Forest structure is shaped by forest management practices, land-use changes and forest disturbances including droughts, fires, storms and insect outbreak. It plays an important role in climate by modifying the carbon-water-energy exchanges with the atmosphere, and affects the capability of forests to undergo future disturbances in a changing climate. Given the importance of forest structure for the climate, land surface models are moving towards explicit representations of forest structure and management strategies. We present a new procedure to initialize forest diameters over Europe and document its implications for simulations of future forest carbon sinks. The simulated diameters for each grid cell covered by forests are initialized toward the diameter from a forest inventory. To this end, a 300-years semi-analytical spinup was carried out to bring the soil carbon and nitrogen pools into equilibrium until the European forests were clearcut. Then, a 150-years biosphere simulation over Europe was performed to build a look-up-table of simulated diameters. For each grid point, the year associated with the simulated diameter that is the closest to the observation is selected, enabling the production of new initial state files over Europe. The new initialization procedure makes the initial state of forest more realistic and therefore is expected to have significant influence on the evolution of the forest carbon sink. In this work, we will assess the effect of the initialization procedure on the simulated land carbon sink and we will evaluate the representation of the diameters in the ORCHDEE LSM. The method could be further extended to initialize other forest state variables such as height or aboveground biomass.

How to cite: Remaud, M., Jeong, J., Marie, G., Flores, O., Naudts, K., and Luyssaert, S.: On the assessment and initialization of European forest state variables in Land Surface Models, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-2268, https://doi.org/10.5194/egusphere-egu25-2268, 2025.

Knowledge of forest ecosystem pattern and process responses to climate change and anthropogenic pressure requires innovative tools that combine monitoring and modelling of tree growth dynamics to account for a more sustainable management of forest resources and ecosystem services. In this context, Digital Twins (DTs) emerge as powerful tool to allow a better interpretation of complex models, summarizing a large amount of data and knowledge into a comprehensive 3D visualization. A Digital Twin is an evolving and comprehensive representation of a physical object, in our case trees, which involves three key elements: a digital representation of the object, an evolving set of data and a dynamic adjustment of the object data. However, due to the structural complexity of the forest stand, and the lack of adequate growth historical data series useful to build and validate the simulations, the full potential of Digital Twin frameworks has yet to be realized in forest field. Our work aims to develop a system that simulate forest growth and spatial patterns through a process-based single tree model and represent the outputs into a 3D immersive and interactive environment, able to reproduce the stand structure of Mediterranean forests. An individual based spatially explicit model has been developed to simulate the biomass growth within a time step of one year and while an immersive 3D dynamic environment enables the user to interact with trees (e.g. tree marking, logging). Competition among trees has been modelled computing the tree influence on surroundings space using a distance-biomass dependent approach. We implemented a set of allometric equations to convert tree biomass into size attributes (e.g. stem diameter, total height) to appropriately represent the modelled forest stand in the 3D environment. The use of DTs can assist forest experts and policymakers in managing complex systems like Mediterranean forests, by simulating several management scenarios and analysing their long-term impacts on forest ecosystem dynamics. Furthermore, process-based models coupled with an immersive 3D representation could help to better understand the forest ecosystem functioning.

How to cite: Fornaro, R., Giannino, F., Heatfield, D. N., Minopoli, V., Aquino, A., Rita, A., Saracino, A., and Saulino, L.: Forest digital twin: coupling field data, mathematical modelling and 3D representation of a Mediterranean forests  , EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-6985, https://doi.org/10.5194/egusphere-egu25-6985, 2025.

Insect disturbances significantly impact multiple functions of forest ecosystems, yet their representation in terrestrial biosphere models remains limited. To address this gap, we developed an insect impacts module in the terrestrial biosphere model QUINCY (QUantifying Interactions between terrestrial Nutrient CYcles and the climate system model). The new module represents bark-beetle and defoliator impacts by introducing standing dead biomass pools and insect-mediated nutrient cycling pathways, and effectively capturing key processes such as snag decay, larvae pool dynamics, compensatory leaf growth, and carbon starvation due to over-defoliation. Model validation against multiple forest sites registering insect disturbances demonstrated good agreement with observed trends in forest dynamics, carbon fluxes, water and energy exchanges, and nutrient transformations during insect disturbances. Long-term simulations revealed that severe insect outbreaks can reduce ecosystem carbon storage by up to 6% for a horizon of 50 years, primarily due to accelerated nutrient leaching through litter decomposition. These results emphasize the critical role of insect disturbances in shaping vegetation carbon dynamics and highlight the importance of integrating these processes into global vegetation models. Our results further underscore the need for observational datasets, including field and satellite-based measurements, to constrain and improve model representations of insect disturbances. By advancing understanding of insect impacts and their interactions with climate, our study contributes to reducing uncertainties in projections of vegetation dynamics and the terrestrial carbon sink under future climate change.

How to cite: Ma, Y., Zaehle, S., Jornet-Puig, A., and Bastos, A.: Incorporating Insect Disturbances into Terrestrial Biosphere Model: Impacts and Challenges, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-12297, https://doi.org/10.5194/egusphere-egu25-12297, 2025.

Climate change poses a challenge for European forestry, requiring the selection of tree species adapted to future conditions. Analyzing this for a large country like Germany requires considering diverse regional environmental conditions in climate, soil, and management history. A promising approach is to utilize simulation models to derive potential natural vegetation (PNV) under climate change, which can help to identify robust candidate species for regions.

We employed the process-based forest landscape model iLand to investigate: (i) the impact of climate change on PNV species composition and carbon stocks  across regions in Germany, and (ii) regional adaptation deficits by comparing future PNV composition with current forest composition (derived from national inventory data). We defined 12 representative ecoregions via cluster analysis of climate, soil, and vegetation data. For each, we created generic landscapes (20-30k ha) reflecting regional environmental gradients. We used these landscapes to simulate PNV with iLand under historical and nine climate change scenarios. Changes in equilibrium species composition and attainable carbon stocks were calculated relative to historical climate simulations. Finally, we created high-resolution maps of future PNV in Germany by mapping the stands of our simulated landscapes to country scale. 

Our landscapes cover 95% of Germany’s forested climate and soil space (defined by the ratio of forest pixels, after removing outliers). Simulations identified regions particularly vulnerable to climate change, as well as those with the greatest mismatch between expected PNV and current forests. To account for regional differences in species suitability is crucial for developing climate change adaptation policies at the national level within Germany.

How to cite: Kerber, J., Seidl, R., and Rammer, W.: Mapping the Future of Germany’s Forests: Modelling Potential Natural Vegetation under Climate Change Scenarios, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-16504, https://doi.org/10.5194/egusphere-egu25-16504, 2025.

Forest ecosystems are vital for a multitude of ecosystem services including timber provision, climate change mitigation, local climate regulation, and provision of habitat for biodiversity. However, previous studies have primarily focused on individual ecosystem service indicators, with limited attention to the underlying biophysical mechanisms. Investigating multiple services under diverse strategies is critical for assessing their impacts on forest ecosystems. Therefore, in this study, we used the global dynamic vegetation model LPJ-GUESS to simulate the temperate forests in China under scenarios of natural succession and forest management strategies. The natural succession refers to forest regeneration without any human intervention. We analyzed multiple ecosystem services, including carbon sequestration, timber provision, water retention, and biodiversity. We found that (1) under management, forests exhibited short-term higher timber yields and economic benefits, but natural succession maintained higher long-term carbon sequestration; (2) density-based management strategies increased timber production and accelerated the forest regeneration in the short term. However, these activities temporarily increased evapotranspiration and reduced biodiversity due to habitat disturbance, which then affected ecosystem services, especially at the initial stages of harvesting; (3) integrated optimization strategies, focusing on tree species, density, and age structure, can optimize forest structure and enhance the multifunctional ecosystem services in the long term. Our study provides valuable insights into the diverse impacts of the management strategies on ecosystem service provision, offering guidance to policymakers and local stakeholders in balancing ecological conservation and economic priorities through sustainable forestry practices.

How to cite: Liu, L., Gregor, K., Gu, Q.-L., Liu, Y., Wang, A., and Rammig, A.: The Impact of Forest Management Strategies on Ecosystem Services in China, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-18432, https://doi.org/10.5194/egusphere-egu25-18432, 2025.

The intensity, frequency, and spatial distribution of forest disturbance regimes across Europe are shifting due to climate change. This raises concerns about the vulnerability of forest ecosystems and the impacts on the goods and services that they provide. Protection against natural hazards is a key service provided by forests in the Alps but current protective effects are threatened by the growing incidence of disturbance events such as windstorms, heavy snowfalls and drought. For planning effective management interventions, detailed information on the patterns of recent forest disturbances and quantifications of their impacts on protection forests are necessary. In our study we focused on a region in the Italian Alps (South Tyrol) with the aims of: i) providing a wall-to-wall disturbance map by agent type (wind, snow, beetles) and an analysis of the spatial patterns of disturbance agents and their interaction, and ii) quantifying the loss of protective effects in protection forests and areas with residual protection given by standing dead trees due to bark beetle.

We analyzed Sentinel-2 timeseries to map disturbances covering the period 2019-2023. We then applied a supervised machine learning classifier leveraging multisource predictors to attribute a disturbance agent to each disturbed patch. Afterwards, we explored the correlation between the areas disturbed by different agents and assessed the areas of protection forest which were affected by disturbances. For these areas, we performed a pixel-based classification to identify areas with residual protective effects given by standing dead trees (i.e., pixels with dead canopy but not downed or salvaged yet) due to recent bark beetle outbreaks.

Our results showed that, over a period of five years, disturbances affected 5.9% of the forests of the study area. Damages due to windthrow (1.6%) and snow (1.3%) had a comparable cumulated impact, while bark beetle caused much larger damages (3%). Snow-damaged areas correlated more strongly with bark beetle damage than wind disturbances. Notably, 5.6% of protection forests in the area were disturbed, with bark beetles causing disproportionately higher impacts compared to the other two agents. Overall, about 1.3% of protection forests still provide some level of protection because they are covered by standing dead trees. These are forests that will soon lose their protective function and should be given high priority in management planning. These findings provide the first detailed mapping of recent disturbances in the region and highlight critical areas where protection forests can no longer offer adequate hazard mitigation. By identifying forests most at risk of losing their protective function, we offer useful information for managers to plan near future interventions in these areas.

How to cite: Dorigatti, E., Mina, M., and Sonnenschein, R.: Mapping forest disturbances and their impacts on protection forests in South Tyrol (Italian Alps), EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-16695, https://doi.org/10.5194/egusphere-egu25-16695, 2025.

Wildfire risk is an escalating concern across EU territories, amplified by climate change and necessitating proactive management. Addressing this issue requires nature-based solutions, such as fuel management, forest conservation, and restoring fire-adapted ecosystems to their natural fire regimes. This study models forest growth across Europe under climate change and varying management strategies, presenting three scenarios aligned with potential policies. We focus on future wildfire dynamics and their impacts on forests, relying on high-resolution modeling of forest growth and burned areas.

We developed a new model for deadwood and litter dynamics and integrated it with models for forest growth and development and wildfire risks to simulate annual disturbances and post-disturbance management. The Wildfire Climate Impacts and Adaptation model (FLAM) identifies wildfire hotspots under historical, current, and future conditions and projects burned areas under various climate scenarios and management strategies. The Global Forest Model (G4M) simulates large-scale forest changes, accounting for growth, mortality, regeneration, and management activities like thinning, harvesting, and replanting.

Results from integrating and calibrating these models with observed fire events, harvest levels, biomass stocks, and other parameters will be presented. Three management scenarios reflecting key directions in forest management are proposed, linked to climate projections through 2070. This approach provides a robust framework for assessing the impacts of policies and legislation on wildfire dynamics across Europe, enhancing our ability to mitigate risks and adapt to changing conditions.
 

How to cite: Johnstone, C., Krasovskiy, A., Hyun-Woo, J., Eunbeen, P., Shchepashchenko, D., and Kraxner, F.: Modeling Wildfire Risks and Forest Dynamics in Europe: Strategies for Climate-Resilient Management, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-19761, https://doi.org/10.5194/egusphere-egu25-19761, 2025.

Historic climatic data suggests that severe windstorms have been observed every 10-15 years in Ireland (Gallagher, 1974) and sometimes even more frequently, having a devastating impact on forests in the country. Such severe storms cause a significant number of trees to be uprooted or snapped (McInerney et al. 2016), a phenomenon commonly known as windthrow. Windthrow has extensive consequences for forest management, impacting the operations of forest for timber (wood volume shift to salvage wood, possible quality downgrade due to premature extraction, etc.), the dynamics of forests for nature (light availability, regeneration options, higher deadwood volume, etc.), the safety of forests for public use, the soil dynamics (especially for uprooted trees due to exposed soil), among others. In the context of climate change, natural disturbances such as windthrow might shift forests from carbon sinks to temporary carbon sources (Albrich et al. 2023). In order to understand the impact of windthrow on carbon dynamics in temperate forests, this work uses National Forest Inventory data from county Laois (Ireland) as a study case. Centrally located, county Laois has a forest cover (16.5%) higher than the national average (11.6%), and features diverse conditions, including varied soil types, forest types, as well as management purposes. This study models the impact of windthrow events on carbon pools in county Laois’ temperate forests using the CBM-CFS3 framework (Kurz et al. 2009). Varying disturbance intensities (25%, 50%, 70% and 100% of trees damaged by windthrow) are simulated, and their effects on carbon fluxes across biomass, soil organic carbon, and harvested wood products are analyzed. Management strategies, including salvage logging and natural regeneration, are evaluated to assess both immediate impacts and recovery potential, as well as their role in enhancing carbon resilience.

References

Albrich, K., Seidl, R., Rammer, W., & Thom, D. (2022). From sink to source: changing climate and disturbance regimes could tip the 21st century carbon balance of an unmanaged mountain forest landscape. Forestry: An International Journal of Forest Research, 96(3), 399-409.

Gallagher, G. (1974). Windthrown in state forests in the Republic of Ireland. Irish Forestry, 31(2), 14.

Kurz, W. A., Dymond, C. C., White, T. M., Stinson, G., Shaw, C. H., Rampley, G. J., Smyth, C., Simpson, B. N., Neilson, E. T., Trofymow, J. A., Metsaranta, J., & Apps, M. J. (2009). CBM-CFS3: A model of carbon-dynamics in forestry and land-use change implementing IPCC standards. Ecological Modelling, 220(4), 480-504. 

McInerney, D., Barrett, F., Landy, J., & McDonagh, M. (2016). A rapid assessment using remote sensing of windblow damage in Irish forests following Storm Darwin. Irish Forestry, 73, 19.

How to cite: Longo, B. L., Tobin, B., and Byrne, K. A.: The impact of windthrow on carbon dynamics in temperate forests: a study case of Co. Laois in Ireland, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-13709, https://doi.org/10.5194/egusphere-egu25-13709, 2025.

According the the IPCC's 2023 Synthesis Report on Climate Change, global temperatures have risen approximately 1C since the the pre-industrial period, and there is significant uncertainty around future climate projections. Additionally, IPCC and related scientific literature find that the forestry sector is both vulnerable to and already feeling the effects of climate change. This work sets out to accomplish two goals. The first is contribute a new modeling approach that accounts of intra-annual changes in the variability of weather patterns on tree growth using signal processing and statistical modeling techniques. The second uses these models, in conjunction with climate projections, to develop a portfolio view of the forest through the lens of a changing and uncertain climate future. We leverage publicly available data from the USFS's Forest Inventory and Analysis Database, ORNL's DAYMET, and NASA's NEX-GDDP-CMIP6 to train models based on past observation and then simulate future growth based on 88 projections of future climate. Our models consider species-level reactions to site characteristics and weather patterns across the southeastern United States. 

Finally, we compare the performance of roughly 4.6 million forest compositions, across four species and two management scenarios, to explore the trade-off between expected return and the variance of said return in a Markowitz Portfolio Selection framework when optimiizing financial returns to timber and carbon production, respectively. Special attention is paid to the performance of different species and their relative prevalence in portfolios along the efficient frontier. 

How to cite: Baker, J. and Manner, R.: A Portfolio of Trees in a Changing Climate: Using Signal Processing and Individual Tree Growth Simulations to Develop Mean-Variance Tradeoff Frontiers for Forest Establishment in the Southern United States, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-20362, https://doi.org/10.5194/egusphere-egu25-20362, 2025.

A reliable assessment of forest resource stocks, productivity, and harvesting is a central goal of environmental monitoring programs. More specifically, evaluating appropriate management tools has become increasingly critical for assessing forest sustainability. Understanding how forests respond to various management tools is essential for developing and implementing sustainable strategies that enhance the resilience of forest ecosystems. Chestnut forest management practices differ across regions, with coppicing being one of the most common techniques. However, evidence from coppiced chestnut forests has raised concerns, particularly related to soil erosion and land degradation.

This study explores the use of advanced remote sensing and spectroscopic techniques to address two key aspects of land and soil degradation in Italian forests. The first objective is to utilize multi-temporal hyperspectral and multispectral satellite imagery to develop and test methods for identifying clearcut areas in chestnut forests resulting from coppice treatments, as opposed to other causes of bare soil, such as wildfires. The second objective focuses on monitoring the erosion impacts on land and soil degradation using mid-infrared (MIR) spectroscopy.

To achieve these goals, the study employed large-scale, multi-temporal satellite imagery from PRISMA, Sentinel-2, and Landsat 8, with a focus on developing a robust methodology for accurately delineating clearcut zones in chestnut forests located in central Italy (Campania). A pixel-based approach was used to differentiate between clearcut areas and pixels affected by other disturbances, beginning with a bare soil masking technique to create an annual bare soil composite image, followed by the delineation of clearcut zones.

In addition to remote sensing analysis, a comprehensive soil sampling campaign was conducted at active clearcut sites to evaluate the impact of chestnut management on soil degradation, with a focus on soil organic carbon content. Samples were collected from multiple locations within the clearcut areas to account for spatial variability. This dataset was used to identify areas vulnerable to soil erosion through MIR spectroscopy, offering valuable insights into soil function and the long-term impacts of management techniques on soil health.

The results show that the annual chestnut coppice clearcut areas were mapped with overall accuracies of 80%, 87%, and 92% for Landsat 8, PRISMA, and Sentinel-2, respectively. This approach enabled a detailed, high-resolution assessment of land use changes over time and the identification of clearcut zones due to coppice treatments. The use of MIR spectroscopy also facilitated the assessment and monitoring of erosion-prone areas within chestnut clearcuts.

The findings of this research have significant implications for forest management strategies, particularly regarding sustainable forest management and conservation. This study contributes to enhancing land management strategies by providing a deeper understanding of the environmental consequences of forest systems management techniques and highlighting the potential of remote sensing and spectroscopy for monitoring soil degradation.

How to cite: Mzid, N. and Terribile, F.: Integrating Remote Sensing and Mid-Infrared Spectroscopy to Assess Land and Soil Degradation in Forest Ecosystems: Implications for Sustainable Management, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-19324, https://doi.org/10.5194/egusphere-egu25-19324, 2025.