Resilience in aquatic ecosystems - hysteresis, homeostasis, and ...

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8 Reynolds/ Aquatic Ecosystem Health and Management 5 (2002) 3–17 Figure 1. Comparison of the potential energy harvest of a primary-producing biomass with the fixed, biomass-dependent maintenance requirement. The excess of energy income over maintenance expenditure is the energy flux of the system and which, while positive, provides a margin of structural resilience to external variability. Modified from Reynolds (1997). weight of 894 Da, an approximation that 1 g chlorophyll a is organized into about 3 × 10 18 LHC receptors, each Chlorella cell is able to present ~ 0.4 × 10 6 receptors in the path of the unmodified photon flux, with a spatial density of 32 × 10 12 m –2 . Cells may harvest only light falling on the cell. At low cell concentrations, most of the light is unused; the amount of energy that is intercepted is, theoretically, in direct proportion to the intercepting biomass. As the number of cells is increased, there is an increasing probability that the projection areas of the cells interact (they “self-shade”) and the flux intercepted per unit biomass ceases to be linear. With uniform distribution of cells, the threshold of non-linearity occurs at a population of 1/(12.6 × 10 –12 ) cells m –2 , or ~ 0.048 mol cell C m –2 . Thereafter, further gain in harvesting capacity as a function of producer biomass is sublinear and asymptotic towards a point where the entire photon flux is harvested. The minimum concentration of LHCs to do this is determined by the reaction rate, for the energy of the intercepted photon is not captured if the LHC is effectively closed in the action of processing the previous photon intercepted (Kolber and Falkowski, 1993). At 20º C, the LHC saturates at about 250 reactions s –1 . Thus, the density of LHCs required to harvest the full photon flux of 8 × 10 20 m –2 s –1 is not less than 32 × 10 17 m –2 , requiring the activity of not fewer than 80 × 10 11 cells m –2 , containing 4.8 mol cell carbon m –2 . There is no reason why a greater but less intensively active photosynthetic biomass should not be supported to do the same work, though only to the limit of its maintenance costs. Taking the basal respiration of Chlorella to be 1.1 × 10 –6 mol C (mol cell C) –1 s –1 (Reynolds 1990), the daily energetic cost of replacing 0.095 mol C (mol cell C) –1 was calculated to be about 1.2 MJ (mol cell C) –1 , meaning that
Reynolds/Aquatic Ecosystem Health and Management 5 (2002) 3–17 9 the maximum sustainable biomass is about 10.4 mol (125 g) carbon m –2 . Some of the assumptions in that calculation may now be viewed as inappropriate and employing more realistic assembly costs of ~ 470 kJ per mol organic carbon, a supportable maximum biomass of about 25 mol carbon (300 g) m –2 may be proposed. Both figures accommodate comfortably reported natural maximal densities of phytoplankton (~ 50 g C m –2 ) and the active parts of terrestrial plant biomass (~ 75 g C m –2 : see Margalef, 1997). It is a good deal less than the 20 to 30 kg C m –2 standing crops of tropical forest stands, though this is, of course, dominated by the accumulated necromass that is wood. The numbers used to construct Figure 1 are less important to the present argument than the shape that they generate. In systems supporting low biomass and incurring low maintenance costs, there is a large buffer of spare harvesting capacity which is available to fund the provision of new harvesting biomass. It will also provide a cushion against exploitation by the consumer organisms of the phagotroph tier, without loss of standing crop or growth potential, though it is sustained at the cost of reduced investment. It is also a cushion against submaximal solar energy income, which, at this scale, is consequential upon variable cloud cover, day length and declination. Wind mixing and plankton entrainment to depth in lakes and seas also exacts a heavy toll in light absorption which can be quantified and set to subtract from the potential energy income in Figure 1. However, so long as the energy harvesting can satisfy the maintenance cost, the existing structure can endure and recover quickly from the setbacks of environmental variability. The model can be adapted to represent the balance between almost any set of anabolic assembly and catabolic destruction, so long as they are amenable to rendering in energy fluxes in comparable units. At the scale of the individual cell, it summarizes the ability to increase mass and divide; at the level of the population, it represents the potential to increase the crop. It does not yet explain the interactions of different populations with each other, but the supposition is advanced that the individuals and the species that are able to invest most in new or additional structure are those most likely to contribute to the assembly at the next level (strongest-growing individuals contribute most to the populations; strongest-growing populations are, at least starting from equal abundance, most likely to dominate communities). In other words, rapid structural anabolism also demands high exergy margins. This is a decisive mechanism about how the dynamics of individuals— the only organizational level under direct genetic control—eventually feed upwards to determine the development of communities. The emergent behavior, expressed in the assembly of functional ecosystems, relates to the exergy arising from the activities of the most efficient individuals. This, in turn, establishes the pattern of development in the building ecosystem. The apparent ability of communities to organize themselves (autopoesis) around the fluxes of usable energy has, for long, promoted speculation and debate about its mechanisms and controls, and about what Straškraba (1980) called “the goal-seeking behavior” of systems. The principle of maximum exergy permitting maximal structural dynamism (Jørgensen, 1982) is but one of several thermodynamic explanations for the high-order patterns of ecosystem. That of Odum (1982) argued for the selection of organisms and structures that make the best use of the available power, while Ulanowicz (1986) regarded system growth and development as the simultaneous increase in system throughput, using increasingly complex structural networks accumulating more information. These theories are not mutually exclusive (Salomonsen, 1992), indeed, they are mutually supportive. Their merits and demerits are not the concern here, save that it is important to emphasize that each relates the strong and consistent patterns of community organization to the sum of the behaviors of individual organisms. Analogizing them to the flow of energy and to the rate of its biological dissipation that their activities represent, however, recognizes openly the finite capacity to buffer contingent variability in the energy sources. Some preliminary estimates of their probable ranges are noted in Table 1. The effect of external forcing on community assembly It is rather obvious that few planetary ecosystems carry either the biomass or the structural complexity for which the foregoing passages argue, or achieve the ultimate autopoetic goal of stability. The override of resource scarcity as a causal impediment is generally recognized and the systemic reaction to eutrophication and its reversal make it an issue for consideration here. The override caused by frequent exceedence of buffer capacity is also well accepted but the relationship between external forcing and internal exergy needs to be clarified first. We have already shown that the assembly of an energy-harvesting network provides a capacity for
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