SEARCH

SEARCH BY CITATION

Keywords:

  • carbon;
  • global change;
  • scaling;
  • stoichiometric flexibility;
  • terrestrial ecosystems

Summary

  1. Top of page
  2. Summary
  3. Stoichiometric flexibility across scales
  4. Stoichiometric flexibility and the structuring of terrestrial ecosystems
  5. Stoichiometric flexibility and terrestrial responses to global change
  6. Synthesis
  7. Acknowledgements
  8. References

Ecosystems across the biosphere are subject to rapid changes in elemental balance and climatic regimes. A major force structuring ecological responses to these perturbations lies in the stoichiometric flexibility of systems – the ability to adjust their elemental balance whilst maintaining function. The potential for stoichiometric flexibility underscores the utility of the application of a framework highlighting the constraints and consequences of elemental mass balance and energy cycling in biological systems to address global change phenomena. Improvement in the modeling of ecological responses to disturbance requires the consideration of the stoichiometric flexibility of systems within and across relevant scales. Although a multitude of global change studies over various spatial and temporal scales exist, the explicit consideration of the role played by stoichiometric flexibility in linking micro-scale to macro-scale biogeochemical processes in terrestrial ecosystems remains relatively unexplored. Focusing on terrestrial systems under change, we discuss the mechanisms by which stoichiometric flexibility might be expressed and connected from organisms to ecosystems. We suggest that the transition from the expression of stoichiometric flexibility within individuals to the community and ecosystem scales is a key mechanism regulating the extent to which environmental perturbation may alter ecosystem carbon and nutrient cycling dynamics.


Stoichiometric flexibility across scales

  1. Top of page
  2. Summary
  3. Stoichiometric flexibility across scales
  4. Stoichiometric flexibility and the structuring of terrestrial ecosystems
  5. Stoichiometric flexibility and terrestrial responses to global change
  6. Synthesis
  7. Acknowledgements
  8. References

Stoichiometric relationships underpin the structuring of biological systems. These relationships differ systematically from molecules to ecosystems, reflecting the variation in biological functions and biochemical limitations (Sterner & Elser, 2002). Because all organisms must meet their basic metabolic requirements, biotic interactions are both regulated by and also feed back to their environment’s resource availability (Elser et al., 1996). Therefore, a system’s response to environmental change, from gene expression to macro-scale processes, will ultimately be constrained by its ability to adjust to shifting elemental balances — its stoichiometric flexibility.

Anthropogenic impacts on the Earth’s climate, energy and element cycles (Table 1) include global-scale alterations in nitrogen (N) and phosphorus (P) cycling: more than doubling the available N inputs into the biosphere via fertilizer manufacture and redistributing mined P across the Earth (Falkowski et al., 2000). As N and P commonly limit primary producers (Elser et al., 2010; Harpole et al., 2011; Marklein & Houlton, 2012), such massive perturbations are expected to have stoichiometric consequences across food webs. The rapid shift in the bioavailability of essential elements, coupled with increasing atmospheric CO2 and warming (Raupach et al., 2007), can alter the stoichiometric relationships of biological systems at multiple scales. For example, because rapidly growing organisms require the coupled use of N- and P-rich resources to meet high demands for RNA and protein, nutrient enrichment may select for species with high growth rates, ultimately shifting the community composition and, potentially, ecosystem function (Smith, 1983; Chapin et al., 1986; Mack et al., 2004; Marklein & Houlton, 2012).

Table 1.   Anthropogenic perturbations to global chemical cycles based on mid 1990s data. Adapted from Falkowski et al. (2000)
ElementForm of changeProcesses (approximate contribution to total flux in parentheses)Anthropogenically-driven % change
CCO2 release to atmosphere from organic matter oxidationTerrestrial respiration and organic matter decay as CO2 (88%); fossil fuel combustion and land-use (12%) 13
NConversion to biologically-available forms from N2Natural biological fixation (48%); fixation from agricultural production, fossil fuel production, and fertilizer production (52%)108
PRedistribution of biologically-available forms through miningChemical weathering (20%); mining (80%)400

The increase in anthropogenically caused environmental perturbations has provoked interest in understanding how stoichiometric relationships control responses to disturbances. Organisms generally have conservative stoichiometries relative to the elemental heterogeneity of their environment (Moe et al., 2005), such that the acquisition of carbon (C), N and P constrains both the individual and community response to perturbation. Biological systems may demonstrate strict homeostasis, in which element ratios are fixed (Sterner & Elser, 2002). From the organismal to community state, strict homeostasis will drive the most limiting resource (in terms of supply rate, although not necessarily concentration) to regulate productivity (Rastetter & Shaver, 1992). Alternatively, systems might be stoichiometrically plastic, shifting their elemental balance in response to perturbation (Sterner & Elser, 2002). At the organismal level, this can be manifested by an adjustment in growth form or tissue allocation patterns. For example, temperate forest hardwoods have been shown to increase their relative investment to woody biomass with greater N availability (Melillo et al., 2011). At larger scales, changes in community composition and trophic interactions can alter the stoichiometric composition of an ecosystem. This phenomenon can occur with succession or invasions, and may be driven by abiotic perturbations (e.g. nutrient or warming-driven shrub expansion into sedge-dominated tussock tundra) (Chapin et al., 1986; Mack et al., 2000; Walker et al., 2006).

The expression of stoichiometric plasticity will be regulated both by the nature of the perturbation and the costs associated with change. At the organismal level, primary producers tend to be more stoichiometrically flexible than their consumers (Hessen et al., 2004). For example, plants can shift tissue allocation towards more woody biomass (molar ratio C : N : P ≈ 7900 : 25 : 1; Vitousek et al., 1988) than leaf tissue (C : N : P ≈ 1212 : 28 : 1; McGroddy et al., 2004). Plant stoichiometric flexibility also stems from their nutrient resorption capacity, with senescing leaves resorbing > 60% of leaf N and P (Vergutz et al., 2012), increasing litter C : X relative to green foliage (litter C : N : P = 3007 : 45 : 1) (McGroddy et al., 2004).

The stoichiometric flexibility of terrestrial plants reflects their physiological capacity to accumulate and store elements in excess of their immediate needs, to adjust allocation towards the synthesis of more C- or nutrient-rich compounds, and to alter growth form towards defense, storage and structural tissues. By contrast, consumers tend to have more fixed tissue partitioning (Anderson et al., 2005). As consumers are less stoichiometrically plastic because of greater physiological constraints on allocation, stoichiometric shifts in primary producers can regulate the composition and behavior of herbivore and decomposer communities, and the ecological processes they carry out (Hessen et al., 2004; Sardans et al., 2011).

Ecosystems may therefore be stoichiometrically flexible by two connected mechanisms. First, by varying stoichiometry within individuals: organisms can alter allometric patterns and tissue chemistry to adjust their overall stoichiometry (Sterner & Elser, 2002). Second, by shifting dominance among organisms that differ in their average stoichiometry: the composition of key guilds and their functions can change (e.g. altered consumer pressures, competitive interactions amongst guilds or trophic group, invasion potential; Moe et al., 2005).

Variation in the C : N : P range of organisms and their biological components is generally greater than that in the systems that they build (Table 2). Although stoichiometry may vary significantly within or amongst organisms and across trophic groups, the chemically coupled feedbacks between primary producers, heterotrophs and their abiotic environment suggest that biota in terrestrial ecosystems will tend towards relatively convergent C : N : P ratios when moving from local to global scales (Elser et al., 2010). These patterns emerge when comparing variation in microbial and phytoplankton C : N : P from the macromolecules building individuals to communities (Goldman et al., 1979; Geider & La Roche, 2002; Hall et al., 2011), and to global scales (Cleveland & Liptzin, 2007), and in plant C : N : P relationships from biomes to the global scale (Vitousek et al., 1988; Reich & Oleksyn, 2004; McGroddy et al., 2004). To accurately quantify the impacts of stoichiometric flexibility (or lack thereof) on ecosystem processes, researchers must identify where and to what extent the potential for stoichiometric change exists across biologically relevant scales (Fig. 1).

Table 2.   Example of stoichiometeric ranges for C : N, C : P and N : P (expressed in atomic molar ratios) for different biological states, increasing in scale from sub-cellular components to single celled planktonic organisms, and from terrestrial plant tissues to whole forest biomass. Note that these ranges represent potential molar ratios, but not the concentration of the component (e.g. percent of a cell that is DNA) contained within its larger biological state (e.g. a cell)
Biological stateC : NC : PN : PSource
Common subcellular components (e.g. nucleotides, RNA, DNA, amino acids, fatty acids, carbohydrates, chitin, chlorophyll) c. 0.5 (e.g. cystine) to > 80 (e.g. phosphoglycerides) to ∞ (no N; e.g. carbohydrates, waxes, sterols, fatty acids)< 5 (e.g. DNA, RNA) to > 15 (e.g. phosphoglycerides) to ∞ (no P; e.g. nucleotides, waxes, chitin, chlorophyll)< 0.2 (e.g. phosphoglycerides) to < 2 (e.g. RNA) to ∞ (no P) Geider & La Rouche (2002)
Marine phytoplankton (range reflects decreasing P resource supply and growth rate in P-limited culture of Monochrysis lutheri)7.1–11.3106–130015–115 Goldman et al. (1979)
Forest components: subalpine to tropical forest biomes (foliage, woody tissue, roots)26 (foliage, fertile site) to 505 (woody tissue)800 (foliage, fertile site) to 12197 (woody tissue)11 (root) to 57 (foliage, infertile sites) Vitousek et al. (1988)
Total forest biomass134–2993043–624117–25 
image

Figure 1. Schematic representation of the ways in which stoichiometric flexibility may be expressed in ecosystems and in their component parts (boxes). Each type of stoichiometric flexibility can be directly or indirectly influenced by the other states. Similarly, drivers (ovals) may influence stoichiometric relationships at multiple scales simultaneously.

Download figure to PowerPoint

Ecosystem processes, such as C or N storage, are emergent properties that result from interactions of organisms with the abiotic environment. Organisms may themselves reflect stoichiometric variation across scales, both through shifts in the physiological state of individuals (e.g. increasing woody biomass production relative to other tissues) and/or the biotic structuring of communities (e.g. shrub invasion into grasslands). Therefore, both within and across scales, the expression of potential stoichiometric range will vary with the biological composition of systems. Recognizing that ecological processes are not necessarily the direct sum of their parts, we will explore how the plasticity of macro-scale ecosystem processes is regulated by the stoichiometric flexibility of the organisms that generate them. A consideration of how the cross-scale structuring of stoichiometric relationships influences responses to perturbation spurs several key questions:

  • How does the expression of stoichiometric flexibility at one scale influence the expression of stoichiometric flexibility among linked systems?
  • Is there a correlation between the biological state of either individuals or communities (e.g. physiological and ontogenetic condition, successional status) and susceptibility to stoichiometric perturbation?
  • What mechanisms regulate whether a perturbed system returns to its initial stoichiometric condition, or shifts towards an alternative stable state (Beisner et al., 2003)?
  • What are the consequences of these responses for macro-scale biogeochemical processes, such as terrestrial C sequestration potential?

An understanding of how the stoichiometric flexibility of organisms within ecosystems influences the system’s overall stoichiometric plasticity, and how this varies across systems, is a key component to the accurate prediction of ecological responses to perturbation using a stoichiometric framework. These questions, however, are more readily posed than answered, partly because studies often use different methodologies (Mikkelsen et al., 2008), and partly because they rarely directly address stoichiometric changes among interacting ecosystem components in response to perturbation (Moe et al., 2005). This lack of focus on stoichiometric flexibility reflects both the wide array of conditions under which elemental plasticity can occur in biological systems, and the lack of a coherent framework under which stoichiometric flexibility is identified.

Although a definitive synthesis on the role of stoichiometric flexibility in response to global change may be impossible at present, we can identify potential insights and limits of the application of this theoretical framework for the exploration of the responses of terrestrial systems to global change stressors. We suggest that integrating field measurements into coupled-element models that overtly address stoichiometric flexibility might better inform projections of ecosystem dynamics, relative to those derived using short-term, small-scale and single-factor manipulation studies.

Stoichiometric flexibility and the structuring of terrestrial ecosystems

  1. Top of page
  2. Summary
  3. Stoichiometric flexibility across scales
  4. Stoichiometric flexibility and the structuring of terrestrial ecosystems
  5. Stoichiometric flexibility and terrestrial responses to global change
  6. Synthesis
  7. Acknowledgements
  8. References

Differences in the demand and competitive ability of plants for elements within heterogeneous soil environments are key forces structuring terrestrial communities. This concept stems from the 19th century observations of Sprengel and Liebig that mismatches in the supply of and demand for nutrients drive resource limitation and regulate the growth of individual plants (van der Ploeg et al., 1999). Scaling up, cross-ecosystem comparisons of C : N : P ratios should reflect selection for the efficient use of the most limiting nutrient. For example, a global comparison of forest foliar C : N : P demonstrates that the abundance of P relative to C and N correlates with the variation in P availability at the biome level, consistent with selection for efficient foliar P use (McGroddy et al., 2004).

Such cross-scale stoichiometric relationships in terrestrial systems are challenging to identify because of their patchy resource distributions and broad spectrum of autotrophic growth forms (Cleveland & Liptzin, 2007). In general, the wide range of C : element ratios among plant tissues is driven by the C-rich compounds needed for structural support and defensive chemicals. For example, chemically recalcitrant lignocellulose woody tissues contain only 0.01–0.1% N by weight, as opposed to the typical 1–5% N of herbaceous tissues (Cowling & Merrill, 1966). As a result, heterotrophs face an enormous diversity of plant-derived organic compounds that differ in their underlying elemental ratios, driving a substantial range of heterotrophic substrate use efficiency (SUE; the fraction of consumed molecules converted into biomass; Sterner & Elser, 2002).

Plant stoichiometry thus creates the ‘boundary conditions’ for heterotrophic productivity. Organisms cannot produce more biomass than allowed by the supply rate of their most limiting resource, but the specific chemistry of plant compounds controls where, within these stoichiometric boundaries, consumer groups operate. The efficiency with which heterotrophs can use plant chemicals varies widely, with SUE approaching 70% for bacteria using plant sugars (Sugai & Schimel, 1993) vs 0% for most animals eating lignocellulose. In the transfer of energy from plants to their consumers, C : N : P ratios shrink and the stoichiometric ranges contract (Sterner & Elser, 2002). Therefore, heterotrophs characteristically live in a C-rich, nutrient-poor world relative to their requirements. This elemental mismatch between primary producers and their consumers drives an imbalance between resource supply and demand that limits an ecosystem’s rate of C and nutrient transfer among trophic levels (Sterner & Elser, 2002).

Within the heterogeneous soil environment, as detritus C : N approaches that of its decomposers, microbes shift from nutrient immobilization to mineralization, thereby regulating plant-available nutrients (Manzoni et al., 2008). Regardless of the absolute decomposition rate, decomposers retain or release nutrients based on their elemental needs relative to resource supply (Manzoni et al., 2008). Although the stoichiometric regulation of decomposers operating in a coupled feedback with plants over relatively small spatial and temporal dimensions shapes ecosystem processes and structures at the community level (Chapin et al., 1986), terrestrial stoichiometries tend to be conserved relative to local environmental heterogeneity over large scales (e.g. the cross-biome variation of the C : N, C : P and N : P tree foliar and soil microbe nutrient ratios is lower or equal to the within-biome level variation; McGroddy et al., 2004; Cleveland & Liptzin, 2007).

Supporting these Redfield-like patterns of terrestrial biota are observations that, although soil microbial biomass C, N and P concentrations vary globally over several orders of magnitude (5–2500 μmol kg−1 soil, 1–178 μmol kg−1 soil and 0.1–14 μmol kg−1 soil, respectively), microbial biomass C : N : P ratios are conserved at a global scale (C : N average = 8.6 ± 0.3, N : P average = 6.9 ± 0.4; Cleveland & Liptzin, 2007). This result parallels the findings of McGroddy et al. (2004) that, despite biome-level differences trending towards greater foliage N : P with decreasing latitude (reflecting that P is a primary limiting nutrient in older tropical soils and N is the dominant limiting nutrient in younger temperate and high-latitude soils; Reich & Oleksyn, 2004), forest leaf C : N : P ratios are broadly constrained worldwide (C : N average = 43.6 ± 3.5; N : P = 27.8 ± 1.4). Further, although total soil C, N and P content varies globally by orders of magnitude (e.g. total soil C ranges nearly 40-fold, from 1108 to 39 083 mmol kg−1), soil C : N : P ratios are markedly constrained at the global scale (log-normal molar C : N range from 2 to 30, N : P range from 1 to 77; Cleveland & Liptzin, 2007), suggesting a tight stoichiometric coupling between decomposers and their soil environment.

Changes in nutrient availability or litter chemistry may alter microbial dynamics, driving stoichiometric feedbacks between primary producers, their consumers and decomposers within ecosystems and at local scales. For example, although soil microbial biomass C and total soil C are positively correlated over large scales, microbial N : P appears to follow relatively strict homeostatic control: it does not vary with latitude nor does it correlate with soil N : P supply ratios. This pattern suggests that sufficient relative N and P availability is necessary to maintain microbial N : P stoichiometry, with greater N and P supporting greater microbial C (Cleveland & Liptzin, 2007).

The observation of relatively strict microbial N : P homeostasis correlates with the observation that P often appears to limit microbial biomass and activity in low-latitude, P-poor ecosystems (Cleveland et al., 2006; Townsend et al., 2007), whereas N seems to limit soil microbes in high-latitude, N-poor organic soil systems (Lavoie et al., 2011; Sistla et al.. 2012). In both cases, in situ fertilization with the limiting resource stimulates microbial activity, amplifying soil decomposition (Mack et al., 2004; Cleveland & Townsend, 2006). Intriguingly, fertilization significantly stimulates soil C losses and increases plant C gain (by facilitating shrub expansion), whilst driving a net C and N loss in the Arctic system by accelerating decomposition (Mack et al., 2004). This phenomenon highlights that, in systems in which the same nutrient stoichiometrically constrains both plant and microbial productivity, alleviation of the limiting nutrient may drive divergent patterns in plant and soil C storage – and, potentially, a net loss of the added element. Therefore, depending on the strength of the stoichiometric linkages among a system’s components, including their degree of stoichiometric homeostasis and nutrient limitation, the expression of stoichiometric flexibility in response to environmental stressors can significantly alter – or help to maintain – macro-scale states and processes.

Stoichiometric flexibility and terrestrial responses to global change

  1. Top of page
  2. Summary
  3. Stoichiometric flexibility across scales
  4. Stoichiometric flexibility and the structuring of terrestrial ecosystems
  5. Stoichiometric flexibility and terrestrial responses to global change
  6. Synthesis
  7. Acknowledgements
  8. References

Despite several decades of global change research, the impacts of climate warming, elevated atmospheric CO2 (eCO2) and altered nutrient availability on terrestrial C dynamics have remained surprisingly difficult to predict, at least in part reflecting the complexity of the coupling between C and nutrient cycles (Rastetter et al., 1997). Stoichiometric responses to perturbation are intrinsically tied to altered resource limitation. Because these disturbances impact nested biological systems, approaching global change questions with a stoichiometric flexibility perspective may provide deeper insights into the feedbacks between environmental perturbation and ecosystem responses over time.

Varying from sub-cellular investigations to ecosystem-level manipulations, numerous studies have shown that warming, eCO2, N and P fertilization can drive stoichiometric change (Elser et al., 2010). Although global change phenomena inherently involve coupled shifts in resource availability and climate, global change experiments often focus on single drivers. While imperfect, such experiments help to collapse the complexity in identifying the potential range of a system’s stoichiometric flexibility, including the stoichiometric feedbacks, thresholds and the mechanisms underlying them.

Changes in the chemical composition of plants and/or decomposers will inevitably have consequences for the other trophic levels to which they are biogeochemically coupled, scaling up to macro-processes such as ecosystem C storage. Thus, global change drivers can affect both directly and indirectly each of the connected axes of nutrient cycling, primary productivity and community structure (Elser et al., 2010). Because stoichiometric flexibility will vary across ecosystem components, the identification of stoichiometric constraints and linkages among components is critical to projecting the responses of terrestrial systems to environmental change.

A major challenge in the application of a stoichiometric flexibility perspective to global change questions is scaling between stoichiometric responses measured over different spatial and temporal scales. A classic example of this phenomenon lies in the conflicting responses to eCO2 moving from the leaf to the ecosystem scale. At the molecular level, eCO2 stimulates photosynthesis by increasing the carboxylation rate of N-rich Rubisco, whilst competitively inhibiting photooxidation (Drake et al., 1997). Scaling to the leaf level, plants regulate the greater N demand by increasing leaf-level C : N, partly by down-regulating Rubisco synthesis. Although this limits the eCO2-driven increase in photosynthesis, leaf-level net C gain generally remains elevated. Therefore, eCO2 might be expected to scale up to increase net primary productivity (NPP) and potentially, net ecosystem C storage capacity. However, eCO2 response patterns vary at the ecosystem level, ranging from net C gain to no net change (Ainsworth & Long, 2005; Norby & Zak, 2011).

Variation in net C storage under eCO2 therefore tends to increase with scale, with predictable cellular-level C gain not necessarily translating to ecosystem C gain. Biological differences in the stoichiometric regulation of response to eCO2 when scaling from cells to ecosystems creates dissonance in predicting the integrative macro-scale process of net C storage based on leaf-level responses. This phenomenon reflects the fact that the sequestration of more ecosystem C requires plants and soils to be able to store more C, and that the system must have the nutrients necessary for plants to make molecules that can be sequestrated (Rastetter et al., 1992). Therefore, the identification of the key mechanisms regulating stoichiometric flexibility, with a focus on nutrient availability and allocation patterns, will allow researchers to better model plausible macro-scale consequences of global change phenomena. With this perspective, we consider terrestrial responses to global change perturbations, highlighting mechanisms that limit the translation of stoichiometric flexibility across biological states.

Organismal-level stoichiometric flexibility

A common plant response to both eCO2 and warming is a faster growth rate. For example, young trees with expanding canopies and exponential growth often have greater growth responses to eCO2 than older stands, including increasing leaf area and NPP (Hättenschwiler et al., 1997; Norby et al., 2001). Because rapidly growing organisms have increased anabolic rates, and thus require more nutrients per unit biomass C than slower growing organisms, faster growth is stoichiometrically regulated by increased N and P demands relative to C (Hall et al., 2011; Harpole et al., 2011; Marklein & Houlton, 2012). Linking ontogeny and environmental stressors to plant stoichiometric flexibility at the metabolomic level, Rivas-Ubach et al. (2012) demonstrated that the stimulation of growth decreases leaf-level C : nutrient and N : P ratios, whilst increasing primary metabolite content.

Nitrogen, in particular, has long been noted to be a stoichiometric regulator of the potential for increased NPP gain with eCO2 or warming, because the redistribution of N from relatively low C : N soil pools to high C : N plant tissues can increase C sequestration. CO2 fertilization can drive increased woody growth in established individuals (Hamilton et al., 2002; Finzi et al., 2002) and promote increased woody plant dominance (Souza et al., 2010). The sequestration of N in high C : N recalcitrant tissues and soil organic matter (SOM) may reduce plant-available N by retarding decomposer activity over time, however, and ultimately reduce plant growth (Luo et al., 2006). As such, if the production and use of photosynthate is nutrient limited, the effect of eCO2 (Hu et al., 2001; de Graaff et al., 2006) or warming (Hobbie et al., 2001; Rustad et al., 2001; Melillo et al., 2011) on plant growth will be constrained.

There is evidence that eCO2-driven N limitation may occur in both forests and perennial grasslands (Hu et al., 2001; Reich et al., 2006; Norby et al., 2010; Garten et al., 2011), including a decline in the stimulation of NPP coupled with increasing plant N deficiency (Norby et al., 2010) and greater microbial N immobilization (Hu et al., 2001) in experimental systems. Plants may initially compensate for greater N demand by expanding their exploration of the soil through increased allocation to roots, producing greater fine root biomass and rooting more deeply (Luo et al., 2006; Iversen et al., 2008). As plants expand their root systems, however, more N is committed to long-lived woody structures that decompose slowly and immobilize N, reducing N availability over time. The increasing accumulation of recalcitrant, high C : N litter has been hypothesized to inhibit decomposer activity, thus limiting the ability of plants to respond to eCO2 (Luo et al., 2006). Therefore, although the development of N limitation under eCO2 will be controlled by plant–soil–microbe feedbacks, alleviating this limitation will depend on a net increase in N at the ecosystem-scale (Rastetter et al., 1997).

In contrast with eCO2-driven N limitation, warming can act as a positive feedback that promotes woody encroachment in nutrient-poor systems by stimulating decomposer activity and N mineralization (Sturm et al., 2008; Melillo et al., 2011). For example, a multi-year warming experiment in an N-limited temperate forest enhanced N mineralization sufficiently to support C gain in woody biomass, nearly compensating for belowground soil C loss (Melillo et al., 2011). Intriguingly, although soil warming experiments in a variety of ecosystems have driven short-term increases in soil respiration, the response tends to decline over several years (Rustad et al., 2001; Allison et al., 2010; Melillo et al., 2011). This acclimation may be driven by a decline in microbial C use efficiency (CUE; the ratio of biomass synthesis to C uptake) which governs biomass C : X elemental relationships in response to altered environmental or physiological conditions (Allison et al., 2010). In the short term, reduced CUE can be caused directly by thermal stress and the depletion of labile, high-SUE compounds, or indirectly via longer term plant–microbe feedbacks that alter microbial community composition (Allison et al., 2010). Therefore, warming may drive decomposer nutrient-limitation over time, acting as a negative feedback to the initial acceleration of decomposition and ultimately, plant growth.

In extremely nutrient-limited systems, such as Arctic and boreal ecosystems, N (and to a lesser extent available P) most commonly limits NPP (Shaver & Chapin, 1986; Hobbie et al., 2001). Over the decadal time frame, woody plant growth in Arctic systems is strongly responsive to experimental air warming, N and P fertilization, and ongoing climate warming (Mack et al., 2004; Sturm et al., 2008; Myers-Smith et al., 2011). Greater N availability, in particular (through both fertilization and indirectly via warming), stimulates plant N sequestration (Natali et al., 2012), increasing woody biomass production and dominance in tundra systems (Rundqvist et al., 2011; Myers-Smith et al., 2011).

The acceleration of woody biomass synthesis with greater N uptake is tied to the ability of certain shrub species to shift their allocation patterns towards structural branch production (Bret-Harte et al., 2002). Warming also promotes directly woody expansion over time by lengthening the growing season, whilst stimulating shrub growth rate and fine root production, increasing their ability to both acquire N and capture C used in secondary stem biomass production (Hobbie & Chapin, 1998; Bret-Harte et al., 2002; Walker et al., 2006; Sullivan et al., 2007). Therefore, if allocation to woody biomass increases at the ecosystem level with warming, the redistribution of a relatively small proportion of soil N can significantly promote long-term C storage (McKane et al., 1997; Melillo et al., 2011).

Community-level stoichiometric flexibility

Warming, eCO2 and fertilization can independently drive stoichiometric change at the organismal level, potentially altering macro-scale processes. At the community level, plant stoichiometric flexibility may be expressed through shifts in stand establishment and composition towards woody dominance (Mack et al., 2004; Souza et al., 2010; Melillo et al., 2011). Conversely, fertilization may facilitate a positive feedback between rapidly growing plants and soil nutrient availability (Chapin et al., 1986). For example, in nutrient-poor ecosystems, invasion by fast-growing (high nutrient-demand) species may drive a positive feedback through a combination of less conservative plant nutrient use efficiency, increased deposition of nutrient-rich litter, and faster SOM turnover (Hobbie, 1992; Allison & Vitousek, 2004). In contrast with greater C sequestration due to N mobilization allocated towards producing relative high C : N tissues like wood, such a trajectory would probably drive a more rapidly cycling, lower C : nutrient community (Hobbie, 1992) potentially reducing net C storage.

Relatively small-scale shifts among interacting plant and microbial communities can also feed back through changes in both resource inputs and demand to regulate macro-scale nutrient cycling dynamics. For instance, the invasion of Morella faya (formerly Myrica faya) with its N-fixing root symbionts (Frankia spp.) in N-poor volcanic Hawaiian soils stimulated N mineralization rates (increasing the supply of available N by more than four-fold), litterfall production and soil organic C stocks in densely colonized areas (Vitousek & Walker, 1989; Asner et al., 2009). Paralleling this greater N availability, N oxide (N2O and NO) emissions increased by 16-fold (or 296 ± 1.5 kg N yr−1) under wet conditions in densely invaded areas (Hall & Asner, 2007). Invasion by M. faya also decreased P availability through the immobilization of P during the decomposition of its litter (Vitousek & Walker, 1989), and negatively affected the regeneration of the dominant native tree (Walker & Vitousek, 1991). Notably, despite increasing N availability and N emissions across a variety of Hawaiian ecosystems, M. faya invasion did not increase aboveground biomass at the landscape-scale, reflecting that other factors (e.g. losses of native understory species and low water availability) ultimately constrain the system’s NPP (Asner et al., 2009).

The alteration of stoichiometrically governed ecosystem feedbacks may thus further alter macro-scale biogeochemical fluxes by affecting plant and microbe community structure, including decomposer food webs (Moore et al., 2005). Although individual soil organism populations might be expected to express a range of stoichiometric flexibility in response to environmental perturbation (Hall et al., 2011), in situ stoichiometric studies of soil microbes are typically conducted at a higher community level of organization (Cleveland & Liptzin, 2007) and through the characterization of the processes which they regulate (e.g. soil respiration, extracellular enzyme-mediated decomposition).

Extracellular enzymes (which are produced primarily by microbes, although some are synthesized by plants) make nutrients and C available for uptake by catalyzing the breakdown of polymeric SOM (Allison et al., 2010). The acquisition of nutrients thus requires an investment in N-rich extracellular enzymes, such that nutrient uptake is inherently coupled to nutrient loss (Marklein & Houlton, 2012; Mooshammer et al., 2012). Organisms have developed strategies to minimize this system’s inherent stoichiometric tradeoff in response to N or P limitation, which may feed back to ecosystem-scale processes. For example, a recent meta-analysis by Marklein & Houlton (2012) demonstrated that P-mineralizing phosphatase enzyme activity (from both plant roots and bulk soil) is increased by N fertilization in P-limited systems, whereas P fertilization strongly suppresses phosphatase activity. Further, the synthesis of extracellular enzymes appear to be regulated stoichiometrically, as the activity of enzymes targeting more P-, N- or C-rich compounds correlates with microbial demand (Sinsabaugh et al., 2008).

Extracellular enzyme activity therefore links SOM decomposition with microbial community structure, driving a feedback between environmental conditions, plant and decomposer community dynamics. Changing soil conditions may also drive the microbial community towards a more fungal-like (higher microbial biomass C : N ratio) or more bacterial-like (lower C : N ratio) composition (Strickland & Rousk, 2010), which can significantly alter C and nutrient cycling dynamics. Greater fungal to bacterial dominance is often associated with lower N availability and increased oxidative enzyme activities, which tend to mediate the decomposition of recalcitrant soil compounds. By contrast, higher N availability tends to be correlated with increased hydrolytic enzyme activities, which are associated with the degradation of more labile compounds (Sinsabaugh et al., 2008; Sinsabaugh, 2010). For example, in N-rich tropical soils, N fertilization increases hydrolytic enzyme activity and accelerates the decomposition of the labile soil C pool, whilst concurrently decreasing oxidative enzyme activity and the decomposition of the more recalcitrant C pool (Cusack et al., 2010).

If litter lability increases with invasion, warming or nutrient addition (Weintraub & Schimel, 2003; Allison & Vitousek, 2004; Sturm et al., 2008) and decreases SOM C : N, the soil faunal composition may shift towards a more rapidly cycling, bacterial consumer-based community at the expense of the fungal community and their consumers. By contrast, if food web perturbations increase more recalcitrant, C-rich SOM litter inputs, such as lignified tissues (Weintraub & Schimel, 2005), a slower cycling, fungal-dominated community may be favored (Moore et al., 2005). Fungal-based food webs may be more resistant (but less resilient) than bacterial-dominated communities to drought and similar climate perturbations because of these differences in their life history strategies (de Vries et al., 2012). Alternatively, fungal-based food webs may be less resistant than bacterial-dominated communities to physical stressors, such as soil habitat fragmentation driven by land use change (Hedlund et al., 2004). Therefore, shifting between bacterial and fungal dominance can have significant ramifications for both ecosystem nutrient cycling and subsequent responses to perturbation.

Numerous studies have suggested the potential for these types of feedbacks between aboveground and belowground communities in response to perturbation to further alter ecosystem stoichiometric relationships. Under both warming and fertilization, ectomycorrhizal biomass increased in a tundra ecosystem because these symbionts tracked the rise in shrub abundance, creating a positive feedback that further facilitated shrub growth (Clemmensen et al., 2006; Deslippe & Simard, 2011). Similarly, eCO2 can stimulate C inputs into the soil whilst reducing N availability, which may promote soil fungal abundance (Klamer et al., 2002; Janus et al., 2005; Lipson et al., 2005; Carney et al., 2007). For example, Carney et al. (2007) reported that eCO2-driven increases in plant-derived soil inputs promoted the relative abundance of fungi and stimulated oxidative enzyme activity, offsetting nearly 52% (442 g C m−2) of the additional C gained through increased NPP by a scrub-oak ecosystem.

Trophic interactions and disturbance

Complementing plant–decomposer stoichiometric feedbacks, plant anabolism and allocation of C and nutrients in response to perturbation may further alter the trajectory of net C storage by changing trophic interactions which can cascade through food webs. For example, eCO2 can lower the quality of plant tissue (widening C : nutrient ratios), increasing the amount of tissue insect herbivores must eat to meet their metabolic demands (Stiling et al., 1999). Similarly, chronic N deposition has been found to widen foliar N : P ratios and to intensify P limitation in insect herbivores (Elser et al., 2000). Notably, although eCO2 tends to reduce insect herbivore performance, these effects can be mitigated in combination with greater temperature by stimulating herbivore browsing activity, whilst increasing the quality of plant leaf tissue, relative to eCO2 alone (Zvereva & Kozlov, 2006). Stoichiometric feedbacks can also occur between primary producers and megafauna. In Arctic systems, for instance, the effects of warming on increased shrub production can be offset by greater muskoxen and caribou herbivory (Post & Pedersen, 2008; Olofsson et al., 2009).

At the biome scale, plant community change may feed back with large-scale disturbance regimes. For example, tundra fires appear to have been more common under ancient birch-dominated conditions, because woody biomass created an abundance of fine fuels (Higuera et al., 2008). Fire may drive significant ecosystem N and C loss because of their relatively low volatilization temperatures, whilst converting aboveground P into available mineral forms through ash deposition (Boerner, 1982). In tallgrass prairie soils, for instance, an experimental fire simulation promoted cyanobacteria N fixation as the available N relative to available P (aN : P) declined. This study yielded a maximal estimate of 21 kg N-fixed ha−1 yr−1 following fire lowering of aN : P (Eisele et al., 1989); a fraction of which would offset a significant portion of the 18 kg N ha−1 yr−1 estimated to be lost via fire in ungrazed prairie systems (Hobbs et al., 1991). Trophic cascades and disturbance feedbacks to stoichiometric change can thus ultimately regulate C accumulation and other macro-scale ecological processes, regardless of a system’s potential stoichiometric flexibility.

Synthesis

  1. Top of page
  2. Summary
  3. Stoichiometric flexibility across scales
  4. Stoichiometric flexibility and the structuring of terrestrial ecosystems
  5. Stoichiometric flexibility and terrestrial responses to global change
  6. Synthesis
  7. Acknowledgements
  8. References

Biological systems have long been recognized to use essential elements at characteristic ratios that differ systematically among molecules, tissues and organisms (Sterner & Elser, 2002). The flexibility of these relationships in response to global change stressors, however, remains an area that is ripe for exploration. A major challenge faced in the understanding of long-term ecological responses to environmental change is that outcomes based on short-term experimental manipulations may not accurately reflect long-term trajectories. The application of a stoichiometric approach to the evaluation of such studies might help to better constrain these projections by highlighting stoichiometric thresholds in which observed changes over the short term can realistically be expected to significantly influence macro-scale processes over time.

A consideration of the range of stoichiometric responses to perturbation relative to resource availability, ontological stage or community composition provokes additional questions.

  • How much stoichiometric flexibility do systems have to maintain macro-scale processes (e.g. C sequestration) without undergoing a shift to a new state (e.g. a transition from grassland to shrubland)?
  • How is the potential range of stoichiometric flexibility related to the relative nutrient richness of a system?

These uncertainties highlight the fact that the potential for lagged responses, areas for local stability and thresholds to stoichiometric change must be addressed in concert with the identification of stoichiometric flexibility. As such, researchers should bear in mind that empirical studies serve as snapshots in time and space of dynamic processes in systems under change. Therefore, a coupled measurement–model approach (Conant et al., 2011) represents a particularly powerful method to explore stoichiometric flexibility phenomena over multiple scales.

Notably, stoichiometric constraints are one of many factors that influence community structure and ecosystem processes (Moe et al., 2005). As such, the range of elemental ratios alone can serve as boundary conditions. However, changes in substrate use and synthesis efficiency will reflect both the variation in chemical structure and elemental ratios (Elser et al., 2010), and may control where within these boundaries a system functions. Similarly, abiotic factors linking elements to biota – such as hydrological connectivity – will be key regulators in the potential for stoichiometric response to perturbation. Nevertheless, framing global change questions within a stoichiometric flexibility framework may help to guide the understanding of controls on the variability of ecosystem responses to perturbation.

Although potential stoichiometric range tends to decrease with increasing scale, the transition from the expression of stoichiometric plasticity within organisms to the community and ecosystem scales appears to be a key threshold when considering its impact on ecosystem processes in response to perturbation. Thus, the identification of the mechanisms controlling the linkages between the individual-, community- and ecosystem-level expression of stoichiometric flexibility is particularly relevant when applying a stoichiometric framework to global change problems. Within the biologically defined boundaries on the physiological plasticity of organisms, shifting resource limitation appears to be a primary constraint on the expression of stoichiometric flexibility at the organismal scale for both primary producers and their consumers. In contrast, by assuming maximum expression of the stoichiometric range of organisms, stoichiometric flexibility from the community to ecosystem scale is likely to be ultimately regulated by disturbance dynamics and trophic feedbacks (Fig. 2). Therefore, the duration and magnitude of altered C and nutrient cycling dynamics in terrestrial systems under change will be regulated by both the stoichiometric plasticity of their organisms and the large-scale controls on the ecosystems that they build.

image

Figure 2. Conceptual diagram of the stoichiometric range potential of nested biological states that are linked across increasing scale. At smaller levels of biological organization (green), a change in nutrient limitation is likely to be a primary regulator of the expression of stoichiometric flexibility within the potential range. At larger scales (blue), disturbance dynamics and trophic feedbacks are major regulators of the expression of stoichiometric flexibility.

Download figure to PowerPoint

Acknowledgements

  1. Top of page
  2. Summary
  3. Stoichiometric flexibility across scales
  4. Stoichiometric flexibility and the structuring of terrestrial ecosystems
  5. Stoichiometric flexibility and terrestrial responses to global change
  6. Synthesis
  7. Acknowledgements
  8. References

We would like to thank the attendees of the 27th New Phytologist Symposium, ‘Stoichiometric flexibility in terrestrial ecosystems under global change’, for the rich diversity of questions and insights that their discussions provoked. We also thank Carla D’Antonio, Jennifer King, Edward Rastetter and the anonymous reviewers whose comments greatly improved the quality of the manuscript.

References

  1. Top of page
  2. Summary
  3. Stoichiometric flexibility across scales
  4. Stoichiometric flexibility and the structuring of terrestrial ecosystems
  5. Stoichiometric flexibility and terrestrial responses to global change
  6. Synthesis
  7. Acknowledgements
  8. References
  • Ainsworth EA, Long SP. 2005. What have we learned from 15 years of free-air CO2 enrichment (FACE)? A meta-analytic review of the responses of photosynthesis, canopy properties and plant production to rising CO2. New Phytologist 165: 351371.
  • Allison SD, Vitousek PM. 2004. Rapid nutrient cycling in leaf litter from invasive plants in Hawai’i. Oecologia 141: 612619.
  • Allison SD, Wallenstein MD, Bradford MA. 2010. Soil-carbon response to warming dependent on microbial physiology. Nature Geoscience 3: 336340.
  • Anderson TR, Hessen DO, Elser JJ, Urabe J. 2005. Metabolic stoichiometry and the fate of excess carbon and nutrients in consumers. The American Naturalist 165: 115.
  • Asner GP, Martin RE, Knapp DE, Kennedy-Bowdoin T. 2009. Effects of Morella faya tree invasion on aboveground carbon storage in Hawaii. Biological Invasions 12: 477494.
  • Beisner B, Haydon D, Cuddington K. 2003. Alternative stable states in ecology. Frontiers in Ecology and the Environment 1: 376382.
  • Boerner REJ. 1982. Fire and nutrient cycling in temperate ecosystems. BioScience 32: 187192.
  • Bret-Harte MS, Shaver GR, Chapin FS III. 2002. Primary and secondary stem growth in arctic shrubs: implications for community response to environmental change. Journal of Ecology 90: 251267.
  • Carney KM, Hungate BA, Drake Bert G, Megonigal JP. 2007. Altered soil microbial community at elevated CO2 leads to loss of soil carbon. Proceedings of the National Academy of Sciences, USA 104: 49904995.
  • Chapin FS III, Vitousek PM, Cleve KV. 1986. The nature of nutrient limitation in plant communities. The American Naturalist 127: 4858.
  • Clemmensen KE, Michelsen A, Jonasson S, Shaver GR. 2006. Increased ectomycorrhizal fungal abundance after long-term fertilization and warming of two arctic tundra ecosystems. New Phytologist 171: 391404.
  • Cleveland CC, Liptzin D. 2007. C : N : P stoichiometry in soil: is there a “Redfield ratio” for the microbial biomass? Biogeochemistry 85: 235252.
  • Cleveland CC, Reed SC, Townsend AR. 2006. Nutrient regulation of organic matter decomposition in a tropical rain forest. Ecology 87: 492503.
  • Cleveland CC, Townsend AR. 2006. Nutrient additions to a tropical rain forest drive substantial soil carbon dioxide losses to the atmosphere. Proceedings of the National Academy of Sciences, USA 103: 1031610321.
  • Conant RT, Ogle SM, Paul EA, Paustian K. 2011. Measuring and monitoring soil organic carbon stocks in agricultural lands for climate mitigation. Frontiers in Ecology and the Environment 9: 169173.
  • Cowling EB, Merrill W. 1966. Nitrogen in wood and its role in wood deterioration. Canadian Journal of Botany 44: 15391554.
  • Cusack DF, Torn MS, McDowell WH, Silver WL. 2010. The response of heterotrophic activity and carbon cycling to nitrogen additions and warming in two tropical soils. Global Change Biology 16: 25552572.
  • Deslippe JR, Simard SW. 2011. Below-ground carbon transfer among Betula nana may increase with warming in Arctic tundra. New Phytologist 192: 689698.
  • Drake Bert G, Gonzàlez-Meler MA, Long Steve P. 1997. More efficient plants: a consequence of rising atmospheric CO2? Annual Review of Plant Physiology and Plant Molecular Biology 48: 609639.
  • Eisele KA, Schimel DS, Kapustka LA, Parton WJ. 1989. Effects of available P and N : P ratios on non-symbiotic dinitrogen fixation in tallgrass prairie soils. Oecologia 79: 471474.
  • Elser JJ, Dobberfuhl DR, Mackay NA, Schampel JH. 1996. Organism size, life history, and N : P stoichiometry: toward a unified view of cellular and ecosystem processes. BioScience 46: 674684.
  • Elser JJ, Fagan WF, Kerkhoff AJ, Swenson NG, Enquist BJ. 2010. Biological stoichiometry of plant production: metabolism, scaling and ecological response to global change. New Phytologist 186: 593608.
  • Elser JJ, Sterner RW, Gorokhova E, Fagan WF, Markow TA, Cotner JB, Harrison JF, Hobbie SE, Odell GM, Weider LW. 2000. Biological stoichiometry from genes to ecosystems. Ecology Letters 3: 540550.
  • Falkowski P, Scholes RJ, Boyle E, Canadell J, Canfield D, Elser J, Gruber N, Hibbard K, Högberg P, Linder S et al. 2000. The global carbon cycle: a test of our knowledge of Earth as a system. Science 290: 291296.
  • Finzi A, DeLucia E, Hamilton J, Schlesinger W, Richter D. 2002. The nitrogen budget of a pine forest under free air CO2 enrichment. Oecologia 132: 567578.
  • Garten CT, Iversen CM, Norby RJ. 2011. Litterfall 15N abundance indicates declining soil nitrogen availability in a free-air CO2 enrichment experiment. Ecology 92: 133139.
  • Geider R, La Roche J. 2002. Redfield revisited: variability of C : N : P in marine microalgae and its biochemical basis. European Journal of Phycology 37: 117.
  • Goldman JC, McCarthy JJ, Peavey DG. 1979. Growth rate influence on the chemical composition of phytoplankton in oceanic water. Nature 279: 210215.
  • de Graaff M-A, van Groenigen K-J, Six J, Hungate B, van Kessel C. 2006. Interactions between plant growth and soil nutrient cycling under elevated CO2: a meta-analysis. Global Change Biology 12: 20772091.
  • Hall SJ, Asner GP. 2007. Biological invasion alters regional nitrogen-oxide emissions from tropical rainforests. Global Change Biology 13: 21432160.
  • Hall EK, Maixner F, Franklin O, Daims H, Richter A, Battin T. 2011. Linking microbial and ecosystem ecology using ecological stoichiometry: a synthesis of conceptual and empirical approaches. Ecosystems 14: 261273.
  • Hamilton J, Finzi A, DeLucia E, George K, Naidu S, Schlesinger W. 2002. Forest carbon balance under elevated CO2. Oecologia 131: 250260.
  • Harpole WS, Ngai JT, Cleland EE, Seabloom EW, Borer ET, Bracken MES, Elser JJ, Gruner DS, Hillebrand H, Shurin JB et al. 2011. Nutrient co-limitation of primary producer communities. Ecology Letters 14: 852862.
  • Hättenschwiler S, Miglietta F, Raschi A, Korner C. 1997. Thirty years of in situ tree growth under elevated CO2: a model for future forest responses? Global Change Biology 3: 463471.
  • Hedlund K, Griffiths B, Christensen S, Scheu S, Setälä H, Tscharntke T, Verhoef H. 2004. Trophic interactions in changing landscapes: responses of soil food webs. Basic and Applied Ecology 5: 495503.
  • Hessen DO, Ågren GI, Anderson TR, Elser JJ, de Ruiter PC. 2004. Carbon sequestration in ecosystems: the role of stoichiometry. Ecology 85: 11791192.
  • Higuera PE, Brubaker LB, Anderson PM, Brown TA, Kennedy AT, Hu FS. 2008. Frequent fires in ancient shrub tundra: implications of paleorecords for arctic environmental change. PLoS ONE 3: e0001744.
  • Hobbie SE. 1992. Effects of plant species on nutrient cycling. Trends in Ecology & Evolution 7: 336339.
  • Hobbie SE, Chapin FS III. 1998. The response of tundra plant biomass, aboveground production, nitrogen, and CO2 flux to experimental warming. Ecology 79: 15261544.
  • Hobbie SE, Nadelhoffer KJ, Högberg P. 2001. A synthesis: the role of nutrients as constraints on carbon balances in boreal and arctic regions. Plant and Soil 242: 163170.
  • Hobbs NT, Schimel DS, Owensby CE, Ojima DS. 1991. Fire and grazing in the tallgrass prairie: contingent effects on nitrogen budgets. Ecology 72: 13741382.
  • Hu S, Chapin FS III, Firestone MK, Field CB, Chiariello NR. 2001. Nitrogen limitation of microbial decomposition in a grassland under elevated CO2. Nature 409: 188191.
  • Iversen CM, Ledford J, Norby RJ. 2008. CO2 enrichment increases carbon and nitrogen input from fine roots in a deciduous forest. New Phytologist 179: 837847.
  • Janus LR, Angeloni NL, McCormack J, Rier ST, Tuchman NC, Kelly JJ. 2005. Elevated atmospheric CO2 alters soil microbial communities associated with trembling aspen (Populus tremuloides) roots. Microbial Ecology 50: 102109.
  • Klamer M, Roberts MS, Levine LH, Drake BG, Garland JL. 2002. Influence of elevated CO2 on the fungal community in a coastal scrub oak forest soil investigated with terminal-restriction fragment length polymorphism analysis. Applied and Environmental Microbiology 68: 43704376.
  • Lavoie M, Mack MC, Schuur EAG. 2011. Effects of elevated nitrogen and temperature on carbon and nitrogen dynamics in Alaskan arctic and boreal soils. Journal of Geophysical Research 116: G03013.
  • Lipson DA, Wilson RF, Oechel WC. 2005. Effects of elevated atmospheric CO2 on soil microbial biomass, activity, and diversity in a chaparral ecosystem. Applied and Environmental Microbiology 71: 85738580.
  • Luo Y, Hui D, Zhang D. 2006. Elevated CO2 stimulates net accumulations of carbon and nitrogen in land ecosystems: a meta-analysis. Ecology 87: 5363.
  • Mack MC, Schuur EAG, Bret-Harte MS, Shaver GR, Chapin FS III. 2004. Ecosystem carbon storage in arctic tundra reduced by long-term nutrient fertilization. Nature 431: 440443.
  • Mack RN, Simberloff D, Lonsdale MW, Evans H, Clout M, Bazzaz FA. 2000. Biotic invasions: causes, epidemiology, global consequences, and control. Ecological Applications 10: 689710.
  • Manzoni S, Jackson RB, Trofymow JA, Porporato A. 2008. The global stoichiometry of litter nitrogen mineralization. Science 321: 684686.
  • Marklein AR, Houlton BZ. 2012. Nitrogen inputs accelerate phosphorus cycling rates across a wide variety of terrestrial ecosystems. New Phytologist 193: 696704.
  • McGroddy ME, Daufresne T, Hedin LO. 2004. Scaling of C : N : P stoichiomery in forests worldwide: implications of terrestrial Redfield-type ratios. Ecology 85: 23902401.
  • McKane RB, Rastetter EB, Shaver GR, Nadelhoffer KJ, Giblin AE, Laundre JA, Chapin FS III. 1997. Reconstruction and analysis of historical changes in carbon storage in arctic tundra. Ecology 78: 11881198.
  • Melillo JM, Butler S, Johnson J, Mohan J, Steudler P, Lux H, Burrows E, Bowles F, Smith R, Scott L et al. 2011. Soil warming, carbon–nitrogen interactions, and forest carbon budgets. Proceedings of the National Academy of Sciences, USA 108: 95089512.
  • Mikkelsen TN, Beier C, Jonasson S, Holmstrup M, Schmidt IK, Ambus P, Pilegaard K, Michelsen A, Albert K, Andresen LC et al. 2008. Experimental design of multifactor climate change experiments with elevated CO2, warming and drought: the CLIMAITE project. Functional Ecology 22: 185195.
  • Moe SJ, Stelzer RS, Forman MR, Harpole WS, Daufresne T, Yoshida T. 2005. Recent advances in ecological stoichiometry: insights for population and community ecology. Oikos 109: 2939.
  • Moore JC, McCann K, de Ruiter PC. 2005. Modeling trophic pathways, nutrient cycling, and dynamic stability in soils. Pedobiologia 49: 499510.
  • Mooshammer M, Wanek W, Schnecker J, Wild B, Leitner S, Hofhansl F, Blöchl A, Hämmerle I, Frank AH, Fuchslueger L et al. 2012. Stoichiometric controls of nitrogen and phosphorus cycling in decomposing beech leaf litter. Ecology 93: 770782.
  • Myers-Smith IH, Forbes BC, Wilmking M, Hallinger M, Lantz T, Blok D, Tape KD, Macias-Fauria M, Sass-Klaassen U, Lévesque E et al. 2011. Shrub expansion in tundra ecosystems: dynamics, impacts and research priorities. Environmental Research Letters 6: 045509.
  • Natali SM, Schuur EAG, Rubin RL. 2012. Increased plant productivity in Alaskan tundra as a result of experimental warming of soil and permafrost. Journal of Ecology 100: 488498.
  • Norby RJ, Todd DE, Fults J, Johnson DW. 2001. Allometric determination of tree growth in a CO2-enriched sweetgum stand. New Phytologist 150: 477487.
  • Norby RJ, Warren JM, Iversen CM, Medlyn BE, McMurtrie RE. 2010. CO2 enhancement of forest productivity constrained by limited nitrogen availability. Proceedings of the National Academy of Sciences, USA 107: 1936819373.
  • Norby RJ, Zak DR. 2011. Ecological lessons from Free-Air CO2 Enrichment (FACE) experiments. Annual Review of Ecology, Evolution, and Systematics 42: 181203.
  • Olofsson J, Oksanen L, Callaghan T, Hulme PE, Oksanen T, Suominen O. 2009. Herbivores inhibit climate-driven shrub expansion on the tundra. Global Change Biology 15: 26812693.
  • van der Ploeg RR, Böhm W, Kirkham MB. 1999. On the origin of the theory of mineral nutrition of plants and the law of the minimum. Soil Science Society of America Journal 63: 1055.
  • Post E, Pedersen C. 2008. Opposing plant community responses to warming with and without herbivores. Proceedings of the National Academy of Sciences, USA 105: 1235312358.
  • Rastetter EB, Ågren GI, Shaver GR. 1997. Responses of N-limited ecosystems to increased CO2: a balanced-nutrition, coupled-element-cycles model. Ecological Applications 7: 444460.
  • Rastetter EB, McKane RB, Shaver GR, Melillo JM. 1992. Changes in C storage by terrestrial ecosystems: how C–N interactions restrict responses to CO2 and temperature. Water, Air & Soil Pollution 64: 327344.
  • Rastetter EB, Shaver GR. 1992. A model of multiple-element limitation for acclimating vegetation. Ecology 73: 1157.
  • Raupach MR, Field CB, Buitenhuis ET, Ciais P, Canadell JG, Que CL, Conway TJ, Gillett NP, Houghton RA, Marland G. 2007. Contributions to accelerating atmospheric CO2 growth from economic activity, carbon intensity, and efficiency of natural sinks. Proceedings of the National Academy of Sciences, USA 104: 1886618870.
  • Reich PB, Hobbie SE, Lee T, Ellsworth DS, West JB, Tilman D, Knops JMH, Naeem S, Trost J. 2006. Nitrogen limitation constrains sustainability of ecosystem response to CO2. Nature 440: 922925.
  • Reich PB, Oleksyn J. 2004. Global patterns of plant leaf N and P in relation to temperature and latitude. Proceedings of the National Academy of Sciences, USA 101: 1100111006.
  • Rivas-Ubach A, Sardans J, Pérez-Trujillo M, Estiarte M, Peñuelas J. 2012. Strong relationship between elemental stoichiometry and metabolome in plants. Proceedings of the National Academy of Sciences, USA 109: 41814186.
  • Rousk J, Bååth E. 2011. Growth of saprotrophic fungi and bacteria in soil. FEMS Microbiology Ecology 78: 1730.
  • Rundqvist S, Hedenås H, Sandström A, Emanuelsson U, Eriksson H, Jonasson C, Callaghan TV. 2011. Tree and shrub expansion over the past 34 years at the tree-line near Abisko, Sweden. Ambio 40: 683692.
  • Rustad LE, Campbell JL, Marion GM, Norby RJ, Mitchell MJ, Hartley AE, Gurevitch JHC, Cornelissen J. 2001. A meta-analysis of the response of soil respiration, net nitrogen mineralization, and aboveground plant growth to experimental ecosystem warming. Oecologia 126: 543562.
  • Sardans J, Rivas-Ubach A, Peñuelas J. 2011. The elemental stoichiometry of aquatic and terrestrial ecosystems and its relationships with organismic lifestyle and ecosystem structure and function: a review and perspectives. Biogeochemistry, doi: 10.1007/s10533-011-9640-9.
  • Shaver GR, Chapin FS III. 1986. Effect of fertilizer on production and biomass of tussock tundra, Alaska, U.S.A. Arctic and Alpine Research 18: 261268.
  • Sinsabaugh RL. 2010. Phenol oxidase, peroxidase and organic matter dynamics of soil. Soil Biology and Biochemistry 42: 391404.
  • Sinsabaugh RL, Lauber CL, Weintraub MN, Ahmed B, Allison SD, Crenshaw C, Contosta AR, Cusack D, Frey S, Gallo ME et al. 2008. Stoichiometry of soil enzyme activity at global scale. Ecology Letters 11: 12521264.
  • Sistla SA, Asao S, Schimel JP. 2012. Detecting microbial N-limitation in tussock tundra soil: implications for Arctic soil organic carbon cycling. Soil Biology & Biochemistry 55: 7884.
  • Smith VH. 1983. Low nitrogen to phosphorus ratios favor dominance by blue–green algae in lake phytoplankton. Science 221: 669671.
  • Souza L, Belote RT, Kardol P, Weltzin JF, Norby RJ. 2010. CO2 enrichment accelerates successional development of an understory plant community. Journal of Plant Ecology 3: 3339.
  • Sterner RW, Elser JJ. 2002. Ecological stoichiometry: the biology of elements from molecules to the biosphere. Princeton, NJ, USA: Princeton University Press.
  • Stiling P, Rossi AM, Hungate B, Dijkstra P, Hinkle CR, Knott WM, Drake B. 1999. Decreased leaf-miner abundance in elevated CO2: reduced leaf quality and increased parasitoid attack. Ecological Applications 9: 240244.
  • Strickland MS, Rousk J. 2010. Considering fungal : bacterial dominance in soils – methods, controls, and ecosystem implications. Soil Biology and Biochemistry 42: 13851395.
  • Sturm M, Schimel JP, Michaelson G, Welker JM, Oberbauer SF, Liston GE, Fahenstock J, Romanovsky VE. 2008. Winter biological processes could help convert arctic tundra to shrubland. BioScience 55: 1726.
  • Sugai S, Schimel JP. 1993. Decomposition and biomass incorporation of 14C-labeled glucose and phenolics in taiga forest floor: effect of substrate quality, successional state, and season. Soil Biology and Biochemistry 25: 13791389.
  • Sullivan PF, Sommerkorn M, Rueth HM, Nadelhoffer KJ, Shaver GR, Welker JM. 2007. Climate and species affect fine root production with long-term fertilization in acidic tussock tundra near Toolik Lake, Alaska. Oecologia 153: 643652.
  • Townsend AR, Cleveland CC, Asner GP, Bustamante MMC. 2007. Controls over foliar N : P ratios in tropical forests. Ecology 88: 107118.
  • Vergutz L, Manzoni S, Porporato A, Novais RF, Jackson RB. 2012. Global resorption efficiencies and concentrations of carbon and nutrients in leaves of terrestrial plants. Ecological Monographs 82: 205220.
  • Vitousek PM, Fahey T, Johnson D, Swift MJ. 1988. Element interactions in forest ecosystems – succession, allometry and input–output budgets. Biogeochemistry 5: 734.
  • Vitousek PM, Walker LR. 1989. Biological invasion by Myrica faya in Hawai’i: plant demography, nitrogen fixation, ecosystem effects. Ecological Monographs 59: 247.
  • de Vries FT, Liiri ME, Bjørnlund L, Bowker MA, Christensen S, Setälä HM, Bardgett RD. 2012. Land use alters the resistance and resilience of soil food webs to drought. Nature Climate Change 2: 276280.
  • Walker LR, Vitousek PM. 1991. An invader alters germination and growth of native dominant tree in Hawai’i. Ecology 72: 14491455.
  • Walker MD, Wahren CH, Hollister RD, Henry GHR, Ahlquist LE, Alatalo JM, Bret-Harte MS, Calef MP, Callaghan TV, Carroll AB et al. 2006. Plant community responses to experimental warming across the tundra biome. Proceedings of the National Academy of Sciences, USA 103: 13421346.
  • Weintraub MN, Schimel JP. 2003. Interactions between carbon and nitrogen mineralization and soil organic matter chemistry in arctic tundra soils. Ecosystems 6: 129143.
  • Weintraub MN, Schimel JP. 2005. Nitrogen cycling and the spread of shrubs control changes in the carbon balance of arctic tundra ecosystems. BioScience 55: 408415.
  • Zvereva EL, Kozlov MV. 2006. Consequences of simultaneous elevation of carbon dioxide and temperature for plant–herbivore interactions: a metaanalysis. Global Change Biology 12: 2741.