Lisa Wingate

Photosynthetic carbon isotope discrimination and its relationship to the carbon isotope signals of stem, soil and ecosystem respiration

• Photosynthetic carbon (C) isotope discrimination (Δ(Α)) labels photosynthates (δ(A) ) and atmospheric CO(2) (δ(a)) with variable C isotope compositions during fluctuating environmental conditions. In this context, the C isotope composition of respired CO(2) within ecosystems is often hypothesized to vary temporally with Δ(Α). • We investigated the relationship between Δ(Α) and the C isotope signals from stem (δ(W)), soil (δ(S)) and ecosystem (δ(E)) respired CO(2) to environmental fluctuations, using novel tuneable diode laser absorption spectrometer instrumentation in a mature maritime pine forest. • Broad seasonal changes in Δ(Α) were reflected in δ(W,) δ(S) and δ(E). However, respired CO(2) signals had smaller short-term variations than Δ(A) and were offset and delayed by 2-10 d, indicating fractionation and isotopic mixing in a large C pool. Variations in δ(S) did not follow Δ(A) at all times, especially during rainy periods and when there is a strong demand for C allocation above ground. • It is likely that future isotope-enabled vegetation models will need to develop transfer functions that can account for these phenomena in order to interpret and predict the isotopic impact of biosphere gas exchange on the C isotope composition of atmospheric CO(2).

The impact of soil microorganisms on the global budget of δ18O in atmospheric CO2

Improved global estimates of terrestrial photosynthesis and respiration are critical for predicting the rate of change in atmospheric CO2. The oxygen isotopic composition of atmospheric CO2 can be used to estimate these fluxes because oxygen isotopic exchange between CO2 and water creates distinct isotopic flux signatures. The enzyme carbonic anhydrase (CA) is known to accelerate this exchange in leaves, but the possibility of CA activity in soils is commonly neglected. Here, we report widespread accelerated soil CO2 hydration. Exchange was 10–300 times faster than the uncatalyzed rate, consistent with typical population sizes for CA-containing soil microorganisms. Including accelerated soil hydration in global model simulations modifies contributions from soil and foliage to the global CO18O budget and eliminates persistent discrepancies existing between model and atmospheric observations. This enhanced soil hydration also increases the differences between the isotopic signatures of photosynthesis and respiration, particularly in the tropics, increasing the precision of CO2 gross fluxes obtained by using the δ18O of atmospheric CO2 by 50%.

Rapid changes in δ13C of ecosystem‐respired CO2 after sunset are consistent with transient 13C enrichment of leaf respired CO2

The CO₂ respired by darkened, light-adapted, leaves is enriched in ¹³C during the first minutes, and this effect may be related to rapid changes in leaf respiratory biochemistry upon darkening. We hypothesized that this effect would be evident at the ecosystem scale. High temporal resolution measurements of the carbon isotope composition of ecosystem respiration were made over 28 diel periods in an abandoned temperate pasture, and were compared with leaf-level measurements at differing levels of pre-illumination. At the leaf level, CO₂ respired by darkened leaves that had been preadapted to high light was strongly enriched in ¹³C, but such a ¹³C-enrichment rapidly declined over 60-100 min. The ¹³C-enrichment was less pronounced when leaves were preadapted to low light. These leaf-level responses were mirrored at the ecosystem scale; after sunset following clear, sunny days respired CO₂ was first ¹³C enriched, but the ¹³C-enrichment rapidly declined over 60-100 min. Further, this response was less pronounced following cloudy days. We conclude that the dynamics of leaf respiratory isotopic signal caused variations in ecosystem-scale ¹²CO₂/¹³) CO₂ exchange. Such rapid isotope kinetics should be considered when applying ¹³C-based techniques to elucidate ecosystem carbon cycling.

The comparison of several colour indices for the photographic recording of canopy phenology of Fagus crenata Blume in eastern Japan

Background: To understand how forests and woodland respond to global climate change, phenological observations are being made at a number of sites worldwide. Recently, digital cameras have been deployed as part of the existing network of ecosystem CO2 flux towers to provide a time-series of canopy images, and various numerical indices have so far been used by different authors. Aims: To identify which are the most effective colour indices to calculate from the signals extracted from digital cameras, in order to provide recommendations to the scientific community. Methods: Sample images of a Japanese beech (Fagus crenata) forest on Mt. Tsukuba (Japan) were used to define and calculate 12 colour signals and vegetation indices. Results: Although the strength of green signal and green excess index were reliable indicators for estimating foliage growth period, the indices were susceptible to low-visibility weather conditions and distance from the camera. Hue provided a robust metric, showing much less scatter during the vegetative period and a good indication of spring bud break. The bud break dates derived from the indices were slightly earlier than those assessed by visual observation, while the abscission dates were later. Conclusions: We propose that of all the candidate colour indices, hue is the most promising for the detection of bud break as it was least affected by atmospheric conditions.

Biotic and abiotic factors affecting the δ13C of soil respired CO2 in a Mediterranean oak woodland.

The flux (R s) and carbon isotopic composition (δ13C Rs ) of soil respired CO 2 was measured every 2 h over the course of three diel cycles in a Mediterranean oak woodland, together with measurements of the δ13C composition of leaf, root and soil organic matter (δ13C SOM) and metabolites. Simulations of R s and δ13C Rs were also made using a numerical model parameterised with the SOM data and assuming short-term production rates were driven mainly by temperature. Average values of δ13C Rs over the study period were within the range of root metabolite and average δ13C SOM values, but enriched in 13C relative to the bulk δ13C of leaf, litter, and roots and the upper soil organic layers. There was good agreement between model output and observed CO 2 fluxes and the underlying features of δ13C Rs . Observed diel variations of 0.5 ‰ in δ13C Rs were predicted by the model in response to temperature-related shifts in production rates along a ∼3 ‰ gradient observed in the profile of δ13C SOM. However, observed δ13C Rs varied by over 2 ‰, indicating that both dynamics in soil respiratory metabolism and physical processes can influence short-term variability of δ13C Rs .

How do leaf and ecosystem measures of water-use efficiency compare?

The terrestrial carbon and water cycles are intimately linked: the carbon cycle is driven by photosynthesis, while the water balance is dominated by transpiration, and both fluxes are controlled by plant stomatal conductance. The ratio between these fluxes, the plant water-use efficiency (WUE), is a useful indicator of vegetation function. WUE can be estimated using several techniques, including leaf gas exchange, stable isotope discrimination, and eddy covariance. Here we compare global compilations of data for each of these three techniques. We show that patterns of variation in WUE across plant functional types (PFTs) are not consistent among the three datasets. Key discrepancies include the following: leaf-scale data indicate differences between needleleaf and broadleaf forests, but ecosystem-scale data do not; leaf-scale data indicate differences between C3 and C4 species, whereas at ecosystem scale there is a difference between C3 and C4 crops but not grasslands; and isotope-based estimates of WUE are higher than estimates based on gas exchange for most PFTs. Our study quantifies the uncertainty associated with different methods of measuring WUE, indicates potential for bias when using WUE measures to parameterize or validate models, and indicates key research directions needed to reconcile alternative measures of WUE.

Biophysical modelling of intra-ring variations in tracheid features and wood density of Pinus pinaster trees exposed to seasonal droughts

Process-based models that link seasonally varying environmental signals to morphological features within tree rings are essential tools to predict tree growth response and commercially important wood quality traits under future climate scenarios. This study evaluated model portrayal of radial growth and wood anatomy observations within a mature maritime pine (Pinus pinaster (L.) Aït.) stand exposed to seasonal droughts. Intra-annual variations in tracheid anatomy and wood density were identified through image analysis and X-ray densitometry on stem cores covering the growth period 1999-2010. A cambial growth model was integrated with modelled plant water status and sugar availability from the soil-plant-atmosphere transfer model MuSICA to generate estimates of cell number, cell volume, cell mass and wood density on a weekly time step. The model successfully predicted inter-annual variations in cell number, ring width and maximum wood density. The model was also able to predict the occurrence of special anatomical features such as intra-annual density fluctuations (IADFs) in growth rings. Since cell wall thickness remained surprisingly constant within and between growth rings, variations in wood density were primarily the result of variations in lumen diameter, both in the model and anatomical data. In the model, changes in plant water status were identified as the main driver of the IADFs through a direct effect on cell volume. The anatomy data also revealed that a trade-off existed between hydraulic safety and hydraulic efficiency. Although a simplified description of cambial physiology is presented, this integrated modelling approach shows potential value for identifying universal patterns of tree-ring growth and anatomical features over a broad climatic gradient.

The Water Isotopic Version of the Land-Surface Model ORCHIDEE: Implementation, Evaluation, Sensitivity to Hydrological Parameters

Land-Surface Models (LSMs) exhibit large spread and uncertainties in the way they partition precipitation into surface runoff, drainage, transpiration and bare soil evaporation. To explore to what extent water isotope measurements could help evaluate the simulation of the soil water budget in LSMs, water stable isotopes have been implemented in the ORCHIDEE (ORganizing Carbon and Hydrology In Dynamic EcosystEms: the land-surface model) LSM. This article presents this implementation and the evaluation of simulations both in a stand-alone mode and coupled with an atmospheric general circulation model. ORCHIDEE simulates reasonably well the isotopic composition of soil, stem and leaf water compared to local observations at ten measurement sites. When coupled to LMDZ (Laboratoire de Meteorologie Dynamique-Zoom: the atmospheric model), it simulates well the isotopic composition of precipitation and river water compared to global observations. Sensitivity tests to LSM (Land-Surface Model) parameters are performed to identify processes whose representation by LSMs could be better evaluated using water isotopic measurements. We find that measured vertical variations in soil water isotopes could help evaluate the representation of infiltration pathways by multi-layer soil models. Measured water isotopes in rivers could help calibrate the partitioning of total runoff into surface runoff and drainage and the residence time scales in underground reservoirs. Finally, co-located isotope measurements in precipitation, vapor and soil water could help estimate the partitioning of infiltrating precipitation into bare soil evaporation.

Carbon isotope discrimination during branch photosynthesis of Fagus sylvatica: a Bayesian modelling approach

Field measurements of photosynthetic carbon isotope discrimination ((13)Δ) of Fagus sylvatica, conducted with branch bags and laser spectrometry, revealed a high variability of (13)Δ, both on diurnal and day-to-day timescales. We tested the prediction capability of three versions of a commonly used model for (13)Δ [called here comprehensive ((13)(Δcomp)), simplified ((13) Δsimple) and revised ((13)(Δrevised)) versions]. A Bayesian approach was used to calibrate major model parameters. Constrained estimates were found for the fractionation during CO(2) fixation in (13)(Δcomp), but not in (13)(Δsimple), and partially for the mesophyll conductance for CO(2)(gi). No constrained estimates were found for fractionations during mitochondrial and photorespiration, and for a diurnally variable apparent fractionation between current assimilates and mitochondrial respiration, specific to (13)(Δrevised). A quantification of parameter estimation uncertainties and interdependencies further helped explore model structure and behaviour. We found that (13)(Δcomp) usually outperformed (13)(Δsimple) because of the explicit consideration of gi and the photorespiratory fractionation in (13)(Δcomp) that enabled a better description of the large observed diurnal variation (≈9‰) of (13)Δ. Flux-weighted daily means of (13)Δ were also better predicted with (13)(Δcomp) than with (13)(Δsimple).

Sensitivity of colour indices for discriminating leaf colours from digital photographs

Summary Digital images of tree canopies have been analysed to understand how forest phenology responds to climate change. Researchers have used different colour indices to carry out quantitative analyses, but uncertainties over the performance of the various indices are hampering progress in their use. To compare the various indices under controlled conditions, we carried out experiments using a low-cost off-the-shelf digital camera with a set of standard colour charts as model leaves for different stages: emerging leaves, yellowish green; newly expanded leaves, green; fully mature leaves, dark green; senescent leaves, yellow. Two models of cameras, a compact digital camera and a surveillance ‘live image’ camera were used, and photographs were taken by two cameras for each model under clear or overcast sky conditions with two colour balance settings. The indices were also compared with those derived from spectral reflectance. Colour indices based on hue distinguished leaf colour samples with only a small influence of camera models, balance setting and sky conditions, while indices based on green were strongly influenced by camera models and were relatively insensitive to leaf colours. The strength of the green channel relative to the total of digital numbers took similar values for the mature and senescent replica leaves, highlighting its poor ability to identify the change of colour in autumn. Spectral-based hue was also sensitive to the gradation of leaf colours and showed a good correlation with the digital representation of hue regardless of camera models and balance setting. Remarkably, the primitive digital number of red, Nred, also discriminated leaf colours well, with a small influence of the factors investigated here, showing a good correlation with the reflectance of the red band, except from images taken by the surveillance cameras with auto balance. Hue was a robust index across the image set, while the green-based indices often used to quantify canopy phenology in previous studies performed poorly. Hue was well correlated with spectral reflectance indices and worked better than all other indices to discriminate leaf colours. We recommend using hue as a colour index for tracking different stages of leaf development.