Handbook of Ecological Indicators for Assessment of Ecosystem Health - Chapter 7 doc

The correlations among the 11 indicators were examined, and the extent to which the 5 thermodynamic indicators: exergy, exergy destruction, exergy produc-tion, exergy destruction/exergy,

CHAPTER 7

Application of Ecological and Thermodynamic Indicators for the Assessment of the Ecosystem

Health of Coastal Areas S.E Jørgensen

Six ecological indicators, taken from Odum’s attributes (1969, 1971), and

5 thermodynamic indicators were studied in 12 coastal ecosystems The correlations among the 11 indicators were examined, and the extent to which the 5 thermodynamic indicators: exergy, exergy destruction, exergy produc-tion, exergy destruction/exergy, and specific exergy, can be applied to assess ecosystem health was discussed It can be concluded that the thermodynamic indicators cover a range of important properties of ecosystems and correlate well with several of Odum’s attributes, which are widely applied as ecological indicators To give a sufficiently comprehensive assessment of ecosystem health for environmental management, however, will probably require other indicators in addition to the thermodynamic indicators

7.1 INTRODUCTION This chapter presents the results of a study in which several ecological indicators (including recently proposed thermodynamic indicators, exergy, exergy destruction, exergy destruction/exergy, exergy production increase in exergy, and specific exergy) were applied to 12 coastal ecosystems (described in detail by Christensen and Pauly, 1993) The extent to which the ecological indicators are correlated with the thermodynamic indicators will be explained

A recommendation on the application of thermodynamic indicators for the assessment of ecosystem health in environmental management can probably

be derived from these results Figure 7.1 gives an example of the steady-state models available for all 12 case studies

7.2 RESULTS The 12 ecosystems are:

1 Tamaihua, a Coastal Lagoon in Mexico

2 Celestun Lagoon, southern Gulf of Mexico

3 A coastal fish community in southwestern Gulf of Mexico

4 The Campeche Bank, Mexico

5 The Maputo Bay, Mozambique

6 A Mediterranean lagoon: Etang de Tahu, France

7 Pangasinan coral reef, Philippines

Figure 7.1 Flow diagram of the fish community of Tamiahua Lagoon, Mexico The diagram

indicates the results by use of ECOPATH II in g/m 2 for biomasses and in g/m 2 /year for rates.

8 Caribbean coral reef

9 Yucatan Shelf Ecosystem, Mexico

10 Continental Shelf Ecosystem, Mexico

11 Shelf Ecosystem, Venezuela

12 Brunei Darassulak, South China Sea

The following ecological indicators were determined for all 12 ecosystems:

Biomass (g dry weight/m2)

Respiration (g dry weight/m2

y)

Exergy (kJ/m2

)

Exergy destruction (kJ/m2

/year)

Diversity as number of species included in the model (—)

Connectivity as number of connections relatively to the total number of possible connections (—)

Complexity expressed as ‘‘diversity’’ times ‘‘connectivity’’ (—)

Respiration/biomass ¼ B/A (year  1)

Exergy destruction/exergy ¼ D/C (year  1) Jørgensen (2002)

Exergy production (kJ/m2

/year) Jørgensen (2002)

Specific exergy (kJ/g) Jørgensen (2002)

Using a correlation matrix it was found that only the following of the 11 indicators were correlated with a correlation coefficient  0.64:

Exergy production to exergy, R2¼0.93, see Figure 7.2

Respiration to exergy, R2

¼0.98, seeFigure 7.3

Respiration to biomass, R2¼0.68, seeFigure 7.4 Notice in this context that respiration is considerably better correlated to exergy than to biomass

Respiration to exergy production, R2¼0.855, seeFigure 7.5

Figure 7.2 Exergy production plotted against exergy.

Exergy destruction to respiration, R2¼0.87 seeFigure 7.6.

Respiration/biomass to specific exergy, R2

¼0.86, seeFigure 7.7

Respiratory to exergy dissipation or destruction, R2¼0.86, seeFigure 7.8

7.3 DISCUSSION Higher exergy levels are, at least for the examined marine ecosystems, associated with higher rates of exergy production which is consistent with the

Figure 7.4 Respiration plotted against biomass Notice that the correlation in Figure 7.3 is

considerably better than this correlation.

Figure 7.3 Respiration plotted against exergy.

translation of Darwin’s theory to thermodynamics by the use of exergy As an ecosystem develops, its biomass increases, and when all the inorganic matter is used to build biomass, a reallocation of the matter in form of species with more information may take place Increased information gives increased possibility

to build even more exergy (information)

The respiration levels for the various examined ecosystems are considerably better correlated with the exergy levels than with the amount of biomass in the examined ecosystems, although there is a tendency slope respiration/exergy to decrease as exergy increases (as shown inFigure 7.3) This tendency cannot be

Figure 7.6 Exergy dissipation plotted against respiration.

Figure 7.5 Respiration plotted against exergy production (increase in exergy storage).

shown to be statistically significant as it would require information from more marine ecosystems

Biomass includes plants (algae) that have relatively low exergy and also lower respiration It explains why exergy with high weighting factors for fish and other higher organisms is better correlated with respiration than biomass (see Figures 7.3 and 7.4) The relationship is not surprising, as more stored exergy means that the ecosystem becomes more complex and more developed, which implies that it also requires more energy (exergy) for maintenance More developed ecosystems also mean that bigger and more complex organisms become more dominant As bigger organisms have less respiration relative to the biomass (according to the allometric principles), it is not surprising that the ratio of respiration to exergy (the slope of the plot in Figure 7.3) decreases with

Figure 7.8 Respiration is plotted versus exergy dissipation (or destruction).

Figure 7.7 Respiration/Biomass plotted against specific exergy.

increasing exergy These results are also inconsistent with Figure 7.5, where respiration is well correlated with exergy production A high respiration level is associated with higher organisms with more information, which again gives the opportunity to increase the information further

The correlation between the respiration level and the rate of exergy destruction inFigure 7.6is not surprising, as the exergy destruction is caused

by respiration It is just two sides of the same coin

Figure 7.7indicates that the specific exergy for the examined ecosystems — higher specific exergy means more dominance of higher organisms — is well correlated with the ratio of respiration to biomass, which is also consistent with the results presented in Figure 7.5

The results are consistent with the discussion in chapter 2, where the concepts of exergy-specific exergy were presented and associated with ecosystem health characteristics:

1 Exergy measures the distance from thermodynamic equilibrium Svirezhev (1992) has shown that exergy measures the amount of energy needed to break down the ecosystem Exergy is therefore a reasonably good measure of the following (compare with Costanza, 1992)

a Absence of disease (may be measured by the growth potential)

b Stability or resilience (destruction of the ecosystem is more difficult the more exergy the ecosystem has)

c Vigor or scope for growth (notice in this context thatFigure 7.2shows

a good correlation between exergy and exergy production [growth])

2 Specific exergy measures the organization in the sense that more developed organisms correspond to higher specific exergy More developed organisms usually represent higher trophic levels It implies a more complicated food web Specific exergy is a therefore a reasonably good measure of:

a Homeostasis (more feed back is present in a more complicated food web)

b Diversity or complexity

c Balance between system components — the ecosystem is not dominated by the first trophic levels as this is usually for ecosystems

at an early stage

Notice that exergy or specific exergy is not correlated to diversity or complexity as determined by the connectivity Complexity of ecosystems has several dimensions as illustrated by this chapter: complexity due to: (1) the presence of more complex organisms; (2) diversity; and (3) a more complex network These three complexities increase independently of each other

7.4 CONCLUSIONS Eleven ecological and thermodynamic indicators were examined for 12 marine ecosystems The results showed that a good correlation could only be

obtained for the following pairs: exergy/exergy production, exergy/respiration, biomass/respiration, exergy production/respiration, respiration/exergy dissipa-tion, specific exergy/respiration/biomass

It was discussed that exergy and specific exergy and the other three thermodynamic indicators together cover the properties normally associated with ecosystem health (Costanza, 1992) It is probably not possible to assess the health of such a complex system as an ecosystem by means of only two to five indicators, which is also consistent with the lack of correlation between these two concepts and the other attributes included in this examination It can, however, be assessed that exergy is a good measure of the ability of the ecosystem to grow (seeFigure 7.2) Exergy is also a good measure of the energy (exergy) required for maintenance — better than biomass on its own — as more stored exergy and higher exergy production mean that more exergy is also needed for maintenance (see Figure 7.3, Figure 7.5 and Figure 7.6) Exergy or specific exergy is not well correlated with diversity (expressed simply

as the number of state variables in the model) or complexity (measured simply

as the product of number of state variables in the model and the connectivity), which is consistent with the results of several other chapters in this volume On the other hand, specific exergy is a good expression for the presence of more developed organisms (and a more complex ecosystem)

The two concepts of exergy and specific exergy cover a certain range of properties that we generally associate with ecosystem health They should, however, be supplemented by other indicators in most practical management situations, as they are not strictly correlated to other important attributes

REFERENCES

Christensen, V and Pauly, D Trophic Models of Aquatic Ecosystems ICLARM, Manila, Philippines 1993, 390 p

Costanza, R ‘‘Toward an operational definition of ecosystem health,’’ in Ecosystem Health, New Goals for Environmental Management, Costanza, R., Norton, B.G., and Haskell, B.D., Eds Island Press Washington, D.C., 1992, pp 239–256 Jørgensen, S.E., Nielsen, S.N., and Mejer, H Emergy, environ, exergy and ecological modelling Ecol Mod 77, 99–109, 1995

Jørgensen, S.E Integration of Ecosystem Theories: A Pattern 3 Kluwer, Dordrecht,

428 p

Odum, E.P The strategy of ecosystem development Science 164, 262–270, 1069 1969 Odum, E.P Fundamentals of Ecology W.B Saunders, Philadelphia, 1971

Svirezhev, Y Exergy as a measure of the energy needed to decompose an ecosystem Presented as a poster at ISEM’s International Conference on State-of-the-Art

of Ecological Modelling, 28, 1992, Kiel