Effects of leaf age-related shading and declining photosynthetic capacity on net carbon balance
Estimated mean daily net carbon balance declined with leaf age in all species because of increased shading, declining photosynthetic capacity (Amax) and associated light response functions, and their combined effects (Figs 3, 4, Table 4). On average across the 10 species, daily net carbon balance declined across the leaf life-span by 64% as a result of the combined effects of all factors, with declining photosynthetic function and increased shading being almost entirely responsible for this, given the modest impact of leaf orientation (Table 4, Fig. 4). In each species, the overall decline in net carbon balance was greater than that which would have occurred as a result of either increased shading or deterioration in physiological performance taken separately, although it was always less than the sum of the two effects. On average, across the 10 species, mean daily carbon income would decline by 39% over the leaf life-time because of decreased light interception, even if photosynthetic performance hypothetically remained at its peak throughout the leaf lifetime. Similarly, on average across the 10 species, mean carbon income would decline by 39% over the leaf life-time because of declining photosynthetic performance, even if light interception remained constant.
Figure 3. Proportional change in net daily carbon balance vs leaf age in three individuals from each of three different species. Data are for scenario 4 (triangles, thin full line), incorporating combined effects of leaf orientation, within-branch and beyond-branch shading, and scenario 5 (thick full line), incorporating the effects of leaf orientation with leaf physiology only. Because scenario 5 is driven almost entirely by the effect of leaf physiology, there is no scatter in the proportional change data. Consequently, symbols are not shown. The curvature in the lines for scenario 5 reflects the curvature of functions describing age-related declines in Amax (Table 2).
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Figure 4. Proportional change in net daytime carbon balance across the entire leaf life-span for each species. Points represent the mean effect size for different factors: within-branch shading (open circles), beyond-branch shading (crosses), leaf orientation, within-branch shading and beyond-branch shading combined (triangles), leaf physiology (squares) and total decline (filled circles). Bars show the range observed across individuals for each factor.
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Table 4. Proportional changes in net daily carbon balance with increasing leaf age as a result of leaf orientation, beyond-branch shading, within-branch shading, leaf physiology, all sources of shading plus leaf orientation and all factors
|Species||n||LL (yr)||Carbon balance age 0 (mol m−2 d−1)||Proportional change in daily carbon balance with increasing leaf age||Decline per year|
|Leaf orientation gradient||Within-branch shading||Beyond-branch shading||Leaf physiology||All shading + leaf orientation ||All factors|
|Acacia suaveolens||6||2.45||0.07||−0.01 (0.15, −0.20)||−0.34 (−0.13, −0.49)||−0.06 (0.52, −0.27)||−0.18 (−0.16, −0.19)||−0.40 (0.03, −0.68)||−0.51 (−0.12, −0.76)||−0.21 (−0.05, −0.31)|
|Banksia marginata||5||3.03||0.11||−0.05 (0.01, −0.18)||−0.34 (−0.24, −0.46)||0.09 (0.86, −0.59)||−0.42 (−0.41, −0.42)||−0.31 (0.25, −0.76)||−0.61 (−0.24, −0.92)||−0.20 (−0.08, −0.30)|
|B. oblongifolia||5||1.9||0.19||0.09 (0.24, −0.03)||−0.52 (−0.34, −0.69)||−0.25 (−0.01, −0.46)||−0.50 (−0.49, −0.51)||−0.68 (−0.37, −0.88)||−0.89 (−0.71, −1.02)||−0.47 (−0.38, −0.54)|
|Corymbia gummifera||5||1.22||0.12||0.04 (0.29, −0.12)||−0.24 (−0.04, −0.43)||−0.04 (0.30, −0.25)||−0.27 (−0.26, −0.28)||−0.27 (−0.11, −0.44)||−0.48 (−0.36, −0.60)||−0.39 (−0.29, −0.49)|
|Eriostemon australasius||5||1.01||0.08||0.04 (0.14, −0.04)||−0.16 (−0.07, −0.27)||−0.08 (0.11, −0.27)||−0.34 (−0.32, −0.36)||−0.19 (0.14, −0.41)||−0.47 (−0.21, −0.64)||−0.46 (−0.21, −0.63)|
|Eucalyptus haemastoma||5||1.55||0.19||−0.08 (0.15, −0.24)||−0.19 (−0.06, −0.38)||−0.04 (0.20, −0.17)||−0.33 (−0.31, −0.36)||−0.28 (−0.04, −0.47)||−0.53 (−0.36, −0.66)||−0.34 (−0.23, −0.43)|
|Grevillea buxifolia||5||1.25||0.11||−0.24 (−0.12, −0.32)||−0.52 (−0.36, −0.67)||−0.10 (0.12, −0.24)||−0.73 (−0.68, −0.79)||−0.67 (−0.55, −0.83)||−0.99 (−0.90, −1.08)||−0.79 (−0.72, −0.86)|
|Hakea dactyloides||5||3.45||0.08||−0.13 (0.03, −0.34)||−0.47 (−0.19, −0.81)||0.24 (1.31, −0.21)||−0.28 (−0.26, −0.31)||−0.43 (−0.07, −0.73)||−0.60 (−0.28, −0.84)||−0.17 (−0.08, −0.24)|
|Lambertia formosa||7||2.48||0.11||0.03 (0.14, −0.03)||−0.25 (−0.18, −0.38)||−0.09 (0.00, −0.18)||−0.44 (−0.43, −0.45)||−0.30 (−0.16, −0.42)||−0.63 (−0.55, −0.71)||−0.25 (−0.22, −0.28)|
|Persoonia levis||5||3.79||0.08||0.00 (0.07, −0.06)||−0.23 (−0.08, −0.35)||−0.14 (0.11, −0.41)||−0.43 (−0.43, −0.44)||−0.35 (−0.18, −0.48)||−0.65 (−0.53, −0.74)||−0.17 (−0.14, −0.19)|
Species varied in the magnitude of the decline in net carbon balance with age, and in the causes of the decline (Table 4). When both local architecture and physiological deterioration with leaf position/ageing were considered together, declines were as great as 99% (Grevillea buxifolia) and as low as 47% (Eriostemon australasius). Among the 10 species, declines in carbon income as a result of physiological decline and of the changes in light environment were correlated (P < 0.05, r = 0.62), with the slope not far from the 1 : 1 line (data not shown). These results are consistent with the hypothesis (Field, 1983) that the reallocation of nitrogen in ageing leaves (to enhance, if not optimize, whole-plant photosynthetic nitrogen use) should generally occur to match shifts in light environment.
An important question is whether the observed differences among species in the decline with age in net carbon balance are associated with aspects of their ecophysiology? The variation in the magnitude of decline in net carbon balance among species was, however, unrelated to any measured leaf trait (e.g. Amax, leaf life-span, percentage nitrogen, percentage phosphorus, leaf mass per area). Nor was there any discernible pattern regarding the known ecology of the species that could help us explain the species’ differences. Thus, it is impossible to deduce whether differences among species are real (but unexplained) or largely reflect random experimental error.
Net carbon balance at the leaf age equal to the average leaf life-span
For all species, leaves at ages equal to their average leaf life-span retained positive predicted daytime net carbon balance, although just slightly for Grevillea (Table 4, Figs 4, 5). The carbon balance of an ageing leaf was also evaluated including leaf respiratory costs from a 24-h perspective. At a leaf age equal to the average leaf life-span, leaves of seven of the species had positive predicted 24-h leaf net carbon balance, and the other three species had near-zero balances (24-hleaf, Fig. 5). Ackerly (1999) also made carbon balance calculations that included leaf respiration costs on a whole-day (24-h) basis. In doing so, he examined two different optimality models involving self-shading, net carbon balance and leaf dynamics. One model, based largely on light declines (caused by leaf position), provided plausible predictions that also matched field measurements of saplings of three species. This model and the field data suggested that 24-h daily net carbon assimilation per unit leaf should be near-zero at the mean age of leaf death (as with three of our 10 species). By contrast, however, the other model, based largely on age declines in net photosynthesis, suggested leaves should be shed when they have a positive carbon balance (as with seven of our 10 species), but this model predicted infinite values for some properties, and did not match well with empirical field data (Ackerly, 1999). Several theoretical studies on optimal leaf life-span also considered construction costs, leaf production rates and carbon export vs leaf production functions (Kikuzawa, 1991; Ackerly, 1999; Kikuzawa & Ackerly 1999). Such issues are potentially influential, but are beyond the scope of this paper.
Figure 5. Estimated net daily carbon balance for leaves of each species at the end of the life-span (other than for young leaves on a daytime basis). Symbols show the daytime net carbon balance of the leaf alone when young (12y) and when at the mean age of the leaf life-span (12lf, with lf short for ‘leaf’), the 24-h net carbon balance of the leaf alone (24lf) and the 24-h net carbon balance of the leaf examined from the whole-plant perspective (24pl). The 24-h net carbon balance of the leaf alone includes night-time leaf respiration. The 24-h net carbon balance of the leaf from the whole-plant perspective includes both night-time leaf respiration and 24-h respiration of roots and stems estimated from a simple scenario (see text for details). Bars show the range observed across individuals.
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On average, across all leaves for our 10 study species, the predicted positive 24-h leaf net carbon balance was approximately 0.025 mol m−2 d−1. This surplus is roughly the equivalent of the net carbon gained by photosynthesis for 1 h at a rate of approximately 7 µmol m−2 s−1. Such a surplus might imply that leaves are typically shed for reasons unrelated to their net carbon-generating benefits to the plant. However, a plant incurs costs elsewhere in the plant to sustain a given leaf, including respiratory costs in root and stem tissues that supply the leaf with resources, transport carbon away from leaves and physically support the leaf (Givnish, 1987).
Given the positive leaf-level carbon balances, how much root and stem respiration can a leaf at the age equal to the average leaf life-span hypothetically support? We addressed this question using output from the simulations by calculating the amount of beyond-the-leaf respiration that would be required to reduce the net carbon balance to zero. On average, leaves at the mean age of leaf death had sufficient net carbon balance surplus on a 24-h basis to support total respiratory costs roughly three times the night-time respiration of the leaf itself (data not shown).
To interpret the implication of a leaf as old as the mean leaf life-span supporting a respiratory flux three times larger than the total nightly leaf respiration cost, it may be useful to provide some perspective on the relative respiratory costs per unit leaf at both leaf and whole-plant scales. To do so, we used some of the few whole-plant data available for both leaf and whole-plant respiration rates. Using data from Reich et al. (2006), we estimated the ratio of whole-plant respiratory cost per gram of leaf to the night-time leaf respiratory cost per gram of leaf, based on a re-analysis of 248 plants from 12 species. For these 248 plants, nonleaf respiratory flux rates (i.e. instantaneous respiration rates of roots and stems combined) per plant averaged just slightly more than the total instantaneous leaf dark respiratory flux rate per plant (data not shown). However, when extrapolated over a 24-h period (and assuming a 12-h dark period relevant to the Australian simulations), the total respiratory flux per plant averaged slightly more than three times (3.2) the night-time aggregate respiration flux of all foliage, as root and stem respiration fluxes occur for 24 h per day and leaf respiration during the day is already incorporated into estimates of net photosynthesis. This summary of data for 248 plants thus provides an estimate of the total 24-h respiratory costs per leaf (approximately 3.2 times the nightly leaf respiration) that roughly matches the amount of respiration that the average leaf at the mean age of its life-span can pay for from its 24-h carbon surplus (approximately three times the nightly leaf respiration), as suggested by our simulations.
As both the respiration estimates (based on data in Reich et al., 2006) and our YPLANT simulations include a variety of uncertain simplifications and assumptions, their values and the comparison between them should be taken merely as a rough correspondence rather than a reliable quantitative estimate. Nonetheless, the comparison suggests that, at a first approximation, the average leaf at the mean age of leaf death produces just enough surplus carbon to pay for its share (i.e. its proportion) of total plant respiration. This suggests that the notion of old leaves being shed when they reach a zero carbon balance can be supported, but only when respiratory carbon costs per leaf are accounted for at the whole-plant scale. To visualize what supporting root and stem respiratory costs would do to the estimated 24-h carbon balances, we also display the 24-h net carbon balance of the leaf examined from the whole-plant perspective (24-hplant) for each of the 10 species (Fig. 5), under a scenario in which stem and root respiration costs were double those of each leaf.
The results of our analysis therefore suggest that, on average, for these 10 species, ageing leaves are shed when they can no longer pay for both their own ongoing costs and for the respiratory load in other parts of the plant that is required to support their activities. If leaves were maintained until each leaf, unto itself, had a zero net carbon balance, the plant would run a carbon deficit to maintain that leaf. This interpretation assumes that whole-plant respiratory costs are adjusted to reflect the size of the canopy. Although it is probably true that, at the moment a single leaf is senesced, such support costs do not instantaneously change, in our view it is equally likely that a plant continuously adjusts the balance of plant organs that play different roles in resource acquisition, physical structure, metabolic processing, and the like (Brouwer, 1962a,b). Thus, from an integrated perspective, the assumption that total respiratory costs can be considered as shared among all leaves is probably appropriate. Plainly, measurements for a more complete whole-plant carbon balance would be preferable, but such data are absent from most (perhaps almost all) studies. The approximate analysis undertaken here represents a step in refining carbon balance for native species to incorporate whole-plant infrastructure, as first suggested by Givnish (1987). An obvious caveat is that our study includes simplifications made in estimating LRCs, standardizing for temperature, assuming well-watered conditions and ignoring light quality, among others. Therefore, we recognize considerable uncertainty in our results, but point out that they are based on a dataset with at least as much, if not more, empirical foundation than most other attempts to address questions of this kind. Hence, we present our results as a first approximation and to provide a stepping-stone for future work that is yet more rigorous in its empirical basis.
One additional caveat to these analyses and interpretations is that the subpopulation of leaves that are alive at the mean age of leaf death may not be representative of the original cohort for each species (Reich et al., 2004). A subset of the initial population may tend to suffer high mortality because of innate or acquired weakness, and the survivors might differ in their photosynthetic attributes. Leaves alive to be sampled for photosynthetic performance beyond the mean age of leaf death must, by definition, live longer than the mean leaf age, and perhaps might sustain a positive net carbon balance to an older age than leaves that died at an earlier age. There is no technical way to overcome this source of bias, which is present in studies of ageing populations of all living (and even nonliving) entities (Vaupel et al., 1998). One can only bear it in mind for interpretation. In our study, this phenomenon would not influence the interpretation of the implications of net carbon balance at the age of the mean leaf life-span (i.e. whether a plant should keep an old leaf or not), but it could influence the interpretation of the proportional declines in net carbon balance as a function of ageing (as ostensibly the subset of leaves that are alive have higher rates than those that are dead – which should be zero – but which are not counted).
In several respects, the issue of how long to hold onto individual ageing leaves parallels the question of how large a canopy to make and how fast to turn over its various strata. The consideration of the optimal leaf area index (e.g. Anten et al., 1995; Hikosaka, 2003) is in part the problem of when to produce and drop leaves, in terms of levels of foliage (i.e. leaf area index) rather than leaf number on a stem. Boonman et al. (2006) reported that shade-induced leaf senescence of wild tobacco leaves low in a canopy leads to greater whole-plant carbon gain under competitive conditions, because of the advantages of reallocating nitrogen from senesced foliage to new leaf area at the canopy top. These results parallel the conclusions of Ackerly (1999) based on a model employing leaf population dynamics rather than whole-canopy optimization. However, Hikosaka (2003) concluded from his simulations and results of Anten et al. (1995) that old leaves might be dropped at quite different irradiance levels depending on the magnitude of the nitrogen supply, implying that there might not be a predictable association of light level and leaf senescence. The approach based on the canopy as a system (Anten et al., 1995; Hikosaka, 2003; Boonman et al., 2006), however, differs from the approach taken herein, in that optimization of canopy carbon gain is used to constrain multiple leaf traits as well as whether, and when, to drop old leaves. In the current study, we do not consider the entire canopy – instead we evaluate individual leaves, as their light supply is influenced by the rest of the canopy and as their photosynthetic capacity is diminished with age. It is interesting, therefore, to note that the results of these different studies are relatively compatible. In Australian woodland, species are characterized by low nutrient supply and low nutrient concentrations, and the most shaded leaves that are retained are appreciably less shaded than the most shaded leaves in more fertile forests with higher leaf nutrient concentrations and leaf area indices. It is impossible to conclude, however, whether the shedding of old leaves with positive 24-h leaf-level carbon balances (as generally noted in this study) is the result of needing to offset other respiratory costs (in roots and stems) or of the benefit of optimizing canopy carbon gain in a realistic competitive context (Ackerly, 1999; Boonman et al., 2006). Of course, both could occur simultaneously. Additional studies that combine a consideration of canopy optimization (as in Hikosaka, 2003) with a more rigorous treatment of leaf-level environment and physiology than that performed in this study, and with the direct assessment of total plant carbon balance considerations, could go a long way towards unravelling some of these issues.