Tropical and subtropical savannas have been increasingly targeted for increased carbon (C) storage via increasing tree cover. These projections typically assume large gains in soil carbon accompanying increasing tree cover, assumptions which may not reflect real changes in soil C under woody encroachment or afforestation. Studies have shown that productive grasses dominate C inputs into soils and that changes in ecosystem structure can sometimes result in losses of grass-derived carbon, but we only poorly understand the contributions of grass-derived C to total soil organic C (SOC) and the determinants of SOC responses to increasing tree cover in savannas. Here we show, using data from a semiarid savanna in Kruger National Park, South Africa, that both SOC concentration and grass-derived C in surface soils (0-20 cm) are predicted by grass biomass and soil texture, but not by tree basal area, stem density, or tree cover. More broadly across tropical savannas, grass-derived C contributes more than half of the SOC within the whole 1-m soil profile even under full tree cover. Although increasing tree cover increases SOC storage marginally, both SOC gain and loss are commonly observed across broad gradients of rainfall and soil sand content. These results highlight the continued high contribution of grasses to savanna SOC and the uncertain effects of increasing tree cover on SOC storage, challenging the widespread assumption that increasing tree cover has ubiquitous benefits to enhance SOC storage.

How to cite: Zhou, Y. and Staver, C.: Most carbon is grass-derived in tropical savanna soils, even under woody or forest encroachment, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-802, https://doi.org/10.5194/egusphere-egu22-802, 2022.

Anthropocene impact on atmospheric carbon has led to increased efforts to better understand the carbon cycle in terrestrial vegetation. Forests and their natural ability to assimilate carbon dioxide (CO₂) from the air have increasingly been incorporated into climate change mitigation policies. The increase in global CO₂ levels has also been shown to cause photosynthetic enhancement, although the extent of this CO₂-fertilization effect varies across vegetation type, age, species and the availability of other resources. An important knowledge gap for the projected mitigation function of (future) forests is the currently unknown fate of this additional carbon as a result of the increased photosynthetic activity [1]. Woody biomass is still thought to harbour a substation fraction of the unaccounted for carbon [2] and by including smaller woody compartments to the well-represented stem diameter datasets this research project aims to provide more details to the standing and turned over woody biomass inventories. The branch and twig compartments might detach faster from trees pre-mortality under elevated CO₂, increasing the turn-over rate of carbon within forest stands where this has previously gone unnoticed. To determine the choices of trees regarding growth under future CO₂ levels observation will be collected in two second-generation Free Air CO₂ Enrichment (FACE) facilities: BIFoR FACE, in Staffordshire UK and EucFACE in Sydney Australia. By making stand scale inventories using Terrestrial Laser Scanning (TLS) for standing biomass and line transects along with litter traps for fallen woody tissue, the fluxes of newly grown wood under eCO2 versus wood exposed to long term ambient concentrations can be compared. With additional comparisons between the two facilities, subsequent environmental factors and weather events to follow so that predictive carbon budget models can be improved. The increased CO₂ concentrations at these sites reach the levels estimated to be the global ambient in 30-40 years. In the current phase of this research project, the datasets resulting from the first fieldwork campaign and pipelines for array scale TLS analysis and turnover expansion factors are constructed.

References
[1] Jiang, M., Medlyn, B. E., Drake, J. E., Duursma, R. A., Anderson, I. C., Barton, C. V., ... & Ellsworth, D. S. (2020). The fate of carbon in a mature forest under carbon dioxide enrichment. Nature, 580(7802), 227-231.
[2] Walker, A. P., De Kauwe, M. G., Medlyn, B. E., Zaehle, S., Iversen, C. M., Asao, S., ... & Norby, R. J. (2019). Decadal biomass increment in early secondary succession woody ecosystems is increased by CO 2 enrichment. Nature communications, 10(1), 1-13.

How to cite: van Wijngaarden, K., Larsen, J., Pugh, T., Smith, B., and Medlyn, B.: From branch to forest to globe: how do tree choices regarding growth affect forest response to elevated CO2 levels?, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-894, https://doi.org/10.5194/egusphere-egu22-894, 2022.

Solutions to reduce carbon dioxide (CO₂) emissions and to achieve carbon neutrality have become an important subject. Thus, there is a growing interest in accelerating also the carbon sinks of urban vegetation and finding the best practices for designing green areas that maximize their carbon sinks and stocks. In cities, heavy management alters the natural carbon flows compared with the non-urban environment as green areas are usually irrigated and mowed, trees may have limited space to grow, and the aboveground litter is removed. Also, urban temperatures are increased due to heat island effect. Therefore, it is important to quantify urban carbon sequestration and develop models to describe urban carbon cycling. The aim of this study was to test the applicability of the different C cycling models to describe urban ecosystems and to determine the rate of carbon sequestration at different urban vegetation types.

Model performances were tested at different green spaces in Helsinki, Finland. Measurements of leaf area index, sap flow, soil respiration, soil temperature, soil moisture and photosynthesis were collected in the footprint area of the SMEAR III ICOS station in a small urban birch forest (Betula pubencens), in botanical garden with Tilia trees (Tilia cordata), in a partly irrigated lawn and in a non-irrigated lawn during 2020-2021. In addition, ecosystem-level net CO₂exchange over the whole area was measured at the SMEAR III. The models tested were LPJ-GUESS, JSBACH, SUEWS and SURFEX-ISBA.

How to cite: Thölix, L., Backman, L., Havu, M., de Munck, C., Masson, V., Järvi, L., Nevalainen, O., Karvinen, E., and Kulmala, L.: Carbon sequestration to different green urban land-use types in Helsinki Finland, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-4805, https://doi.org/10.5194/egusphere-egu22-4805, 2022.

Peatlands store more than a third of the global soil organic carbon stock. Bryophytes, and more specifically sphagnum mosses, play a major role in the carbon and water cycles of these ecosystems. There is a crucial need to include sphagnum mosses into Earth system models to better simulate the functional dynamics of peatlands in a changing environment. 

Leaf Area Index (LAI) is a key integrated whole plant trait that characterizes the capacity of plants to photosynthesize. Moreover, LAI is also a variable calculated by land surface models used in climate models allowing control of the exchange of matter and energy between vegetation and environment. LAI is often validated by satellite observations in the land surface modelling community.

However, to date, too few studies are focused on  the seasonal evolution of LAI of sphagnum mosses, which remains a difficult exercise. Therefore, we propose a seasonal monitoring of the LAI of sphagnum mosses in a mountainous peatland site (alt. 1343m) of the Pyrenees. Two techniques for determining the LAI are confronted. First, monthly in situ moss sampling at the stand scale (25 cm2) followed by laboratory measurement of wet and dry biomass, and the LAI with a 2D scanner. Secondly, calculation of LAI using ESA's SNAP toolbox (10m resolution). 

We found that both Sphagnum LAI derived from field campaigns and the remote sensing approach show a strong seasonality from June to December 2021. Both techniques give the same range of LAI values during this period ( 1 to 6 m².m²). However, the peak of the growing season does not occur at the same time, with a peak in August for field experiments and July for remote sensing approaches.

How to cite: Garisoain, R., Delire, C., Decharme, B., and Gandois, L.: Seasonality of Sphagnum LAI in a mountainous peatland (Pyrenees, France), EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-9730, https://doi.org/10.5194/egusphere-egu22-9730, 2022.

The length of the growing season in temperate and boreal forests has a strong effect on the global carbon balance. Yet, our current understanding of the drivers of phenological processes such as autumn leaf senescence in deciduous trees is not sufficient for making reliable estimates of future growing-season lengths under climate change. While temperature has been shown to be an important driver of autumn leaf senescence, recent evidence suggests that the concept of carbon sink limitation might help to reduce unexplained variation in leaf senescence predictions. According to the carbon sink limitation hypothesis, senescence is regulated by the balance of the plant carbon source and the plant carbon sink, so that senescence occurs later when carbon inputs (source) are low and earlier when there is a low carbon demand (sink). In our experiment, we manipulated carbon source–sink dynamics in birch seedlings (Betula pendula L.) to evaluate the evidence for an effect of carbon sink limitation on autumn leaf senescence in a widespread deciduous tree. Specifically, we removed leaves and/or buds from the seedlings and monitored the effects on autumn net photosynthesis and leaf senescence. In agreement with the carbon sink limitation hypothesis, we observed that a decrease in the carbon source through a high degree of leaf removal increased autumn leaf-level photosynthesis by ~14% and postponed senescence by 5.5 ± 2.4 days. Yet, we did not see significant effects of the lower- and medium-degree defoliation treatments. Further, we did not observe an effect of bud removal on either photosynthesis or senescence, which was likely caused by the fact that our bud removal treatment did not considerably change the plant carbon sink. At least partly, our results are in line with the hypothesis of carbon sink limitation as a driver of growing-season length and move the scientific field closer to narrowing a main uncertainty in climate change predictions.

How to cite: Maschler, J., Keller, J., Bialic-Murphy, L., Zohner, C. M., and Crowther, T. W.: A reduction of the plant carbon source postpones autumn leaf senescence in birch seedlings, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-7743, https://doi.org/10.5194/egusphere-egu22-7743, 2022.

Forests in Europe have been modified by centuries of intensive land use, substantially influencing forest dynamics and biomass stocks, as well as forest interactions with climate. This makes the accounting for forest management crucial in any large-scale analysis of forest ecosystems, including the estimation of the forest carbon sink dynamics. However, the realistic representation of management in projection models is still hindered by the availability of data. To fill this gap, we analyzed recent forest harvest information in permanent plots of national forest and landscape inventories in several European countries. We used the harvest status information of individual trees between two measurements to characterize probability of different types of harvest events (partial cut vs removal of all trees), harvest intensity and characteristics of harvested trees on a plot level. These results were aggregated to a spatial grid, catching variations on sub-national scale. We then quantified the relationships of harvest events and their properties with potential predictors, including pre-harvest status of the forest (e.g., stand basal area, species and size structure of trees) and climatic, abiotic and socio-economic variables. The results reveal the variation in how forests are currently managed across the continent, with the differences stemming from different climatic and ecological conditions as well as different histories, priorities and goals of forest use and management. For example, the prevalence of even-aged rotation forestry with clear cuts in northern Europe is captured in the results as higher intensities of harvest events and higher probabilities for removing all trees. The results provide a realistic quantification of the current forest harvesting regimes across Europe, providing much needed detail in our understanding of contemporary management practices and a finer spatial resolution compared to existing data sources, such as national-level harvest statistics.

How to cite: Suvanto, S., Esquivel-Muelbert, A., Schelhaas, M.-J., Ruiz-Benito, P., Henttonen, H., Zavala, M., Kändler, G., Stadelmann, G., Talarczyk, A., Fridman, J., Govaere, L., Cienciala, E., and Pugh, T.: Observation-based quantification of forest management in Europe, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-12779, https://doi.org/10.5194/egusphere-egu22-12779, 2022.

Vegetation biomass carbon stocks play a vital role in the climate system, but the analysis of long-term carbon budgets is hindered by the lack of benchmarked estimates from the 20^th century. Here, by integrating inventory-based information on land use and carbon densities in a closed-budget land accounting approach, we establish a mid-20^th century global carbon stocks account. Our approach integrates global forest assessments from the mid-20^th century, previously ignored in global land change studies, and inventory-based land use reconstructions across the 20^th century with contemporaneous information on potential carbon stocks, the likely presence/absence of woody cover and the extent of shifting cultivation in the tropics. In a scenario-based analysis, we find that vegetation stored 540 PgC in biomass (median of 1728 cases per world region; inner quantiles 455-618 PgC). We focus on two Focal Cases, with total carbon stocks of 454-469 PgC, representing reasonable assumptions of carbon densities in forests and other wooded lands to reveal the distribution of carbon stocks across 8 land categories and 14 world regions. We found that ecosystems in Southern America, Western Africa and the erstwhile Soviet Union stored more than 27, 16 and 12% of all carbon stocks, predominantly in forests. Carbon stocks in Other Vegetated Lands, calculated as a residual from all known land uses, demonstrated the highest uncertainties. Comparisons with early-21^st century carbon stocks estimates revealed significant reductions in global carbon stocks, but with distinct subcontinental characteristics, providing first evidence of a carbon stocks transition following a forest area transition underway in industrialised regions in the Global North as well as indicating the maximum possible carbon sequestration from restoration initiatives in a realistic timeframe in the future. Our integrative methodology can be used to reconstruct global carbon stocks over the 20^th century to supplement other carbon flux-based modelling efforts, thus helping to constrain present and future simulations of global biomass carbon stocks.

How to cite: Bhan, M., Meyfroidt, P., Gingrich, S., Matej, S., and Erb, K.-H.: A mid-20th century benchmark estimate of global vegetation biomass carbon stocks , EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-11678, https://doi.org/10.5194/egusphere-egu22-11678, 2022.

Compound climate events can significantly impact vegetation productivity, yet the direct and lagged vegetation productivity responses to seasonal compound warm-dry and cold-dry events remain unclear. Using observationally-constrained and process-based model data, we analyze vegetation productivity responses to the compound conditions of precipitation and temperature in spring and summer. Our results show the regional asymmetries in direct and lagged effects of compound warm-dry events. In high-latitudes (>50°N), compound warm-dry events raise productivity. In contrast, in mid-latitudes (23.5-50°N/S), compound warm-dry events reduce productivity and compound warm-dry springs can cause and amplify summer droughts, thereby reducing summer productivity. Moreover, compound cold-dry events impose directly and indirectly adverse synergistic effects on productivity in mid-to-high latitudes and their effects exceed individual cold and dry impacts. Our results highlight that a multivariate perspective is necessary to appropriately investigate the impacts of climate extremes on vegetation productivity as precipitation and temperature often covary.

How to cite: li, J., Bevacqua, E., Chen, C., Wang, Z., Chen, X., Myneni, R. B., Wu, X., Xu, C.-Y., Zhang, Z., and Zscheischler, J.: The direct and lagged responses of vegetation productivity to seasonal compound events, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-6284, https://doi.org/10.5194/egusphere-egu22-6284, 2022.

The frequency and severity of droughts are expected to increase in the wake of climate change in many regions. Droughts not only cause concurrent impacts on the ecosystem carbon balance, but also result in legacy effects during the following seasons and years. These legacies result from, for example, drought-driven hydraulic damage or adjustments in carbon allocation. To understand how droughts might affect the carbon cycle, it is important to consider both concurrent and legacy effects. Such effects likely affect the interannual variability in carbon fluxes, but are challenging to detect in observations, and poorly represented in land surface models. Therefore, the understanding of patterns and mechanisms inducing legacy effects of drought on ecosystem carbon balance need to be improved.

In this study, we analyze the seasonal dynamic of gross primary productivity (GPP) from the FLUXNET dataset and detect legacy effects from past droughts. We predict the potential GPP in legacy periods based on a trained data-driven model using data in non-legacy periods and infer legacy effects from the difference between actual and potential GPP in legacy periods. We find that the drought-induced lagged GPP reductions are overall of similar magnitude to the concurrent GPP reductions in many sites. We further explore how drought legacy effects depend on drought intensity, vegetation type, and climate zone. These results have the potential to improve our understanding of the mechanisms of recovery and resilience of GPP to drought, thereby drought impacts on the ecosystem carbon cycle.

How to cite: Yu, X., Orth, R., Reichstein, M., Bahn, M., and Bastos, A.: Drought legacy effects on ecosystem productivity across eddy-covariance FLUXNET sites, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-3886, https://doi.org/10.5194/egusphere-egu22-3886, 2022.

Unprecedented change is occurring in the Northern high latitude regions as a result of climate change. With related degradation of large carbon stocks sequestered in Arctic permafrost, it is essential that the carbon cycle, and its changes over time, is properly monitored. Greenhouse gas (GHG) fluxes can directly be monitored through the eddy covariance (EC) method and flux chambers. However, harsh weather conditions and remoteness make it difficult to establish and keep such monitoring sites running in the Arctic, and accordingly the past and current data coverage is comparatively sparse.

In this study, we aim to evaluate the coverage of the existing network of high latitude GHG flux monitoring sites, and quantify uncertainties in our understanding of regional-scale vertical carbon exchange processes. Our intent is to outline the limits of this network both spatially and temporally. We investigate how changes over time in flux observations affect the networks extrapolation potential, and how gaps in the network extent could best be filled. For this purpose, we applied and extended the network representativeness metric used for the FLUXCOM project. First we calculate an extrapolation index, which indicates the relative error when predicting fluxes at increasing dissimilarity in environmental conditions from the existing sites in the network. Here we train a model to predict fluxes based on the top 10 predictor variables from FLUXCOM of the nearest locations in variable space to reference flux data. We then correlate prediction errors to distance in variable space, which allows us to quantify prediction errors for each location and time step in our domain.

This analysis uses an extended version of our database of high latitude GHG flux monitoring sites produced in previous studies. This information is also available as an online mapping tool, which facilitates a variety of science applications. Although coverage is improved over past epochs, large gaps still remain in Russia and Canada, and across the Arctic wintertime. The most consistent year-round coverage of GHG fluxes occurs in Alaska and Europe. Our study prioritizes locations for network extension in Russia, Canada, and select locations in Alaska, and highlights where upgrades in instrumentation and battery capacity (e.g., extend monitoring into shoulder seasons and winter) would be most efficient.  

How to cite: Pallandt, M., Jung, M., Natali, S., Rogers, B., Virkkala, A., Watts, J., and Göckede, M.: Extrapolation error quantification of the Arctic flux network across space and time, with data driven network optimization., EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-9350, https://doi.org/10.5194/egusphere-egu22-9350, 2022.

Tropical land carbon-climate feedback is a key determinant of uncertainties in climate change projections. Temperature has been proposed as a primary driver for the land carbon sink and it has been widely used to characterize carbon-climate feedback metrics in the latest reports of the Intergovernmental Panel on Climate Change (IPCC). The historical interannual sensitivity of CO2 growth rate (CGR) to tropical temperature was further identified as an observational constraint that can significantly lower uncertainties in projected changes in tropical land carbon storage. Here, we utilize 1pctCO2 ensemble experiments from the 6th Coupled Model Intercomparison Project (CMIP6) and show that previous emergent constraints (ECs) on tropical land carbon-climate feedback relying on temperature derived from the previous set of CMIP experiments (C4MIP) do not perform well for CMIP6. Long-term climate-driven tropical land carbon uptake is more directly coupled with water availability (soil moisture as the proxy in models) than temperature at both regional and local scale in CMIP6, suggesting that water has a stronger role than temperature in directly determining tropical land carbon-climate feedbacks. We further find that there is a significant emergent relationship between long-term sensitivity of tropical land carbon uptake to drying and its interannual sensitivity to water in CMIP6 (R=0.91, n=16). Combining with observations of interannual sensitivity of CGR to terrestrial water storage during 2002-2018, the resulting EC shows that, compared with an unconstrained ensemble of ESMs in CMIP6 (-1.9±1.4 PgC/yr/ Tt H2O), tropical land carbon losses by drying per Tt H2O are much lower (-0.9±0.7 PgC/yr/Tt H2O). Nonetheless, this does not ensure a less actual carbon loss per degree of global warming, because it also depends on the sensitivity of tropical land drying to global warming. This study suggests a strong potential for constraining future climate-driven terrestrial carbon sink from the perspective of water-carbon limitations.

How to cite: Liu, L. and Seneviratne, S.: Constraining future tropical land carbon-climate feedbacks by water, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-6204, https://doi.org/10.5194/egusphere-egu22-6204, 2022.

Drying is expected in many regions of the world by the end of the 21st century under increased greenhouse gas emissions. Climate projections robustly indicate that the tropical Amazon region is particularly sensitive to future climate change. On the one hand, an increased occurrence of heat and aridity events may largely impact the main vegetation processes in the coming decades. On the other hand, these extreme heat and drought events interfere with and are mediated by slowly changing climatic conditions, primarily those associated with raising CO₂ concentrations, that could alleviate negative impacts of global warming on regional ecosystems and carbon stocks. In this context, the relationship between extreme climatological events and climatic modes of variability plays a critical role. Throughout the tropics, El Niño Southern Oscillation (ENSO) is the predominant mode regulating vegetation's carbon dynamics, with significant reductions in terrestrial carbon uptake being related to increased temperatures and decreased precipitation associated with its Niño positive phase. However, its future amplitude and contribution to extreme climatological events and consequently to tropical atmosphere-carbon fluxes is still debated in the scientific community. At the same time, the importance of other modes of variability on the terrestrial vegetation dynamics and carbon sinks remains unexplored. On this premise, this research aims at filling this gap of knowledge by exploiting the results of several Earth System Models (ESM) simulations contributing to CMIP6 for three future scenarios: ssp585, ssp370, and ssp534-over. Given its importance for the balance of the global carbon cycle, the focus of the analysis is on the Amazon region. In this contribution, we will illustrate multi-model results concerning the projected future behavior of selected climatic modes of variability that are known to affect the Amazon region. A special focus will be on climate modes' characteristic timescales and amplitudes since these could effectively enhance or damp climatological extremes.

How to cite: Mastropierro, M. and Zanchettin, D.: Carbon cycle responses in the Amazon region to large scale climatic modes of variability, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-9641, https://doi.org/10.5194/egusphere-egu22-9641, 2022.

How to cite: Hari, M. and Tyagi, B.: Effect of aerosols on ecosystem productivity: a double-edged sword in climate change, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-545, https://doi.org/10.5194/egusphere-egu22-545, 2022.

Ecosystem disturbances such as wildfires, storms or insect outbreaks are important elements of forest dynamics. As a changing and more extreme climate is expected to lead to an increase in such disturbances in many places, they have to be considered in coupled land surface – atmosphere dynamics.

Next to releasing large pulses of carbon to the atmosphere through large-scale forest mortality, disturbances can also play an important role in catalyzing or enhancing ecosystem state shifts. In the boreal zone, results from field and landscape modeling studies indicate that disturbances drive transient or permanent shifts from needleleaf evergreen to broadleaf deciduous species. While such changes are also visible in biome-wide simulations, the role of disturbances therein remains open.

We here investigate the impact of changing disturbance regimes on the species composition of the boreal zone under climate change. We perform simulations with the Dynamic Global Vegetation Model LPJ-GUESS, which allows simulating disturbances and post-disturbance recovery through its representation of vegetation demographics and patch dynamics. We combine varying rates of stylized disturbances with different climate scenarios to create controlled simulation experiments of changing climate, changing disturbance regimes and their interactions.

Our simulations reproduce findings from previous studies and theory, with increasing disturbance rates leading to higher shares of deciduous trees in areas where they would be negligible in the absence of disturbance. We further investigate if these changes represent (1) a transient state of early-successional species that disappears again once disturbance pressure is lifted or (2) a stable reorganization of the ecosystem towards a deciduous-dominated forest.

How to cite: Layritz, L. S., Gregor, K., Krause, A., Meyer, B., Pugh, T. A. M., and Rammig, A.: Interaction effects of climate change and disturbance regimes on high latitude forest dynamics, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-10096, https://doi.org/10.5194/egusphere-egu22-10096, 2022.

Predicting species-level responses to drought at the landscape scale is critical to reducing future uncertainty in terrestrial carbon and water cycle projections. We embedded a stomatal optimisation model in the Community Atmosphere Biosphere Land Exchange (CABLE) land surface model. We parameterised the model for 15 canopy dominant eucalypt tree species representative of a broad precipitation gradient across South East Australia (mean annual precipitation range: 344–1424 mm yr^-1). We conducted three experiments: (i) applying CABLE to the 2017–2019 drought in South East Australia; (ii) a 20% drier drought; and (iii) a 20% drier drought with a doubling of atmospheric carbon dioxide (CO₂). We identified several drought hotspots across the ranges of E.viminalis, E.obliqua, E.globulus, E.saligna, and E.grandis. By contrast, CABLE simulated drought resilience in species that are found predominately in semi-arid areas such as E.largiflorens and E.populnea. We identified several key model assumptions (e.g., the degree of stomatal control) and sensitivities (e.g., the role of CO₂ in ameliorating drought) that require future research. Our results represent an important step forward in our capacity to forecast the resilience of individual tree species, providing an evidence base for decision-making around the resilience of restoration plantings or strategies associated with achieving net-zero emissions.

How to cite: De Kauwe, M., Sabot, M., Medlyn, B., Pitman, A., Meir, P., Cernusak, L., Gallagher, R., Ukkola, A., Rifai, S., and Choat, B.: Towards species-level forecasts of drought-induced tree mortality risk, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-2419, https://doi.org/10.5194/egusphere-egu22-2419, 2022.

To capture the vegetation-driven seasonal variability in surface fluxes, land surface models (LSM) simulate the evolution of leaf area index (LAI) prognostically. A common approach to achieve this, is by directly coupling the carbon assimilation flux to the leaf biomass evolution.
In this study, we evaluate this scheme by isolating it from the LSM framework, and forcing it with in situ observations of the carbon flux from a selection of 56 sites from the ICOS network. The resulting LAI is validated with the remote sensed product from Copernicus GLS. The parametrization of the biomass allocation scheme in ISBA was adopted, and a sensitivity analysis was performed.
Across a broad range of vegetation types and climate regions, it was found that the simulated phenological cycle was delayed, compared to the observations. The results highlight the importance of non-structural carbohydrate dynamics in LSM, which can decouple the direct link between photosynthesis and leaf biomass.

How to cite: De Pue, J., Barrios, J. M., Arboleda, A., Hamdi, R., Janssens, I., Balzarolo, M., and Gellens-Meulenberghs, F.: Evaluation of the photosynthesis-driven biomass allocation scheme in land surface models, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-4650, https://doi.org/10.5194/egusphere-egu22-4650, 2022.

Land-surface models aim to represent exchange processes between soil and atmosphere via the surface by coupling hydrological and carbon fluxes. Vegetation directly links between hydrological and carbon cycle and, thus essentially, is included in land-surface models. But its dynamics are challenging to capture in models, which is not least because of difficulties in data acquisition. Nevertheless, some land-surface models are available that come with modules for dynamic vegetation. Here, we conducted a model-data comparison to evaluate the representation of dynamic vegetation and related surface fluxes of the two models ECLand and Noah-MP by using the FLUXNET 2015 dataset, data from the TERENO site “Hohes Holz” and a MODIS leaf area product. With the current implementation, using dynamic vegetation modules did not enhance representativeness of the vegetation in ECLand. Dynamic vegetation in Noah-MP improved vegetation representations at least for some sites. For the exchange fluxes, using prescribed leaf-area climatology from remote sensing products appeared with the best model performance. The representation of hydrological fluxes and soil moisture remained almost untouched for both models. Additionally, the performance of the models in vegetation- and hydrology-related variables did not depend on each other. The current implemented modules for dynamic vegetation in these two models yielded no better model performance compared to runs with prescribed leaf-area climatology. Hence, they provide an example that additional model complexity does not lead to improved model performance.

How to cite: Westermann, S., Hildebrandt, A., Boussetta, S., and Thober, S.: Performance of dynamic vegetation in land-surface models - a multi-site comparison, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-11796, https://doi.org/10.5194/egusphere-egu22-11796, 2022.

Temperate forest ecosystems play a crucial role in governing global carbon and water cycles, that are both sensitive to global warming due to its various effects on the functionality of the forest ecosystems. The total carbon uptake of ecosystems by photosynthesis (GPP) is the largest flux between the land and the atmosphere within the carbon cycle. GPP quantification has thus a direct consequence on carbon budget estimations. However, this carbon flux has one of the largest uncertainties for estimates of the global carbon cycle. Similarly, for the water cycle a prognostic simulated vegetation leaf area index (LAI) would substantially improve representation of the water cycle components in hydrological models (e.g., evapotranspiration), while GPP predictions would benefit from simulated soil water storage. Those two key variables can be estimated using the light use efficiency concept, total carbon uptake by plants (GPP), and partly allocation of that to the leaves carbon pool. Although many models have been successfully developed to estimate GPP, they either use satellite-based LAI/fPAR (fraction of photosynthetically active radiation) data which are subjected to uncertainty and/or the level of the model complexity (when LAI is also simulated) prohibits their integration into hydrologic models. In this study, we develop a parsimonious forest canopy model to simulate the daily development of both GPP and LAI, while ensuring adequate level of complexity to be coupled into hydrological models. We test the model on deciduous broad-leafed forest sites located in Europe and North America selected from the FLUXNET network. A mass balance approach, the difference between daily carbon uptake and carbon loss in the plant canopy pool, is used to calculate daily leaf biomass. The model consists of several sub-models including routines for the estimation of soil hydraulic parameters based on pedotransfer functions, vertically weighted soil moisture considering the underground root distribution, phenology, and leaf litter generation. We analyze the model parameter sensitivity on the resulting carbon flux dynamics (GPP) and stock (leave pool). The model performance is evaluated in a validation period against in-situ measurements of GPP and LAI. Finally, we test the cross-location transferability of model parameters and derive a compromise parameter set to be used across sites. We identified on average 10 sensitive parameters for the model at each study site (e.g., LUE, SLA, etc). The model adequately captures the daily dynamics of observed GPP and LAI at each study site (e.g., with KGE (Kling-Gupta-Efficiency) values varying between 0.79 and 0.92). It also shows reasonable performance regarding a compromise single set of parameters obtained from the model transferability assessment with a slight loss in model skill. In this presentation, we discuss on the suitability of the model structure and important observations made during the investigation. The model will be implemented into the existing mesoscale Hydrologic Model (mHM) in order to improve representation of water and carbon cycle components.

How to cite: Bahrami, B., Kumar, R., Thober, S., Hildebrandt, A., Fischer, R., Samaniego, L., and Rebmann, C.: Predicting Forest Gross Primary Productivity and Leaf Area Index by Coupling Light Use Efficiency and Leaf Phenology in a Parsimonious Canopy Model , EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-8844, https://doi.org/10.5194/egusphere-egu22-8844, 2022.

Pollination is a key ecosystem service vital to the preservation of wild plant communities and good agricultural behaviour. However, pollinators are rapidly declining in Europe, primarily as a result of human activity and climate change. Therefore, there is growing concern that observed declines in insect pollinators may impact on production and revenues from pollinator-dependent crops. In the forest, the presence of pollinators depends strongly on the openness of the canopy and the presence of wild plants that attract pollinators. The distribution of such plants is, therefore, crucial for estimating the pollinators presence. In general, however, there is incomplete knowledge of where those wild plants occur and how well they grow. To overcome this issue, we developed a species distribution model to predict the potential presence of important plant species for pollinators under present and future climatic conditions. The result of the distribution model is then refined using the dynamic vegetation model CARAIB. By combining the results of the distribution model and CARAIB, we can determine where the plants are located and calculate their net primary productivities.

How to cite: Lanssens, B., François, L., Hambuckers, A., Moen, M., Anders, T., Tölle, M., Verma, A., and Remy, L.: Assessing the effects of climate and land use changes on the distribution and growth of important plants species for pollinators, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-4559, https://doi.org/10.5194/egusphere-egu22-4559, 2022.

Future projections suggest that the Arctic will undergo extreme changes in the near future, with the largest changes occurring during the wintertime. Still, cold season processes and their impact on the annual carbon and water budgets are often understudied.

We aim to assess and quantify the impact of winter warming on the arctic carbon cycle by improving the representation of cold-season processes in the LPJ-GUESS DGVM. Firstly, we developed and implemented a new, dynamic snow scheme into the model to enhance the simulation of snow-soil-vegetation interaction. These updates improved the simulation of modelled soil temperature and permafrost extent compared to observations. In our latest study, we are assessing the physical controls on non-growing season methane emissions in the model, focusing on potential burst-like methane emissions during the zero curtain period. We set out to evaluate whether enabling non-growing season methane emissions may influence the annual methane budget.

So far, we found that changes in the cold season significantly affect arctic biogeochemistry. We also observed that wintertime changes affect vegetation dynamics and composition over the Arctic. Improving the model representation of wintertime processes enables to further investigate the future snow-soil-vegetation interaction. These simulations can be used to assess the impact of warming on the arctic carbon cycle and its global consequences.

How to cite: Pongracz, A., Wårlind, D., Miller, P. A., and Parmentier, F.-J. W.: Quantifying the impact of winter warming on arctic-boreal ecosystems and greenhouse gas exchange, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-2843, https://doi.org/10.5194/egusphere-egu22-2843, 2022.

While climate change is impacting all parts of the globe, boreal forests are experiencing disproportionally higher rates of temperature increase, thus drastically impacting one of the largest biomes in the world. Changes in high-latitude forests have strong implications to the regional water and carbon cycling, and shifts in canopy cover (i.e., abundance and shifts between evergreen and deciduous species) will alter albedo, ecosystem productivity, and surface and canopy water fluxes. For example, high latitude warming may increase nutrient availability via a deepening of the soil active layer. Warming also induces permafrost degradation and loss, leading to strong interactions that alter the hydrology, and soil biological and physical processes. These climate-related interactions will affect plant competitive interactions, survival, and ultimately community distribution and carbon storage. In this study we explore how vegetation dynamics will be affected by changes in plant and microbial N competition, differences in nutrient demand due to shifts in PFTs (e.g., faster resource acquisition in deciduous plants), and ultimately carbon allocation. To be able to accurately predict and model these complex ecological processes we are using a new demographic vegetation model (FATES; Functionally-Assembled Terrestrial Ecosystem Simulator) that is coupled to ELMv1, the land surface model in the global Earth System Model - E3SM. We present here the newly implemented representation of nutrient competition, acquisition, and extensible approach of nutrient and carbon allocation within plants in the ELM-FATES model. This work has successfully coupled the interactions of nutrients between soil biogeochemistry (BGC) in ELM and plant productivity and carbon in FATES, with improved model hypothesis testing for plant’s nutrient storage capacity. With the inclusion of nutrient cycling in the previously ‘carbon-only’ ELM-FATES where the largest competition was light driven, the productivity and biomass storage was significantly reduced for the simulated boreal forests. After conducting an uncertainty quantification experiment (i.e., using large ensembles to generate surrogate models) in order to test the model parameter sensitivity, we found that model parameters related to carbon storage and leaf economics had the largest sensitivity on plant processes. We then applied a Bayesian inference approach using neural networks to calibrate the model parameters against observational datasets, and greatly improved model predicts to match field inventory data.  These newly represented ecological-based processes have helped to improve the representation of these vulnerable forests in an Earth System Model. 

How to cite: Holm, J. A., Knox, R., Zhu, Q., and Ricciuto, D.: Combining nutrient competition, dynamic vegetation, and parameter calibration to improve boreal forest predictions to changing climate, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-10649, https://doi.org/10.5194/egusphere-egu22-10649, 2022.

Vegetation plays an important role in global carbon and water cycles. Long-term environmental changes modify vegetation distributions and consequently impact fluxes of carbon, water and energy. Vegetation dynamic models are useful tools to analyze terrestrial ecosystem processes and can simulate the impact of vegetation structure changes on carbon and water cycles and their interactions with climate when coupled to land surface models. Because of the complexity to represent plant growth processes, these models typically have a large number of parameters that can potentially contribute to uncertainty in model results and need to be adequately parameterized. In this study, we used the Community Land Model (CLM v5) coupled to the Functionally Assembled Terrestrial Simulator (FATES) and applied it to four forest sites from the database of European Long-Term Ecosystem Research Infrastructures (eLTER) which provides a wide range of observational data to calibrate and evaluate vegetation models. Using this database, we performed sensitivity analysis to evaluate parameter uncertainties in model results for forest growth, gross primary production, leaf area index, evapotranspiration, soil water content and soil temperature. We also explored the sensitivity of model parameters for different vegetation distributions and climate conditions. The results of this study allow us to understand the vegetation dynamics and their impact on carbon and water fluxes which will be helpful to improve model parameterization and to provide more accurate estimates of carbon and water fluxes and climate model projections.

How to cite: Naz, B. S., Poppe, C., Hendricks-Franssen, H.-J., and Vereecken, H.: Modeling and evaluation of vegetation and carbon dynamics of European forest sites with CLM-FATES, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-7163, https://doi.org/10.5194/egusphere-egu22-7163, 2022.

Vegetation of temperate and boreal ecosystems increases its tolerance to freezing when temperatures decrease in autumn. This process is known as hardening, and results in a set of physiological changes at the molecular level that initiates the synthesis of anti-freeze proteins. Together with the freezing of extracellular water, these changes reduce plant water potentials and xylem conductivity. In this study, we implemented a hardening and frost mortality scheme into CTSM5.0-FATES-Hydro, and evaluate how these modifications impact plant hydraulics and vegetation growth. Our work shows that the hydraulic modifications prescribed by the hardening scheme are necessary to model realistic vegetation growth in cold climates, in contrast to the default model that simulates almost nonexistent and declining vegetation due to abnormally large water loss through the roots. The frost mortality scheme also simulates damage from frost events when temperatures drop below the hardiness level of plants, in contrast to the default model where frost is described by a constant PFT temperature threshold. This work makes it possible to use CTSM5-FATES-Hydro to model realistic impacts from frost and droughts on vegetation growth and photosynthesis, leading to more reliable projections of how northern ecosystems respond to climate change.

How to cite: Lambert, M., Tang, H., Aas, K. S., Stordal, F., Fisher, R. A., Bjerke, J. W., and Permentier, F.-W.: Towards realistic plant hydraulics and frost damage in the Arctic-Boreal Zone by modelling cold acclimation in CTSM5-Fates (hydro), EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-4068, https://doi.org/10.5194/egusphere-egu22-4068, 2022.

Limited process-representation of plant hydraulics in Dynamic Global Vegetation Models (DGVMs) impacts our ability to improve our understanding of the effect of plant water availability on vegetation dynamics and vegetation carbon content.  More detailed plant hydraulics have so far been only introduced in a few DGVMs. Here, we apply the new hydraulics version of the DGVM LPJ-GUESS to explore the impact of hydraulic functional traits on plant productivity and succession dynamics. We perform a sensitivity analysis on hydraulic and shade-tolerance traits across different Plant Functional Types (PFTs).

Our study is performed at multiple sites along a water-availability gradient in a temperate environment. We put special focus on exploring the simulated interplay between shade-tolerant and intolerant broadleaf summergreen PFTs and discuss the most sensitive parameters and the implications of constraining them for future climate projections.

How to cite: Eckes-Shephard, A., Papastefanou, P., Rammig, A., and Pugh, T. A. M.: Parameter sensitivity of plant productivity in a plant hydraulics-enabled DGVM, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-13225, https://doi.org/10.5194/egusphere-egu22-13225, 2022.

The Amazon rainforest is the largest intact tropical forest ecosystem and stores about 120 Pg of carbon. To this day, it acts as a carbon sink by taking up carbon from the atmosphere, however, long-term observations show a decline in strength of this carbon sink, a trend that at current rates would likely lead to the Amazon basin becoming a carbon source around year 2050. The reasons for this declining trend are disputed, increasing temperatures and more frequent and intense droughts are becoming the potential drivers. Vegetation modelling offers a possibility to disentangle the effects of these drivers, however, most Dynamic Global Vegetation Models (DGVMs) or Earth System Models (ESMs) are still not able to reproduce this observed carbon sink decline and the correct response of vegetation to drought stress. Here, we apply a new version of the DGVM LPJ-GUESS with improved plant hydraulics. It is one of the few state-of-the-art DGVMs that can successfully (1) capture the carbon dynamics under severe drought stress and (2) reproduce the current observed declining trend of the carbon sink. We investigate whether the Amazon rainforest will recover its sink strength or turn into a carbon when driven by climate projection source from the latest Inter-Sectoral Impact Model Intercomparison Project (ISIMIP 3a), using multiple forcing datasets. The simulations show strongly diverging response patterns of the Amazon rainforest that depend on both the selected emission scenario (e.g. SSP5-8.5 or 1-2.6) and the climate model (e.g. UKESM vs. ESM4). Using the SSP5-8.5 scenarios we find higher drought-induced carbon losses in the second half of the 21^st century compared to the first half of the century. However, these losses are partly (e.g. ESM4) or completely (e.g. UKESM) outweighed by higher carbon gains induced by higher CO₂ concentrations. Our findings highlight the complex interplay of CO₂ fertilization, higher atmospheric dryness (more negative vapour pressure deficit) and its effects on stomatal conductance. 

How to cite: Papastefanou, P., Pugh, T., Buras, A., Eckes-Shephard, A., Fleischer, K., Grams, T., Gregor, K., Hickler, T., Krause, A., Lapola, D., Liu, D., Zang, C., and Rammig, A.: Diverging simulated effects of future drought stress on the Amazon rainforest , EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-12669, https://doi.org/10.5194/egusphere-egu22-12669, 2022.