Soil properties influence plant physiology and growth, playing a fundamental role in shaping species niches in forest ecosystems. Here, we investigated the impact of soil data quality on the performance of climate-topography species distribution models (SDMs) of temperate forest woody plants. We compared models based on measured soil properties with those based on digitally mapped soil properties at different spatial resolutions (25m and 250m). We first calibrated SDMs with measured soil data and plant species presences and absences from plots in mature temperate forest stands. Then, we developed models using the same soil predictors, but extracted from digital soil maps at the nearest neighbouring plots of the Swiss National Forestry Inventory. Our approach enabled a comprehensive assessment of the significance of soil data quality for 41 Swiss forest woody plant species. The predictive power of SDMs without soil information compared to those with soil information, as well as those with measured vs digitally mapped soil information at different spatial resolutions was evaluated with metrics of model performance and variable contribution. On average, performance of models with measured and digitally mapped soil properties was significantly improved over those without soil information. SDMs based on measured and high-resolution soil maps showed a higher performance, especially for species with an ‘extreme’ niche position (e.g. preference for high or low pH), compared to those using coarse-resolution (250m) soil information. Nevertheless, globally available soil maps can provide important predictors if no high-resolution soil maps are available. Moreover, among the tested soil predictors,  pH and clay content of the topsoil layers improved the predictive power of SDMs for forest woody plants the most. Such improved model performance informs biodiversity modelling about the relevance of soil data quality in SDMs for species of temperate forest ecosystems. In conclusion, the incorporation of accurate soil information into SDMs becomes indispensable for making well-informed forecasts for guiding decisions in forest management, also when addressing the potential distribution shifts of woody plant species due to climate change.

How to cite: Rota, F., Scherrer, D., Bergamini, A., Price, B., Walthert, L., and Baltensweiler, A.: Soil data quality and resolution matter when predicting woody plant species in temperate forests, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-1315, https://doi.org/10.5194/egusphere-egu24-1315, 2024.

Climate change has profound implications for global ecosystems, particularly in mountainous regions where species distribution and composition are highly sensitive to changing environmental conditions. Understanding the potential impacts of climate change on native forest species is crucial for effective conservation and management strategies. Despite numerous studies on climate change impacts, there remains a need to investigate the future dynamics of climate suitability for key native forest species, especially in specific mountainous sections. This study aims to address this knowledge gap by examining the potential shifts in altitudinal range and suitability for forest species in Italy's mountainous regions. By using species distribution models, through MaxEnt we show the divergent impacts among species and scenarios, with most species experiencing a contraction in their altitudinal range of suitability whereas others show the potential to extend beyond the current tree line. The Northern and North-Eastern Apennines exhibit the greatest and most widespread impacts on all species, emphasizing their vulnerability. Our findings highlight the complex and dynamic nature of climate change impacts on forest species in Italy. While most species are projected to experience a contraction in their altitudinal range, the European larch in the Alpine region and the Turkey oak in the Apennines show potential gains and could play significant roles in maintaining wooded populations. The tree line is generally expected to shift upward, impacting the European beech, a keystone species in the Italian mountain environment, negatively in the Alpine arc and Northern Apennines, while showing good future suitability above 1,500 meters in the Central and Southern Apennines. Instead, the Maritime pine emerges as a promising candidate for the future of the Southern Apennines. The projected impacts on mountain biodiversity, particularly in terms of forest population composition, suggest the need for comprehensive conservation and management strategies. The study emphasizes the importance of using high-resolution climate data and considering multiple factors and scenarios when assessing species vulnerability. The findings have implications at the local, regional, and national levels, emphasizing the need for continued efforts in producing reliable datasets and forecasts to inform targeted conservation efforts and adaptive management strategies in the face of climate change.

How to cite: Noce, S., Cipriano, C., and Santini, M.: Altitudinal shifting of major forest tree species in Italian mountains under climate change, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-2788, https://doi.org/10.5194/egusphere-egu24-2788, 2024.

Future Forest is an “AI Lighthouse” project funded by the German Ministry of the Environment that has two main objectives: develop a decision support system for forest management and build the foundations for a forest transformation data space.

The Future Forest decision support system is based on a chain of AI/numerical models. The information used to analyse the best alternatives in an area of interest comes from state-of-the-art process-based forest simulations of specific forest management scenarios, AI-based upscaling techniques, and remotely sensed data on current forest composition and health. This data will cover Germany’s forests wall-to-wall with an unprecedented resolution of 100m for the management scenarios and climate data, and up to 10m for other variables.

Creating such a system is impossible without having an accessible pool of data. Since much of the needed information is not freely available, data is collected and organized as an IDSA-compliant data space. Such a data space serves as a platform where various data holders and users converge, exchanging information and analytical applications within a structured data governance framework. This arrangement empowers platform users to retain comprehensive control over their data and enables them to share information with third parties in a controlled and secure environment.

Future Forest is one year away from completion, and we can now present the first results on our way towards a forest management 2.0 system. This system is designed to offer a spectrum of alternatives for effectively managing local forest stands in response to climate change. Considering the forest owner's management objectives, such as timber production or biodiversity, the system proposes alternatives using various ecosystem indicators, encompassing wood production, carbon storage, and biodiversity considerations. The final ranking of the alternatives is based on a multi-criteria decision analysis algorithm, which incorporates also a comprehensive robustness and sensitivity analysis.

In this contribution, we outline the tools utilized to make informed decisions, from the neuronal networks for forest classification to the forest dynamic simulations, and the decision support system. We discuss the constraints encountered and highlight the innovations incorporated in each of these tools. We will discuss the attempt made to offer an explainable or even interpretable model, as far as this was possible. 

How to cite: Catalli, F., Faßnacht, F., Kerber, J., Költzow, J., Mohr, J., Rammer, W., Reitz, T., and Schiller, C.: Future Forest: A Decision Support System for Smart and Sustainable Forest Management., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-3570, https://doi.org/10.5194/egusphere-egu24-3570, 2024.

Informing forest decision makers about the impacts of climate change on forests is challenging because the representative concentration pathway scenarios (RCPs) impose deep uncertainty and complexity that is difficult to integrate in management planning. A user-oriented translation of the RCPs would facilitate the integration of climate change impacts in forest decisions and improve the understanding of how different climate policy actions would affect forests.

We applied a translation of the RCPs by analyzing how three global warming scenarios related to climate policy actions – the Paris targets (1.5°C and 2°C warming) and a higher warming level without climate policy (3°C) – would impact forest dynamics. We developed indices of forest processes (e.g., species succession, biomass, harvest) that capture changes induced by the global warming scenarios relative to a reference period (1981 – 2010). The methodology was adapted from the JRC PESETA IV project, where climate indices had been developed and impacts on forest vulnerability was explored.

We applied this method with a large-scale forest model (LandClim) on a complex and highly diverse 5000 ha forest landscape over an elevation gradient from lowland deciduous to high montane conifer forests in the area of Freiburg, Southern Germany. Simulations started from the state of the forest in the year 2010, and both no-management and a business-as-usual management (BAU) was simulated. For the initial state of the forest, we applied a state-of-the-art initialization procedure that makes use of a detailed inventory network (over 2000 inventory points in the study area) to depict the current forest conditions (e.g., species distribution, stem numbers, tree ages, stem diameters at breast height) at high resolution. BAU was applied in the form of close-to-nature management based on the guidelines by the State Forestry Department. It includes >10 forest types with both younger and older stands.

Simulation results indicate reductions of biomass and species richness at lower elevations, including both lowland and submontane zones, connected to an upslope shift of species. As these changes intensify with increasing global warming, the largest impacts are observed under the 3°C warming scenario, leading to the loss of biodiversity associated with dominant species capitalizing on the changing ecological conditions.

In summary, by applying this method for a diversity in continuous cover forests over a large elevation gradient, our study outlines important forest dynamics representative for temperate forests in Central Europe under three global warming scenarios. Moreover, the evaluation of close-to-nature management can give important insights for forest decision making.

How to cite: Djahangard, M., Costa, M., Bugmann, H., and Yousefpour, R.: Development of continuous cover forests under different levels of global warming – a methodological case study in Southern Germany, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-5097, https://doi.org/10.5194/egusphere-egu24-5097, 2024.

Boreal forests play an important role in climate change mitigation, biodiversity conservation and the provision of vital ecosystem services. Changing climate is likely to increase the frequency and the severity of forest disturbances. Hence, increasing disturbances may offset the past and ongoing efforts to increase forest-based mitigation and halt biodiversity loss. Therefore, understanding the dynamics of forest ecosystems and predicting their responses to management, changing climate and disturbance regimes is vital.  While forest disturbance risk prevention measures i.e., adaptive management, offer solutions to safeguard future timber yields, the effects of adaptive management on biodiversity, climate change mitigation potential of forests and other ecosystem services have received little attention. In addition, it remains unknown whether climate change alters disturbance regimes in a way that cancels out efforts to increase and preserve carbon stocks and protect forest biodiversity. In this study we contrast the effects of mitigation versus adaptation forest management on the resilience of boreal forest ecosystems in a changing climate. We address the following questions: i) How timber harvests, forest carbon stocks and disturbed volumes develop in different forest management and land-use options that emphasize either adaptation or mitigation under different climate scenarios? ii) What are the synergies and trade-offs in ecosystem service and biodiversity indicators in adaptation and mitigation options? To address these questions, we used the process-based forest landscape and disturbance model iLand to dynamically simulate interactions of forest management, climate change and disturbances. We simulated combinations of seven forest management scenarios and three climate scenarios with ten replicate runs for 80 years in Finland. The forest management scenarios included a business-as-usual scenario and mitigation and adaptation scenarios with changes in rotation lengths and in the shares of deciduous trees in regeneration. Mitigation managements resulted in on average 6 to 15% higher carbon stocks over the simulation period compared to business-as-usual even when disturbances were accounted for but even halved the annual harvests. Mitigation management generally increased the amount of deadwood (3-21%) and large diameter trees (10-52%) compared to business-as-usual management but the severity of climate change reduced the positive trend on large diameter trees. Adaptive management reduced especially the bark beetle disturbances but, in some cases, the disturbed volumes were even higher than business-as-usual management because of increased wind damages. Generally, over the simulation period, adaptive management had a small positive impact on deadwood and mixed effects on large diameter trees.  Scenic beauty was impacted very little by climate change or management. Our findings highlight the complex interactions between disturbance risk prevention, biodiversity, carbon storage and sequestration and other ecosystem services. The results help to guide forest managers and policymakers in planning conservation and mitigation efforts, maximizing multiple benefits and enhancing forest resilience under a changing climate.

How to cite: Repo, A., Albrich, K., Jantunen, A., Aalto, J., Lehtonen, I., and Honkaniemi, J.: Contrasting mitigation and adaptation forest management strategies: unraveling the effects on biodiversity and ecosystem services in changing climate and disturbance regimes, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-8520, https://doi.org/10.5194/egusphere-egu24-8520, 2024.

Tree age plays an essential role in forest ecosystems' functioning by affecting structural and physiological plant traits that modulate the water and carbon budgets. On the other hand, tree age distribution in forests depends on population dynamics and, therefore, on the balance between tree mortality and regeneration events, which are ultimately controlled by natural and anthropogenic disturbances. Therefore, the human-induced modulation of the tree age distribution in forests represents a significant and not fully explored pathway to optimize the stability and resilience of forests.

To examine the influence of age distribution on the stability and resilience of forest carbon budget under current and future climate conditions, we applied a biogeochemically process-based model to three past-managed forest stands and modeled their stability and resilience in terms of Net Primary Production (NPP) in the future as undisturbed systems. The model was forced with climate outputs of five Earth System Models under four representative climate scenarios plus one baseline climate scenario over a matrix of 11 age classes for each forest. We found that the NPP peak was reached in the young and middle-aged class (16- to 50-year-old) regardless of the climate scenario, as ecological theories postulate. Under climate change scenarios, the beech forest showed an increasing NPP as well as stability with increasing atmospheric CO₂ and temperature across all age classes, while resilience remained stable. Conversely, in the spruce and Scots pine-dominated sites, NPP decreased under climate change scenarios. In coniferous stands, stability and resilience seem to be controlled mainly by age rather than the climate, with the older stands being more stable and resilient under all scenarios.

These findings highlight the importance of considering age classes and species-specific responses when assessing the impacts of climate change on forest stability and resilience, calling for tailored management strategies to enhance the adaptability of forests in the face of changing climatic conditions, reflecting the different species and age-dependent responses to climate.

How to cite: Vangi, E., Dalmonech, D., Cioccolo, E., Marano, G., Bianchini, L., Puchi, P., Grieco, E., Cescatti, A., Chirici, G., and Collalti, A.: Stand age diversity affects forests' resilience and stability, although unevenly., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-8664, https://doi.org/10.5194/egusphere-egu24-8664, 2024.

Regional and national level projections of forest growth, productivity and carbon sequestration are in high demand for policy makers to understand the impacts of climate change and forest management on ecosystem services. The rapid environmental change has accentuated the need of environmentally sensitive forest models that are simultaneously capable of simulating the development of forests under different management regimes and from an initial state defined in terms of standard forest mensuration variables. Efforts to make environmentally sensitive process models more management oriented have been supported by recent developments in model-data assimilation, allowing for quantitatively reliable, policy-relevant projections. However, while the processes related to forest C balance are quite well understood, possible future changes of nitrogen availability still remain a challenge for modelling, as empirical results are few and theories have not converged to a consensus. This is particularly important for the boreal zone where forests are generally regarded as N limited.

PREBAS is a management-sensitive carbon-balance model that has been calibrated to forest mensuration type data in Finland. In the calibration, N availability was assumed to be derivable from empirical site quality classification. Following empirical observations and predictions from theoretical models, site quality influences fine-root foliage ratio and stand carrying capacity in PREBAS. The model has been linked with a soil C balance model, Yasso. The combined model incorporates environmental impacts on photosynthesis, respiration, litter fall and soil organic matter decomposition. The model system has been found to produce a spatial distribution of national forest growth and C balance levels in Finland that are well comparable with forest statistics and the Finnish national greenhouse gas inventory, and it has also been evaluated more widely in Northern Europe.

The objective of this study was to examine the implications of different future N availabilities on PREBAS projections under climate change. For this, we carried out simulations in a set of 35 sites across a climatic transect and with variable site quality. For these sites we first estimated stand nitrogen requirement on the basis of growth, litter fall and tissue N concentration under maximum canopy cover and in current climate. We then postulated that N uptake depends on N availability and fine root biomass, and estimated N availability by demanding that N uptake should match the N requirement. Based on the results, we developed a method for estimating carrying capacity and below-ground allocation on the basis of changes in the relative availabilities of carbon and nitrogen.

We tested the method by simulating growth in a hypothetical FACE experiment, which showed results qualitatively consistent with the literature of ectomycorrhiza-dominated forests. We then compared three different assumptions of changing nitrogen availability under climate change: 1) no change, 2) change is derivable from changing SOM decomposition rate, and 3) N availability increases in pace with N requirement. These were applied in country-wide simulations under different climate scenarios. The plausibility of the scenarios and results are discussed in the light of previous literature.

How to cite: Mäkelä, A., Minunno, F., Srinet, R., and Peltoniemi, M.: Incorporating nitrogen effects in a management and environment sensitive forest model at regional scale, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-9634, https://doi.org/10.5194/egusphere-egu24-9634, 2024.

Harvesting of wood is one of the key processes of forest management, strongly impacting the structure and dynamics of European forests. This makes accounting for it crucial in any large-scale analysis of forest ecosystems. Yet, the representation of forest harvests in large-scale models is typically far from realistic, as the actual management regimes are not well described by simple rules or even by formal management guidelines.

Here, we show an implementation of national forest inventory (NFI) -based forest harvesting regimes in a demographic vegetation model, LPJ-GUESS. In our approach, the probability of harvest in the model simulation is based on frequency of harvest events in the NFI data in forests with similar structure and geospatial location. Similarly, the characteristics of the harvest event (the percentage of the removed tree basal area and, in case of partial harvests, the tree size targeted in the harvest) are based on the observed harvest events in the data, and depend in the simulation on forest structure and location. This means that model simulations are dynamic, responding to the real state of the forest. We demonstrate this with several countries in Europe, for which we have earlier created NFI-based harvest regimes based on analysis of more than 180 000 forest plots. Forests are simulated with LPJ-GUESS with different forest harvesting set-ups, allowing us to compare the outcome of the suggested NFI-based harvest implementation to other approaches, including simplified clear-cut rules and density-based thinning (based on Reineke’s rule). In addition, the simulation results are compared to observational evaluation data.

Moving from simple rule-based approaches to observed NFI-based harvest regimes can bring the model simulations closer to how forests are actually currently managed. Our approach blending big data and dynamics modelling has potential to both enable improved assessments of continental-scale carbon dynamics and provide a realistic reference to which potential future forest management changes can be compared to.

How to cite: Suvanto, S., Lindeskog, M., Olin, S., Piltz, K., and Pugh, T. A. M.: Realistic representation of forest harvesting for large-scale models – integrating harvest information from national forest inventories to LPJ-GUESS, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-9929, https://doi.org/10.5194/egusphere-egu24-9929, 2024.

Global warming and climate change caused by greenhouse gas (GHG) emission is projected to have multiple impacts on the forest ecosystems. To mitigate these impacts, the UK Government has set a goal of net zero emissions of GHG by 2050. One core strategy is to use afforestation and forestry management to implement large-scale Greenhouse Gas Removal (GGR). However, the effectiveness of afforestation as a GGR strategy is difficult to fully evaluate with standard empirical models due to the complexities of environmental conditions under a changing climate. Alternatively, process-based land surface models (LSM), such as the Joint UK Land Environment Simulator (JULES), are increasingly being used to evaluate forest growth within a national GGR context as they are driven by environmental drivers. By coupling the Robust Ecosystem Demography (RED) model with JULES, we model the forest dynamic and carbon sequestration among a set of Representative Concentration Pathway (RCP) projections geographically across the UK up to 2080. Our results demonstrate the capability of mapping the potential GGR across the UK while also accounting for the changing environment and risks of climate change. The results show that JULES-RED can provide an effective tool for national-scale afforestation evaluation toward the 2050 net-zero targets.

How to cite: Chou, H.-K., Harper, A., Argles, A., Duran-Rojas, C., Littleton, E., and Cox, P.: Evaluating the UK forest demography and carbon cycle using a process-based Land Surface Model, JULES-RED, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-15673, https://doi.org/10.5194/egusphere-egu24-15673, 2024.

Predicting forest understorey community responses to global change and forest management is vital given the importance of the understorey for biodiversity conservation and forest functioning. Though substantial effort has gone into disentangling how global change will impact the understorey community, the scarcity of information on site-specific environmental drivers together with large temporal and spatial drivers has limited our understanding of how global change drivers affect understorey characteristics at specific forest sites. Here, using understorey resurvey data collected from 1363 plots across temperate Europe and applying a machine learning approach, we used Gradient Boosting Regression Models (GBM) to model and predict trajectories of four understorey characteristics (species richness, total understorey vegetation cover, proportion of woody species and proportion of forest specialists) to global-change and site-specific drivers (e.g. soil, overstory conditions). We applied the final GBM models to 8 forest sites in Austria to evaluate the effect of future scenarios for nitrogen deposition, climate change and forest management on the forest understory in the year 2030, and project the trajectory of understorey properties from year 1993 to 2030.  The trajectory results showed that increasing nitrogen deposition decreased species richness and proportion of woody species, but increased total understorey vegetation cover and proportion of forest specialists. The effect of climate warming on the proportion of forest specialists appeared to be limited but led to a decrease in species richness, total vegetation cover and proportion of woody species. Finally, a closed canopy could shift the community towards more woody species and forest specialists but may lower species richness and total vegetation cover. Our presented model allows the prediction of trajectories of understorey vegetation responses to global change and management interventions at specific forest sites. 

How to cite: Wen, B. and the forestREplot and PASTFORWARD: Predicting trajectories of temperate forest understorey vegetation responses to global change, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-16274, https://doi.org/10.5194/egusphere-egu24-16274, 2024.

Understanding the water balance components in forests is crucial for sustainable land and water management. The Frankfurt Rhine-Main metropolitan region in Germany is heavily dependent on groundwater, with the Hessian Ried forest being one of the main sources. However, climate change, population growth, continuous land sealing, and the expansion of farmland and irrigation in the region, have increased the pressure on water resources, exacerbating conflicts over water use between the affected sectors. Therefore, the region requires comprehensive solutions for a sustainable and flexible water management.

This study focuses on modelling the water balance components in three monitoring plots located in the Hessian Ried. Each plot is dominated by a different tree species — pine, oak, and beech. The aim of the study is to assess the impact of tree species and soil physical properties on water dynamics and availability. We employed the LWF-Brook90R package for the implementation of the LWF-Brook90 model considering climatic boundary conditions, vegetation parameters and soil physical parameters at different depths. The study covers the period of 2005 to 2023 allowing the assessment of seasonal variations over several years. Moreover, we performed the assessment of different parameter sets and a Bayesian calibration in order to analyse the variations in the resulting water balance components for each plot. We compared our simulations to throughfall and soil water content observations.

Our findings revealed complex interplays between tree species and water balance components, highlighting the importance of species-specific considerations when modelling forests. We obtained a good agreement between our results and observed throughfall, indicated by an R² ≥ 0.7. The different parameter sets and the calibration delivered highly similar statistical indicators of observed versus simulated throughfall. However, the calibration did not improve the throughfall simulations in all cases. Regarding actual transpiration and interception rates, the pine plot exhibited larger variations depending on the parameter set used, compared to oak and beech. Both deciduous stands presented a larger transpiration deficit as water stress indicator compared to the pine plot. The transpiration deficit increased considerably in the three plots after calibrating interception and soil physical parameters, compared to default datasets. Additionally, the simulations of the pine plot resulted in the lowest drainage rates among the plots, due to a combination of factors including the evergreen canopy and predominant sandy soil texture along the entire rooting depth. We achieved a more comprehensive and improved estimation of the soil water content — and consequently soil water storage in the root zone — after calibrating the soil physical parameters in contrast to pre-established soil datasets. This allowed for uncertainties in the estimation of soil water content in the unsaturated zone, which is a key consideration when modelling water balance components.

The insights gained from this research have implications for climate change adaptation and mitigation. As climate patterns shift, understanding how different tree species influence water availability and utilization becomes paramount. The presented models serve as a valuable tool for predicting and managing water resources in diverse forested landscapes, supporting the development of adaptive strategies for sustainable forest management.

How to cite: Morales-Santos, A., Köhler, M., Fleck, S., Scheler, B., Wagner, M., and Meesenburg, H.: Modelling water balance components in a temperate forest in Germany: A comparative analysis of pine, oak, and beech, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17088, https://doi.org/10.5194/egusphere-egu24-17088, 2024.

Forest ecosystems play a well established role in providing a multitude of ecosystem services. It is imperative to maintain the health of forests to ensure a continuous supply of these services. However, increasing pressures such as growing demand of wood products and forest overexploitation, climate change, land use change, etc. are compromising their resilience and services provision.
To address this challenge, various European and national policies are directed on either expanding natural and unmanaged forests (e.g. EU Biodiversity Strategy; European Climate Law ) or improving forest management practices (e. EU Forest Strategy, EU Bioeconomy Strategy). In the former case, the goal is to contain or exclude direct and indirect human intervention and disturbances. In the latter case, while human presence and management are allowed, they must adhere to sustainable and respectful practices
The burden to provide a better balanced array of ecosystem services, ensuring the maintenance of forest resilience in the future, falls largely on the shoulders of forest owners and managers who will face opportunity costs and a deviation from their profit maximization objective.
Nevertheless, achieving policy targets will be made more efficient and realistic with an active involvement of the entire community in a collective endeavour. Individuals may be encouraged and required to contribute to mitigating private economic effort by acknowledging the economic value of market and non market ecosystem services other than provisioning and facilitating payments for these services through a mechanism commonly referred as payments for ecosystem services (PES).

Employing a Choice Experiment methodology, we contribute to the existing knowledge regarding the economic value assigned to forest ecosystem services by assessing the willingness to pay of European citizens under future scenarios, which differ in policy ambition and forest management
Interestingly, as we explore alternative options, also based on outcomes of a project stakeholder workshop, we draw attention to emerging paradoxes within EU strategies. For instance, while provisioning services are generally perceived as undermining regulation services, the substitution of fossil fuels with wood biomass may indeed help reduc ing greenhouse gases emissions and supporting EU climate mitigation targets. Moreover, unlike many studies that treat cultural services as a n undistinguished bundle, we highlight potential conflicts arising from the increase in recreational opportunities and facilities, which may contrast with the desire to enjoy a more natural forest environment and wild biodiversity.
This research is conducted within the project ForestNavigator, involving multidisciplinary scientists dedicated to shape the future EU forests. The result of the economic assessment will be used to enhance the models employed within the project to help support both private and public actors in making well informed decisions on forests management and the preservation of their ecosystem services.

How to cite: eboli, F. and michetti, M.: Navigating Sustainable Forest Futures: Balancing Ecosystem Services in the EU, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17423, https://doi.org/10.5194/egusphere-egu24-17423, 2024.

 Heat and drought stress events have a significant impact on plant phenology. Changes in phenology can alter the length of the growing season and affect carbon, water, and energy fluxes. Some of these changes can persist for several years, especially in response to successive stress events. In this work, we combine remote sensing data and process-based modeling to investigate the effect of different heat and drought stress events on land surface phenology (LSP) and water and carbon fluxes in a deciduous and coniferous forest in southwest Germany. We used climate data to characterize different stress events for selected forest sites and as input for the process-based model LandscapeDNDC (LDNDC). For the determination of different LSP metrics we used time series of the Enhanced Vegetation Index (EVI) covering the last two decades. The evaluation of the model simulations was done using remote sensing data. The results indicated that different EVI and LSP trajectories exist for deciduous and coniferous sites. The model simulations also demonstrated that significant variations in water and carbon fluxes exist for the period during and after the stress events, and that leaf area recovery was linked to gas exchange. Since the overall forest development strongly depends on stress response strategy as well as stress frequency and intensity, combining climate projections and process-based models is needed to explore the suitability of forest response types under expected climate changes

How to cite: Moutahir, H., Petrik, P., Grote, R., and Kiese, R.: Changes in land surface phenology and gas exchange of deciduous and coniferous forests in response to heat and drought stress, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-20048, https://doi.org/10.5194/egusphere-egu24-20048, 2024.