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Control of Phytoplankton Growth in Nutrient Recycling Ecosystems

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Control of Phytoplankton Growth in Nutrient Recycling Ecosystems MARINE ECOLOGY PROGRESS SERIES Published May 29 Mar. Ecol. Prog. Ser. Control of phytoplankton growth in nutrient recycling ecosystems. Theory and terminology T. Frede ~hingstadl,Egil sakshaug2 ' Department of Microbiology and Plant Physiology, University of Bergen, Jahnebk. 5,N-5007 Bergen, Norway Trondhjem Biological Station, The Museum. University of Trondheim, Bynesvn. 46, N-7018 Trondheim, Norway ABSTRACT: Some of the principles governing phytoplankton growth, biomass, and species composi- tion in 2-layered pelagic ecosystems are explored using an idealized, steady-state, mathematical model, based on simple extensions of Lotka-Volterra type equations. In particular, the properties of a food web based on 'small' and 'large' phytoplankton are investigated. Features of the phytoplankton community that may be derived from this conceptually simple model include CO-existenceof more than one species on one limiting nutrient, a rapid growth rate for a large fraction of the phytoplankton community in oligotrophic waters, a long food chain starting from a population of small phytoplankton in waters with moderate mixing over the nutricline, and a transition to dominance of a food chain based on large phytoplankton when mixing is increased. As pointed out by other authors, careless use of the concept of one limiting factor may be potentially confusing in such systems. To avoid this, a distinction in terminology between 'controlling' and 'limiting' factors is suggested. INTRODUCTION dominance of short food chains in upwelling areas (Ryther 1969). Various aspects of nutrient cycling in pelagic ecosys- Many authors have addressed various aspects of the tems are of prime importance to our understanding of planktonic ecosystem using mathematical models how productivity of the oceans is controlled, and to our which are idealized and conceptual. Many of these ability to analyze present and future impacts of man's have been based on the steady-state solutions to exten- activity on oceanic, coastal, and freshwater ecosystems. sions of classical Lotka-Volterra equations of predator- The coupling of primary production to mineral nu- prey relationships. Riley (1963) analyzed general food- trient cycling is probably strict and important in the chain relationships in planktonic systems, and Smith euphotic zone of waters subject to prolonged periods of (1969) addressed the question of effects of nutrient stratification. In such environments, a large fraction of enrichment on food webs, pointing out the important primary production may depend upon regeneration of differences between food chains with even and odd nutrients originally sequestered in biomass during numbers of trophic steps. Using network analysis, Lane primary production, regeneration thus constituting & Levins (1977) reached many of the same conclusions. feed-back loops in the system. The behavior of systems Concepts of this kind have inspired a large body of with loops is not always easy to understand without investigations in limnology, mainly aimed at minimiz- some kind of support from mathematical analysis, and ing the profuse growth of phytoplankton in eutrophied the mechanisms underlying many apparently general lakes by manipulation of the number of predator levels aspects of phytoplankton communities are not intui- in the food chain (e.g. Carpenter et al. 1985 and tlvely obvious. Examples of this would be the co-exist- references therein). ence of many species in an apparently homogenous The concept of 'new' versus 'old' production (Dug- environment, i.e. Hutchinson's paradox (Hutchinson dale & Goering 1967, Eppley & Peterson 1979) is essen- 1961); the apparently rapid phytoplankton growth tial to the understanding of how the closed loops of the rates at undetectable nutrient concentrations in oligo- recycling part of these systems interact with the trophic environments (Goldman et al. 1979, Goldman imports and exports of mineral nutrients. A mathemati- 1986, Laws et al. 1984, Sakshaug et al. 1983); and the cal description demonstrating the importance of algal O Inter-Research/Printed in F. R. Germany 262 Mar. Ecol. Prog. Ser 63: 261-272, 1990 loss rates to the behavior of such systems was given by tem. Through processes such as uptake, predation and Dugdale (1967).Simple conceptual food web models in regeneration, No is shared among the free mineral laboratory chemostat systems based on microorgan- nutrient N and the biological populations. In a closed isms have been analyzed by several authors (e.g. Jost system, No is a constant; in an open system, mineral et al. 1973b, Thingstad & Pengerud 1985). Laws (1975) nutrients may be imported or exported by processes developed a model that allowed an analysis of how the such as sedimentation or hydrodynamic transport cellular properties of phytoplankton species and the through the nutricline. As a consequence, the degree of hydrographic properties of the water column could nutrient enrichment No becomes a dynamic variable influence size distribution in the phytoplankton com- with a steady state value N:. In reading the subsequent munity. The effect of predation on phytoplankton size text, it is essential to keep in mind the difference distribution has been modelled by Carpenter & Kitchell between free mineral nutrient N and nutrient enrich- (1984). ment No. The work presented here attempts to explore the The discussion is based on an analysis of the steady combined effects of recycling and sedimentation on states of Lotka-Volterra type equations with population steady-state properties of the phytoplankton commun- growth rates assumed either to be proportional to sub- ity. Non-steady states are of obvious importance to the strate (prey) concentrations, or, at high substrate (prey) understanding of many aspects of planktonic ecosys- levels, to be constant (= pm). In a linear food chain tems (see e.g. Harris 1983). The range of features that (Frame l),the steady state conditions lead to a recur- may be derived from extremely simple steady-state sive formula (Frame 2. Eq. 2.1) for the steady state models such as those examined in this paper are, how- values of the populations. For the simple food web with ever, astonishingly large. A diverse suite of aspects of 2 size classes of phytoplankton shown in Fig. 2, the phytoplankton ecology proposed by many authors may analytical equilibrium solutions for the closed system be described within such a simple formalized are shown in Frame 3. Using a standard microcomputer framework. spreadsheet, Eq. 2.1 and Eqs. 3.1 to 3.6 have been Limitation of phytoplankton growth rate is usually solved numerically to give the steady state distribution assumed to play an extremely important part in the of mineral nutrient between the biomass of the popula- control of the phytoplankton community (e.g. Tilman et tion~,and the free mineral nutrient N. Values used for al. 1982 and references therein). Yet, as stressed by the parameters are given in Table 1. Lane & Levins (1977), there is an apparent contradic- tion between the 'everything depends on everything' philosophy that emerges from holistic analyses of Closed systems with linear food chains larger systems, and the concept of 'a single limiting factor'. Lane & Levins conclude their paper with the In an ecosystem with a linear food chain, the effect of statement: '. we urge a whole system approach and a change in nutrient enrichment on a population at one believe that the limiting factor concept is an ecological trophic level is dependent upon the number of trophic myth, despite its simultaneous existence as a phy- levels in the chain (e.g. Lane & Levins 1977). If there siological truth'. We will argue that the Limiting factor are n levels in the chain, the effect of an increased concept may still be vahd and fruitful, provided care is nutrient enrichment No will be a linear increase in taken to restrict its use to the factor(s) explicitly and biomass of populations at levels n, n-2, n-4 etc., while directly limiting the growth rate of a population, as populations at levels n-l, n-3, n-5 etc will remain distinguished from a broader concept of controlling constant (Eq. 2.1). A new population (X,,,) can estab- factors which may act indirectly through the links of the lish itself at level n+l of the linear chain once its food ecosystem. supply, i.e. the population X, at level n, becomes abun- dant enough for population n+ l to reach a growth rate that balances its loss rates. The population at level n MATHEMATICAL MODELS will no longer increase in biomass, but its growth rate will now increase with increasing nutrient enrichment. General description With the model described in Frame 1, the concentration of population or substrate X, that allows establishment The analysis is developed using a description based of population X,+ is given by the combined parameter on the mineral nutrient sequestered by each population bn+llfin+~an+l. in a food chain or food web. Mineral nutrient in the For some value of No, one of the populations at levels biomass of the populations, together with free mineral n-l, n-3, etc., will reach its maximum growth rate pm. nutrient in the water (N), sum up to the degree of In this case both biomass and growth rate at this trophic nutrient enrichment (eutrophication) (No)of the ecosys- level becomes constant, i.e. independent of any further Thingstad & Sakshaug Control of phytoplankton growth 263 Frame 1 Differential equations describing the transfer of mineral nutrient in a linear food chain with n trophic levels The properties of a population are characterized by 4 parameters: v, a, pm, and 6 (Table 1). Growth rate of a population is assumed to be proportional to nutrient uptake (proportionality constant = assimilation efficiency (3). The specific uptake rate of a population is assumed either to be proportional to substrate (prey) concentration (proportionality factor = affinity constant a), or, at saturating food levels, to be constant (= )I"'). Specific death rate b is assumed to be constant.
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