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FIGURE 3. The hypothesized relationship between the orga- nization necessary to maximize empower in a network and the spectrum of possible emergy signatures. The support emergy, Em, is calculated without double counting any source. (a) The relationship between system organization in a network and the empower generated (after Odum 1996). (b) The relationship between the number of units organized (# species) and the emergy available to support and organize units (area). (after Odum 1983). (c) The hypothesized trajec- tory for maximum empower production given a series of sys- tem networks (A-E) organized by signatures of increasing emergy.

Figure 3 The hypothesized relationship between the orga- nization necessary to maximize empower in a network and the spectrum of possible emergy signatures. The support emergy, Em, is calculated without double counting any source. (a) The relationship between system organization in a network and the empower generated (after Odum 1996). (b) The relationship between the number of units organized (# species) and the emergy available to support and organize units (area). (after Odum 1983). (c) The hypothesized trajec- tory for maximum empower production given a series of sys- tem networks (A-E) organized by signatures of increasing emergy.

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OPERATING PRINCIPLES: THE MAXIMUM EMPOWER PRINCIPLE AND SELF-ORGANIZATION
OPERATING PRINCIPLES: THE MAXIMUM EMPOWER PRINCIPLE AND SELF-ORGANIZATION
* By convention transformities lower than 1.0E5 are reported to the nearest whole integer.
* By convention transformities lower than 1.0E5 are reported to the nearest whole integer.
should correspond to at least a local maximum in empower production. Once a system is on a ther- modynamic branch, a general course of develop- ment is set, assuming that external conditions re- main within a given range. However, the details of development are not fixed, because of the redun-
should correspond to at least a local maximum in empower production. Once a system is on a ther- modynamic branch, a general course of develop- ment is set, assuming that external conditions re- main within a given range. However, the details of development are not fixed, because of the redun-
new dynamic equilibrium or to recover an old one after a permanent or temporary change in the em- ergy signature (Figure 4). Over time ecosystems follow an expected strategy of development (suc- cession) and if the maximum empower principle guides their development, they will self-organize into patterns that are increasingly more effective at utilizing the new mix of available energy. One
new dynamic equilibrium or to recover an old one after a permanent or temporary change in the em- ergy signature (Figure 4). Over time ecosystems follow an expected strategy of development (suc- cession) and if the maximum empower principle guides their development, they will self-organize into patterns that are increasingly more effective at utilizing the new mix of available energy. One
FIGURE 5. The hierarchical organization of systems represented as three levels of pulsing accumulator-frenzor pairs (Odum 1999). The magnitude of the emergy source is increasing as one moves toward higher levels. The relationship be- tween energy (in italics), emergy (plain text), and transformity (plain text/italics) is given for each level in the hierarchy. The letters on the level 3 plot refer to the stages in the cycle of change for the accumulator and the frenzor.
FIGURE 5. The hierarchical organization of systems represented as three levels of pulsing accumulator-frenzor pairs (Odum 1999). The magnitude of the emergy source is increasing as one moves toward higher levels. The relationship be- tween energy (in italics), emergy (plain text), and transformity (plain text/italics) is given for each level in the hierarchy. The letters on the level 3 plot refer to the stages in the cycle of change for the accumulator and the frenzor.
FIGURE 6. A generic ecosystem network used in defining ecological integrity and ecosystem health. This network includes 3 energy sources and 7 energy storages interacting through 13 processes to produce 37 energy flows. If we could specify all the important compo- nents and processes of an ecosystem and know their connections and arrangement, we would be able to completely define the network upon which the ecological integrity and the health of that eco- system depends. For a moderately complex ecosys- tem of 7 components receiving energy from 3 ex- ternal sources (Figure 6) there are (27-1) times 3 or 381 possible ways to connect the 3 energy sources to the seven system components (2°-1) times 7 or 441 possible ways to connect the seven system components, and 381 times 441 or 168,021 possible ways to combine the 3 energy sources with the seven components. Analysis of this amount of complexity would be a difficult task. Thus, we use models to simplify real systems so that we can study them and attain an understanding of their expected states of structure and function. Fortunately, many possible aggregations and ar- rangements of storages and forcing functions are not physically or biologically possible and others, Ecological integrity can be defined on the basis of an ecosystem network where it may be specified as a function of the system components, the fluxes of material, information and energy linking these components, and the processes that govern their interactions with the external forcing functions and with each other (Figure 6). Ecosystems that operate at maximum power have distinct structural and functional characteristics (Odum 1971b, 1975) and the concept of integrity may also be applied to both of these aspects of the ecosystem (Cairns 1977). The functional integrity, or health of an ecosystem (Leopold 1949), is a function of the flows of energy, material, and information in the system. The struc- tural integrity or completeness of the system can be defined by the storages of material, information,
FIGURE 6. A generic ecosystem network used in defining ecological integrity and ecosystem health. This network includes 3 energy sources and 7 energy storages interacting through 13 processes to produce 37 energy flows. If we could specify all the important compo- nents and processes of an ecosystem and know their connections and arrangement, we would be able to completely define the network upon which the ecological integrity and the health of that eco- system depends. For a moderately complex ecosys- tem of 7 components receiving energy from 3 ex- ternal sources (Figure 6) there are (27-1) times 3 or 381 possible ways to connect the 3 energy sources to the seven system components (2°-1) times 7 or 441 possible ways to connect the seven system components, and 381 times 441 or 168,021 possible ways to combine the 3 energy sources with the seven components. Analysis of this amount of complexity would be a difficult task. Thus, we use models to simplify real systems so that we can study them and attain an understanding of their expected states of structure and function. Fortunately, many possible aggregations and ar- rangements of storages and forcing functions are not physically or biologically possible and others, Ecological integrity can be defined on the basis of an ecosystem network where it may be specified as a function of the system components, the fluxes of material, information and energy linking these components, and the processes that govern their interactions with the external forcing functions and with each other (Figure 6). Ecosystems that operate at maximum power have distinct structural and functional characteristics (Odum 1971b, 1975) and the concept of integrity may also be applied to both of these aspects of the ecosystem (Cairns 1977). The functional integrity, or health of an ecosystem (Leopold 1949), is a function of the flows of energy, material, and information in the system. The struc- tural integrity or completeness of the system can be defined by the storages of material, information,
trol bays by 12%, whereas, the transformity of sys- tem respiration in the thermal bays exceeded the transformity of respiration in the control bays by 32%. (3) The ratio of the emergy produced to the emergy consumed in an ecosystem is the emergy P/R ratio which may have characteristic values for systems with different emergy signatures. For ex- ample, the P/R ratio for the thermally impacted inner bay at Crystal River Florida was consistently higher than the P/R ratio for its control bay (Fig- ure 7b). These three emergy indices need to be further evaluated and tested to determine if they are viable indicators of the integrity and health of ecosystems.
trol bays by 12%, whereas, the transformity of sys- tem respiration in the thermal bays exceeded the transformity of respiration in the control bays by 32%. (3) The ratio of the emergy produced to the emergy consumed in an ecosystem is the emergy P/R ratio which may have characteristic values for systems with different emergy signatures. For ex- ample, the P/R ratio for the thermally impacted inner bay at Crystal River Florida was consistently higher than the P/R ratio for its control bay (Fig- ure 7b). These three emergy indices need to be further evaluated and tested to determine if they are viable indicators of the integrity and health of ecosystems.
FIGURE 8. An evaluated energy systems diagram of an ecosystem represented as a P-R loop. Flows of matter are separated and shown as a dashed line. The model equations and a table of energy, emergy, and transfor- mity for the matter and energy flows are also shown.
FIGURE 8. An evaluated energy systems diagram of an ecosystem represented as a P-R loop. Flows of matter are separated and shown as a dashed line. The model equations and a table of energy, emergy, and transfor- mity for the matter and energy flows are also shown.
FIGURE 9. The results from simulating the P-R model (Figure 8) showing how to measure ecological integrity using empower production in the network. (a) the time history for the state variables in the model. (b) the time history of the emergy stored in Q. (c) comparison of the emergy stored in Q to the cumulative empower gener- ated by the system when a disordering pulse is imposed on the system. (d) The change in system transformity as the emergy storage develops. (e) change in the emergy P/R ratio as the emergy storage develops.
FIGURE 9. The results from simulating the P-R model (Figure 8) showing how to measure ecological integrity using empower production in the network. (a) the time history for the state variables in the model. (b) the time history of the emergy stored in Q. (c) comparison of the emergy stored in Q to the cumulative empower gener- ated by the system when a disordering pulse is imposed on the system. (d) The change in system transformity as the emergy storage develops. (e) change in the emergy P/R ratio as the emergy storage develops.
fied from any coherent class of ecosystems (e.g. streams receiving municipal wastes). In this case we would determine how a stream receiving sew- age compared to other streams with similar em- ergy signatures, thus this approach could be ap- plied to different classes of waters with different designated uses. In a test ecosystem of unknown condition, a substantial departure of the measured values for ecological indicators from their refer- ence values leads the investigator to suspect that there has been a quantitative or qualitative change in the emergy signature of the test ecosystem.
fied from any coherent class of ecosystems (e.g. streams receiving municipal wastes). In this case we would determine how a stream receiving sew- age compared to other streams with similar em- ergy signatures, thus this approach could be ap- plied to different classes of waters with different designated uses. In a test ecosystem of unknown condition, a substantial departure of the measured values for ecological indicators from their refer- ence values leads the investigator to suspect that there has been a quantitative or qualitative change in the emergy signature of the test ecosystem.
Related topics:
Computer ScienceEcologyEcosystem healthSystems EcologyEnvironmental Resource ManagementEcological IntegrityPublic health systems and services researchVeterinary SciencesEnergy Systems Theory
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