Changes in the interannual variability (IAV) of vegetation greenness and carbon sequestration are key indicators of the stability and climate sensitivities of terrestrial ecosystems. Recent studies have examined the changes in the vegetation IAV using atmospheric CO₂ observations and dynamic global vegetation models (DGVMs), however, reported different and even contradictory trends of IAV. Here, we investigate the changes in the IAV of vegetation greenness, quantified as coefficient of variability (CV), over the past few decades based on six long-term and three short-term satellite remote sensing products. Our results suggested that on half of the global vegetated surface, CV trends were uncertain (i.e., inconsistent CV trends when using different satellite remote sensing products). Meanwhile, we found that 22.20% and 28.20% of the global vegetated surface (i.e., mostly in the non-tropical land surface) show significant positive and negative CV trends (p ≤ 0.1), respectively. Regions with higher air temperature and greater aridity tend to have increasing CV trends, whereas greater vegetation greening trend and higher nitrogen deposition lead to smaller CV trends. Our study provides a remote sensing-based examination of the changes in the IAV of global vegetation greenness, and highlights the potential issues in studying the response of terrestrial ecosystems to climate change.

How to cite: Tian, J. and Luo, X.: Uncertain Changes of Vegetation Greenness Interannual Variability on Half of the Global Vegetated Surface, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-4210, https://doi.org/10.5194/egusphere-egu24-4210, 2024.

Drought is a complex and pervasive natural disaster that frequently exerts adverse effects on
vegetation dynamics. Recent advancements in satellite-based solar-induced chlorophyll
fluorescence (SIF) remote sensing offer unprecedented opportunities to monitor and understand
vegetation responses to drought on a large scale. In this study, we utilized high-resolution
TROPOspheric Monitoring Instrument (TROPOMI) SIF data, Bidirectional Reflectance Distribution
Function and Albedo (BRDF/Albedo) Model Parameters dataset (MODIS MCD43C1), MODIS land
cover data, and meteorological information to investigate the physiological responses of crops in
the Huang-Huai-Hai Plain of China during the drought period of 2019. Our results demonstrate
that NIRv, SIF, and BRDF-adjusted SIF/PAR (SIFn) exhibited significant dynamic changes during the
drought period, outperforming traditional vegetation indices such as NDVI in sensitivity.
Furthermore, a high correlation was observed between anomalies in precipitation and SIFn,
elucidating the substantial impact of moisture availability on crop physiology. These findings
provide essential insights into our understanding of plant responses to drought conditions at
large spatial scales and underscore the unique value of high-resolution remote sensing SIF
observations in tracking the physiological responses of vegetation to water stress.

How to cite: Zeng, Y. and Gao, Y.: Vegetation drought monitoring in the Huang-Huai-Hai Plain of China using solar-inducedfluorescence and near-infrared reflectance, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-21011, https://doi.org/10.5194/egusphere-egu24-21011, 2024.

Direct measurement of gross primary production (GPP) beyond a single leaf is a core challenge that prevents accurate quantification of global GPP and its spatiotemporal dynamics. Recent advancements in satellite Solar-Induced chlorophyll Fluorescence (SIF) retrieval offer promising opportunities, but so far incorporating satellite SIF to estimate GPP across scales is based solely on empirical linear scaling, an assumption that does not always hold at short timescales and stress conditions. In this study, we employ a process-based model, based on the mechanistic light reaction (MLR) model, to establish the link between SIF, electron transport rate (ETR), and GPP at the canopy scale using SIF retrievals from TROPOspheric Monitoring Instrument (TROPOMI) onboard Sentinel-5p. Our approach is applied across diverse NEON (National Ecological Observatory Network) ecoregions during the growing seasons of 2018-2021. We compare GPP estimates obtained from the conventional linear scaling approach and our mechanistic MLR-based approach with eddy-covariance (EC) flux tower measurements. Additionally, we analyze cross-biome variability in GPP estimates by incorporating ancillary information from hyperspectral reflectance spectra. Our findings highlight the potential of MLR for enabling satellite SIF for global GPP estimation, and the mechanistic advantage of MLR over the widely-accepted linear SIF-GPP scaling.

How to cite: Luo, Z., Sun, Y., and Wen, J.: Estimating Gross Primary Production (GPP) from satellite Solar-Induced chlorophyll Fluorescence (SIF) with a mechanistic model across NEON Ecoregions, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-4446, https://doi.org/10.5194/egusphere-egu24-4446, 2024.

Solar Induced Fluorescence (SIF) has significant potential to constrain the carbon cycle in land surface models. This requires either that the target variables in the model are first retrieved from the SIF data (for example, by estimating Gross Primary Productivity, GPP), or that the SIF is directly predicted from the model itself using a so-called observation operator. In the retrieval problem it is difficult to guarantee that assumptions made in the retrieval scheme are consistent with the assumptions in any given land surface model. Observation operators, on the other hand, offer the potential to enforce that consistency, but this comes with additional complexity. Ideally, observation operators should themselves be consistent with the assumptions inside the land surface model. If that is not the case, mismatches between the modelled and observed SIF can arise purely due to the observation operator, potentially resulting in biases. With a perfectly consistent system, we can be confident that any discrepancies are due to the underlying land model itself, and hence the discrepancies with the observed SIF inform us about land surface model.

This presentation describes an observation operator that is physically consistent with the two-stream radiative transfer scheme of Sellers (1985) commonly used in land surface models to represent the interaction of sunlight with vegetation canopies. We describe the derivation of the new observation operator and how it can be used to predict SIF. The scheme is numerically efficient, and can be easily extended to work with vertically inhomogeneous canopies. We show results from the JULES model (the land surface scheme of the UK’s flagship climate model UKESM) for both GPP and SIF at eddy covariance sites.

How to cite: Quaife, T., Stretton, M., Douglas, N., and McGuire, P.: A Two-Stream Observation Operator for Solar Induced Fluorescence in Land Surface Models, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-3833, https://doi.org/10.5194/egusphere-egu24-3833, 2024.

Vegetation is the major sink of carbonyl sulfide (COS), and for this reason, COS is a valuable proxy for assessing gross primary productivity (GPP). In this study, a comprehensive analysis of three years (2020-2022) of eddy-covariance measurements over a boreal forest in Hyytiälä (Finland) has unravelled intriguing patterns in COS fluxes in response to environmental conditions. The measurements were done following a partial harvest of the forest stand, where 40% of the basal area was removed from the footprint area. An anticipated reduction in uptake was observed in the summer of both 2020 and 2022. However, during the summer of 2021, anomalous positive COS fluxes (emission of COS) were consistently observed. The primary mechanism responsible for the removal of COS in leaves is hydrolysis, facilitated by the enzyme carbonic anhydrase (CA), leading to the production of hydrogen sulfide (H₂S) and carbon dioxide (CO₂). In the case of the Hyytiälä forest, CA-driven hydrolysis of the canopy acted as the dominant sink for COS. A detailed examination of environmental conditions prevailing during this period revealed a confluence of factors contributing to the unusual COS fluxes. Elevated temperatures, higher vapour pressure deficit, and decreased soil water content during the 2021 summer were identified as potential reasons for the anomalous COS flux responses. These conditions could collectively exert a suppressing effect on both stomatal and non-stomatal uptake of COS by the vegetation and soil. The empirical soil model used in the study also points towards increased abiotic production of COS from the soil due to increased soil temperature. However, the environmental conditions alone cannot explain the positive emissions during the daytime. Examining night-time fluxes shows that the canopy still uptakes COS even at a reduced rate. The analyses point towards the photodegradation production of COS from litter from the forest floor, which is overlooked in the empirical soil models and canopy uptake models. The thinning of the forest stand has led to a more open subcanopy, allowing increased sunlight penetration to the forest floor. The pine needles and residuals from the thinning are speculated to be the source of the photodegradation production of COS. Understanding the possible sources of these anomalous COS fluxes is crucial for refining our interpretation of COS as a proxy for GPP and, consequently, enhancing our ability to model and predict ecosystem productivity in a changing climate. In summary, the discovery of anomalous positive COS fluxes in the Hyytiälä boreal forest during the summer of 2021 represents a unique and significant observation, prompting further research into the complex interplay of environmental variables influencing COS fluxes within the boreal forest ecosystem.

How to cite: Thomas, A., Laasonen, A., Kohonen, K.-M., Vesala, T., Aslan, T., Kolari, P., Maseyk, K., Dewar, R., and Mammarella, I.: Insights to anomalous positive carbonyl sulfide fluxes in a boreal forest by using eddy covariance flux measurements., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-7135, https://doi.org/10.5194/egusphere-egu24-7135, 2024.

Carbonyl sulfide (COS) has gained attention as a proxy for stomatal conductance and photosynthesis. It is taken up by the plants through their stomata, similar to carbon dioxide (CO₂), and destroyed at the chloroplast surface by the enzyme carbonic anhydrase in a hydrolysis reaction. The main limiting factor of COS uptake in the leaves has been found to be the stomatal control. Thus, COS flux measurements have been linked to stomata-controlled carbon and water fluxes. However, existing studies, both in the field and in the laboratory, have predominantly focused on C3 and C4 plants, leaving a gap in understanding COS exchange in crassulacean acid metabolism (CAM) plants.

CAM plants, such as sisal (Agave sisalana), aim to minimize water loss by closing stomata during the day and opening them at night. During nighttime, they take up CO₂ but also other gases, including COS, from the atmosphere. CO₂ is stored as malic acid until light becomes available during daytime and it can be utilized in photosynthesis. This allows the plants to avoid water loss in harsh environments and reach high water-use efficiencies.

In this study, we measured COS fluxes with the eddy covariance (EC) technique over a sisal plantation for the first time. The measurement period covers three weeks during the rainy season in Kenya in November and December 2019. We show that COS and CO₂ fluxes followed a similar diurnal pattern, with uptake observed during nighttime, while water (H₂O) fluxes showed an opposite cycle with highest evaporation observed during daytime. We also show that the soil COS fluxes, measured with soil chambers, were positive under radiation (i.e., indicating COS emission) and negative (i.e., indicating COS uptake) in the dark, and soil COS emissions increased with increasing soil temperature. Our aim is to quantify the canopy conductance of Agave sisalana using COS together with H₂O and CO₂ flux measurements at the ecosystem scale. Our study provides valuable insights into the intricate interplay of COS with water and carbon fluxes in ecosystems dominated by CAM plants. 

How to cite: Kohonen, K.-M., Skogberg, M., Kübert, A., Räsänen, M., Merbold, L., Buchmann, N., Mammarella, I., Pellikka, P., and Vesala, T.: COS, CO2 and H2O eddy covariance flux measurements over Agave sisalana , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-13720, https://doi.org/10.5194/egusphere-egu24-13720, 2024.

Much information of photosynthesis and carbon cycling was embedded in the stable carbon isotope, as plants discriminate against heavier carbon isotope. The process of isotope discrimination has been implemented in most terrestrial biosphere models (TBMs), mainly following the standard equation by Farquhar et al. With National Center for Atmospheric Research (NCAR) Community Land Model (CLM5), we found this standard equation cannot reproduce the historical long-term increase of isotope discrimination as deduced from atmospheric 13C/12C measurements. We attributed such a mismatch to the missed representation of photorespiration and mesophyll diffusion. Updating the discrimination equation by leveraging a mechanistic mesophyll diffusion model developed by Sun et al. (2014), we reproduce the trend towards a larger discrimination under higher CO2 levels: globally the trend is 0.013‰ ppm−1, consistent with atmospheric measurements. Mesophyll effects significantly contribute to this global trend, with the largest contribution in natural ecosystems. Moreover, we found that an explicit consideration of mesophyll conductance can lead to a higher response of historical water use efficiency to climate and environmental changes. Our results have implications for advanced modeling of isotopic discrimination and therefore for a better understanding of the coupled carbon-water cycle under changing climate.

References:

Farquhar, G. D., Ehleringer, J. R., and Hubick, K. T.: Carbon isotope discrimination and photosynthesis, Annu. Rev. Plant Phys., 40, 503–537, (1989).

Sun, Y. et al. Impact of mesophyll diffusion on estimated global land CO2 fertilization. Proc. Natl. Acad. Sci. U. S. A. 111, 15774–15779 (2014).

How to cite: Lai, J. and Sun, Y.: Mesophyll largely contributes to the historical increase in isotope discrimination of C3 plants and implications for water use efficiency, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-2946, https://doi.org/10.5194/egusphere-egu24-2946, 2024.

Terrestrial vegetation regulates climate by photosynthetic uptake of CO₂. The extensive coverage of vegetation in Hong Kong (more than 70% of land) highlights the potential for terrestrial carbon sink to play a major role in achieving carbon neutrality in such a metropolitan city. To quantify the potential, local measurements and allometric modeling have estimated the aboveground biomass (AGB) on plot scales in Hong Kong. However, it remains a challenge to illustrate the temporal trends and spatial distribution of carbon uptake by vegetation in the city, and to understand what factors have shaped them. Here, we aim to estimate the net primary productivity (NPP) of Hong Kong vegetation, and identify the key drivers for variability of NPP on a city scale. We use the Terrestrial Ecosystem Model in R-Hong Kong (TEMIR-HK), a localized process-based ecosystem model, to evaluate the changes in NPP trends induced by changing CO₂ concentration, temperature, ozone concentration, and changing leaf area index (LAI) shaped by these factors as well as land use. Simulation results show an increasing trend of NPP, with an average NPP of 1.53 Tg C y^-1, which is less than 10% of the annual total anthropogenic carbon emission from Hong Kong, suggesting a limited but indispensable potential of urban forestry to achieve city-level carbon neutrality. The factorial simulations show that increasing ambient CO₂ concentration is the most dominant driver of increasing NPP among all potential drivers. This suggests that the globally well-mixed CO₂ concentration is impacting NPP more than the local climate, environmental and land-use changes in Hong Kong.

How to cite: Lam, H. C. H., Tai, A. P. K., Yung, D. H. Y., and Lo, J. T. W.: Modeling Climate Regulating Service Provided by Hong Kong Vegetation and Its Decadal Climatic and Environmental Drivers, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-7798, https://doi.org/10.5194/egusphere-egu24-7798, 2024.

Whether tropical land carbon sink will persist in the future to slow climate change remains elusive in Earth System Model (ESM) projections, largely due to carbon-climate feedback uncertainties. Unraveling drivers of interannual variability (IAV) of the land carbon cycle can inform tropical land carbon-climate feedbacks. Here we utilize two generations of factorial ESM experiments to show that the IAV of the tropical land carbon uptake under both present and future climate is consistently dominated by terrestrial water variations in ESMs. The magnitude of this interannual sensitivity of tropical land carbon uptake to water variations (γ_IAV,W) under future climate shows a large spread across the latest 16 ESMs (2.3 ± 1.5 PgC/yr/Tt H₂O). Based on the identified significant emergent relationship between γ_IAV,Wunder future climate and present climate, the mean and spread of future γ_IAV,Ware reduced by about 41% and 44%, respectively (1.3 ± 0.8 PgC/yr/Tt H₂O), using observations and the emergent constraint methodology. However, the long-term tropical land carbon-climate feedback uncertainties in the latest 16 ESMs can no longer be directly constrained by land carbon cycle IAV compared with previous generations of ESMs, given that additional important processes such as tree mortality are not well represented in IAV but could determine long-term tropical land carbon storage. This result highlights the importance of recommended out-of-sample testing for validating previously diagnosed emergent constraint. In summary, our results suggest the limited implication of IAV for long-term tropical land carbon-climate feedbacks and help isolate remaining uncertainties with respect to the effects of water limitation on tropical land sink in ESMs.

How to cite: Liu, L., Fisher, R., Douville, H., Padrón, R., Berg, A., Mao, J., Alessandri, A., Kim, H., and Seneviratne, S.: Can long-term tropical land carbon-climate feedback uncertainties be constrained from interannual variability?, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-11205, https://doi.org/10.5194/egusphere-egu24-11205, 2024.