BG3.6 | Present and future global vegetation dynamics and carbon stocks from observations and models
EDI
Present and future global vegetation dynamics and carbon stocks from observations and models
Convener: Martin ThurnerECSECS | Co-conveners: Ana Bastos, Matthias Forkel, Aliénor Lavergne, Thomas Pugh
Orals
| Mon, 15 Apr, 14:00–15:45 (CEST), 16:15–18:00 (CEST)
 
Room N1
Posters on site
| Attendance Mon, 15 Apr, 10:45–12:30 (CEST) | Display Mon, 15 Apr, 08:30–12:30
 
Hall X1
Orals |
Mon, 14:00
Mon, 10:45
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, nutrient availability, 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.

This limited observation base 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, will accelerated background tree mortality or more frequent and more severe disturbance events (e.g. drought, fire, insect outbreaks) turn vegetation into carbon sources? How will shifts in dynamics of plant mortality, establishment and growth influence forest composition?

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.

Orals: Mon, 15 Apr | Room N1

The oral presentations are given in a hybrid format supported by a Zoom meeting featuring on-site and virtual presentations. The button to access the Zoom meeting appears just before the time block starts.
Chairpersons: Martin Thurner, Ana Bastos, Matthias Forkel
14:00–14:05
New observations and modelling approaches of vegetation dynamics
14:05–14:25
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EGU24-4183
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BG3.6
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solicited
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Highlight
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On-site presentation
Wannes Hubau and the DAMOCO, PILOTMAB & CANOPI consortium

Congo Basin forests are among the most diverse, carbon-rich and CO2-absorbing areas in the World (1,2) and play an increasingly important role in international climate policy (3). On the pivotal CoP26 in Glasgow, more than 100 World leaders promised to stop deforestation by 2030, including specific pledges to focus on protecting Congo Basin forests. However, there is a striking discrepancy between the Congo Basin’s paramount importance versus its poor scientific coverage (4). As a result of this data gap, Earth System Models are not capturing present-day tropical forest carbon dynamics (5). Therefore, our consortium is contributing to closing the Congo Basin forest data gap and improve Land Surface Models to capture its biodiversity and carbon dynamics. To reach this ambition, we are collecting field data on permanent forest inventory plots scattered across the Congo basin.

The data covers multiple time scales by combining different methodological approaches: (i) weakly monitoring of cambial and foliar phenology of selected trees in the plots provides seasonal- and annual-scale changes in carbon uptake, (ii) repeated tree diameter and height measurements of all trees in the plots reveal decadal-scale changes in the carbon balance and tree community composition, (iii) measuring whole-tree, wood and leaf traits on selected trees in the plots allow in-depth analysis of decadal-scale changes in taxonomic and functional composition, (iv) identification of radiocarbon dated soil charcoal sampled in the plots reveal century-scale and millennial-scale changes in biodiversity, (v) continuous monitoring of climate variables provides yearly and decadal-scale changes in temperature and water availability.

By themselves, those data shed light on the short- and long-term resilience of critical Congo Basin forest ecosystem functions. Here we present an overview of recently published and preliminary results showing how our consortium contributes to advance our understanding of the effects of environmental change on vegetation dynamics, tree mortality and carbon dynamics of Congo Basin forests. Combining all these collected field data will ultimately allow to parameterize and validate Land Surface Models specifically for the Congo Basin.

1.Hubau, W. et al. Nature 579, 80–87 (2020). 2. Jung, M. et al. Nat. Ecol. Evol. 5, 1499–1509 (2021). 3. Rockström, J. et al. PNAS 118, 1–5 (2021). 4. White, L. J. T. et al. Nature 598, 411–414 (2021). 5. Koch, A., Hubau, W. & Lewis, S. L. Earth’s Future. 9, 1–19 (2021).

How to cite: Hubau, W. and the DAMOCO, PILOTMAB & CANOPI consortium: Closing the data gap to develop Land Surface Models for Congo Basin forests, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-4183, https://doi.org/10.5194/egusphere-egu24-4183, 2024.

14:25–14:35
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EGU24-12243
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BG3.6
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ECS
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On-site presentation
Muhammed Sinan, Mathias Neumann, and Hubert Hasenauer

In Austria, the Austrian Federal Office and Research Centre for Forests (BFW) provides basic forest data such as volume stock or the national carbon inventory. The Austrian carbon inventory currently records the carbon stored in the bark as part of the forest's total tree carbon stock. However, tree bark plays a vital role in the life span of a tree and is also important for the decomposition process following tree death. There is a veritable need to quantify the proportion of bark accurately because it has an important impact on economic calculations. In this study we assess the amount of carbon stored in the stem bark of Austrian commercial forests (in German “Wirtschaftswald”) as it can be derived from (i) the taper curve, (ii) the bark percentage, (iii) the bark density, and (iv) the bark fissure index. We applied this “bark carbon model" to the latest data from the Austrian National Forest Inventory (NFI). The model predicts for each tree the corresponding bark carbon content, which can be easily aggregated to plot or regional level for further use. Our results suggest, that about 7% of the total carbon in Austrian commercial forest is stored in the bark of the tree stems. The findings provide bark carbon information that can also be used for other purposes like potential harvesting of bark, or determining the fire adaptation of tree species. Moreover, this study helps to provide information for the bark carbon share of the Austrian National carbon inventory.

How to cite: Sinan, M., Neumann, M., and Hasenauer, H.: The bark carbon storage of Austrian commercial forests, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-12243, https://doi.org/10.5194/egusphere-egu24-12243, 2024.

14:35–14:45
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EGU24-21672
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BG3.6
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ECS
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On-site presentation
Nezha Acil, Richard Lucas, Maurizio Santoro, and Heiko Balzter

Recent advances in the spatial resolution and sensitivity of satellite sensors have allowed the mapping of aboveground biomass (AGB) with enhanced levels of detail and a wall-to-wall worldwide coverage. However, determining the magnitude and direction of AGB changes over time remains challenging due to large uncertainties in AGB estimates (biases and random errors), inconsistencies across sensors/instruments and limited availability of ground-truth data (national forest inventories, multi-census plots and airborne lidar). Combining multiple environmental descriptors derived from independent (mainly optical) satellite-based data sources, we apply a framework that infers evidence of pressures and impacts to characterise temporal changes in vegetation (fast or slow, gain or loss) and check agreement with the changes detected in the global ESA CCI Biomass time series product. We deploy the approach at the global scale focusing on forests that we define with a tree cover greater than 10% and tree height greater than 5 m. We illustrate the comparison with local case studies, highlighting processes such as regrowth, degradation and disturbances, and differentiating between natural and anthropogenic causes (e.g., wildfire, flooding, harvest, plantations). Selected sites represent different biomes and continents, including tropical moist forests in the Amazon, tropical drylands in Africa, temperate forests in Europe, Mediterranean woodlands in Australia and boreal forests in Siberia and North America. The results provide enhanced understanding of the processes underlying AGB changes in different regions and allow new insights into the quality of remotely-sensed AGB for tracking changes in carbon stocks and informing decision-making.

How to cite: Acil, N., Lucas, R., Santoro, M., and Balzter, H.: Characterising space-based aboveground biomass change: from global to local, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-21672, https://doi.org/10.5194/egusphere-egu24-21672, 2024.

14:45–14:55
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EGU24-7557
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BG3.6
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On-site presentation
Ruxandra-Maria Zotta, Leander Moesinger, Robin van der Schalie, Mariette Vreugdenhil, Wolfgang Preimesberger, Thomas Frederikse, Richard de Jeu, and Wouter Dorigo

Vegetation optical depth (VOD) is a model-based indicator derived from microwave Earth observations. It quantifies the attenuation of surface microwave emissions by the overlaying vegetation. VOD is an indicator of the total water content stored in the vegetation canopy and is related to vegetation density, its relative moisture content, and above-ground biomass (AGB). VOD has been used in various applications such as phenology analysis, drought,  biomass monitoring, and estimating the likelihood of fire occurrence, leaf moisture, and gross primary productivity. Most of these applications require consistent long-term measurements, which are not provided by single-sensor time series.  

The first version of the global, long-term Vegetation Optical Depth Climate Archive (VODCA v1)[1] enables long-term analysis by harmonising VOD retrievals from multiple passive microwave sensors, derived through the Land Parameter Retrieval Model (LPRM)[2]. VODCA v1 provides separate VOD products for different spectral bands, namely the Ku-band (period 1987–2017), X-band (1997–2018), and C-band (2002–2018).   

Here, we present a new version of the VODCA dataset. VODCA v2 comprises two new products: a multi-frequency product called VODCA CXKu (1987 – 2021), obtained by merging the C-, X- and Ku-band observations and an L-band product (2010 – 2021) based on LPRM-derived VOD from the SMOS (Soil Moisture and Ocean Salinity) and SMAP (Soil Moisture Active Passive) missions. Even though the single-frequency products of VODCA v1 have merits on their own, merging them into VODCA CXKu yields a dataset with lower random levels and improved temporal sampling. It provides similar spatiotemporal information to optical and microwave vegetation indicators, such as the Fraction of Absorbed Photosynthetically Active Radiation (fAPAR) from MODIS and the slope of the backscatter incidence angle relation of Metop ASCAT (ASCAT slope). VODCA CXKu agrees best with fAPAR in short vegetation (Spearman's R: 0.57) and broadleaf forests (Spearman's R: 0.49) and with ASCAT slope in grassland (Spearman's R: 0.48) and cropland (Spearman's R: 0.48). Additionally, VODCA CXKu shows temporal patterns similar to the Normalised Microwave Reflection Index (NMRI) from in situ L-band GNSS measurements of the Plate Boundary Observatory (PBO) and sapflow measurements from SAPFLUXNET. VODCA L shows strong spatial agreement (Spearman's R: 0.86) and plausible temporal patterns with yearly AGB maps from the Xu et al. (2021) dataset. 

We conclude that VODCA CXKu provides valuable information to study the vegetation canopy response to climate variability and anthropogenic impacts. We recommend using it in long-term vegetation monitoring studies focusing on short vegetation types and broadleaf forests. VODCA L provides valuable insight into AGB.

[1] Moesinger, L., Dorigo, W., de Jeu, R., van der Schalie, R., Scanlon, T., Teubner, I., and Forkel, M.: The global long-term microwave Vegetation Optical Depth Climate Archive (VODCA), Earth Syst. Sci. Data, 12, 177–196, https://doi.org/10.5194/essd-12-177-2020, 2020.  

[2] Van der Schalie, R., de Jeu, R.A., Kerr, Y.H., Wigneron, J.P., Rodríguez-Fernández, N.J., Al-Yaari, A., Parinussa, R.M., Mecklenburg, S. and Drusch, M., 2017. The merging of radiative transfer based surface soil moisture data from SMOS and AMSR-E. Remote Sensing of Environment189, pp.180-193. 

How to cite: Zotta, R.-M., Moesinger, L., van der Schalie, R., Vreugdenhil, M., Preimesberger, W., Frederikse, T., de Jeu, R., and Dorigo, W.: VODCA v2: Multi-sensor, multi-frequency vegetation optical depth data for long-term canopy dynamics and biomass monitoring , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-7557, https://doi.org/10.5194/egusphere-egu24-7557, 2024.

14:55–15:05
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EGU24-11047
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BG3.6
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ECS
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On-site presentation
Liling Chang, Shaoqing Liu, Alexander Antonarakis, Marcos Longo, Hao Tang, John Armston, and Paul Moorcroft

Reliable predictions of ecosystem dynamics and carbon stocks depend on accurate initialization of ecosystem states in process-based model simulations. Unlike traditional potential vegetation simulations which assume that ecosystems equilibrate with long-term climate, observation-initialized simulations integrate the impacts of previous history of disturbance events and human activities on ecosystem structure and composition. However, observation-constrained initialization is challenging at regional scales due to limited availability of spatially-comprehensive measurement data. In this study, we assimilate remote-sensing estimates of canopy structure from Global Ecosystem Dynamics Investigation (GEDI) and canopy composition from AVIRIS imaging spectrometry into Ecosystem Demography version 2 (ED2), a cohort-based Terrestrial Biosphere Model. We drive model simulations with future climate scenarios and rising atmospheric CO2 concentrations to predict ecosystem responses to environmental changes over an elevational transect region in California’s Sierra Nevada by the end of the century. Our simulations suggest that predictions are significantly impacted by ecosystem initial condition at the multi-decadal (50+ year) scale. The impacts are stronger in dense-canopy forests at mid-to-high elevations than woody savannahs at low elevations. Under a hotter and drier future climate with CO2 enrichment, ecosystems across the elevational transect are predicted to act as a net carbon sink but with marked changes in composition. Aboveground biomass (AGB) is predicted to increase at low elevations due to increasing abundance in both deciduous and coniferous trees. However, at mid-to-high elevations, AGB increases are caused by increasing abundance of coniferous trees but large declines in the abundance of deciduous trees. Our research demonstrates how large-scale remote-sensing data can be assimilated into process-based model simulations to improve future predictions of ecosystem dynamics.  

How to cite: Chang, L., Liu, S., Antonarakis, A., Longo, M., Tang, H., Armston, J., and Moorcroft, P.: Future Predictions of Ecosystem Changes in California’s Sierra Nevada over the coming century using Remote-Sensing Constrained Terrestrial Biosphere Model Simulations, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-11047, https://doi.org/10.5194/egusphere-egu24-11047, 2024.

15:05–15:15
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EGU24-17051
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BG3.6
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ECS
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On-site presentation
Siqing Xu, Yves Balkanski, Sebastiaan Luyssaert, Philippe Ciais, and Jean Sciare

In semi-arid regions, grasslands naturally display a self-organized pattern that optimizes resource utilization and productivity. Representing this type of vegetation in land surface model constitutes a difficult challenge. To simulate these grasses, the ORCHIDEE land surface model treats grass density as the ratio of the area occupied by individuals to the Plant Functional Type (PFT) area, assuming a fixed grass density of 1 for maximal occupancy. However, the fixed maximal grass density lacks the response of grassland to environmental perturbations. In addition, the low biomass contained in certain pixels results in frequent mortality, indicative of resource limitations at the plant individual level. To address this considerable limitation, we introduced dynamic reduction of grass density based on mortality indicators, hence enhancing individual biomass and alleviating mortality occurrences. The adaptive approach significantly decreased mortality events across most pixels while enhancing leaf area index (LAI) for the majority of them. Our findings suggest that optimizing resource through grass density reduction in response to environmental condition, could not only improve individual biomass to alleviate mortality but also enhance overall grassland production.

How to cite: Xu, S., Balkanski, Y., Luyssaert, S., Ciais, P., and Sciare, J.: Representation of dynamic grass density in land surface model ORCHIDEE trunk v4.1, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17051, https://doi.org/10.5194/egusphere-egu24-17051, 2024.

15:15–15:25
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EGU24-20269
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BG3.6
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On-site presentation
David Wårlind, Jette Elena Stoebke, Stefan Olin, Paul A. Miller, and Thomas A. M. Pugh

Several efforts are being pursued to improve the representation of ecological demographic processes that govern terrestrial vegetation canopy structure within Dynamic Global Vegetation Models (DGVM) as it influences critical fluxes of carbon, nutrients, and water. How trees are structured within the canopy determines how they absorb incoming solar radiation and is partitioned between different tree cohorts. Here we present two new schemes with more detailed vegetation canopy structure representation in the DGVM LPJ-GUESS. These new schemes provide a closer linkage to observations to better constrain processes of growth and mortality, improve the representation of species coexistence as well as the capability to represent reestablishment in small canopy gaps following small-scale mortality or selective harvest. LPJ-GUESS is currently structuring its canopy with vertically overlapping cohort crowns without horizontal spatial structure as the crowns are distributed uniformly across the entire patch area. This original approach does not provide a realistic representation of competition between trees of different heights and sizes, nor canopy gaps following mortalities. A first solution to amend the model is to adopt an approach similar to the perfect plasticity approximation in which cohorts are sorted according to tree height and perfectly fill the patch area with each cohort crown area. When the patch is filled an understory layer is created with the next tallest tree and so on for each consecutive layer. A second solution is to explicitly position cohorts within the patch according to forest floor light conditions during establishment. The death of a tree will result in a gap formation which will persist over time and allow new cohorts to establish within the gap exposed to full light conditions. All schemes have been evaluated against aboveground woody biomass, aboveground woody mortality, and aboveground woody productivity split into diameter at breast height size classes and how forestry thinning generates re-establishment of a woody understory. Also, their capability to represent species coexistence has been evaluated. We see improvements in the capability to simulate stand biomass-size distributions, species coexistence, and reestablishment in small canopy gaps with a more detailed canopy structure scheme.

How to cite: Wårlind, D., Elena Stoebke, J., Olin, S., A. Miller, P., and A. M. Pugh, T.: Representing canopy structure dynamics within the LPJ-GUESS dynamic global vegetation model, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-20269, https://doi.org/10.5194/egusphere-egu24-20269, 2024.

15:25–15:35
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EGU24-19555
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BG3.6
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On-site presentation
Rosie Fisher, Charles Koven, Ryan Knox, Jessica Needham, Gregory Lemiuex, Chonggang Xu, Adrianna Foster, Rutuja Chitra-Tarak, and Zachary Robbins

The relationship between carbon dioxide emissions and their accumulation in the atmosphere is one of the most important elements of the function of the Earth system.  Exertion of control over the terrestrial carbon budget, via afforestation, reforestation, bioenergy production and other methods to enhance land carbon storage (biochar, enhanced weathering) all imply a need to forecast and understand the dynamics of these carbon stores as they evolve in changing atmospheric CO2 and climatic conditions. The dynamics of the carbon cycle, however, are notably complex and require comprehension of models representing the functioning of numerous coupled systems which must produce predictions under these no-analog conditions, and so must necessarily embed process understanding to allow for meaningful extrapolation into the future. 

Models of the terrestrial biosphere, often embedded in Earth system models, thus contain advanced representations of a large set of processes that are known to impact ecosystem carbon storage.  This complexity, however, has presented a substantial barrier to objective calibration using conventional statistical approaches, as the number of model parameters and the computational expense of the models means that comprehensive exploration of the parameter space is effectively unmanageable. Further, many ecosystem processes exhibit non-linear and threshold properties (notably, vegetation death, competitive interactions, fire thresholds) and thus are challenging for methods that assume linearity. 

Here we propose a method for decomposing the complexity of one such model, the Functionally Assembled Terrestrial Ecosystem Simulator (FATES) that allows investigation, calibration and comprehension of individual parts of the system in isolation (driven by observed data fields). This ‘modular complexity’ approach allows the full complexity model to be run in a series of ‘modes’ that can operate as domain-specific models for, e.g. ecohydrology, community ecology, biogeochemistry etc. while also allowing the full complexity version to be used for higher order problems, such a predicting global vegetation dynamics under future climate scenarios.  We describe a series of investigations using FATES that illustrate the potential for this model decomposition approach and discuss the potential for further application of this philosophy. 

 

How to cite: Fisher, R., Koven, C., Knox, R., Needham, J., Lemiuex, G., Xu, C., Foster, A., Chitra-Tarak, R., and Robbins, Z.: How to model all the plants on Earth?  An approach to managing system complexity in the Functionally Assembled Terrestrial Ecosystem Simulator (FATES). , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-19555, https://doi.org/10.5194/egusphere-egu24-19555, 2024.

15:35–15:45
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EGU24-15303
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BG3.6
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On-site presentation
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Sebastian Wolf, David L. Miller, and Eugenie Paul-Limoges

Climate extremes threaten the land carbon sink and it is important to understand their impact in a changing climate. An elevated incidence of drought has been observed recently in some regions (e.g. Europe), and projections indicate an increased prevalence with climate warming. This is concerning because ecosystem carbon uptake currently mitigates increases in atmospheric CO2 concentrations. Although the link between drought and reduced carbon uptake is well established, important questions remain regarding the impact of recurrent droughts, the strength of seasonal and regional compensation effects, land-atmosphere feedbacks that can exacerbate heatwaves, and forest management strategies in a changing climate.

Here we present an overview on the current knowledge of drought impacts on ecosystem carbon uptake and related feedbacks on energy and water fluxes. These results are based on a recent perspective1 and a global synthesis of ecosystem flux measurements combined with terrestrial biosphere models (TBMs)2.

Reduced carbon uptake during drought originates from stress-related declines in photosynthesis. Respiration from plants and soil is also reduced due to limitations in soil moisture, but this is typically to a lower extent than photosynthesis. These relative differences result in reduced net carbon uptake or even net losses. For forests, the combined stress of intense drought over prolonged periods (or recurrent events) leads to increased crown and eventually tree mortality. During severe drought, enhancing (i.e. positive) land-atmosphere feedbacks often further exacerbate extremely dry and hot conditions: as water transpired by plants and evaporated from soils is reduced, evaporative cooling becomes less efficient and more of the available energy heats the air.

While ecosystem carbon uptake is typically reduced during severe summer drought1, there is also evidence for increased photosynthesis (i.e. gross primary productivity, GPP) during meteorological drought (i.e. precipitation deficit) in energy-limited ecosystems, particularly during spring2. Comparing ecosystem observations of GPP from eddy covariance (EC) flux towers across the Northern Hemisphere with TBM outputs across the water-energy limitation spectrum, we found a consistent increase in GPP from EC during spring drought in energy-limited ecosystems. Half of spring GPP sensitivity to precipitation was predicted solely from the wetness index (an indicator for aridity) , with weaker relationships in summer and fall. Our results suggest GPP increases during spring drought for 55% of vegetated Northern Hemisphere lands (>30° N). Comparing theses sensitivities with the output from TBMs indicated that the TBMs were insufficiently sensitive to spring precipitation deficits.

Reduced carbon uptake during drought might be no longer exceptional in a warming climate, revealing the vulnerability of the land carbon sink to such climate extremes – particularly for forests. Comparing ecosystem EC observations for GPP with TBMs indicates a need for TBMs to better account for the varying effects of meteorological drought on carbon cycling in mid- and high-latitude ecosystems.

 

References

1 Wolf S, Paul-Limoges E. (2023) Drought and heat reduce forest carbon uptake. Nature Communications, 14: 6217.

2 Miller DL, Wolf S, Fisher JB, Zaitchik BF, Xiao J, Keenan TF (2023) Increased photosynthesis during spring drought in energy-limited ecosystems. Nature Communications, 14: 7828.

How to cite: Wolf, S., Miller, D. L., and Paul-Limoges, E.: Impacts of drought on ecosystem carbon uptake, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-15303, https://doi.org/10.5194/egusphere-egu24-15303, 2024.

Coffee break
Chairpersons: Thomas Pugh, Ana Bastos, Martin Thurner
Processes of vegetation dynamics and impact on the carbon cycle
16:15–16:25
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EGU24-2558
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BG3.6
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solicited
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Highlight
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On-site presentation
Giovanni Forzieri and the DEFID2 team

Insect and disease outbreaks in forests are biotic disturbances that can profoundly alter ecosystem dynamics. In many parts of the world, these disturbance regimes are intensifying as the climate changes and shifts the distribution of species and biomes. As a result, key forest ecosystem services, such as carbon sequestration, regulation of water flows, wood production, protection of soils, and the conservation of biodiversity could be increasingly compromised. Despite the relevance of these detrimental effects, there are currently no spatially detailed databases that record insect and disease disturbances on forests at the pan-European scale. Here, we present the new Database of European Forest Insect and Disease Disturbances (DEFID2). It comprises over 650,000 harmonized georeferenced records, mapped as polygons or points, of insects and disease disturbances that occurred between 1963 and 2021 in European forests. The records currently span eight different countries and were acquired through diverse methods (e.g., ground surveys, remote sensing techniques). The records in DEFID2 are described by a set of qualitative attributes, including severity and patterns of damage symptoms, agents, host tree species, climate-driven trigger factors, silvicultural practices, and eventual sanitary interventions. They are further complemented with a satellite-based quantitative characterization of the affected forest areas based on Landsat Normalized Burn Ratio time series, and damage metrics derived from them using the LandTrendr spectral-temporal segmentation algorithm (including onset, duration, magnitude, and rate of the disturbance), and possible interactions with windthrow and wildfire events. The DEFID2 database is a novel resource for many large-scale applications dealing with biotic disturbances. It offers a unique contribution to design networks of experiments, improve our understanding of ecological processes underlying biotic forest disturbances, monitor their dynamics and enhance their representation in land-climate models. Further data sharing is encouraged to extend and improve the DEFID2 database continuously. The database is freely available at https://jeodpp.jrc.ec.europa.eu/ftp/jrc-opendata/FOREST/DISTURBANCES/DEFID2/.

How to cite: Forzieri, G. and the DEFID2 team: The Database of European Forest Insect and Disease Disturbances: DEFID2, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-2558, https://doi.org/10.5194/egusphere-egu24-2558, 2024.

16:25–16:30
16:30–16:40
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EGU24-16050
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BG3.6
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Highlight
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On-site presentation
Pieter Zuidema, Flurin Babst, Peter Groenendijk, Mizanur Rahman, and Valerie Trouet and the Tropical Tree-ring Network

An increasing incidence and intensity of droughts under anthropogenic climate change jeopardizes the potential of tropical forests and woodlands to capture carbon in woody biomass and act as CO2 sink. A pantropical quantification of drought impacts on tree stem growth is needed to evaluate this risk.

We assessed drought impacts in a pantropical network of 477 tree-ring chronologies (>10,000 trees from >150 species and 35 plant families) and found modest stem growth declines (median: 2-4%) during drought years. Growth declines were larger for dry-season than wet-season droughts, specifically for Gymnosperms, and at hotter and more arid sites. Lagged growth reductions during post-drought years were rare. Over half of the growth reduction during drought years was mitigated during wet extreme years.

Thus, drought impacts on tropical forest carbon sequestration through stem growth have been small and short-lived. Yet, risks of increasing drought-induced carbon loss is expected to aggravate under climate change, in particular through elevated mortality associated with droughts.

How to cite: Zuidema, P., Babst, F., Groenendijk, P., Rahman, M., and Trouet, V. and the Tropical Tree-ring Network: Pantropical tree growth resilience to drought , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-16050, https://doi.org/10.5194/egusphere-egu24-16050, 2024.

16:40–16:50
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EGU24-16058
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BG3.6
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ECS
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On-site presentation
Stephen Byrne, Ken Byrne, Brian Tobin, Silvia Caldararu, Blair Ruffing, Luke Dowd, and Matt Saunders

Climate change poses a significant threat to the carbon (C) sequestration capacity of Irish forests, exacerbated by heightened risks from pests, pathogens, and escalating climate extremes, including drought and intense rainfall. Building resilience in forest ecosystems is vital to protecting the ecosystem services they deliver and has therefore gained increased attention from both research and industry. ADAPTForRes is a project dedicated to assessing forest management options and identifying enhanced climate-smart mitigation strategies.

In this study, we utilise Eddy Covariance (EC), soil chamber and biometric methodologies to investigate the C stock and flux dynamics of three distinct forest types: commercial Sitka spruce coniferous forest on mineral soil, broadleaf-dominated native woodland on mineral soil, and a mixed species (Norway spruce and Birch) forest on peat soil. Initial results suggest that the Sitka spruce forest nearing the end of its first rotation assimilates the most C, while the native deciduous broadleaved forest shows near C neutrality due to the age/maturity of the stand and high quantities of decaying biomass on the forest floor. The C dynamics of the Norway spruce/Silver birch mixed forest were dominated by high levels of ecosystem respiration driven by the high organic content of the soil and low water table heights in summer.

Furthermore, advanced footprint analyses have been employed to address the heterogenous nature of the native Irish forest studied here – acknowledging challenges posed by dynamic forest management practices, diversity in vegetative distribution and complex terrain. This approach provides additional insight into the flux dynamics from the forest compartments and encompasses management practices (thinning, clearfelling, underplanting), phenology (budburst, leaf expansion, senescence), inventory (species, ages, height), NDVI and disease outbreak information. The additional parameters generated from this analysis enhances data richness, allowing for a greater understanding of ecosystem C dynamics. Additionally, biometric stocks of C and soil derived C flux measurements including auto- and heterotrophic partitioning experiments have been conducted to further explore the impacts of forest composition and management on fluxes from wider ecosystem carbon pools.

These data are also being used in combination with the QUINCY land surface model to assess the model’s performance in capturing the effects of management, soil, forest type and climate on the ecosystem C balance. The EC data provides a foundational basis for the development and parameterization of the model, whereby ground-truthing is increasing our predictive capacity for future C budgets under various management regimes and varying magnitudes of climate change. The EC, biometric and soil flux data in combination with QUINCY model outputs will inform future management options for greater adaptability, as well as policy targets around strategic land-use goals for multifunctional and resilient forests.

How to cite: Byrne, S., Byrne, K., Tobin, B., Caldararu, S., Ruffing, B., Dowd, L., and Saunders, M.: ADAPTForRes: Assessing Forest resilience and carbon dynamics in differing Irish forest types to promote more sustainable sinks, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-16058, https://doi.org/10.5194/egusphere-egu24-16058, 2024.

16:50–17:00
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EGU24-10400
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BG3.6
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ECS
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On-site presentation
Lucia S. Layritz, Konstantin Gregor, Andy Krause, Stefan Kruse, Ben Meyer, Tom A. M. Pugh, Carl Boettiger, and Anja Rammig

In the evergreen boreal forest, field studies show that vegetation does not always regenerate to its previous state after disturbance but instead transitions to systems dominated by deciduous trees or non-forest vegetation. Gaining a better understanding of drivers and impacts of post-disturbance recovery is thus crucial to accurately project future vegetation dynamics and associated impacts on the carbon, water, and energy balance of the region. We here perform simulations with the dynamic vegetation model LPJ-GUESS to investigate (1) if observations of post-disturbance recovery dynamics can be reproduced in the model, (2) which environmental factors control such shifts, and (3) how these in turn influence land surface properties such as albedo and evapotranspiration. We find that post-disturbance recovery trajectories can be clustered into distinct response patterns of recovery and shifts to alternative plant types. These shifts occur even in places where multiple plant types can in theory establish in the model and thus emerge due to shifts in competitive advantage mediated by warming and soil properties. We further find that shifts from forested to non-forested ecosystems have strong impacts on land-surface properties while shifts between different forest types are less impactful. We conclude that LPJ-GUESS is capable of reproducing observed disturbance-induced changes in vegetation dynamics following disturbances. Post-disturbance recovery is a key process driving accelerated vegetation change under climate change, further stressing the importance of accurately representing disturbance impact and recovery processes in land surface and coupled modeling.

How to cite: Layritz, L. S., Gregor, K., Krause, A., Kruse, S., Meyer, B., Pugh, T. A. M., Boettiger, C., and Rammig, A.: Post-Disturbance Recovery Shifts in Boreal Evergreen Landscapes: Impacts on Carbon Dynamics and Land Surface Properties., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10400, https://doi.org/10.5194/egusphere-egu24-10400, 2024.

17:00–17:10
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EGU24-9771
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BG3.6
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On-site presentation
Lars Nieradzik, Hanna Lee, Paul Miller, Jörg Schwinger, and David Wårlind

Within the framework of the project IMPOSE (Emit now, mitigate later? IMPlications of temperature OverShoots for the Earth system) six idealized emission-overshoot simulations have been performed with the Earth System Model NorESM2-LM2 and used as forcing for the 2nd generation dynamic global vegetation model LPJ-GUESS to investigate the impact of different CO2 overshoots on global vegetation.

The simulations describe a set of scenarios with high, medium, and low cumulative CO2 emissions, each of which has a short (immediate) and a long (100 years) peak of cumulative CO2 emissions before declining towards a baseline simulation where a cumulative 1500 PgC is emitted within the first 100 years. The simulations have been performed in a “World without humans”, i.e. without land-use change, urban areas, fire-suppression, etc. to eliminate the somewhat arbitrary human factor.

The results clearly show that the height of the overshoot has a large impact on global vegetation distribution and composition while its duration does not seem to play a significant role. Overall, we can state that any overshoot scenario results in vegetation patterns that are different from (though converging towards) the non-overshoot baseline simulation. The higher the overshoot, the larger the initial deviation.

We have observed that there is less savannah after an overshoot and less so, the higher the overshoot, due to a reduced amount of tropical rain-green trees. As a result, there is also significantly less potential for fire. Further, there is more boreal vegetation, partly at the expense of temperate summer-green trees. A convergence towards the baseline simulation seems to be possible but isn’t reached by the end of the simulation window.

Furthermore, it can be observed that overshoots are asymmetrical when it comes to succession, i.e. while there are well-known succession patterns when global temperatures rise and vegetation is expanding into previously colder regions, patterns are different when the temperatures on the decline.

Finally, we like to state that dynamic vegetation is an important feature in Earth-system models w.r.t. vegetation carbon sequestration. Not only do the biogeophysical feedbacks matter, the total amount of carbon sequestered is about 16% higher than in simulations in which dynamic vegetation was supressed. These, and other feedbacks will be investigated in more detail in the ongoing Horizon Europe projects OptimESM and RESCUE.

How to cite: Nieradzik, L., Lee, H., Miller, P., Schwinger, J., and Wårlind, D.: Changes in global vegetation distribution and composition under idealized overshoot scenarios, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-9771, https://doi.org/10.5194/egusphere-egu24-9771, 2024.

17:10–17:20
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EGU24-13194
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BG3.6
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On-site presentation
Hui Yang, Maurizio Santoro, Ingrid Luijkx, Philippe Ciais, Siyuan Wang, Markus Reichstein, Simon Besnard, and Nuno Carvalhais

The land carbon cycle is fundamental in regulating atmospheric CO2 dynamics from seasonal to centennial scales. The fine equilibrium between photosynthetic gains spent in metabolic costs and/or lost in mortality underpins the contribution of terrestrial ecosystems to the global carbon cycle. Uncertainties and divergent hypotheses on the role of climate in regulating their underlying mechanisms hamper our current diagnostic and prognostic abilities despite growing evidence on ecosystem vulnerability to present and future changes in climate. However, quantitative knowledge of the contributions of different carbon cycle processes regulating carbon uptake and release still need to be improved, inflating the uncertainties in future projections of net land-atmosphere carbon exchanges. In this study, we rely on satellite-based Earth observation retrievals of above-ground biomass and vegetation primary productivity to reconstruct the land-atmosphere carbon exchange dynamics over the last two decades, through the application of a three-box model at the pixel level. Our approach confidently reproduces 60% of the observed variability in atmospheric CO2 growth rate (CGR) over throughout 1997-2019 (R = 0.78, p-val < 0.05), with a low RMSE of 1.0 PgC yr-1. We further detail CO2 release from vegetation dynamics emerging from quick turnover induced by wildfires and leaves senescence, as well as the slow turnover from plant and soil decomposition mechanisms. This allows us to differentiate between transient and lagged effects on land-to-atmosphere fluxes. The carbon release, characterized by a lag of over one year, referred to as lagged effects. Globally, the lagged responses accounted for 50% of the variability in CGR, exceeding three times the contribution of transient fluxes from live vegetation. We have yet to a change or trend in the total contributions of vegetation dynamics to CGR. Yet, the relative role of lagged effects to CGR via decomposition fluxes increased by 50%, possibly due to accelerated mortality and decomposition fluxes. As global warming imposes higher stress on vegetation while increasing temperature-mediated decomposition, our results highlight the importance of quantifying their underlying metabolic responses. Such understanding is instrumental for assessing the contribution of adaptation and mitigation measures that will shape the contribution of the terrestrial carbon cycle to dampen the effects of anthropogenic emissions on global climate.

How to cite: Yang, H., Santoro, M., Luijkx, I., Ciais, P., Wang, S., Reichstein, M., Besnard, S., and Carvalhais, N.: Transient and lagged effects of vegetation dynamics on the global CO2 growth rate, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-13194, https://doi.org/10.5194/egusphere-egu24-13194, 2024.

17:20–17:30
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EGU24-6618
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On-site presentation
Wenjia Cai, Iain Colin Prentice, and Joram Hooghiem

Land-atmosphere carbon exchanges and feedbacks constitute one of the largest uncertainties in future climate projections. Seasonal variations in atmospheric CO2 content depend on uptake by photosynthesis and release by autotrophic and heterotrophic respiration, providing an atmospheric signal of land ecosystem activity. Large increases in the seasonal cycle amplitude (SCA) of CO2 have occurred since the 1950s, especially in northern high latitudes. However, land surface and dynamic vegetation models have produced a wide range of magnitudes for the SCA, and have generally underestimated its increase. We explored the controls of the SCA by using a parameter-sparse eco-evolutionary optimality (EEO) model, the ‘P model’, combined with generic representations of plant and decomposer respiration, to simulate seasonal cycles and decadal trends of net ecosystem exchange (NEE). Simulated NEE fields were used to model near-surface CO2 concentrations during the satellite era, with the help of the atmospheric chemistry-transport model TM5. The P model has previously been shown to reproduce trends of gross primary production (GPP) at flux sites with long records. Our model set-up also generated a realistic simulation of global net terrestrial carbon uptake, comparable with results produced by more complex dynamic vegetation models; and allowed us to attribute causes to observed SCA increases at high-latitude CO2 monitoring stations.

How to cite: Cai, W., Prentice, I. C., and Hooghiem, J.: Simulating CO2 seasonal cycle amplitude in northern high latitudes with an eco-evolutionary optimality model, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-6618, https://doi.org/10.5194/egusphere-egu24-6618, 2024.

17:30–17:40
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EGU24-5483
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On-site presentation
Cosmin Cosofret, Olivier Bouriaud, and Laura Bouriaud

Reducing the net CO2 emissions is a key target worldwide, as shown, for instance, by the commitment of the Paris Agreement, and in this context, forests are being scrutinized for their capacity to act as carbon sinks and store large amounts of carbon over long periods. Quantifying the substitution effect of wood remains very difficult as it depends on many factors difficult to measure, such as the distribution of wood products into types of products having different lifetimes and which can substitute for different materials.

In Romania, forests have a large overall biomass stock, even in managed forests, since the management is operating at an intensity much lower than in many other European countries. Increased regionality in the global change effects requires a more local investigation. Therefore, we used a dynamic forest landscape model (LandClim model) to compare the three opposed mitigation strategies of forests and quantify their potential for sequestration of carbon and substitution of carbon in the context of global changes.

Under the mild climate RCP26 the carbon stocks were kept at levels roughly similar to the current stocks. The Set Aside 100% (SA100) managed stands stored the highest quantity of carbon, showing a capping of growth at the end of the 200 simulated years. Under the extreme climate RCP85, stocks increased for three decades but then plummeted. The highest stocks were obtained by the Set Aside 0% (SA0) management.

The cumulative harvest showed two surges under the climate scenario RCP26, first at the beginning of the simulation (2020-2060) and then during the 2170-2210 period. Under mild climate change RCP26, the effect of substitution from wood procurement clearly exceeds the increase in storage that can be expected. Under the RCP85 climate, harvest occurred exclusively during 2020-2070, then practically stopped when all stocks and fluxes became a lot more similar among management scenarios, given the catastrophic drop of stocks past 2080.

Wind-related disturbances had relatively constant consequences under RCP26, albeit with more fluctuations and a much higher intensity in SA100. SA0 and SA30 had similar magnitudes until 2120, and then wind-induced losses increased more strongly for Set Aside 30% (SA30). By 2210 the amounts of wind-induced carbon losses were 50% larger for SA100 than for SA30. Under scenario RCP85, the management strategy did not influence these losses which were near zero after 2080, as a result of the very small stocks.

The literature suggests no management strategies for carbon storage in mild climates, but in extreme climates cannot be a solution. Therefore, under the cloud of increased disturbance and pressure of climate change, the substitution strategy is more effective and safer than sequestration.

 

How to cite: Cosofret, C., Bouriaud, O., and Bouriaud, L.: Comparing the efficiency of forest mitigation policies: Is sequestering more efficient than using wood?, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-5483, https://doi.org/10.5194/egusphere-egu24-5483, 2024.

17:40–17:50
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EGU24-14716
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ECS
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On-site presentation
Lina Teckentrup, Martin De Kauwe, Andy Pitman, Anna Ukkola, David Wårlind, and Benjamin Smith

Semi-arid ecosystems, common across the Australian continent, strongly influence the inter-annual variability and trend in the global terrestrial net carbon sink. Here we explore the future Australian terrestrial carbon cycle using the CMIP6 ensemble, and the dynamic global vegetation model LPJ-GUESS. Uncertainty in Australia’s carbon storage in vegetation ranged between 6 and 49 PgC at the end of the century and was strongly linked to biases in the meteorological forcing. Using LPJ-GUESS with bias-corrected meteorological forcing reduced uncertainty in the vegetation carbon storage to between 14 and 20 PgC, with the remaining range linked to model sensitivities to rising atmospheric CO2 concentration, temperature, and precipitation variability. Reducing this uncertainty will require improved terrestrial biosphere models, but also major improvements in the simulation of regional precipitation by Global Climate Models.

How to cite: Teckentrup, L., De Kauwe, M., Pitman, A., Ukkola, A., Wårlind, D., and Smith, B.: Resolving uncertainty in the response of Australia's terrestrial carbon cycle to projected climate change, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14716, https://doi.org/10.5194/egusphere-egu24-14716, 2024.

17:50–18:00
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EGU24-3888
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ECS
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On-site presentation
Simon Besnard, Viola H.A Heinrich, Nuno Carvalhais, Martin Herold, Wouter Peters, Ingrid Luijkx, Maurizio Santoro, and Hui Yang

Understanding the relationship between forest age, an indicator of successional stages, and net carbon fluxes is crucial for effective forest management and climate mitigation. Using the satellite-based Global Age Mapping Integration (GAMI) v1.0 dataset, we analyzed forest age shifts from 2010 to 2020 and their correlation with net carbon dioxide (CO2) flux changes from independent atmospheric inversions. Globally, we do not report substantial forest age shifts during this period. The total area of young (1-20 years old), intermediate (21-60 years old), mature (61-150 years old), and old-growth (>150 years old) forests in 2020 compared to 2010 changed by approximately -0.07 (-7.7% compared to 2010), +0.03 (+6.0%), +0.03 (+2.1%), +0.01 (+1.1%) billion hectares, respectively. Despite these relatively stable global trends in forest age classes, we observe substantial changes at the regional scales. The Amazon, Congo basin, and Southeast Asia regionally experienced significant forest age decreases with local changes of up to 30% compared to 2010, attributed to deforestation and degradation. Siberian forests maintained their older age structure; however, large areas are transitioning to younger ages (0.09 billion hectares, 7.2% of Eurasia Boreal region), likely driven by increased fire frequency, logging activities, or climate-induced changes. Most European and North American forests trended toward older ages. However, those changes were heterogeneous at the sub-pixel level, revealing a complex mix of stand-replacement and aging dynamics across the different forest age spectrums. Stand-replaced forests, followed by regrowth, constitute a relatively minor fraction (6%) of the overall forested ecosystems, primarily dominated by aging forests (64%) and "stable" old-growth tropical forests (30%). Stand-replaced forests were prominent in young forests (0.1 billion hectares, 54.3% of total stand-replaced forests), while intermediate, mature, and old-growth forests accounted for 13.2%, 17.9%, and 14.6% of the total area of stand-replaced forests. Conversely, aging forests (excluding old-growth "stable" tropical forests) were primarily observed in the mature age classes, encompassing 1.2 billion hectares and constituting around 53% of the total aging forests. When coupling GAMI data with CO2 flux estimates, we observe a significant correlation between the spatial patterns of the stand-replaced forest fraction and net CO2 flux changes (R2 = 0.37, slope = 118.7 gC m-2 year-1 [a positive slope indicates increased carbon released], p-val = 0.05) across the eleven TRANSCOM-land regions. This correlation surpasses the correlation with aging forests (R2 = 0.02, slope = -3.7 gC m-2 year-1, p-val = 0.69). We attribute this significant correlation to the net above-ground biomass (AGB) losses in stand-replaced forests per unit area, substantially exceeding the magnitude of the net AGB gains observed in aging and old-growth "stable" tropical forests throughout 2010-2020. Our study highlights the importance of rapid forest turnover through stand-replacement, despite its limited spatial extent, on regional net carbon balance, especially when contrasted with the more gradual process of forest maturation.

How to cite: Besnard, S., Heinrich, V. H. A., Carvalhais, N., Herold, M., Peters, W., Luijkx, I., Santoro, M., and Yang, H.: The covariation of forest age shifts and net carbon balance over the period 2010 to 2020, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-3888, https://doi.org/10.5194/egusphere-egu24-3888, 2024.

Posters on site: Mon, 15 Apr, 10:45–12:30 | Hall X1

The posters scheduled for on-site presentation are only visible in the poster hall in Vienna. If authors uploaded their presentation files, these files are linked from the abstracts below, but only on the day of the poster session.
Display time: Mon, 15 Apr 08:30–Mon, 15 Apr 12:30
Chairpersons: Martin Thurner, Matthias Forkel, Thomas Pugh
X1.12
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EGU24-8510
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BG3.6
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Iris Dion, Jerome Chave, Stuart Davies, Alvaro Duque, Oliver Phillips, Camille Piponiot-laroche, Beatriz Schwantes Marimon, Klaus Scipal, and Irie Casimir Zo Bi

Verifiable and consistent measurement of forest carbon stocks and fluxes are necessary and they require to know where the biomass carbon is whether the vital functions of forests are changing, and what their future holds. Space agencies have made enormous investments in Earth Observation missions to map forest biomass across continents to support climate science and carbon markets. But satellites alone cannot produce accurate carbon maps–all maps vitally rely on field data collected by people and instruments to train their models and validate their products. To ensure satellites are producing reliable maps, it is needed frequently-acquired, high-quality field data. Furthermore, the challenge of acquiring ground biomass measurements is also one of environmental and social justice. The forests for which reference data are most needed, and the people depending on these forests, already suffer the worst impacts of climate change. Those in-country partners with unique forest expertise are key players in the fight against climate chaos, yet they are among the most disadvantaged globally. It follows that they need sustained support not only to collect data but to grow, train, and develop their own group's capacities. The GEO-TREES initiative proposes to fill this critical gap by building the world's first ground-based, standardized, open-access, equitably developed, reference forest biomass validation system to ensure that satellite observations accurately represent real forest carbon stocks, today and in the future. GEO-TREES is an ambitious world-wide network. It aims to establish at least 100 high-intensity forest biomass reference sites, to represent the main environmental and anthropogenic dimensions over which forests occur globally, and achieve greater sampling intensity in the critical tropics with an additional 210 lower-cost highly-distributed sites. Standing at the nexus of ecology and remote sensing, GEO-TREES builds on four principles: 1. Partnerships & engagement: To generate high-quality ground measurements, GEO-TREES partners with ecological and botanical specialists around the world. Partners are fully engaged and involved in every step of building the reference system. Without strong representation and fair funding of partners, particularly from the Global South, science capacity cannot be advanced, and the long-term sustainability of the GEO-TREES system would not be possible. 2. Innovative technologies: Ground measurement involves four integrated sets of measurements: forest inventory plots, airborne laser scanning, terrestrial laser scanning, and climate monitoring. GEO-TREES is based on established recommendations of the Committee on Earth Observation Satellites for validating biomass observations (https://lpvs.gsfc.nasa.gov/AGB/AGB_home.html), and will improve them based on new advances when necessary. 3. Long-term commitment: Forests are alive. Forest carbon stores change, sometimes rapidly, through space and time. Maintaining current, accurate estimates of carbon and biomass stocks requires continued long-term measurements. Long-term measurements also ensure the continued engagement and participation of partners throughout the system. 4. Open-access data: GEO-TREES is committed to equitably produced and openly shared global forest biomass reference measurements. High-quality, high-resolution maps of the world’s forests developed through the Earth Observation missions in partnership with GEO-TREES will be made open to all.

How to cite: Dion, I., Chave, J., Davies, S., Duque, A., Phillips, O., Piponiot-laroche, C., Schwantes Marimon, B., Scipal, K., and Zo Bi, I. C.:  The GEO-TREES initiative: high-accuracy ground data for satellite-derived biomass mapping, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-8510, https://doi.org/10.5194/egusphere-egu24-8510, 2024.

X1.13
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EGU24-2469
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BG3.6
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Ripan Das, Rajiv Kumar Chaturvedi, Adrija Roy, Subhankar Karmakar, and Subimal Ghosh

India has made the second-largest contribution to global greening in the last two decades. However, it is not clear whether this greening has led to an overall increase in net primary productivity and hence carbon uptake potential, given the impact of climate change on vegetation. In this study, using MODIS satellite data for the period 2001–2019, we attempt to find out the extent to which increased greening in India has led to an overall increase in primary productivity in recent decades. Despite a statistically significant increase in the Leaf Area Index (LAI), we found a slightly decreasing trend (not statistically significant) in Net Primary Productivity (NPP) and stable Gross Primary Productivity (GPP) during the 21st century. Our analysis also shows that the NPP of temporally consistent Indian forests shows a significant decreasing trend despite the increase in LAI. Notably, there are spatial differences in the NPP trend, with the regions contributing the most to NPP in India showing a stronger decreasing trend. The regions with a significantly decreasing NPP trend also experienced the strongest warming during the study period. We also used the nonlinear kernel regression method to investigate the temperature response of vegetation productivity in these regions. We observed that photosynthesis in these regions decreased above a certain temperature and respiration became stable, leading to a decrease in NPP. Our analysis shows that climate change, especially the rise in temperature, has already begun to affect vegetation productivity and carbon uptake in Indian forests. The study also conveys the clear scientific message that increased greening does not necessarily lead to increased carbon uptake, especially in a country like India where agriculture is intensifying. This analysis also has significant implications for the scientific analysis of planning to achieve India's net zero emissions pledge by 2070.

How to cite: Das, R., Chaturvedi, R. K., Roy, A., Karmakar, S., and Ghosh, S.: Greening fails to translate into an increase in Net Primary Productivity due to warming constraints in India, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-2469, https://doi.org/10.5194/egusphere-egu24-2469, 2024.

X1.14
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EGU24-4893
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BG3.6
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Vijaykumar Bejagam, Ashutosh Sharma, and Xiaohua Wei

The increase in vegetation productivity in India (net primary productivity; NPP) has been observed in recent decades; however, substantial uncertainty exists about the continued strength of these land carbon sinks under climate change. The enhanced NPP is driven by the strong positive carbon-concentration feedback (CO2 fertilization effect; CFE), but the temporal dynamics of this feedback are unclear. Using the carbon fluxes from the multiple Earth System Models (ESMs) of Coupled Model Inter-comparison Project (CMIP6), we showed an increasing trend in NPP would continue under climate change with projections of NPP to 2.00 ± 0.12 PgCyr-1 (25% increase) during 2021-2049, 2.36 ± 0.12 PgCyr-1 (18% increase) during 2050-2079, and 2.67 ± 0.07 PgCyr-1 (13% increase) during 2080-2099 in Indian tropic forests under SSP585 scenario. This suggests a significant decline in the growth rate of NPP in future periods. To understand the feedbacks that drive the NPP increase, we analyzed the relative effects of CFE and warming. We compared the simulations from the biogeochemical coupled model (BGC) from ESMs, which exclude the warming effects, with the fully coupled model, which includes both CFE and warming effects. The BGC model projected a 74.7% increase in NPP by the end of the century, significantly higher than the 55.9% increase projected by the fully coupled model. This shows that the consistent increase in the NPP was associated with the rise in atmospheric CO2. More importantly, results reveal that the decrease in the growth rate of NPP was due to the decline in the contribution of CFE across the different vegetations at a rate of -0.62% 100 ppm-1. Such a decline could be attributed to nutrient limitation, negative responses to high temperatures, droughts, heat waves, etc. Additionally, statistically significant shifts in the strength of carbon sinks (at a rate of -1.15% per decade) were identified in abating anthropogenic CO2 emissions. These shifts in land carbon sinks can potentially exacerbate global warming and impose additional challenges on our collective efforts to meet climate policy targets.

How to cite: Bejagam, V., Sharma, A., and Wei, X.: Projected decline of CO2 fertilization effects on vegetation carbon sequestration in India, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-4893, https://doi.org/10.5194/egusphere-egu24-4893, 2024.

X1.15
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EGU24-7220
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BG3.6
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ECS
Impacts of BBOA on the carbon sink of transitional forests in the Cerrado-Amazonian Forest ecotone: results from observational measurements and numerical estimates
(withdrawn)
Glauber Cirino, Simone Rodrigues, Demerval Moreira, Rafael Palácios, Sung-Ching Lee, Breno Imbiriba, Maria Isabel Vitorino, Andrea Pozzer, and José Nogueira
X1.16
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EGU24-3354
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ECS
Steven De Hertog, Félicien Meunier, and Hans Verbeeck

The Congo basin forests play a crucial role in the global carbon cycle, hosting a carbon sink of more than 10% of the global sink. This carbon potential also appears more stable than those of comparable other tropical forests. However, despite its importance for global climate, the Congo basin forest is receiving much less scientific attention. Yet, in recent years the body of data and knowledge is reaching a critical level which allows a study on the stability of the Congo basin forest under present and future climates. Here we applied an advanced vegetation model (ED2) over the Congo basin forests and explored their potential (in)stability under different climate forcings. The main objective was to explore the climate sensitivity of the Congo basin forests in terms of functional composition and carbon balance. This allows to asses the risk of the rain forest to shift into a savanna type vegetation. We addressed this question by integrating for the first time observational meteorological data available over the Congo basin in order to evaluate global reanalysis and climate modelling datasets. This led to unique simulations of the vegetation changes observed during past decades as well as for potential climate futures.

How to cite: De Hertog, S., Meunier, F., and Verbeeck, H.: Assessing the climatological stability of the Congo basin rainforest, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-3354, https://doi.org/10.5194/egusphere-egu24-3354, 2024.

X1.17
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EGU24-1159
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BG3.6
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K Narender Reddy and Somnath Baidya Roy

Carbon exchange from agroecosystems contributes to the fluctuations of the carbon cycle. The present research employs the Community Land Model version 5 (CLM5) to examine the effects of climate and agricultural management methods, such as fertilization and irrigation, on carbon fluxes in the primary agroecosystems of India. In this study, CLM5 is calibrated and validated against the crop phenology dataset of spring wheat and rice. The crop phenology data is an unprecedented dataset that we have compiled by gathering information from many agricultural institutes around India. The crop dataset covers the period from 1970 to 2020. We have comprehensively tested and validated the CLM5 crop module in the Indian region. Subsequently, regional-scale simulations were conducted. The findings indicated that there are large variations in fluxes among different climatic regions of India, primarily due to disparities in growing circumstances. Throughout the study period, all fluxes exhibited statistically significant upward trends (p<0.1). Further numerical experiments are performed to examine the potential impact of natural factors, such as variations in temperature and levels of carbon dioxide (CO2), as well as agricultural techniques like nitrogen fertilizer and water availability, on the previously observed upward trends. The tests demonstrated that elevated levels of carbon dioxide (CO2), nitrogen fertilization, and irrigation water resulted in heightened carbon fluxes, with nitrogen fertilization exerting the most pronounced impact.

How to cite: Reddy, K. N. and Baidya Roy, S.: Impact of climate and agricultural management practices on carbon fluxes using a CLM5 land surface model, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-1159, https://doi.org/10.5194/egusphere-egu24-1159, 2024.

X1.18
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EGU24-10956
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Xueying Li, Wenxin Zhang, Minchao Wu, Hao Zhou, Stefan Olin, EI Houssaine Bouras, Shangharsha Thapa, and Zheng Duan

Matching the rising demand for food from a rapidly increasing population is a crucial challenge for the 21st century. Crop yield can be strongly impacted by weather conditions, especially extreme events (e.g., floods and droughts). Therefore, understanding the spatial and temporal vaiations of crop yield enables us to develop effective adaptation strategies for enhancing the resilience of agriculture sectors under climate change.

Dynamic global vegetation models (DGVMs) represent growth and development of vegetation based on the understanding of underlying physical and physiological processes, which are efficient tools to assess impacts of climate change and human management on vegetation response to these variations. During the past two decades, satellite observations have emerged as essential gridded datasets to calibrate various vegetation-related variables at large spatial scales, and are often used to benchmark DGVMs. Commonly used satellite-derived variables for model calibration include the fraction of absorbed photosynthetically active radiation, phenological dates, soil properties, leaf area index (LAI), and evapotranspiration (ET).

One of the process-based DGVMs LPJ-GUESS (Lund-Potsdam-Jena General Ecosystem Simulator) has shown its acceptable performance in simulating crop yield at global and regional scales. However, to the best of our knowledge, no studies have comprehensively investigated the added value of using multi-source data, particularly satellite-derived estimates for calibrating LPJ-GUESS at multiple spatial scales. Therefore, we aim to bridge this gap by calibrating LPJ-GUESS at both site and district level to improve model performance of simulating the winter wheat yield in southern Sweden.

First, all the parameters sensitive to LAI, ET and crop yield in LPJ-GUESS, along with their ranges, are derived from the literature and sensitivity analysis. Second, the LAI-related parameters are calibrated against the in-situ observed LAI at the experimental site in Alnarp during 2022–2023. The simulated yield based on the optimized parameters (achieved from calibration results) is further validated by the observed winter wheat yield at the same site. At the district level, the parameters for ET and crop yield are subsequently calibrated against the satellite-derived ET and crop yield estimates, and the observed district-level winter wheat yield (from Jordbruksverket), respectively during 2003–2012. Finally, the observed district-level yield during 2013–2022 are used for the model validation to access the performance of the calibrated LPJ-GUESS. We expect this proposed calibration framework can be applied to other DGVMs and geographic extents focusing on high details of local landscape.

How to cite: Li, X., Zhang, W., Wu, M., Zhou, H., Olin, S., Bouras, E. H., Thapa, S., and Duan, Z.: Crop model calibration at multiple spatial levels in southern Sweden using leaf area index, evapotranspiration and winter wheat yield data, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10956, https://doi.org/10.5194/egusphere-egu24-10956, 2024.

X1.19
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EGU24-341
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BG3.6
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ECS
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Md Rafikul Islam, Anna Maria Jönsson, John Bergkvist, Fredrik Lagergren, Mats Lindeskog, Meelis Mölder, Marko Scholze, and Natascha Kljun

Boreal forests play a crucial role in global carbon sequestration and storage, yet their vulnerability to climate change remains a significant concern. We present results from simulations with the process-based dynamic global vegetation model LPJ-GUESS of the combined effects of climate change and forest management on the carbon sink capacity of a boreal forest in southern Sweden. We compared two future climate change scenarios (RCP 4.5 and RCP 8.5) along with four forest management options against a baseline scenario without management interventions. Our findings indicate that projected temperature increases (+2 to +4°C) in the late 21st century will diminish the net carbon sink strength, particularly in old-growth forests. Clear-cut and subsequent reforestation resulted in a substantial decline (57-67%) in vegetation carbon during 2022-2100. The carbon compensation point (CCP) was reached 12-16 years after the clear-cut, indicating a period of carbon debt before the ecosystems resumed acting as a net carbon sink. Specific reforestation strategies, such as pine plantations, enhanced the overall net carbon sink by 7-20% relative to the baseline during 2022-2100. The carbon parity point, without considering harvested carbon, was reached 56-73 years after the clear-cut, highlighting the extended period required for the reforestation to achieve a carbon stock equivalent to the uncut baseline. These findings highlight the substantial influence of forest management on the net carbon budget, surpassing that of climate change alone. The adoption of relevant reforestation strategies could enhance carbon uptake, simultaneously improving forest productivity and ensuring the forest's vital role in carbon sequestration and storage amid a changing climate.

How to cite: Islam, M. R., Jönsson, A. M., Bergkvist, J., Lagergren, F., Lindeskog, M., Mölder, M., Scholze, M., and Kljun, N.: Integrated Assessment of Climate Change and Forest Management Impacts on Carbon Fluxes and Biomass in a Southern Boreal Forest , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-341, https://doi.org/10.5194/egusphere-egu24-341, 2024.

X1.20
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EGU24-13116
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BG3.6
Emilie Joetzjer, Sebastien Lafont, Matthias Cuntz, Benjamin Loubet, Pedro Herig Coimbra, Nicolas Delpierre, Jean Marc Limousin, Jean Christophe Domec, and Guillaume Simioni

In 2022, Europe experienced a widespread severe summer edaphic drought and heat event. We explore how the gross primary productivity (GPP) was affected by this dry spell by contrasting 2022 with previous years, using high-frequency Eddy-Covariance and meteorological monitoring from 16 ICOS forest stations spanning across Europe. With the exception of Scandinavian forests, all monitored stations experienced a reduction of GPP ranging from 5 to 60% and a reduction of evapotranspiration ranging from 10 to 62% during summer. GPP reduction was predominantly attributed to a decrease in the maximum apparent carboxylation rate rather than a direct effect of soil water content limitation on stomatal aperture at the canopy scale. Some sites showed more GPP than usual after the drought due to abnormally hot and wet autumn conditions. However, most severely affected sites did not fully recover to normal GPP levels after the drought, suggesting a potential lagged effect of the adverse summer conditions.

How to cite: Joetzjer, E., Lafont, S., Cuntz, M., Loubet, B., Herig Coimbra, P., Delpierre, N., Limousin, J. M., Domec, J. C., and Simioni, G.: Carbon assimilation limitations during and after the European 2022 drought and heat wave, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-13116, https://doi.org/10.5194/egusphere-egu24-13116, 2024.

X1.21
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EGU24-604
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BG3.6
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ECS
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Yunkun Song and Xiaodong Yan

Forest ecosystems represent significant carbon sinks within terrestrial ecosystems. Simulating carbon budgets in forest ecosystems located within complex terrains forms the foundation for understanding global carbon cycle dynamics. In this study, employing the FORCCHN model and utilizing mountain climate data as forcing parameters, the impact of the terrain factors of the Changbai Mountain Nature Reserve on carbon budget change in 1998–2017 was studied. The dynamics and distribution patterns of carbon fluxes at different slope aspects and elevations were discussed. Findings demonstrated that between 1998 and 2017, the per unit area gross primary production (GPP), net primary production (NPP), and net ecosystem production (NEP) for the Changbai Mountain Reserve were 839.35 gC·m-2·yr-1, 462.03 gC·m-2·yr-1, and 192.72 gC·m-2·yr-1, respectively. The carbon fluxes varied significantly with elevation: the GPP of the north, south, and west and the NPP of the east, south, and west decreased, and the NEP of the south and west increased. The total amount in GPP and NPP of the Changbai Mountain Nature Reserve fluctuated slightly year by year, but the carbon sequestration capacity decreased from year to year. The reserve had an average annual total GPP, NPP, and NEP of 1.62 TgC·yr-1, 0.89 TgC·yr-1, and 0.37 TgC·yr-1, respectively. The north was the strongest carbon sink in the study area, contributing 35.98%, 35.88%, and 36.80% to the total amount of GPP, NPP, and NEP, respectively. This study emphasized the significance of precise mountain meteorological data to accurately quantify the carbon fluxes of mountain forest ecosystems.

How to cite: Song, Y. and Yan, X.: Carbon Budget of Complex Terrain Forest, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-604, https://doi.org/10.5194/egusphere-egu24-604, 2024.

X1.22
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EGU24-11507
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BG3.6
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ECS
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Highlight
Lidong Mo, Constantin Zohner, Thomas Crowther, and Haozhi Ma

Forests are a substantial terrestrial carbon sink, but anthropogenic changes in land use and climate have considerably reduced the scale of this system. Remote-sensing estimates to quantify carbon losses from global forests are characterized by considerable uncertainty and we lack a comprehensive ground-sourced evaluation to benchmark these estimates. Here we combine several ground-sourced and satellite-derived approaches to evaluate the scale of the global forest carbon potential outside agricultural and urban lands. Despite regional variation, the predictions demonstrated remarkable consistency at a global scale, with only a 12% difference between the ground-sourced and satellite-derived estimates. At present, global forest carbon storage is markedly under the natural potential, with a total deficit of 226 Gt (model range = 151–363 Gt) in areas with low human footprint. Most (61%, 139 Gt C) of this potential is in areas with existing forests, in which ecosystem protection can allow forests to recover to maturity. The remaining 39% (87 Gt C) of potential lies in regions in which forests have been removed or fragmented. Although forests cannot be a substitute for emissions reductions, our results support the idea that the conservation, restoration and sustainable management of diverse forests offer valuable contributions to meeting global climate and biodiversity targets.

How to cite: Mo, L., Zohner, C., Crowther, T., and Ma, H.: Integrated global assessment of the natural forest carbon potential, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-11507, https://doi.org/10.5194/egusphere-egu24-11507, 2024.

X1.23
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EGU24-7624
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BG3.6
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ECS
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Zimin Tan and Shuai Wang

China’s drylands cover a large area and provide important ecosystem services as carbon sink by storing large amounts through vegetation and soils, so that it can be the key component of China’s terrestrial ecosystems. Due to water limitation and severe carbon-water trade-offs, China’s drylands are highly dynamic, which has an important impact on the trend of carbon sequestration in ecosystems of China and the interannual variability. Many studies have focused on carbon storage in cropland, grassland and forest ecosystems, but few comprehensive analyses focused on carbon storage and potentials in China's drylands. Here, we train a model with multiple influence factors to simulate the carbon storage potential in drylands of China to predict the biomass carbon carrying capacity of China’s drylands. After comparing observed and predicted biomass carbon density of drylands of China, we find that the carbon storage in China’s drylands realised by nearly 70 percent. The carbon actual storage in the drylands of the east of Inner Mongolia, the Northeast China, the northern part of Xinjiang, and the Huang-huai-hai region are the highest, and the potential carbon benefits of these places are highest too. Following by the Qinghai-Tibet Plateau and Jin-Shaan-Gan areas, and the lowest carbon storage and potential carbon benefits were found in the central and western parts of Inner Mongolia. Divided by the aridity gradient, it was found that the semi-arid zone has highest potential for carbon storage. We also identified areas where vegetation has not yet reached its full potential, such as the eastern and southern parts of the Tibetan Plateau and the Xinjiang region. Although the potential carbon storage in these areas is low, the proportion of carbon storage realised is below 40 percent, which has higher potential and conservation priority, indicating that the conservation of carbon in drylands of China needs to pay attention to the proportion of carbon sequestration realised at the same time, in addition to the potential carbon benefits.

How to cite: Tan, Z. and Wang, S.: The potential carbon benefit in drylands of China, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-7624, https://doi.org/10.5194/egusphere-egu24-7624, 2024.

X1.24
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EGU24-21067
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BG3.6
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ECS
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Danbi Lee, Jin-Soo Kim, So-Won Park, and Jong-Seong Kug

The terrestrial ecosystem in East Asia mainly consists of semi-arid regions that are sensitive to climate change. Therefore, gross primary productivity (GPP) in East Asia could be highly variable and vulnerable to climate change, which can significantly affect the local carbon budget. Here, we examine the spatial and temporal characteristics of GPP variability in East Asia and its relationship with climate factors over the last three decades. We detect an abrupt decrease in GPP over Eastern China-Mongolia region around the year 2000. This is attributed to an abrupt decrease in precipitation associated with the phase shift of the Pacific decadal oscillation (PDO). We also evaluate the reproducibility of offline land surface models to simulate these abrupt changes. Of the twelve models, eight were able to simulate this abrupt response, while the others failed due to the combination of an exaggerated CO2 fertilization effect and an underrated climate impact. For accurate prediction, it is necessary to improve the sensitivity of the GPP to changes in CO2 concentrations and the climate system.

How to cite: Lee, D., Kim, J.-S., Park, S.-W., and Kug, J.-S.: An abrupt shift in gross primary productivity over Eastern China-Mongolia and its inter-model diversity in land surface models, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-21067, https://doi.org/10.5194/egusphere-egu24-21067, 2024.

X1.25
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EGU24-19832
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BG3.6
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ECS
Xiaoyi Wang and Guanting Lyu

Forests are the largest carbon reservoirs in terrestrial ecosystems, with climate and anthropogenic disturbance have considerably reshaped the size of this system. However, remote sensing estimates to quantify current and future carbon stock are characterized by large uncertainty. Here, we developed a new spatially explicit map of forest aboveground carbon storage at a 30 m spatial resolution across Northeast China, by integrating an image-to-image U-Net deep convolutional neural network algorithm with in situ measurements, Global Ecosystem Dynamics Investigation observations, Landsat, and PALSAR2 images. The result yields a high coefficient of determination (R2) of 0.83 and a relatively low relative root mean squared error of 24.02%, and is superior to traditional pixel-based and in situ-based methods. The forest aboveground biomass carbon stock was estimated as 2.74 ± 0.38 PgC, with precipitation and forest age being important determinants. By developing a climate and age-driven predictive model, local forest biomass C sink is estimated to be 7.42 and 2.51 TgC year-1 for 2060s and 2100s, a significant decline due to aging forests. The study highlights the importance of forest protection and management to optimize forest age structure and sustain natural forest carbon sinks.

How to cite: Wang, X. and Lyu, G.: Current and future projections of forest aboveground carbon storage over Northeast China using an advanced deep convolutional neural network , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-19832, https://doi.org/10.5194/egusphere-egu24-19832, 2024.

X1.26
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EGU24-3780
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BG3.6
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ECS
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Ran Yan, Jun Wang, Weimin Ju, Xunmei Wang, and Jingye Tan

Gross primary production (GPP) stands as a crucial component in the terrestrial carbon cycle, greatly affected by large-scale circulation adjustments. This study investigates the influence of El Niño-Southern Oscillation (ENSO) and Indian Ocean Dipole (IOD) on China’s GPP, utilizing long-term GPP data simulated by the Boreal Ecosystem Productivity Simulator (BEPS). Partial correlation coefficients between GPP and ENSO reveal substantial negative associations in most parts of western and northern China during September-October-November (SON). These correlations shift to strongly positive over southern China in December-January-February (DJF), then weaken in March-April-May (MAM), eventually turning generally negative over southwestern and northeastern China in June-July-August (JJA). In contrast, the relationship between GPP and IOD basically exhibits opposite patterns. Composite analysis further confirms these seasonal GPP anomalous patterns. Mechanistically, we ascertain that, in general, these variations are predominantly controlled by soil moisture in SON and JJA, but temperature in DJF and MAM. Quantitatively, China's annual GPP demonstrates modest positive anomalies in La Niña and nIOD years, in contrast to minor negative anomalies in El Niño and pIOD years. This results from counterbalancing effects with significantly greater GPP anomalous magnitudes in DJF and JJA. Additionally, the relative changes in total GPP anomalies at the provincial scale display an east-west pattern in annual variation, while the influence of IOD events on GPP presents an opposing north-south pattern. We believe that this study can significantly contribute to our comprehension of how intricate atmospheric dynamics influence China’s GPP on an interannual scale.

How to cite: Yan, R., Wang, J., Ju, W., Wang, X., and Tan, J.: Significant Impacts of El Niño-Southern Oscillation and Indian Ocean Dipole on China’s Gross Primary Production, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-3780, https://doi.org/10.5194/egusphere-egu24-3780, 2024.

X1.27
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EGU24-6377
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BG3.6
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ECS
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Yibiao Zou, Thomas Crowther, Gabriel Smith, Haozhi Ma, Lidong Mo, Zhaofei Wu, Dominic Rebindaine, and Constantin Zohner

Deforestation has exacerbated the fragmentation of habitats into smaller, more isolated patches, driving global declines in biodiversity. Yet, a comprehensive global perspective of the trends in forest fragmentation, and its key drivers in relation to forest cover change remains elusive. To provide a comprehensive global overview of recent changes in forest fragmentation, we compare multiple fragmentation metrics, including those that are sensitive to forest cover and those that are not. Our analysis reveals that, according to cover-sensitive metrics that reflect the ecological implications of forest fragmentation, 52% of the world's forests have become more fragmented over the last two decades, a trend that is primarily attributed to increased deforestation in tropical zones. This value is twice as high than estimates from previous research, which estimated that forest fragmentation is declining across 75% of the global forest area. This discrepancy arises from a mathematical artifact, as previous cover-insensitive metrics equate declines in forest cover with decreased fragmentation. By adjusting for this and focusing on metrics that capture the ecologically relevant aspects of forest fragmentation, our study highlights a worrying trend: the ecological integrity of the global forest system has been significantly deteriorating in recent decades. This underscores the importance of using appropriate metrics to accurately assess the ecological impacts of forest fragmentation, especially in the context of global environmental change.

How to cite: Zou, Y., Crowther, T., Smith, G., Ma, H., Mo, L., Wu, Z., Rebindaine, D., and Zohner, C.: Global trends in forest fragmentation using multiple metrics, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-6377, https://doi.org/10.5194/egusphere-egu24-6377, 2024.