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Growth rate is seen as a key indicator of a species’ ecology and life history and is one of the most important axes of variation among species (Grime & Hunt, 1975; Madsen & Shine, 2000; Ricklefs & Wikelski, 2002). In plants, even when species are grown in isolation under favourable conditions, they display large variation in potential relative growth rates (RGR), with growth rate often varying by > 10 fold (Grime & Hunt, 1975; Poorter & Remkes, 1990). There are obvious benefits to a high growth rate, including an increased competitive ability for occupying space and capturing resources such as light and limiting soil nutrients (Poorter, 1989). If an individual can grow fast enough to monopolize these resources and subsequently reproduce, it should be more successful than slower-growing individuals. However, as there is large variation in growth rate between species, there must be important benefits to an inherently slow growth rate and costs of fast growth under certain conditions (Grime & Hunt, 1975; Chapin, 1980; Lambers & Dijkstra, 1987).
Slower-growing plants are generally found in low nutrient, unpredictable and ‘stressful’ environments. For example, slow-growing plants dominate when there is low available nitrogen or high salinity in the soil (Parsons, 1968; Grime & Hunt, 1975; Grime, 1977; Clarkson, 1985). Fast growers typically display more flexible responses to environmental conditions, responding to low soil nutrient availability by reducing photosynthetic rates and increasing their root capacity to absorb limiting nutrients (Chapin, 1980). However, fast-growing plants lack the physiological plasticity to survive in very low nutrient conditions. The low nutrient conditions that some plants are adapted to therefore place considerable restrictions on physiological plasticity, life history and ecological strategies. Nevertheless, it is thought that a low growth rate may not always be the result of a physiological limitation, but may actually be part of a broader landscape of functional trade-offs that increase survival in low nutrient conditions and other unfavourable environments (Ardent, 1997; Metcalf & Koons, 2007).
Allocation to traits that improve longevity and defence is especially important in slow growers, as life history theory assumes that the potential benefit of increased future fecundity by delaying reproduction is weighed against the chance of mortality in that period (McLaren, 1966; Koons et al., 2008). However, the wider picture of exactly how slow-growing species are able to live longer is incomplete. In particular, it is not well understood how growth rate interacts with allocation to long-term nutrient reserves, which could serve to buffer plants when environmental conditions are unsuitable to support growth, and aid re-growth after herbivory (Chapin et al., 1990).
Many species have taproots that are thought to be involved in storage (Steinlein et al., 1993). In plants, carbon, alongside nitrogen and phosphorus, is the most vital resource required for growth and maintenance. Plants store carbon as carbohydrates such as starch, sucrose and larger oligosaccharides, especially polysaccharides containing fructose molecules (Kandler & Hopf, 1982; Keller & Matile, 1985; Chapin et al., 1990; Keller & Pharr, 1996). However, other sources (e.g. lipids) (Beeson & Proebsting, 1988), can also be used for carbon storage. Plants are also known to store nitrogen and phosphorous in various ways (Chapin et al., 1990).
Currently, there is evidence that accumulated carbohydrate reserves are used by plants for respiration during dormancy (Kozlowski, 1992) and to replace shoot tissue after herbivory (Marquis et al., 1997). Reserves can be mobilized at the beginning of the growth season to support new tissue growth (Chapin et al., 1990; Kozlowski, 1992; Gaucher et al., 2005). In addition, in some species that are often exposed to fire, plants with high levels of stored starch are more likely to resprout, rather than regenerate from seed after fire damage, suggesting that some reserves are allocated as a back-up to aid regrowth after such an event (Pate et al., 1990; Bell et al., 1996). The idea that carbohydrates are used as buffers in many circumstances is therefore widely accepted, as is the general idea that there are life-history explanations for resource allocation differences between species. However, the present evidence for an explicit relationship between growth rate and carbohydrate storage is unconvincing.
Our understanding of the link between growth rate and carbohydrate storage comes primarily from trees. Several studies on trees have found that RGR was negatively correlated with sugar or nonstructural carbohydrate concentrations and total pool sizes (Myers & Kitajima, 2007; Poorter & Kitajima, 2007). This strategy increases the probability of survival in shady forests, while saplings are small. However, in the main, investigations that look for trade-offs between growth and storage in plants provide conflicting conclusions (Poorter & Bergkotte, 1992; Van Der Meijden et al., 2000; Metcalf et al., 2006; Poorter & Kitajima, 2007) and there has been very little work on short-lived plants.
Uncovering a trade-off between growth and storage has proven difficult for two principal reasons. First, the widespread use of the classical method for measuring RGR, which does not account for the size-dependence of growth, can result in trade-offs being masked by size effects (Turnbull et al., 2008). For example, trade-offs between growth and defence have proven difficult to detect, but new size-corrected analyses of RGR have recently provided good evidence for this trade-off in Arabidopsis thaliana (Paul-Victor et al., 2010). In order to remove the effects of size, we estimated RGR at a common plant size (Rose et al., 2009). Second, the methods used to measure storage are often very selective for specific families of compounds or use easy-to-measure proxies for storage. Therefore, it is likely that important information contained in a full metabolite profile is lost. For example, some studies have used dry root weight instead of, or as a proxy for, storage, although root biomass may not be an accurate indicator of readily mobilized carbon stores (Metcalf et al., 2006). Commonly, nonstructural carbohydrates are extracted from tissues, the complex carbohydrates hydrolysed to glucose, and total glucose is then measured (Mooney et al., 1995; Myers & Kitajima, 2007; Poorter & Kitajima, 2007). An alternative approach would be to use nontargeted mass spectrometry to detect many hundreds of metabolites in a tissue sample. The result is then a snapshot at a particular point in time of the metabolite pool contained in a plant sample, and presents a more complete picture of the compounds that are present and their relative abundances. Metabolomics, therefore, offers an insight into how individual compounds covary with other families of compounds and can also reveal relationships between particular metabolites and other measured plant traits. This metabolite profiling provides clues to whole-plant responses to stress or applied treatments (Bundy et al., 2009). The application of metabolomics in life-history research is particularly appropriate because it is possible to infer resource allocation priorities within and between organs. Significantly, if expected compounds are not found to change as predicted, the complete metabolomics data could reveal which other compounds are changing.
Monocarpic perennials typically have size-dependent reproduction, although in some species there is an additional weak age-dependent component (Rose et al., 2002). This is a strategy that spreads the risk of reproduction over time in a variable environment (Venable & Brown, 1988; Rees, 1994). Delayed reproduction can evolve in semelparous species when this results in higher fecundity (McLaren, 1966); however, the potential benefit of increased future fecundity by delaying reproduction is weighed against the chance of mortality in that period (Koons et al., 2008). Therefore, taproot reserves, which can be used for both reproduction and ‘risk-aversion’ (e.g. herbivory), may decrease the risk of mortality associated with delayed reproduction (Chapin et al., 1990). In addition, belowground storage is less vulnerable to herbivory than aboveground stores, which is suggestive of a significant role in maintenance and survival compared with stores in other plant organs. The taproot stores that are available for maintenance may ultimately be used for reproduction, and indeed previously we found a growth–reproduction trade-off in monocarpic perennials as well as a growth–survival trade-off after full defoliation, whereas in the absence of defoliation faster growers had an increased probability of flowering in the second year (Rose et al., 2009).
In this investigation, we use monocarpic plants to look at the relationships between growth rate and storage, focusing on the enlarged taproots observed in the chosen species. Monocarpic plants are ideal for studying allocation strategies, as their simple life history, with its single reproductive event, means that the complications involved with understanding the costs of reproduction, and how these influence returns from current and future reproduction, do not arise. Our work builds on a previous study that linked a lower size-corrected RGR in individual plants to higher survival and bolting probability after two full defoliation events (Rose et al., 2009), and uses a novel application of metabolomic methodology to analyse the relative amounts of carbohydrate reserves in roots. In order to look at the relationship between growth and storage, we used a nontargeted approach to identify the compounds that varied in the roots, followed by a targeted approach to analyse changes in more detail. Plants may vary their investment in storage in three ways: either by changing the relative abundance of different storage compounds; by changing the total concentration of compounds; or by altering the size of taproot, that is, the total pool size. As total pool size can be confounded with plant size, for example a large plant might have a larger total store despite having a lower allocation to storage, we measured the concentration and the relative abundance of carbohydrates. The metabolomics approach also enabled us to identify all compounds that are associated with differences in growth rate between species. After performing this non-targeted analysis, we then ask which of the compounds associated with growth are known storage compounds. By doing so, we provide a unique insight into the mechanisms of storage.
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- Supporting Information
Our findings showed that slower-growing monocarps invested proportionally more of their root carbon resources than fast-growing species in specific carbohydrates and amino acids, particularly sucrose, raffinose and proline. These compounds were also present at greater relative concentrations and absolute amounts in slow-growing than fast-growing species. When scaled to the total taproot in order to account for interspecific variation in root size, slower-growing species also had a larger total carbohydrate pool. The findings demonstrate how differences in the type, concentration and absolute amount of carbon were linked with growth. Furthermore, our results showed a strong negative relationship between nitrogen-storing amino acids, such as proline and arginine, and species growth rate. The relationships between growth rate and these nutrient-storing compounds suggests that long-term reserves of both carbohydrates and nitrogen are critical storage traits. Our approach provides a novel insight into resource allocations to the root organ. We have shown the significance of carbon and nitrogen stores in slow-growing species by demonstrating that specific carbohydrates and amino acids are among the compounds that fluctuate most between species of varying average growth rates. This in turn provides strong evidence that the roots of the slow-growing species had a key role in resource storage, as variation in root size or total carbohydrate pools alone do not provide sufficient evidence for this.
We found that slower-growing species accumulated high levels of sucrose and raffinose when m/z bins were expressed as a percentage of the total ion count in the root. These m/z bins were also within the top 5% out of a 1000 m/z bins that could have been associated with low RGR (Figs 2, 3, 4). This is a strong indication that allocation to sugars is important for the slower-growing species. Sugars and the raffinose series of polysaccharides are known nonstructural carbon storage components that accumulate in plant tissue and can be easily mobilized by the cell (Chapin et al., 1990). As these sugars are osmotically active, they may also have significant roles in variable and seasonal environments. For example, they may be involved in frost tolerance (Bloom et al., 1985). The link between proportional allocation to root carbon-storing carbohydrates and interspecific variation in growth rate provides a mechanism to explain the growth-survival trade-off and our previous results, which demonstrated the benefits of slower growth to both survival and future reproduction following defoliation (Rose et al., 2009).
Slow-growing species not only allocated proportionally more of their total detected metabolites to sucrose and raffinose storage than fast growers, they also accumulated these compounds at higher concentrations (Table 2). After accounting for sucrose and the RFOs together, growth rate continued to have a significant negative relationship with carbohydrate concentration, although the effect was more dependent upon harvest date (Table 2, Fig. 5). This result was probably due to the presence of the larger oligosaccharides, stachyose and verbascose as, individually, the relationships of these compounds with relative growth rate were weak and dependent upon harvest (Table 2). Figs 2–4 also show that the relative allocation to stachyose and/or verbascose was only highly negatively associated with RGR in one harvest (stachyose in harvest 1) out of the three harvests analysed. Finally, when scaled to the total FW of each individual, the relationship between growth rate and combined root carbohydrates was highly significantly negative (Table 2, Fig. 6). This relationship remained consistent over all six harvests, from 12 wk after germination in spring 2007, until spring the following year, c. 2 months before flowering occurred. The consistency in the compounds’ relationships between harvests suggests that despite possible short-term dynamic changes in specific storage compounds, that there are fundamental resource allocation differences between the species, and these were not an artefact of differential responses to a short-term environmental change.
Ions identified as proline, arginine and other amino acids were associated with slower growth rate (Figs 2–4). In plants, amino acids are known to be important nitrogen reserves, with proline and arginine being the most significant (Sagisaka & Araki, 1983; Chapin et al., 1986; Sagisaka, 1987; Ohlson et al., 1995). In internal transport networks between plant organs, amino acids are the most common nitrogen carriers (Okumoto & Pilot, 2011). Amino acids are also synthesized into proteins, which are more complex nitrogen storage structures. Nitrogen limitation in natural environments is extremely common, therefore an accumulation of amino acids ensures that growth can be supported when this occurs (Chapin et al., 1990; Pate et al., 1990; Bell et al., 1996). Significantly, the strong relationship between the amino acids, as well as the carbohydrates, and a slow growth rate remained consistent from seedling to pre-reproductive adulthood.
Our results therefore provide clear evidence that investment in nitrogen root reserves is prioritized in slower growers compared with faster growers. Our findings may seem inconsistent with those of Poorter & Bergkotte (1992) and Poorter et al. (1990), who found that higher nitrate concentration in the whole plant, and the root in the first study, was positively associated with growth rate. However, we did not measure total nitrates directly, but found a relationship between several amino acids that are known for nitrogen storage. In this way, we have revealed information about how nitrogen is stored within the root organ, which has the potential to uncover further details regarding whole-plant functioning, in contrast to measures of total nitrogen or carbon. For example, amino acids also have other important physiological roles in the plant; they may be important osmolytes. In addition, the soil composition we made up was purposefully a low-nutrient mix, which could have altered allocation strategies in comparison with previous findings. By using a low-nutrient mix, we aimed to demonstrate the possible benefits of slow growth in a low-nutrient environment, and to find a possible mechanistic explanation for these benefits (see Rose et al., 2009), given that the advantages of fast growth are more easily revealed.
The metabolomics method allowed us to look at the relationships between growth rate and specific compounds without pre-judging which compounds to select. For example, this method identified that proline was consistently associated with slow growth. Previous work shows that proline is not only known for nitrogen storage but also accumulates under physiological stress in many plants. This amino acid may also be important for cold tolerance (Wanner & Junttila, 1999), drought stress (e.g. Zrust, 1994) and salt tolerance (Stewart & Lee, 1974). Mechanistic explanations for how proline may be involved in stress tolerance are discussed by Hare & Cress (1997). The relatively high allocation to this compound in the root is consistent with the assumption that slow growers invest more in maintenance traits and with ecological and life-history theory.
In the OPLS analyses, the only amino acid positively associated with fast growth was putatively identified as tryptophan. Tryptophan, which is involved in growth and plant developmental regulation, is a precursor for the production of auxin and defence chemicals and is used in protein synthesis (Radwanski & Last, 1995). Tryptophan could be a more common amino acid for nitrogen storage in some or all of the faster-growing species. However, the strong positive association (within the top 5% of m/z bins) with growth rate was not consistent through the three harvests. Also highly associated with fast growth was the m/z bin 413 (in two harvests), which was thought to be a phytosterol and the m/z bin 205, which was also putatively identified as mannitol and/or sorbitol (H6 only). Phytosterols such as stigmasterol regulate membrane and cell processes (reviewed in Piironen et al., 2000), while mannitol and sorbitol are sugar alcohols, which are an important carbon transporter in plants (Bloom et al., 1985). Again, the correlation between the putatively identified sugar alcohols and high RGR was not consistent over harvests, contrasting with low RGR being highly associated with larger carbohydrates in all three harvests. Therefore, the presence of sugar alcohols and tryptophan in the roots of faster-growing species could indicate a more short-term nutrient store.
Our results provide a mechanistic explanation for variation in growth rate in a group of plants where we know the effects of defoliation on subsequent survival and reproduction are linked with the growth strategy (Rose et al., 2009). The nontargeted metabolomics approach allowed us to quantify the abundance of nutrient-storage compounds in the context of the entire root metabolite fingerprint, thus providing a unique insight into the mechanisms of storage. We have demonstrated that there is a broad scope for metabolomic approaches in novel contexts.