GEOHAB modeling activities

Wolfgang FennelBaltic Sea Research Institute

Warnemünde (IOW)

at the University of Rostock

GEOHAB Modeling Workshop 2009

workshop is being planned to stimulate the development of modeling in relation to the study of Harmful Algal Blooms (HABs).

This workshop is being developed under the auspices of the SCOR/IOC program on Global Ecology and Oceanography of

Harmful Algal Blooms.  

The Workshop will take place from June 15 to 19, 2009 at the Martin Ryan Institute, National University of Ireland, and is open to

graduate students, post-docs and scientists.

The overall scientific goal of GEOHAB is to:

Improve prediction of HABs by determining the ecological and oceanographic mechanisms underlying their population dynamics, integrating biological, chemical, and physical studies supported by enhanced observation and modelling techniques. SP 2001, IP 2003

http://www.jhu.edu/scor/GEOHABfront.htm

Each system has site-specific and universal aspects

Modeling starts with considering of the required

• complexity of the model (number of state variables),

• resolution of physical processes

HABs occur in a variety of systems and settings.

‘Harmfulness’ is a societal, not a scientific, term.(i.e. it does not help to design models)

It points to the species that are harmful and definesthe locations, where they occur.

recommendations of the GMG (Warnemünde meeting, 5-6 April 2002)

“As a mean of identifying needs of regional programs and to interact with the GMG we propose the following list:

Tic list for involvement of modelling in regional GEOHAB programs

• What models are required to provide prediction ? • Can the accuracy of the model be ascribed to the required predictions before they will be useful? (e.g. Is a prediction that there is a 20% chance a HAB occurring within 1 week, useful?)• What kind of modelling HABs in the region is needed to help understand processes?• How strong is the occurrence of HABs controlled by physics?• What models of the region do exist?• What needs to be developed and implemented?• How can models help to design field work?”

Classes of relevant systemsUpwelling systems

advanced circulation models coupled to biogeochemical model components (GLOBEC, JGOFS)

Eutrophication, marginal seas coupled model systems to run 30-40 years scenarios

(climate variations, river discharges), (GLOBEC, JGOFS)

Thin layers Modeling thin layers (~ 50cm) in 3D circulation models implies a very high vertical resolution ( challenge)

Fjord and embayments local models, site-specific mixing and advection, advanced chemical biological components

Modeling can build on existing model system

Ocean General Circulation Models,community model, e.g. MOM, ROMS, POM, MICOM

MOM physical/ecosystem modeling in JGOFS,

ROMS physical/ecosystem modeling in GLOBEC regions. 

Species of interest and the food-web

Can we consider the HAB species alone(low concentration, minor effect on nutrients, weak interaction with grazers)?

What is the role of toxicity?

Are the cells toxic by pure coincidence or is the toxicity part of the survival strategy? Is toxicity a chemical weapon to keeping away other algae competing for nutrients or to chase away grazers, or making cells just inedible?

How can we decide these questions by observations?

Live cycle of species of interest

Overwintering

Dormant stages, resting in sediments?What triggers the awakening of resting stages?

Initiation of blooms?Locally, after being released from the sea bed?Accumulation of cells from the open ocean, by on-shore transports?

can be decided these by observations, or combining models and observations.

Golf of Main (e.g. Anderson et al., 2000; McGillicuddy et al., 2003) Alexandrium fundyenseLow abundance, advection of cells important,Weak interaction within the food web,Life cycle: cysts formation important,few state variables, nutrient fields prescribed by climatological data3d circulation models.

Baltic Sea(e.g.Kononen 2001; Neumann et al., 2002)

Cyanobacteria: Nodularia & AphanzoimenonNear sea-surface accumulation of biomass Strong interaction within the food webSeasonal succession,Competiton for nutrients, many state variables,3d physical-chemical-biological-model.

Example systems:

How to model HABs

• As continuous distributions, [aggregating many individuals in a state variable]?

• As individual particles, [individual based

models, IBM’s] ?

Models range from simple biogeochemical box models or Particle tracking (so-called ’individual based models’)

( first step for development, easy to understand and to use, provide forum for the interdisciplinary dialogue)

to

3D coupled physical chemical biological model systems (require super-computers, educated modeller)

Most measurements deal practically withindistinguishable ‘particles’ [within a group], e.g.,

• cell counts with microscopes, • optical plankton recorders,• acoustic backscatter.

The resulting concentrations represent state variables.

Choice of model depends on the problem at hand.

time scales:

A few days:Predict the spreading of a detected bloom for the next days, circulation model with a ‘biological’ tracer

The yearly cycleDescribe the annual cycle of the physical-biological processes, i.e., start, development and ceasing of the bloom in response to forcing scenarios. full coupled physical and biogeochemical model.

HAB‘s and Eutrophication

surface accumulations of cyanobacteria

Model issues:Coupled 3d circulation and biogeochemical models

Forcing data, including river loads

Wassertiefe(Meter)

01020304050607080>80

Rostock

Gdansk

Lübeck

Kiel

Klaipeda

Rïga

Tallinn

Sankt-Peterburg

Helsinki

Stockholm

Göteborg

Oslo

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Rügen

Born-

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F. Tauber, T. Seifert, B. Kayser, Institut für Ostseeforschung Warnemünde

Monitoring

5 times a year

along the ‘Talweg‘

P-E>0(60 km3/y)River discharge 480 km3/y

Mean depth = 50 mSill depth = 18 mVol.= 21 700 km3

The example of the Baltic Sea

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Salinity and oxygenTemperature(winter/summer)

(courteously, H. Siegel, T. Ohde)MODIS NASA (Δx=250m)

6.7.2001

Bio-chemical model for the Baltic Sea

NO3

O2

P

NH4

Zoopl.

Detrit.Fixation

Uptake

Mortality

Grazing

Recycling

Settling Resuspen-sion

Respira-tion

Denitrifi-cation

Atmosph.Input

Nitrifica-tion

N2

SolarRadiation

O2

P. onlyN2

Flagellates

Blue-Greens

Diatoms

Sediment

bulk-zooplankton can optionally be replaced by a stage resolving model!

eggs

nauplii

copepodites1

copepodites2

adults

(Neumann, JMS, 2000;Fennel Neumann, ICES Mar Sci Symp. 2003

Surface accumulations are easy to detect, but they are only one aspect!

Challenge:

to better understand and quantify the seasonal development of Blue-Greens in the water column.

Role of stratification is implicitly important, but not the key factor.

HAB’s in stratified systems (thin layers)

French west coast

Gentien, et al. 1998

Gentien et al. 1995, DSR 1,

Species of interest (Dinophysis, Gymnodinium) were found only in the thin layer !

Celtic sea - very thin layer containing a high density accumulation of Karenia mikimotoi (data by courtesy of Robin Raine)

transported westwards,upwelled at the southwest corner of Ireland.Raine et al. 2001Hydrobiologica

Building predictive models (t >> a few days) understanding of biological questions:

Why do the cells aggregate in thin layers?

Do the cells migrate vertically and what are the controls? e.g., response to light, chemical signals, etc.

Proxies for switches to control behavioral patterns as reaction to stimuli.

What kind of experiments can be designed to decide these questions?

Modeling thin layers (~ 0.5m) in 3D circulation Models implies a very high vertical resolution

problem

Way out:

high resolution modeling, advection can be very important, e.g., coastal jets, river plumes, up-and downwelling.

Example: dynamics of river plumes, stratified plumes

Eastern boundariesand

Upwelling systems

Deep Chlorophyll Maximum, DCM. can be simulated for non-sinking model flagellates, limited by light and nitrate.

Model simulationBenguela system,off Angola, 8oS,By courtesy ofM.Schmidt

Note, the model system is virtually the same as for the Baltic.

Alongshore, y-z-section shows that the DCM occurs only in the downwelling, not in the upwelling region.

By courtesy of M.Schmidt & S.Schäfer

Combining models and observation:Experimental simulations with sinking cells can give a clue about possible deposition areas to guide field studies (search for seed beds)

60 days, strong wind eventsinitial concentration 0.1g/cm2

Summary:

Modeling HAB‘s can largely build on existing biogeochemicalmodels (with some modifications).

Specific HAB aspects of the models require a quantitative understanding of toxicity for food-web interaction, and of the live cycles.

thanks

How to model behaviour?

If .... then ..... decisions in response to environmental ourinternal signals (fuzzy logic)

Fuzzy logic, a multivalued logic developed to deal with imprecise or vague data. (as opposed to a binary logic, where everything can be expressed in binary terms: 0 or 1, black or white, yes or no) Fuzzy logic allows for a set of values between 0 and 1, shades of gray. Fuzzy logic may used with an expert system, logical inferences can be drawn from imprecise relationships. Fuzzy logic theory was developed by Lofti A. Zadeh at the Univ. of California in the mid 1960s.

Or, alternatively, by evaluation functions, which map a set of decisions on a number.

Note that if... then ... statements are inefficient in complex model codes.

Vertical distributionApril 02 July 02

T [°C]; S [PSU]; O2 [ml l-1]0 3 6 9 12 15 18 0 3 6 9 12 15 18

TemperatureSalinityOxygen

courteously GLOBEC Germany: J. Renz, J. Dutz, C. Möllmann, H.-J. Hirche

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Evaluation functionassesses the quality of the environment,force migration when requiredNeumann&Fennel, Ocean Modelling,(2005), (in press)

Sketch of the fi‘s, which characterize the potential response Neumann& Fennel, Ocean

Modelling,(2005), (in press)

Neumann& Fennel, Ocean Modelling,(2005), (in press)

First Principles? Genetic code versus phenomenological theory?[Starting from genetics seems not (yet) to be feasible]

Phenomenological theorypostulates that organisms grow, divide and produce toxins. [Knowledge of their genetic constitution is not necessarily required]

Properties (nutrient uptake, primary production, grazing,...) and Behaviour (vertical migration, foraging, avoidance, adjustments to habitats,.....)

are observable features, which can be quantified and formulated in equations. [The equations do not explain the features, but provide the base to describe system properties, future developments etc.]