A. Wood density as an integrator of wood properties
Wood density, defined here, is the oven-dry mass divided by green volume. It has traditionally been regarded as a key functional trait by ecologists. The density of woody structures excluding open spaces in wood is c. 1.5 (Siau 1984), hence wood density is bounded by 0 and 1.5 g cm−3. Wood density thus also describes the carbon investment or carbon storage per unit volume of stem (see Section 5).
Wood density varies within individuals. As wood ages, the inward part of sapwood is converted into heartwood (duramen) through the polymerization of compounds such as lignan, stilbene and flavonoid derivatives (Hillis 1987Schultz et al. 1995). Heartwood xylem lacks functional conduits and parenchyma. Foresters typically measure heartwood density, yet sapwood (xylem containing functional conduits and parenchyma) densities are often significantly lower than heartwood densities (Woodcock & Shier 2002; Patiño et al. 2008). This pattern has been attributed to the structural support required at different ontogenetic stages or changes in chemical deposition in heartwood. Furthermore, wood density varies with height within the plant (Swenson & Enquist 2008). The wood density of roots has not been measured as extensively as stems; however, roots tend to have lighter wood (Pratt et al. 2007).
Given the perceived importance of wood density with mechanical support, water transport and storage capacity of woody tissues, we have assembled the largest compilation of wood density data to date, encompassing 8412 taxa, 1683 genera, 191 families (for more details on database construction, see Appendix 1 in the Supplementary Online Information). The dataset is available in the Dryad data repository (http://datadryad.org/). In the forthcoming sections, we will also discuss geographic, phylogenetic and ecological patterns related to wood density.
B. Water transport in the xylem
One of the major roles of xylem in land plants is to transport sap to the leaves and photosynthate to the plant organs (Kozlowski 1992). This places important constraints on the architecture of stems (Tyree & Zimmermann 2002; Sperry et al. 2008). Vessel elements represent the most important water conductive cell types in angiosperms (Glossary, see Supplementary Online Information). Vessels vary in length from a few millimetres up to several metres, and they vary in diameter from < 20 to > 500 μm, while cross-sectional area percentages of vessels range from 4% to 60%. The degree to which vessels are connected to each other can influence both rates of water transport and ability to deal with xylem dysfunction, or embolism (Fig. 1, Zanne et al. 2006; Choat et al. 2008). In general, vessel length is positively correlated with vessel diameter (Ewers et al. 1997; Hacke et al. 2006). In conifers, which lack vessels, c. 95% of the constituent cells are long, fibrous tracheids, a more primitive cell type than vessel elements (Carlquist 2001). Tracheids vary in length from < 1 to > 5 mm, and from < 10 to > 50 μm in diameter. Water transport in conifers mainly occurs via wide earlywood tracheids, and mechanical support mainly occurs via narrow latewood tracheids. The relative distribution of angiosperms and conifers is likely related to differences in their wood properties (Sperry et al. 2008). For instance, it has been suggested that in lowland tropical environments, angiosperms have out-competed conifers because of their innovations in hydraulic transport (Bond 1989).
Figure 1. Xylem structure and water transport. This figure shows a reconstruction of the vessel network in Populus based on serial sectioning. A particular vessel may jump from one vessel group to a solitary position or to another vessel group. Modern technology enables a rapid analysis of the vessel network by 3D X-ray computed microtomographic reconstruction. Modified from Braun (1970) with permission from Borntraeger-Cramer.
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At the conduit level, the efficiency of water transport can be mechanistically described by the Hagen-Poiseuille equation, which relates the theoretical hydraulic conductivity K of a conduit assuming a laminar flow (Appendix 2). The longer and wider the conduit is the lower is its resistance to water flow. At the same time, increased conduit diameter greatly decreases safety, especially with respect to freezing-induced cavitation. This represents what some believe to be an important trade-off in plant function (Baas et al. 2004). At the whole-plant level, simple theoretical models have been constructed to simulate how ideal plants should work. Such models include the classic pipe model (Tyree & Zimmermann 2002), the West–Brown–Enquist theory for water conduction in plants (West et al. 1999), and Murray’s law (McCulloh et al. 2004).
The vulnerability of xylem conduits to cavitation is empirically assessed through a number of methods, which often consist of estimating the xylem tension (negative pressure) at which 50% of the conductivity is lost (Ψ50, see Tyree & Zimmermann 2002). Ψ50 varies greatly among species, from −0.18 MPa to −14 MPa, with larger absolute values in conifers than in angiosperms (Maherali et al. 2004). Based on empirical evidence, there is general agreement that the primary cause of water stress-induced embolism is penetration of air through pit membranes, a process known as ‘air-seeding’. Increasing porosity of pit membranes makes water transport more efficient, but it also makes transporting elements more vulnerable to air-seeding. Recent studies have suggested that it is the total area of intervessel pit membranes in a vessel rather than the individual pit structure that is most important in determining a vessel’s cavitation resistance and transport efficiency (Hacke et al. 2006).
How do conduit properties co-vary? The frequency of conduits mm−2 was correlated negatively with the mean diameter of those conduits across a wide range of conifer and of angiosperm species (fig. 1a in Sperry et al. 2008). This is in agreement with the idea that fewer wide conduits than narrow ones can pack into a unit area of stem. Second, sapwood area hydraulic conductivity KS (conductivity per unit of cross-sectional sapwood area) also scales with conduit diameter in conifers and angiosperms, and the scaling is consistent with the Hagen-Poiseuille equation (Fig. 2a, see also Sperry et al. 2006). This equation places a ceiling on the value of KS (solid line labelled lumen conductivity in Fig. 2a), as in reality the laminar flow of water in conduits has been measured at anywhere from 20% to 100% of theoretical conductivity. Third, typically water molecules must pass between many thousands of conduits in order to move from the roots to the canopy. Hence, in addition to the resistance imposed by the conduits, water will encounter resistance imposed by conduit end walls. The resistance accounted for by end walls is ∼50% of total xylem hydraulic resistance, suggesting that pit structure in end walls plays an important role in the overall hydraulic efficiency of plants (Choat et al. 2008). Finally, only a weak relationship has been found between sapwood area hydraulic conductivity KS and Ψ50 (Fig. 2b). In a meta-analysis of the literature, Maherali et al. (2004) found that the significant relationship between KS and Ψ50 was primarily driven by the structural difference between conifers and angiosperms. If the two clades are considered separately (or a phylogenetically independent contrast analysis is performed), no correlation was observed. These results suggest that vulnerability to cavitation and hydraulic efficiency are largely independent axes of the wood economy spectrum. Such findings are somewhat surprising as air-seeding is thought to be related to vessel volume and if diameter and length scale then one would expect diameter and vulnerability to be related (Sperry et al. 2008).
Figure 2. Water transport and wood anatomy. (a) Relation between sapwood area conductivity (mm2 kPa−1 s−1) and conduit diameter (μm), from Sperry et al. (2006). Closed circles are gymnosperms and open circles are angiosperms. The solid line across the plot represents the theoretical conduit conductivity. (b) Relation between xylem area conductivity (kg m−1 kPa−1 s−1) and vulnerability to cavitation (as xylem tension at which 50% of conductivity is lost, MPa). The relation between these variables was negative and significant (main panel, n = 168). Phylogenetic independent contrasts (PIC) of these two traits are plotted in the inset. Unlike the traits, the PICs were not correlated, showing that the two traits showed no concerted evolution. Modified from Maherali et al. (2004).
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It is often believed that wood density and water transport efficiency should be correlated because tissue density is related to the amount of space dedicated to conduits. At least in angiosperms, evidence for the relationship between vessel anatomy and wood density is mixed (Preston et al. 2006; Pratt et al. 2007). The proportions of non-conducting elements, such as fibres, vary greatly among species (Gartner et al. 2004). For instance, some angiosperm species with dense wood, such as Leptospermum scoparium in New Zealand, contain a scattering of large conduits within a matrix of fibres (Meylan & Butterfield 1978) so may not have especially low conductivity, provided that these conduits remain free from embolism. Additionally, fibres are the main tissue providing mechanical strength in angiosperms. Fibre wall thickness can vary across species and is typically a strong correlate of wood density (Pratt et al. 2007). We computed the mean wood density for the species with very thin-walled fibres and those with very thick-walled fibres, and found that species with very thick-walled fibres had a significantly higher mean wood density than species with very thin-walled fibres (Appendix 3). Furthermore, wood density is typically negatively related to capacitance, the ability of wood to store and release water under tension (Jacobsen et al. 2007; Pratt et al. 2007; Sperry et al. 2008). Wood density then is related to transport safety if not transport efficiency.
C. Mechanical properties
Plant shape is limited by structural constraints of mechanical stability against bending and buckling (Niklas 1995). The ability of plants to resist bending or breakage should be important across different ecological settings, depending on the likelihood of environmental disturbances. The elasticity to bending is measured by Young’s modulus (modulus of elasticity), defined as the ratio of stress over strain, in MPa. If too large a stress is applied to a material, it loses its elasticity, and eventually breaks. The stress needed to reach this point is called modulus of rupture (also in MPa). Other quantities have been routinely reported in the wood mechanics literature, including the dynamic resilience to breakage and the resistance to splitting (Appendix 4). These measures may also be of relevance to ecological studies. Additionally, denser wood is known to convey greater mechanical stability (Niklas 1995; Jacobsen et al. 2007; Pratt et al. 2007; Poorter 2008). Figure 3 reports the correlation of four wood mechanical traits with wood density among angiosperm species. A significantly positive correlation was found in all four cases.
Figure 3. Wood mechanical traits plotted against wood density for 1341 samples from 63 families, 298 genera and 520 species. (a) Young’s modulus (GPa, or 103 MPa). (b) Modulus of rupture (MPa). (c) Resistance to splitting of a normalized piece of wood along the fibres (kg cm−1). (d) Resilience to dynamic breakage, k, where W is the work needed to completely break a piece of wood. See Appendix 4 for more details. All linear regressions are significant (P < 0.01; solid line; r2 coefficient of correlation is reported in each panel).
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How do these standard wood measurements relate to the conditions encountered by living trees in the field? Surprisingly few publications address this topic (Niklas 1993; Jacobsen et al. 2007; Pratt et al. 2007; Poorter 2008). van Gelder et al. (2006), however, reported figures for Young’s modulus ranging between 2000 and 8000 MPa, and modulus of rupture between 5 and 30 MPa, both in the low range (Fig. 3) compared with laboratory measurements. This discrepancy may be understood by the fact that field samples were measured in wet condition, and Young’s modulus is smaller for wet than for dry samples (Mencuccini et al. 1997).
D. Defence properties
Plants must defend themselves against their predators and pathogens but also against natural hazards, such as fire, snow or wind. One mechanism of defence after the development of an infection or wound is compartmentalization of decay via a barrier zone made of non-conducting tissue (Shigo 1984; Pearce 1996). Other defence mechanisms, most efficient against animals and pathogens, consist of synthesizing chemicals (Hawley et al. 1924). Over 25 000 secondary compounds are known in plants (Croteau et al. 2000), and these compounds are believed to be critical for the evolution of plant defence (Agrawal & Fishbein 2006). For instance, the chemical deposition that occurs during heartwood formation helps prevent attack from predators and pathogens (Hillis 1987; Schultz et al. 1995). The presence of secondary compounds in hardwood has long been thought to be related to their durability (Hawley et al. 1924). However, to our knowledge, a database cataloguing the presence and amount of secondary compounds in wood, especially relative to wood durability is missing; as a result no large cross-species check of this hypothesis is available.
A simple test of this hypothesis is whether coloured (brown or red) hardwoods, richer in secondary compounds, are more durable than light-coloured hardwoods. Scheffer & Morrell (1998) reported the durability of wood of many species based on ‘graveyard’ experiments, where pieces of hardwood were placed in the ground and deterioration status recorded. Heartwood colour is available for some of these species from the InsideWood database. We combined both datasets to show that dark-coloured hardwoods were significantly more resistant to decay than light-coloured ones in agreement with the hypothesis (Appendix 5).
E. The wood economics spectrum
Baas et al. (2004) suggested the existence of a ‘trade-off triangle’ comprised of (i) a negative trade-off between the resistance to embolism (Ψ50) and conductive efficiency, (ii) a negative trade-off between conductive efficiency and mechanical strength and (iii) a positive relation between resistance to embolism and mechanical damage. While the relationships suggested by Baas et al. (2004) are intuitive, we suggest that they do not encompass the full range of variation in wood properties (e.g. water and carbon storage and defence properties), so may be missing key components needed for determining the economy of stem structure and function. Furthermore, relationships between hydraulic conductivity and both resistance to embolism and mechanical strength have fairly limited empirical support. Figure 4 summarizes the relations between major ecological functions and the above-mentioned wood traits.
Figure 4. The role of wood in major plant ecological functions (competitive ability, resistance to stress and disturbance). Wood properties are reported around the triangle (see also main text): water transport and storage, mechanical properties and defence properties (resistance to decay and embolism). The outer circle relates the main wood traits associated with these wood properties (see also Table 1).
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Based upon the evidence presented above, we suggest that a more comprehensive wood economics spectrum may be defined, as the three following points hold. (i) A number of key ecologically-relevant woody stem variables are available (Table 1). (ii) Some of these traits co-vary. With respect to water transport, conduit dimensions correlate with hydraulic conductivity KS, and wood density correlates with vulnerability to embolism. Several variables describe mechanical properties of wood and these variables relate strongly to wood density. Finally, heartwood colour, a likely indicator of secondary compound deposition, is related to wood durability. (iii) The observed covariation in traits should reflect trade-offs in carbon and nutrient allocation patterns across species.
Table 1. The main wood functional traits as measured in the ecological literature, with units and typical ranges
|Wood density||ρ||g cm−3|| 0.1–1.5|
| Number of conduits per cross-sectional area of the xylem||N||No. mm−2|| 1–1000|
| Mean conduit diameter||d||μm|| 10–500|
| Conduit element length||l||μm||100–5000|
| Total conduit length||L||cm|| 0.1–1800|
| Hydraulic conductivity||Kh||mm2 kPa−1 s−1|| 0.3–200|
| Resistance to cavitation||Ψ50||MPa|| −0.18 to −14|
| Modulus of elasticity (MOE)||Y||MPa||500–30 000|
| Modulus of rupture (MOR)||R||MPa|| 10–350|
| Resistance to splitting||S||N m|| 1–45|
| Resilience to dynamic breakage||k||NA|| 0.01–1.8|
| Proportion of cellulose|| ||%|| 38–53|
| Proportion of lignin|| ||%|| 16–32|
| Concentration in N|| ||p.p.m.||700–1200|
| Concentration in P|| ||p.p.m.|| 50–100|
| Concentration in K|| ||p.p.m.||500–1000|
| Concentration in Ca|| ||p.p.m.||700–1200|
| Concentration in polyphenols (incl. Tannins)|| ||‰||NA|
| Presence of latex/gums/oils/mucilages|| ||0/1||NA|
As discussed above, the existence of a wood economics spectrum depends on a fourth condition, namely that plants maximize fitness by making allocation ‘decisions’ that optimize growth and survival across all tissues. The next section presents evidence of coordination and trade-offs between wood traits and other plant traits. We also take the integrator trait of wood density and relate it to the demographic variables of growth and survival to determine how this stem trait may be affecting long-term reproductive success in woody plant species.