A widely-used eddy covariance gap-filling method creates systematic bias in carbon balance estimates.

Climate change mitigation requires, besides reductions in greenhouse gas emissions, actions to increase carbon sinks in terrestrial ecosystems. A key measurement method for quantifying such sinks and calibrating models is the eddy covariance technique, but it requires imputation, or gap-filling, of missing data for determination of annual carbon balances of ecosystems. Previous comparisons of gap-filling methods have concluded that commonly used methods, such as marginal distribution sampling (MDS), do not have a significant impact on the carbon balance estimate. By analyzing an extensive, global data set, we show that MDS causes significant carbon balance errors for northern (latitude [Formula: see text]) sites. MDS systematically overestimates the carbon dioxide (CO[Formula: see text]) emissions of carbon sources and underestimates the CO[Formula: see text] sequestration of carbon sinks. We also reveal reasons for these biases and show how a machine learning method called extreme gradient boosting or a modified implementation of MDS can be used to substantially reduce the northern site bias.

Estimating intraseasonal intrinsic water-use efficiency from high-resolution tree-ring δ13 C data in boreal Scots pine forests.

Intrinsic water-use efficiency (iWUE), a key index for carbon and water balance, has been widely estimated from tree-ring δ13 C at annual resolution, but rarely at high-resolution intraseasonal scale. We estimated high-resolution iWUE from laser-ablation δ13 C analysis of tree-rings (iWUEiso ) and compared it with iWUE derived from gas exchange (iWUEgas ) and eddy covariance (iWUEEC ) data for two Pinus sylvestris forests from 2002 to 2019. By carefully timing iWUEiso via modeled tree-ring growth, iWUEiso aligned well with iWUEgas and iWUEEC at intraseasonal scale. However, year-to-year patterns of iWUEgas , iWUEiso , and iWUEEC were different, possibly due to distinct environmental drivers on iWUE across leaf, tree, and ecosystem scales. We quantified the modification of iWUEiso by postphotosynthetic δ13 C enrichment from leaf sucrose to tree rings and by nonexplicit inclusion of mesophyll and photorespiration terms in photosynthetic discrimination model, which resulted in overestimation of iWUEiso by up to 11% and 14%, respectively. We thus extended the application of tree-ring δ13 C for iWUE estimates to high-resolution intraseasonal scale. The comparison of iWUEgas , iWUEiso , and iWUEEC provides important insights into physiological acclimation of trees across leaf, tree, and ecosystem scales under climate change and improves the upscaling of ecological models.

Estimating intra-seasonal photosynthetic discrimination and water use efficiency using δ13C of leaf sucrose in Scots pine.

Sucrose has a unique role in recording environmental and physiological signals during photosynthesis in its carbon isotope composition (δ13C) and transport of the signal to tree rings. Yet, instead of sucrose, total organic matter (TOM) or water-soluble carbohydrates (WSC) are typically analysed in studies that follow δ13C signals within trees. To study how the choice of organic material may bias the interpretation of δ13C records, we used mature field-grown Scots pine (Pinus sylvestris) to compare for the first time δ13C of different leaf carbon pools with δ13C of assimilates estimated by a chamber-Picarro system (δ13CA_Picarro), and a photosynthetic discrimination model (δ13CA_model). Compared with sucrose, the other tested carbon pools, such as TOM and WSC, poorly recorded the seasonal trends or absolute values of δ13CA_Picarro and δ13CA_model. Consequently, in comparison with the other carbon pools, sucrose δ13C was superior for reconstructing changes in intrinsic water use efficiency (iWUE), agreeing in both absolute values and intra-seasonal variations with iWUE estimated from gas exchange. Thus, deriving iWUE and environmental signals from δ13C of bulk organic matter can lead to misinterpretation. Our findings underscore the advantage of using sucrose δ13C to understand plant physiological responses in depth.

Intercomparison of methods to estimate gross primary production based on CO2 and COS flux measurements.

Separating the components of ecosystem-scale carbon exchange is crucial in order to develop better models and future predictions of the terrestrial carbon cycle. However, there are several uncertainties and unknowns related to current photosynthesis estimates. In this study, we evaluate four different methods for estimating photosynthesis at a boreal forest at the ecosystem scale, of which two are based on carbon dioxide (CO2) flux measurements and two on carbonyl sulfide (COS) flux measurements. The CO2-based methods use traditional flux partitioning and artificial neural networks to separate the net CO2 flux into respiration and photosynthesis. The COS-based methods make use of a unique 5-year COS flux data set and involve two different approaches to determine the leaf-scale relative uptake ratio of COS and CO2 (LRU), of which one (LRUCAP) was developed in this study. LRUCAP was based on a previously tested stomatal optimization theory (CAP), while LRUPAR was based on an empirical relation to measured radiation. For the measurement period 2013-2017, the artificial neural network method gave a GPP estimate very close to that of traditional flux partitioning at all timescales. On average, the COS-based methods gave higher GPP estimates than the CO2-based estimates on daily (23% and 7% higher, using LRUPAR and LRUCAP, respectively) and monthly scales (20% and 3% higher), as well as a higher cumulative sum over 3 months in all years (on average 25% and 3% higher). LRUCAP was higher than LRU estimated from chamber measurements at high radiation, leading to underestimation of midday GPP relative to other GPP methods. In general, however, use of LRUCAP gave closer agreement with CO2-based estimates of GPP than use of LRUPAR. When extended to other sites, LRUCAP may be more robust than LRUPAR because it is based on a physiological model whose parameters can be estimated from simple measurements or obtained from the literature. In contrast, the empirical radiation relation in LRUPAR may be more site-specific. However, this requires further testing at other measurement sites.

Tree organ growth and carbon allocation dynamics impact the magnitude and δ13C signal of stem and soil CO2 fluxes.

Incomplete knowledge of carbon (C) allocation dynamics in trees hinders accurate modeling and future predictions of tree growth. We studied C allocation dynamics in a mature Pinus sylvestris L. dominated forest with a novel analytical approach, allowing the first comparison of: (i) magnitude and δ13C of shoot, stem and soil CO2 fluxes (Ashoot, Rstem and Rsoil), (ii) concentration and δ13C of compound-specific and/or bulk non-structural carbohydrates (NSCs) in phloem and roots and (iii) growth of stem and fine roots. Results showed a significant effect of phloem NSC concentrations on tracheid growth, and both variables significantly impacted Rstem. Also, concentrations of root NSCs, especially starch, had a significant effect on fine root growth, although no effect of root NSC concentrations or root growth was detected on Rsoil. Time series analysis between δ13C of Ashoot and δ13C of Rstem or δ13C of Rsoil revealed strengthened C allocation to stem or roots under high C demands. Furthermore, we detected a significant correlation between δ13C of Rstem and δ13C of phloem sucrose and glucose, but not for starch or water-soluble carbohydrates. Our results indicate the need to include C allocation dynamics into tree growth models. We recommend using compound-specific concentration and δ13C analysis to reveal C allocation processes that may not be detected by the conventional approach that utilizes bulk organic matter.

Explicitly accounting for needle sugar pool size crucial for predicting intra-seasonal dynamics of needle carbohydrates δ18 O and δ13 C.

We explore needle sugar isotopic compositions (δ18 O and δ13 C) in boreal Scots pine (Pinus sylvestris) over two growing seasons. A leaf-level dynamic model driven by environmental conditions and based on current understanding of isotope fractionation processes was built to predict δ18 O and δ13 C of two hierarchical needle carbohydrate pools, accounting for the needle sugar pool size and the presence of an invariant pinitol pool. Model results agreed well with observed needle water δ18 O, δ18 O and δ13 C of needle water-soluble carbohydrates (sugars + pinitol), and needle sugar δ13 C (R2 = 0.95, 0.84, 0.60, 0.73, respectively). Relative humidity (RH) and intercellular to ambient CO2 concentration ratio (Ci /Ca ) were the dominant drivers of δ18 O and δ13 C variability, respectively. However, the variability of needle sugar δ18 O and δ13 C was reduced on diel and intra-seasonal timescales, compared to predictions based on instantaneous RH and Ci /Ca , due to the large needle sugar pool, which caused the signal formation period to vary seasonally from 2 d to more than 5 d. Furthermore, accounting for a temperature-sensitive biochemical 18 O-fractionation factor and mesophyll resistance in 13 C-discrimination were critical. Interpreting leaf-level isotopic signals requires understanding on time integration caused by mixing in the needle sugar pool.

Does growing atmospheric CO2 explain increasing carbon sink in a boreal coniferous forest?

The terrestrial net ecosystem productivity (NEP) has increased during the past three decades, but the mechanisms responsible are still unclear. We analyzed 17 years (2001-2017) of eddy-covariance measurements of NEP, evapotranspiration (ET) and light and water use efficiency from a boreal coniferous forest in Southern Finland for trends and inter-annual variability (IAV). The forest was a mean annual carbon sink (252 [ ± 42] gC m-2a-1 ), and NEP increased at rate +6.4-7.0 gC m-2a-1 (or ca. +2.5% a-1 ) during the period. This was attributed to the increasing gross-primary productivity GPP and occurred without detectable change in ET. The start of annual carbon uptake period was advanced by 0.7 d a-1 , and increase in GPP and NEP outside the main growing season contributed ca. one-third and one-fourth of the annual trend, respectively. Meteorological factors were responsible for the IAV of fluxes but did not explain the long-term trends. The growing season GPP trend was strongest in ample light during the peak growing season. Using a multi-layer ecosystem model, we showed that direct CO2 fertilization effect diminishes when moving from leaf to ecosystem, and only 30-40% of the observed ecosystem GPP increase could be attributed to CO2 . The increasing trend in leaf-area index (LAI), stimulated by forest thinning in 2002, was the main driver of the enhanced GPP and NEP of the mid-rotation managed forest. It also compensated for the decrease of mean leaf stomatal conductance with increasing CO2 and LAI, explaining the apparent proportionality between observed GPP and CO2 trends. The results emphasize that attributing trends to their physical and physiological drivers is challenged by strong IAV, and uncertainty of LAI and species composition changes due to the dynamic flux footprint. The results enlighten the underlying mechanisms responsible for the increasing terrestrial carbon uptake in the boreal zone.

Uncovering the critical soil moisture thresholds of plant water stress for European ecosystems.

Understanding the critical soil moisture (SM) threshold (θcrit ) of plant water stress and land surface energy partitioning is a basis to evaluate drought impacts and improve models for predicting future ecosystem condition and climate. Quantifying the θcrit across biomes and climates is challenging because observations of surface energy fluxes and SM remain sparse. Here, we used the latest database of eddy covariance measurements to estimate θcrit across Europe by evaluating evaporative fraction (EF)-SM relationships and investigating the covariance between vapor pressure deficit (VPD) and gross primary production (GPP) during SM dry-down periods. We found that the θcrit and soil matric potential threshold in Europe are 16.5% and -0.7 MPa, respectively. Surface energy partitioning characteristics varied among different vegetation types; EF in savannas had the highest sensitivities to SM in water-limited stage, and the lowest in forests. The sign of the covariance between daily VPD and GPP consistently changed from positive to negative during dry-down across all sites when EF shifted from relatively high to low values. This sign of the covariance changed after longer period of SM decline in forests than in grasslands and savannas. Estimated θcrit from the VPD-GPP covariance method match well with the EF-SM method, showing this covariance method can be used to detect the θcrit . We further found that soil texture dominates the spatial variability of θcrit while shortwave radiation and VPD are the major drivers in determining the spatial pattern of EF sensitivities. Our results highlight for the first time that the sign change of the covariance between daily VPD and GPP can be used as an indicator of how ecosystems transition from energy to SM limitation. We also characterized the corresponding θcrit and its drivers across diverse ecosystems in Europe, an essential variable to improve the representation of water stress in land surface models.

A modelling study of OH, NO3 and H2SO4 in 2007-2018 at SMEAR II, Finland: analysis of long-term trends.

Major atmospheric oxidants (OH, O3 and NO3) dominate the atmospheric oxidation capacity, while H2SO4 is considered as a main driver for new particle formation. Although numerous studies have investigated the long-term trend of ozone in Europe, the trends of OH, NO3 and H2SO4 at specific sites are to a large extent unknown. The one-dimensional model SOSAA has been applied in several studies at the SMEAR II station and has been validated by measurements in several projects. Here, we applied the SOSAA model for the years 2007-2018 to simulate the atmospheric chemical components, especially the atmospheric oxidants OH and NO3, as well as H2SO4 at SMEAR II. The simulations were evaluated with observations from several shorter and longer campaigns at SMEAR II. Our results show that daily OH increased by 2.39% per year and NO3 decreased by 3.41% per year, with different trends of these oxidants during day and night. On the contrary, daytime sulfuric acid concentrations decreased by 2.78% per year, which correlated with the observed decreasing concentration of newly formed particles in the size range of 3-25 nm with 1.4% per year at SMEAR II during the years 1997-2012. Additionally, we compared our simulated OH, NO3 and H2SO4 concentrations with proxies, which are commonly applied in case a limited number of parameters are measured and no detailed model simulations are available.

Effects of drought and meteorological forcing on carbon and water fluxes in Nordic forests during the dry summer of 2018.

The Nordic region was subjected to severe drought in 2018 with a particularly long-lasting and large soil water deficit in Denmark, Southern Sweden and Estonia. Here, we analyse the impact of the drought on carbon and water fluxes in 11 forest ecosystems of different composition: spruce, pine, mixed and deciduous. We assess the impact of drought on fluxes by estimating the difference (anomaly) between year 2018 and a reference year without drought. Unexpectedly, the evaporation was only slightly reduced during 2018 compared to the reference year at two sites while it increased or was nearly unchanged at all other sites. This occurred under a 40 to 60% reduction in mean surface conductance and the concurrent increase in evaporative demand due to the warm and dry weather. The anomaly in the net ecosystem productivity (NEP) was 93% explained by a multilinear regression with the anomaly in heterotrophic respiration and the relative precipitation deficit as independent variables. Most of the variation (77%) was explained by the heterotrophic component. Six out of 11 forests reduced their annual NEP with more than 50 g C m-2 yr-1 during 2018 as compared to the reference year. The NEP anomaly ranged between -389 and +74 g C m-2 yr-1 with a median value of -59 g C m-2 yr-1. This article is part of the theme issue 'Impacts of the 2018 severe drought and heatwave in Europe: from site to continental scale'.

Do all chlorophyll fluorescence emission wavelengths capture the spring recovery of photosynthesis in boreal evergreen foliage?

Chlorophyll a fluorescence (ChlF) is closely related to photosynthesis and can be measured remotely using multiple spectral features as solar-induced fluorescence (SIF). In boreal regions, SIF shows particular promise as an indicator of photosynthesis, in part because of the limited variation of seasonal light absorption in these ecosystems. Seasonal spectral changes in ChlF could yield new information on processes such as sustained nonphotochemical quenching (NPQS ) but also disrupt the relationship between SIF and photosynthesis. We followed ChlF and functional and biochemical properties of Pinus sylvestris needles during the photosynthetic spring recovery period to answer the following: (a) How ChlF spectra change over seasonal timescales? (b) How pigments, NPQS , and total photosynthetically active radiation (PAR) absorption drive changes of ChlF spectra? (c) Do all ChlF wavelengths track photosynthetic seasonality? We found seasonal ChlF variation in the red and far-red wavelengths, which was strongly correlated with NPQS , carotenoid content, and photosynthesis (enhanced in the red), but not with PAR absorption. Furthermore, a rapid decrease in red/far-red ChlF ratio occurred in response to a cold spell, potentially relating to the structural reorganization of the photosystems. We conclude that all current SIF retrieval features can track seasonal photosynthetic dynamics in boreal evergreens, but the full SIF spectra provides additional insight.

Linking stem growth respiration to the seasonal course of stem growth and GPP of Scots pine.

Current methods to study relations between stem respiration and stem growth have been hampered by problems in quantifying stem growth from dendrometer measurements, particularly on a daily time scale. This is mainly due to the water-related influences within these measurements that mask growth. A previously published model was used to remove water-related influences from measured radial stem variations to reveal a daily radial growth signal (ΔˆGm). We analysed the intra- and inter-annual relations between ΔˆGm and estimated growth respiration rates (Rg) on a daily scale for 5 years. Results showed that Rg was weakly correlated to stem growth prior to tracheid formation, but was significant during the early summer. In the late summer, the correlation decreased slightly relative to the early summer. A 1-day time lag was found of ΔˆGm preceding Rg. Using wavelet analysis and measurements from eddy covariance, it was found that Rg followed gross primary production and temperature with a 2 and 3 h time lag, respectively.This study shows that further in-depth analysis of in-situ growth and growth respiration dynamics is greatly needed, with a focus on cellular respiration at specific developmental stages, its woody tissue costs and linkages to source-sink processes and environmental drivers.

Towards physiologically meaningful water-use efficiency estimates from eddy covariance data.

Intrinsic water-use efficiency (iWUE) characterizes the physiological control on the simultaneous exchange of water and carbon dioxide in terrestrial ecosystems. Knowledge of iWUE is commonly gained from leaf-level gas exchange measurements, which are inevitably restricted in their spatial and temporal coverage. Flux measurements based on the eddy covariance (EC) technique can overcome these limitations, as they provide continuous and long-term records of carbon and water fluxes at the ecosystem scale. However, vegetation gas exchange parameters derived from EC data are subject to scale-dependent and method-specific uncertainties that compromise their ecophysiological interpretation as well as their comparability among ecosystems and across spatial scales. Here, we use estimates of canopy conductance and gross primary productivity (GPP) derived from EC data to calculate a measure of iWUE (G1 , "stomatal slope") at the ecosystem level at six sites comprising tropical, Mediterranean, temperate, and boreal forests. We assess the following six mechanisms potentially causing discrepancies between leaf and ecosystem-level estimates of G1 : (i) non-transpirational water fluxes; (ii) aerodynamic conductance; (iii) meteorological deviations between measurement height and canopy surface; (iv) energy balance non-closure; (v) uncertainties in net ecosystem exchange partitioning; and (vi) physiological within-canopy gradients. Our results demonstrate that an unclosed energy balance caused the largest uncertainties, in particular if it was associated with erroneous latent heat flux estimates. The effect of aerodynamic conductance on G1 was sufficiently captured with a simple representation. G1 was found to be less sensitive to meteorological deviations between canopy surface and measurement height and, given that data are appropriately filtered, to non-transpirational water fluxes. Uncertainties in the derived GPP and physiological within-canopy gradients and their implications for parameter estimates at leaf and ecosystem level are discussed. Our results highlight the importance of adequately considering the sources of uncertainty outlined here when EC-derived water-use efficiency is interpreted in an ecophysiological context.

Do the energy fluxes and surface conductance of boreal coniferous forests in Europe scale with leaf area?

Earth observing systems are now routinely used to infer leaf area index (LAI) given its significance in spatial aggregation of land surface fluxes. Whether LAI is an appropriate scaling parameter for daytime growing season energy budget, surface conductance (Gs ), water- and light-use efficiency and surface-atmosphere coupling of European boreal coniferous forests was explored using eddy-covariance (EC) energy and CO2 fluxes. The observed scaling relations were then explained using a biophysical multilayer soil-vegetation-atmosphere transfer model as well as by a bulk Gs representation. The LAI variations significantly alter radiation regime, within-canopy microclimate, sink/source distributions of CO2 , H2 O and heat, and forest floor fluxes. The contribution of forest floor to ecosystem-scale energy exchange is shown to decrease asymptotically with increased LAI, as expected. Compared with other energy budget components, dry-canopy evapotranspiration (ET) was reasonably 'conservative' over the studied LAI range 0.5-7.0 m2 m-2 . Both ET and Gs experienced a minimum in the LAI range 1-2 m2 m-2 caused by opposing nonproportional response of stomatally controlled transpiration and 'free' forest floor evaporation to changes in canopy density. The young forests had strongest coupling with the atmosphere while stomatal control of energy partitioning was strongest in relatively sparse (LAI ~2 m2 m-2 ) pine stands growing on mineral soils. The data analysis and model results suggest that LAI may be an effective scaling parameter for net radiation and its partitioning but only in sparse stands (LAI <3 m2 m-2 ). This finding emphasizes the significance of stand-replacing disturbances on the controls of surface energy exchange. In denser forests, any LAI dependency varies with physiological traits such as light-saturated water-use efficiency. The results suggest that incorporating species traits and site conditions are necessary when LAI is used in upscaling energy exchanges of boreal coniferous forests.

Pinus sylvestris as a missing source of nitrous oxide and methane in boreal forest.

Boreal forests comprise 73% of the world's coniferous forests. Based on forest floor measurements, they have been considered a significant natural sink of methane (CH4) and a natural source of nitrous oxide (N2O), both of which are important greenhouse gases. However, the role of trees, especially conifers, in ecosystem N2O and CH4 exchange is only poorly understood. We show for the first time that mature Scots pine (Pinus sylvestris L.) trees consistently emit N2O and CH4 from both stems and shoots. The shoot fluxes of N2O and CH4 exceeded the stem flux rates by 16 and 41 times, respectively. Moreover, higher stem N2O and CH4 fluxes were observed from wet than from dry areas of the forest. The N2O release from boreal pine forests may thus be underestimated and the uptake of CH4 may be overestimated when ecosystem flux calculations are based solely on forest floor measurements. The contribution of pine trees to the N2O and CH4 exchange of the boreal pine forest seems to increase considerably under high soil water content, thus highlighting the urgent need to include tree-emissions in greenhouse gas emission inventories.

Potential and limitations of inferring ecosystem photosynthetic capacity from leaf functional traits.

The aim of this study was to systematically analyze the potential and limitations of using plant functional trait observations from global databases versus in situ data to improve our understanding of vegetation impacts on ecosystem functional properties (EFPs). Using ecosystem photosynthetic capacity as an example, we first provide an objective approach to derive robust EFP estimates from gross primary productivity (GPP) obtained from eddy covariance flux measurements. Second, we investigate the impact of synchronizing EFPs and plant functional traits in time and space to evaluate their relationships, and the extent to which we can benefit from global plant trait databases to explain the variability of ecosystem photosynthetic capacity. Finally, we identify a set of plant functional traits controlling ecosystem photosynthetic capacity at selected sites. Suitable estimates of the ecosystem photosynthetic capacity can be derived from light response curve of GPP responding to radiation (photosynthetically active radiation or absorbed photosynthetically active radiation). Although the effect of climate is minimized in these calculations, the estimates indicate substantial interannual variation of the photosynthetic capacity, even after removing site-years with confounding factors like disturbance such as fire events. The relationships between foliar nitrogen concentration and ecosystem photosynthetic capacity are tighter when both of the measurements are synchronized in space and time. When using multiple plant traits simultaneously as predictors for ecosystem photosynthetic capacity variation, the combination of leaf carbon to nitrogen ratio with leaf phosphorus content explains the variance of ecosystem photosynthetic capacity best (adjusted R2 = 0.55). Overall, this study provides an objective approach to identify links between leaf level traits and canopy level processes and highlights the relevance of the dynamic nature of ecosystems. Synchronizing measurements of eddy covariance fluxes and plant traits in time and space is shown to be highly relevant to better understand the importance of intra- and interspecific trait variation on ecosystem functioning.

Latent heat exchange in the boreal and arctic biomes.

In this study latent heat flux (λE) measurements made at 65 boreal and arctic eddy-covariance (EC) sites were analyses by using the Penman-Monteith equation. Sites were stratified into nine different ecosystem types: harvested and burnt forest areas, pine forests, spruce or fir forests, Douglas-fir forests, broadleaf deciduous forests, larch forests, wetlands, tundra and natural grasslands. The Penman-Monteith equation was calibrated with variable surface resistances against half-hourly eddy-covariance data and clear differences between ecosystem types were observed. Based on the modeled behavior of surface and aerodynamic resistances, surface resistance tightly control λE in most mature forests, while it had less importance in ecosystems having shorter vegetation like young or recently harvested forests, grasslands, wetlands and tundra. The parameters of the Penman-Monteith equation were clearly different for winter and summer conditions, indicating that phenological effects on surface resistance are important. We also compared the simulated λE of different ecosystem types under meteorological conditions at one site. Values of λE varied between 15% and 38% of the net radiation in the simulations with mean ecosystem parameters. In general, the simulations suggest that λE is higher from forested ecosystems than from grasslands, wetlands or tundra-type ecosystems. Forests showed usually a tighter stomatal control of λE as indicated by a pronounced sensitivity of surface resistance to atmospheric vapor pressure deficit. Nevertheless, the surface resistance of forests was lower than for open vegetation types including wetlands. Tundra and wetlands had higher surface resistances, which were less sensitive to vapor pressure deficits. The results indicate that the variation in surface resistance within and between different vegetation types might play a significant role in energy exchange between terrestrial ecosystems and atmosphere. These results suggest the need to take into account vegetation type and phenology in energy exchange modeling.

Field and controlled environment measurements show strong seasonal acclimation in photosynthesis and respiration potential in boreal Scots pine.

Understanding the seasonality of photosynthesis in boreal evergreen trees and its control by the environment requires separation of the instantaneous and slow responses, as well as the dynamics of light reactions, carbon reactions, and respiration. We determined the seasonality of photosynthetic light response and respiration parameters of Scots pine (Pinus sylvestris L.) in the field in southern Finland and in controlled laboratory conditions. CO2 exchange and chlorophyll fluorescence were measured in the field using a continuously operated automated chamber setup and fluorescence monitoring systems. We also carried out monthly measurements of photosynthetic light, CO2 and temperature responses in standard conditions with a portable IRGA and fluorometer instrument. The field and response measurements indicated strong seasonal variability in the state of the photosynthetic machinery with a deep downregulation during winter. Despite the downregulation, the photosynthetic machinery retained a significant capacity during winter, which was not visible in the field measurements. Light-saturated photosynthesis (P sat) and the initial slope of the photosynthetic light response (α) obtained in standard conditions were up to 20% of their respective summertime values. Respiration also showed seasonal acclimation with peak values of respiration in standard temperature in spring and decline in autumn. Spring recovery of all photosynthetic parameters could be predicted with temperature history. On the other hand, the operating quantum yield of photosystem II and the initial slope of photosynthetic light response stayed almost at the summertime level until late autumn while at the same time P sat decreased following the prevailing temperature. Comparison of photosynthetic parameters with the environmental drivers suggests that light and minimum temperature are also decisive factors in the seasonal acclimation of photosynthesis in boreal evergreen trees.

Assimilate transport in phloem sets conditions for leaf gas exchange.

Carbon uptake and transpiration in plant leaves occurs through stomata that open and close. Stomatal action is usually considered a response to environmental driving factors. Here we show that leaf gas exchange is more strongly related to whole tree level transport of assimilates than previously thought, and that transport of assimilates is a restriction of stomatal opening comparable with hydraulic limitation. Assimilate transport in the phloem requires that osmotic pressure at phloem loading sites in leaves exceeds the drop in hydrostatic pressure that is due to transpiration. Assimilate transport thus competes with transpiration for water. Excess sugar loading, however, may block the assimilate transport because of viscosity build-up in phloem sap. Therefore, for given conditions, there is a stomatal opening that maximizes phloem transport if we assume that sugar loading is proportional to photosynthetic rate. Here we show that such opening produces the observed behaviour of leaf gas exchange. Our approach connects stomatal regulation directly with sink activity, plant structure and soil water availability as they all influence assimilate transport. It produces similar behaviour as the optimal stomatal control approach, but does not require determination of marginal cost of water parameter.