Orals: Wed, 6 May, 10:45–18:00 | Room L3
Tropical forests play an important role in regulating climate and the hydrological cycle. Rapid deforestation across the tropics is radically changing the land surface, causing local and regional warming and altering the pattern of precipitation. The biogeophysical mechanisms behind these changes are complex and still not fully understood: climate models disagree on the sign of the precipitation change in response to tropical deforestation and the extent to which recent tropical deforestation has altered precipitation remains highly uncertain. Here, we apply observation and model-based approaches to provide new information on how tropical deforestation impacts precipitation. We combine satellite-based precipitation and forest loss data to explore how tropical deforestation is associated with rainfall trends across the tropics (30°S–30°N) from 2001 to 2024. We find the largest precipitation declines within and downwind of regions that have experienced the largest reductions in tropical forest canopy cover. To explore mechanisms behind these observed precipitation changes, we analyse simulations from climate models participating in the Land Use Model Intercomparison Project (LUMIP). Models predict a diverging response of precipitation to Amazon deforestation, largely due to opposite moisture convergence responses across models. We find that models with larger positive surface albedo response to deforestation typically have larger reductions in evapotranspiration, moisture convergence and precipitation. Finally, we use simulations from the UKESM and the Brazilian Atmospheric Model (BAM) to simulate the local and regional climate responses to different future land use scenarios and explore potential impacts on human health, agriculture and fire.
How to cite: Spracklen, D., Argles, A., Arnold, S., Baker, J., Butt, E., Chadwick, R., Coelho, C., Kubota, P., Marsham, J., Maybee, B., McClory, S., Parker, D., Reddington, C., Robertson, E., Smith, C., and Wright, E.: Tropical forests make it rain: new understanding from observation and model-based approaches, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-19859, https://doi.org/10.5194/egusphere-egu26-19859, 2026.
Land use and land cover change (LULCC) remains one of the largest and most persistent sources of uncertainty in the global carbon budget, limiting confidence in estimates of terrestrial carbon sources and sinks. Within LULCC, deforestation in tropical dense humid forests contributes a substantial share of emissions due to high biomass stocks and continued land conversion across major tropical regions. Despite the availability of several global forest change datasets, estimates of annual deforested area differ widely. Variations in forest definitions, disturbance detection methods, and temporal attribution lead to inconsistent estimates of both the magnitude and timing of forest loss, which propagate directly into uncertainty in LULCC emission estimates used in global carbon budget (GCB) assessments and Earth system models.
Consistent monitoring of tropical deforestation is particularly challenging because of persistent cloud cover, heterogeneous disturbance processes, and strong spatial and temporal variability in forest loss dynamics. These challenges are most pronounced in regions such as the Congo Basin, where observational limitations lead to uneven detection performance and reduced comparability across datasets. Improving the spatial and temporal consistency of deforestation estimates across tropical regions is therefore critical for reducing uncertainty in LULCC emissions and for supporting model evaluation within the GCB.
The objective of this study is to improve the spatial and temporal consistency of pantropical deforestation estimates derived from optical satellite data over the last 25 years. We present a consistent, high-resolution deforestation monitoring approach based on Landsat Analysis Ready Data, with application to Amazonia, Central Africa, and Southeast Asia.
Deforestation is detected within masks of intact tropical forests. To improve robustness in persistently cloudy environments, standard Landsat Quality Flags are complemented by a regionally adaptive, cloud-tolerant masking strategy, enabling the construction of continuous spectral time series suitable for long-term analysis. Deforestation signals are identified using Normalized Burn Ratio time series combined with forest-based local standardization. This yields a statistical change indicator designed to balance sensitivity to disturbance with robustness to noise and data gaps. Candidate deforestation events are further refined using complementary spatial and temporal metrics, including data availability constraints, disturbance amplitude, and spatial proximity to neighbouring events, enhancing coherence while limiting spurious detections. Parameter calibration and optimisation are conducted independently, with reference to existing operational monitoring systems, including Global Forest Change and Tropical Moist Forest products.
Evaluation using a targeted two-level validation framework combining spatial intersections and temporal stratification indicates reduced bias and root-mean-square error in annual deforestation estimates relative to widely used global datasets. Improved detection performance is particularly evident in observationally challenging regions such as the Congo Basin. Analyses in Amazonia and Southeast Asia are ongoing and already show coherent spatial patterns and realistic temporal dynamics.
Overall, this work demonstrates that harmonized, high-resolution optical time series can provide more consistent estimates of tropical deforestation, supporting improved quantification of LULCC emissions. By reducing discrepancies in annual forest loss estimates, the approach provides a more stable observational basis for GCB assessments and Earth system model evaluations like IPCC assessments.
How to cite: Bos, A., Lamarche, C., De Maet, T., and Defourny, P.: Consistent Pantropical Deforestation Monitoring in Dense Humid Forests from Landsat Time Series (2000–2025), EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-18137, https://doi.org/10.5194/egusphere-egu26-18137, 2026.
Oil palm plantation is a major form of land use and land cover change in the tropics, frequently occurring at the expense of natural vegetation and thereby altering carbon, water and energy fluxes. To assess the biophysical and biogeochemical impacts of future oil palm expansion under climate change, we developed a pan-tropical expansion scenario spanning from 2023 to 2100. Using CLM-palm, a perennial crop module based on the Community Land Model 5 (CLM5), we conducted oil palm expansion simulations for Southeast Asia, Africa and the Amazon under two climate scenarios (SSP1-2.6 and SSP3-7.0).
Across all regions, oil palm expansion increases total vegetation carbon (+9.7%) and net ecosystem production (more than fivefold), but reduces soil carbon (-5.9%) under the SSP1-2.6, reflecting trade-offs between productivity and long-term carbon storage. Vegetation carbon responses depend strongly on previous land use, with forest-to-oil palm conversion causing the largest losses and cropland conversions yielding modest gains. Hydrologically, expansion enhances evapotranspiration (+2.5%), leading to decreases in surface water availability (-3.3%), runoff (-3.3%) and soil moisture (-3.7%). Land surface temperature responses reflect competing biogeophysical cooling (-0.54°C) and biogeochemical warming (+0.18°C), with strong regional contrasts: cooling in Africa (-0.37°C), warming in the Amazon (+0.23°C), and near offsets in Southeast Asia. Results under SSP3-7.0 show similar spatial patterns but substantially larger magnitudes, indicating that warming amplifies these responses.
These results show that oil palm expansion produces region-specific, climate-dependent trade-offs in carbon, water and land surface temperature, underscoring the importance of accounting for land-use in climate assessments.
How to cite: Xu, R., Fan, Y., Ali, A., Beerling, D., and val Martin, M.: Impacts of Future Oil Palm Expansion on Carbon and Hydrological Fluxes across the Tropics, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-5102, https://doi.org/10.5194/egusphere-egu26-5102, 2026.
Tropical deforestation causes substantial changes to local climate, including strong daytime warming at the land surface. While deforestation is driven by a wide range of factors such as commodity production, shifting agriculture, and forestry, it remains unclear whether the local climate impacts of forest loss vary across these drivers. Using remotely sensed atmospheric and land-surface datasets, we examined whether the local warming due to tropical forest loss from 2001 to 2019 differed by deforestation driver. We find that forest loss consistently induced local daytime warming across the tropics that exceeds regional climate change over the same period, with 0.6 °C of warming in the Amazon, 0.47 °C in South-East Asia, and 0.18 °C in the Congo. In the Amazon, commodity-driven deforestation caused 0.66 °C of warming, more than double that from shifting agriculture (0.31 °C). Across the tropics, commodity-driven forest loss produced 0.02 °C warming per percentage point of forest loss, compared to 0.01 °C for shifting agriculture. This contrast reflects the biophysical differences between commodity-driven deforestation, typified by large scale, intensive conversion of forest to crops and pasture and shifting agriculture which often involves small-scale land clearance, land abandonment and vegetation regrowth. In the Congo where the predominant driver is shifting agriculture, smaller canopy reductions and vegetation recovery explain the weaker warming response. However, a projected shift toward commodity-driven deforestation, leading to larger reductions in leaf area index and greater increases in surface albedo, could substantially increase local warming. Expansion of commodity agriculture across the tropics will amplify local climate impacts, with serious consequences for communities in forest regions. Our findings highlight the need for climate, agriculture, and land-use policies that account for deforestation drivers. Preserving a mosaic of forest cover within agricultural landscapes can deliver significant local climate benefits and help safeguard livelihoods in tropical regions.
How to cite: Smith, C., Baker, J. C. A., Doggart, N. H., Argles, A. P. K., Robertson, E., Chadwick, R., Adami, M., Coelho, C. A. S., and Spracklen, D. V.: Commodity-driven deforestation doubles local warming from tropical forest loss, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-14277, https://doi.org/10.5194/egusphere-egu26-14277, 2026.
Land-use change is an essential forcing dataset for climate and carbon cycle models, prescribing both the biogeophysical boundary conditions of the land surface as well as the land-based carbon sinks and sources. These datasets are built upon model requirements of a consistent set of variables and formats throughout the historical period as well as into future scenarios. Over the past two decades, both the ability of carbon and climate models to simulate land-use change, and the land-use datasets themselves, have advanced from relatively simple representations of 4 land-use types and their related transitions, to datasets that represent 13 land-use types, their transitions, as well as multiple data layers describing the detailed management of those land-use types. The Land-Use Harmonization (LUH) dataset has been used in both CMIP5 and CMIP6 experiments, as well as over 10 Global Carbon Budgets (GCBs), ISIMIP, IPBES, and will be used again in CMIP7 with several new features and new future scenarios, all provided at a resolution of 0.25 degrees for the years 850-2100 and beyond. In this presentation we will provide an overview of this data product, including recent updates to the historical dataset developed for GCB and comparisons with previous versions. We will present details of the 7 new harmonized future land-use scenarios developed for ScenarioMIP, including new variables used to model land-based Carbon Dioxide Removal (CDR) technologies such as BECCS and Re/Afforestation. Finally we will discuss our plans for new land-use datasets within the “Combining LAnd-use, modeling and Remote-sensing to Transform carbon budgets” (CLARiTy) project, which seeks to reduce the persistently high uncertainties in land carbon flux estimates and will include the development of new LUH products built upon high resolution remote sensing data to inform historical forest disturbances and areas of forest plantations.
How to cite: Chini, L., Hurtt, G., Ma, L., Chapman, J., Klein Goldewijk, K., Rosan, T., Brasika, I. B. M., Sitch, S., Pongratz, J., Lawrence, D., Lawrence, P., and Friedlingstein, P.: Next-Generation Harmonized Land-Use Forcing Datasets for Global Carbon and Climate Models, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-15682, https://doi.org/10.5194/egusphere-egu26-15682, 2026.
Accurate representation of land use and land cover change (LULCC) is critical for simulating land–atmosphere interactions and biogeochemical feedbacks in Earth system models. Here we present a new, spatially and temporally consistent global Plant Functional Type (PFT) dataset designed for land surface and Earth system modeling, with direct applicability to CMIP7 model simulations. The dataset integrates high-resolution satellite-based land cover information with the latest Land-Use Harmonization dataset ( LUH3, updated from LUH2 – Hurtt et al., 2020), while improving the representation of grassland and cropland functional diversity through explicit C3/C4 partitioning.
The historical PFT baseline is derived from the ESA Climate Change Initiative multi-resolution land cover (ESA-CCI MRLC) product for 1992–2022. Annual maps of fractional PFT composition are generated at 300 m resolution using a hierarchical framework that combines satellite observations, auxiliary datasets (tree cover, canopy height, surface water, urban extent), and bioclimatic constraints (Harper et al., 2023). Fourteen generic PFTs are represented, capturing sub-grid heterogeneity relevant for land surface and dynamic vegetation models. These maps are aggregated to coarser resolutions (≥0.1°) to support Land Surface Model (LSM) simulations.
To improve functional realism, natural grasslands are partitioned into C3 and C4 types using a synthesis of optimality-based estimates of potential C4 grass distribution (Luo et al., 2024), satellite-derived herbaceous cover, and complementary global datasets. Croplands are further refined using LUH3 to distinguish managed grasslands and crop types. LUH3 historical land-use states and transitions (850–2024) are merged with the satellite-based PFT baseline, allowing land-use changes such as deforestation, crop expansion, shifting cultivation, and wood harvest to be prescribed consistently through time.
The resulting harmonized PFT–land-use dataset provides a robust forcing for transient Earth system simulations from the pre-industrial period to the present. It improves the representation of LULCC processes, grassland physiology, and human land management, and is fully compatible with LSMs such as ORCHIDEE and CMIP7 requirements. This product enables more consistent assessments of land-based climate feedbacks and anthropogenic impacts on the Earth system.
How to cite: Olivera Guerra, L. E., Bastrikov, V., Lamarche, C., Ottlé, C., and Peylin, P.: A New Plant Functional Type Dataset for Earth System Modeling: Integrating ESA-CCI MRLC, LUH3, and C3/C4 Partitioning for CMIP7, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-14326, https://doi.org/10.5194/egusphere-egu26-14326, 2026.
Reliable, transferable, and locally relevant land-cover information is critical for informed decision-making and ecosystem services assessment. However, this kind of information remains limited in data-scarce, topographically complex regions such as the Andes, constraining the analysis of ecosystem dynamics and climate impacts. Project GRADIENTES addresses this gap through the development of a regional Earth Observation (EO) Foundation Model trained on multi-sensor Sentinel-1 SAR and Sentinel-2 optical data across ecologically diverse watersheds of the Peruvian Andes.
The Foundation Model is trained using self-supervised contrastive learning on seasonally aggregated, multisensor image composites, enabling the learning of task-agnostic surface representations without reliance on dense manual labels. The frozen encoder is subsequently reused to support downstream applications through lightweight supervised models, including land-cover classification and change analysis. Land-cover classes are co-designed with local and regional stakeholders, through the establishment of Living Labs, to ensure operational and ecological relevance.
Downstream land-cover products derived from the Foundation Model achieved overall accuracies exceeding 0.9, comparable to region-specific handcrafted models while requiring substantially fewer training samples. The learned representations further enable the analysis of land-cover transitions and vegetation stress patterns relevant for ecosystem service assessment, especially when combined with gridded precipitation and temperature products developed within GRADIENTES.
This work demonstrates that regional EO Foundation Models can provide a scalable and reusable representation of surface processes in data-challenged mountainous environments. The approach supports integrated analyses of land dynamics, hydro-climatic variability, and ecosystem stress, and establishes a transferable framework for climate-impact and tipping-point research across the Andes and other topographically complex regions.
How to cite: Mantas, V. and Caro, C.: Towards scalable monitoring of mountain ecosystems: assessing land use and land cover transitions and ecosystem services from a new EO Foundation Model, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-14877, https://doi.org/10.5194/egusphere-egu26-14877, 2026.
Land use plays a critical role in achieving the Paris Agreement goals, yet inconsistencies between global carbon models, Earth Observation (EO), and national greenhouse gas inventories (NGHGIs) lead to significant mismatches in CO₂ emission estimates. NGHGIs, reported by countries using IPCC guidelines, guide national policies, while global models and satellite-based Earth Observation estimates support independent evaluations. Ensuring comparability among these datasets is essential.
Here we introduce the LULUCF Data Hub, an interactive platform hosted by the EU Forest Observatory to visualize CO₂ emissions and removals as reported by countries to the UNFCCC, alongside independent global land-use emission datasets. NGHGI data indicate a global net LULUCF sink of -2.3 Gt CO₂ yr⁻¹ (on average 2000-2023), with declining deforestation emissions and increasing forest sinks. For total LULUCF, a good agreement emerges between the translated results from the Global Carbon Budget (GCB 2024, representing the modelling scientific community) and NGHGIs at global level, both in magnitude – with the original gap of 7.2 Gt CO2 yr-1 (2000-2022 average) reduced to 0.8 Gt CO2 yr-1 – and trend. When combining estimates for forest and deforestation, the translated results from Global Forest Watch (GFW, representing the EO scientific community in this study) also show a similar magnitude than NGHGI, but a divergent trend.
While the translation methodology used here effectively addresses conceptual differences among the studied datasets at the global level and for most countries, we highlight regions and countries where disagreements in estimates persist. We provide insights into possible reasons for these discrepancies and indicate areas where further research is warranted. The ultimate objective of the LULUCF data hub is to stimulate dialogue and foster collaborative efforts across different communities to reach a greater consensus on the magnitude and trends of land use emissions and removals, in support of the implementation of the Paris Agreement and in anticipation of the next UNFCCC Global Stocktake.
How to cite: Melo, J., Rossi, S., Achard, F., Alkama, R., Canadell, J. G., Federici, S., Friedlingstein, P., Gibbs, D., Harris, N., Heinrich, V., O'Sullivan, M., Peters, G. P., Pongratz, J., Rose, M., Roman-Cuesta, R., Sanz, M. J., Schwingshackl, C., Sitch, S., and Grassi, G.: The LULUCF Data Hub: regional- and national-level discrepancies between independent global datasets and national GHG inventories., EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-22427, https://doi.org/10.5194/egusphere-egu26-22427, 2026.
Among the most uncertain aspects of how land cover change impacts the Earth system is its effect on cloud formation. These cloud changes are important for both the hydrological cycle through shifts in precipitation, as well as the planetary energy balance through their radiative effects. However, quantifying land surface impacts on clouds remains a challenge, since the outcome depends on numerous convective and mesoscale processes that are not well-resolved in large-scale models. In this work, we focus on deforestation in Southeast Asia as a case study of extensive land cover changes in a complex convective environment. Using a combination of high-resolution atmospheric models and object-based analysis, we demonstrate that the cloud response to deforestation is not uniform and varies strongly across the diurnal cycle and with spatial scale.
We use the Regional Atmospheric Modeling System (RAMS) to conduct a pair of multi-day large eddy simulations (LES; Δx=150m) of shallow-to-deep convection over the island of Borneo. By using identical atmospheric boundary conditions but differing land surface properties, we explore the changes in convective initiation and development that occur due to realistic patterns of tropical deforestation. We use tobac (tracking and object-based analysis of clouds) to quantify shifts in the cloud population and find contrasting responses between various modes of tropical convection. Localized deforestation-driven changes to boundary layer processes result in widespread reductions in shallow cloud cover and suppression of the transition from shallow to deep convection. However, shallow cumuli which do form start raining earlier in the day, resulting in more widespread light rain throughout the afternoon. Furthermore, we also find localized increases in cloudiness along the boundary between forested and deforested areas due to surface heating-induced mesoscale circulations.
Our results demonstrate that land-atmosphere interactions and their implications for convection, hydrology, and radiation can vary greatly throughout the day, depending on prevailing cloud type and their interactions with mesoscale phenomena. We propose that this diurnal variability must be considered to more accurately capture the full impact of deforestation and other land cover changes on clouds, rainfall, and climate.
How to cite: Leung, G. and van den Heever, S.: Cloud Responses to Deforestation Vary Across the Diurnal Cycle, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-14746, https://doi.org/10.5194/egusphere-egu26-14746, 2026.
Solar parks are a rapidly expanding form of land use, primarily aimed at producing renewable energy. However, the aim is to make them multifunctional, and limit negative impacts on soils and biodiversity which requires light availability for plant growth. Previous research has shown a significant decline in plant biomass and soil biota beneath solar panels across different solar parks in the Netherlands that have a dense packing of relatively large, relatively flat solar panel arrays. The ground irradiance under these solar panel arrays is well below 10% of the open field irradiance, and the ecological decline was related to very low light availability beneath the panels. However, plant growth, soil biota and soil organic carbon may still be well-supported at intermediate levels of light availability and by favourable microclimatic conditions. In this research an experimental solar park was constructed with varying solar panel density to test the effect of a light gradient on the vegetation, CO2-fluxes, and on soil biota. The experiment consisted of 6 different light treatments (8%, 20%, 30%, 40%, 65% and 100% of annual open field irradiance) and 3 vegetation treatments (non-sowing, sowing of shade tolerant plant species and sowing of a “standard” species diverse grassland mixture). Plant biomass and species composition, nematode and earthworm abundance and net ecosystem exchange (NEE) were measured. Plant biomass, and the abundance of earthworms and nematodes all significantly increased with increasing levels of light, with the strongest increases between 8% and 20% light. At low light levels, shade tolerant plant species’ biomass was higher compared to the other vegetation treatments. These results show with a relatively small increase in light availability can lead to large benefits to soil health and biodiversity.
How to cite: Scholten, L., de Goede, R. G. M., Edlinger, A., Van Aken, Bas. B., Cesar, K., and De Deyn, G. B.: Exploring the minimum light availability to support plant biomass and soil life in solar parks, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-11526, https://doi.org/10.5194/egusphere-egu26-11526, 2026.
Rapid urbanization across developing regions is driving extensive land-use and land-cover change, profoundly affecting ecosystem productivity and terrestrial carbon cycling. However, the spatially explicit identification of future urban expansion and associated hotspots of carbon sink loss remains limited, constraining the development of targeted land-based strategies for climate mitigation and ecosystem resilience. Here, we project urban expansion across Southeast Asia to 2050 under Shared Socio-economic Pathway (SSP1–SSP5) scenarios by integrating and validating multiple global urban growth models. We combine projected urban growth areas with spatial forest aboveground carbon stocks and fluxes to characterize carbon sinks. Focusing on sixty major cities selected based on socioeconomic characteristics and built-up extent in 2020, we identify spatial hotspots of carbon sink loss relevant for urban land management. We find that future urban expansion is most likely to occur in landscapes already exhibiting low carbon sequestration, often reflecting fragmented or degraded habitats. Across Southeast Asia, total potential carbon sequestration losses during 2020–2050 range from 241.81 to 242.93 Tg C yr⁻¹ under SSP1–SSP5. Aboveground carbon stock losses range from 21.91 to 21.94 Gt C, equivalent to approximately 80.46 Gt CO₂, representing about 16–20% of the remaining global carbon budget since 2020. Spatial hotspots of carbon sink loss are most pronounced in Indonesia, Malaysia, Viet Nam, and Thailand, with distinct patterns emerging at the city scale. Our transferable methodology enables application across diverse regions and delivers spatially explicit, actionable evidence to support place specific land-based interventions for reducing future urban heat risk and enhancing the resilience of human settlements.
How to cite: Xu, R., Hamel, P., Zeng, Y., and Grashoff, P.: Projected Hotspots of Carbon Sink Loss under Urban Expansion in Southeast Asia by 2050, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-5287, https://doi.org/10.5194/egusphere-egu26-5287, 2026.
How to cite: Ghosh, S., Franklin, O., and Zimmermann, B.: Linking LULCC (SSP1-SSP5) scenarios to forest regeneration via wolf-deer-browsing dynamics in boreal forest, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-14648, https://doi.org/10.5194/egusphere-egu26-14648, 2026.
Boreal forests play an important role in the global carbon (C) cycle, but carbon and energy fluxes are still poorly constrained because of complex disturbance histories and a limited number of observation stations throughout remote northern landscapes. The La Romaine watershed in Quebec has undergone extensive hydroelectric development, including dam construction and related land-cover changes. We aim to use a land surface model to quantify the impact of land cover changes from natural and anthropogenic disturbances on net ecosystem productivity (NEP), gross primary productivity (GPP), ecosystem respiration (ER), and latent heat flux. In the initial phase of this study, plant functional types (PFTs) were derived from ESA-CCI land-cover data and used to drive site-level simulations with the Canadian Land Surface Scheme Including Biogeochemical Cycles (CLASSIC) together with ERA5 reanalysis data.
The simulations produced daily time series of NEP, GPP, ER, and net latent heat flux, depicting typical boreal seasonality with strong summer season peaks and snow-dominated dormant seasons. GPP presents a pronounced rise in late spring, while high in mid-summer, but falloff in autumn, whereas ER trailed temperature closely, led to periods of reduced but non-zero C losses during the winter season. Moreover, NEP is characterized by comparatively short windows of net C uptake when photosynthesis surpasses respiration, with longer, milder spring and autumn transition periods and winters with near-neutral or net C loss, while latent heat flux varies with growing-season productivity and moisture availability, signifying a tight coupling between carbon uptake and evapotranspiration.
We show that satellite-derived PFTs with ERA5 reanalysis forcing enable process-based exploration of boreal C and energy dynamics in a remote hydropower complex, even in the absence of dense local measurements. Ongoing work will replace the ESA-CCI PFTs with high-resolution (Landsat 30m resolution), Romaine-specific LULC-derived PFTs and refine the forcing, paving the way to link simulated flux responses with the observation’s ones in the La Romaine watershed.
How to cite: Moazzam, M. F. U., Helbig, M., Talbot, J., Garneau, M., and Roy, A.: Simulating boreal carbon and energy fluxes in the La Romaine watershed with the CLASSIC land surface model, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-6069, https://doi.org/10.5194/egusphere-egu26-6069, 2026.
Under ongoing climate change, high-latitude regions are becoming increasingly suitable for agricultural production, while climate-related risks to food systems are intensifying in many low-latitude regions. Accordingly, the northward expansion of cultivable land has been analyzed as a mitigation buffer for climate change and global food security. However, such expansion raises concerns regarding land-use competition with forestry and the encroachment on forests, soils, and peatlands that takes important roles in the terrestrial carbon cycle. Therefore, the proposition of a practical northern front that defines actually utilizable cropland potential is necessary to enable further analysis of these inherent issues. In this study, we assess the practical northern front under constraints imposed by agricultural workforce availability, used as a proxy for complex socio-economic interactions. The northern front of cultivable land is projected based on a data driven framework that integrates historical trajectories of agricultural employment with demographic assumptions from the SSP narratives. In contrast to the pronounced northward expansion of environmentally suitable land, the projected practical cultivable land area exhibits limited expansion. Under the SSP3 scenario, for instance, a southward retreat of the practical cultivable frontier is identified across Central Asia and the Far Eastern region. In Europe (50–90°N), most environmentally suitable areas remain practically cultivable, whereas in North America, agricultural workforce rarely extends beyond 50°N, except in a few localized regions. These results point to limitations in climate and food security mitigation strategies relying on high-latitude land expansion, while indicating that challenges in low-latitude agricultural systems persist.
Acknowledgment: This research was supported by the National Research Foundation of Korea (NRF) grant funded by the Ministry of Science and ICT (RS-2021-NR055516, RS-2025-02312954).
How to cite: Lee, H., Forsell, N., and Kim, H.: Future Agricultural Workforce Availability as a Constraint on the Northward Expansion of Cultivable Land, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-16122, https://doi.org/10.5194/egusphere-egu26-16122, 2026.
Ecosystem restoration often aims to re-establish environmental conditions required by specific habitat types and improve key ecosystem functions, including greenhouse gas (GHG) regulation and biodiversity support. This study compares two sites in a managed spruce forest landscape on drained wet moorlands in the Ardennes uplands in Belgium. A recently restored area, where spruce stands were cleared, and rewetting was encouraged by blocking drainage ditches to promote the development of moorland habitat, and a longer-established wet moorland site restored over a decade earlier, where vegetation and ecosystem functions have reached a more stable state. The objective was to assess how the restoration stage influences GHG fluxes, associated soil conditions, and biodiversity. From September 2023, methane (CH4), carbon dioxide (CO2), and nitrous oxide (N2O) fluxes were measured bi-weekly using closed dark chambers with LI-7810 and LI-7820 trace gas analyzers (LI-COR Biosciences). From March 2025, transparent chambers were used during the growing season to quantify net ecosystem exchange (NEE). Sampling focused on five zones: three within the recently restored site (adjacent to a closed ditch, far from the ditch, and near a functional drainage ditch), one plot in the managed spruce forest, and one in a longer-established moorland site (Control). At each plot, we also measured soil pore water electrical conductivity, temperature, moisture content, bulk density, and concentrations of soil carbon (C%) and nitrogen (N%). Additionally, ground-dwelling carabid beetles were surveyed using pitfall traps to characterize local biodiversity. GHG measurements revealed large spatial differences among the sites. The Control showed the lowest CH4 fluxes, ranging from −3.62 to 0.47 nmol CH4 m-2 s-1, and ecosystem respiration (Reco) from 0.05 to 3.93 µmol CO2 m-2 s-1. In contrast, the recently restored areas showed greater variability, with CH4 fluxes from −0.68 to above 84.88 nmol CH4 m-2 s-1 and Reco from 0.01 to above 28.49 µmol CO2 m-2 s-1. Growing-season NEE indicated that all plots acted as net CO2 sinks, with the control site reaching peak uptake around −29 µmol CO2 m-2 s-1 and the restored plots showing weaker sinks. The control site also had the highest soil nutrient values (C% = 12.7, N% = 0.73) and the lowest bulk density, whereas the other sites showed lower and more variable C and N (C% = 3.7–10.5; N% = 0.21–0.61) and higher bulk density. N2O and other measured parameters also varied substantially across the sampling sites. In total, over 772 individuals from 22 carabid beetle species were captured, with differences in richness, density, and biomass among sites. These findings indicate that the restoration stage has a large impact on GHG dynamics, soil properties, and biodiversity. The longer-established control site represents a relatively stable semi-natural moorland with low CH4 and N2O fluxes, strong net CO2 uptake, higher soil C and N, and lower bulk density, while the recently restored areas are characterized by higher and more variable fluxes and denser soils. By comparing restoration stages, this study provides insight into ecosystem recovery and can inform strategies to enhance ecosystem functioning, biodiversity, and climate mitigation.
How to cite: Okiti, I., Verdonschot, R. C. M., González Macé, O., de Bijl, J., Pindus, M., Collas, P., and Kasak, K. K.: Greenhouse gas dynamics and soil conditions in restored wet moorlands in an upland managed spruce forest landscape, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-8739, https://doi.org/10.5194/egusphere-egu26-8739, 2026.
Forest and agricultural systems represent major reservoirs of terrestrial carbon and play a key role in the carbon balance of Mediterranean landscapes. Their capacity to sequester carbon in both soils and biomass is highly sensitive to land management and disturbance regimes. However, the soil organic carbon (SOC) response to management practices in these systems remains highly uncertain. Accurate mechanistic modelling of SOC dynamics and validation under different forest and agricultural management scenarios are essential to support national and EU climate policies.
We used the state-of-the-art biogeochemical ecosystem model DayCent to simulate SOC stocks and total biomass in Mediterranean agricultural and forest soils at national scale in Grreece. The modelling framework builds on extensive validation of SOC dynamics in agricultural soils, whereas model evaluation in forests soils remains constrained by the lack of long-term field observations of management and disturbance histories. To address this limitation and evaluate model performance in forest soils, we used publicly available field observations from forest sites in Greece combined with spatial datasets of biomass and SOC stocks. Soil organic carbon dynamics were simulated at the 0-30 cm depth. We applied the model under a set of land management scenarios to assess their effects on SOC dynamics and total biomass. This work provides a promising framework to assess carbon sequestration potential of different land management practices in Mediterranean agricultural and forest soils and supports policy-relevant assessments of carbon dynamics.
How to cite: Sánchez-García, C., Fendrich, A. N., Panagos, P., and Lugato, E.: Modelling carbon responses to land management in Mediterranean forests and agricultural systems: insights from Greece, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-5460, https://doi.org/10.5194/egusphere-egu26-5460, 2026.
Large-scale forestation, a profound form of land cover change, is widely proposed for climate mitigation. Its full Earth system impact, however, depends on complex trade-offs between carbon sequestration in biomass and soils and other biogeophysical feedbacks, alongside stringent land availability constraints. This study assesses the global potential and limits of forestation as a land use change strategy by integrating high-resolution simulations of soil organic carbon dynamics with spatially explicit constraints on land availability designed to prevent adverse impacts on surface albedo, water resources, and biodiversity. Our analysis reveals that when forestation is restricted to these ecologically viable lands, its scale and consequent carbon sequestration potential are substantially lower than previous estimates that did not fully account for these Earth system trade-offs. Furthermore, when land use is limited only to areas aligned with existing national policy commitments, the feasible scope for forestation and its associated carbon sink becomes drastically reduced. Realizing significant climate benefits from forestation requires navigating critical land use trade-offs and expanding ambitious, spatially optimized land-use policies, particularly in regions with high potential.
How to cite: Qin, Z., Wang, Y., Zhu, Y., Cook-Patton, S., Sun, W., Zhang, W., Ciais, P., Li, T., Smith, P., Yuan, W., Zhu, X., Canadell, J., Deng, X., Xu, Y., Xu, H., and Yue, C.: The climate mitigation of global forestation: Constrained by land availability and policy, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-4147, https://doi.org/10.5194/egusphere-egu26-4147, 2026.
Large-scale reforestation is a prominent proposed climate mitigation strategy, yet our understanding of its impact on global and regional temperature remains incomplete. Here, we present the first comparison of temperature responses to three distinct reforestation potentials – Bastin et al. (2019), Moustakis et al. (2024), and Hurtt et al. (2020) – integrated into a fully-coupled Earth System Model (CESM2) under an SSP2-4.5 warming trajectory. Our simulations reveal that while all scenarios achieve a net global cooling ranging from -0.13°C to -0.25°C by 2100, the cooling from carbon uptake is partially offset by biogeophysical warming. Consequently, a comparable net global cooling can be achieved with substantially less reforested area (up to 450 Mha) if planting locations are better suited for regional-scale cooling. Reforestation locally cools the tropics but triggers albedo-driven warming in higher latitudes, which is further amplified by non-local effects. Thus, tropical and subtropical regions emerge as high-potential climate mitigation areas where local cooling dominates, whereas reforestation in mid-to-high latitudes can be climatically counterproductive due to this amplified local warming. Regional temperature outcomes diverge most significantly due to non-local responses, illustrating how specific reforestation patterns reshape the climate through large-scale circulation and oceanic adjustments. Interestingly, despite these divergent temperature patterns, we find that precipitation changes remain surprisingly consistent across the different reforestation scenarios. Our findings underscore the importance of "climate-smart" policies that prioritize the geographical placement of reforestation over total area, accounting for both biogeochemical and biogeophysical effects to maximize global cooling benefits.
Reference to preprint: https://doi.org/10.21203/rs.3.rs-7714264/v1
How to cite: Fahrenbach, N. L. S., De Hertog, S., Jäger, F., Lawrence, P., and Jnglin Wills, R.: Unpacking the potential: How proposed reforestation scenarios shape global and regional temperature, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-3277, https://doi.org/10.5194/egusphere-egu26-3277, 2026.
Forestation has gained prominence as a nature-based climate solution considering international commitments to limit global warming to well-below 2°C above pre-industrial levels. In addition to sequestering carbon dioxide from the atmosphere, forestation affects energy and water fluxes between the land surface and atmosphere, ultimately impacting the hydrologic cycle. Using a multi-model ensemble of Earth system model simulations for scenarios from the sixth phase of the Coupled Model Intercomparison Project wherein all forcings except land use change are identical, we examine forestation impacts on surface energy and water balance across five climatically diverse study regions. Surface and cloud albedo, turbulent heat fluxes, and longwave radiation fluxes are altered with implications for surface temperature where tree cover increase is ≥ 10% of grid cell area. Surface temperature decreases in the tropics and subtropics while slight warming occurs in the highest latitude study region, consistent with previous studies. Evapotranspiration (ET) and precipitation (P) increase in all study regions. P partitioned into ET increases and available water (P-ET) decreases in most study regions. Decreased runoff (R) often follows P-ET decrease and runoff ratio (R/P) decreases in all study regions, whereas subsurface soil moisture decreases in some, all with implications for water management. Shifting transpiration-to-evapotranspiration ratio plays a role in these anomalies. Our findings highlight the need to consider hydrologic cycle impacts when implementing forestation as a climate solution.
How to cite: Leclerc, C. and Zickfeld, K.: Quantifying the Surface Energy and Water Balance Impacts of Forestation Using an Earth System Multi-Model Ensemble, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-16075, https://doi.org/10.5194/egusphere-egu26-16075, 2026.
Accurate estimates of land-use change CO2 fluxes (FLUC) are essential for understanding the terrestrial carbon cycle and for informing national and global climate reporting. FLUC can be quantified using a range of approaches, including bookkeeping models, dynamic global vegetation models (DGVMs), national greenhouse gas inventories, Earth observation-based products, and atmospheric inversions. However, systematic comparison of FLUC estimates across approaches remains challenging due to fundamental methodological differences. Additionally, individual approaches are often associated with substantial uncertainties.
Here, we provide an overview of the main sources of uncertainty and methodological discrepancies across approaches, while highlighting recent advances and identifying promising directions to further harmonize and improve FLUC estimates. Key sources of uncertainty and inconsistency include differing objectives and definitions across approaches, differences in the separation of natural and anthropogenic drivers (leading to FLUC differences of up to 2.8 PgC yr-1), incomplete process representation (contributing up to 30% uncertainty in FLUC), uncertainties in land-use data (up to 30% uncertainty), and constraints related to spatial resolution. At the same time, several important methodological improvements have been achieved recently, including the consideration of environmental changes in bookkeeping-based FLUC estimates and the correction for replaced sinks and sources (RSS) in DGVM-based FLUC estimates. Ongoing research projects are addressing several remaining challenges, including the improvement of regrowth estimates, the quantification of disturbance impacts, and the consolidation and harmonization of different land-use datasets. These developments build primarily on combining high-resolution Earth observation-based databases with the flexibility and traceability of semi-empirical modelling. Together, these advances provide an important contribution towards more consistent and robust estimates of land-use change CO2 fluxes within and across approaches.
How to cite: Schwingshackl, C., Obermeier, W., Gasser, T., Qin, Z., Ravi Panangattuparambil, A., Metzler, H., and Pongratz, J.: Differences and uncertainties in land-use CO2 flux estimates, and how to overcome them, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-10050, https://doi.org/10.5194/egusphere-egu26-10050, 2026.
Vegetation and land cover information play an important role in land-atmosphere interactions for both Numerical Weather Prediction and reanalysis systems. In the ECMWF land surface model (ecLand), a fixed monthly climatology is currently employed for land cover, leaf area index (LAI) and lake cover. Whilst this information accounts for the seasonal cycle, it lacks inter-annual variability. As part of the Copernicus Climate Change Evolution (CERISE) project, monthly varying maps of LAI, land cover and lake information have been developed from 1925 onwards. These maps are based on a combination of observation data sets, machine learning and back-filling methods. These maps are being tested in ecLand forced by ERA5, together with an offline land data assimilation system (LDAS), to produce the ERA-Land-CERISE reanalysis (1939-2019). The LDAS is based on the operational ECMWF land DA system, and consists of a soil moisture, snow depth, 2 m temperature/humidity and lake temperature analysis. Here we briefly describe the time-varying vegetation, land cover and LDAS methods. Case studies for ERA-Land-CERISE are presented, including the warm European summer of 2003. Furthermore, an evaluation of the soil moisture, snow, lake temperature and heat fluxes is performed.
How to cite: Fairbairn, D., de Rosnay, P., Hersbach, H., Pinnington, E., Choulga, M., Boussetta, S., Day, J., Tourigny, E., Mozaffari, A., Huggannavar, V., Ayan, I., and Materia, S.: Exploring the impact of time-varying land cover and data assimilation in ecLand, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-17926, https://doi.org/10.5194/egusphere-egu26-17926, 2026.
This study develops and evaluates an enhanced Land Use and Land Cover Change (LULCC) scheme integrated within the Common Land Model (CoLM) of CAS-ESM2.0, which is coupled with the dynamic vegetation model IAP-DGVM. The updated model captures carbon fluxes and storage changes from key LULCC activities (e.g., deforestation, afforestation, wood harvest) and simulates the dynamic responses of both natural and human-managed vegetation to climate. Historical simulations conducted for CMIP6 LS3MIP/LUMIP demonstrate that the updated model reasonably reproduces the evolution of land-use emissions and trends in ecosystem carbon storage, showing significant improvements over the standard CoLM in simulating the surface climate and terrestrial carbon cycle.
We further quantify multi-source uncertainties in simulated historical LULCC carbon emissions (1850–2014) through ensemble experiments. Results indicate that model parameterization is the dominant source of uncertainty (contributing >50% and exceeding 80% in some comparisons), followed by climate forcing. Initial state uncertainty is significant only in the first few decades, while differences among CMIP6 land-use pathways contribute least to the total uncertainty, highlighting the priority of refining model parameterizations.
Finally, a comparison of simulations forced by CMIP6 (LUH2) and CMIP7 (LUH3) land-use datasets reveals that while global totals of carbon sink and LULCC emissions are similar, notable spatial discrepancies exist in key regions. Emissions in the LUH3-driven simulation show a marked increase (~40%) over the last three decades, attributable to accelerated forest-to-cropland conversion and intensified management in the updated dataset. This work underscores the critical roles of model process representation and input data in assessing the carbon impacts of land-use change.
How to cite: Zhang, Q. and Zeng, X.: Impacts of LULCC on Land Carbon Cycle in CAS-ESM2.0: Historical Benchmarking, Uncertainty, and CMIP6/7 Comparisons, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-21698, https://doi.org/10.5194/egusphere-egu26-21698, 2026.
India is experiencing rapid land-use transitions through cropland expansion and afforestation, which modify surface properties such as albedo and evapotranspiration and, in turn, influence land surface temperature. What remains unclear, however, is how much of the resulting temperature change is driven by individual surface energy balance components, and whether cropland expansion and afforestation produce symmetric or distinct biogeophysical responses, a question we address using idealised ICON model experiments. Therefore, we conduct three land-cover change experiments using the ICON Earth system model and follow the AMIP protocol: (i) a control simulation mirroring the historical land cover change until present-day (CTRL), (ii) a forest-to-cropland experiment (F2C) where all tropical deciduous forests are replaced by cropland, and (iii) a cropland-to-forest experiment (C2F) in which all croplands are replaced by tropical deciduous forest. All simulations are global and span the period 1850-2014 (165 years).
Preliminary results show that, relative to the CTRL simulation, the F2C experiment exhibits a long-term mean surface warming of 0.26°C, while the C2F simulation shows a weaker warming of 0.05 °C over India. Surface energy balance decomposition, which quantifies the contributions of individual radiative and turbulent flux components (shortwave radiation, longwave radiation, latent heat flux, sensible heat flux, ground heat flux, and albedo) to surface temperature change, indicates that the F2C simulation leads to surface warming relative to CTRL (+0.26 °C in the model, compared to +0.55 °C inferred from energy balance attribution). This difference between the attributed and model-simulated warming arises because the attribution estimate sums individual flux-driven contributions, whereas the model-diagnosed temperature additionally reflects nonlinear feedbacks and heat storage effects. Warming is primarily due to increased net longwave radiation (+0.46 °C), decreased latent heat flux (+0.23 °C) and enhanced sensible heat flux (+0.21 °C), partially offset by albedo-driven cooling (-0.36 °C). In contrast, C2F produces weaker warming relative to CTRL (+0.05 °C in the model; +0.07 °C from attribution), dominated by reduced surface albedo (+0.70 °C) and increased net shortwave absorption (+0.06 °C), despite enhanced latent heat flux. C2F exhibits the highest latent heat flux (55.87 W m-2) and lowest downward longwave radiation (61.92 W m-2), favouring cooling, but this is counteracted by low albedo (0.17), high net shortwave radiation (167.87 W m-2), and elevated sensible heat flux (47.30 W m-2). Trend analysis further indicates that C2F warms slightly faster (0.0062 °C yr-1) than CTRL (0.0059 °C yr-1) and F2C (0.0055 °C yr-1), mainly due to a persistently decreasing albedo. Overall, our results show that neither complete afforestation nor extensive cropification maximizes surface cooling over India. Instead, a mixed land-cover configuration optimizes competing biogeophysical processes that regulate surface temperature, highlighting the importance of explicitly accounting for surface energy balance mechanisms in land-use planning.
How to cite: Sharma, J., Kumar, P., and J. Winkler, A.: Mixed Land Cover Maximizes Surface Cooling in India: An ICON Model Energy-Balance Attribution Study, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-12652, https://doi.org/10.5194/egusphere-egu26-12652, 2026.
The large-scale deployment of carbon dioxide removal (CDR) methods will be required to achieve the climate targets set in the Paris Agreement, with afforestation/reforestation (AR) currently being the most widely implemented one. While AR is recognized for its carbon sequestration potential, its biogeophysical effects remain insufficiently understood. This is particularly the case for climate extremes, since their quantification and robust statistical inference against internal variability require large simulation ensembles, which are typically lacking in modelling studies. Climate extremes such as heatwaves, floods and droughts have far-reaching consequences for ecosystems and human society, and understanding whether large-scale AR could unintentionally intensify climate extremes, or may support mitigation efforts by dampening them, is thus critical for assessing its viability as a mitigation measure. To investigate that, it is crucial to disentangle how the biogeophysically-induced effects on climate extremes are affected by the associated AR-induced global cooling and whether such effects differ across various emissions pathways.
Here, using an unprecedented multi-member ensemble of emission- and concentration-driven simulations with a fully coupled Earth System Model (MPI-ESM), we investigate the influence of large-scale AR on precipitation and heat extremes across different scenarios (SSP1-2.6, SSP5-3.4os, SSP3-7.0, SSP5-8.5). The AR scenario used includes an ambitious deployment in the range of country pledges, reaching 935 Mha by 2100 globally. Our setup featuring 120 simulations in total enables a robust quantification of changes in climatic extremes due to AR across spatial and temporal scales and their uncertainty boundaries. We assess the responses of eight climate extreme indicators for 2091-2100.
Our results reveal spatially heterogeneous but overall dampening effects of AR on end-of-century heat extreme indicators. On average, annual maximum temperature decreases by 0.24 °C [0.17 °C, 0.19 °C, 0.17 °C] under SSP5-3.4os [SSP1-2.6, SSP3-7.0, SSP5-8.5]. The number of extreme heat days decreases by 15.1 % [11.3 %, 7.4 %, 4.6 %], annual maximum wet-bulb temperature by 0.10 °C [0.07 °C, 0.08 °C, 0.07 °C] and warm spell duration by 20.3 % [13.0 %, 11.7 %, 7.6 %], respectively. Any biogeophysical warming visible in concentration-driven simulations seems to be largely offset by AR-induced cooling in emission-driven ones, although regional exceptions exist. While the emission scenarios influence the magnitude of differences, they do not alter the overall signal. The dampening of heat extremes is especially evident in major population exposure hotspots, such as Central Africa and Eastern Asia, suggesting that AR can provide co-benefits for mitigating heat-related risks.
AR effects on precipitation extremes are less consistent and exhibit strong regional and scenario-specific variability, with most changes being within the boundaries of internal variability. AR-induced intensification in some regions (e.g. in the tropics) balances out reduction elsewhere, showing a mixed global signal. Within re/afforested regions, precipitation extremes tend to be less intense in high-emission scenarios (SSP3-7.0 and SSP5-8.5).
Overall, our study offers a robust, policy-relevant assessment of the impacts of large-scale AR on future climate extremes. Our results suggest that large-scale AR application not only contributes to climate change mitigation but also offers adaptation benefits, particularly by reducing heat extremes, offsetting any biogeophysically-induced warming.
How to cite: Raberg, K., Pongratz, J., and Moustakis, Y.: Beyond carbon: Does afforestation/reforestation mitigate or trigger future climate extremes?, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-11721, https://doi.org/10.5194/egusphere-egu26-11721, 2026.
Across Northern Canada’s boreal–tundra (CBT) ecozones, climate warming has driven rapid northward greening induced land-cover vegetation type changes that modifies the land–atmosphere energy exchanges. While classical vegetation-type-dependent albedo constrained models predict that high-stature vegetation expansion amplifies warming through surface darkening, our observations suggest contrary diverse climate responses.
Using Landsat-based NDVI and MODIS albedo trends (1986–2023), integrated with land-cover transitions, meteorological records, and surface-energy fluxes, we find that, rather than declining, vegetation increases across ecozones largely correspond to snow-free albedo increases of 0.2–0.8 % dec⁻¹. These albedo increases are spatially collocated with surface-energy trends ranging from −0.003 to −0.009 W m⁻² yr⁻¹, consistent with stronger surface-warming reduction tendencies reaching up to −0.028 °C yr⁻¹ across the majority of central and northern CBT ecozones, particularly where landcover shifts toward mixedwood, broadleaf, and treed-wetlands compared with ecozones regions dominated by highly conifers and shrubified assemblages.
Under classical albedo-constrained expectations, CBT afforestation has often been viewed as a warming risk. Here, by viewing CBT greening–induced increases in high-stature vegetation as natural afforestation analogs, our results show that near-surface warming can be dampened upon afforestation with specific vegetation types, indicating that CBT afforestation feasibility is highly conditional on vegetation structure, hydrological context, and ecozone setting. These findings provide empirical evidence for the possibilities of surface cooling–dominated boreal afforestation pathways in boreal–tundra regions, with implications for permafrost stability, land-based climate mitigation, adaptation, and ecosystem restoration.
How to cite: Amaogu, D. C., Ofosu, E., Kevin Bradley, D., Pigeon, J., Arenson, L. U., Boudreault, R., Moreno-Cruz, J., Leonenko, Y., and Maghoul, P.: Emerging Land-Cover Changes from Boreal-Tundra Greening Reveal Reduced Surface-warming Feedback Relevant to Boreal Afforestation Feasibility in Northern Canada., EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-4048, https://doi.org/10.5194/egusphere-egu26-4048, 2026.
Tropical deforestation causes local warming resulting in elevated human heat stress and a potential human health risk. Analysis of satellite data shows tropical deforestation during 2001–2020 exposed 345 million people to a population-weighted daytime land surface warming of 0.27 °C that is associated with 28,000 (95% confidence interval: 23,610–33,560) heat-related deaths per year. Despite this important impact on public health, limited information is available at the local level on the scale and magnitude of deforestation-induced warming or the potential human healh impacts. Here we present a new interactive online tool that provides local-level information to stakeholders across the tropics on deforestation-induced warming and associated health impacts. In regions of forest loss, local warming from deforestation could account for over one third of total climate heat-related mortality, highlighting the important contribution of tropical deforestation to ongoing warming and heat-related health risks within the context of climate change. Our work provides locally-relevant information to inform stakeholders on the local climate and public health impacts of tropical deforestation.
How to cite: Spracklen, D., Reddington, C., Butt, E., Doggart, N., Rigby, R., Baker, J., Smith, C., Oliveira, B., and Yamba, E.: A new online tool for assessing local climate heating and heat-related mortality associated with tropical deforestation, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-20986, https://doi.org/10.5194/egusphere-egu26-20986, 2026.
Afforestation and reforestation (A/R) are widely promoted as cost-effective climate change mitigation strategies. In policy discussions, the focus often lies primarily on the local carbon sequestration potential, while potential side effects relevant for mitigation and adaptation are often overlooked. Forests, however, also exert strong biogeophysical impacts on the climate system, affecting the land-atmosphere coupling through changes in surface albedo, surface roughness, and evapotranspiration. Such processes may alter the local and remote hydrological cycle. This is particularly critical for monsoon regions, which are home to nearly one third of the global population and strongly depend on seasonal rainfall for agriculture.
Here, we assess whether and how large-scale afforestation affects precipitation seasonality and wet-season characteristics in global monsoon systems using fully coupled, emission-driven Earth system model (CESM2.1.5) simulations. We compare a large-scale A/R scenario initiated in 2025 with a reference scenario without land-use and land-cover change, both conducted under an SSP2-4.5 forcing pathway and evaluated for late-century conditions (2071 - 2100). Attribution of the simulated precipitation responses is explored using global warming level comparisons and optimal fingerprinting. These approaches indicate that precipitation responses cannot be fully explained by greenhouse-gas forcing alone, suggesting a contribution from biogeophysical-driven processes and associated feedback within the emission-driven framework.
To robustly quantify changes in monsoon timing, we apply an onset and cessation detection method developed by Dunning et al. (2016) that allows explicit identification of wet-season start, end, and duration, rather than relying on fixed seasonal averages over multiple months. This enables an assessment of agriculturally relevant precipitation metrics, including wet-season length, shifts in onset and cessation, and changes in rainfall distribution within the rainy season. An analysis of general precipitation regimes (wet-year-round, dry-year-round, annual, and biannual regimes) indicates no major spatial shifts in their global distribution. However, our results reveal regionally heterogeneous responses to afforestation within the annual regimes. The onset of the rainy season advances over South America and the Sahel but is delayed over Australia. Cessation shifts toward earlier dates over India and later dates over Australia, indicating both wet-season shortening and lengthening across monsoon domains. These findings suggest that afforestation can modify precipitation seasonality beyond greenhouse-gas–driven changes, with important implications for water availability and food security in monsoon-dependent regions.
How to cite: Rapp, N., Fahrenbach, N. L. S., Jäger, F., Lawrence, P., and Jnglin Wills, R.: Large-scale afforestation impact on precipitation seasonality in global monsoonregions, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-5078, https://doi.org/10.5194/egusphere-egu26-5078, 2026.
China has pledged to achieve carbon neutrality by 2060, with forestation as one of the key mitigation strategies due to its capacity to absorb and store carbon. However, forests can also emit biogenic volatile organic compounds (BVOCs), potentially affecting the climate. Here, we used the Model of Emissions of Gases and Aerosols from Nature (MEGAN) combined with future forestation dataset for China to investigate the changes in BVOC emissions and the potential climatic effects. The forestation dataset is developed based on the policies and tree species suitability, including a maximal carbon stock scenario and a maximal suitability scenario. To estimate BVOC emissions more accurately, we modified MEGAN to incorporate species-specific emission factors. The simulated results under forestation scenarios maximizing either carbon stock or ecological suitability show that BVOC emissions in China will increase by 0.21 and 0.19 Tg/year under Shared Socioeconomic Pathway 1-2.6 (SSP1-2.6), respectively. Forestation contributes more than 30% of the total BVOC emission increase, although the magnitude varies across scenarios. Broadleaf tree species are the dominate BVOC emitters, which are prioritized in southeastern and southwestern China under the maximal biomass scenario, while are selected in northeastern China under the maximal suitability scenario. These differences thus lead to distinct spatial patterns of BVOC emission increases and the associated climatic effects. Using emission-based radiative forcing responses derived from CMIP6, it is found that the increase in BVOC emissions induced by forestation will result in an additional cooling effect, thereby enhancing the biogeochemical cooling of forestation, particularly under the maximal biomass scenario. These findings highlight the necessity of accounting for BVOC emissions when assessing the climate mitigation potential of forestation.
How to cite: Zhang, Y.: Enhanced BVOC emissions and the corresponding biogeochemical cooling effects controlled by future forestation scenarios in China, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-7853, https://doi.org/10.5194/egusphere-egu26-7853, 2026.
Rapid urbanization has induced substantial changes in land use and land cover (LULC), leading to pronounced modifications in the thermal characteristics of urban environments and, consequently, local climatic conditions. Although the impacts of urbanization on urban heat island (UHI) dynamics have been extensively investigated in large metropolitan regions,smaller and rapidly growing urban centers such as Kharagpur remain comparatively underexplored. This study assesses the influence of LULC transitions on the UHI phenomenon over Kharagpur, including the Indian Institute of Technology (IIT) Kharagpur campus, which has undergone accelerated urban expansion and surface transformation over the past two and a half decades.
Multi-temporal Landsat 5, 7, and 8 satellite imagery were used to analyze spatiotemporal variations in LULC, land surface temperature (LST), and UHI characteristics during the period 2000–2025. LULC classes were generated using supervised classification with the Maximum Likelihood Classifier (MLC) algorithm. The Normalized Difference Vegetation Index (NDVI) and Normalized Difference Built-up Index (NDBI) were employed to characterize surface properties and to estimate LST, enabling the identification and quantification of UHI intensity.
The results reveal a marked expansion of built-up areas, increasing from 26% to 55% across Kharagpur and from 6.7% to 42.3% within the IIT Kharagpur campus, primarily at the expense of barren and vegetated land. A significant and spatially coherent increase in LST is observed over the last 25 years, with pronounced UHI hotspots consistently associated with built-up and barren surfaces. The findings demonstrate that rapid urban growth and LULC transitions play a critical role in modulating the local thermal environment. This study provides valuable insights for sustainable urban planning and the development of heat mitigation strategies in emerging and mid-sized urban centers.
Keywords: LULC, Land Surface Temperature, Urban Heat Island, Landsat
How to cite: Bag, G. G. and Satyanarayana, A.: Impact of Land Use–Land Cover Changes on Urban Heat Island Dynamics in a Rapidly Growing Mid-Sized Indian City, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-16111, https://doi.org/10.5194/egusphere-egu26-16111, 2026.
Rising global temperatures are expected to drive a northward expansion of boreal forests into Arctic regions, triggering multiple and interacting climate feedbacks. This land cover change is also relevant as a parallel to mitigation strategies such as afforestation, which are often evaluated solely for their carbon benefits, while other biogeophysical and biogeochemical effects may substantially offset the intended carbon uptake. Reduced surface albedo from forests replacing snow-covered, treeless areas is widely recognised as a strong warming mechanism. Chemical emissions, specifically biogenic volatile organic compounds (BVOCs), in these regions may also play a substantial role, potentially counteracting albedo-driven warming. In this study, we aim to provide new insights into the climate impacts of Arctic land cover change by assessing both biogeophysical and biogeochemical pathways beyond carbon uptake.
BVOCs influence climate through multiple, partly opposing pathways. Their oxidation products contribute directly to secondary organic aerosol formation and modify indirectly cloud optical properties, potentially leading to a cooling effect. At the same time, BVOCs affect atmospheric chemistry by altering the concentrations and lifetimes of key climate forcers such as ozone and methane, which can introduce a positive radiative forcing. The combined effect of these processes, and their relative importance compared to albedo changes, remains uncertain.
Here, we use the Norwegian Earth System Model version 2.3 (NorESM2.3), including a newly implemented comprehensive atmospheric chemistry scheme, to investigate the radiative impacts of projected boreal forest expansion. We perform targeted simulations under present-day and warmer climate scenarios, allowing us to isolate the contributions from surface albedo changes, BVOC-driven direct aerosol effects, cloud interactions, and chemistry-related impacts on ozone and methane.
By comparing these pathways within a single modelling framework, this work evaluates whether BVOC-related processes can significantly offset albedo-driven warming and how their relative importance evolves under climate warming. The results provide a comprehensive understanding of how land use and land cover changes influence the Arctic climate via interacting biogeophysical and biogeochemical mechanisms.
How to cite: Zaini, A., Blichner, S. M., Tang, J., Fisher, R. A., Lund, M. T., Olivié, D. J., and Berntsen, T. K.: Beyond carbon, from Arctic forest migration to climate mitigation: can biogeochemical effects challenge albedo-driven warming?, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-20671, https://doi.org/10.5194/egusphere-egu26-20671, 2026.
Forest fragmentation is accelerating worldwide as large, continuous forests are divided into increasingly smaller and more isolated patches. While the impacts of fragmentation on biomass storage are well documented, its consequences for forest productivity and carbon sequestration rates remain uncertain. Here, we analyse all ~17 million forest patches across the conterminous United States (CONUS) using a spatial mixed-effects framework to control for broad-scale socio-environmental heterogeneity and spatial autocorrelation. We find that larger forest patches consistently exhibit higher vegetation reflectance and significantly greater per-area net primary productivity (NPP) and gross primary productivity (GPP) than smaller patches under comparable conditions. This produces a robust superlinear scaling of total forest productivity with patch size. On average, a hectare embedded within a 100,000 km² forest is approximately 38% more productive than an isolated hectare in similar environments, and this size-related boost accounts for nearly one-quarter of total annual forest productivity across CONUS. Extending the workflow globally revealed consistent relationships across major forest biomes and continents, indicating that the phenomenon extends beyond CONUS. These findings highlight that fragmentation can substantially reduce carbon uptake even without net forest-area loss, underscoring the need for forest policies that consider spatial configuration alongside total area.
How to cite: Zou, Y., Smith, G., Lauber, T., Wan, J., Ma, H., Gorelick, N., Zohner, C., and Crowther, T.: Larger Forest Patches Exhibit Greater Per-Area Productivity in the U.S. and Worldwide, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-5740, https://doi.org/10.5194/egusphere-egu26-5740, 2026.
The climatic impacts of land cover changes (LCCs) due to altered biophysical properties include local effects in LCC areas and nonlocal effects in both LCC and non-LCC areas resulting from atmospheric feedback. The biophysical impacts of LCC simulated by climate models typically represent only the total effects, i.e., the sum of local and nonlocal effects. The respective local and nonlocal effects have been disentangled from climate model simulations using several methods. However, a systematic intercomparison of these methods under a comparable modeling framework is still lacking, hindering the complete understanding of LCC’s biophysical effect on the methodological nature. This study employs a series of unified global deforestation experiments to assess the performance of existing methods in quantifying the local and nonlocal effects of LCC on land surface temperature. Results show that local effects derived by different methods exhibit overall consistent latitudinal and seasonal patterns compared to those in observational datasets, including the transition zone between warming and cooling across the Northern Hemisphere. The separated nonlocal effects, which dominate the total effects, can be reproduced with broad similarity across methods. Nevertheless, regional discrepancies exist, reflecting the different assumptions of each method. We further discuss and summarize the strengths and limitations of each approach and offer practical suggestions on their usage. This study provides methodological guidance for the quantitative assessment of biophysical climate effects of LCC across multi-scales for climate change research.
How to cite: zhao, Z. and li, Y.: Intercomparison of Methods for Disentangling Local and Nonlocal Biophysical Impacts of Land Cover Changes, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-6581, https://doi.org/10.5194/egusphere-egu26-6581, 2026.
Agricultural management offers a pathway for climate change mitigation beyond greenhouse gas fluxes through biophysical processes that directly modify land-atmosphere energy exchange. Changes in cropland surface albedo influence the climate that operates independently of the biogeochemical impact. The need to account for both biogeochemical and biophysical processes in agriculture is increasingly recognized in assessments of climate-neutral agriculture, but the biophysical impacts remain largely unconstrained.
In this study, we quantified the albedo-mediated climate impacts of three promising agricultural practices, which include cover crop, residue management, and selection of highly reflective crop varieties (pale wheat) over European croplands under present and future climate conditions. To do so, we employed the ORCHIDEE-CROP land surface model, which incorporates a detailed representation of crop growth and management, together with improved albedo dynamics calibrated using observations from nine European cropland sites and satellite-derived leaf area index (LAI) from the Copernicus Land Monitoring Service.
In idealized simulations assuming EU-wide implementation of solutions, we show that scenarios of cover crop, residue retention and pale-wheat cultivation increase annual mean surface albedo by 0.001±0.001, 0.008±0.003 and 0.021±0.004, with pale wheat generating the largest enhancement. All three practices induce modest local surface cooling (-0.11±0.07°C, -0.25±0.13°C and -0.13±0.03°C), with stronger cooling in southern Europe than in northern regions. Residue retention produces the strongest cooling response due to pronounced albedo contrasts during high-radiation summer months, and this biophysical signal persists and strengthens under future climate conditions. Although the albedo-mediated mitigation benefits of cover crops and residue retention are relatively small compared to their biogeochemical impacts on greenhouse gas emissions, these practices are readily deployable and are increasingly adopted for agronomic purposes, particularly in comparison with pale wheat cultivation. Beyond mitigation, albedo management offers adaptation benefits by reducing absorbed shortwave radiation and surface temperatures, thereby alleviating heat stress during critical crop growth stages and enhancing yield stability. Overall, agricultural albedo management emerges as a scalable strategy for climate mitigation and local adaptation across European croplands.
How to cite: Yu, K., Su, Y., Lauerwald, R., Ciais, P., Lesschen, J. P., Bastos, A., Schierbaum, D., Zhang, X., Yi, B., Liu, L., Zhu, L., Vidal, T., and Goll, D.: Biophysical climate responses to albedo management for wheat residue retention, cover crops, and pale wheat across European croplands, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-9895, https://doi.org/10.5194/egusphere-egu26-9895, 2026.
Managed forest regions are increasingly exposed to disturbance regimes that generate cascading impacts beyond directly affected areas. In Austria, disturbance events trigger salvage logging that can disrupt regular harvesting and spill over across space through operational and institutional factors, yet such cross-district dynamics are rarely quantified as a systemic resilience problem. Here we assess systemic resilience in Austria’s district-level forestry system by measuring how regular harvesting responds to salvage “shocks” within affected districts and their spatial neighbors.
Using annual harvest reports for Austrian forest districts from 2000–2024, we use the amount of salvage timber as a measure of disturbance severity. We label years with unusually high salvage volumes as “hotspot” years, based on percentile thresholds. We then compare how regular harvesting deviates from its baseline in (i) hotspot districts and (ii) neighboring districts that share a border, capturing indirect and cascading effects beyond the directly affected area. To examine institutional heterogeneity, we analyze responses by forest ownership type (small private, large private, and public forests) and track trajectories in the years following hotspot events.
We find strong disruptions in regular harvesting in hotspot districts, together with clear spillover responses in neighboring districts. Recovery after hotspot events differs systematically across ownership types. We interpret changes in regular harvesting as an indicator of systemic resilience, capturing (i) resistance (how strongly harvesting is disrupted), (ii) recovery (how quickly harvesting returns toward baseline), and (iii) spillovers (how impacts extend to neighboring districts). These results show that disturbance impacts and recovery in forestry are spatially connected and institution-dependent, suggesting that post-disturbance planning should consider effects beyond the directly affected districts.
How to cite: Golestani, N. and Rauch, P.: Cascading impacts of forest disturbances: spatial spillovers in regular harvesting across Austrian forest districts (2000–2024), EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-10521, https://doi.org/10.5194/egusphere-egu26-10521, 2026.
The renewed surge in atmospheric methane (CH₄) growth since 2020 has necessitated a critical re-examination of anthropogenic sources. Rice cultivation plays a pivotal role in global food security but is also a substantial source of anthropogenic methane (~8–10%). However, quantifying its contribution to the recent surge in atmospheric methane remains uncertain due to the spatiotemporal heterogeneity of methanogenesis and inconsistencies in official agricultural statistics.
Here, by integrating a continuous remote sensing-based dataset of China’s rice agricultural systems with refined pixel-based emission factors that account for localized cropping intensity, we reveal that rice methane emissions declined from 9.41 Tg yr-1 in 2000 to 3.61 Tg yr-1 in 2022, a reduction of 61.6% in China. This steep downward trend (0.36 Tg CH₄ yr-1) stands in stark contrast to the flat or slightly increasing trends reported by previous statistical inventories. We demonstrate that this trend is dominated by a "north-south offset", where emission reductions from shrinking southern double rice systems outweigh the increases from expanding northern single rice systems.
These findings highlight that rice emission inventories relying on statistical data likely overestimate methane emission of rice agricultural systems by overlooking shifts in rice cropping pattern. Crucially, our refined 1-km resolution spatially explicit map of rice methane emissions offers a robust prior to constrain top-down satellite inversions. This framework also provides a transferable pathway for other main rice-growing countries to refine their estimation methods and better understanding of emission responses to structural changes in agricultural systems.
How to cite: fan, C., Zhang, G., Zhao, Z., Wang, J., Liu, R., Zhuang, M., Peng, S., and Xiao, X.: Declining rice methane emissions in China due to decreased and displaced rice cropping, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-10925, https://doi.org/10.5194/egusphere-egu26-10925, 2026.
Land use and land cover (LULC) significantly influence terrestrial carbon cycling and soil functioning in Mediterranean mountain regions, yet the relative contribution of different vegetation types to soil organic carbon (SOC) storage remains poorly quantified. Understanding these relationships is essential for developing effective land-based climate mitigation and adaptation strategies that balance carbon sequestration with broader ecosystem services. This study quantifies SOC and nitrogen (N) stocks across five contrasting LULC types in La Rioja, northern Spain: Pinus sylvestris, Fagus sylvatica, Quercus pyrenaica, Quercus ilex, and a pastureland.
We assessed SOC and N stocks in both forest floor and mineral soil layers (0-40 cm), alongside key physicochemical properties. A soil quality index (SQI) was developed to evaluate overall soil functioning beyond carbon storage alone.
Results demonstrate substantial variation in carbon storage mechanisms among LULC types. Total SOC stocks ranged from 42.9 Mg ha⁻¹ (Quercus ilex) to 112.9 Mg ha⁻¹ (pasture), while N stocks varied from 4.0 to 10.3 Mg ha⁻¹. Pastureland stored the highest mineral soil stocks, associated with elevated organic matter content, finer texture, and lower bulk density. Coniferous forests accumulated substantial SOC and N in surface organic layers, reflecting slow litter decomposition and high C:N ratios, but lower mineral soil stocks. SQI values ranged from 0.32 (Fagus sylvatica) to 0.47 (pasture), indicating significant differences in overall soil functioning.
These findings reveal important considerations for land management decisions: while forest expansion provides carbon sequestration through distinct accumulation pathways, well-managed pastureland systems can achieve comparable or superior total carbon storage with additional co-benefits for soil quality. Our results highlight that vegetation-specific effects on SOC distribution, soil properties, and nutrient dynamics must inform land-based climate strategies. An integrated management approach considering species-specific traits, soil characteristics, and multiple ecosystem services is essential for optimizing carbon storage and maintaining soil functioning in Mediterranean mountain environments under environmental change.
This research project is supported by the FORWARD project (PID2024-161314OB-I00) funded by the MICINN-FEDER.
How to cite: Nadal Romero, E. and Wagner, C.: Soil Organic Carbon Storage and Soil Quality across Forest Types and Pastureland in Mediterranean Mountain Ecosystems, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-16804, https://doi.org/10.5194/egusphere-egu26-16804, 2026.
The CORINE Land Cover (CLC) project, part of the Copernicus program, provides harmonized European data for detecting and monitoring land cover and land use dynamics, with particular attention to environmental protection.
ISPRA (Italian Institute for Environmental Protection and Research), as the National Focal Point of the Europea Environment Agency (EEA) network Eionet, is responsible for producing national CLC datasets for Italy.
The first CLC database was created in 1990 and is updated every six years since 2000. CORINE Land Cover 2024 (CLC2024) introduces an important innovation: the voluntary mapping of newly established ground-mounted photovoltaic (PV) power stations (solar parks, solar power plants) built between 2018 and 2024 on previously non-built-up land.
The mapping is voluntary, however recommended as results will give information not only on the increase of renewable energy production, but also on the extent and type of land occupied by these structures. Given that PV power stations occupy at least one hectare per megawatt of installed capacity, their rapid growth raises increasing concerns about competition for land with agriculture and natural ecosystems.
In this context, Italy, with over 37 MW of PV capacity installed at the end of 2024, represents a critical case study, where 80% of the 1,702 ha of land consumed in 2024 by new ground-mounted plants was previously agricultural.In line with the updated technical guidelines, CLC2024 classification system has been improved by introducing a fourth hierarchical level within class 121. This innovation allows, for the first time, the systematic identification of new bigger ground-mounted PV installation from other industrial or commercial units.
This study presents a nationwide assessment of new PV plants constructed in Italy between 2018 and 2024. Using the CLC change detection framework (MMU 5 ha), we quantify the conversion of agricultural (class 2) and natural (class 3) land into energy infrastructure, comparing results with other national and more detailed data (MMU in order to derive the accuracy. The aim is to provide objective data on the so-called ‘Green-on-Green’ trade-off: balancing the urgent need for renewable energy expansion with the preservation of existing land cover.
The paper describes the national mapping methodology and the statistical analysis carried out on the complete dataset. The results will provide a comprehensive overview of the land cover classes most affected by PV expansion, contributing to the broader debate on agrivoltaics and soil protection. The final results will support land use planners and policymakers in harmonizing energy transition goals with the protection of the national ecological heritage.
How to cite: Palamidessi, A., Cimini, A., D'Antona, M., De Fioravante, P., Dichicco, P., Luti, T., Mariani, L., Marinosci, I., and Munafò, M.: Mapping the "Green-on-Green" trade-off: tracking new solar photovoltaic plants in Italy through the CLC2024 change detection framework., EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-20605, https://doi.org/10.5194/egusphere-egu26-20605, 2026.
Ski slope development represents one of the most intensive land use and land cover changes (LULCC) in Alpine environments, involving large-scale soil disturbance, vegetation removal, and terrain modification. While these transformations are evident, their consequences for hydrological regimes remain poorly quantified.
We analysed more than 20 years of artificial rainfall simulation data from 74 experiments conducted in 12 Alpine ski regions. Surface runoff generation on ski slopes was directly compared to adjacent reference areas with comparable environmental characteristics, allowing robust attribution of observed differences to ski slope development. We complement this experimental design with random forest regression to identify the key site characteristics that most strongly control runoff generation on each surface type.
Surface runoff coefficients on ski slopes (median 0.57) were approximately six times higher than on reference areas (0.09), indicating a substantial reduction in infiltration capacity following ski slope development. Model results indicate contrasting hydrological controls: soil properties and land use are most important for reference areas, while geological factors dominate on ski slopes.
These findings suggest that land use change shifts hydrological sensitivity from near-surface conditions to substrate and geomorphic context. By integrating long-term experimental data with machine learning, this study provides a framework to quantify land use impacts on Alpine hydrology and to support sustainable land management and planning in mountain environments.
How to cite: Lechner, V., Scheidl, C., Schlögl, M., Huber, A., Kohl, B., Klebinder, K., Meißl, G., and Markart, G.: Ski tourism as land use change: Assessing impacts on Alpine surface runoff generation, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-3439, https://doi.org/10.5194/egusphere-egu26-3439, 2026.
Anthropogenic pressures such as agricultural activities and urban development increasingly alter biogeochemical processes in headwaters catchments by modifying hydrological pathways, sediment and nutrient inputs, and carbon cycling. These impacts are intensified in tropical regions where high temperatures and intense episodic rainfall promote enhanced mobilisation of particulate matter and solutes from the landscape and rapid in-stream processing. Despite this, integrated studies linking land-use gradients to changes in carbon isotopes, nutrient dynamics and respiration pathways remain limited in tropical streams. Here we investigate how agricultural activities and human development (as reflected in land use cover) influence nutrients (PO₄3-, NO₃-, NO₂-,NH4+), dissolved inorganic and organic carbon concentrations and isotopes (δ¹³C-DIC, δ¹³C-DOC), particulate organic carbon isotopes (δ¹³C-POC, δ¹⁵N-PN), sediment δ¹³C and δ¹⁵N, and carbon-processing pathways (pelagic and sediment respiration) across inland (Chania, Sagana, Thiba) and coastal (Ramisi, Mkurumudzi) catchments in Kenya. Seasonal sampling during both wet and dry periods captured contrasting biogeochemical conditions. We observed pronounced spatial contrasts in carbon sources and processing. Inland catchments exhibited progressively lower δ¹³C-DIC values (-3.1‰ to -12.6‰) with increasing agricultural cover, whereas coastal catchments showed an increase of δ¹³C–DIC (−16.9‰ to −2.1‰) along similar land use gradients. Across all catchments, δ¹³C-DOC, sediment δ¹³C, and sediment δ¹⁵N increased significantly with the fraction of agricultural land use . Nutrient responses were spatially and seasonally variable, with urbanised sections, particularly in the Thiba catchment showing strong relationships between built-up land use and NO₂⁻ concentrations, as well as between built-up land within 2 km–200 m buffers and N₂O. Both PO₄³⁻ and NO₃⁻ increased with agricultural land cover, though correlation strength varied among Catchments and season. By integrating hydrology, land use, isotopes, nutrients and respiration metrics, this study demonstrates that tropical catchments exhibit distinct inland to coastal controls on carbon sources and nutrient enrichment. These findings underscore the need for region-specific understanding of how land-use change is reshaping carbon and nutrient dynamics in the tropical river systems, in order to guide adequate management strategies to improve water quality.
How to cite: Ngari, S., Tamooh, F., V. Borges, A., Omengo, F., Kibue, G., and Bouillon, S.: Cascading influence of land use on riverine carbon and nutrients in a tropical coastal and inland headwaters streams., EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-3701, https://doi.org/10.5194/egusphere-egu26-3701, 2026.
The Earth has exceeded six critical environmental boundaries, posing threats to sustainable development and the realization of human well-being. Protected areas (PAs) are the core global governance tool to address this challenge and need to be ensured to achieve effective conservation outcomes. The existence of spillover effect may either enhance or diminish the value of PAs, but the consistency between local and spillover effectiveness remains unclear. Here, we focused on 10768 PAs in six typical global regions to explore the consistency between local effectiveness and spillover intensity in two dimensions of anthropogenic mitigation and vegetation conservation. During this process, we employed a nonlinear method to quantify the extent of spillover effect and used the counterfactual method to evaluate the conservation effectiveness. Our analysis indicates that in different regions, the change in the proportion of ecological land varies nonlinearly with the distance from the PA boundary, and the spillover extent varies among regions. A small part of PAs exhibited a significant isolated phenomenon. The spillover intensity and local effectiveness were positive for more than half of the PAs. PAs have achieved consistent local and spillover effectiveness in both dimensions, while the spillover intensity was weaker. Precipitation, NPP and elevation were the dominant influencing factors for local effectiveness in both dimensions. Our results showed that merely designating PAs is not sufficient for success. Effective management measures are also needed. The assessment of PA effectiveness should not be limited to the designated boundaries, but also consider the indirect impact of spillover effect. Indicators of multiple dimensions should be taken to quantify the effectiveness comprehensively.
How to cite: Jiang, H. and Peng, J.: Symmetrical local and spillover effectiveness of protected areas in anthropogenic mitigation and vegetation conservation, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-5392, https://doi.org/10.5194/egusphere-egu26-5392, 2026.
Rising demand for palm oil has driven rapid expansion of oil palm plantations in Southeast Asia over the past decades, yet their impacts on the regional carbon budget remain poorly constrained due to complex interactions between oil palm ecosystems and climate change, stand age, soils, and management. Here, we develop a diagnostic terrestrial biosphere model that incorporates key processes of oil palm carbon cycles, driven by high-resolution remote-sensing products and meteorological forcings. We validate our model using extensive observational data, including 31 site-years of carbon flux observations from eddy covariance sites and 360 sub-national yield records, and then simulate the carbon dynamics from 2001 to 2020 across Indonesia and Malaysia. Our model reproduces the observed carbon fluxes well, with R2 > 0.90 and RMSE < 502 gC/m2/year against eddy covariance measurements. We find oil palm plantations initially (yrs < 10 years) act as strong carbon sources, with annual net ecosystem exchange (excluding harvested fruits) exceeding 2,000 gC/m2/year. The plantations approach carbon neutrality and can become net sinks on mineral soils after maturity (yrs > 10 years), whereas those on peat soils remain net sources in their lifetime. Our study reveals the controlling factors of oil palm carbon fluxes and provides a spatially explicit estimate of carbon fluxes across oil palm plantations, offering insight into their contribution to the regional carbon budget.
How to cite: Zhao, R. and Luo, X.: The impacts of oil palm expansion on the terrestrial carbon cycle in Southeast Asia, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-4739, https://doi.org/10.5194/egusphere-egu26-4739, 2026.
Ensuring food security under climate change is a critical challenge for humanity. Maximizing food security requires an understanding of the drivers of within-field crop yield variation. Edge effects are expected to play an important role in determining total farm yields, as agricultural edges differ in their microenvironmental conditions and ecological processes, impacting crop productivity. However, the magnitude and variation of such effects remains largely unclear. Here, we used the normalized difference vegetation index (NDVI) as a proxy of crop yields to estimate the edge effects on two major US crops (corn and soybeans). We found that crop yields tend to be higher near field edges in the eastern US, an effect that was entirely reversed in the western US. This spatial variation may be driven by environmental conditions, as moist conditions in the Eastern US support natural vegetation and pollinators that promote crop growth near field edges, while dry conditions in the western US make field edges harsher than the interiors. Based on these edge effects, we simulate that optimizing edge effects to maximize their benefits on productivity leads to an annual economic gain of nearly 900 million dollars for corn and 500 million dollars for soybeans. These findings highlight the importance of strategic field-boundary management to enhance yields and economic returns.
How to cite: Yang, G., Smith, G., Crowther, T., Lauber, T., and Zohner, C.: Water availability reverses edge effects on crop yields across the United States, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-7202, https://doi.org/10.5194/egusphere-egu26-7202, 2026.
Cropland conversion is a significant driver of tropical tree cover loss. Recent research has mapped tree cover loss as well as cropland expansion in separate themes using satellite data, but the amount of tree cover loss driven by cropland expansion and the spatiotemporal dynamics are less well understood. The objective of this research is to conduct mapping and quantitative assessments of tree cover to cropland conversion using a combination of satellite-derived land cover change products and design-based inference. We combined the University of Maryland global tree cover loss and global cropland gain maps, both at 30 m resolution, to generate tree cover-to-cropland conversion over five epochs between 2004 and 2023. We employed this new set of maps to aid selection of a stratified random sample for area estimation. We used high-resolution images in Google Earth and time series of Landsat images to interpret the land cover and land use change for each sample unit. This sample allowed us to estimate the area of tree cover-to-cropland conversion over the five epochs and subsequently the temporal trends. Our results suggested that tropical tree cover-to-cropland conversion reached a total of 23.1 ± 2.1 Mha between 2004 and 2023. These results are important for understanding the socioeconomic drivers of deforestation in the tropics.
How to cite: Song, X.-P.: Quantifying tropical tree cover loss driven by cropland conversion, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-10231, https://doi.org/10.5194/egusphere-egu26-10231, 2026.
