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Species composition of temperate forests vary with successional age (i.e., years after a major disturbance) and seems likely to change in response to significant global climate change. Because photosynthesis rates in co-occurring tree species can differ in their sensitivity to environmental conditions, these changes in species composition are likely to alter the carbon dynamics of temperate forests. To help improve our understanding of such atmosphere-biosphere interactions, we explored changes in leaf-level photosynthesis in a 60-70 yr old temperate mixed-deciduous forest in Petersham, Massachusetts (USA). Diurnally and seasonally varying environmental conditions differentially influenced in situ leaf-level photosynthesis rates in the canopies of four mature temperature deciduous tree species: red oak (Quercus rubra), red maple (Acer rubrum), white birch (Betula papyrifera), and yellow birch (Betula alleghaniensis). We measured in situ photosynthesis at two heights within the canopies (top of the canopy at ∼ 20 m, and in the sub-canopy of the same individual trees at ∼ 14-16 m) through a diurnal time course on 7 d over two growing seasons. We simultaneously measured a suite of environmental conditions surrounding the leaf at the time of each measurement. We used path analysis to examine the influence of environmental factors on in situ photosynthesis in the tree canopies. Overall, red oak had the highest photosynthesis rates, followed by white birch, yellow birch, and red maple. There was little evidence for a substantial midday depression in photosynthesis. Instead, photosynthesis declined throughout the day, particularly after 1600. Diurnal patterns of light reaching canopy leaves, leaf and air temperature, and vapor pressure deficit (VPD) contributed to diurnally varying photosynthesis rates. Large differences in these parameters through the growing season partly led to the seasonal differences observed in photosynthesis rates. Path analyses helped to identify the relative contribution of various environmental factors on photosynthesis and further revealed that species-specific sensitivities to various environmental conditions shifted through the season. Red oak photosynthesis was particularly sensitive to air temperatures late in the season when air temperatures were low. Further, red maple photosynthesis was particularly sensitive to high VPDs through the growing season. Incorporating data on the physiological differences among tree species into forest carbon models will greatly improve our ability to predict alterations to the forest carbon budgets under various environmental scenarios such as global climate change, or with differing species composition.

There is a critical need for sensitive remote sensing approaches to monitor the parameters governing photosynthesis, at the temporal scales relevant to their natural dynamics. The photochemical reflectance index (PRI) and chlorophyll fluorescence (F) offer a strong potential for monitoring photosynthesis at local, regional, and global scales, however the relationships between photosynthesis and solar induced F (SIF) on diurnal and seasonal scales are not fully understood. This study examines how the fine spatial and temporal scale SIF observations relate to leaf level chlorophyll fluorescence metrics (i.e., PSII yield, YII and electron transport rate, ETR), canopy gross primary productivity (GPP), and PRI. The results contribute to enhancing the understanding of how SIF can be used to monitor canopy photosynthesis. This effort captured the seasonal and diurnal variation in GPP, reflectance, F, and SIF in the O2A (SIFA) and O2B (SIFB) atmospheric bands for corn (Zea mays L.) at a study site in Greenbelt, MD. Positive linear relationships of SIF to canopy GPP and to leaf ETR were documented, corroborating published reports. Our findings demonstrate that canopy SIF metrics are able to capture the dynamics in photosynthesis at both leaf and canopy levels, and show that the relationship between GPP and SIF metrics differs depending on the light conditions (i.e., above or below saturation level for photosynthesis). The sum of SIFA and SIFB (SIFA+B), as well as the SIFA+B yield, captured the dynamics in GPP and light use efficiency, suggesting the importance of including SIFB in monitoring photosynthetic function. Further efforts are required to determine if these findings will scale successfully to airborne and satellite levels, and to document the effects of data uncertainties on the scaling.

Solar‐induced fluorescence (SIF) is a proxy of ecosystem photosynthesis that often scales linearly with gross primary productivity (GPP) at the canopy scale. However, the mechanistic relationship between GPP and SIF is still uncertain, especially at smaller temporal and spatial scales. We deployed a ultra‐hyperspectral imager over two grassland sites in California throughout a soil moisture dry down. The imager has high spatial resolution that limits mixed pixels, enabling differentiation between plants and leaves within one scene. We find that imager SIF correlates well with diurnal changes in leaf‐level physiology and gross primary productivity under well‐watered conditions. These relationships deteriorate throughout the dry down event. Our results demonstrate an advancement in SIF imaging with new possibilities in remotely sensing plant canopies from the leaf to the ecosystem. These data can be used to resolve outstanding questions regarding SIF's meaning and usefulness in terrestrial ecosystem monitoring. Plain Language Summary Estimating the rate of carbon uptake by vegetation across space and time remains a challenge. Solar‐induced fluorescence (SIF), the emission of light by vegetation during photosynthesis, has recently emerged as a potential estimate of carbon uptake in many ecosystems and is observable from both satellites and ground‐based sensors. Here we present results from a field campaign with a novel SIF instrument that creates images (akin to a photo) across a landscape, allowing for SIF measurements from individual leaves, plants, or areas of interest. We find that SIF retrievals from the imager correspond to seasonal variations in carbon dioxide fixation rates and leaf‐level physiology relating to photosynthesis. We use this novel technology to improve understanding of SIF and carbon uptake across spatial and temporal scales. Key Points Novel imagery technology enables solar‐induced fluorescence (SIF) acquisition across space and time SIF diurnal and seasonal variations correspond to carbon fluxes and environmental conditions Imaging capacity predicts leaf‐level physiology across leaf, plant, and landscape scales

Rainfall thresholds under which forests grow in Central Africa are lower than those of Amazonia and southeast Asia. Attention is thus regularly paid to rainfall whose seasonality and interannual variability has been shown to control Central African forests' water balance and photosynthetic activity. Nonetheless, light availability is also recognized as a key factor to tropical forests. Therefore this study aims to explore the light conditions prevailing across Central Africa, and their potential impact on forests' traits. Using satellite estimates of hourly irradiance, we find first that the four main types of diurnal cycles of irradiance extracted translate into different levels of rainfall, evapotranspiration, direct and diffuse light. Then accounting for scale interactions between the diurnal and annual cycles, we show that the daily quantity and quality of light considerably vary across Central African forests during the annual cycle: the uniqueness of western Central Africa and Gabon in particular, with strongly light-deficient climates especially during the main dry season, points out. Lastly, using an original map of terra firme forests, we also show that most of the evergreen forests are located in western Central Africa and Gabon. We postulate that despite mean annual precipitation below 2000 mm yr−1, the light-deficient climates of western Central Africa can harbour evergreen forests because of an extensive low-level cloudiness developing during the June-September main dry season, which strongly reduces the water demand and enhances the quality of light available for tree photosynthesis. These findings pave the way for further analyses of the past and future changes in the light-deficient climates of western Central Africa and the vulnerability of evergreen forests to these changes.

Forest ecosystem models based on heuristic water stress functions poorly predict tropical forest response to drought partly because they do not capture the diversity of hydraulic traits (including variation in tree size) observed in tropical forests. We developed a continuous porous media approach to modeling plant hydraulics in which all parameters of the constitutive equations are biologically interpretable and measurable plant hydraulic traits (e.g., turgor loss point πtlp, bulk elastic modulus [straight epsilon], hydraulic capacitance Cft, xylem hydraulic conductivity ks,max, water potential at 50% loss of conductivity for both xylem (P50,x) and stomata (P50,gs), and the leaf:sapwood area ratio Al : As). We embedded this plant hydraulics model within a trait forest simulator (TFS) that models light environments of individual trees and their upper boundary conditions (transpiration), as well as providing a means for parameterizing variation in hydraulic traits among individuals. We synthesized literature and existing databases to parameterize all hydraulic traits as a function of stem and leaf traits, including wood density (WD), leaf mass per area (LMA), and photosynthetic capacity (Amax), and evaluated the coupled model (called TFS v.1-Hydro) predictions, against observed diurnal and seasonal variability in stem and leaf water potential as well as stand-scaled sap flux. Our hydraulic trait synthesis revealed coordination among leaf and xylem hydraulic traits and statistically significant relationships of most hydraulic traits with more easily measured plant traits. Using the most informative empirical trait-trait relationships derived from this synthesis, TFS v.1-Hydro successfully captured individual variation in leaf and stem water potential due to increasing tree size and light environment, with model representation of hydraulic architecture and plant traits exerting primary and secondary controls, respectively, on the fidelity of model predictions. The plant hydraulics model made substantial improvements to simulations of total ecosystem transpiration. Remaining uncertainties and limitations of the trait paradigm for plant hydraulics modeling are highlighted.

Estimates of the gross terrestrial carbon uptake exhibit large uncertainties. Sun-induced chlorophyll fluorescence (SIF) has an apparent near-linear relationship with gross primary production (GPP). This relationship will potentially facilitate the monitoring of photosynthesis from space. However, the exact mechanistic connection between SIF and GPP is still not clear. To explore the physical and physiological basis for their relationship, we used a unique data set comprising continuous field measurements of leaf and canopy fluorescence and photosynthesis of corn over a growing season. We found that, at canopy scale, the positive relationship between SIF and GPP was dominated by absorbed photosynthetically active radiation (APAR), which was equally affected by variations in incoming radiation and changes in canopy structure. After statistically controlling these underlying physical effects, the remaining correlation between far-red SIF and GPP due solely to the functional link between fluorescence and photosynthesis at the photochemical level was much weaker (ρ=0.30). Active leaf level fluorescence measurements revealed a moderate positive correlation between the efficiencies of fluorescence emission and photochemistry for sunlit leaves in well-illuminated conditions but a weak negative correlation in the low-light condition, which was negligible for shaded leaves. Differentiating sunlit and shaded leaves in the light use efficiency (LUE) models for SIF and GPP facilitates a better understanding of the SIF–GPP relationship at different environmental and canopy conditions. Leaf level fluorescence measurements also demonstrated that the sustained thermal dissipation efficiency dominated the seasonal energy partitioning, while the reversible heat dissipation dominated the diurnal leaf energy partitioning. These diurnal and seasonal variations in heat dissipation underlie, and are thus responsible for, the observed remote-sensing-based link between far-red SIF and GPP.

We report on diurnal, tidal, and seasonal variations of dissolved inorganic carbon (DIC), water partial pressure of CO2 (pCO2), and associated water–air CO2 fluxes in a tidal creek of a temperate coastal lagoon with 70% of intertidal flats, during eight tidal/diurnal cycles and two consecutive years covering all seasons. Surface waters of the lagoon were always slightly oversaturated in CO2 with respect to the atmosphere with an average pCO2 value of 496 ± 36 ppmv. Seasonally, subsurface water pCO2 values were controlled by both temperature and biological/tidal advection effects that compensated each other and resulted in weak annual variations. High-resolution temporal pCO2 records reveal that the highest fluctuations (192 ppmv) occurred at the tidal/diurnal scale as a result of biological activity, advection from the tidal flat, and porewater pumping that all contributed to water pCO2 and carbonate chemistry variations. Total alkalinity (TA) versus salinity plots suggest a net production of alkalinity in the lagoon attributed to benthic carbonate dissolution and/or anaerobic degradation of organic matter. We specifically highlighted that for the same salinity range, during flooding, daytime pCO2 were generally lower than nighttime pCO2 values because of photosynthesis, whereas during ebbing, daytime pCO2 were higher than nighttime pCO2 values because of heating. Waters in the lagoon were a relatively weak CO2 source to the atmosphere over the year compared to other estuarine and lagoon waters elsewhere, and to sediment-air fluxes measured simultaneously by atmospheric Eddy Covariance (EC) in the Arcachon lagoon. Because of low values and small variations of the air-sea pCO2 gradient, the variability of fluxes calculated using the piston velocity parameterization was greatly controlled by the wind speed at the diurnal and, to a lesser extent, seasonal time scales. During the emersion, the comparison of these pCO2 data in the tidal creek with EC fluxes measured 1.8 km away on the tidal flat suggests high heterogeneity in air-sea CO2 fluxes, both spatially and at short time scales according to the inundation cycle and the wind speed. In addition to tidal pumping when the flat becomes emerged, our data suggest that lateral water movement during the emersion of the flat generates strong spatial heterogeneity in water–air CO2 flux.

Atmospheric CO2 mole fractions are observed at Beijing (BJ), Xianghe (XH), and Xinglong (XL) in North China using Picarro G2301 cavity ring-down spectroscopy instruments. The measurement system is described comprehensively for the first time. The geographical distances among these three sites are within 200 km, but they have very different surrounding environments: BJ is inside the megacity; XH is in the suburban area; XL is in the countryside on a mountain. The mean and standard deviation of CO2 mole fractions at BJ, XH, and XL between October 2018 and September 2019 are448.4±12.8, 436.0±9.2, and420.6±8.2 ppm, respectively. The seasonal variations ofCO2 at these three sites are similar, with a maximum in winter and a minimum in summer, which is dominated by the terrestrial ecosystem. However, the seasonal variations of CO2 at BJ and XH are more affected by human activities as compared to XL. Using CO2 at XL as the background,CO2 enhancements are observed simultaneously at BJ and XH. The diurnal variations of CO2 are driven by the boundary layer height, photosynthesis, and human activities at BJ, XH, and XL. We also compare theCO2 measurements at BJ, XH, and XL with five urban sites in the USA, and it is found that the CO2 mean concentration at BJ is the largest. Moreover, we address the impact of the wind on the CO2 mole fractions at BJ and XL. This study provides an insight into the spatial and temporal variations ofCO2 mole fractions in North China.

Lack of knowledge still remains on many processes leading to carbonyl sulfide (COS) atmospheric fluxes, either natural, such as the oceanic sources or the vegetation and soil uptakes, or anthropogenic, with emissions from industrial activities and power generation. Moreover, COS atmospheric mixing ratio data are still too sparse to evaluate the estimations of these sources and sinks at the regional scale; in this context, regional estimates are very challenging. This study assesses the anthropogenic emissions and biogenic COS uptakes at the regional scale, in the footprint of a measurement site in western Europe, at a seasonal to diurnal time resolution over half a decade. The continuous time series of COS mixing ratios obtained at the monitoring site of Gif-sur-Yvette (GIF; in the Paris region) from August 2014 to December 2019 are compared to simulations with the Lagrangian model FLEXPART (FLEXible PARTicle), transporting oceanic sources, biogenic land fluxes from the land surface models ORCHIDEE and SiB4 (Simple Biosphere Model), and anthropogenic emissions by two different inventories. At GIF, the seasonal variations in COS mixing ratios are dominated by the contributions of the background and ocean, the weekly to daily variations are driven by the biogenic land contribution and anthropogenic emissions may dominate for short episodes of high concentrations. The anthropogenic emission inventory based on reported industrial emissions and the characteristics of coal power plants in Europe is consistent with the observations. The main limitation of this inventory is the flat temporal variability applied to anthropogenic fluxes due to the lack of information on industrial and power-generation activities in viscose factories and in coal power plants. As a consequence, there are potential mismatches in the simulated plumes emitted from these hot spots. We find that the net ecosystem COS uptake simulated by both ORCHIDEE and SiB4 is underestimated in winter at night, which suggests improvements in the parameterization of the nighttime uptake by plants for COS. In spring, SiB4 simulates persistent nighttime uptake by vegetation, which is different than ORCHIDEE, which leads to more realistic simulations with SiB4 than with ORCHIDEE. In summer, both models represent fluxes sufficiently well, with better agreement from ORCHIDEE in terms of magnitudes.

Variations in the δ(18O) of atmospheric O2, δatm(18O), are an indicator of biological and water processes associated with the Dole–Morita effect (DME). The DME and its variations have been observed in ice cores for paleoclimate studies; however, variations in present-day δatm(18O) have never been detected so far. Here, we present diurnal, seasonal, and interannual variations of δatm(18O) based on observations at a surface site in central Japan. The average diurnal δatm(18O) cycle reached a minimum during the daytime, and its amplitude was larger in summer than in winter. We found that use of δatm(18O) enabled separation of variations of atmospheric δ(O2/N2) into contributions from biological activities and fossil fuel combustion. The average seasonal δatm(18O) cycle reached at a minimum in summer, and the peak-to-peak amplitude was about 2 per meg (1 per meg is 0.001 ‰). A box model that incorporated biological and water processes reproduced the general characteristics of the observed diurnal and seasonal cycles. A slight but significant secular increase in δatm(18O) by (0.22 ± 0.14) per meg a−1 occurred during 2013–2022. Secular changes in δatm(18O) were also simulated by using the box model considering long-term changes in terrestrial gross primary production (GPP), photorespiration, and δ(18O) of leaf water (δLW(18O)). We calculated changes in δLW(18O) using a state-of-the-art, three-dimensional model, MIROC5-iso. The observed secular increase in δatm(18O) was reproduced by the box model that incorporated the isotopic effects associated with the DME from Bender et al. (1994), while the simulated δatm(18O) showed a secular decrease when the model incorporated the isotopic effects from Luz and Barkan (2011). Therefore, long-term observations of δatm(18O) and better understanding of the DME are indispensable for an application of δatm(18O) to constrain long-term changes in global GPP and photorespiration.