
Calculated below thermocline where ∆T<0.5oC
Dashed Contour is∆T=2 oC
Holt & Proctor, 2003, JPO, 33: 2288-2306
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Quasi-1D experiments
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Numerical experiments
1-dimensional ‘cut-down’ POLCOMS + A/K-G:experiments in ‘top-down’, ‘bottom-up’ control(Kelly-Gerreyn et al, 2004, ECSS, 59: 363-383)
3-dimensional POLCOMS + ERSEM:large scale and role of horizontal processes(Holt et al, JGR, in press)
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1-D conclusions
At the well mixed site …
Either:
BOTH bottom-up AND top-down factors control seasonal succession
Or:
Bottom-up or top-down factors control seasonal succession
And at the stratified site …
Bottom-up control via stratification prevents diatoms succeeding in summer
Also “low” microzooplankton grazing pressure allows non-diatoms to dominate
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3-D complexity
Temperature oC
Irish Sea surface currents & temperatures,JDay114 (late May)
Complex eddystructure
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Detail in nested 1nm Irish Sea model:Patchiness
Nitrate
Chlorophyll
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Comparison with CEFAS Scanfish Chlorophyll dataNeed more of this kind of data!
Scanfish data courtesy of Liam Fernand, CEFAS
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Time Series of Diatoms and Flagellates in Gyre
Intermittent production
in surface layer caused
by advection of
nutrients into domain
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Advective and diffusive processes
Advective
flux
Diffusive
flux
Average summer surface layer integrated
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Cumulative Production
Observed annual production ~140 gC m-2
Nutrient fluxes
Mtonnes/y
Proctor et al., 2003,
Sci Tot Env, 314-315: 769-785
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What next?
Better data:
In space, time and type
(e.g. Scanfish,
fixed moorings – coastal observatories,
Case II waters satellite measurements)
The crunch:
Short term forecasting of ecosystem response
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Short term ecosystem forecasting: POLCOMS-ERSEM
IndicatorsTypical indicators produced by model
based marine monitoring system include
• plankton concentration
• total, new or primary production
• peak production of algal groups
• bottom oxygen concentrations
• zoobenthos
• oxygen consumption
• nutrient concentration and ratios
• nutrient transports to target areas
Ocean Colour
SmartBuoysForecasting for spring 2004
FerryBox
Products to users, e.g. Govt Agencies
1nmCOBS SNS
Shelf
GMES MERSEA-1: www.nersc.no/MERSEA.S1 POL COBS: coastobs.pol.ac.uk
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Seasonal cycle from 6km model
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The real test:
50 year hindcast (can we model observed decadal change?)
50 year forecast of impact of future climate change
(using models to aid marine management)
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The test: simulating climate change
Reid et al. (1998) Nature
Long-term changes at the base of the food web
• Phytoplankton abundance in North Sea and NE Atlantic
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The test: simulating climate change
Massive increases in meroplanktonCentral North Sea
Echinoderm larvae
see Lindley & Batten (2002) JMBA
Decapod larvae
Fisheries or climate?
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The test: simulating climate change
Biogeographic Changes in the Northeast AtlanticWarm temperate slope species
Beaugrand et al. Science 2002
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Making a start
1960 2000Forced by POL surge model, and DNMI and NCEP met. data
UK hydrometric areas for salinity modelling
Temperature
Salinity
40 Year Irish Sea Simulation (3.5km)
Time series at Cypris Station
Courtesy EmmaYoung, POL
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Summary
• Shelf seas coupled physics-ecosystem models now at a ‘useable’ stage
• Need good datasets to test them (space, time, multi-parameters)
• Need to explore what they can tell us, and what they can’t
• Need further development for whole shelf management
(we have plans, no money)
