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

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6 Reynolds/ Aquatic Ecosystem Health and Management 5 (2002) 3–17 collecting dilute calanoid zooplankton are evident among their (typically) clupeoid representatives (shads, smelts, coregonids, and salmonids), fish biomass and growth are often demonstrably unsustainable on the basis of production in the zooplankton. Elsewhere, littoral and benthic foraging is required to sustain the resource requirements of more intensive and more diverse production of adult fish. The underpinning primary products may emanate from sedimenting phytoplankton or be augmented, substantially in the case of smaller water bodies, from aquatic macrophytes and/or inwashed organic matter. Among these small lakes, feeding activities of fish populations, including recruiting juveniles, “cascade” (Carpenter et al., 1985) through the substantial cropping of zooplankton to mitigate the impact of grazing on the phytoplankton (Carpenter and Kitchell, 1993). There now seems little doubt that the complexity of interactions arising through resource exploitation and cropping contributes to the richness of fish species that may co-exist in a lake (Hairston et al., 1960; Vander Zanden et al., 1999). This present appreciation of the structure of the carbon pathways in freshwaters recognizes the enduring contribution of autotrophs (aquatic or otherwise), a series of phagotrophs and, indeed, of heterotrophic microorganisms. There remains a need to investigate the provenance of the particulate organic carbon fluxes in selected lakes, and to determine how much is actually autochthonous. Jónasson’s (1996) comparisons of the sedimentary fluxes in various lake types covered a range between 90 and >300 g C m –2 y –1 . On the other hand, it is difficult to argue for a supporting flux of atmospheric carbon dioxide, entering exclusively across the air-water interface of much more than 50 to 70 g C m –2 y –1 (Reynolds, 1996, 1999). The shortfall may be met by dissolved carbon dioxide supplied in inflow streams (Maberly, 1996), but its photosynthetic fixation would be aquatic. On the other hand, inflows to particular lakes have been shown to bring in a substantial load of particulate organic carbon that is either sedimented or consumed by the lake’s heterotrophs. Organic loads are not necessarily diagnostic of pollution but may contribute to the normal carbon dynamics of a lake. The direct consumption by zooplankton of catchment-derived organic debris in Loch Ness (Jones, 1992) may not be at all unusual. The building of aquatic ecosystems For the present, the concern is not the precision of the structure of the trophic network described, nor even whether the fund of organic carbon is generated in the water body itself or on the land. The preceding section identifies the central flow of organic carbon, from its synthesis in primary producers, through the food web to its final dissipation by the heterotrophs. The present section seeks a comparably reductionist view of how such organization comes about. In so doing, we should keep in mind a general picture of the above structure but we must not simply try to explain the assemblages we observe. Even the issue of where the essential control resides—at the bottom, among the producers, or at the top, among the consumers, or on the way down again, among the decomposers— is avoided. What is required is an understanding of the powering mechanisms and processing constraints and the nature of the outcomes. The strength of the ecosystem lies in its power. Thus, the capture and chemical fixation of energy in photosynthesis is the foundation of the building ecosystem. In order to develop the gathering potential, it is necessary to be able to deploy photosynthate into assembling further structures for photointerception and photoconversion. Growth and replication provide the means of harnessing more of the solar power available and siphoning its energy into the biological components. These include the phagotrophs and the decomposers that exploit the energy store into building their own biomass, once they have covered the costs of gathering it. Common to each of these component steps is the ability for growth and replication to occur, provided the energy and resources are available, and that it can be realized provided that the energetic costs of their accumulation and the losses to other levels are exceeded or, at least, balanced by the energetic income. This makes it sound like a simple profit and loss account, and that is just what it is. Indeed, it is this logic which underpins harvest theory for forestry and fishery management. The growth-reproduction curves developed by Ricker (1954) and the stock-recruitment models considered by Gulland (1983) extrapolate the potential biomass losses and fishery exploitation against the capacity of the population to recruit subsequent generations and to increase the standing
Reynolds/Aquatic Ecosystem Health and Management 5 (2002) 3–17 7 stock. A positive balance is essential to population growth and a balance may represent some kind of ecological stability but a negative balance represents a population in decline and in danger of extinction through over-exploitation. One of the interesting features of these models is that no constancy in the rates of growth is assumed: they are sensitive to the effects of stochastic food shortages (resource depletion) or inhospitable conditions of cold or warmth (processing constraints) and the manager is required to judge the impacts on subsequent recruitment rates and the tolerable limits of exploitation. If the recruitment is too poor or the exploitation too heavy, he will judge correctly that the stock will shrink. He must also attempt to judge whether the population is likely to recover in the future or whether it is permanently impaired to a level from which recovery is impossible or protracted. Such activities amount to assessments of the resilience of the population to variable rates of survivorship and recruitment success in the face of stochastic environmental stresses. Fluctuations evoke damped responses if the relevant excess capacity at the lower scale does not fall below the minimum required at the higher scale. Thus, the heavily fished population can maintain its power if a larger number of juveniles makes it to maturity. The algal population continues to self-replicate in reduced light so long as the biomass-specific rate of photosynthesis continues to supply sufficient fixed carbon to supply the fastest attainable growth rate. In this way, the comparison with a balance sheet provides a realistic analogue of how individuals, populations and interactive systems build biomass and acquire resilience. When the total income of organic carbon exceeds the total running expenditure (respiration, repair, harvesting effort), there is a profit available to reinvest in growth. If the total income fails to meet the running costs, then the structure is unsustainable and some regression is inevitable (individuals lose weight, populations experience loss of individuals, systems become stressed and lose structure). Fluctuations in income that nevertheless maintain a variable, positive balance may support erratic performance but a foundation for recovery remains intact—the structure is resilient to environmental variation! We may go a step further in the graphical representation of the resilience of community and ecosystem structure by expressing large-scale balances in terms of thermodynamic exchanges. Here, the energetic costs of maintaining the assembled biomass may be compared directly with its energy-harvesting potential. Again, the system that captures more shortwave energy than it dissipates as heat is able to build more capacity and so move the structure further from energetic equilibrium. This positive counter-current to the entropic breakdown of structure has been called negentropy or exergy (Mejer and Jørgensen, 1979; Jørgensen, 1982). System exergy is a convenient aid to interpreting biological dynamics. It represents the current trading balance of the system in question, some of which may be reinvested in increasing trade. Moreover, so long as it is positive, there is a slack, a sort of buffer (Nielsen, 1992) or cushion, against income fluctuations and small losses. Nielsen’s (1992) diagrammatic representation of the exergy buffer provided the original inspiration for the drawing employed here (as Figure 1), which is simplified from an earlier attempt to quantify the exergy of an aquatic system and to determine its liability to be exceeded (Reynolds, 1997). It must be first emphasized that the system represented was itself reduced to absolute simplicity, initially comprising a population of a single photoautotrophic species (having the properties of a laboratory strain of the green alga, Chlorella, operating in an environment where the only variable is the energy income. Temperature is even at 20º C and there is no nutrient limitation imposed on growth or achievable biomass. Thus the representation is of maximal energy harvesting as a function of harvester biomass. The vertical axis stretches from zero (no income or no biomass) to the maximum harvestable income of solar energy, scaled in MJ m –2 d –1 . The nominated maximum, corresponding to daily flux of photosynthetically-available solar radiation penetrating the atmosphere to reach the earth’s surface is set at 12.6 MJ m –2 (which is about 47% of the total reaching the earth’s surface), and representing a mean photon flux density of ~ 8 × 10 20 m –2 s –1 or ~ 1.33 mmol photon m –2 s –1 . Into this light field, we start to place healthy, grown, quasispherical cells of Chlorella (diameter of 4 mm, or 4 × 10 –6 m), projecting an area of 12.6 × 10 –12 m –2 and containing about 7 pg (~ 0.6 × 10 –12 mol) of structural carbon and about 0.14 pg chlorophyll a pigment. Then, supposing that each light harvesting centre (LHC) comprises some 200 to 300 molecules of chlorophyll, each having a molecular
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