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Relation between carbon dioxide assimilation and the ambient and intercellular partial pressures of carbon dioxide

Relation between carbon dioxide assimilation and the ambient and intercellular partial pressures of carbon dioxide


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So, water-use efficiency (and carbon assimilation rate) is correlated with ambient CO₂ concentration (Ca), and carbon isotope discrimination Δ is correlated with Pi/Pa (partial CO₂ pressure, intercellular and atmospheric, respectively) in C3 species. If the Ca increased, would that result in decreasing Δ? In other words, would increasing ambient CO₂ levels result in less discrimination towards the ¹³C isotope, in C3 species? And if that's true, is my math sound?


After more research, I've found this to be true and the reason why. Discrimination against ¹³CO₂ isotope comes from two reasons; kinetic effects (diffusion and enzyme fractionation), and thermodynamic effects (1). ¹²CO₂ and ¹³CO₂'s diffusion rates are different, carboxylation reaction's discrimination value is 30 per million, and the diffusivity of ¹³CO₂ is 4.4 per million less than that of ¹²CO₂ (2).

When stomata are fully open

they place no place no limitation on diffusion of CO₂, C3 leaves should discriminate against ¹³CO₂ by 30 per million, with respect to the atmosphere. When stomata are sufficiently closed that they become the sole source of limitation, the discrimination should be 4 per million. Intermediate cases give intermediate discriminations. (2)

It's known that when CO₂ is abundant in the atmosphere, stomata start to close because their job is to balance the CO₂ uptake and water loss by transpiration. This, combined with the previously mentioned information, to my understanding, means that, when they are more closed, CO₂ in the intercellular space gets consumed more. This lessens the carboxylation reaction's effect on the ¹³CO₂ discrimination because the CO₂ in intercellular space becomes more limited compared to the free diffusion of fully open stomata. In other words, carboxylation reaction has less CO₂ molecules to choose from intercellular space because free diffusion doesn't supply a constant flow of CO₂ molecules, making it use more ¹³CO₂.

(1) Farquhar et al., 1989, Annual Rev. Plant Physiol, Carbon Isotope Discrimination and Photosynthesis

(2) Farquhar et al., 1982, Aust. J. Plant Physiol, On the Relationship between Carbon Isotope Discrimination and the Intercellular Carbon Dioxide Concentration in Leaves


A Negative Relationship between Foliar Carbon Isotope Composition and Mass-Based Nitrogen Concentration on the Eastern Slope of Mount Gongga, China

Plants adopt ecological strategy to resist environmental changes and increase their resource-use efficiency. The ecological strategy includes changes in physiological traits and leaf morphology, which may result in simultaneous variations in foliar N concentration and the ratio of intercellular CO2 concentration to ambient CO2 concentration (ci/ca). This in turn links to foliar carbon isotope discrimination, and thus, a relationship between foliar N concentration and foliar carbon isotope composition (δ 13 C) is expected. To understand how plants integrate their structural and physiological resistance to environmental changes, the relationship between foliar N concentration and foliarδ 13 C has been assessed intensively, especially the correlation between area-based N concentration (Narea) and δ 13 C.Less effort has been dedicated to the examination of the relationship between mass-based N concentration(Nmass) and δ 13 C. Studies on the Nmass–δ 13 C relationship, especially those including a large amount of data and species, will enhance our understanding of leaf economics and benefit ecological modeling. The present study includes an intensive investigation into this relationship by measuring foliar Nmass and δ 13 C in a large number of plant species grown on the eastern slope of Mount Gongga, China. This study shows that foliar Nmass decreases with increasing δ 13 C, which is independent of functional group, vegetation type, and altitude. This suggests that a negative correlation between Nmass and δ 13 C may be a general pattern for plants grown not only on Mount Gongga, but also in other areas.

Citation: Li J, Wang G, Zhang R, Li L (2016) A Negative Relationship between Foliar Carbon Isotope Composition and Mass-Based Nitrogen Concentration on the Eastern Slope of Mount Gongga, China. PLoS ONE 11(11): e0166958. https://doi.org/10.1371/journal.pone.0166958

Editor: Paul C. Struik, Wageningen University, NETHERLANDS

Received: May 17, 2016 Accepted: November 7, 2016 Published: November 21, 2016

Copyright: © 2016 Li et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: All relevant data are within the paper and its Supporting Information files.

Funding: The Fundamental Research Funds for the Central Non-profit Research Institution of CAF (No. CAFYBB2014QB048) JL, the National Natural Science Foundation of China (No. 41272193) GW, the National Natural Science Foundation of China (No. 41403069) JL. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Competing interests: The authors have declared that no competing interests exist.


ORIGINAL RESEARCH article

Mario Esparza 1 , Eugenia Jedlicki 2 , Carolina González 2 , Mark Dopson 3 and David S. Holmes 2,4*
  • 1 Laboratorio de Biominer໚, Departamento de Biotecnolog໚, Facultad de Ciencias del Mar y Recursos Biológicos, Universidad de Antofagasta, Antofagasta, Chile
  • 2 Center for Bioinformatics and Genome Biology, Fundación Ciencia & Vida, Santiago, Chile
  • 3 Centre for Ecology and Evolution in Microbial Model Systems (EEMiS), Linnaeus University, Kalmar, Sweden
  • 4 Centro de Genómica y Bioinformática, Facultad de Ciencias, Universidad Mayor, Santiago, Chile

This study was motivated by surprising gaps in the current knowledge of microbial inorganic carbon (Ci) uptake and assimilation at acidic pH values (pH < 3). Particularly striking is the limited understanding of the differences between Ci uptake mechanisms in acidic versus circumneutral environments where the Ci predominantly occurs either as a dissolved gas (CO2) or as bicarbonate (HCO3 - ), respectively. In order to gain initial traction on the problem, the relative abundance of transcripts encoding proteins involved in Ci uptake and assimilation was studied in the autotrophic, polyextreme acidophile Acidithiobacillus ferrooxidans whose optimum pH for growth is 2.5 using ferrous iron as an energy source, although they are able to grow at pH 5 when using sulfur as an energy source. The relative abundance of transcripts of five operons (cbb1-5) and one gene cluster (can-sulP) was monitored by RT-qPCR and, in selected cases, at the protein level by Western blotting, when cells were grown under different regimens of CO2 concentration in elemental sulfur. Of particular note was the absence of a classical bicarbonate uptake system in A. ferrooxidans. However, bioinformatic approaches predict that sulP, previously annotated as a sulfate transporter, is a novel type of bicarbonate transporter. A conceptual model of CO2 fixation was constructed from combined bioinformatic and experimental approaches that suggests strategies for providing ecological flexibility under changing concentrations of CO2 and provides a portal to elucidating Ci uptake and regulation in acidic conditions. The results could advance the understanding of industrial bioleaching processes to recover metals such as copper at acidic pH. In addition, they may also shed light on how chemolithoautotrophic acidophiles influence the nutrient and energy balance in naturally occurring low pH environments.


Results

Photosynthetic fractionation over the last glacial cycle

First, we mathematically model the effects of shifts in pCO2 from 150 to 400 ppmv, over a range of relevant δ 13 (>_<>_>>) (glacial maxima to present day) to demonstrate the potential magnitude and direction of changes in δ 13 Cp. We consider four models which represent different scenarios of plant physiological control on isotope fractionation (Supplementary Fig. 1) in C3 land plants. The first three models are based on the expression developed by Farquhar et al. 11, 12 , which combines fractionations associated with carboxylation and diffusion of CO2 into the leaf:

where a is the magnitude of fractionation during gaseous diffusion of CO2 through the lead boundary layer and stomata, and b is the magnitude of net discrimination during carboxylation in C3 plants. Both diffusion and carboxylation are dependent on the ratio of leaf intercellular to atmospheric partial pressures of CO2 (ci/ca).

Two of these models assume that ci/ca varies linearly with ca, but with different gradients for angiosperms and gymnosperms, which are called models “Voelker-2016a” and “Voelker-2016g” respectively (see Methods for details). Motivation for different leaf gas-exchange strategies in these two groups comes from analyses of modern experiments and fossil tree-ring data from the Last Glacial 31 , as well angiosperm leaf waxes and terpenoids from the Palaeogene 32 , which consistently show a 2‰ depletion in 13 C relative to gymnosperm species. For comparison, another model (hereafter “Farquhar-1982”) assumes a leaf gas-exchange strategy where constant ci/ca is maintained across the entire range of pCO2, which is unlikely. Finally, we consider the hyperbolic model (SJ-2012) proposed by Schubert and Jahren 13 , which is based on the expression

where (>^<13>> = left( >_<>_2> - delta ^<13>>_>> ight)left( <1 + delta ^<13>>_>1000> ight)) , and A, B, and C are constants obtained by fitting Eq. (2) to data from modern growth chamber experiments conducted on Raphanus sativus and Arabidopsis plants, as well as fossil δ 13 Cp from the Last Glacial, which together provides a large range of pCO2 (180 to 4200 ppmv) and δ 13 (>_<>_>>) (−6.4 to −18.0‰).

To identify the timing and magnitude of expected shifts in δ 13 Cp over the past 155 kyr, we compute the predictions of the four models using Antarctic ice core records of δ 13 (>_<>_>>) and δ 13 (>_<>_>>) (Supplementary Data 1). Our ice core compilation (Fig. 1) makes use of a recently published record 33 which significantly improves the temporal resolution of δ 13 (>_<>_>>) measurements between Terminations I and II, which are already well-represented. These pCO2 and δ 13 (>_<>_>>) measurements present a near-continuous record, apart from the period between 47–43 kyr BP, where there is disagreement between EPICA Dronning Maud Land and Talos Dome cores.

Ice core records of stable carbon isotope composition and concentration of CO2 from 155 kyr BP to the present. a CO2 concentration data from the preindustrial era compiled from EPICA Dome C (EDC), Talos Dome, EPICA Dronning Maud Land (EDML), and Siple ice cores, with post-industrial records from Law Dome and South Pole. Black curve shows a Monte Carlo average (MCA) spline. b Corresponding δ 13 (>_<>_>>) records and MCA spline. Error bars are 1σ uncertainties. Dark grey region is 1σ confidence interval for spline. Open circles indicate outliers identified by ref. 33 . c Models of δ 13 Cp calculated from ice core records. SJ-2012 model (light green curve) is shown with 1σ propagated uncertainties. Blue bars indicate three periods where this model predicts a change in δ 13 Cp of more than 1‰ at a rate exceeding 0.25‰/kyr, excluding the period of recent anthropogenic change

All models, with the exception of Farquhar-1982, resolve a −2.5‰ change in δ 13 Cp due to the anthropogenic isotope effect, and offer similar predictions for future δ 13 Cp. However, it is important to note that the models diverge strongly under conditions of low pCO2. During the period between the Last Glacial and the beginning of the Holocene (11.4 kyr BP), ice cores document an 80 ppmv rise in pCO2, which is accompanied by fluctuations in δ 13 (>_<>_>>) of up to 0.3‰ (Fig. 1). Over the same period, a change of similar magnitude (i.e. 0.3‰) is predicted in δ 13 Cp by Farquhar-1982, which assumes a negligible pCO2 effect. The Voelker-2016a and Voelker-2016g models predict a larger change in δ 13 Cp of −0.8‰ and −0.9‰, respectively. The largest change is predicted by SJ-2012 (−2.0‰), which is comparable to the recent anthropogenic isotope effect. This is a significant change which is larger than that implied by an hypothetical doubling in MAP (1‰) 15 , combined with any changes in δ 13 (>_<>_>>) (<0.3‰) over the LGM/Holocene transition.

Furthermore, the SJ-2012 model predicts high amplitude changes (>1‰) in δ 13 Cp during three periods over the past 155 kyr (12–18, 60–62.7, and 129.4–135 kyr). These changes occur at a rate which exceeds 0.25‰/kyr (Fig. 1), excluding the past 130 years, where the change in δ 13 Cp is two orders of magnitude greater (40‰/kyr). The durations of the three pre-Industrial high-amplitude episodes range from 2.7 to 5.6 kyr, and are therefore relatively brief on Quaternary timescales. Interestingly, while two of these episodes can be attributed to the rise in pCO2 during both glacial terminations, the 1‰ shift in δ 13 Cp predicted by this model between 60 and 62.7 kyr is mainly driven by a 0.5‰ decrease in δ 13 (>_<>_>>) , which is accompanied by an increase in CO2 concentration occurring during Marine Isotope Stage (MIS) 4 33 .

The rates and timings of these predicted changes need to be considered when evaluating the pCO2 effect from fossil archives. Previous examination of faunal collagen and tooth enamel from the Eocene to the present appears to show no pCO2 effect 15 . However, considering that our analysis shows that high amplitude changes in δ 13 Cp are predicted to occur during relatively brief periods (i.e.

2.7–5.6 kyr), and faunal data from previous studies are thinly represented across several million years, it is unlikely that they provide the necessary temporal resolution to discern a possible pCO2 effect. In other words, beyond the limit of radiocarbon dating (

50 kyr), fossil archives will have minimum age uncertainties of several thousand years, which makes evaluation of the pCO2 effect impossible. Our analysis reveals that the only period during which the effect would be statistically distinguishable is the last deglaciation, when radiocarbon methods offer sufficient dating precision (

Comparison with plant and faunal isotope archives

To test each model we compile a record of δ 13 Cp which is based on 720 samples of radiocarbon-dated wood cellulose from the Northern Hemisphere, spanning the last deglaciation (Fig. 2). We also compile 521 δ 13 C values of well-dated herbivore collagen from predominantly C3 locations in northwestern Europe and northern Eurasia. Since this compilation is biased towards these regions, and herbivore diets are selective, the faunal record will not always reflect the ‘average’ composition of plants in an ecosystem. Additionally, our cellulose data are over-represented by woody species from temperate northern latitudes. Therefore, to make these very widely dispersed samples comparable, we adopt a strategy of adjusting both cellulose and collagen δ 13 C records for geographical variability in latitude, altitude and MAP (see Methods). When we adjust for geographical variability in this way (Fig. 2) the amplitude of changes across the LGM/Holocene transition is reduced from 1.41 to 0.93‰ (fauna) and 3.54 to 2.77‰ (plants). Therefore, the residual effect appears different for both cellulose and collagen. Note that our faunal data show greater scatter than our cellulose records, but the shift in δ 13 C between <10 and >20 kyr faunal data is statistically significant (one-sided paired sample t-test, t = −5.9, p = 5.2 × 10 −8 , α = 0.05).

Stable carbon isotope composition of terrestrial fossil archives over the last deglaciation, from predominantly C3 ecosystems. a Faunal collagen from northwestern Europe and northern Eurasia from 33.4 kyr BP to early 20 th century. Light red circles show δ 13 C before adjustment for MAP, altitude and latitude. Dark red circles show adjusted δ 13 C, based on the regressions of Kohn 1 . Dark black lines indicate adjusted means of faunal δ 13 C before 20 kyr and after 10 kyr, which are −20.85‰ and −21.78‰, respectively. b Plant cellulose δ 13 Cp records from the Northern Hemisphere, 40.5 kyr BP to early 20th century, with model curves. Colour codes match legend in Fig. 1: light green, SJ-2012 blue, Voelker-2016g dashed yellow, Farquhar-1982. SJ-2012 model is shown with 1σ propagated uncertainties. Dark blue squares show gymnosperm data adjusted for geographic variability in MAP, altitude, and latitude. Light blue squares show raw gymnosperm data before adjustment. Filled white circles and grey circles show mixed species (either angiosperm or unidentified) before and after adjustment for geographic variability, respectively

We hypothesise that the residual isotopic changes in adjusted cellulose and collagen records through time consist of two components: first, changing atmospheric chemistry, and second, changes in MAP, which are reasonably described by the regressions of Kohn 1 . Under this assumption we are able to constrain the pCO2 effect after correcting adjusted δ 13 Cp for the effect of changing MAP between <10 and >20 kyr, which we infer from an ensemble of coupled atmosphere-ocean general circulation models (GCMs, see Methods for further details). Note that these corrections are different from our adjustments for geographical variability whilst the latter only adjust for geographical bias, the former correct for changes through time. We find that in most cases (

95% for plants) the PMIP3-CMIP5 ensemble model predicts a change to wetter conditions during the Holocene. The average effect of MAP on the isotopic signal, constrained by GCMs, is therefore negative for both plants and fauna (Fig. 3b, c). The effect of faunal records, confined to Eurasia, is −0.4 ± 0.88‰, which is larger than both gymnosperms (−0.27 ± 0.55‰) and all plants (−0.13 ± 0.74‰) but smaller than plants from North America (−0.46 ± 0.88‰). Our corrections for changes in MAP imply a residual pCO2 effect during the deglacial rise in CO2 (

80.5 ppmv) of −0.53‰ for fauna, or equivalently −0.7 ± 1.9‰ per 100 ppmv (Fig. 3a). Only gymnosperm species are represented across our entire plant cellulose compilation, and these species distinguish a larger pCO2 effect of −1.7 ± 1.5‰ per 100 ppmv. Therefore, both collagen and cellulose records reflect changes in pCO2 (in addition to changing MAP), but with different magnitudes. Our fauna primarily reflect a dietary contribution from angiosperms, whereas our plant compilation is biased towards gymnosperm species at the LGM. We suggest that the disagreement between our plant and faunal records is likely caused by a genuine physiological difference in leaf gas-exchange strategy between angiosperm and gymnosperm plants 31, 34 .

Effect of atmospheric pCO2 on mean stable carbon isotope composition over the last deglaciation, determined from terrestrial records and from changes in MAP. a Magnitude of pCO2 effect predicted by models and palaeo-data. Error bars for models, fauna, and gymnosperms (all this study) and speleothems 16 are 1σ propagated uncertainties, and 2 s.e. for fauna from Kohn 15 . b Changes in MAP predicted by PMIP3-CMIP5 multi-model ensemble between the LGM and mid-Holocene, used to constrain the pCO2 effect on our data set. c Geographical distribution of our data, showing the magnitude of MAP changes predicted by the multi-model ensemble over the same time period

The magnitudes of the pCO2 effect implied by our data are consistent with models of photosynthesis which predict a dynamic leaf gas-exchange strategy, and a variable ratio of intercellular to atmospheric pCO2 over the 180–400 ppmv range. This is less than that proposed by Breecker 16 for speleothems, −1.6 ± 0.3‰ per 100 ppmv (1σ), but greater than that proposed by Kohn 15 for fossil collagen, −0.03 ± 0.13‰ per 100 ppmv (2 s.e., see Fig. 3a). We suggest the latter discrepancy is due to the limited temporal resolution of that data set, which is neither large enough nor sufficiently well dated to resolve millennial-scale shifts in δ 13 Cp.

With respect to our gymnosperm cellulose record, we find that δ 13 C (adjusted for geographical variability) is best described by SJ-2012 and Voelker-2016g (SJ-2012 RMSE = 1.07, AIC = 25, BIC = 31 Voelker-2016g RMSE = 1.04, AIC = 26, BIC = 34). This is not surprising because SJ-2012 is biased towards gymnosperm palaeo-data below

350 ppmv. Our faunal analysis shows that the SJ-2012 model leads to an overestimation of the pCO2 effect for other plants and fauna, particularly at periods of low concentration. Therefore, although this model may be appropriate for gymnosperms, we suggest that SJ-2012 should not be used as a baseline to infer changes in angiosperm plants and hence the majority of ancient fauna. With respect to these records, the Voelker-2016a model best reproduces the magnitude of the deglacial shift observed in fauna (–0.53‰, Supplementary Table 4), but is offset from all cellulose records. The

1.4‰ offset is probably related to our choice of a and b constants, and/or inaccuracies in the fitted relationship between ci/ca and ca. Another alternative is some hitherto unknown subtlety of the isotopic relationship between fauna and bulk diet. This last scenario is unlikely because the difference between the cellulose and collagen records, averaged over the Holocene, imply an average collagen-diet enrichment factor consistent with the value of 5.1‰ determined from modern controlled-feeding studies 35,36,37 , after factoring in the

1‰ isotopic offset between cellulose and bulk leaf tissue (faunal diet) 38 . Further chamber and palaeo-data from angiosperm plants, across a wider range of pCO2, might be needed to shed light on the other explanations.


Discussion

Under most environmental conditions a strong water potential gradient drives evaporation from hydrated moss tissue to the atmosphere. The only, rather limited, barriers to the evaporation of external water from moss tissue are any undulations in the surface topography (Oliver et al., 2000 ) or the overlap of adjacent leaflets. For desiccation-tolerant mosses growing without a continuous water supply, brief periods of hydration and metabolic activity must be exploited for net carbon gain and growth before the onset of desiccation. The initial rapid decline in S. ruralis relative water content (Fig. 1) was attributable to evaporating external water. Following the loss of external water, the internal water evaporated at a slower rate until only tightly bound metabolic water remained and photosynthesis ceased (Proctor et al., 1998 ). Despite this extreme desiccation, Syntrichia tissue remains capable of rapidly reinitiating photosynthesis when water becomes available (Oliver et al., 2000 ).

The peak in Δ 13 C at 110% RWC (Fig. 2b) was associated with the transition between the evaporation of external and internal tissue water. At this point CO2 diffusion limitation is minimal, yet sufficient cellular and metabolic water remains for diffusive supply to maximize photosynthetic reactions (Rice & Giles, 1996 Proctor et al., 1998 Meyer et al., 2008 ). The slow increase in discrimination from 8‰ to 16‰ between 400% and 110% RWC was a direct response of the reduction in diffusion limitation as the external water layer evaporated. Photosynthesis also responded to the reduction in diffusion limitation for RWC values above 350% and reached 90% of Amax below this threshold (Fig. 2a), suggesting that in the presence of an external water film A and Δ 13 C co-vary in a nonlinear fashion. The mean maximum discrimination of 16‰ was lower than the theoretical maximum value of 29‰ in C3 plants when fractionation by Rubisco is the limiting factor (O'Leary, 1988 ), but similar to the maximum values measured in liverworts and consistent with diffusion limitation in the absence of intercellular air spaces (Meyer et al., 2008 ).

Bryophytes assimilate carbon and grow more slowly than their vascular counterparts, but with the flexibility conferred by their poikilohydric characteristics they are able to exploit a wide range of niches and thrive in environments with irregular, unpredictable periods of free water availability (Proctor et al., 2007 ). This was exemplified in Syntrichia by the 200% range of RWC over which the carbon assimilation rate was maintained at c. 90% of Amax (Fig. 2a), although the absolute value of Amax (c. 0.5 μmol(CO2) m −2 s −1 ) was at least an order of magnitude below that measured in many vascular plants. At high RWC quantum efficiency was maximal (Fig. 4) but photosynthesis was only 60% of Amax. This suggested that the light-harvesting apparatus was fully operational, but that photosynthesis was limited by the internal conductance of CO2 to chloroplasts. By contrast, the three indicators of photosynthetic capability, namely assimilation rate, quantum efficiency and ∆ 13 C, all declined extensively and rapidly when RWC was below 100%, as metabolic reactions were compromised because of desiccation. The quantum efficiency of Syntrichia showed a similar relationship with RWC to that observed in Sphagnum species in both Alaska (Murray et al., 1989 ) and New Zealand (Maseyk et al., 1999 ).

The linear increase in ∆H2 18 OTW as RWC decreased (Fig. 2d) reflected the isotopic enrichment that occurs in evaporating water pools (Craig & Gordon, 1965 ). The fact that this linear relationship holds even at low RWC values, with no isotopic shift at the implied transition between the pools (110% RWC), may indicate that the internal and external tissue water pools are well mixed, although with little metabolic activity and associated fractionation at low RWC values the linear relationship could alternatively indicate that evaporation is the dominant fractionating factor. The fact that ∆C 18 O 16 O in CO2 also increased linearly with decreasing RWC (Fig. 2c) is most likely the consequence of rapid oxygen isotope exchange between CO2 and tissue water catalysed by carbonic anhydrase activity, even at the lowest range of RWC values.

The transpired water vapour was depleted in heavy isotopes compared with the tissue water (Fig. 3) because of both kinetic (H2 18 O has a lower diffusivity than H2 16 O) and equilibrium effects (H2 18 O has a lower saturating vapour pressure than H2 16 O). The output of both the steady-state (SS, δM) and nonsteady-state (NSS, δL) models predicted values close to the measured δ 18 OTW. However, particularly at high RWC, the NSS model was in closer agreement with the measurements than the SS model. This is because, in the absence of a constant water influx into the system, isotopic steady state was unlikely to be reached at each successive measurement point. Therefore, when environmental conditions are well characterized, the NSS model provides a suitable framework for the prediction of the isotopic composition of moss tissue water.

The stable isotopic composition of Syntrichia cellulose represents an integrated signal related to the conditions in which the moss was growing during years of development in the natural environment. The estimated source water input during organic matter synthesis of −6‰, calculated from δ 18 OC, fitted with the weighted annual isotopic composition of precipitation measured at Keyworth, Nottinghamshire, UK (c. 130 km NW of Syntrichia source), during 2005–2006 of −6.5‰ (Jones et al., 2007 ) and the measured isotopic composition of precipitation in Cambridge, UK, during 2004 of −6.4‰ (Reyes-García et al., 2008 ). Given the evaporative enrichment of tissue water during drying events (Fig. 2d), this implies that Syntrichia cellulose synthesis only seems to have occurred during times of saturation (i.e. following rainfall and perhaps in response to early morning dew), when, having been recharged yet undergone minimal evaporative enrichment, tissue water was isotopically similar to source water.

In contrast, δ 13 CC indicated that the majority of net carbon assimilation occurred during times of minimal diffusion resistance, with the estimated 13 C value of 17.8‰ slightly higher than the maximum measured online carbon discrimination of 16‰, which occurred when the RWC had declined from saturation, to a substantially drier 110%. By this point the oxygen isotopic composition of the tissue water had undergone evaporative enrichment of 5‰ under laboratory conditions.

The contrasting δ 13 C and δ 18 O signals of the cellulose raise the intriguing possibility of temporal separation between optimal conditions for carbon assimilation (low RWC, minimal diffusive resistance, immediately before desiccation) and cellulose synthesis (high RWC, during or immediately after saturation). The optimal period of carbon assimilation is ended by one of two phenomena, both of which have been experimentally shown to cause a reduction in assimilation rate and Δ 13 C (Rice & Giles, 1996 Williams & Flanagan, 1996 Meyer et al., 2008 ). First, desiccation-related metabolic shut-down, would include the slowing, and eventual cessation, of assimilation and growth. Second, a precipitation (or other water saturating) event, that recharges internal and external water pools of the moss tissue. Saturation would increase the diffusion resistance (reducing A and Δ 13 C) while metabolic reactivation facilitates cellulose synthesis (from the carbon products assimilated when CO2 conductance was high) in the presence of water with an isotopic composition equal to that of precipitation. A consequence of the desiccation scenario would be the presence of a high concentration of soluble sugars during periods of metabolic shutdown, and indeed a pool of sucrose contributing up to 18% DW, has been measured in moss species, including S. ruralis (Smirnoff, 1992 ). Although osmotica do play a role in desiccation tolerance (Proctor et al., 2007 ), previous studies found that the concentration of sucrose was not correlated directly with the relative degree of desiccation tolerance in six moss species and that the sucrose concentration in Syntrichia ruralis varied little with water status (Smirnoff, 1992 ). Thus the temporal separation of assimilation and growth, supported by our data, may not rely completely on a significantly different concentration of sucrose reserves between the two phases and instead indicate that both reasonably high glucose concentrations and optimal turgor conditions are required for the upregulation of enzymes required to synthesize cellulose (e.g. cellulose synthase) and to provide the necessary cellular pressure to kick-start cambial activity. Further molecular investigations on the temporal phasing of the production of key enzymes responsible for cellulose synthesis would help confirm the underlying cause of this temporal separation of growth and assimilation.

The environmental feasibility of this ‘temporal separation’ hypothesis was investigated by using meteorological data to predict the changes in δ 18 OTW diurnally and seasonally (Fig. 5). The model output showed that the RWC of the moss decreased rapidly from the maxima at times of saturation to levels too low for net assimilation (A), with the extent of ∆ 13 C proportional to A throughout these daytime declines in RWC. As most assimilation occurred under highly discriminating, rapidly drying conditions this model output is consistent with the measured δ 13 CC value.

In phase with the measured diel cycle in relative humidity, the model output (Fig. 5) indicated significant isotopic enrichment of leaf water (δL) during the day, followed by depletion to a level approximately equal to δP overnight. In addition, the small volume of leaf water and rapid turnover time resulted in δL being very similar to the steady-state value of δM. If the overnight increase in relative humidity provided sufficient moisture to activate metabolic machinery, there would be little or no light to stimulate photosynthetic machinery (and hence no assimilation). However, soluble sugars could be converted into cellulose with the carbonyl oxygen atoms exposed during the metabolic processes exchanging with water molecules (Sternberg et al., 2006 ) in equilibrium with, or, in the case of atmospheric water vapour, more isotopically depleted than, δP, as has been previously shown in Tillandsia usneoides (Helliker & Griffiths, 2007 ). The measured δ 18 OC value was more consistent with the modelled isotopic composition of tissue water during periods of full turgor than the more enriched flux-weighted tissue water composition (L), suggesting that cellulose synthesis was temporally independent from periods of assimilation.

From a physiological perspective it is important to consider that all daytime desiccation events will be preceded, however briefly, by conditions optimal for maximal assimilation. At this point, with a precipitous metabolic and photosynthetic decline looming (as measured by A and Φ), investment in growth is a high-risk strategy, whilst the maintenance of soluble sugars as both osmotica and respiratory substrates for survival and post-desiccation recovery are essential. Following resaturation, the pool of sugars remains, while assimilation is limited both by the need to reactivate photosynthetic machinery and the CO2 diffusion limitation it is at this point we hypothesize an upregulation in the production of enzymes involved in cellulose synthesis. Thereafter, as the external liquid phase evaporates there is a gradual increase in CO2 conductance and assimilation and a gradual decrease in cell turgor. At this point, investment in the synthesis of cellulose is stopped and the sucrose pool is then replenished by maximum carbon assimilation rates. If the desiccation persists then an optimal concentration of compatible solutes will be synthesized to ensure adequate protection of the metabolic apparatus and DNA during the quiescent period until wet conditions return. As the growth rate of moss is slow it is likely that genetic studies will be required to confirm exactly when during the rewetting and drying cycle of mosses cellulose synthesis takes place (Roberts et al., 2012 ).

These experiments confirm the importance of RWC to the instantaneous stable isotope composition of carbon and oxygen in moss tissue, and to the integrated cellulose signal that reflects periods of net assimilation. While fundamentally an interesting phenomenon, the possible temporal separation of carbohydrate utilization discussed here has implications for the interpretation of peatland stable isotope palaeoclimate records, as the majority of both net assimilation of carbon and conversion into preserved organic matter will occur during periods of ‘optimal hydration’, a state that may differ for the two processes (CO2 assimilation and cellulose synthesis) and that will not necessarily reflect mean climatic conditions.


PG contributed to the research design, conducted major parts of the field survey, analyzed and treated the results and wrote the first manuscript draft. HNR essentially initiated the idea for this research on the basis of an unpublished literature review. HTL helped to identify sampling locations and performed some of the sample collection. GG coordinated the project, supervised the isotope abundance analyses and supported data treatment. All coauthors contributed to the manuscript.

Please note: Wiley Blackwell are not responsible for the content or functionality of any Supporting Information supplied by the authors. Any queries (other than missing material) should be directed to the New Phytologist Central Office.

Table S1 The mycorrhizal type and arbuscular mycorrhizal subtype of target plant species A. maculatum, P. quadrifolia and their respective reference plants separated by sampling location.

Table S2 Equipment and substances related to stable isotope measurements and their reproducibility.

Table S3 Statistical test procedure on stable isotope enrichment factors ε.

Table S4 Root staining procedure and microphoto-documentation of hyphal structures.

Table S5 Stable isotope natural abundances in δ-values (‰) and leaf total nitrogen concentrations (mmol g −1 dry weight) of the target plant species A. maculatum, P. quadrifolia and their respective reference plants.

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4. Optimum Biochemical Properties During a Dry Season

[35] Soil water potential and humidity have seasonal cycles and interannual and random fluctuations. In this section, the seasonal cycle of transpiration is modelled as a function of soil moisture content. Now, not only optimum photosynthetic capacity and internal carbon dioxide concentration but also the optimum seasonal cycle of transpiration is calculated. A simple differential equation for a soil reservoir is introduced. It is assumed that the dry period is long enough to affect the biochemical processes in the vegetation but too short for the vegetation to change biomass and respiration (intermediate timescale). Factors that can influence medium timescale biochemical processes are soil water potential, temperature, and radiation during a season.

[41] The question is now to find the unstressed photosynthetic capacity ν0 and c0 (or Ci) for which growth is maximized. It can intuitively be expected that the longer the expected duration of the dry period, the lower the initially unstressed transpiration rate in order to save water in anticipation of a long dry period. Makela et al. [1996] used a model for optimal stomatal control during dry periods of stochastic duration, and the assumption that vegetation aims to maximize cumulative growth. They indeed found that the initial transpiration rate decreases with the expected duration of the dry period. The approach followed here is different because both photosynthetic capacity and internal carbon dioxide concentration are optimized, whereas in their model, photosynthetic capacity had a fixed a priori value, and only stomatal regulation was optimized.

[42] The seasonal cycles of surface conductance, transpiration and assimilation as functions of photosynthetic capacity and internal carbon dioxide concentration, have been derived above. Next, the cumulative net carbon gain during the season is calculated. The optimum conditions are those for which cumulative carbon gain is maximized with respect to photosynthetic capacity and internal carbon dioxide concentration.

[45] We have now derived an optimum shape of the seasonal cycle of transpiration for a not recharged reservoir of soil water. Like in the stationary case, optimum photosynthetic capacity is proportional to g in unstressed conditions, but now g decreases with time as drought progresses.

[46] Figure 5 clearly illustrates the dilemma: if the initial photosynthesis rate is high, then a large portion of available water is transpired, and gross photosynthesis is high. However, a high initial photosynthesis rate also implies a stronger reduction of photosynthesis by stress later during the season and relatively high respiration losses.

[48] Thus the model predicts that vegetation with a high internal carbon dioxide concentration has a higher transpiration rate in unstressed conditions but is more sensitive to drought than vegetation with a low internal carbon dioxide concentration. This prediction agrees with observations by Ehleringer [1993] , who found that vegetation with a high Ci grows faster than vegetation with a low Ci when stress is removed, while vegetation with a low Ci is more resistant to drought.

[50] The above set of equations provides optimum photosynthetic capacity, internal carbon dioxide concentration and transpiration in conditions of drought. Optimum Ci can be calculated by solving equation (34) numerically. One remarkable feature is, that the lower the value for , the lower optimum Ci. This would mean that the higher the availability of water s0 (at constant sf), the lower the optimum Ci. This is contrary to some studies, which show a positive relation between water availability and Ci [ Meinzer et al., 1992 ]. In the next section, the optimality hypothesis will be discussed and alternatives presented, which explains why this contradiction occurs. Another interpretation is that the lower the value for sf at constant s0 (i.e., water stress starts at a lower soil moisture content), the lower the optimum Ci, which implies that drought resistant vegetation has a lower optimum Ci.


Results

We performed a statistical comparison of δ 13 C among different functional groups using one-way ANOVA for the plants grown on the eastern slope of Mount Gongga. The statistical analysis revealed that functional group had a significant influence on leaf δ 13 C (p< 0.001) and that a significant difference existed between herbaceous plants and woody plants, annual herbaceous plants and perennial herbaceous plants, and evergreen woody plants and deciduous woody plants no difference was observed between ferns and seed plants (Fig 1). However, functional group did not seem to exert an influence on the variation of δ 13 C with altitude, because all functional groups, except annual herbs, displayed a similar altitudinal pattern that leaf δ 13 C first decreased and then increased with increasing elevation (Fig 2).

Different letters indicate significant difference at the 0.05 level. 1: ferns 2: seed plants 3: herbaceous plants 4: woody plants 5: annual herbaceous plants 6: perennial herbaceous plants 7: evergreen woody plants 8: deciduous woody plants.

a: seed plants b: herbaceous plants c:woody plants d: ferns e:annual herbaceous plants f:perennial herbaceous plants g:evergreen woody plants h: deciduous woody plants.

An RMA regression of Nmass against δ 13 Cfor all plant samples pooled together revealed that δ 13 C significantly decreased as Nmass increased (r = -0.355, p< 0.001) (Table 1, Fig 3A).A series of RMA regressions were also conducted for each functional group and each vegetation type. A significant negative relationship between δ 13 C and Nmass was found for most of the functional groups studied, although the relationship was not significant for annual herbaceous (r = -0.234, p = 0.251) or evergreen woody plants (r = -0.003, p = 0.989), and it was only marginally significant for ferns (r = -0.521, p = 0.082)(Table 1, Fig 3B–3I). Negative relationships between δ 13 C and Nmass were also observed in most of the vegetation types studied, but some of the correlations were weak (e.g., p = 0.06 for evergreen broad-leaved forests and p = 0.97 for the alpine frigid meadow vegetation)(Table 2, Fig 4).

a: evergreen broad-leaved forests b:coniferous and broad-leaved mixed forests c:frigid dark coniferous forests d:alpine sub-frigid shrub and meadow vegetation and e:alpine frigid meadow vegetation. Solid lines indicate the linear regressions of δ 13 C vs. Nmass.

For all plants pooled together, the bivariate correlation analysis between Nmass and δ 13 C and the partial correlation analyses between Nmass and δ 13 C after controlling for functional group, vegetation type, and altitude revealed a significant negative relationship (Table 3). The correlation coefficients (r) for the bivariate correlation analysis (-0.355, p<0.001) and the partial correlation analyses (-0.353,p<0.000) between Nmass and δ 13 C after controlling for functional group were similar. However, the correlation coefficients for the partial correlation analysis after controlling for vegetation type (-0.237,p<0.001) and altitude (-0.259,p<0.001) differed from that for the bivariate correlation analysis between Nmass and δ 13 C (r = -0.355) (Table 3).

The statistical analyses of the seed plants yielded similar results as those for all plants (Table 3).The bivariate correlation analysis and the three partial correlation analyses also revealed a significantly negative relationship between Nmass and δ 13 C. Controlling for the functional group resulted in almost no change in the coefficient for the bivariate correlation analysis (r = -0.334)and the partial correlation analysis (r = -0.341) however, correlation coefficients after controlling for the vegetation type (r = -0.210) and altitude (r = -0.237) were different from that for the bivariate correlation analysis between Nmass and δ 13 C(r = -0.334) (Table 3).


1 Introduction

The terrestrial carbon cycle and its response to increasing CO2 concentrations, increased temperatures, and altered water availability is one of the least certain aspects of the climate system (e.g., Bonan et al., 2019 Friedlingstein et al., 2014 ). Terrestrial carbon cycling is fundamentally linked with the terrestrial energy balance and water cycle, as more than half of the water leaving the land surface during evapotranspiration passes through plants as transpiration (Bowen et al., 2019 Good et al., 2015 Schlesinger & Jasechko, 2014 ). As a result, several approaches have been developed to improve constraints on terrestrial carbon fluxes. Eddy covariance (EC) has emerged as a popular and powerful technique to investigate fluxes of carbon, water, and energy between the land surface and the atmosphere (e.g., Baldocchi et al., 2001 Loescher et al., 2006 ), but additional measurements and/or assumptions must be made to estimate constituent fluxes (e.g., Reichstein et al., 2005 ). For example, partitioning net ecosystem exchange (NEE) from EC measurements into ecosystem gross primary productivity and ecosystem respiration components requires a model (Lasslop et al., 2010 Reichstein et al., 2005 ). Given current limitations of these models, the resulting component fluxes still exhibit substantial uncertainty (Keenan et al., 2019 Wehr et al., 2016 ). When paired with EC measurements, complementary measurements of additional tracers that better capture underlying processes driving these component fluxes present a promising approach to reduce these uncertainties.

Stable carbon isotope ratios provide synergistic process-level information on the exchange of carbon between ecosystems and the atmosphere that cannot be gleaned from net carbon fluxes alone. Carbon isotope ratios in atmospheric CO2 (hereafter δ 13 C-CO2) have been used in a wide array of applications, including: (1) constraining anthropogenic CO2 emissions, as CO2 from combusted fossil fuels are comparatively depleted in heavy isotopologues (Pazdur et al., 2007 Sonnerup et al., 1999 Suess, 1955 ), (2) examining patterns of CO2 exchange between the land surface, ocean, and the atmosphere, as oceanic fluxes of CO2 have higher δ 13 C values than terrestrial fluxes (Ciais et al., 1995 Trolier et al., 1996 ), (3) partitioning NEE into assimilatory and respiratory components (Bowling et al., 2001 Knohl & Buchmann, 2005 Wehr & Saleska, 2015 ), (4) probing the abundance of C3 and C4 photosynthesis and their relative roles in the carbon cycle (Buchmann & Ehleringer, 1998 Ehleringer et al., 1997 Still et al., 2003 ), (5) examining recycling of respired CO2 within vegetation canopies (Yakir & Sternberg, 2000 ), and (6) estimating plant water use efficiency (Baldocchi & Bowling, 2003 Farquhar & Richards, 1984 Medlyn et al., 2017 Seibt et al., 2008 ). Initial studies of δ 13 C-CO2 used flask samples (Ciais et al., 1995 Keeling, 1958 , 1961 Trolier et al., 1996 ), which limited both the spatial and temporal frequency of sampling and our ability to infer process controls and flux magnitudes in terrestrial systems. Advances in laser spectroscopy have allowed for higher frequency measurements and the resolution of δ 13 C-CO2 atmospheric profiles (Bowling et al., 2005 Griffis et al., 2007 Raczka et al., 2017 ). These efforts have typically been driven by individual research groups with site-specific protocols and instrumentation unfortunately, this lack of coordination introduces challenges and uncertainties into cross-site comparison efforts. Furthermore, record lengths vary substantially, and the lack of concurrent multi-year records limits the comparability and information content of existing δ 13 C-CO2 data sets.

The National Ecological Observatory Network (NEON Metzger et al., 2019 Thorpe et al., 2016 ), supported by the U.S. National Science Foundation, has established a new data stream documenting atmospheric δ 13 C-CO2 across the United States using standardized instrumentation, data collection and processing protocols. These observations are collocated with EC measurements, as well as periodic measurements of δ 13 C values in other ecosystem pools, such as soil, litter, and plant matter. Measurements of δ 13 C-CO2 are made at multiple heights on NEON EC towers as part of the EC storage exchange system. At present, NEON calibrates isotopic analyzers once annually, but these observations are otherwise uncalibrated to remove instrumental drift and variation in the base calibration. Yet, three reference standards with known δ 13 C and CO2 mole fractions are run daily at each analyzer. By making use of these standards, the accuracy of the NEON raw δ 13 C-CO2 data streams can be corrected to remove this bias associated with drift and tie the absolute values at the network of sites to a common scale. Without this step, robust cross-site data comparison and analyses cannot be guaranteed since the bias may equal or exceed the size of the ecological signal of interest and give rise to spatial difference between sites. In this study, we present calibration strategies and an R package for NEON's δ 13 C-CO2 measurements and highlight trends apparent across the first 2–3 years of observatory data.


MATERIALS AND METHODS

Plant Growth and Stress Application

Tomato (Lycopersicon esculentum Mill. cv Moneymaker Hild, Marbach, Germany) seeds were sown individually in small pots of compost (ED 73, Einheitserdenwerk, Hameln, Germany) and then transferred to 2.5-L pots with a mixture of 10% sand in potting compost 7 d after germination. Plants were grown in a growth chamber under weak light (200 μmol photons m −2 s −1 ) during a 16-h-light period with 23°C in the light and 17°C in the dark with a constant relative air humidity of 70%. Plants were watered daily and regularly supplied with a commercial nutrient solution (Flori 3, Planta Düngemittel, Regenstauf, Germany). The youngest, fully expanded leaf (normally the fifth leaf from the top) of 5-week-old plants was used. Leaves of well watered plants then showed a leaf water potential of −0.6 MPa measured according to Scholander et al. (1965) with a pressure bomb (self constructed, Metallwerkstätten der Universität, Kaiserslautern, Germany). To induce an almost natural, reversible drought stress allowing the plant enough time to acclimate, irrigation was stopped 2, 5, or 8 d before measurements were taken. These treatments resulted in weak (leaf water potential −0.9 MPa), moderate (−1.3 MPa), or severe water stress (−1.8 MPa). Even severely stressed plants showed complete recovery of leaf water potential, transpiration, and net photosynthesis after rewatering.

The CO2 Isotope Fluxes in Illuminated Leaves

To determine true CO2 assimilation, photorespiration, and mitochondrial respiration in the light in attached leaves, we use 13 CO2 and mass spectrometry to measure the 13 CO2 flux into and the 12 CO2 flux out of an illuminated leaf.

Scheme of CO2 fluxes into and out of an illuminated leaf provided with 13 CO2 in the atmosphere. The fluxes of 13 CO2 and 12 CO2 measurable outside the leaf (gross 13 CO2uptake A 13C 12 CO2 releaseR 12C) and the assumed fluxes inside the leaf (gross 12 CO2 releaseR C 12 CO2 re-assimilationA R) are shown. For further details see text in “Materials and Methods.”

Scheme of CO2 fluxes into and out of an illuminated leaf provided with 13 CO2 in the atmosphere. The fluxes of 13 CO2 and 12 CO2 measurable outside the leaf (gross 13 CO2uptake A 13C 12 CO2 releaseR 12C) and the assumed fluxes inside the leaf (gross 12 CO2 releaseR C 12 CO2 re-assimilationA R) are shown. For further details see text in “Materials and Methods.”

Gas Exchange Measurements

The Open Gas-Exchange System

Diagram of the open gas exchange system used for 12 CO2/ 13 CO2measurements.

Diagram of the open gas exchange system used for 12 CO2/ 13 CO2measurements.

Proceeding of the Gas-Exchange Measurement and CO2 Flux Calculations

At the beginning of an experiment the mass spectrometric signals for 12 CO2 (350 μL L −1 ) without a leaf in the cuvette are registered. Then an attached leaf is placed into the cuvette and illuminated in a continuous gas stream (50 L h −1 ) containing 12 CO2 until photosynthetic steady state is reached. The rates of net photosynthetic CO2 uptake (A), transpiration (E), and leaf conductance (gs) are calculated as previously described ( Biehler and Fock, 1996).

Measurements at different light intensities were done on the same leaf one after the other beginning with the lowest intensity. It was carefully checked that no 13 CO2 taken up in the previous measurement was released in the subsequent run. In these experiments 13 CO2 was offered for only 1 min before the gas mixture containing 12 CO2 was applied again. The ground signal for 13 CO2 was then reached within 2 min and 13 CO2 was not evolved from the leaf.



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