• Food webs;
  • growth rate;
  • herbivores;
  • life history evolution;
  • phosphorus;
  • rDNA;
  • RNA;
  • stoichiometry


  1. Top of page
  2. Abstract
  3. Introduction
  4. Biological stoichiometry – what is it and where did it come from?
  5. The association between C:N:P stoichiometry and growth
  6. The cell biology of organismal C:N:P-growth stoichiometry
  7. Ribosomal RNA genes: functional variability in copy number and in the intergenic spacer?
  8. The molecular genetics of food-web dynamics: a hypothesis
  10. Acknowledgements
  11. Bibliography

Ecological stoichiometry is the study of the balance of multiple chemical elements in ecological interactions. This paper reviews recent findings in this area and seeks to broaden the stoichiometric concept for use in evolutionary studies, in integrating ecological dynamics with cellular and genetic mechanisms, and in developing a unified means for studying diverse organisms in diverse habitats. This broader approach would then be considered “biological stoichiometry”. Evidence supporting a hypothesised connection between the C:N:P stoichiometry of an organism and its growth rate (the “growth rate hypothesis”) is reviewed. Various data indicate that rapidly growing organisms commonly have low biomass C:P and N:P ratios. Evidence is then discussed suggesting that low C:P and N:P ratios in rapidly growing organisms reflect increased allocation to P-rich ribosomal RNA (rRNA), as rapid protein synthesis by ribosomes is required to support fast growth. Indeed, diverse organisms (bacteria, copepods, fishes, others) exhibit increased RNA levels when growing actively. This implies that evolutionary processes that generate, directly or indirectly, variation in a major life history trait (specific growth rate) have consequences for ecological dynamics due to their effects on organismal elemental composition. Genetic mechanisms by which organisms generate high RNA, high growth rate phenotypes are discussed next, focusing on the structure and organisation of the ribosomal RNA genes (the “rDNA”). In particular, published studies of a variety of taxa suggest an association between growth rate and variation in the length and content of the intergenic spacer (IGS) region of the rDNA tandem repeat unit. In particular, under conditions favouring increased growth or yield, the number of repeat units (“enhancers”) increases (and the IGS increases in length), and transcription rates of rRNA increase. In addition, there is evidence in the literature that increased numbers of copies of rDNA genes are associated with increased growth and production. Thus, a combination of genetic mechanisms may be responsible for establishing the growth potential, and thus the RNA allocation and C:N:P composition, of an organism. Furthermore, various processes, during both sexual and asexual reproduction, can generate variation in the rDNA to provide the raw material for selection and to generate ecologically significant variation in C:N:P stoichiometry. This leads us to hypothesize that the continuous generation of such variation may also play a role in how species interactions develop in ecosystems under different conditions of energy input and nutrient supply.


  1. Top of page
  2. Abstract
  3. Introduction
  4. Biological stoichiometry – what is it and where did it come from?
  5. The association between C:N:P stoichiometry and growth
  6. The cell biology of organismal C:N:P-growth stoichiometry
  7. Ribosomal RNA genes: functional variability in copy number and in the intergenic spacer?
  8. The molecular genetics of food-web dynamics: a hypothesis
  10. Acknowledgements
  11. Bibliography

During this century, biology has become increasingly sophisticated and predictive. With increasing sophistication has come increasing specialisation (Maienschein 1991). Narrowing of research focus occurs not only at particular levels of organisation (e.g. ecosystem science, molecular genetics) but also within the confines of particular model organisms (e.g. Drosophila, Arabidopsis) or of particular habitats (e.g. lakes, temperate forests). As a result, knowledge is increasingly fragmented and it has become more difficult to connect disparate areas of inquiry in order to appreciate the full context of living things as functional wholes (Appel 1988; Allen & Hoekstra 1992; Pickett et al. 1994; Smocovitis 1996; Vogel 1998). Biologists now face the challenge of developing broadly generalisable approaches for the study of living systems that can re-connect our deepening understanding of individual levels of biological organisation and highlight the concurrence of phenomena across diverse biota and ecosystems.

Integrating our growing knowledge base across multiple levels of organisation, diverse types of organisms and contrasting habitats is a daunting challenge. Is it possible that coherent hypotheses can be posed to link the disparate levels of organisation under study by modern biology, from the molecular structure of genes to ecosystem dynamics? We believe that a rich suite of principles emerges when one couples the first law of thermodynamics, the principle of evolution by natural selection and the central dogma of molecular biology. We call this approach “biological stoichiometry”. In this paper we describe recent developments in this area and suggest how biological stoichiometry may someday be able to successfully integrate from genes to ecosystems, from microbes to metazoans and from oceans to deserts.

Biological stoichiometry – what is it and where did it come from?

  1. Top of page
  2. Abstract
  3. Introduction
  4. Biological stoichiometry – what is it and where did it come from?
  5. The association between C:N:P stoichiometry and growth
  6. The cell biology of organismal C:N:P-growth stoichiometry
  7. Ribosomal RNA genes: functional variability in copy number and in the intergenic spacer?
  8. The molecular genetics of food-web dynamics: a hypothesis
  10. Acknowledgements
  11. Bibliography

Biological stoichiometry is the study of the balance of energy and multiple chemical elements in living systems (Reiners 1986; Sterner 1995; Elser et al. 1996; Hessen 1997). It has its roots in the work of A. J. Lotka (1925), one of the first to consider how thermodynamic laws of physical–chemical systems structure the living world. Lotka’s thinking echoes in concepts that are now corner-stones of ecology: optimal foraging (Belovsky 1978), resource ratio competition theory (Tilman 1982), the Redfield ratio in oceanic biogeochemical cycling (Redfield 1958) and nutrient use efficiency (Vitousek 1982).

A direct application of Lotka’s contributions can be seen in how stoichiometry mediates food web dynamics. Disparities in elemental composition between animals and their food can affect animal feeding behaviour (Butler et al. 1989; White 1993), consumer population stability (White 1993; Sterner & Hessen 1994; Andersen 1997) and community organisation (White 1993; Gulati et al. 1991; Andersen 1997; Fig. 1d). Stoichiometric balance also impinges on trophic dynamics (Urabe & Sterner 1996; Sterner et al. 1997; Elser et al. 1998; Sterner et al. 1998) and biogeochemical cycling in food webs (Andersen 1997; Sterner et al. 1992; Elser & Hassett 1994; Urabe et al. 1995; Schindler & Eby 1997; Vanni & Layne 1997; Elser & Urabe 1999; Elser et al. 2000d; Fig. 1e). Direct evidence now exists for direct P-limitation of Daphnia growth when feeding on algae of high C:P ratio, both from laboratory studies (Urabe et al. 1997) and field experiments (Elser et al. 2000c). A key insight from this work is that organisms that must maintain elevated body nutrient content (e.g. low body C:P ratios) are generally more susceptible to poor food quality when available food develops increased C:nutrient ratios (Sterner & Schulz 1998). More recently, studies have begun to highlight how such stoichiometric constraints may shape animal evolution (Elser et al. 1996, 2000a; Markow et al. 1999; Moen et al. 1999). Furthermore, stoichiometric effects have also been demonstrated for microbial food webs in aquatic and terrestrial realms, mediating the tendency for net mineralisation vs. immobilisation of nutrients (Tezuka 1989; Chrzanowski & Kyle 1996; Paul & Clark 1996) and flagellate–bacteria interactions (Caron et al. 1985, 1990; Vadstein et al. 1993; Nakano 1994). Thus, C:N:P balance has proven to be a powerful tool for analysing ecological systems.


Figure . 1. .  Hypothesised chain of causality linking the molecular genetics of growth to ecological consequences via C:N:P stoichiometry. Direct or indirect natural selection on growth rate generates genetic change associated with ribosomal genes [for example, differences in the number of repeat units in the IGS of the rDNA may result in increased production of rRNA, as shown in (a); modified from Grimaldi & Di Nocera (1988)] because high RNA content is needed for rapid growth [(b); modified from (Sutcliffe 1970)]. Thus, there is an association between growth rate and organism C:N:P because RNA is P-rich [for example, in crustacean zooplankton, rapidly growing animals have high P-content and low N:P, as shown in (c); modified from (Main et al. 1997)]. In ecosystems, food with unbalanced elemental composition can influence the community dominance of consumer taxa with different characteristic C:N:P [for example, in lakes with P-rich seston at the base of the food web, P-rich, low N:P Daphnia dominate the zooplankton community but in lakes with P-deficient seston, low P, high N:P animals like Bosmina are the dominants; (d), modified from (DeMott & Gulati 1999)]. Furthermore, differences in the somatic C:N:P of consumers can affect nutrient excretion rates and ratios in the internal nutrient cycle of ecosystems as grazers attempt to maintain physiological homeostasis [for example, in nutrient recycling studies in Lake Biwa, Japan, high recycling N:P ratios occurred when the zooplankton community was dominated by low N:P taxa but recycling N:P was low when high N:P taxa predominated; (e), modified from (Urabe et al. 1995)].

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But what determines the C:N:P stoichiometry of living biomass? We and colleagues have proposed that, in organisms lacking major mineral storage of P (as in vacuoles or in bones), biomass C:N:P depends largely on the disproportionate demands for P-rich ribosomal RNA (rRNA) in rapidly growing cells (Fig. 1b; Elser et al. 1996; Hessen & Lyche 1991). This growth rate hypothesis potentially connects cellular allocation to organism function and ultimately to ecological dynamics. In this paper we extend this hypothesis to the level of molecular genetics. To do so, we first synthesise information regarding the connection between growth rate and C:N:P stoichiometry and then consider pertinent studies that connect biomass C:N:P to rRNA allocation and ultimately to the organisation of ribosomal genes in diverse biota. Our synthesis suggests a thread of causality linking the evolutionary genetics of rRNA to biogeochemical cycling and trophic dynamics in ecosystems.

The association between C:N:P stoichiometry and growth

  1. Top of page
  2. Abstract
  3. Introduction
  4. Biological stoichiometry – what is it and where did it come from?
  5. The association between C:N:P stoichiometry and growth
  6. The cell biology of organismal C:N:P-growth stoichiometry
  7. Ribosomal RNA genes: functional variability in copy number and in the intergenic spacer?
  8. The molecular genetics of food-web dynamics: a hypothesis
  10. Acknowledgements
  11. Bibliography

Growth is linked directly to fitness, as organisms must grow to reproduce. While life history strategies involve a rich suite of characters generated by multifaceted selective pressures (Stearns 1992), Arendt (1997) has argued that specific growth rate is a central integrating parameter of overall life history strategy. (Specific growth rate is the rate of change in mass per unit mass; hereafter, μ. To clarify discussions in the following, let μm designate the maximum μ that a particular species at a particular life stage can achieve at a standard temperature. We assume that μm is a genetically determined trait characteristic of a particular species’ developmental program. Furthermore let μ′ be the realised μ at a given time; μ′ may be reduced below μm by resource conditions.) Arendt (1997) also suggests that a relatively unexplored set of tradeoffs associated with rapid growth life-styles (high μm) is likely. We suspect that some of these tradeoffs reflect the stringent stoichiometric demands of rapid growth (Sterner & Schulz 1998; Elser et al. 2000a). Indeed, if there are clear connections between C:N:P and μm, then there also would be connections between life history evolution, physiological demand for major elements, and even ecosystem processes. What evidence is there for relationships between C:N:P and μ?

Autotrophs are characterised by wildly variable C:N:P composition. This variation has both interspecific and intraspecific components. Across a wide range of autotrophs from algae to trees to cactus (Nielsen et al. 1996), percentage N and percentage P of photosynthetic biomass decrease with increasing organism size, a change accompanied by decreasing μm. Closer analysis of these trends shows that, as μm increases, percentage P increases faster than percentage N and thus rapidly growing, small autotrophs have low N:P. Thus, at the interspecific level, there is major variation in C:N:P coupled to allometry and μm. Much variation in C:N:P in autotrophs also occurs at the physiological level as a result of plants’ abilities to store energy and nutrients in excess of immediate demands and, in a strategy of unbalanced growth, to flexibly adjust their growth rate (μ′) to ambient conditions (Chapin 1980; Marschner 1995). Indeed, when grown under wide-ranging conditions, one species of algae can exhibit nearly as much variation in C:N:P as exists in the data set studied by Nielsen and colleagues (Nielsen et al. 1996). Rules of thumb for autotroph C:N:P are: biomass N:P tracks N:P of the nutrient supply (Rhee 1978); at fixed supply rate of nutrient X, biomass C:X increases as light intensity and/or pCO2 increase (Greenwood 1976; Rhee & Gotham 1981; Smith 1983; Cotrufo et al. 1998); and under conditions of X-limited growth, biomass C:X increases steeply as μ′ declines (Goldman et al. 1979; Droop 1983; Agren 1988). The picture that emerges is one of enormous variation in C:N:P at the base of food webs (Elser et al. 2000b).

In contrast to the extreme plasticity in C:N:P exhibited by autotrophs in laboratory cultures, metazoans of a given life stage undergo balanced growth and appear to regulate elemental composition within narrower bounds, even when consuming food with large variation in C:N:P composition (Andersen & Hessen 1991; Sterner & Hessen 1994). Note, however, that physiological accumulation of large energy storage compounds (fats, wax esters and lipids lacking in N and P) can cause temporal variation in biomass C:nutrient ratios in animals with such storage capabilities. In general, however, most animals maintain a relatively tight homeostasis in C:N:P stoichiometry. When nutrient element X is in excess relative to requirements, consumers increase the specific rate of loss of that element (via excretion or egestion; Urabe 1993; DeMott et al. 1998). When challenged with food of low nutrient content (high C:X relative to their body), animals can suffer a growth penalty (μ′ declines) and their biomass C:X increases only moderately (DeMott et al. 1998). In contrast to the muted plasticity in metazoan C:N:P within a species, there is considerable (previously unappreciated) variation in biomass C:N:P stoichiometry among different taxa, even within taxonomic orders. Crustacean zooplankton alone vary more than five-fold in body P content (Fig. 1c), ranging from ∼ 0.5% P in adult copepods to ∼ 2.6% P in particular anomopods (Andersen & Hessen 1991; Hessen & Lyche 1991; Main et al. 1997). Herbivorous insects in terrestrial systems exhibit a similar range of variation in N and P content (Elser et al. 2000b). In addition, variation in zooplankton C:N:P stoichiometry seems associated with μm: in the study of Main and colleagues (Main et al. 1997), rapidly growing taxa and/or life stages had slightly elevated percentage N but much more strongly increased percentage P and, as a result, had low body N:P. In a comparative study of taxa within the Daphnia pulex species complex, Elser et al. (2000a) showed that, relative to individuals from temperate habitats, individuals from the arctic (where growing season is short and selection on growth rate should be severe) had higher μm and body percentage P, were inefficient recyclers of P, and were more susceptible to P-deficient diets. In both these zooplankton studies we see a striking association between growth and P metabolism.

It is important to note that this paradigm of nutrient composition has primarily been developed in study of freshwater zooplankton. The degree of regulation of element content, its allometric and taxonomic correlates, and the coupling of μ and C:N:P stoichiometry in other groups of organisms is still very poorly known. Is there any reason to expect that similar patterns should hold for other groups of organisms? Concordant patterns would be expected if the patterns observed in zooplankton are associated with fundamental cellular mechanisms shared with other biota. To determine if this is the case, we need to consider potential underlying mechanisms driving the association of C:N:P stoichiometry with growth rate.

The cell biology of organismal C:N:P-growth stoichiometry

  1. Top of page
  2. Abstract
  3. Introduction
  4. Biological stoichiometry – what is it and where did it come from?
  5. The association between C:N:P stoichiometry and growth
  6. The cell biology of organismal C:N:P-growth stoichiometry
  7. Ribosomal RNA genes: functional variability in copy number and in the intergenic spacer?
  8. The molecular genetics of food-web dynamics: a hypothesis
  10. Acknowledgements
  11. Bibliography

Although an empirical relationship between growth and C:N:P is clear, the mechanisms underlying the relationship are not. Why do rapidly growing organisms have such high P content and thus low biomass C:P and N:P? Several results implicate growth rate and variation in cellular allocation to P-rich ribosomal RNA (rRNA) as the source of variation in μm among organisms (Fig. 1c). For example, in metazoan zooplankton, low-P (∼ 0.5% P), high-N:P calanoid copepods have only ∼ 2% RNA by weight while P-rich (∼ 1.3% P), low-N:P Daphnia have ∼ 10% RNA (Båmstedt 1986; McKee & Knowles 1987). Because RNA is ∼ 10% P by weight, differences in RNA-P are entirely sufficient to explain the difference between Daphnia and adult copepods in whole organism P content (Sterner 1995; Elser et al. 1996). This difference is consistent with the known life histories of these taxa: calanoid copepods are long-lived, slow-growing as adults with relatively low reproductive output whereas Daphnia are fast-growing, generalists that produce multiple cohorts of large offspring. This association between growth and RNA concentration appears to be broadly applicable across diverse organisms (Fig. 1b). (Let [RNA]′ be the instantaneous RNA concentration of an organism at a given time and [RNA]m be the maximum [RNA] characteristic of a particular species at a particular life stage.) From Salmonella to cockroaches, organisms with high μm have high [RNA]m (Sutcliffe 1970). This makes perfect sense as: (1) RNA makes up 50–60% of the ribosome, the machine of growth in the cell (Becker 1986); (2) the steady-state level of this ribosomal RNA (rRNA) usually comprises 80–90% of the total cellular RNA, with increasing total allocation at high growth rate (Alberts et al. 1983) and (3) approximately 10 million ribosomes are necessary to support protein synthesis in the average cell (Lewin 1980).

These studies lead us to suggest that a P-rich, low-N:P signature of rapid growth is a cellular necessity derived from the fact that ribosomes are unusually P-rich (Elser et al. 1996). We would expect, then, a consistent positive association between μm and [RNA]m, while biomass C:P and N:P should generally decline with μm. Indeed, this appears to be the pattern in crustacean zooplankton (Fig. 1c), and it is commonplace in cell culture, aquaculture and fisheries studies to use [RNA]′, RNA′:DNA, or RNA′:protein to assess the growth status (μ′) of target organisms, including fish (Bulow 1987; Buckley & Caldarone 1999), decapods (Juinio & Cobb 1994), mysids (Båmsted 1983), copepods (Ota & Landry 1984; Saiz et al. 1998; Wagner et al. 1998), Daphnia (McKee & Knowles 1987; Barber et al. 1994), chaetognaths (Båmsted 1983), phytoplankton (Rhee 1973; Dortch et al. 1983) and bacteria (Kato 1994; Massana et al. 1998). Furthermore, changes in [RNA]m during ontogenetic development of a single species [e.g. in copepods (Båmsted & Skjoldal 1976), euphausids (Skjoldal & Båmsted 1976), herring larvae (Clemmesen 1994)] and in [RNA]′ in response to environmental variability [e.g. in temperature (Saiz et al. 1998), in food availability (Malloy & Targett 1994; Wagner et al. 1998)] have been documented. It is interesting to note that measurements of insect RNA levels under field conditions seem almost completely lacking. Nevertheless, there seems ample evidence in existing studies that high growth rate lifestyles are associated with elevated RNA allocation. But how is a high RNA phenotype generated? What are the genetic mechanisms necessary to achieve elevated cellular rRNA and thus high μm?

Ribosomal RNA genes: functional variability in copy number and in the intergenic spacer?

  1. Top of page
  2. Abstract
  3. Introduction
  4. Biological stoichiometry – what is it and where did it come from?
  5. The association between C:N:P stoichiometry and growth
  6. The cell biology of organismal C:N:P-growth stoichiometry
  7. Ribosomal RNA genes: functional variability in copy number and in the intergenic spacer?
  8. The molecular genetics of food-web dynamics: a hypothesis
  10. Acknowledgements
  11. Bibliography

To answer these questions, one needs to know the molecular organisation of ribosomal RNA genes and associated spacer regions in the genome (rDNA), its variability and the functional significance of this variation in satisfying the demand for rRNA in different organisms. In most eukaryotes, rRNA genes are present in high copy number and are clustered as tandem repeats at one or more chromosomal sites, termed nucleolus organiser regions. Each rDNA array consists of a transcription unit, which includes the genes for the 18S, 5.8S and 28S rRNA subunits (the “rrn” genes), the internal transcribed spacers separating the genes within a unit, and an intergenic spacer (IGS, formerly NTS – nontranscribed spacer) separating adjoining units. Because of their structural and catalytic functions during protein synthesis, the rrn genes are essential for the support of cell differentiation, development, and growth. That is why they are usually present in high copy number (see reviews by Long & Dawid 1980; Cortadas & Pavon 1982; Sollner-Webb & Tower 1986). Thus, rDNA array size is a function of copy number and gene/spacer repeat length. The transcription unit as a whole is usually highly conserved across a wide range of species and shows a high degree of sequence and secondary structure similarity among phylogenetically diverse taxa (Goldman et al. 1983; Elwood et al. 1985). In contrast, the subrepetitive elements within the IGS appear to be changing rapidly and, as a result, IGS regions can vary not only between different species but also between populations, individuals, and even within a single cell (Boseley et al. 1979; Paule & Lofquist 1996; Ganley & Scott 1998). Both restriction-site variation and, more commonly, length variation occur (Rogers & Bendich 1987). It is now known from molecular genetic studies that the IGS is critically important for the regulation of rDNA metabolism, carrying all the elements necessary for transcription and correct termination of rRNAs (for references see Reeder & Dunaway 1983). Indeed, Polymerase I transcribes through the IGS of Xenopus (Labhart & Reeder 1987) and Drosophila (Grimaldi et al. 1990) and promoter-proximal termination IGS sequences stimulate initiation of transcription in vertebrates (Grummt et al. 1986; Henderson & Sollner-Webb 1986). Given these regulatory properties, variation in sequence and organisation of the IGS seems highly functional, resulting in “molecular coevolution” (Dover 1982) of the transcription machinery (Evers & Grummt 1995).

Despite the apparent functional significance of rDNA variation suggested by molecular studies and the solid evidence for variation of rDNA structure in different taxa, to date rDNA heterogeneity has largely been studied for construction of phylogenetic relationships and for quantification of gene flow between populations (Gray & Schnare 1996). There is little knowledge concerning the effects of rDNA heterogeneity on growth and development, performance of different organismal functions, and adaptive response; needless to say, the consequences for ecosystem dynamics owing to such variation have not yet been contemplated. However, several lines of evidence indicate that variation in the intergenic spacers has major functional consequences due to the relationship between cellular RNA levels and organism growth rate (Table 1). For example, under selection for development time (μm), spacer length in Drosophilamelanogaster increased in concert with accelerated development, i.e. increased μm (Cluster et al. 1987). This response is consistent with the idea that, as for other genes, transcription rates of rDNA genes are increased by the presence of enhancer regions (Paule & Lofquist 1996). In the case of rDNA, these enhancers are located in the IGS and occur in multiple copies that vary both intra- and interspecifically (Reeder et al. 1983; Paule & Lofquist 1996). Indeed, another study of D. melanogaster has shown that the rate of transcriptional production of prerRNA is directly proportional to the number of enhancers in the IGS (Fig. 1a, Table 1; Grimaldi & Di Nocera 1988). This suggests that there should be relationships between the multiplicity of enhancers in the IGS (and hence variation in spacer length), [RNA]m, and μm. Increased numbers of rDNA enhancers should act to increase the rate of rRNA production by RNA Polymerase I. However, rates of Polymerase I transcription per rDNA gene have an upper limit and one might then expect, under strong selective pressures for high μm, increased dosage of rDNA genes in order to further increase rRNA production rate. Indeed, it appears that organisms have adopted diverse strategies to assure sufficient rRNA production according to the particular demands of their life history (Table 2). The tendency to increase copy number of ribosomal genes is rather obvious. While ribosomal genes can be amplified externally in certain organisms and tissue types (e.g. oocytes), most variation occurs in chromosomal rDNA copy number. According to the review of Long and Dawid (Long & Dawid 1980), rDNA gene copy number within the Class Insecta alone varies at least 7-fold (and at least 3.5-fold within the drosophilids). In plants at least, it appears that many of the added copies of rDNA genes are superfluous (Rogers & Bendich 1987); thus, to evaluate these ideas it will be necessary to distinguish between active and inactive rDNA genes in the genome. In any case, while many authors have implicated ecogeographic factors connected to genetic variation in rDNA in particular taxa, to our knowledge no studies have examined the functional significance and evolutionary ecological implications of rDNA copy number and spacer length variation across a wide range of taxa and selective environments. We hypothesise that major features of the organisation of rDNA genes (such as spacer length, copy number) underpin phenotypic variation in rRNA synthesis, ribosomal production and thus also μm, [RNA]m and C:N:P. Furthermore, if C:N:P variation has broad ecological significance as indicated by various recent studies, particular behavioural, physiological and ecological correlates should accompany major patterns in the structure of rDNA genes.

Table 1.  . Observations related to variation in the structure of rDNA genes (as rrn copy number, IGS length) and growth-or rRNA-related parameters in different species Thumbnail image of
Table 2.  . Genetic mechanisms by which a large demand for rRNA can be satisfied in different organisms Thumbnail image of

Observation of significant variation in the organisation of the rDNA genome raises the question of how such variation is generated at the molecular level. Indeed, the fact that rDNA copy number is known to vary so widely within a species suggests that duplication and deletion of repeats is easy and frequent. Divergence of rDNA is directly tied to the same forces that influence variation of any repetitive DNA: mutation, unequal crossing-over, nonhomologous exchange, intrachromosomal recombination, gene conversion, and random drift (Ohta & Dover 1983; Ganley & Scott 1998). The relative roles of these processes in inducing and maintaining rDNA variability are uncertain, although it is believed that some of these mechanisms are linked (Szostak et al. 1983). Intra-chromosomal recombination (unequal crossing-over or gene conversion between sister chromatids) is probably the most important (e.g. Schlötterer & Tautz 1994) but interchromosomal exchange can also take place at high rates in Drosophila (Polanco et al. 1998). Fluctuations in either rDNA copy number and/or IGS length are thought to occur by unequal crossing over at the level of the entire rDNA units or at the level of IGS subrepeats, respectively (Dover et al. 1993). Recombination can be mitotic or meiotic and therefore repeat variants can arise during both sexual and asexual reproduction or even in somatic cell lineages (Cullis & Charlton 1981). For example, it has been shown recently that unequal crossing over in the fungus Neotyphodium can produce significant changes in the IGS in just two generations (Ganley & Scott 1998). Thus, the overall picture with respect to genetic mechanisms is that there are many means by which major changes in the organisation of the IGS can be generated during production of gametes, mitotic production of asexual propagules, and even during mitotic production of somatic cells. If, as suggested by material reviewed in preceding paragraphs, such variations have functional significance, then considerable raw material for the evolution of C:N:P – growth stoichiometry is constantly being made available. Whether these connections to evolution and genetics have major effects on the structure and function of food webs remains to be seen. We suspect that they do and conclude by proposing that it may now be possible to generate a functionally realistic model of ecological dynamics informed by modern genetic understanding.

The molecular genetics of food-web dynamics: a hypothesis

  1. Top of page
  2. Abstract
  3. Introduction
  4. Biological stoichiometry – what is it and where did it come from?
  5. The association between C:N:P stoichiometry and growth
  6. The cell biology of organismal C:N:P-growth stoichiometry
  7. Ribosomal RNA genes: functional variability in copy number and in the intergenic spacer?
  8. The molecular genetics of food-web dynamics: a hypothesis
  10. Acknowledgements
  11. Bibliography

The work we have described indicates that evolution of growth rate and molecular mechanisms related to RNA allocation are inextricably linked. Furthermore, it seems clear that growth and C:N:P stoichiometry of organisms are closely connected due to major effects of RNA allocation on organism P-content. Finally, major effects of organism C:N:P stoichiometry for trophic dynamics, population stability and nutrient cycling are manifest from a variety of recent findings. This synthesis leads us to hypothesise that patterns of community structure, trophic interactions, and biogeochemical cycling in food webs are generated by specific molecular genetic variations among interacting and coevolving biota. In the most general sense we predict that variation in the relative abundance of high growth rate, low C:P and N:P consumer taxa with relatively long IGS regions and elevated rDNA dosage should be higher in systems with abundant, good quality (low C:N and C:P) food. Conversely, only slow growing taxa (with high C:P and N:P ratios, short IGS regions, and low rDNA copy number) should be able to persist in strongly nutrient-deficient systems with poor quality (high C:P and C:N) food. Because the mechanisms described are fundamental, we expect that these patterns should hold both within particular habitats (e.g. across different lakes differing in trophic status, across agricultural fields subjected to different levels of fertilisation) as well as across habitats (e.g. oceans to lakes to wetlands to deserts). Furthermore, reflecting the consequences of stoichiometric constraints for consumer dynamics (Andersen 1997), we also expect that consumers with elevated RNA allocations due to variation in their ribosomal genome will enjoy a growth advantage during good food conditions but will be unusually susceptible to stoichiometrically unbalanced food. As a result, they may have particularly erratic population dynamics and be more vulnerable to deterministic extinction (Andersen 1997).

Furthermore, an appreciation of the molecular mechanisms by which functionally significant variation in key rDNA genes is generated and of the functional consequences of that variation permits us to hypothesise how stoichiometric relations might operate in the self-organisation of trophic interactions and nutrient cycling in food webs over evolutionary time. Imagine a limited number of individuals in a few functional groups (e.g. primary producers, herbivores, detritivores, decomposer bacteria, higher predators) introduced to an environment with a set supply of chemical elements and external solar energy inputs. Upon introduction, some set of interactions will inevitably proceed and indeed such dynamics are the topic of most existing food web models. However, it no longer seems prudent to ignore evolutionary change in consideration of ecological dynamics (Thompson 1999), especially given the apparent propensity of ribosomal genomes to reorganise with significant consequences for organism life history and physiological function. Thus, if the growth-related genes are allowed to mutate (with their associated effects on organism C:N:P stoichiometry), one can imagine that some environments (low phosphorus vs. high phos-phorus, for example) might favour or disfavour particular strains, with concurrent effects on the web of trophic interactions and recycling feedback. It is not clear from any existing theory what shape such food webs should event-ually develop. We suggest that recent increases in our un-derstanding of these stoichiometric relationships now make it feasible for such a theory to be constructed and tested.


  1. Top of page
  2. Abstract
  3. Introduction
  4. Biological stoichiometry – what is it and where did it come from?
  5. The association between C:N:P stoichiometry and growth
  6. The cell biology of organismal C:N:P-growth stoichiometry
  7. Ribosomal RNA genes: functional variability in copy number and in the intergenic spacer?
  8. The molecular genetics of food-web dynamics: a hypothesis
  10. Acknowledgements
  11. Bibliography

James J. Elser is a biologist who primarily studies trophic dynamics and nutrient cycling in pelagic food webs. He is a professor of biology at Arizona State University and project director of the interdisciplinary study “Biological stoichiometry from genes to ecosystems” (, funded by the National Science Foundation’s Integrated Research Challenges in Environmental Biology (IRCEB) program. The co-authors are collaborating investigators on that project.

Editor, Ulrich Sommer

Revised manuscript received 5 September 2000

Manuscript accepted 6 September 2000


  1. Top of page
  2. Abstract
  3. Introduction
  4. Biological stoichiometry – what is it and where did it come from?
  5. The association between C:N:P stoichiometry and growth
  6. The cell biology of organismal C:N:P-growth stoichiometry
  7. Ribosomal RNA genes: functional variability in copy number and in the intergenic spacer?
  8. The molecular genetics of food-web dynamics: a hypothesis
  10. Acknowledgements
  11. Bibliography
  • 1
    Agren, G.I. (1988). Ideal nutrient productivities and nutrient pro-portions in plant growth. Plant Cell Environment, 11, 613620.
  • 2
    Alberts, B, Bray, D., Lewis, J, Raff, M., Roberts, K. & Watson, J.D. (1983). Molecular Biology of the Cell. Garland Publishing Inc., New York, NY, USA.
  • 3
    Andersen, T. (1997). Pelagic Nutrient Cycles: Herbivores as Sources and Sinks. Springer-Verlag, Berlin, Germany.
  • 4
    Andersen, T. & Hessen, D.O. (1991). Carbon, nitrogen, and phosphorus content of freshwater zooplankton. Limnol. Oceanogr., 36, 807814.
  • 5
    Arendt, J.D. (1997). Adaptive intrinsic growth rates: an integration across taxa. The Q Rev. Biol., 72, 149177.
  • 6
    Båmsted, U. (1983). RNA concentration in zooplankton: seasonal variation in boreal species. March Ecol. Prog. Ser., 11, 291297.
  • 7
    Båmsted, U. & Skjoldal, H.R. (1976). Studies on the deep-water pelagic community of Korsfjorden, Western Norway: Adenosine phosphates and nucleic acids in Euchaeta norvegica (Copepoda) in relation to its life cycle. Sarsia, 60, 6380.
  • 8
    Båmstedt, U. (1986). Chemical composition and energy content. In: The Biological Chemistry of Marine Copepods. (eds Corner, E.D.S. & S.C.M. O’Hara). Oxford University Press, Oxford, UK.
  • 9
    Barber, I., Baird, D.J. & Calow, P. (1994). Effect of cadmium and ration level on oxygen consumption, RNA concentration, and RNA–DNA ratio in two clones of Daphnia magna Straus. Aquat. Toxicol., 30, 249258.
  • 10
    Becker, W.M. (1986). The World of the Cell. Benjamin/Cummings Publishing. Menlo Park, CA, USA.
  • 11
    Boseley, P., Moss, T., Machler, M., Portmann, R. & Birnstiel, M. (1979). Sequence organisation of the spacer DNA in a ribosomal gene unit of Xenopus laevis. Cell, 17, 1931.
  • 12
    Buckley, L.E. & Caldarone, O.T.L. (1999). RNA–DNA ratio and other nucleic acid-based indicators for growth and condition of marine fishes. Hydrobiologia, 401, 265277.
  • 13
    Bulow, F.J. (1987). RNA–DNA ratios as indicators of growth in fish: a review. In: The Age and Growth of Fish. (eds Summerfelt, R.C. & Hall, G.E.). Iowa State University Press, Ames, Iowa.
  • 14
    Caron, D.A., Goldman, J.C., Andersen, O.K. & Dennett, M.R. (1985). Nutrient cycling in a microflagellate food chain: II. Population dynamics and carbon cycling. March Ecol. Prog. Ser., 24, 243254.
  • 15
    Caron, D.A., Porter, K.G. & Sanders, R.W. (1990). Carbon, nitrogen, and phosphorus budgets for the mixotrophic phytoflagellate Poterioochromonas malhamensis (Chrysophyceae) during bacterial ingestion. Limnol. Oceanogr., 35, 433442.
  • 16
    Chapin, F.S. (1980). The mineral nutrition of wild plants. Ann. Rev. Ecol. Syst., 11, 233260.
  • 17
    Chrzanowski, T.H. & Kyle, M. (1996). Ratios of carbon, nitrogen, and phosphorus in Pseudomonas fluorescens as a model for bacterial element ratios and nutrient regeneration. Aquat. Microb. Ecol., 10, 115122.
  • 18
    Clemmesen, C. (1994). The effect of food availability, age or size on the RNA/DNA ratio of individually measured herring larvae: laboratory calibration. March Biol., 118, 377382.
  • 19
    Cluster, P.D., Marinkovic, D., Allard, R.W. & Ayala, F.J. (1987). Correlations between development rates, enzyme activities, ribosomal DNA spacer-length phenotypes, and adaptation in Drosophila melanogaster. Proc. Natl. Acad. Sci. USA, 84, 610614.
  • 20
    Cortadas, J. & Pavon, M.C. (1982). The organization of ribosomal genes in vertebrates. EMBO J., 1, 10751080.
  • 21
    Cotrufo, M.F., Briones, M.J.I. & Ineson, P. (1998). Elevated CO2 affects field decomposition rate and palatability of tree leaf litter: Importance of changes in substrate quality. Soil Biol. Biochem., 30, 15651571.DOI: 10.1016/S0038-0717(98)00032-7
  • 22
    Cullis, C.A. & Charlton, L. (1981). The induction of ribosomal DNA changes in flax. Plant Sci. Lett., 20, 213217.
  • 23
    Delany, M.E. & Krupkin, A.B. (1999). Molecular characterization of ribosomal gene variation within and among NORs segregating in specialized populations of chicken. Genome, 42, 6071.
  • 24
    Delany, M.E., Emsley, A., Smiley, M.B., Putnam, J.R. & Bloom, S.E. (1994a). Nucleolar size polymorphisms in commercial layer chickens – determination of incidence, inheritance, and nucleolar sizes within and among chicken lines selected for enhanced growth. Poultry Sci., 73, 12111217.
  • 25
    Delany, M.E., Muscarella, D.E. & Bloom, S.E. (1994b). Effects of rRNA gene copy number and nucleolar variation on early development: inhibition of gastrulation in rDNA-deficient chick embryos. J. Heredity, 85, 211217.
  • 26
    DeMott, W.R. & Gulati, R.D. (1999). Phosphorus limitation in Daphnia: evidence from a long-term study of three hypereutrophic Dutch lakes. Limnol. Oceanogr., 44, 15571564.
  • 27
    DeMott, W.R., Gulati, R.D. & Siewertsen, K. (1998). Effects of phosphorus-deficient diets on the carbon and phosphorus balance of Daphnia magna. Limnol. Oceanogr., 43, 11471161.
  • 28
    Desalle, R., Slightom, J. & Zimmer, E. (1986). The molecular through ecological genetics of abnormal abdomen: II. Ribosomal DNA polymorphism is associated with the abnormal abdomen syndrome in Drosophila mercatorum. Genetics, 112, 861876.
  • 29
    Dortch, Q., Roberts, T.L., Clayton, J.R. & Ahmed, S.I. (1983). RNA/DNA ratios and DNA concentrations as indicators of growth rate and biomass in planktonic marine organisms. March Ecol. Prog. Ser., 13, 6171.
  • 30
    Dover, G.A. (1982). Molecular drive: a cohesive mode of species evolution. Nature, 295, 564568.
  • 31
    Dover, G.A., Linares, A.R., Bowen, T. & Hancock, J.M. (1993). The detection and quantification of concerted evolution and molecular drive. Meth. Enzymol., 224, 525541.
  • 32
    Droop, M.R. (1983). 25 years of algal growth kinetics: a personal view. Bot. Marina, 26, 99112.
  • 33
    Elser, J.J. & Hassett, R.P. (1994). A stoichiometric analysis of the zooplankton–phytoplankton interaction in marine and freshwater ecosystems. Nature, 370, 211213.
  • 34
    Elser, J.J. & Urabe, J. (1999). The stoichiometry of consumer-driven nutrient cycling: theory, observations, and consequences. Ecology, 80, 735751.
  • 35
    Elser, J.J, Dobberfuhl, D., MacKay, N.A. & Schampel, J.H. (1996). Organism size, life history, and N:P stoichiometry: towards a unified view of cellular and ecosystem processes. Bioscience, 46, 674684.
  • 36
    Elser, J.J, Chrzanowski, T.H., Sterner, R.W. & Mills, K.H. (1998). Stoichiometric constraints on food-web dynamics: a whole-lake experiment on the Canadian Shield. Ecosystems, 1, 120136.
  • 37
    Elser, J.J., Dowling, T., Dobberfuhl, D.A. & O’Brien, J. (2000a). The evolution of ecosystem processes: ecological stoichiometry of a key herbivore in temperate and arctic habitats. J. Evol. Biol., in press.
  • 38
    Elser, J.J., Fagan, W.F., Denno, R.F., Dobberfuhl, D.R., Folarin, A., Huberty, A., Interlandi, S., Kilham, S.S, McCauley, E, Schulz, K.L, Siemann, E.H. & Sterner, R.W. (2000b). Nutritional constraints in terrestrial and freshwater food webs. Nature, in press.
  • 39
    Elser, J.J., Hayakawa, H. & Urabe, J. (2000c). Nutrient limitation reduces food quality for zooplankton: Daphnia response to seston phosphorus enrichment. Ecology, in press.
  • 40
    Elser, J.J., Sterner, R.W., Galford, A.E., Chrzanowski, T.H., Findlay, D.L., Mills, K.H., Paterson, M.J., Stainton, M.P. & Schindler, D.W. (2000d). Pelagic C: N: P stoichiometry in a eutrophied lake: responses to a whole-lake food-web manipulation. Ecosystems, 3, 293307.
  • 41
    Elwood, H.J., Olsen, G.J. & Sogin, M.L. (1985). The small-subunit ribosomal RNA gene sequences from the hypotrichous ciliates Oxytricha nova and Stylonychia pustulata. Mol. Biol. Evol., 2, 399410.
  • 42
    Evers, R & Grummt, I. (1995). Molecular evolution of the mammalian ribosomal gene terminator sequences and the transcription termination factor TTF-I. Proc. Natl. Acad. Sci. USA, 92, 58275831.
  • 43
    Flavell, R.B., O’Dell, M., Sharp, P. & Nevo, E. (1986). Variation in the intergenic spacer of ribosomal DNA of wild wheat, Triticum dicoccoides, in Israel. Mol. Biol. Evol., 3, 547558.
  • 44
    Franz, G. & Kunz, W. (1981). Intervening sequences in ribosomal RNA genes and bobbed phenotype in Drosophila hydei. Nature, 292, 638640.
  • 45
    Gall, J.G. (1968). Differential synthesis of the genes for ribosomal RNA during amphibian oogenesis. Proc. Natl. Acad. Sci. USA, 60, 553560.
  • 46
    Ganley, A.R.D. & Scott, B. (1998). Extraordinary ribosomal spacer length heterogeneity in a neotyphodium endophyte hybrid: implications for concerted evolution. Genetics, 150, 16251637.
  • 47
    Goldman, W.E., Goldberg, G., Bowman, L.H, Steinmetz, D. & Schlessinger, D. (1983). Mouse rDNA: Sequences and evolutionary analysis of spacer and mature RNA regions. Mol. Cell. Biol., 3, 14881500.
  • 48
    Goldman, J.C., McCarthy, J.J. & Peavey, D.G. (1979). Growth rate influence on the chemical composition of phytoplankton in oceanic waters. Nature, 279, 210215.
  • 49
    Gray, M.W & Schnare, M.N. (1996). Evolution of rRNA gene organization. In: Ribosomal RNA: Structure, Evolution, Processing, and Function in Protein Biosynthesis. (eds Zimmerman, R.A. & Dahlberg, A.E.). CRC Press, Boca Raton, FL, USA.
  • 50
    Greenwood, E.A.N. (1976). Nitrogen stress in plants. Adv. Agron., 28, 135.
  • 51
    Grimaldi, G. & Di Nocera, P.O. (1988). Multiple repeated units in Drosophila melanogaster ribosomal DNA spacer stimulate rRNA precursor transcription. Proc. Natl. Acad. Sci. USA, 85, 55025506.
  • 52
    Grimaldi, G., Fiorentini, P. & DiNocera, P.P. (1990). Spacer promoters are orientation-dependent activators of pre-ribosomal RNA transcription in Drosophila melanogaster. Mol. Cell. Biol., 10, 46674677.
  • 53
    Grummt, I., Kuhn, A., Bartsch, I. & Rosenbauer, H. (1986). A transcription terminator located upstream of the mouse rDNA initiation site affects rRNA synthesis. Cell, 47, 901911.
  • 54
    Gulati, R.D., Siewertsen, K. & Van Liere, L. (1991). Carbon and phosphorus relationships of zooplankton and its seston food in Loosdrecht Lakes. Mem. Ist. Ital. Idrobiol., 48, 279298.
  • 55
    Henderson, S. & Sollner-Webb, B. (1986). A transcription terminator is a novel element of the promoter of the mouse ribosomal RNA gene. Cell, 47, 891900.
  • 56
    Hessen, D.O. & Lyche, A. (1991). Inter- and intraspecific variations in zooplankton element composition. Archiv. Hydrobiol., 121, 343353.
  • 57
    Jackson, P.J. (1980). Characterization of the ribosomal DNA of soybean cells. Fed. Proc., 39, 1878.
  • 58
    John, B. & Miklos, G. (1988). The Eukaryote Genome in Development and Evolution. Allen & Unwin. London, UK.
  • 59
    Juinio, M.A.R. & Cobb, J.S. (1994). Estimate of recent growth of field-caught postlarval American lobsters, Homarus americanus, from RNA:DNA Ratios. Can. J. Fish. Aquat. Sci., 51, 286294.
  • 60
    Kafatos, F.C., Orr, W. & Delidakis, K. (1985). Developmentally regulated gene amplification. Trends Genet., 1, 301306.
  • 61
    Kato, K. (1994). Planktonic bacterial DNA and RNA synthesis from algal extracellular products in a eutrophic lake. FEMS-Microb. Ecol., 15, 291298.
  • 62
    Labhart, P. & Reeder, R. (1987). A 12-base pair sequence is an essential element of the ribosomal gene terminator in Xenopus laevis. Mol. Cell. Biol., 7, 19001905.
  • 63
    Lewin, B. (1980). Gene Expression, Vol. 2. Eucaryotic Chromosomes. John Wiley and Sons, New York, NY, USA.
  • 64
    Long, E.O. & Dawid, I.B. (1980). Repeated genes in eukaryotes. Ann. Rev. Biochem., 49, 727764.
  • 65
    Maienschein, J. (1991). Transforming Traditions in American Biology, 1880–1915. The Johns Hopkins University Press, Baltimore, MD, USA.
  • 66
    Main, T., Dobberfuhl, D.R. & Elser, J.J. (1997). N:P stoichio-metry and ontogeny in crustacean zooplankton: a test of the growth rate hypothesis. Limnol. Oceanogr., 42, 14741478.
  • 67
    Malloy, K.D. & Targett, T.E. (1994). The use of RNA:DNA ratios to predict growth limitation of juvenile summer flounder (Paralichthys dentatus) from Delaware and North Carolina estuaries. March Biol., 118, 367375.
  • 68
    Markow, T.A., Raphael, B., Dobberfuhl, D., Breitmeyer, C.M., Elser, J.J. & Pfeiler, E. (1999). Elemental stoichiometry of Drosophila and their hosts. Func Ecol., 13, 7884.
  • 69
    Marschner, H. (1995). Mineral Nutrition of Higher Plants. Academic Press, London, UK.
  • 70
    Massana, R., Taylor, L.T., Murray, A.E., Wu, K., Jeffrey, W.H. & DeLong, E.F. (1998). Vertical distribution and temporal variation of marine planktonic archaea in the Gerlache Strait, Antarctica, during early spring. Limnol. Oceanogr., 43, 607617.
  • 71
    McKee, M. & Knowles, C.O. (1987). Levels of protein, RNA, DNA, glycogen, and lipids during growth and development of Daphnia magna straus (Crustacea: Cladocera). Freshwater Biol., 18, 341351.
  • 72
    Moen, R.A, Pastor, J. & Cohen, Y. (1999). Antler growth and extinction of Irish Elk. Evol. Ecol. Res., 1, 235249.
  • 73
    Nakano, S. (1994). Carbon:nitrogen:phosphorus ratios and nutrient regeneration of a heterotrophic flagellate fed on baceria with different elemental ratios. Arch. Hydrobiol., 129, 257271.
  • 74
    Nielsen, S.L., Enríquez, S., Duarte, C.M. & Sand-Jensen, K. (1996). Scaling maximum growth rates across photosynthetic organisms. Func Ecol., 10, 167175.
  • 75
    Nomura, M., Gourse, R. & Baughman, G. (1984). Regulation of the synthesis of ribosomes and ribosomal components. Ann. Rev. Biochem., 53, 75117.
  • 76
    Ohta, T. & Dover, G.A. (1983). Population genetics of multigene families that are dispersed into two or more chromosomes. Proc. Natl. Acad. Sci. USA, 80, 40794083.
  • 77
    Ota, A.Y. & Landry, M.R. (1984). Nucleic acids as growth rate indicators for early developmental stages of Calanus pacificus Brodsky. J. Exp. March Biol. Ecol., 80, 147160.
  • 78
    Paul, E.A. & Clark, F.E. (1996). Soil Microbiology and Biochemistry. Academic Press, San Diego, CA, USA.
  • 79
    Paule, M.R & Lofquist, A.K. (1996). Organization and expression of eukaryotic ribosomal RNA genes. In: Ribosomal RNA: Structure, Evolution, Processing, and Function in Protein Biosynthesis. (eds Zimmerman, R.A. & Dahlberg, A.E.). CRC Press, New York, NY, USA.
  • 80
    Polanco, C., Gonzalez, A., Del La Fuente, A. & Dover, G. (1998). Multigene family of ribosomal DNA in Drosophila melanogaster reveals contrasting patterns of homogenization for IGS and ITS spacer regions: a possible mechanism to resolve this paradox. Genetics, 149, 243256.
  • 81
    Polanco, C. & Perez de la Vega, M. (1997). Intragenic ribosomal spacer variability in hexaploid oat cultivars and landraces. Heredity, 78, 115123.
  • 82
    Redfield, A.C. (1958). The biological control of chemical factors in the environment. Am. Sci., 46, 205221.
  • 83
    Reeder, R.H. & Dunaway, M. (1983). Spacer regulation of Xenopus ribosomal gene transcription. Competition Oocytes. Cell, 35, 449456.
  • 84
    Reiners, W.A. (1986). Complementary models for ecosystems. Am. Nat., 127, 5973.
  • 85
    Rhee, G.-Y. (1973). Continuous culture study of phosphate uptake, growth rate and polyphosphate in Scenedesmus sp. J. Phycology, 9, 495506.
  • 86
    Rhee, G. (1978). Effects of N:P atomic ratios and nitrate limitation on algal growth, cell composition, and nitrate uptake. Limnol. Oceanogr., 23, 1025.
  • 87
    Rhee, G.-Y. & Gotham, I.J. (1981). The effect of environmental factors on phytoplankton growth: light and the interactions of light with nitrate limitation. Limnol. Oceanogr., 26, 649659.
  • 88
    Ritossa, F. (1976). The bobbed locus (Drosophila). Genet. Biol. Drosophila, 1b, 801846.
  • 89
    Rocheford, T.R., Osterman, J.C. & Gardner, C.O. (1990). Variation in the ribosomal DNA intergenic spacer of a maize population mass-selected for high grain yield. Theor. Appl. Genet., 79, 793800.
  • 90
    Rogers, S.O. & Bendich, A.J. (1987). Ribosomal RNA genes in plants: variability in copy number and in the intergenic spacer. Plant Mol. Biol., 9, 509520.
  • 91
    Saiz, E., Calbet, A, Fara, A. & Berdalet, E. (1998). RNA content of copepods as a tool for determining adult growth rates in the field. Limnol. Oceanogr., 43, 465470.
  • 92
    Schindler, D.E. & Eby, L.A. (1997). Stoichiometry of fishes and their prey: implications for nutrient recycling. Ecology, 78, 18161831.
  • 93
    Schlötterer, C. & Tautz, D. (1994). Chromosomal homogeneity of Drosophila ribosomal DNA arrays suggests intrachromosomal exchanges drive concerted evolution. Curr. Biol., 4, 777783.
  • 94
    Shermoen, A.W. & Kiefer, B.I. (1975). Regulation in rDNA-deficient Drosophila melanogaster. Cell, 4, 275280.
  • 95
    Skjoldal, H.R & Båmsted, U. (1976). Studies on the deep-water pelagic community of Korsfjorden, western Norway: adenosine phosphates and nucleic acids in Euchaeta norvegica (Copepoda) in relation to its life cycle. Sarsia, 60, 6380.
  • 96
    Smith, V.H. (1983). Light and nutrient dependence of photosynthesis by algae. J. Phycol., 19, 306313.
  • 97
    Smocovitis, V.B. (1996). Unifying Biology. Princeton University Press, Ewing, New Jersey.
  • 98
    Sollner-Webb, B. & Tower, J. (1986). Transcription of cloned euk-aryotic ribosomal RNA genes. Ann. Rev. Biochem., 55, 801803.
  • 99
    Standiford, D.M. (1988). The development of a large nucleolus during oogenesis in Acanthocyclops vernalis (Crustacea, Copepoda) and its possible relationship to chromatin diminution. Biol. Cell, 63, 3540.
  • 100
    Stearns, S.C. (1992). The Evolution of Life Histories. Oxford University Press, Oxford, UK.
  • 101
    Sterner, R.W. (1995). Elemental stoichiometry of species in ecosystems. In: Linking Species and Ecosystems. (eds Jones, C. & Lawton, J.). Chapman & Hall, New York, NY, USA.
  • 102
    Sterner, R.W., Clasen, J, Lampert, W. & Weisse, T. (1998). Carbon:phosphorus stoichiometry and food chain production. Ecol. Lett, 1, 146150.
  • 103
    Sterner, R.W., Elser, J.J., Fee, E.J., Guildford, S.J. & Chrzanowski, T.H. (1997). The light:nutrient ratio in lakes: the balance of energy and materials affects ecosystem structure and process. Am. Nat., 150, 663684.
  • 104
    Sterner, R.W, Elser, J.J. & Hessen, D.O. (1992). Stoichiometric relationships among producers, consumers, and nutrient cycling in pelagic ecosystems. Biogeochemistry, 17, 4967.
  • 105
    Sterner, R.W. & Hessen, D.O. (1994). Algal nutrient limitation and the nutrition of aquatic herbivores. Ann. Rev. Ecol. Syst., 25, 129.
  • 106
    Sterner, R.W. & Schulz, K.L. (1998). Zooplankton nutrition: recent progress and reality check. Aquat. Ecol., 33, 119.
  • 107
    Sutcliffe, W.H. (1970). Relationship between growth rate and ribonucleic acid concentration in some invertebrates. J. Fish. Res. Bd. Can., 27, 606609.
  • 108
    Szostak, J.W., Orr-Weaver, T.L., Rothstein, R.J. & Stahk, F.W. (1983). The double-strand-break repair model for recombination. Cell, 33, 2535.
  • 109
    Templeton, A.R., Crease, T.J. & Shah, F. (1985). The molecular through ecological genetics of abnormal abdomen in Drosophila mercatorum. I. Basic genetics. Genetics, 111, 805818.
  • 110
    Tezuka, Y. (1989). The C:N:P ratio of phytoplankton determines the relative amounts of dissolved inorganic nitrogen released during aerobic decomposition. Hydrobiologia, 173, 5562.
  • 111
    Thiebaud, C.H. (1979). Quantitative determination of amplified rDNA and its distribution during oogenesis in Xenopus laevis. Chromosoma, 73, 3744.
  • 112
    Thompson, J.N. (1999). The evolution of species interactions. Science, 284, 21162118.DOI: 10.1126/science.284.5423.2116
  • 113
    Tilman, D. (1982). Resource Competition and Community Structure. Princeton University Press, Princeton, New Jersey.
  • 114
    Urabe, J. (1993). N and P cycling coupled by grazers’ activities: food quality and nutrient release by zooplankton. Ecology, 74, 23372350.
  • 115
    Urabe, J., Clasen, J. & Sterner, R.W. (1997). Phosphorus-limi-tation of Daphnia: is it real? Limnol. Oceanogr., 42, 14361443.
  • 116
    Urabe, J., Nakanishi, M. & Kawabata, K. (1995). Contribution of metazoan plankton to the cycling of N and P in Lake Biwa. Limnol. Oceanogr., 40, 232241.
  • 117
    Urabe, J. & Sterner, R.W. (1996). Regulation of herbivore growth by the balance of light and nutrients. Proc. Natl. Acad. Sci., 93, 84658469.
  • 118
    Vadstein, O., Olsen, Y., Reinertsen, H. & Jensen, A. (1993). The role of planktonic bacteria in phosphorus cycling in lakes – sink and link. Limnol. Oceanogr., 38, 15391543.
  • 119
    Vanni, M.J. & Layne, C.D. (1997). Nutrient recycling and herbivory as mechanisms in the ‘top-down’ effect of fish on algae in lakes. Ecology, 78, 2140.
  • 120
    Vitousek, P. (1982). Nutrient cycling and nutrient use efficiency. Am. Nat., 119, 553572.
  • 121
    Vogel, S. (1998). Academically correct biological science. Am. Sci., 86, 504506.
  • 122
    Vogt, V.M. & Braun, R. (1976). Structure of ribosomal DNA in Physarum polycephalum. J. Mol. Biol., 106, 567587.
  • 123
    Vogt, V.M & Braun, R. (1977). The replication of ribosomal DNA in Physarum polycephalum. Eur. J. Biochem., 80, 557587.
  • 124
    Wagner, M, Durbin, E. & Buckley, L. (1998). RNA:DNA ratios as indicators of nutritional condition in the copepod Calanus finmarchicus. March Ecol. Prog. Ser., 162, 173181.
  • 125
    Welker, D.L, Hirth, K.P. & Williams, K.L. (1985). Inheritance of extrachromosomal ribosomal DNA during the asexual life cycle of Dictyostelium discoideum: examination by use of DNA polymorphisms. Mol. Cell. Biol., 5, 273280.
  • 126
    White, T.C.R. (1993). The Inadequate Environment: Nitrogen and the Abundance of Animals. Springer-Verlag, New York, NY, USA.
  • 127
    Williams, K.L. (1986). Extrachromosomal DNA elements in the nucleus of Dictyostelium discoideum. In: Extrachromosomal Elements in Lower Eukaryotes. (ed. Wickner, R.B.). Plenum Press, New York, NY, USA.