THE USE OF ECO-EXERGY IN OCEANOLOGY:

APPLICATION TO POSIDONIA OCEANICA MEADOWS

Dorothée Pête, Branko Velimirov & Sylvie Gobert

PhD student, University of Liège

Introduction

Exergy = « Useful work a system can perform when brought into equilibrium with its environment » (Szargut et al., 1988)

= distance from thermodynamic equlibrium

Applying this theory to understand ecosystems and to detect environmental perturbations

What a mystification!

It’s metaphysics!

Are you crazy?

Thermodynamic theory for Ecosystems(S. E. Jørgensen)

Thermodynamic equilibrium = Inorganic

soup

Take energy in:

Matter

Storage in biochemical constituents

Thermodynamic theory for Ecosystems(S. E. Jørgensen)

Trends to keep away from thermodynamic equilibrium when becoming more complex (Prigogine, 1980)

Loose energy:

Matter

Maintenance

Trophic webs

Exergy index or eco-exergy: a practical way to apply the exergy theory to

ecosystems

• Ex (kJ/volume or surface)

= distance between the system and the thermodynamic equilibrium

when the ecosystem is moving away from thermodynamic equilibrium

when the ecosystem is getting closer from its climax, its ecological optimum

= « work capacity possessed by organisms and ecological networks of organisms due to biomass and information embodied in their genome and the amino acid sequence of proteins » (Jørgensen et al., 2010)

i

n

ii CEx .

• βi:

-β-factor of the ith organism

-defined on a genetic basis: enzymes and proteins, defined by DNA, are driving life processes (Jørgensen et al., 2005)

- kind of approximation of organisms complexity

- higher for « specialised » organisms

- expressed relatively to detritus (no genetic information, only free energy of the organic matter, ≅ 18,7 kJ.g-1)

- ex: β = 1 for detritus, 8,5 for bacteria and 133 for nematods

Exergy index or eco-exergy

Formula:

• Ci: Biomass of the ith organism

Specific exergy (Structural exergy, Silow, 1998)

Exsp = expresses the presence of more specialised organisms in the ecosystem

n

ii

sp

C

ExEx

Ex = informations on the capacity of the ecosystem to develop and get more complex

Exsp = information on the « quality » of the biomass

Use of Ex and Exsp in Oceanology

• 2 main uses:

- Modeling of ecosystems development (plankton dynamics)

- Indicators of environmental quality

Use of Ex and Exsp in Oceanology

Can we use them to detect a perturbation in a marine ecosystem

early?

Exportation of vegetal

biomass

Production of vegetal

biomass Production of

animal biomass

Biodiversity hot spot

Basis for food webs

Spawning and breeding ground

Hydrodynamic protection

Stabilization of the bottom

Trapping of suspended particules

• Focus ecosystem = Posidonia oceanica meadow

- What? Posidonia oceanica = endemic seagrass of the Mediterranean Sea

• Focus ecosystem = Posidonia oceanica meadow

- Why?

P. oceanica = descriptor of the quality of the Mediterranean coastal zone

University of Liege:- Tradition of marine research (Biology, chemistry,

physics, modeling)- Research station in Calvi Bay, Corsica: STARESO (STAtion

de REcherche Sous-marine et Océanographique)- Years of experience in the Mediterranean Sea

with a special focus on the Posidonia oceanica ecosystem

Can we use them to detect a perturbation in a marine ecosystem

early?

In Calvi Bay, pristine and perturbated meadows are well known.

Good zone to test the use of Ex and Exsp

Can we use them to detect a perturbation in an ecosystem early?

Posidonia oceanica meadow has a low turnover.

Sediment = final container of pollutants (sedimentation)

Microbenthic loop: organic matter (OM), microphytobenthos (microscopic algae), meiofauna (microscopic animals), bacteria

Important sub-system in P. oceanica meadows

High turnover

Goals

Clarification and validation of the use of Ex and Exsp as descriptors of anthropogenic perturbations in P. oceanica beds

Effects of nutrients and organic matter inputs which are the main perturbations in the Mediterranean coastal zone

New method to measure and detect perturbations affecting P. oceanica meadows

Precise, early and global method

Sampling

What?

- sediment cores (vertical profile)- Biomass determination for every component of the microbenthic loop.- sediment and environment parameters

How to validate an index and a method?

• Spatial heterogeneity at small scale

• Comparison between a pristine and a perturbated site

• In situ experiments

Sampling sites

10 m, 22 m

Small scales

Alteration

Shading

= Reference site

Fish farm

22 m

Seasonal variations

Perturbated site

Ad

ap

ted

fro

m V

erm

eule

n e

t al., 2

01

1

Fro

m S

TA

RES

O S

A

From STARESO SA

Spatial heterogeneityS

TA

RES

O

125 cm

25 cm

3 grids

March, June, November 08, March 09

12 nodes/grid (uniform random)

3 cores/node

Results : DIVA analysisBiomass of bacteria

0-1 cm 1-2 cm

5-10 cm

40

120

50

130

60

140

260

60

140

240

2-5 cm

Heterogeneity and « hot spots » of biomass

Spatial heterogeneity : Estimation of Ex & Exsp

0

1000

2000

3000

4000

5000

6000

0

1

2

3

4

0-1 cm 1-2 cm 2-5 cm 5-10 cm0

1000

2000

3000

4000

November 2008

March 2008

June 2008

March 2009

Sediment depth 0-1 cm 1-2 cm 2-5 cm 5-10 cm0123456789

1011121314

Sediment depth

Median ± rangeFor 10 cm

For 1 cm

• Important heterogeneity especially for the 1st cm of the sedimentMost dynamic slice, exchanges with the water columnBUT probably the most affected by environmental perturbations

• The less heterogenous slice is the 5-10 cmLess dynamic slice and no exchanges with the water columnAnoxic conditions for most samples BUT « old » sediment

Choose the 5-10 cm to prevent heterogeneity effects

Spatial heterogeneity : Ex & Exsp

5-10 cm

0

100

200

300

400

0

1

2

3

• Important heterogeneity in spite of the choice• No real seasonal variability

Seems stable along the year

Median ± range

STARESO vs. Fish farm: 5-10 cm

0

50

100

150

200

250

300

350Fish farm

STARESO

0.00

0.25

0.50

0.75

1.00

1.25

1.50

1.75Fish farm

STARESO

• Awaited results for November 2008 only Not an estimation…

Median ± range

• No difference in Exsp

No difference in biomass « quality » between sites

• This estimation is not able to catch the difference in EX between sites.

• In November 2008, Ex STARESO>Ex Fish farmSTARESO is closer from the ecosystem climax than the fish farm.

• No difference in Exsp.

No difference in the « complexity » of organisms living in the ecosystem. The ecosystem is able to adapt itself to this perturbation (Silow, 1998).

In situ experiments: Sediment alteration

Site: STARESO, 10 m depth. Duration: 3 months (from end of May to end of August 2009).

Alteration (mimic pollution by fish farms or dredging):- 500 ml of sediment were added once a week on 21 marked points in a 3x3 m frame.

In situ experiments: Shading Shading ( in turbidity because of in nutrients concentration, fish farms, sewages, land farms):

- 3 nets (3x1 m, mesh size: 0,5 mm2) about 50 cm from the canopy.

- Light extinction: 52 ± 1,6 %- Cleaning once a week to avoid fouling

In situ experiment : Ex 5-10 cm

0

50

100

150

200

250 Control

0

50

100

150

200

250 Alteration

0

50

100

150

200

250 Shading

• No difference between periodsEstimation? Too short experiment?

Median ± range

In situ experiment : Exsp 5-10 cm

0.00

0.25

0.50

0.75

1.00

1.25

1.50

1.75 Control

0.00

0.25

0.50

0.75

1.00

1.25

1.50

1.75Alteration

0.00

0.25

0.50

0.75

1.00

1.25

1.50

1.75 ShadingMedian ± range

• No real difference between periodsEstimation? Too short experiment?

Conclusions

Spatial variability• Important heterogeneity BUT less important in the 5-

10 cm sediment depth zoneChoice of the 5-10 cm sediment horizon to compare

samples even if it is maybe less precise

Fish farm vs. STARESO• Ex STARESO>Ex Fish farm in November 2008 for the

5-10 cm horizonEx seems able to dicriminate both sites

In situ experiment• No difference along the experiment.Too short experiment to see an impact…

• Use of Ex and Exsp as a tool to detect perturbations in the Mediterranean coastal zone is not easy to validate in this part of P. oceanica ecosystem.

• Important to link the results with environmental parameters to understant why it works or not.

• Work in progress…

Conclusions

Thank you!

Tanks to Loïc Michel, Renzo Biondo, Gilles Lepoint, Sylvie Gobert, Branko Velimirov, people of the STARESO, students, cleaning team, spreading team, repairing team,…