Emerging constraints of photosynthesis (including chlorophyll fluorescence), respiration, and transpiration at ecosystem to global scales
Gross photosynthetic CO2 uptake is the single largest component of the global carbon cycle and a crucial variable for monitoring and understanding global biogeochemical cycles and fundamental ecosystem services. Nowadays routine measurements of the net biosphere-atmosphere CO2 exchange are conducted at the ecosystem scale in a large variety of ecosystem types across the globe. Gross photosynthetic and ecosystem respiratory fluxes are then typically inferred from the net CO2 exchange and used for benchmarking of terrestrial biosphere models or as backbones for upscaling exercises. Uncertainty in the responses of photosynthesis and respiration to the climate and environmental conditions is a major source of uncertainty in predictions of ecosystem-atmosphere feedbacks under climate change. On the other hand transpiration estimates both at ecosystem to global scales are highly uncertain with estimates ranging from 20 to 90 % of total evapotranspiration. The most important bottleneck to narrow down the uncertainty in transpiration estimates is the fact that direct measurements of transpiration are uncertain and techniques like eddy covariance measure only the total evapotranspiration.
During the last decade, technological developments in field spectroscopy, near surface remote sensing, including sun-induced fluorescence, isotope flux measurements and quantum cascade lasers have enabled alternative approaches for constraining ecosystem-scale photosynthesis, respiration and transpiration. On the other hand a variety of approaches have been developed to directly assess the gross fluxes of CO2 and transpiration by using both process based and empirical models, and machine learning techniques.
In this session we aim at reviewing recent progress made with novel approaches of constraining ecosystem gross photosynthesis, respiration and transpiration and at discussing their weaknesses and future steps required to reduce the uncertainty of present-day estimates. To this end we are seeking contributions that use emerging constrains to improve the ability to quantify respiration and photosynthesis processes, transpiration and water use efficiency, at scales from leaf to ecosystem and global. Particularly welcome are studies reporting advancements and new developments in CO2 and evapotranspiration flux partitioning from eddy covariance data, the use of carbonyl sulfide, stable isotopes approaches, and sun-induced fluorescence.
Kaniska Mallick, Dennis Baldocchi, Andrew Jarvis, Ivonne Trebs, Mauro Sulis, and Joseph Berry
Evapotranspiration (EET) observed by eddy covariance (EC) towers is composed of physical evaporation (EE) from wet surfaces and biological transpiration (ET), that involves soil moisture uptake by roots and water vapor transfer regulated through the canopy-stomatal conductance (gC) during photosynthesis. ET plays a dominant role in the global water cycle and represents 80% of the total terrestrial EET. Understanding the magnitude and variability of ET are critical to assess the ecophysiological responses of vegetation to drought. While separating ET signals from lumped EET observations and/or simulating ET by terrestrial systems models is insufficiently constrained owing to the large uncertainties in disentangling gC from the aggregated canopy-substrate conductance (gcS), evaluating ecosystem ET derived through partitioning EET observations (or model simulation) is also challenging due to the absence of any ecosystem-scale measurements of this biotic flux and gC. To date, the main methods for partitioning EC-EET observations are largely based on regressing EET with gross photosynthesis (Pg) and atmospheric vapor pressure deficit (DA) observations. However, such methods ignore the essential feedback of the surface energy balance (SEB) and canopy temperature (TC) on gC and ET.
This study demonstrates partitioning EET observations into ET and EE [soil evaporation (EEs) and interception evaporation (EEi)] through an ‘analytical solution’ of gC, TC and canopy vapor pressures by employing a Shuttleworth-Gurney vegetation-substrate energy balance model with minimal complexity. The model is called TRANSPIRE (Top-down partitioning evapotRANSPIRation modEl), which ingests remote sensing land surface temperature (LST) and leaf area index (Lai) information in conjunction with meteorological, sensible heat flux (H) and EET observations from EC tower into the SEB equations for retrieving canopy and soil temperatures (TS, TC), gC, and ET.
ET estimates from TRANSPIRE were tested and evaluated with a remote sensing based ET estimate from an analytical model (STIC1.2), where lumped EET was partitioned by employing a moisture availability constraints across an aridity gradient in the North Australian Tropical Transect (NATT) by using time-series of 8-day MODIS Terra LST and LAI products in conjunction with EC measurements from 2011 to 2018. Both methods captured the seasonal pattern of ET/EET ratio in a very similar way. While ET accounted for 60±10% of the annual EET in the tropical savanna, ET in the arid mulga contributed 75±12% of the annual EET. Seasonal variation of ET was higher in the arid, semi-arid ecosystems (50 - 90%), as compared to the humid tropical ecosystem (10 - 50%). The TRANSPIRE model reasonably captured ET variations along with soil moisture and precipitation dynamics in both sparse and homogeneous vegetation and showed the potential of partitioning EET observations for cross-site comparison with a variety of models.
How to cite:
Mallick, K., Baldocchi, D., Jarvis, A., Trebs, I., Sulis, M., and Berry, J.: Disentangling ecosystem transpiration from evapotranspiration observations employing simplified vegetation-substrate energy balance model, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-5193, https://doi.org/10.5194/egusphere-egu2020-5193, 2020.
Minsu Lee, Juhan Park, Sungsik Cho, and Hyun-Seok Kim
Transpiration and photosynthesis are connected each other through stomata, therefore, biomass increment of trees should have close relationships with their water use. However, the relationship is species specific and it is also dependent on various biotic and abiotic factors. The purpose of this study is to investigate the relationship of sapflux with diameter increment of individual trees among six different species using Granier type sapflow sensors and diameter growth band installed from 2012. The growth of two conifer (Pinus koraiensis, Abies holophylla), five broadleaf (Quercus aliena, Q. variabilis, Q. serrata, Carpinus laxiflora, C. cordata) were investigated at Mt. Taehwa and Gwangneung National Arboretum. Net Primary Production was calcualted based on speceis specific allometric equations. The relationship between sapflux density and diameter growth was different among species. For example, Q. aliena and A. holophylla had positive relationship between sapflux density and diameter growth (p = 0.037 and p =0.001, respectively), while P. koraiensis did not follow the trend (p = 0.5). However, when tree level transpiration was calculated by mulitiplying sapflux density with its sapwood area. In general, all species showed significant positive correlations between the transpiration and NPP (e.g., P. koraiensis(p = 0.003), Q. aliena and A. holophylla(p <0.001). In addition, comparison between conifer and broad leaves species, the conifers show the bigger changes in diameter growth and eventually NPP than that of the broad leaves tree in the same change of transpiration. Therefore, WUE for biomass increment was higher in conifer than broadleaf species.
How to cite:
Lee, M., Park, J., Cho, S., and Kim, H.-S.: Species-specific relationship between sapflux density and diameter growth rates for six years, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-21022, https://doi.org/10.5194/egusphere-egu2020-21022, 2020.
Dan Yakir, Rafat Qubaja, Madi Amer, Fyodor Tatarinov, Eyal Rotenberg, and Yakir Preisler
Soil evaporation (Es) is a significant hydrological component in dry ecosystems and its quantification is critical to the understanding of ecosystem response to change. It is, however, often estimated as a residual in the hydrological balance because of measurement difficulties. Here, we use continuous, high precision chamber-based direct measurements of soil evaporation (Es) in a semi-arid Pinus halepensis forest to partition eddy covariance-based evapotranspiration (ET) to Es and tree transpiration (Et) and assess its daily and seasonal dynamics, and for comparison with measurements carried out at the same site ten years earlier. The ecosystem is characterized by a high annual Es/ET ratio of 0.26, and an Et/ET of 0.63. Es diminished in the long dry season, but as much as 74 ± 5% of the residual flux was due to the re-evaporation of nighttime moisture adsorption (negative Es), which may provide critical protection from soil drying in summer. Across the long-term observation period (over 10 years), an increase in the transpiration ratio (ΔTR, where TR=Et/ET) of +29% (from 0.49 to 0.63) was associated with the increase in leaf area index (LAI) of +44% observed. However, the ratio of TR/LAI remained constant at ~0.31, with persistently closed hydrological balance (ET/P of 0.94 to 1.07). Rainfall use efficiency (the ratio of annual net primary production/annual precipitation; NPP/P) was on average 0.82 (g C m-2/Kg H2O) across the observation period. The observed mean Et/ET values are similar to the estimated global mean values (0.64 ± 0.13), but are attained at a much higher aridity index of 5.5 than the mean one, reflecting adjustments that indicate the potential for expanding forestation into dry regions, and highlight the importance of soil evaporation fluxes in low-density semi-arid forests.
How to cite:
Yakir, D., Qubaja, R., Amer, M., Tatarinov, F., Rotenberg, E., and Preisler, Y.: Long-term evolution of evapotranspiration components in a semi-arid forest using chambers measurement of soil evaporation, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-21335, https://doi.org/10.5194/egusphere-egu2020-21335, 2020.
Antoine Vernay, Xianglin Tian, Jose Lopez, Niles Hasselquist, Annikki Mäkelä, Ram Oren, Pantana Tor-ngern, Zsofia R Stangl, and John D Marshall
Stand-scale estimates of gross primary production (GPP) commonly depend on eddy-covariance or eddy-covariance derived models. Chamber-based methods provide an alternative, but they are tricky to scale up to the stand. We estimate GPP by combining isotopic δ13C of phloem sugars with sap-flow measurements. The method consists of calculating intrinsic water-use efficiency and transpiration to determine GPP. We have improved this approach by considering mesophyll conductance and seasonal variation in photosynthetic capacity and then compared our results to a semi-empirical eddy-covariance based model, PRELES. We compared a fertilised plot and an unfertilised plot in a monospecific Scots pine forest in northern Sweden. The method captured both the stand response to fertilisation and seasonal patterns, as PRELES did. Our results demonstrate the importance of considering a finite mesophyll conductance value to avoid an unreasonable overestimate of GPP. We have now applied the method in a mixed boreal forest where we will partition total stand GPP among the three dominant tree species (pine, spruce, and birch). This approach provides an independent test of GPP estimates and provides a means of estimating GPP where eddy-covariance assumptions are not met.
How to cite:
Vernay, A., Tian, X., Lopez, J., Hasselquist, N., Mäkelä, A., Oren, R., Tor-ngern, P., Stangl, Z. R., and Marshall, J. D.: Combining isotopic and sap flux data to estimate GPP: an alternative ecophysiological approach to eddy-covariance based data, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-6776, https://doi.org/10.5194/egusphere-egu2020-6776, 2020.
Denmark experienced a severe drought in 2018 lasting from the beginning of May to the end of August with very little rain during this period. The influence of drought on the net ecosystem CO2 exchange (NEE) was analysed at the Danish ICOS DK-Soroe site (a mature beech forest). The site has a very long continuous flux data set starting in June 1996. The annual NEE of the site has been increasing over the years, mainly due to a prolonged growing season in the autumn and CO2 fertilisation (Pilegaard et al., 2011).
The effect of the summer drought in 2018 was analysed by means of linear trend estimation based on monthly trends during 1996-2017. The observed monthly NEE in 2018 was compared to the predicted values from the monthly time series.
The analysis showed an increased NEE in May and June and a strongly reduced NEE in July and August. Overall, the NEE was reduced 25% compared to the predicted value.
The increased NEE in May and June can be explained by the benefit for the photosynthesis of the trees of the increased light and temperature, while there was still a sufficient water content in the soil. By the end of June, the low water content in the soil affected the NEE, and despite some heavy rain in the beginning of August, the NEE only recovered by September.
We used the flux data set together with a mechanistic canopy model to examine the tree physiological nature of the photosynthesis limitation. The results showed that stomatal limitation alone was not able to explain the large reduction of GPP during the drought. Based on these findings, we extended the approach and show the seasonal development of drought induced GPP limitation contrasting stomatal and biochemical photosynthesis limitations.
The effects on NEE and energy partitioning during the 2018 summer drought are compared to previous years with (less severe) summer drought.
Kim Pilegaard, Andreas Ibrom, Michael S. Courtney, Poul Hummelshøj, Niels Otto Jensen. Increasing net CO2 uptake by a Danish beech forest during the period from 1996 to 2009. Agricultural and Forest Meteorology 151 (2011) 934–946.
The study was based on data from ICOS/DK.
How to cite:
Pilegaard, K. and Ibrom, A.: Evaluating the effect of the 2018 drought on the NEE in the Sorø beech forest by means of trend analysis and mechanistic canopy modelling of GPP., EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-13917, https://doi.org/10.5194/egusphere-egu2020-13917, 2020.
Felix M. Spielmann, Albin Hammerle, Alexander Knohl, Malte Julian Deventer, and Georg Wohlfahrt
The gross uptake of CO2 on ecosystem level (GPP) can’t be measured directly, but has to be inferred from models or proxies. One of the newly emerged constrains on GPP is the trace gas carbonyl sulfide (COS). COS enters the plant leaf through the stomata and diffuses through the intercellular space, the cell wall, the plasma membrane and the cytosol like CO2. Within the cytosol, it is then catalyzed by the enzyme carbonic anhydrase (CA) in a one-way reaction to H2S and CO2. Basically, this one way flux would make COS a very promising tracer for GPP on ecosystem level, but there is growing evidence that plants are also capable of emitting COS. Mosses and even vascular plants that are under high stress like drought and fungal infection, have been reported to emit COS. Furthermore, a winter wheat field, that showed a good correlation between the CO2 and COS ecosystem fluxes during the peak growing phase turned into a source for COS after going into senescence. This indicates that yet unknown COS emission processes likely related to plant degradation, could complicate the use of COS as a tracer for GPP.
Since the majority of studies have focused on measuring COS ecosystem fluxes during peak growing times or on evergreen forests, we seek to quantify the relationship between the ecosystem-scale exchange of CO2 and COS of an ecosystem going into senescence.
Between September and November 2019 we deployed our quantum cascade laser (Aerodyne Research Inc., MA, USA) at a beech forest in Leinefelde, Germany to conduct eddy covariance measurements for COS, CO2 and H2O. Our observations started when the beech forest was still green and in full leaf and ended when most of the trees had already shed their leaves. The ecosystem fluxes of COS and CO2 concurrently decreased over the course of our campaign up to the point when we could not observe a net uptake of CO2 anymore. We will further compare the GPP estimates resulting from classical flux partitioning and flux partitioning with the additional use of COS to determine if the model differences increase towards the end of the season.
How to cite:
Spielmann, F. M., Hammerle, A., Knohl, A., Deventer, M. J., and Wohlfahrt, G.: Winter is coming – ecosystem-scale COS exchange during senescence of a deciduous forest, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-8871, https://doi.org/10.5194/egusphere-egu2020-8871, 2020.
Amnon Cochavi, Madi Amer, Rafael Stern, and Dan Yakir
Springtime heatwaves are common phenomena in the Mediterranean region, named ‘Sharav’ or ‘Hamsin’. During these heatwaves, air temperatures (Ta) and vapor pressure demand (VPD) increase rapidly over 3-5 days, followed by a dramatic drop of at least 5℃ in Ta and 1 kPa in VPD back to the pre-event values.
Here, we used our mobile lab in an irrigated lemon orchard in Rehovot, Israel to carry out eddy covariance (EC) flux measurements of net ecosystem exchange of CO2 (NEE), water vapor, and carbonyl sulfide (COS), as well as canopy Sun-induced fluorescence (SIF) together with other spectral indices (NDVI, PRI, NIRv). This was supplemented with leaf-scale measurements of Pulse Amplitude modulated (PAM). Five heatwave events were detected during a two-months measurement campaign. Two other events were defined as intermediate days, with VPD values higher than normal but lower than in the full-scale heatwaves.
During both the heatwave and intermediate days, the COS fluxes (Fcos), far-red SIF, and electron transport rate (ETR), decreased during midday to the same level, compared to the control days. In contrast, NEE responded differentially between the heatwave and intermediate days, with midday values of -5.9±0.9, -3.7±0.7 and -0.69±0.62 µmol m-2s-1 CO2, in the control, intermediate and heatwave days, respectively. No differences were detected in both NDVI and NIRv values. The PRI index, related to energy transfer through the non-photochemical quenching (NPQ) pathway, showed a similar pattern to that of NEE. The recovery of the ecosystem from the heatwave events was rapid and occurred within a day after the end of the events.
The results indicate a link between the far-red SIF and the ETR in the response to the heatwaves. Moreover, the reduction in far-red SIF was negatively associated with the increase in NPQ, which was reflected in both the spectral (PRI) and the PAM (NPQ value) measurements. The observed decrease in Fcos is expected to reflect a decrease in stomatal conductance to a similar extent in the heatwave and intermediate days. However, the lower rate of CO2 assimilation in the full-scale heat wave days suggests that additional factors further decreased its rates beyond that limited by conductance. This can be related to the increased effect of the heat stress on other energy-demanding pathways (e.g. photorespiratory, isoprene production) that can suppress net assimilation in these days.
This work demonstrated that the relation between carbon assimilation and far-red SIF can be complex, and that combining SIF and COS measurements can help partition the effects of heat stress on conductance and other physiological effects.
How to cite:
Cochavi, A., Amer, M., Stern, R., and Yakir, D.: Using Sun-induced fluorescence and Carbonyl Sulfide flux to assess the response to seasonal heatwave in a citrus orchard, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-8440, https://doi.org/10.5194/egusphere-egu2020-8440, 2020.
Shari Van Wittenberghe, Valero Laparra, Nacho Ignacio Garcia, Luis Alonso, Beatriz Fernandez Marín, Zbynek Malenovsky, Albert Porcar-Castell, and Jose Moreno
The solar energy absorbed by the vegetation light-harvesting antenna complexes supplies the photosynthetic light reactions with a highly efficient transfer of quantum energy. The absorbed energy is efficiently transferred from one molecule to another, until being used by the reaction centres for the further carbon reactions. The energy transfer to the reaction centres is hereby highly regulated by the variable aggregation of pigments in the antenna complexes, allowing for quick and slower adjustments according to the incoming solar radiance. To control and protect the pigment antenna and the reaction centres from a potentially harmful solar radiance excess, these regulated photoprotective mechanisms are activated at different time scales at the antenna level, allowing vegetation to adapt to changing light conditions. The understanding of these energy regulative processes from optical measurements is essential in order to monitor plants' adaptation strategies to stressful environments and changing climates from remote sensing data.
Using high-spectral resolution leaf spectroscopy in a controlled laboratory set-up, we have observed detailed and significant absorbance shifts controlled by the pigment antennas themselves. Simultaneous measurements of both upward and downward spectrally-resolved leaf radiance (Lup(λ), Ldw(λ), W m-2 sr-1 nm-1) allowed us to observe the specific absorbance changes at leaf level, including changes in chlorophyll (Chl) a fluorescence emission (Fup(λ), Fdw(λ), W m-2 sr-1 nm-1). Interestingly, these changes due to shifts in energy redistribution were: 1) observed in the PAR region and even far beyond 700 nm, and 2) indicated a prominent role of both Carotenoid and Chl a molecules in the creation of alternative energy sinks, i.e. constraining the energy transfer to the reaction centres. Hereby, a significant redistribution of photosynthetic light energy was observed in the 500-800 nm range, highlighting this spectral region to be of potential interest for remote sensing. We further revealed that these energy redistributions do not necessary occur in parallel with Chl a fluorescence changes, illustrating the importance of different energy redistribution mechanisms constraining the photosynthetic light reactions. To conclude, a good quantitative understanding of all mechanisms of energy regulation in plants based on VIS-NIR wavelengths is essential 1) to be able to understand these trends using remote sensing data, 2) to better model the adaptations of vegetation to changing climate and environmental conditions, and 3) potentially better predict future trends in dynamic global vegetation models.
How to cite:
Van Wittenberghe, S., Laparra, V., Ignacio Garcia, N., Alonso, L., Fernandez Marín, B., Malenovsky, Z., Porcar-Castell, A., and Moreno, J.: The pigment antenna constraining the light reactions: photosynthetic energy redistribution indicated by leaf absorbance changes, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-9713, https://doi.org/10.5194/egusphere-egu2020-9713, 2020.
Sebastian Wieneke, Manuela Balzarolo, Han Asard, Hamada AbdElgawad, Josep Peñuelas, Uwe Rascher, Arne Ven, Melanie Verlinden, Ivan Janssens, and Sara Vicca
Due to its close link to the photosynthetic process, sun-induced fluorescence (SIF) is one of the most promising signals to assess spatio-temporal variation in photosynthesis. Yet the positive linear relationship between SIF and photosynthesis, often reported from satellite and proximal remote sensing, contradicts findings from leaf-level studies, particularly under stress conditions. In two separate experiments, we grew Mays (Zea mays L.) under increasing phosphorus limitation and potato (Solanum tuberosum L.) under increasing drought stress to assess whether SIF can detect the phosphorus and drought induced reduction in photosynthesis. We demonstrate that the relationship between photosynthesis and APAR (absorbed photochemical active radiation) normalized SIF (FY) is non-monotonic under increasing environmental stress conditions, rendering the prediction of photosynthesis by FY alone unfeasible. The use of FY in combination with a pigment corrected photochemical reflectance index (PRI) as an indicator of the stress stage, allows the estimation of photosynthesis. However, this approach is strongly affected by uncertainties in PRI and we therefore propose the pigment-corrected ratio of the two SIF peaks (cFratio) as a precise and robust estimator of photosynthesis (R² = 0.90, rRMSE = 10%). Due to its independence on the absorbed photosynthetic active radiation, the cFratio is a promising novel estimator of spatio-temporal variation in photosynthesis.
How to cite:
Wieneke, S., Balzarolo, M., Asard, H., AbdElgawad, H., Peñuelas, J., Rascher, U., Ven, A., Verlinden, M., Janssens, I., and Vicca, S.: Non-monotonic relationship of sun-induced fluorescence to photosynthesis, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-9759, https://doi.org/10.5194/egusphere-egu2020-9759, 2020.
Maria Luisa Buchaillot, David Soba, Tianchu Shu, Liu Juan, José Luis Araus, Shawn C. Kefauver, and Alvaro Sanz-Saez
By 2050 future global food demand is projected to require a doubling of agricultural output, and climate change will exacerbate this challenge by intensifying the exposure of field crops to abiotic stress conditions, including rising temperature, increased drought, and increased CO2 concentration ([CO2]). One of the keys to improving crop yield under different stresses is studying is photosynthesis. Photosynthetic parameters, such as the maximum rate of carboxylation of RuBP (Vc,max), and the maximum rate of electron transport driving RuBP regeneration (Jmax) vary in response to climate conditions and have been identified as a target for improvement. However, the techniques used to measure these physiological parameters are very time consuming, ranging from 30 to 70 min per measurement and require specialized personnel. Therefore, breeding or genetic mapping for these traits under these conditions is prohibitively time-consuming. Spatial and temporal variation in plant photosynthesis can be estimated using remote sensing-derived spectral vegetation indices. Spectral estimates of green vegetation biomass and vigor, including vegetation indices such as the Normalized Difference Vegetation Index (NDVI), are widely used to estimate vegetation productivity across spatial and temporal scales but are unable to provide assessments of specific photosynthetic parameters. For that reason, hyperspectral remote sensing shows promise for predicting photosynthetic capacity based on more detailed leaf optical properties. In this study, we developed and assessed estimates of Vcmax and Jmax through four different advanced regression models: PLS, BR, ARDR, and LASSO based on leaf reflectance metrics measured with an ASD FieldSpec4 Hi-RES of different crops under different environmental conditions such as (1) different varieties of soybean under high [CO2] and high temperature, (2) different varieties of peanut under drought stress and (3) 20 varieties of cotton diverse origin and grown under field conditions. Both phenotypic variability and varying levels of stress were employed with each crop to ensure adequate ranges of responses. Model sensitivities were assessed for each crop and treatment separately and in combination in order to better understand the strengths and weaknesses of each model in all the different conditions. For the combination of three species, all the models suggest a robust prediction of Vcmax around R2:0.67 and the same for the Jmax R2: 0.55.
How to cite:
Buchaillot, M. L., Soba, D., Shu, T., Juan, L., Araus, J. L., Kefauver, S. C., and Sanz-Saez, A.: Use of leaf hyperspectral data and different regression models to estimate photosynthetic parameters (Vcmax and Jmax) in three different row crops , EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-18251, https://doi.org/10.5194/egusphere-egu2020-18251, 2020.
Szilvia Fóti, János Balogh, Krisztina Pintér, and Zoltán Nagy
Monitoring of canopy photosynthetic performance in optimal and stress conditions has major importance in carbon budget estimates or in precision agriculture. Photosynthesis responds very rapidly to the environmental conditions balancing photochemical processes with different other processes through which excitation energy is lost from the system, including photo-protective heat loss and fluorescent light emission. Although the ratio of photosynthesis to fluorescence in optimal and stress conditions differ, it is not an easy task to assess their actual share, because of the quick adjustment of the pigment-protein complexes or the changing intensity of light re-absorption by chlorophylls.
Sun induced fluorescence (SIF) measured by ground-based instrument provided direct data of the photosynthetic capacity of the canopy. The O2 absorptions bands filled with fluorescence served to calculate actual fluorescence intensity within the total upwelling signal. Furthermore, field leaf samples were collected and laboratory analysis was performed to determine photosynthetic pigment contents (both chlorophylls and carotenoids).
The sampling, both for SIF and pigment data collection followed spatial grid arrangements with different resolutions, 10 × 10 m and 30 × 30 m. Spatial analysis lays on a relatively large number of samples, collected within a very short time period. Our aim was to link the spatial distribution of one target phenomenon to the distribution or intensity of different driving forces, such as terrain features, soil moisture content, soil temperature etc., which were also simultaneously collected in the field work. One measuring occasion at both spatial scales were selected for detailed spatial data processing with geostatistics and kriging.
How to cite:
Fóti, S., Balogh, J., Pintér, K., and Nagy, Z.: Spatial analysis of ground-based sun induced fluorescence data and canopy pigment content in a dry grassland, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-18679, https://doi.org/10.5194/egusphere-egu2020-18679, 2020.
Kadmiel Maseyk, Holly Croft, Cheryl Rogers, Terenzio Zenone, Walter Oechel, and Donnatella Zona
The rapid warming of polar regions is having a demonstrable impact on ecosystem composition and there is a pressing need to understand the carbon cycle implications of these changes. A promising approach for investigating photosynthesis at ecosystem and regional scales involves the remote sensing of Solar Induced Fluorescence (SIF). However, ground-validation of SIF and its association with carbon assimilation and other ecophysiological parameters is largely missing from the polar regions. We will present results of measurements of ground-level SIF and hyperspectral reflectance that were coupled with CO2 exchange measurements in three contrasting polar regions: shrub and bog ecosystems in northern Sweden, wet coastal tundra in Alaska and moss turf in Antarctica. We show good agreement between SIF and photosynthesis across scales, from leaf-level to surface fluxes, but with variable relationships between ecosystem types. Our results show strong potential for using SIF to help understand the impact of change in these regions.
How to cite:
Maseyk, K., Croft, H., Rogers, C., Zenone, T., Oechel, W., and Zona, D.: Photosynthesis - Solar Induced Fluorescence relationships in polar ecosystems, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-7284, https://doi.org/10.5194/egusphere-egu2020-7284, 2020.
Christine Chang, Jiaming Wen, Ruiqing Zhou, and Ying Sun
Solar-induced chlorophyll fluorescence (SIF) offers a promising tool to remotely monitor photosynthesis from the canopy to regional scale. However, in order to interpret instantaneous satellite SIF measurements in a biological context, there needs to be a better understanding of the diurnal dynamics of SIF and photosynthesis. Using two maize sites with contrasting row orientations, we acquired canopy scale SIF and hyperspectral reflectance using a tower and UAV, in conjunction with concurrent leaf-level measurements of photosynthesis and chlorophyll fluorescence. We show that SIF dynamics are impacted by a combination of canopy structure and plant physiology, which can lead to a divergent SIF-photosynthesis relationship, particularly at certain times of day. These findings have significant implications for upscaling and interpreting satellite SIF retrievals, which rely on daily mean integrals.
How to cite:
Chang, C., Wen, J., Zhou, R., and Sun, Y.: Disentangling the Control of Canopy Structure and Plant Physiology on the Diurnal Dynamics of SIF and Photosynthesis, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-19486, https://doi.org/10.5194/egusphere-egu2020-19486, 2020.
Simon De Cannière, Michael Herbst, and François Jonard
Photosynthesis is the cornerstone of all life on earth. Light energy, captured by chlorophyll, fuels photosynthesis. As an excess of absorbed light leads to harmful products, the excess light is either dissipated as heat or it is re-emitted in the atmosphere. The latter pathway results in a weak, but very specific spectral signal, right from the heart of the photosynthetic apparatus, called chlorophyll fluorescence. Recent advancements in spectrometry have allowed the retrieval of fluorescence with remote sensing. Given its close link to photosynthesis, it has the potential of informing crop growth models. The aim of this study is to estimate the stress parameter of the crop growth model AgroC by incorporating remotely-sensed sun-induced chlorophyll fluorescence (SIF) data. The radiative transfer model SCOPE converts the leaf-level fluorescence obtained from AgroC to canopy-scale SIF. In case of a stress, the SIF at 760 nm decreases, while the SIF at 687 nm shows a more complex relationship to stress. Comparing the modelled canopy-scale and observed SIF provides information on the plant water stress status, allowing a more precise estimate of the photosynthetic activity. Downstream, this leads to a better estimation of the plant growth, as well as a better estimation of the carbon and water fluxes. A field campaign is conducted over a sugar beet field in Merzenhausen, Germany, in which the fluorescence was measured alongside the water and carbon fluxes. As the fluorescence provides an additional constraint on the photosynthesis, the AgroC-SCOPE model is expected to provide significantly better estimates of the carbon fluxes compared to the AgroC model. The results of the coupled AgroC-SCOPE model will be presented at this meeting. This study provides information on the link between drought stress and fluorescence. An approach similar to the one proposed in this study will allow detecting drought stress at the regional to global scale with FLEX data.
How to cite:
De Cannière, S., Herbst, M., and Jonard, F.: Drought stress detection with a coupled AgroC-SCOPE model, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-21926, https://doi.org/10.5194/egusphere-egu2020-21926, 2020.
Daria Polosukhina, Oxana Masyagina, and Anatoly Prokushkin
In boreal forests, bryophytes and lichens usually dominate the ground floor layer and contribute up to 50% of ecosystem gross CO2 exchange (Bisbee et al. 2001; Goulden & Crill 1997). Sphagnum spp. are the most important contributors in wetland C uptake, and feathermosses and lichens play a significant role in well-drained sites (Nilsson & Wardle 2005; O’Connell et al. 2003; Jarle W. Bjerke et al. 2013). Given their important ecological roles in such a widespread biome, it is surprising that still a few studies have attempted to understand the intrinsic factors that control moss-lichen cover carbon dynamics specifically under ongoing climate change in high latitudes.
The aim of this work was to determine the stocks of moss-lichen stratum and photoassimilation activity of its dominant species during the growing season. The study has been conducted in Central Siberia near Zotino tall tower observatory (ZOTTO, 60 ° N, 89 ° E) in lichen- and feathermoss-dominated pine forests. First, to assess the phyto (bio) mass stocks the grass-shrub and moss-lichen layers were sampled in 100 replicates in each type of forest from 20x25 cm subplots (S = 50 cm2). The intensity of CO2 photoassimilation was determined in situ by Walz GFS-3000 (Heinz Walz GmbH, Effeltrich, Germany) infrared gas analyzer. Photosynthetic activity of lichens and feathermosses was measured during the growing season of 2018 in June, July, August and September around the mid-day time. For every time point we also analyzed CO2 exchange dependence from temperature, photosynthetically active radiation (PAR) and CO2 concentration.
The dominants of ground vegetation for the moss-lichen layer were Cladonia stellaris, Cladonia rangiferina, Cetraria islandica, Pleurozium schreberi, Hylocomium splendens, Aulacomnium palustre. The moss-lichen layer accounted for 78-96% of the total phytomass of ground floor in studied pine forests and comparable (486 g/m2) to the photosynthetic phytomass of the tree canopy (pine needles). During the growing season, carbon assimilation by the moss-lichen layer varied in a relatively narrow range: from 38 ± 4 to 42 ± 5 mgCO2 / m2 / hour for lichen C. stellaris and from 93 ± 11 to 99 ± 13 mgCO2 / m2 / hour for moss P. schreberi. Thus, moss-lichen layer dominants maintained high photoassimilation activity throughout the growing season. Temperature increased the intensity of CO2 assimilation and no inhibition was observed at maximum T used in our study (+40 ° C). There were no differences in the temperature dependence of CO2 photoassimilation between feathermosses and lichens. However, they differed in dependence from PAR. Mosses showed 2-fold larger response of CO2 assimilation intensity to increase of PAR comparatively to lichens. The rate of photosynthesis of both moss and lichen showed log growth with increasing CO2 levels up to 2000 ppm. Compensation poit was varying from 170 to 284 ppm.
This study was supported by the Russian Foundation for Basic Research project № 18-05-60203 "Landscape and hydrobiological controls on the transport of terrigenic carbon to the Arctic Ocean".
How to cite:
Polosukhina, D., Masyagina, O., and Prokushkin, A.: Photosynthesis in a widespread and important sub-Arctic moss and lichens species in pine ecosystems of the ZOTTO tower footprint area, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-5066, https://doi.org/10.5194/egusphere-egu2020-5066, 2020.
Drought has become one of the major constraints on agricultural development, particularly in areas lacking water. By studying the effects of different water stresses on photosynthesis, growth, yield, water use efficiency (WUE) and other indicators of winter wheat, this study provides scientific irrigation strategies for developing water-saving agriculture. According to the size of the water field capacity, four different water stress levels were set, i.e., 30–40% water field capacity (severe stress), 40–50% (moderate stress), 50–60% (mild stress) and 60–80% (well-watered irrigation), through an automatic irrigation system to create different water stress gradients by controlling the irrigation amount. The results showed that the diurnal and seasonal changes in photosynthetic parameters such as net photosynthetic rate (Pn), intercellular carbon concentration (Ci), stomatal conductance (Gs), and transpiration (E) significantly decreased with water stress intensification. The Pn of mild stress only slightly decreased compared to that of well-watered irrigation and was even higher than after May 16th, resulting in an increase in the dry biomass and 1000-grain weight under mild stress. Under all water stresses, the heights and stem weights of the winter wheat significantly decreased. Moderate and severe stress also significantly reduced the fresh weight of the aboveground biomass, dry weight, spike weight, grain weight, WUE and irrigation water productivity (IWP), while mild stress only slightly decreased the fresh weight of aboveground biomass, spike weight and grain weight. Mild stress increased the WUE and IWP. Thus, mild stress results in the optimal use of water resources without a significant reduction in yield. Therefore, mild stress can be considered as a suitable environment for winter wheat growth in arid areas.
How to cite:
Zhao, W., Wu, J., Liu, L., Yang, J., Han, X., Tian, F., and Shen, Q.: Effects of water stress on photosynthesis，growth and yield in winter wheat, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-8785, https://doi.org/10.5194/egusphere-egu2020-8785, 2020.
Marine Remaud, Frédéric Chevallier, Philippe Peylin, Antoine Berchet, and Fabienne Maignan
Inverse systems that assimilate atmospheric carbon dioxide measurements (CO2) into a global atmospheric transport model, are commonly used together with anthropogenic emission inventories to infer net biospheric surface fluxes. However, when assimilating CO2 measurements only, the respiration fluxes cannot be disentangled from the gross primary production (GPP) fluxes, leaving few possibilities to interpret the inferred fluxes from a mechanistic point of view. Measurements of carbonyl sulfide (COS) may help to fill this gap: COS has similar diffusion pathway inside leaves as CO2 but is not re-emitted into the atmosphere by the plant respiration. We explore here the benefit of assimilating both COS and CO2 measurements into the LMDz atmospheric transport model to constrain GPP and respiration fluxes separately. To this end, we develop an analytic inverse system based on the 14 Plant functional Type (PFTs) as defined in the ORCHIDEE land surface model. The vegetation uptake of COS is parameterized as a linear function of GPP and of the leaf relative uptake (LRU), which is the ratio of COS to CO2 deposition velocities in plants. A new parameterization of the atmosphere soil exchanges is also included. We use the system to optimize GPP and respiration fluxes separately at the seasonal scale over the globe. The results lead to a balanced COS global budget and a seasonality of the COS fluxes in better agreement with observations. We find a large sensitivity of the partition between the ocean emissions and the COS plant uptake to the LRU parameterizations.
How to cite:
Remaud, M., Chevallier, F., Peylin, P., Berchet, A., and Maignan, F.: Better constraining the CO2 plant uptake at global scale: joint assimilation of COS and CO2 atmospheric measurements into a transport model., EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-11474, https://doi.org/10.5194/egusphere-egu2020-11474, 2020.
Javier Pacheco-Labrador, Helge Aasen, Agnieszka Bialek, Marco Celesti, Maria Pilar Cendrero-Mateo, Andreas Hueni, Lammert Kooistra, Marlena Kycko, Miriam Machwitz, Laura Mihai, Uwe Rascher, Jean-Louis Roujean, Enrico Tomelleri, Christiaan van der Tol, Shari Van Wittenberghe, Alasdair MacArthur, Jochem Verrelst, and Martin Schlerf
Vegetation in terrestrial ecosystems controls a significant part of the gas and energy exchanges at the atmosphere-biosphere-pedosphere interface. Continuous spatial information about vegetation status (biophysical properties) and photosynthetic rates are needed to understand and model the responses of terrestrial ecosystems to environmental changes induced by human activity. This information is therefore critical to climate change monitoring, adaptation and mitigation.
Earth Observation (EO) allows the collection spatially continuous Earths surface reflectance at ecologically relevant scales. Recent advances in EO are bringing the chance to retrieve from space a subtle emission from vegetation originated at the core of the photosynthetic machinery of the plants: the chlorophyll sun-induced fluorescence (F). The upcoming Fluorescence Explorer (FLEX) mission from the European Space Agency (ESA) will be the first EO mission dedicated to the exploitation of this signal for the study of vegetation photosynthetic activity. FLEX will fly in tandem with Sentinel-3 (S3). This multi-sensor approach brings new opportunities to test the potential of synergistic use of multi-source data to capture scalable ecophysiological traits. The information provided by FLEX-S3 tandem together with observations from other Copernicus missions will boost the development of novel data analytical techniques, still to be realized. The development of these techniques will requires the combination of EO data with drone-based proximal sensing and tower-based eddy covariance (EC) observations. Together with modeling, this approach will allow solving critical and still open spatiotemporal scaling questions. Recent advances allow nowadays the synergistic use, processing and interpretation of data provided by multiple optical sensors featuring different spatial, spectral and temporal resolutions. The implementation of these techniques requires of the collaboration of the remote sensing, EC, and modeling communities; this need has motivated the development of a network within recently approved COST Action SENSECO.
SENSECO aims to ensure the multi-scale compatibility of EO measurements and protocols dedicated to the study of ecophysiological properties. This is needed to enable the synergistic use of multi-sensor data, as well as to ensure the transfer and exchange of knowledge on scaling approaches within the European communities. SENSECO achieves his objectives via dedicated expert workshops, training schools and short term scientific missions.
How to cite:
Pacheco-Labrador, J., Aasen, H., Bialek, A., Celesti, M., Cendrero-Mateo, M. P., Hueni, A., Kooistra, L., Kycko, M., Machwitz, M., Mihai, L., Rascher, U., Roujean, J.-L., Tomelleri, E., van der Tol, C., Van Wittenberghe, S., MacArthur, A., Verrelst, J., and Schlerf, M.: SENSECO: Optical synergies for spatiotemporal sensing of scalable ecophysiological traits. (COST Action CA17134), EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-17609, https://doi.org/10.5194/egusphere-egu2020-17609, 2020.
Karolina Sakowska, Maria Pilar Cendrero-Mateo*, Christiaan van der Tol, Marco Celesti, Giorgio Alberti, Radosław Juszczak, Franco Miglietta, and Uwe Rascher and the other members of the SOYFLEX campaign team
In recent years, technological progress in high-resolution field spectrometers have enabled the use of alternative tracer for constraining ecosystem-scale photosynthesis, i.e. sun-induced fluorescence (SIF). The principle underlying the use of SIF as a proxy of gross primary productivity (GPP) is based on the fact that the light energy absorbed by chlorophyll molecules can proceed into three different pathways: photochemistry, heat dissipation, and chlorophyll fluorescence. Since these processes directly compete for the same excitation energy, measurements of SIF and non-photochemical quenching (NPQ) are expected to provide information on photosynthetic performance.
However, SIF signal measured at the leaf level or beyond is affected by several processes, including wavelength dependent scattering and reabsorption, which may need to be considered when linking SIF data and photosynthetic CO2 assimilation.
To address this question, we conducted a multi-scale and multi-technique study that considered measurements of photosynthetic (GPP), optical (SIF, reflectance - R and transmittance - T), physiological (NPQ) and biophysical (the amount of absorbed photosynthetically active radiation - APAR) parameters of two soybean varieties: the MinnGold mutant, characterized by significantly reduced chlorophyll content (Chl), and the wild type, non-Chl deficient Eiko. We further used the “Soil-Canopy Observation Photosynthesis and Energy fluxes” (SCOPE) model to investigate the reabsorption and scattering of SIF. The measured leaf R, T and SIF and top-of-the-canopy R were used to retrieve biochemical and structural parameters of both varieties by inversion of the SCOPE model, while its forward mode was used to determine and correct for the scattering and reabsorption of SIF at both leaf and canopy level.
Our study revealed that despite the large difference in Chl content (the ratio of Chl between MinnGold and Eiko was nearly 1:5), similar leaf and canopy photosynthesis rates were maintained in the Chl‐deficient mutant. This phenomenon was captured neither by traditional spectral vegetation indices related to canopy greenness, nor by SIF measured in-situ. However, the modelling simulations revealed that when correcting for leaf and canopy scattering and reabsorption processes both varieties presented similar SIF yield (SIF/APAR). Furthermore, field measurements showed that APAR and NPQ in MinnGold were lower than in Eiko. This together explains the similar measured GPP and simulated SIF yield between the two varieties, and indicates that interpretation and application of SIF as a GPP tracer requires understanding and quantification of all these processes.
How to cite:
Sakowska, K., Cendrero-Mateo*, M. P., van der Tol, C., Celesti, M., Alberti, G., Juszczak, R., Miglietta, F., and Rascher, U. and the other members of the SOYFLEX campaign team: Exploring the scattering and reabsorption of chlorophyll fluorescence: implications for remote sensing of photosynthesis, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-18194, https://doi.org/10.5194/egusphere-egu2020-18194, 2020.
Georg Wohlfahrt, Karolina Sakowska, Christiaan Van der Tol, Albin Hammerle, Felix Spielmann, and Katharina Gerdel
Quantitative understanding and monitoring of gross primary productivity (GPP) and its response to environmental variables is critical for understanding the feedbacks of ecosystems to the changing climate and projecting the future climate state.
Due to limitations of the eddy covariance (EC) method related to the restricted spatial coverage obtained with the method, as well as drawbacks of the so-called CO2 flux partitioning approaches, adding scale-appropriate extra-information on canopy physiological status and flux partitioning is crucial for constraining gross photosynthesis (GPP), also beyond the ecosystem scale.
Here, we present the outcome of the H2020-MSCA-IF COSIF project aiming at investigating the potential of two novel GPP traces, i.e. carbonyl sulfide (COS) and sun-induced fluorescence (SIF) for inferring GPP.
The major result of the presented study are three independent GPP data sets obtained with different methods of contrasting theoretical backgrounds (CO2 flux partitioning, COS and SIF) in a temperate mountain grassland in Neustift, Austria (AT-Neu). Moreover, the study compares empirical approaches with a process-based estimates obtained using the “Soil-Canopy Observation Photosynthesis and Energy fluxes” (SCOPE) model, updated with a soil and leaf COS exchange module. The obtained results foster the use of repeated hyperspectral remote sensing observations together with radiative transfer and biochemical models for carbon assimilation monitoring.
How to cite:
Wohlfahrt, G., Sakowska, K., Van der Tol, C., Hammerle, A., Spielmann, F., and Gerdel, K.: Carbonyl sulfide and sun-induced fluorescence as joint constraints on terrestrial carbon cycling in a temperate alpine grassland ecosystem, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-9397, https://doi.org/10.5194/egusphere-egu2020-9397, 2020.
Ulisse Gomarasca, Gregory Duveiller, Alessandro Cescatti, and Georg Wohlfahrt
Accurate estimation of terrestrial gross primary productivity is essential for the development of credible future carbon cycle and climate simulations. Current remote sensing techniques allow retrieval of sun-induced chlorophyll fluorescence (SIF) as a valid proxy for GPP, but low resolution, sparse coverage, or resolution mismatches between the different satellite sensors hinder our ability to effectively link SIF to many environmental variables at fine scales. In order to better characterize heterogeneous landscapes, several attempts to downscale SIF products to higher resolutions have been made. We investigate the ability of the downscaled GOME-2 product developed by Duveiller et al. (2019), to capture the differences in spatiotemporal dynamics over the Greater Alpine Space. We analyse SIF in connection to land cover and elevation, and calculate land phenology metrics based on seasonal SIF time series. Ground-based GPP validation suggests biome-specific SIF-GPP relationships, but the comparison was hindered by the resolution mismatch of the data. Moreover, missing data are present at high elevations, diminishing the suitability of current SIF products to analyse cloud-prone mountainous areas. Important insights into spatial patterns and seasonal trends could be inferred at forest and other large-area land cover types, typical of mid elevations in the Alps, but many anthropogenic habitats at low elevations, as well as high elevation grasslands and other small-scale heterogeneous environments could not be thoroughly investigated and are likely to be underrepresented or prone to biases. Similar downscaling procedures might be applied at finer scales to e.g. TROPOMI products, or alternative advanced remote sensing SIF techniques and instruments might be needed in order to enable detailed and systematic evaluations of the Alpine region or similar highly heterogenous landscapes, before a process-oriented monitoring and unbiased implementation into climate models may be performed.
How to cite:
Gomarasca, U., Duveiller, G., Cescatti, A., and Wohlfahrt, G.: Satellite-based Sun-Induced Chlorophyll Fluorescence in the Greater Alpine Space: Spatial Patterns and Relationship to Gross Primary Productivity, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-20467, https://doi.org/10.5194/egusphere-egu2020-20467, 2020.
Water use efficiency (WUE) is defined as the ratio between gross primary production (GPP) and evapotranspiration (ET) at ecosystem scale, which can help understand the mechanism between water consumption and crop production in guiding field water management. Water consumption control is important in precision agriculture development. Mapping WUE at field scale using remote sensing data could provide crop water use status at high resolution and acquire the WUE spatial distribution. In this study we proposed a method to estimate field-scale maize WUE with Sentienl-2 data. The GPP of maize is estimated by a light use efficiency model with RS observed albedo, sunshine radiation, fraction of photosynthetically active radiation (fpar) fitted using in site observation. Maize ET is modelled using FAO-PM model with crop coefficient simulated using vegetation indexes acquired from Sentinel-2 bands. We compared the GPP, ET and final WUE estimation with eddy covariance (EC) observations in a maize field of North China Plain where water scarcity is a main limit factor of crop development. Comparation results show a high correlation between in site observation and modelled results. Combining the phenology development of maize, the temporal characteristics of maize WUE change is associated with phenology. WUE was low after sowing, then increased during Elongation stage. Maize WUE peaked at Heading and Grouting period and decreased in Maturation stage. Our WUE estimation method with high resolution could guide adopting various irrigation strategies based on different WUE conditions at field scale. This research could help shed light on the future WUE development under climate change background and improve our knowledge of precise water management.
How to cite:
Ma, Z., Wu, B., Yan, N., and Zhu, W.: Capability of maize water use efficiency estimation at field scale using Sentinel-2 data, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-5244, https://doi.org/10.5194/egusphere-egu2020-5244, 2020.