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Present and future global vegetation dynamics and carbon stocks from observations and models

The terrestrial vegetation carbon balance is controlled not just by photosynthesis, but by respiration, carbon allocation, turnover (comprising litterfall, background mortality and disturbances) and wider vegetation dynamics. Observed, and likely future, changes in vegetation structure and functioning are the result of interactions of these processes with atmospheric carbon dioxide concentration, climate and human activities. The quantification and assessment of such changes has proven extremely challenging because of a lack of observations at large scales and over the long time periods required to evaluate trends.

Thus, our current understanding of the environmental controls on vegetation dynamics and properties, and, in turn, their impact on carbon stocks in biomass and soils, is limited. The behaviour of vegetation models regarding many of the processes mentioned above remains under-constrained at scales from landscape to global. This gives rise to high uncertainty as to whether the terrestrial vegetation will continue to act as a carbon sink under future environmental changes, or whether increases in autotrophic respiration or carbon turnover might counteract this negative feedback to climate change. For instance, accelerated background tree mortality or more frequent and more severe disturbance events (e.g. drought, fire, insect outbreaks) might turn vegetation into carbon sources. Likewise, understanding how these shifts in dynamics will influence forest composition is crucial for long-term carbon cycle projections.

Uncertainties and/or data gaps in large-scale empirical products of vegetation dynamics, carbon fluxes and stocks may be overcome by extensive collections of field data and new satellite retrievals of forest biomass and other vegetation properties. Such novel datasets may be used to evaluate, develop and parametrize global vegetation models and hence to constrain present and future simulations of vegetation dynamics. Where no observations exist, exploratory modelling can investigate realistic responses and identify necessary measurements. We welcome contributions that make use of observational approaches, vegetation models, or model-data integration techniques to advance understanding of the effects of environmental change on vegetation dynamics, tree mortality and carbon stocks and fluxes at local, regional or global scales and/or at long time scales.

Convener: Ana BastosECSECS | Co-conveners: Matthias Forkel, Aliénor Lavergne, Thomas Pugh, Martin Thurner
| Mon, 23 May, 13:20–14:50 (CEST), 15:10–18:30 (CEST)
Room 3.16/17

Mon, 23 May, 13:20–14:50

Chairpersons: Aliénor Lavergne, Thomas Pugh


Yong Zhou and Carla Staver

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.

Klaske van Wijngaarden et al.

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.

[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.

Laura Thölix et al.

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.

Holger Lange et al.

The three-dimensional structure of forest canopies is essential for light use efficiency, photosynthesis and thus carbon sequestration. Therefore, high-quality characterization of canopy structure is critical to improving our carbon cycle estimates by Earth system models and better understanding disturbance impacts on carbon sequestration in forested ecosystems.

In this context, a widely used observable is the Leaf Area Density (LAD) and its integral over the vertical dimension, the Leaf Area Index (LAI). A multitude of methods exists to determine LAD and LAI in a forest stand. In this contribution, we use a mature Norway spruce forest surrounding an ICOS flux tower at Hurdal site (NO-Hur) to investigate LAD and LAI with six different methods: field campaigns using (1) the Plant Canopy Analyzer LAI-2000; (2) the LaiPen LP 110; (3) Digital Hemispheric Photography at a set of plots within the area; (4) a Lidar drone flight covering the footprint area of the tower; (5) an airborne Lidar campaign, and (6) a satellite LAI product (MODIS).

The horizontal spatial structure of LAI values is investigated using marked point process statistics. Intercomparison of the methods focusses not only on biases and root mean squared errors, but also on the spatial patterns observed, quantifying to which extent a simple bias correction between the methods is sufficient to make the different approaches match to each other.

How to cite: Lange, H., Tsai, Y.-Y., and Cerny, J.: Leaf Area Index at a forested ICOS site: a detailed method comparison, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-3124, https://doi.org/10.5194/egusphere-egu22-3124, 2022.

Raphael Garisoain et al.

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.

Julia Maschler et al.

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.

Daniel Nadal-Sala et al.

Tree mortality rates have increased in Europe during the last three decades with trends  expected to keep increasing into the future. This makes long-term forest health monitoring essential. In this regard, Landsat satellite observations provide annual estimates of canopy disturbance at moderate (30 meters) resolution. However, canopy disturbances do not always translate directly into tree mortality, as satellites only observe canopy trees at an aggregated grid level. Therefore, there is a need to validate Landsat estimates against actual ground-based tree mortality measurements. In this sense, National Forest Inventories (NFI) quantify the spatial distribution of tree mortality at regional level, but they are costly and have a lower temporal resolution than satellite observations (mostly every ten years). NFI are potentially an excellent asset to validate Landsat estimates, though the spatial agreement between NFI-derived tree mortality and Landsat disturbance estimates has yet to be assessed.

Here we compare Landsat spatial canopy disturbance rates with tree mortality rates derived from the 2nd and 3rd Spanish National Forest Inventories for the 1986-2008 period (n = 45564 stands). We compared the spatial distribution of Landsat canopy disturbance rates with the inventory-derived tree and biomass mortality rates on a grid size of 0.25°. There is positive correlation between satellite estimates and tree mortality obtained from inventories (r = 0.52, p < 0.001). In the case of biomass mortality, the correlation disappears (r = 0.26, p > 0.05). The correlation also weakens as the number of inventoried stands per forest cover extension decreases at grid level. In addition, both canopy disturbance rates and measured tree mortality rates were positively correlated with burned area, thus highlighting fire as a major driver of forest disturbance in Spain. Our results demonstrate that Landsat estimates are correlated spatially with tree mortality obtained from NFI, opening the door to make such analysis extensive to other European countries.

How to cite: Nadal-Sala, D., Senf, C., Pugh, T., Ruehr, N., Astigarraga, J., Ruiz-Benito, P., Zabala, M. A., and Esquivel-Muelbert, A.: Do Landsat satellite estimates of canopy disturbance reproduce tree mortality rates observed from forest inventories across Spain?, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-3593, https://doi.org/10.5194/egusphere-egu22-3593, 2022.

Eva-Marie Schömann et al.

The semi-arid Australian continent significantly influences the interannual variability of the global terrestrial carbon sink. Atmospheric inverse models can be used to estimate land carbon fluxes from CO2 measurements, and study the underlying processes leading to their variability. The spatial coverage of in-situ CO2 measurements over Australia is sparse, leading to large uncertainties in estimated carbon fluxes for the Australian continent. Satellite measurements of CO2 offer an independent and spatially extensive source of information about the Australian carbon cycle.

Here, we examine the decadal data set (2009-2018) of atmospheric CO2 mole fractions delivered by the Greenhouse Gases Observing Satellite (GOSAT) above Australia. We estimate land CO2 fluxes from those measurements via the TM5-4DVAR inverse model and discuss their seasonal and interannual variability. Compared to flux estimates constrained by in-situ mole fraction measurements alone, GOSAT-based inversions suggest greater variability attributable to the seasonal dynamics of biogenic and fire fluxes. To investigate the mechanisms behind the variability, we compare to bottom-up carbon fluxes from the FLUXCOM and the TRENDY ensemble of global dynamic vegetation models.

How to cite: Schömann, E.-M., Vardag, S. N., Basu, S., Jung, M., Sitch, S., and Butz, A.: Seasonal and Interannual Variability of Australian Carbon Fluxes Seen by GOSAT, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-3849, https://doi.org/10.5194/egusphere-egu22-3849, 2022.

Susanne Suvanto et al.

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.


Mon, 23 May, 15:10–16:40

Chairpersons: Ana Bastos, Aliénor Lavergne

Maurizio Santoro and the ESA/JAXA CCI Biomass Team

Characterization and quantification of terrestrial global carbon stocks increasingly integrates spaceborne remote sensing data. The wide range of multi-decadal time series of temporally consistent observations is key to understanding global processes related to terrestrial vegetation. As the organic mass stored in vegetation cannot be sensed, uncertainties in estimates of carbon stocks from remote sensing data can only be reduced by complementing multiple observations. This aspect is even more crucial given the weak sensitivity of the signals acquired by most systems in space to vegetation structural parameters. High-resolution observations, in addition, better allow natural events (e.g., fires) or processes (e.g., forest dieback) or human activities (e.g., shifting cultivation) to be identified, which in turn, improves understanding and explanations of vegetation carbon dynamics.

Time series of above-ground biomass (AGB, live) maps by the European Space Agency (ESA) Climate Change Initiative (CCI) Biomass for the years 2010, 2017, 2018 and 2020 were obtained from a combination of freely available high-resolution C- and L-band radar, laser and optical satellite observations. The pixel size of the maps was set at 100 m as a compromise between preserving spatial detail and reducing observational noise. The non-uniform temporal spacing of the mapping was selected to provide a first assessment of short- and long-term AGB dynamics.

Independent assessment based on in situ plots distributed across the major forest biomes and LiDAR-derived maps of AGB indicated a reliable representation of forest AGB levels globally. This first version of the CCI Biomass maps is therefore sufficiently reliable for identifying areas of changes that impact on the terrestrial carbon cycle. On the contrary, the presence of local biases and a 30-40% uncertainty relative to the estimated value do not allow for an estimate of AGB dynamics at the level of individual pixels. Such errors can be attributed to data quality or approximations in the models relating AGB to the remote sensing data.

Coupling biomass and land cover CCI data products revealed that, between 2010 and 2020, the terrestrial AGB pool in forests fluctuated between 550 Pg and 560 Pg while the global forest area increased by 1%. AGB changes were particularly evident in areas associated with persistent forest land, with areas such as western Canada and northeast Europe losing biomass whilst others (e.g., central and southeast Asia) experienced net gains. Differentiation between natural and plantation forests was not achieved and so the relative contribution of losses and gains associated with each was not able to be discerned. Conversion of forest to cropland and grassland resulted in a loss of approximately 0.8 Pg of AGB whilst conversion of these non-forest landscapes to forest increased the global AGB pool by 0.2 Pg.

This presentation will review these emerging trends and give a perspective on the future suite of ESA CCI Biomass data products, which foresee a more regular temporal sampling, an extended time interval, and the inclusion of a wider range of recent satellite observations (e.g., by spaceborne LiDAR) and satellite data products with improved radiometric quality.

How to cite: Santoro, M. and the ESA/JAXA CCI Biomass Team: Emerging trends in global forest above-ground biomass derived from a decadal time record of high-resolution satellite observations, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-7392, https://doi.org/10.5194/egusphere-egu22-7392, 2022.

Manan Bhan et al.

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 20th century. Here, by integrating inventory-based information on land use and carbon densities in a closed-budget land accounting approach, we establish a mid-20th century global carbon stocks account. Our approach integrates global forest assessments from the mid-20th century, previously ignored in global land change studies, and inventory-based land use reconstructions across the 20th 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-21st 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 20th 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.

jun li et al.

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.

Xin Yu et al.

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.

Martijn Pallandt et al.

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.

Viola Heinrich et al.

The Forest and Land use Declaration negotiated at the 26th climate Conference of the Parties (COP) in Glasgow, November 2021, confirmed that Tropical Moist Forests (TMFs) are a vital nature-based solution to addressing the climate and ecological emergencies. TMFs are estimated to be a net sink of carbon, storing approximately 0.8 Pg C yr-1 [1]. However, the size of this sink is declining due to human activities such as deforestation and forest degradation through logging and fire, as well as climate variability and change1. Tropical forests are therefore a patchwork of undisturbed, degraded, and secondary forests, creating regionally complex patterns of growth and carbon storage.

While there have been numerous studies exploring and quantifying the recovery rates of secondary forests, quantifying the recovery rate of degraded forests has been largely unexplored on a pan-tropical scale. In this study, we address this knowledge gap by quantifying the carbon accumulation in recovering degraded forests as well as secondary forests, which collectively, we have termed “Recovering Forests”.

Recent advances in remote sensing products have made it possible to (i) observe and distinguish degraded forests from undisturbed and secondary forests2; and (ii) estimate the carbon sequestration rates within these forests3,4.

Here we use a combination of remote sensing derived products in a space-for-time substitution approach to quantify the carbon accumulation rates in recovering forests. This includes recovering degraded forests and secondary forests in the three major tropical biomes: the Amazon Basin, Island of Borneo and Congo Basin.

Our results show growth rates to be the highest in Borneo, in recovering degraded forests5. We attribute these inter-biome/forest variations in growth to differences in disturbance and find that environmental variables such as water deficit and temperature influence the recovery of forests in unique ways across the tropics. We also provide estimates of the current and future carbon sink of recovering forests across the three biomes.

We find that recovering degraded forests have a large carbon sink potential, owing largely to their vast areal extent (10% of forest area). Secondary forests, regrow across a smaller land area (2%) but have faster growth rates (up to 30% faster in the Amazon basin) compared to degraded forest recovery. Additionally, we find that 35% of degraded forest are subject to subsequent deforestation2,5, emphasizing the need for continuous monitoring as well as their protection to safeguard the carbon stock in all recovering forests. Our results provide insights into the dynamic patterns of tropical forest recovery, influenced by interactions of humans and the environment that have the potential to improve global vegetation models as well as help to inform national forest inventories.


1 Hubau, W. et al. Nature 579, 80–87 (2020).

2 Vancutsem, C. et al. Sci. Adv. 7, eabe1603 (2021).

3 Santoro, M. & Cartus, O. Centre for Environmental Data Analysis  (2021). 

4 Heinrich, V. H. A. et al.  Nature Commun. 12, 1785 (2021).

5 Heinrich, V. H.A. et al. One quarter of humid tropical forest loss offset by recovery. (in Review).

How to cite: Heinrich, V., Vancutsem, C., Dalagnol, R., Rosan, T., Fawcett, D., Silva Junior, C., Achard, F., Jucker, T., House, J., Sitch, S., Hales, T., and Aragão, L.: What is the current and future carbon sink potential of recovering secondary and degraded forests across the humid tropics?, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-9740, https://doi.org/10.5194/egusphere-egu22-9740, 2022.

Laibao Liu and Sonia Seneviratne

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.

Matteo Mastropierro and Davide Zanchettin

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.

Elisabeth Tschumi et al.

The frequency and severity of droughts and heatwaves are projected to increase under global warming. However, their impacts on the terrestrial biosphere and the anthropogenic CO2 sink remain poorly understood. Here we analyse the effects of six hypothetical climate scenarios with stationary climate but differing drought-heat signatures on vegetation distribution and land carbon dynamics, as modelled by seven state-of-the-art dynamic global vegetation models. The six forcing scenarios are sampled from a long climate model simulation and consist of a control scenario representing a natural climate, a scenario with no hot and dry extremes, one with no compound hot and dry extremes but univariate extremes are possible, one with only hot extremes, one with only dry extremes, and one with both hot and dry extremes. Models show substantial differences in their vegetation coverage response to the different scenarios. While in some models, climate with no droughts and heatwaves favours tree growth, this is not the case for other models, where grasses benefit. Similarly, climates with frequent droughts promote grasses in some models and reduce forest growth in others. Models tend to agree that a climate with frequent concurrent droughts and heatwaves leads to reduced tree cover and increased grass cover. The changes in coverage are mirrored by changes in gross and net carbon fluxes. The stark differences among model responses illustrate the different modelling processes dealing with heat and drought stress and how they are differently affected by the extremes. Overall, this comparison helps quantify model uncertainties and process differences that are important for how vegetation behaves under extreme climate events.

Our study illustrates how factorial model experiments can be employed to disentangle the impacts from single and compound extremes. The findings from this model comparison may also help to identify sources of uncertainty in carbon cycle projections.

How to cite: Tschumi, E., Lienert, S., Bastos, A., Gregor, K., Joos, F., Knauer, J., Pongratz, J., Rammig, A., Thiery, W., van der Wiel, K., Wey, H., Williams, K., Yao, Y., Zaehle, S., and Zscheischler, J.: The effect of differing drought-heat signatures on terrestrial carbon dynamics and vegetation composition: a multi-model comparison, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-7120, https://doi.org/10.5194/egusphere-egu22-7120, 2022.

Manoj Hari and Bhishma Tyagi

Rapid climate change exerts a burden on terrestrial primary productivities, which perturb the carbon budget. Being an atmospheric pollutant, a high load of aerosols dampens/overweigh the diffuse radiation; likewise, optimal aerosol load upsurges diffuse radiation and enhance plant photosynthesis (Net Primary Productivity; NPP). This cascading effect is inevitable for understanding the enviro-climate feedbacks, backing which, the present study is framed for multiple ecosystems of India using MODIS products with Carnegie-Ames Stanford Approach (CASA) model. The sensitivity of NPP to aerosol loading was analysed on a decadal scale, isolated for 2001 – 2020. The analysis revealed that, for the Indian scenario, when the overall AOD was greater than 42% above the threshold, i.e., relatively more than 0.81, it cribs NPP. Contrastingly, NPP was influenced when the AOD was at 14% (0.32). The analysis highlighted that the maximum NPP for the forest ecosystems was observed when AOD was 0.38, and the growth persisted with higher AOD until 0.51. In contrast, the agroecosystem's NPP growth was restricted at 0.59, and maximum growth was observed with 0.49. Even though agroecosystems indicated the maximum NPP growth with higher AOD, the fertilisation effects were comparatively lower than the forest ecosystem due to the consistent, intense AOD load over the croplands (especially over the Indo Gangetic Pain belt). This indicated that the vegetational adaptiveness in the agrosystems to the effect of aerosol was weaker than the forest-based ecosystems. Presumably, anthropogenic interventions in cropland management (biomass burning) may also have steered the sensitivity responses of NPP. Based on the analysis, the presented study elucidates the need for considering the intricating aerosol effects on ecosystem productivity in projecting the Indian terrestrial carbon cycle under changing climate.

Keywords: Aerosol; CASA; India; Net primary productivity; Radiative forcing; Terrestrial carbon cycle

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.

Lucia S. Layritz et al.

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.


Mon, 23 May, 17:00–18:30

Chairpersons: Thomas Pugh, Ana Bastos

Martin De Kauwe et al.

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.

Jan De Pue et al.

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.

Sven Westermann et al.

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.

Yitong Yao et al.

During the last two decades, droughts have recurrently impacted the Amazon forests, as in the severe drought events of 2005, 2010 and 2015/16. The analysis of forest inventory plots suggests that these droughts have resulted in a reduction of the carbon sink of intact forests by causing mortality to exceed growth. Process-based models have struggled to include drought-induced responses of growth and mortality, and have not been evaluated against plot data. In this study, we use ORCHIDEE-CAN-NHA, a DGVM which includes modules of forest demography with different tree size cohorts dynamically influenced by growth, self-thinning from light competition and recruitment, a detailed tree hydraulic architecture function of each tree cohort, and drought-driven mortality due to the loss of tree conductance to simulate the impact of drought on biomass dynamics. We calibrated the model at a long drought experiment site (Caxiuanã). We then ran the model over Amazonia forests using as an input gridded climate fields and rising atmospheric CO2 from 1901 to 2019. The model reproduced the drought sensitivity of aboveground biomass (AGB) growth and mortality observed at forest plots across selected Amazon intact forests for 2005 and 2010, and the net balance between these two carbon fluxes. No plot data have been published yet for the recent 2015/16 El Nino, but we predict a more negative sensitivity of the net carbon sink during this event compared to the former 2005 and 2010 droughts. We then ranked all past drought events of the last century based on their maximum cumulated water deficit anomalies, and found that 2015/16 was the most severe drought in terms of both AGB loss and area experiencing a severe carbon loss. Because of the 2015/16 event, together with the 2005 and 2010 droughts, the last 20 years was the period with the largest climate-driven cumulative AGB loss than any other previous 20-years period since 1901. Factorial simulations allowed us to separate the individual contribution of climate change and rising CO2 concentration on AGB dynamics. We found that even if climate change did increase mortality, increased CO2 concentration contributed to balance the C loss due to mortality. This is because, in our model, CO2-induced stomatal closure reduces transpiration and increases soil moisture, offsetting increasing transpiration from CO2 induced higher foliage area.

How to cite: Yao, Y., Ciais, P., Viovy, N., Chave, J., and Joetzjer, E.: How drought events during the last Century have impacted biomass carbon in Amazonian rainforests, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-3686, https://doi.org/10.5194/egusphere-egu22-3686, 2022.

Bahar Bahrami et al.

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.

Benjamin Lanssens et al.

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.

Alexandra Pongracz et al.

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.

Jennifer A. Holm et al.

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.

Bibi S. Naz et al.

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.

Marius Lambert et al.

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.

Annemarie Eckes-Shephard et al.

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.

Phillip Papastefanou et al.

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 21st 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.