BG3.2

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.

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.

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.

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.

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.

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.

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.

The Forest and Land use Declaration negotiated at the 26^th 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 forests^3,4.

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 deforestation^2,5, 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.

References:

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.

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.

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.

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.

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.

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 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.