Sven Erik Jørgensen

Handbook of Ecological Indicators for Assessment of Ecosystem Health

Ecological Indicators Introduction S. E. Jorgensen Application of Indicators for the Assessment of Ecosystem Health S. E. Jorgensen, Fu-Liu Xu, Joao C. Marques, and Fuensanta Salas Eco-Exergy as Ecological Indicator S. E. Jorgensen Emergy Indices of Biodiversity and Ecosystem Dynamics Mark T. Brown and Sergio Ulgiati Eco-Exergy to Emergy Flow Ratio for the Assessment of Ecosystem Health F. M. Pulselli, C. Gaggi, and S. Bastianoni Natural Capital Security/Vulnerability Related to Disturbance in a Panarchy of Social-Ecological Landscapes Nicola Zaccarelli, Irene Petrosillo, and Giovanni Zurlini Species Richness in Space and Time as an Indicator of Human Activity and Ecological Change Erich Tasser, Georg Niedrist, Patrick Zimmermann, and Ulrike Tappeiner Landscape Development Intensity and Pollutant Emergy/Empower Density Indices as Indicators of Ecosystem Health Mark T. Brown and Kelly Chinners Reiss Ecosystem Services and Ecological Indicators Robert Costanza Assessment of Ecosystem Health Application of Ecological Indicators for the Assessment of Wetland Ecosystem Health S. E. Jorgensen Application of Ecological Indicators for the Assessment of Ecosystem Health in Estuaries and Coastal Zones Joao C. Marques, Fuensanta Salas, J. Patricio, J. Neto, H. Teixeira, and R. Pinto Application of Ecological and Thermodynamic Indicators for the Assessment of Ecosystem Health of Lakes Fu-Liu Xu Application of Ecological Indicators in Forest Management in Africa Kouami Kokou, Adzo Dzifa Kokutse, and Kossi Adjonou Using Ecological Indicators to Assess the Health of Marine Ecosystems: The North Atlantic Villy Christensen and Philippe Cury Indicators for the Management of Coastal Lagoons: Sacca di Goro Case Study J. M. Zaldivar, M. Austoni, M. Plus, G. A. De Leo, G. Giordani and P. Viaroli Ecosystem Indicators for the Integrated Management of Landscape Health and Integrity Felix Muller and Benjamin Burkhard Integrated Indicators for Evaluating Ecosystem Health: An Application to Agricultural Systems V. Niccolucci, R. M. Pulselli, S. Focardi, and S. Bastianoni Ecological Indicators to Assess the Health of River Ecosystems Carles Ibanez, Nuno Caiola, Peter Sharpe, and Rosa Trobajo Appendix Index

Emergy, environ, exergy and ecological modelling

Abstract Hitherto, applied calculations of exergy for higher organisms have been based on traditional thermodynamic considerations, which did not take into account the organizational level of organisms. It seems reasonable to include such perspectives in a thermodynamic evaluation of ecosystems. Therefore, two methods that are theoretically more sound for calculations of exergy for higher organisms are proposed in this paper. The first is based upon the thermodynamic information due to genes. The method is rooted in statistical thermodynamics and should be considered the best candidate for exergy calculations of ecosystems including higher organisms. The second method is a parallel to the method used for calculation of emergy, and is based on the cost of free energy computed from an ecological network. Because this method does not consider the increase of information due to evolution, it should be considered theoretically less sound than the first mentioned method. It is, however, interesting to compare the two methods, as they to a certain extent reflect the differences between emergy and exergy. Emergy attempts, as exergy, to account for the quality of energy by the use of a transformity factor. The transformity factors for calculation of emergy are found from the network as the number of solar equivalents that it has cost to construct the considered organism. Emergy is therefore often more easy to compute, provided that the ecological network is known, while exergy after the new methods for calculations presented here seems to have a better theoretical basis. The two methods tested for calculation of exergy give different results, but the results are in the same order of magnitude. The two major problems in development of ecological models are the parameter estimation and the selection of the best model structure. The latter requires that more ecological system properties are incorporated in our models. A procedure based upon recent developments in ecosystem theory is proposed to meet this requirement. It should be considered a first approach to a theoretical improvement of the modelling procedure for development of models with more ecological properties.

A eutrophication model for a lake

Abstract Different lake models were tested against measured values. It was found that a model based upon phytoplankton population dynamics gave a better description than a model based upon Monods kinetics. The calibration of the model showed that it was necessary to use a recently developed submodel for sediment—water nutrient exchange. Furthermore, the work showed that it was essential to include in the model three trophic levels, denitrification, a time dependent nitrogen input and Steeles expression for the grazing rate. A prediction for different waste-water treatment alternatives was worked out.

Ecosystems emerging. 4 : growth

Abstract This fifth paper in the series on Ecosystems Emerging treats the properties of ecosystem growth and development from the perspective of open (paper four), nonequilibrium, thermodynamic systems. The treatment is nonrigorous and intuitive, interpreting results for living ecosystems based on parallels between these and the much simpler nonliving ones treated rigorously in thermodynamic theory. If an (open, nonequilibrium) ecosystem receives a boundary flow of energy from its environment, it will use what it can of this energy, the free energy or exergy content, to do work. The work will generate internal flows, leading to storage and cycling of matter, energy, and information, which move the system further from equilibrium. This is reflected in decreased internal entropy and increased internal organization. Energy degraded in the performance of work is exhausted as boundary outputs to the systems environment. This is reflected in decreased organization and increased entropy of the surroundings, the dissipative property (paper three). All properties rest on the conservation principle (paper two). Growth is movement away from equilibrium, which occurs in three forms: (I) when there is a simple positive balance of boundary inputs over outputs, which increments storage; (II) when, with boundary inputs fixed, the ratio of internal to boundary flows increases, which reflects increase in the sum of internal flows, which contribute to throughflow; and (III) when, somewhat coincident with but mostly following upon I and II, system internal organization, reflecting its energy-use machinery, evolves the utilization of information to increase the usefulness for work of the boundary energy supply. These three forms of growth are, respectively, growth-to-storage, growth-to-throughflow, and growth-to-organization. Forms I and II are quantitative and objective, concerned with brute energy and matter of different kinds. Form III has qualitative and subjective attributes inherent in information-based mechanisms that increase the exergy/energy ratio in available energy supplies. The open question of this paper is, which of many possible pathways will an ecosystem take in realizing its three forms of growth? The answer given is that an ecosystem will change in directions that most consistently create additional capacity and opportunity to utilize and dissipate available energy and so achieve increasing deviation from thermodynamic ground. The machinery for this synthesized from the three identified growth processes is reflected in a single measure, exergy storage. Abundant and diverse living biomass represents abundant and diverse departure from thermodynamic equilibrium, and both are captured in this parameter. It is the working hypothesis of this paper that ecosystems continually maximize their storage of free energy at all stages in their integrated existence. If multiple growth pathways are offered from a given starting state, those producing greatest exergy storage will tend to be selected, for these in turn require greatest energy dissipation to establish and maintain, consistent with the second law. Energy storage by itself is not sufficient, but it is the increase in specific exergy, that is, of exergy/energy ratios, that reflects improved usability, and this represents the increasing capacity to do the work required for living systems to continuously evolve new adaptive ‘technologies’ to meet their changing environments. Exergy cannot be found for entire ecosystems as these are too complex to yield knowledge of all contributing elements. But it is possible to compute an exergy index for models of ecosystems that can serve as relative indicators. How to compute this index is shown, together with its use in developing models with time-varying parameters. It is also shown how maximization of exergy storage distinguishes between local and global optimization criteria. In ecological succession, energy storage in early stages is dominated by Form I growth which builds structure; the dominant mechanisms are increasing energy capture (boundary inputs) and low entropy production (dissipative boundary outputs). In middle stages, growing interconnection of proliferating storage units (organisms) increases energy throughflow (Form II growth). This increases endogenous inputs and outputs and, in consequence, throughflow/boundary flow ratios, entropy production, and on balance, biomass. In mature phases, cycling becomes a dominant feature of the internal network, increasing storage and throughflow both. Biomass and entropy production are maximal, but specific dissipation (as dissipation/storage ratio) decreases, reflecting advanced organization (Form III growth) typified by cycling. Specific exergy (exergy/energy ratio) increases throughout succession to maturity, in early stages mainly due to mass accrual, and in the later stages to gains in information and organization. During senescence, storage, entropy production, specific dissipation, and specific exergy all decrease, reflecting a declining ecosystem returning toward equilibrium.

Impact of eutrophication and river management within a framework of ecosystem theories

Eutrophication became a dominant process in the Mondego estuarine system in the 1980s, presumably as a result of excessive nutrient release into coastal waters. The main symptoms were the occurrence of seasonal blooms of Enteromorpha spp., green macroalgae, and a drastic reduction of the Zostera noltii meadows. Previous results suggest that this process will determine changes in species composition at other trophic levels. This paper aims at integrating the available information to provide a theoretical interpretation of the recent physicochemical and biological changes in the Mondego estuarine ecosystem, which will be further used as basic framework for the development of a structurally dynamic model. Exergy-based indices, the Exergy Index and Specific Exergy, were applied as ecological indicators (orientors) to describe the state of the ecosystem, taking into account different scenarios along a spatial gradient of eutrophication symptoms. This allowed elucidating the present conditions along the spatial gradient as representing various stages in the temporal evolution of the system, within the framework of bifurcation, Chaos, and Catastrophe theories. Eutrophication appeared as the major driving force behind the gradual shift in primary producers from a community dominated by rooted macrophytes (Z. noltii) to a community dominated by green macroalgae. Through time, concomitant changes at other trophic levels will most probably give origin to a new trophic structure. Moreover, river management emerged as a key question in establishing scenarios in order to determine secondary effects in eutrophied systems. Results suggest that a more conservative river management may be used as a powerful tool to remedy affected areas, including the implementation of ecological engineering principles in different possible management practices. The recent biological changes in the Mondego estuarine ecosystem were found to comply with the framework of the theories considered, while both Exergy-based indices were able to capture the state of the system and distinguish between different scenarios.

A holistic approach to ecological modelling

Models of different complexity were used to examine how the ecological buffer capacity, β (defined as the change in loading relative to the change in a considered state variable) varies when the loading, e.g. the input of phosphorus, is changed. It was found that while β = ΔP(total)/ΔP(soluble) increases with increasing complexity of the model at low P-loading, the β-value will — at medium P-loadings — have a maximum value at a certain degree of complexity, and will be a decreasing function of complexity at high phosphorus loadings. This might explain why very eutrophic lakes, rivers polluted with organic matter or other stressed ecosystems are stable although their complexity is low. The more complex ecosystems seem best able to cope with increasing variations in climatic factors. In the models considered the thermodynamic function exergy correlates well with the sum of relevant buffer capacities. High exergy levels mean that the structure is more able to meet changes in external factors.

Analysis of the properties of exergy and biodiversity along an estuarine gradient of eutrophication

Benthic eutrophication often gives origin to qualitative changes in marine and estuarine ecosystems, for example the shift in primary producers, often followed by changes in species composition and trophic structure at other levels. Through time such modifications may determine a selected new trophic structure. The development of structural dynamic models will allow to simulate such changes, using goal functions to guide ecosystem behaviour and development. The selection of other species and other food web may then be accounted by a continuous optimisation of model parameters according to an ecological goal function. Exergy has been applied in structural dynamic models of shallow lakes, and appears to be one of the most promising approaches. Theoretically, exergy is assumed to become optimised during ecosystems development, and ecosystems are supposed to self organise towards a state of an optimal configuration of this property. Exergy may then constitute not only a suitable system-oriented characteristic to express natural tendencies of ecosystems evolution, but also a good ecological indicator of ecosystems health. Biodiversity is also an important characteristic of ecosystems structure, constituting a powerful and traditional concept, which was found to be suitable to test the intrinsic ecological significance of exergy. We examined the properties of exergy (exergy and specific exergy) and biodiversity (species richness and heterogeneity) along an estuarine gradient of eutrophication, testing the hypothesis that they would follow the same trends in space and time. This hypothesis was validated in a certain extent, with exergy, specific exergy and species richness decreasing as a function of increasing eutrophication, but heterogeneity responding differently. Biodiversity measurements and their interpretation appeared subjective. Exergy and specific exergy may be a suitable alternative, that could be used as goal functions in ecological models and as holistic ecological indicators of ecosystems integrity. Nevertheless, since exergy and specific exergy showed to respond differently to ecosystems seasonal dynamics, it is advisable to use both complementary. The method proposed by Jorgensen et al. (1995) to estimate exergy, which takes into account the biomass of organisms and the thermodynamic information due to genes, appeared to be operational. There is nevertheless an obvious need for the determination of more accurate (discrete) weighing factors to estimate exergy from organisms biomass. We propose to explore the assumption that the dimension of active genomes, which are primarily a function of the required genetic information to build up an organism, are proportional to the relative contents of DNA in different organisms.

Ecological buffer capacity

A new concept — the ecological buffer capacity — has been introduced to express the response of an ecosystem to changes in the loading. Either the relative or absolute stability gives this sort of information. By means of this concept, it has been attempted to show how complicated a model must be to give an acceptable description of the response to changes in the phosphorus loadings. It was found that the ecological buffer capacity increases with increasing model diversity, either expressed by means of the Shannon index or the number of state variables, but since it is of importance to include the most essential mass flows, the exergy is more suitably related to the buffer capacity than the diversity. Consequently, the exergy can be used as an expression for the buffer capacity, that is, as an expression for the response of an ecosystem to changes in the driving functions. Both the buffer capacity and the exergy can be used to select the required state variables for a model. Interchanging Pjeq (= phosphorus concentration in box j at thermodynamic equilibrium) with Pj0 (= phosphorus concentration in box j at steady state) in the exergy expression, seems to give a useful Liapunov function for the considered set of models.

Development of models able to account for changes in species composition

Abstract Our present modelling approach uses constant parameters and therefore does not account for changes in properties within the same species or even for shifts to other species with significantly different properties. A modelling approach using currently changing parameters in accordance with a goal function is introduced in this paper. As goal function ‘energy = biogeochemical energy of the system’ is used. It can be considered as a translation of Darwins theory (‘survival of the fittest’) to thermodynamics. The proposed approach has now been used successfully on four case studies. One was published (Jorgensen, 1986) and three other cases are presented in this paper.

Structural dynamic model

Abstract The need for structural dynamic models is discussed and demonstrated. It is suggested to build this type of model by use of simple models, where the parameters are currently changed by a control function. The thermodynamic function energy is introduced as a possible and ecologically sound control function. Results by the use of energy as a control function demonstrate that it gives expected results. Significant improvement of a prognosis based upon a eutrophication model was obtained in a case where a shift in phytoplankton species composition was observed.