BG3.17 | Land use, land management, and land cover change effects on surface biogeophysics, biogeochemistry, and climate
EDI
Land use, land management, and land cover change effects on surface biogeophysics, biogeochemistry, and climate
Co-organized by CL3
Convener: Alan Di Vittorio | Co-conveners: Ryan Bright, Gregory Duveiller, Thomas O'Halloran, Julia Pongratz
Orals
| Fri, 28 Apr, 10:45–12:30 (CEST)
 
Room 2.17
Posters on site
| Attendance Fri, 28 Apr, 08:30–10:15 (CEST)
 
Hall A
Posters virtual
| Attendance Fri, 28 Apr, 08:30–10:15 (CEST)
 
vHall BG
Orals |
Fri, 10:45
Fri, 08:30
Fri, 08:30
Land use and land cover change (LULCC), including land management, has the capacity to alter the climate by disrupting land-atmosphere fluxes of carbon, water and energy. Thus, there is a particular interest in understanding the role of LULCC as it relates to climate mitigation (e.g., CO2 removal from the atmosphere) and adaptation (e.g., shifts in land use or management) strategies. Recent work has highlighted tradeoffs between the biogeophysical (e.g. changes in surface properties such as albedo, roughness and evapotranspiration) and biogeochemical effects (e.g., carbon and nitrogen emissions) of land management and change on weather and climate. However, characterizing the relationship between these effects with respect to their extents and the effective net outcome remains challenging due to the overall complexity of the Earth system. Recent advances exploiting Earth system modelling and Earth observation tools are opening new possibilities to better describe LULCC and its effects at multiple temporal and spatial scales. An increasing focus on land-based mitigation and adaptation strategies to meet more stringent emissions targets has expanded the range of land management practices considered specifically for their potential to alter biogeophysical and biogeochemical cycles. This session invites studies that improve our understanding of LULCC-related climate and weather perturbations from biogeophysical and biogeochemical standpoints, either separately or focused on the intersection between these two factors. This includes studies focusing on LULCC that can inform land-based climate mitigation and adaptation policies. Observation-based and model-based analyses at local to global scales are welcome, including those that incorporate both modeling and observational approaches.

Orals: Fri, 28 Apr | Room 2.17

Chairpersons: Alan Di Vittorio, Gregory Duveiller
10:45–10:47
10:47–10:50
10:50–11:10
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EGU23-13017
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BG3.17
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solicited
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On-site presentation
Alessandro Cescatti

Changes in land cover deeply affect the surface properties and therefore the direction and magnitude of the energy, water and carbon fluxes between the atmosphere and the land, ultimately impacting the local and global climate. The processes underlying biophysical and biogeochemical vegetation properties are themselves strongly influenced by the background climate and therefore affected by climate change in a complex and circular manner. For these reasons, deepening our understanding and prediction capacity of the ongoing changes in the land-climate nexus is of paramount importance to developing land-based climate mitigation strategies and policies that are robust and achievable.

The high complexity of the land-based climate interaction is driven by its bi-directional nature that involves multiple positive and negative feedbacks, and by the co-occurrence of processes with opposite climate impacts (i.e. climate cooling and warming) both for biophysical and biogeochemical processes (e.g. radiative vs. non-radiative effects, respiration versus photosynthesis). These specific features of the land system lead to an extremely high sensitivity of the net climate impact of land cover change to management practices and environmental drivers.

Because of the inherent complexities of the land-climate systems, simulations performed with land-atmosphere coupled models proved to be rather uncertain and strongly affected by knowledge gaps, weak assumptions and oversimplistic parameterization. On the other hand, disentangling the signals of the different processes from Earth observations is particularly complex and leads to uncertain attribution of causality. Even more challenging is using experimental signals derived under present climate conditions to project the future direction and magnitude of biophysical and biogeochemical impacts of land cover change on climate. To this scope, among the key limitations of the widely used “space for time” substitution we can list the role played by unaccounted factors (e.g CO2 fertilization), the speed and span of ecosystem adaptation, the assumption of steady state and the temporal and spatial dependence of the processes. Given the importance of this research topic in the current fight to mitigate climate warming, new approaches and methodological advances are required to benefit from the increasing computational capacity and by the expanding observation of the Earth system. To address the issue, in this presentation I will review the most recent progress of data-driven and hybrid analyses, and report on a recent attempt to investigate the impact of land transformation on the climate trajectory under future climatic conditions. Additional discussion points will deal with the emerging research needs related to non-linearity in the system and tipping points (e.g. related to plant mortality rates), and the possible way forward on the ingestion of knowledge derived from Earth observation in process-oriented modelling frameworks.

How to cite: Cescatti, A.: Assessing the climate impacts of land cover change under present and future environmental conditions, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-13017, https://doi.org/10.5194/egusphere-egu23-13017, 2023.

11:10–11:20
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EGU23-16740
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BG3.17
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On-site presentation
Celine Lamarche, Kandice Harper, Andrew Hartley, Philippe Peylin, Catherine Ottlé, Vladislav Bastrikov, Rodrigo San Martín, Sylvia Bohnenstengel, Grit Kirches, Martin Boettcher, Roman Shevchuk, Carsten Brockmann, Olivier Arino, and Pierre Defourny

The existing CCI Medium Resolution land cover (MRLC) product delineates 22 primary and 15 secondary land cover classes at 300-meter resolution with global coverage and an annual time step extending from 1992 to the present. Previously, translation of the land cover classes into the plant functional types (PFTs) used by the Earth system and land surface models required the use of the CCI global cross-walking table that defines, for each land cover class, an invariant PFT fractional composition for every pixel of the class regardless of geographic location. Here, we present a new time series data product that circumvents the need for a cross-walking table. We use a quantitative, globally consistent method that fuses the 300-meter MRLC product with a suite of existing high-resolution datasets to develop spatially explicit annual maps of PFT fractional composition at 300 meters. The new PFT product exhibits intraclass spatial variability in PFT fractional cover at the 300-meter pixel level and is complementary to the MRLC maps since the derived PFT fractions maintain consistency with the original land cover class legend. This was only possible by ingesting several key 30m resolution global binary maps like the urban, the open water, the tree cover, and the tree height while controlling their compatibility thanks to the MRLC maps. This dataset is a significant step forward towards ready-to-use PFT descriptions for climate modelling at the pixel level. For each of the 29 years, 14 new maps are produced (one for each of 14 PFTs: bare soil, surface water, permanent snow and ice, built, managed grasses, natural grasses, and trees and shrubs each split into broadleaved evergreen, broadleaved deciduous, needleleaved evergreen, and needleleaved deciduous), with data values at 300-meter resolution indicating the percentage cover (0–100%) of the PFT in the given year. Based on land surface model simulations (ORCHIDEE and JULES models), we find significant differences in simulated carbon, water, and energy fluxes in some regions using the new PFT data product relative to the global cross-walking table applied to the MRLC maps. We additionally provide an updated user tool to assist in creating model-ready products to meet individual user needs (e.g., re-mapping, re-projection, PFT conversion, and spatial sub-setting).

How to cite: Lamarche, C., Harper, K., Hartley, A., Peylin, P., Ottlé, C., Bastrikov, V., San Martín, R., Bohnenstengel, S., Kirches, G., Boettcher, M., Shevchuk, R., Brockmann, C., Arino, O., and Defourny, P.: A 29-year time series of annual 300-metre resolution plant functional type maps for climate models, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-16740, https://doi.org/10.5194/egusphere-egu23-16740, 2023.

11:20–11:30
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EGU23-8607
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BG3.17
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ECS
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On-site presentation
Steven De Hertog, Felix Havermann, Suqi Guo, Julia Pongratz, Iris Manola, Fei Luo, Dim Coumou, Edouard Léopold Davin, Sonia Isabelle Seneviratne, Quentin Lejeune, Inga Menke, Carl-Friedrich Schleussner, Florian Humpenöder, Peter Lawrence, Louise Chini, George Hurtt, Wim Thiery, and Alexander Popp

Land cover and land management changes (LCLMC) have often been highlighted as crucial regarding climate change, both for mitigation (e.g. afforestation) and adaptation (e.g. irrigation). In order to understand this role we present fully coupled Earth System Model (ESM) simulations using external forcing conditions from the SSP1-1.9 scenario, except for land cover and land management scenarios that follow differing trajectories. First we conduct a short 30-year historical simulation (histCTL) and a future (years 2015-2100) simulation under SSP1-1.9 conditions but with present day land cover kept at constant end of 2014 conditions (futCTL). These allow us to isolate climate changes in response to the SSP1-19 forcing, but in the absence of land cover changes. Secondly we conduct two simulations under SSP1-1.9 forcing, but with land cover and land management following two different trajectories. These trajectories are derived from the scenarios presented in Humpenöder et al. (2022) and represent two strongly diverging worlds with regard to socio-economic development, environmental protection, and land-based mitigation: (i) the future sustainability scenario (futSust) in which the land sector experiences sustainable development and application of mitigation strategies (such as greenhouse gas emission pricing) in all countries, (ii) the future inequality scenario (futIneq) in which these developments mostly happen in OECD countries, with the rest of the world continuing on current trends (including massive tropical deforestation). Each of these simulations have been run with three different ESMs (CESM, MPI-ESM and EC-EARTH) in order to identify how robust these results are over different ESMs.

The results of these simulations can be used to increase our understanding of the role of land cover scenarios within a low-warming future as prescribed by the Paris agreement. We can compare the effects of all other forcings (futCTL- histCTL; CO2, aerosols etc.) to the effects of land cover changes in the different scenarios (futSust – futCTL or futIneq-futCTL) as well as to the difference between the future sustainability and the inequality narratives (futSust-futIneq). These results will be analysed for temperature and moisture fluxes, mainly focusing on warm and dry extremes and how land cover scenarios affect these.

 

References

Humpenöder, F., Popp, A., Schleussner, C. F., Orlov, A., Windisch, M. G., Menke, I., Pongratz, J., Havermann, F., Thiery, W., Luo, F., Jeetze, P. V., Philipp Dietrich, J., Lotze-Campen, H., Weindl, I. & Lejeune, Q. (2022). Overcoming global inequality is critical for land-based mitigation in line with the Paris Agreement. Nature Communications, 13(1), 1-15.

How to cite: De Hertog, S., Havermann, F., Guo, S., Pongratz, J., Manola, I., Luo, F., Coumou, D., Davin, E. L., Seneviratne, S. I., Lejeune, Q., Menke, I., Schleussner, C.-F., Humpenöder, F., Lawrence, P., Chini, L., Hurtt, G., Thiery, W., and Popp, A.: Importance of land cover scenarios in a low warming world, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-8607, https://doi.org/10.5194/egusphere-egu23-8607, 2023.

11:30–11:40
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EGU23-5938
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BG3.17
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ECS
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On-site presentation
Callum Smith, Jessica Baker, Eddy Robertson, Robin Chadwick, Douglas Kelley, Arthur Argles, Caio Coelho, Dayana Castilho, Paulo Kubota, Isabella Talamoni, and Dominick Spracklen

Tropical deforestation causes local and regional changes in climate through complex biophysical and biogeochemical processes. These processes must be accurately represented in Earth System models for reliable predictions of how future land-use change will impact climate. The impacts of tropical deforestation in the sixth Coupled Model Intercomparison Project (CMIP6) group of models have yet to be fully assessed and evaluated. Here, we use satellite observations to evaluate the local land-surface temperature and precipitation responses to tropical forest loss within CMIP6 simulations analysed at consistent spatial scales. Remote sensed observations show consistent local warming and drying responses to tropical forest loss across all analysed scales from 25 to 200 km. The multi-model mean broadly agrees with observations, although some models simulate increased rainfall and local cooling due to tropical deforestation, opposite to the observed response. We explore potential reasons for this discrepancy within the models. This work provides key insights for specific model improvement in relation to real-world observations. 

How to cite: Smith, C., Baker, J., Robertson, E., Chadwick, R., Kelley, D., Argles, A., Coelho, C., Castilho, D., Kubota, P., Talamoni, I., and Spracklen, D.: Observed and simulated local climate responses to tropical deforestation, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-5938, https://doi.org/10.5194/egusphere-egu23-5938, 2023.

11:40–11:50
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EGU23-351
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BG3.17
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ECS
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On-site presentation
Jessica Ruijsch, Adriaan J. Teuling, and Ronald W.A. Hutjes

The African continent, although having one of the lowest per-capita contribution to greenhouse gas emissions, is already experiencing the effects of global climate change, resulting in biodiversity loss, droughts, reduced food production, reduced economic productivity and loss of lives. Land restoration and greening practices, such as active reforestation, natural regeneration, and water harvesting are seen as one of the major solutions to mitigate climate change through the carbon sequestration potential of trees. However, land restoration practices can also directly affect the local climate through changes in the biophysical properties of the earth surface (e.g. albedo, evapotranspiration and surface roughness) and can therefore be used as adaptation strategy to reduce the impact of climate change in Africa. Yet, it is currently unknown to what extend land restoration can be used to reduce local temperatures in Africa through biophysical processes, because the net cooling or warming effect of vegetation changes depends on latitude, scale and atmospheric conditions.

In this study, we aim to bridge this gap by determining the biophysical cooling and warming effects of land restoration in Africa. To this end, we use MODIS satellite imagery in Google Earth Engine to analyse the effects of vegetation changes (NDVI) in the twenty-first century on albedo and land surface temperature, after which we apply the found relations to predict the cooling effect of potential large-scale land restoration in Africa. Preliminary results show that increases in vegetation cause biophysical cooling in large parts of Africa and especially in dryland areas. Using these relations, we predict that large scale land restoration can decrease the land surface temperature in some areas up to 5 degrees Celsius. With these results we hope to provide more insight in the climate change adaptation potentials of land restoration projects in Africa, as well as other parts of the world.

How to cite: Ruijsch, J., Teuling, A. J., and Hutjes, R. W. A.: Assessing the Cooling Potential of Land Restoration in Africa with Google Earth Engine, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-351, https://doi.org/10.5194/egusphere-egu23-351, 2023.

11:50–12:00
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EGU23-6294
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BG3.17
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ECS
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On-site presentation
Jie Zhang, Jin Wu, Alice Catherine Hughes, Jed Kaplan, and Eduardo Maeda

Over the past 20 years, soybean cultivation has expanded rapidly across the Amazon Basin. There has been growing evidence that the conversion from forest to croplands can worsen the climatic impacts of deforestation, in comparison to other land use conversions, such as forest to rural settlements, or pastures. This research applied process model simulations to clarify the biophysical mechanisms of regional climatic changes associated with the most common land use transitions in the Amazon Basin.  Our results suggest that soybean plantations, due to their minimal vegetation cover and/or seasonal bare land at harvest or planting periods, transmit more longwave radiation to the atmosphere than pastures or forests, leading to an increase in atmospheric temperature. Although the vegetation properties of the soybean plantations tend to increase the surface heat flux, resulting in a stronger surface heat lifting effect, due to the reduction of the water vapor content in the boundary layer, the regional precipitation will also be affected and reduced. Changes in atmospheric boundary layer elements are more pronounced over soybean plantations than in pastures, thereby confirming previous research that large-scale commodity crops will exacerbate regional climatic change in the Amazon Basin. Furthermore, we provide evidence that large-scale soybean plantations have more pronounced climatic impacts in the northern and western Amazon Basin, suggesting that as large-scale soybean plantations continue to expand into new agricultural frontiers, climatic changes associated with it are likely to be magnified. 

How to cite: Zhang, J., Wu, J., Hughes, A. C., Kaplan, J., and Maeda, E.: Expansion of soybean plantations into new agricultural frontiers may worsen the climatic impacts of deforestation in the Amazon Basin, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-6294, https://doi.org/10.5194/egusphere-egu23-6294, 2023.

12:00–12:10
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EGU23-9625
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BG3.17
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ECS
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Virtual presentation
Doris Álvarez-Lozano, David Rivas-Tabares, and Andrea Urgilez-Clavijo

Among the most important transitions in land use change detected in the Ecuadorian Amazon, two stand out: i) agricultural intensification/rotation and ii) the expansion of populated areas. Both are the result of rural development in recent decades on the slope hills of Ecuador towards the Amazon. The changes registered in the landscape are the consequence of an intensification of forestry, agricultural, livestock and mining activities, which has negatively impacted ecosystems, causing loss/mobilization of fauna and biodiversity. Consequently, ecosystems have also been affected by changes in local climatic characteristics with different degrees of affectation. Local changes in temperature, soil moisture, relative humidity, and wind speed are studied in detail in order to improve decision-making regarding conservation and remediation actions for the Amazon biome. In this study, based on land use and cover maps, spatiotemporal analysis of the evolution of the two transitions was carried out, coupled with an analysis of time series of climatic variables. Contrast analysis with long persistence was carried out in the surroundings of changed patches to confirm the climatic variation because of the transition according to LULCC. A landscape ecology approach was used to support and characterise the analysis of transitions and their relationship with the dynamic characteristics and trends of climatic variables. As a preliminary result, a detected set of points with the greatest territorial dynamics associated with local climate change. This set of patches is valuable to prioritize actions in the short term.

Acknowledgements

The authors acknowledge the support of the Master in Climate Change, Agriculture and Sustainable Rural Development (MACCARD), co-funded by the Erasmus + Programme of the European Union. The authors also acknowledge support from European Union NextGenerationEU and RD 289/2021 and the support of Project No. PGC2018-093854-B-I00 of the Ministerio de Ciencia, Innovación y Universidades de España.
 

References

  • Urgilez-Clavijo, A., de la Riva, J., Rivas-Tabares, D. A., & Tarquis, A. M. (2021). Linking deforestation patterns to soil types: A multifractal approach. European Journal of Soil Science, 72(2), 635-655.
  • David Rivas-Tabares, Ana M. Tarquis, Ángel de Miguel, Anne Gobin, Bárbara Willaarts. Enhancing LULC scenarios impact assessment in hydrological dynamics using participatory mapping protocols in semiarid regions. Sci. Total Environ., 803, 149906, 2022. https://doi.org/10.1016/j.scitotenv.2021.149906
  • Urgilez-Clavijo, A., Rivas-Tabares, D. A., Martín-Sotoca, J. J., & Tarquis Alfonso, A. M. (2021). Local Fractal Connections to Characterize the Spatial Processes of Deforestation in the Ecuadorian Amazon. Entropy, 23(6), 748.

How to cite: Álvarez-Lozano, D., Rivas-Tabares, D., and Urgilez-Clavijo, A.: The effect of agricultural intensification and population growth in the local climate. A case study of the Ecuadorian Amazon., EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-9625, https://doi.org/10.5194/egusphere-egu23-9625, 2023.

12:10–12:20
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EGU23-9741
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BG3.17
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Virtual presentation
Carl Bernacchi, Bethany Blakely, Taylor Pederson, Caitlin Moore, Nuria Gomez-Casanovas, Christy Gibson, Anya Knecht, Tilden Meyers, Kaiyu Guan, Evan DeLucia, Emily Heaton, and Andy VanLoocke

A generally accepted understanding of carbon in agricultural fields is that (1) a significant amount of carbon was lost from soils when land was converted from natural vegetation to agricultural ecosystems, (2) over time a steady-state soil carbon concentration is reached with standard agronomic practices, and (3) that improved management practices or optimal crop species selection can result in increased carbon storage over time.  The extent of the carbon lost from conversion from native to agricultural ecosystems is variable, but multiple studies show that carbon losses were large and consistent (supporting point 1).  While an assumption of steady state is generally accepted (point 2), there are significant challenges in measuring whether mature agroecosystems are gaining or losing carbon.  Multiple strategies are continually proposed to increase soil carbon storage (point 3), yet data is sparce given the plentitude of potential opportunities being considered.  Furthermore, direct analysis of soil carbon is prone to substantial heterogeneity, leading to challenge in detecting signals relative to noise in heterogeneous soil environments.  Eddy covariance measurements, while unable to measure pools of carbon in the soil directly, can infer changes in ecosystem carbon storage when measurements are integrated over time.  Here, long-term eddy covariance datasets were used to measure carbon and water fluxes over agricultural ecosystems in the Central Midwestern United States over multiple years for different crop and management practices.  The measurements show that conventionally tilled Midwestern row crops, maize and soybean, integrated on a rotational basis typical for this region represents a large carbon source to the atmosphere, counter to point 2 above.  However, similar measurements over the same agroecosystem but with conservation tillage practices indicate long-term carbon storage, even after 20+ years of conservation tillage with significant climate variability.  These results suggest that large-scale adoption of no-till practices can significantly reduce the large-scale losses of carbon associated with conventional tillage and, potentially, lead to small but meaningful increases in soil carbon storage, supporting point 3.  Similar measurements were also collected over perennial grass ecosystems with potential for bioenergy production, including Miscanthus giganteus, Panicum virgatum, and high species diversity prairie.  While these agricultural ecosystems show promise for offsetting fossil carbon emissions, they are also predicted to be better at storing carbon than annual row crops.  Multiple years of analysis from these ecosystems show that perennial bioenergy crops are much more likely to lead to ecosystem carbon storage than minimally-tilled annual row crops as early as the first year of transition, but the amount of storage varies based on which species is planted.  While this research is focused on one location, the results suggest that the assumptions of steady-state and increases in storage over time may not hold for all agricultural ecosystems and in all locations.

How to cite: Bernacchi, C., Blakely, B., Pederson, T., Moore, C., Gomez-Casanovas, N., Gibson, C., Knecht, A., Meyers, T., Guan, K., DeLucia, E., Heaton, E., and VanLoocke, A.: Carbon losses and gains from agricultural ecosystems – what happened, where are we, and where do we go from here?, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-9741, https://doi.org/10.5194/egusphere-egu23-9741, 2023.

12:20–12:30
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EGU23-17287
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BG3.17
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On-site presentation
Etienne Fluet-Chouinard, Zhen Zhang, Robert Jackson, Benjamin Poulter, Lukas Gudmundsson, and Sonia Seneviratne

Atmospheric methane (CH4) concentration has more than doubled since per-industrial time. The contribution of natural wetland ecosystems, currently the largest natural emitters of CH4, to this increase is not well known. While temperature may have contributed to an growth in emissions, the extent wetlands has declined over this period due to drainage and land use conversion. In this study, we combine a new reconstruction of global wetland extent with simulated CH4 flux from nine land surface model to estimate wetland CH4 emissions over 1901-2020. Our analysis evaluates: 1) the uncertainty of modelled emissions over the century timescale, 2) the separate and combined effects of climate and land use change on emissions, and 3) the global and regional trends of wetland CH4 emissions. We show that prognostic outputs from model of wetland extent are highly uncertain over the century timescale although most prognostic models suggest an emission increase. We find that inclusion of wetland drainage reducing wetland area primarily in temperate latitudes is sufficient to offset the increase in modeled emission in the absence of land use, with an ensemble mean displaying no significant trend between 1901-1920 and 2001-2020. We evaluate the contribution of individual land uses to the decline in global emissions, in particular the conversion to irrigated rice and wet cultivation which are also methane emitting areas. These results diverge from previous source attributions at the century timescale and may require upward revisions to other biogenic sources to balance the budget and remain within δ13C isotope constraints.  In the future, we will investigate the effect of wetland drainage on CO2, CH4 and aquatic carbon export for a more complete accounting of this land use change on global carbon fluxes.

How to cite: Fluet-Chouinard, E., Zhang, Z., Jackson, R., Poulter, B., Gudmundsson, L., and Seneviratne, S.: Offsetting climate and land use effects on wetland methane emissions over 1901-2020, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-17287, https://doi.org/10.5194/egusphere-egu23-17287, 2023.

Posters on site: Fri, 28 Apr, 08:30–10:15 | Hall A

Chairpersons: Alan Di Vittorio, Thomas O'Halloran
A.269
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EGU23-17586
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BG3.17
Alicja Rynkiewicz, Agata Hoscilo, Milena Chmielewska, Aneta Lewandowska, Linda Aune-Lundberg, and Anne Nilsen

The world around us is constantly changing, and humans contribute to many of these changes. Land cover and land use (LCLU) changes over time have a significant impact on the functioning of the Earth, particularly climate change and global warming. Spatial data of LCLU changes find important applications in land management, monitoring the sustainable development of agriculture, forestry, rural areas, assessing the state of biodiversity and urban planning.

In the frame of the InCoNaDa project "Enhancing the user uptake of Land Cover / Land Use information derived from the integration of Copernicus services and national databases”, the maps of land cover (LC) changes were developed for two study areas - the Łódź Voivodeship in Poland and the Viken County in Norway. The detection of LC changes was performed on the annual bases for the period 2018-2021 based on the analysis of multitemporal optical data from the Sentinel-2 mission. The Google Earth Engine (GEE) platform was used, which allows to analyze satellite data and to perform spatial analyses anywhere in the World while providing computing power. The LC change detection method was divided into two phases. The first phase is based on the analysis of spectral signatures, and the second phase applies the machine learning Random Forest algorithm. The classification was performed separately for each time interval: 2018-2019, 2019-2020, 2020-2021. In this way, three independent classification models were developed for each study area. The following three LC change classes were distinguished:  a) no-change, b) forest loss, and c) construction sites and newly built-up areas. The minimum mapping unit (MMU) was 0.2 ha. The LC change detection models reached high accuracy - in both study areas for all time intervals, the overall accuracy was equal to or greater than 0.97 and the Kappa coefficient than 0.95. The independent verification carried out based on the aerial orthophotos proved that the overall accuracy of the LC changes is pretty good for both study areas (around 0.9). The changes occurring in the construction sites and newly built-up area class reached slightly lower accuracy and has the lowest precision. The presented method showed its universality and adaptability, giving the possibility for further development. We will present the method, algorithm, results and their verification for Poland and Norway.

How to cite: Rynkiewicz, A., Hoscilo, A., Chmielewska, M., Lewandowska, A., Aune-Lundberg, L., and Nilsen, A.: Detection of land cover changes based on the Sentinel-2 multitemporal data on the GEE platform, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-17586, https://doi.org/10.5194/egusphere-egu23-17586, 2023.

A.270
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EGU23-10578
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BG3.17
Tiexi Chen

Vegetation change is one of the essential indices of global change. In the past 30 years, based on the remote sensing records, the whole world has shown an overall greening phenomenon, accompanied by regional browning. How to identify the drivers of regional-scale vegetation change, especially to distinguish between climate change and human activities remains a great challenge. Modeling studies show that the CO2 fertilization effect plays a dominant role, but the significant greening contribution of farmland areas at the global scale seems to indicate that human land management (LMC) activities have a huge impact. Methods can be divided into two categories: model and observation statistics. Models are easy to quantify contributions but lack descriptions of LMC processes, and regional-scale statistical methods are difficult to identify driving factors. This study proposes the theory of Paired Land Use Experiment (PLUE), which selects areas with large differences in land management and consistent climate change to achieve "control" of climate change and attribute the difference in vegetation change to on the LMC. The PLUE theory was applied in two selected regions around the world. First, the Khabur River plain on the border between Syria and Turkey was selected. The two countries occupy roughly the same area of the plain. The climate conditions on both sides are consistent with the changes, and the interannual time series correlation coefficient of the Enhanced Vegetation Index (EVI) after detrending exceeds 0.8 (p <0.01). For multi-year trends, this difference can be attributed to LMC. Combined with relevant reports on Syrian social development, social unrest has caused serious degradation of land management capabilities. Therefore, social unrest and occasional severe natural disasters have led to a continuous decline in land management capabilities in the region, further contributing to the "browning" of Syrian vegetation. Secondly, the Sanjiang Plain was selected. China and Russia roughly divided the plain into two, with farmland and temperate savannah as the main vegetation types on both sides. The temperature and precipitation changes in the two places were basically the same, and the leaf area index (LAI) showed a significant growth trend with the same magnitude. However, the seasonal characteristics of the LAI trend in the two regions are significantly different. Using the PLUE method, it can be seen that this difference is caused by land management, including the expansion of paddy fields and the increase in farmland management intensity (mechanization, pesticide and fertilizer application). At the same time, it is found that the climate residual method will give false conclusions in the attribution of interannual changes. In summary, the PLUE method can directly identify land management activities other than climate elements from observations at the regional scale, which is helpful for further research on the driving forces of long-term vegetation change trends.

How to cite: Chen, T.: the Paired Land Use Experiments (PLUE) theory in driver identification of regional vegetation change, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-10578, https://doi.org/10.5194/egusphere-egu23-10578, 2023.

A.271
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EGU23-5354
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BG3.17
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Erone Ghiznoni Santos, Martin Svátek, Matheus Henrique Nunes, and Eduardo Eiji Maeda

Changes in vegetation structure caused by selective logging have direct impacts on energy exchange and ecosystem functioning, which may result in altered microclimate. In this study, we investigated how selective logging affected microclimate temperatures in tropical forests of Malaysian Borneo. We used structural metrics derived from Terrestrial Laser Scanner (TLS) obtained in 16 permanent forest plots distributed over a logging intensity gradient. The plots were located within the Stability of Altered Forest Ecosystems (SAFE) Project, the world’s largest forest fragmentation experiment. TLS point clouds were used to calculate the following forest structural traits: Canopy Ratio (CR), Effective Number of Layer (ENL), Foliage Height Diversity (FHD), total Plant Area Index (PAI) and PAI layered for each 5 m height, Relative Height (RH) at 25, 50, 75, 95 and 98 percentiles. TOMST-TMS-4 microclimate dataloggers were installed in the centre of each plot to monitor air temperature at 15 cm above ground every 15 minutes during the year 2019. We then tested whether canopy traits derived from TLS point clouds could explain the variability of minimum, mean and maximum air temperature. We found that not recently logged forest plots had consistently lower understory temperatures and lower daily variability in comparison with heavily logged forest plots. Mean daily temperatures decreased by 0.9 °C for each PAI unit. PAI alone, however, could capture only 21% of the microclimate variability between plots, suggesting that structural metrics accounting for the vertical distribution of vegetation are key for a comprehensive understanding of how disturbances arising from logging affect energy dissipation in tropical forests.

How to cite: Ghiznoni Santos, E., Svátek, M., Henrique Nunes, M., and Eiji Maeda, E.: The influence of canopy structural traits on the understorey air temperature of tropical forests in Borneo, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-5354, https://doi.org/10.5194/egusphere-egu23-5354, 2023.

A.272
|
EGU23-11572
|
BG3.17
|
ECS
|
Iris Aalto, Juha Aalto, Steven Hancock, Sauli Valkonen, and Eduardo Maeda

In boreal forests, uneven-aged management has recently become an attractive alternative to even-aged rotation forestry. These different management types, based on selection felling and clear-cutting, respectively, can result in substantial differences in the structural characteristics of  forest stands. Therefore, management modifies net surface radiation and heat fluxes and further regulates microclimatic variability important for forest organisms and ecosystem processes. Yet, the magnitude and structural drivers of microclimate variability in managed boreal forests have remained poorly understood. Here, we studied the stand structure and microclimate of 20 study plots including even-aged and uneven-aged forest stands in the Vesijako Research Forest in southern Finland. We used terrestrial laser scanning (TLS) to quantify the structural characteristics of the sites and measured soil and air temperature with 80 microclimate loggers in 2021–2022. The TLS data showed that the total amount of plant material did not differ between the management types. However, there were significant structural differences in vertical layering and horizontal heterogeneity of vegetation. Our preliminary results show significant differences in microclimate temperatures depending on stand age category. These differences were clearest at the hottest and coldest times of the year. Air and soil temperature variability in uneven-aged stands resembled at stand level the variability that is encountered in even-aged management only across larger areas including young, immature and mature stands. Uneven-aged stands may therefore support more diverse habitats than even-aged forests. We show that the total amount of plant material was a stronger structural modifier of air temperatures than the vertical arrangement of vegetation. We expect our results to clarify how forest management contributes to shaping microclimates experienced by organisms, which has potential consequences on biodiversity and ecosystem resiliency.  

How to cite: Aalto, I., Aalto, J., Hancock, S., Valkonen, S., and Maeda, E.: Effects of forest management on stand structural variability and microclimate in boreal forests, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-11572, https://doi.org/10.5194/egusphere-egu23-11572, 2023.

A.273
|
EGU23-1934
|
BG3.17
|
ECS
|
Jun Ge, Qi Liu, Beilei Zan, Zhiqiang Lin, Sha Lu, Bo Qiu, and Weidong Guo

While the biogeophysical effects of deforestation on average and extreme temperatures are broadly documented, how deforestation influences temperature variability remains largely unknown. To fill this knowledge gap, we investigate the biogeophysical effects of idealized deforestation on daily temperature variability at the global scale based on multiple earth system models and in situ observations. Here, we show that deforestation can intensify daily temperature variability (by up to 20%) in the northern extratropics, particularly in winter, leading to more frequent rapid extreme warming and cooling events. The higher temperature variability can be attributed to the enhanced near-surface horizontal temperature advection and simultaneously is partly offset by the lower variability in surface sensible heat flux. We also show responses of daily temperature variability to historical deforestation and future potential afforestation. This study reveals the overlooked effects of deforestation or afforestation on temperature variability and has implications for large-scale afforestation in northern extratropic countries.

How to cite: Ge, J., Liu, Q., Zan, B., Lin, Z., Lu, S., Qiu, B., and Guo, W.: Deforestation intensifies daily temperature variability in the northern extratropics, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-1934, https://doi.org/10.5194/egusphere-egu23-1934, 2023.

A.274
|
EGU23-9244
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BG3.17
The potential and pitfalls of climate change mitigation of large-scale forestation actions in drylands
(withdrawn)
Dan Yakir, Shani Rohatyn, Eyal Rotenberg, and Yohay Carmel
A.275
|
EGU23-3754
|
BG3.17
|
ECS
Chaorong Chen, Jun Ge, Weidong Guo, Yipeng Cao, Yu Liu, Xing Luo, and Limei Yang

Afforestation can impact surface temperature through local and nonlocal biophysical effects. However, the local and nonlocal effects of afforestation in China have rarely been explicitly investigated. In this study, we separate the local and nonlocal effects of idealized afforestation in China based on a checkerboard method and the regional Weather Research and Forecasting (WRF) Model. Two checkerboard pattern–like afforestation simulations (AFF1/4 and AFF3/4) with regularly spaced afforested and unaltered grid cells are performed; afforestation is implemented in one out of every four grid cells in AFF1/4 and in three out of every four grid cells in AFF3/4. The mechanisms for the local and nonlocal effects are examined through the decomposition of the surface energy balance. The results show that the local effects dominate surface temperature responses to afforestation in China, with a cooling effect of approximately −1.00°C for AFF1/4 and AFF3/4. In contrast, the nonlocal effects warm the land surface by 0.14°C for AFF1/4 and 0.41°C for AFF3/4. The local cooling effects mainly result from 1) enhanced sensible and latent heat fluxes and 2) decreases in downward shortwave radiation due to increased low cloud cover fractions. The nonlocal warming effects mainly result from atmospheric feedbacks, including 1) increases in downward shortwave radiation due to decreased low cloud cover fractions and 2) increases in downward longwave radiation due to increased middle and high cloud cover fractions. This study highlights that, despite the unexpected nonlocal warming effect, afforestation in China still has great potential in mitigating climate warming through biophysical processes.

How to cite: Chen, C., Ge, J., Guo, W., Cao, Y., Liu, Y., Luo, X., and Yang, L.: The Biophysical Impacts of Idealized Afforestation on Surface Temperature in China: Local and Nonlocal Effects, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-3754, https://doi.org/10.5194/egusphere-egu23-3754, 2023.

A.276
|
EGU23-7539
|
BG3.17
Marcus Breil, Felix Krawczyk, and Joaquim Pinto

Afforestation is an important mitigation strategy to climate change due to its carbon sequestration potential. Besides this positive biogeochemical effect on global CO2 concentrations, afforestation also affects the regional climate by changing the biogeophysical land surface characteristics. In this study, we investigate the effects of an idealized global CO2 reduction to pre-industrial conditions by a Europe-wide afforestation experiment on the regional longwave radiation balance, starting in the year 1986 from a continent entirely covered with grassland. Results show that the impact of biogeophysical processes on the surface temperatures is much stronger than of biogechemical processes. Furthermore, biogeophysically induced changes of the surface temperatures, atmospheric temperatures and moisture concentrations are as important for the regional greenhouse effect as the global CO2 reduction. While the greenhouse effect is strengthened in winter, it is weakened in summer. On annual total, a Europe-wide afforestation has a regional warming effect, despite reduced CO2 concentrations. Thus, even for an idealized reduction of the global CO2 concentrations to pre-industrial levels, the European climate response to afforestation would still be dominated by its biogeophysical effects.

How to cite: Breil, M., Krawczyk, F., and Pinto, J.: The response of the regional longwave radiation balance and climate system in Europe to an idealized afforestation experiment, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-7539, https://doi.org/10.5194/egusphere-egu23-7539, 2023.

A.277
|
EGU23-7863
|
BG3.17
|
ECS
Sabine Egerer, Stefanie Frank, and Julia Pongratz

The climate mitigation potential of terrestrial carbon dioxide removal (CDR) methods remains highly uncertain depending on the timing and magnitude of climate mitigation but also due to model uncertainty in the underlying Earth System models. In addition to these uncertainties, there are different approaches to measuring the effectiveness of CDR methods for climate change mitigation. In our study, we introduce various measures of effectiveness and evaluate the climate mitigation potential of afforestation and bioenergy plants under the low-emission scenario ssp126. To do this, we use the land component JSBACH3 of the Earth System Model MPI-ESM; afforestation is represented as the spatial increase of four forest plant functional types. Bioenergy plants are represented as highly efficient C4 plants (miscanthus and panicum). There are various assumptions concerning fossil fuel substitution and carbon capture and storage. Measuring effectiveness over time, we show how bioenergy plants become more effective over the long term compared to afforestation. In addition to this temporal measure, the climate mitigation potential of bioenergy plants depends significantly on the rate of fossil fuel substitution. Lastly, the spatial extent that is needed to match a given CDR amount in time by afforestation and BECCS can be quantified. Our study thus asses and compares the potentials of the two CDR methods highlighting the various perspectives of assessment.

How to cite: Egerer, S., Frank, S., and Pongratz, J.: Measures of effectiveness to compare the climate mitigation potential of afforestation and BECCS, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-7863, https://doi.org/10.5194/egusphere-egu23-7863, 2023.

A.278
|
EGU23-6863
|
BG3.17
Luca Caporaso, Matteo Piccardo, Emanuele Massaro, Gregory Duveiller, and Alessandro Cescatti

Forests can significantly influence local climate both by altering the carbon cycle (biogeochemical effects) and changing the surface energy budget (biophysical effects). Recent debates on the impacts of forestry and deforestation on the climate have focussed on trees' capacity to store carbon, but usually, the biogeophysical implications are not taken into account. In this study, we explore how regional-scale forestation and deforestation affect the Earth's energy balance, which in turn affect temperature and precipitation. We perform simulations where the vegetation cover is either increased or decreased while the carbon dioxide mixing ratio is kept constant, at a convection-permitting grid spacing of 5 km over the larger European domain using the regional climate model (RegCM4) coupled with CLM4.5. Over a time window of 11 years from 2004 to 2014, we study how the change in the forest cover affects the main atmospheric variables both at local level (local effects) and in the neighborhood (non-local effects). The need for a comprehensive understanding of how forests and climate impact each other is nowadays particularly relevant for Europe, and our analysis is one step forward in the direction of supporting the design of new policies and adaptation plans by pointing out the areas where afforestation efforts could mitigate the effects of climate change. This would improve the design of ambitious environmental policies like the European Green Deal project.

How to cite: Caporaso, L., Piccardo, M., Massaro, E., Duveiller, G., and Cescatti, A.: Adaptation strategies in Europe: the biophysical impact of forest cover change on climate simulated at high spatial resolution, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-6863, https://doi.org/10.5194/egusphere-egu23-6863, 2023.

A.279
|
EGU23-15474
|
BG3.17
Florian Wimmer, Etienne Tourigny, Isabel Martinez Cano, Benjamin Stuch, and Rüdiger Schaldach

The H2020 research project LANDMARC1 (Land Use Based Mitigation for Resilient Climate Pathways) will enhance understanding of the realistic potential of land-based negative emission solutions in agriculture, forestry, and other land use sectors. An important component of LANDMARC is modeling the effects of land-based mitigation technologies (LMT) on carbon fluxes and climate on the global scale.

We will present the development of a coupled modeling system consisting of the EC-Earth3-CC Earth System Model (ESM) and the LandSHIFT-G land use model. In this model system, LandSHIFT-G models sequences of land-use maps on a spatial resolution of 5 arc-minutes by integrating assumptions on the future development of the agricultural sector (e.g. crop/livestock production, changes in average crop yields) and assumptions on the implementation of a selection of LMTs as specified in global or regional scaling scenarios. Based on these land-use/land-cover changes (LULCC), EC-Earth3-CC simulates potential effects on vegetation (both natural and managed) and atmospheric CO2 concentrations and climate variables on a spatial resolution of approximately 70 km. Changes in potential crop yields due to climate change are fed back to the land-use model, potentially affecting subsequent land-use patterns. Carbon fluxes between the atmosphere, vegetation, and soils as well as crop yields are modeled by the dynamic vegetation model LPJ-GUESS, which is a component of EC-Earth3-CC. Hence, the system addresses three feedback loops between land-use, vegetation and climate. Land-use change is impacted by crop yields and pasture productivity. Carbon fluxes as well as crop yields and pasture productivity are impacted by land-use change and climate while climate is influenced by changes in atmospheric CO2 and land surface properties.

In the first version of the model system, it is foreseen to cover six different LMTs building on the capabilities of the models that are coupled. The set consists of (i) enhancement of carbon in vegetation and soils by afforestation, increasing soil carbon by (ii) no/reduced tillage agriculture and (iii) organic farming, combination of fossil fuel substitution and medium to long-term storage of carbon by (iv) BECCS (bio-energy and carbon capture and storage) and (v) application of biochar on cropland, as well as (vi) avoiding deforestation by  enhanced cropland irrigation.

In the current implementation, a simulation is done with a simplified modeling system, in which LandSHIFT-G is only coupled to LPJ-GUESS which is driven by atmospheric forcings from a previous EC-Earth3-CC model run, thus neglecting the dynamic effects under which the carbon cycle and land cover change impact the climate. As a proof of concept, we will present results of preliminary experiments simulating the effect of selected LMTs, e.g. afforestation, on the total carbon storage on land.

 

1 The LANDMARC project has received funding from the European Union’s Horizon 2020 Research and Innovation Programme under grant agreement No 869367.

How to cite: Wimmer, F., Tourigny, E., Martinez Cano, I., Stuch, B., and Schaldach, R.: Modeling the effect of land-based mitigation technologies on the carbon cycle and climate, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-15474, https://doi.org/10.5194/egusphere-egu23-15474, 2023.

A.280
|
EGU23-2749
|
BG3.17
|
ECS
|
Enting Tang, Yijian Zeng, Yunfei Wang, Zengjing Song, Danyang Yu, Hongyue Wu, Chenglong Qiao, Christiaan van der Tol, Lingtong Du, and Zhongbo Su

The revegetation practice is one of the most efficient ways to alleviate soil erosion and desertification. However, the land cover change can considerably disturb ecohydrological processes, particularly in arid and semiarid regions where ecosystems are fragile and suffer intense water stress. This study evaluated the effects of revegetation on the energy, water and carbon fluxes in a desert steppe in Yanchi County, Ningxia Province, Northwest China, by simulating two scenarios of shrubs-grassland and grassland ecosystem with the STEMMUS-SCOPE model. The STEMMUS-SCOPE model integrates canopy photosynthesis, fluorescence, energy balance model and soil water and heat transfer model in the soil-plant-atmosphere continuum system. The model was validated by field observations from May to September of 2016-2019, and showed good performances in simulating the energy, water and carbon fluxes. It indicated that the revegetation facilitated carbon fixation (+69.34%). Latent heat flux was the primary consumer of the available energy and was stronger in the shrubs-grassland ecosystem (+16.76%). With the remarkably increased transpiration of the shrubs-grassland ecosystem (+86.72%), revegetation intensified the soil water losses, especially the soil water content within the 0-200 cm depth (−18.97%). Moreover, the water consumption of the shrubs-grassland ecosystem tended to exceed the received precipitation over the growing seasons. These results emphasized the necessity of considering the adverse impacts of revegetation in future ecological restoration, especially the irreversible soil water depletion and imbalance of energy, water and carbon cycles.

How to cite: Tang, E., Zeng, Y., Wang, Y., Song, Z., Yu, D., Wu, H., Qiao, C., van der Tol, C., Du, L., and Su, Z.: Understanding the Effects of Revegetated Shrubs on Energy, Water and Carbon Fluxes in a Semiarid Steppe Ecosystem Using STEMMUS-SCOPE Model, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-2749, https://doi.org/10.5194/egusphere-egu23-2749, 2023.

A.281
|
EGU23-3159
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BG3.17
|
ECS
Jianyong Ma, Peter Anthoni, Stefan Olin, Sam Rabin, Anita Bayer, and Almut Arneth

Increasing crop productivity while keeping detrimental side-effects on the environment low is a major challenge for global agriculture. Cover crops (CCs), mostly grown during the fallow period and incorporated in soils, are expected to improve soil fertility and crop yields while reducing chemical fertilizer use, with climate change mitigation co-benefits. However, quantifying these ecosystem services across global agricultural lands remains uncertain. In this study we investigate how the use of herbaceous CCs with and without biological nitrogen (N) fixation affects yields and cropland carbon and nitrogen balances using the dynamic global vegetation model LPJ-GUESS. Model performance is evaluated against observations from field trials worldwide as well as other published model-based estimates. LPJ-GUESS generally captures the observed enhanced soil carbon, reduced N leaching, and yield changes caused by CCs. We found that the combination of N-fixing CCs with no-tillage management could potentially increase soil carbon storage by 7% (+0.32 Pg C yr-1 in global croplands) while reducing N leaching by 41% (-7.3 Tg N yr-1) compared with bare fallows after 36 years of simulation. This integrated practice is accompanied by a 2% increase in total crop production (+37 million tonnes yr-1 including wheat, maize, rice, and soybean) in the last decade of the simulation. Legume cover cropping is found to contribute more to increasing the subsequent crop yields than non-legumes. The effects of CCs on crop productivity are highly dependent on the main food crop types, chemical fertilizer use, and management duration, with smallest yield changes found in soybean systems and highly fertilized agricultural soils. Our results demonstrate the possibility of conservation agriculture when targeting long-term environmental sustainability without compromising crop production in global croplands.

How to cite: Ma, J., Anthoni, P., Olin, S., Rabin, S., Bayer, A., and Arneth, A.: Integrating cover crops with no-tillage benefits crop yields, increases soil carbon storage while reducing nitrogen leaching in global croplands, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-3159, https://doi.org/10.5194/egusphere-egu23-3159, 2023.

A.282
|
EGU23-14584
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BG3.17
|
ECS
Yi Yao, Kjetil Schanke Aas, Pedro Arboleda Obando, Mats Bentsen, Liang Chen, Benjamin Cook, Narayanappa Devaraju, Agnès Ducharne, Simon Gosling, Andrew Hartley, Jonas Jägermeyr, Colin Jones, Hyungjun Kim, David Lawrence, Peter Lawrence, Ruby Leung, Min-Hui Lo, and Sonali McDermid and the IRRMIP members

As the most dominant freshwater-use practice, irrigation plays an important role in global and regional environmental changes. Its extent experienced a substantial increase during the 20th century, from less than 100 mha before 1950 to about 300 mha around the year 2000. To advance the scientific understanding of the irrigation-expansion-induced impacts during the last century, we launched a model-intercomparison project (MIP), through which we intend to discover its effects on different sectors, i.e. water, climate, and agriculture, with Earth system models. In the protocol, two experiments are designed, i) simulation with transient irrigation extent and ii) simulation with the irrigation extent fixed at the level of the year 1901. For every experiment, three ensemble members are required to reduce the uncertainty. Currently, the analysis of outputs will be focused on climate extremes, the water cycle, vegetation-carbon interactions and some social implications. In the next phase of IRRMIP, we plan to combine the Earth system model community with both the hydrological model and crop model communities.

How to cite: Yao, Y., Aas, K. S., Arboleda Obando, P., Bentsen, M., Chen, L., Cook, B., Devaraju, N., Ducharne, A., Gosling, S., Hartley, A., Jägermeyr, J., Jones, C., Kim, H., Lawrence, D., Lawrence, P., Leung, R., Lo, M.-H., and McDermid, S. and the IRRMIP members: Irrigation-expansion-induced impacts model-intercomparison project (IRRMIP), EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-14584, https://doi.org/10.5194/egusphere-egu23-14584, 2023.

A.283
|
EGU23-4131
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BG3.17
|
ECS
Kyungil Lee and Seonyoung Park

In comparison to naturally developed cities, a new town is strategically built in a short period of time according to development plans. It is considered as an appropriate study area for analyzing the urban climate issues such as Local Climate Zone (LCZ) and Urban Heat Islands (UHIs) phenomenon that are differently generated according to urban planning and development. However, there are few research on comparative investigation of new towns based on urban planning due to several external variables such as environmental considerations and economic situations. In this study, we suggest comprehensive method for determining and comparing changes in LCZ distribution and UHI phenomenon in two new towns in South Korea  with different urban planning. The LCZ distribution for each new town was analyzed using Sentinel 1&2 imagery as the main material, and Convolutional Neural Networks (CNN) method, a one of the deep learning algorithms. In addition, the UHI phenomenon was analyzed using Landsat imagery and the constructed LCZ map. These results have the potential to improve knowledge of the thermal environmental implications of urbanization and give guidance for sustainable urban development and maintenance when combined with architectural evaluation models.

How to cite: Lee, K. and Park, S.: Analysis of changes in Local Climate Zone and Urban Heat Island phenomenon of new towns in South Korea according to urban planning, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-4131, https://doi.org/10.5194/egusphere-egu23-4131, 2023.

A.284
|
EGU23-3539
|
BG3.17
|
ECS
André Pinto da Silva, Filip Thörn, Anne-Kathleen Malchow, Damaris Zurell, and Juliano Cabral

Land use is the main direct driver of biodiversity loss and Southern-Asia is, globally, one of the regions under the highest land-use change. Here we estimate how mammals that play a key role in the ecosystem functioning will cope with landscape transformations. We used the a state-of-the-art spatially-explicit agent-based model (RangeShifter) combining local density-dependence on fecundity, stage-structured demographics and dispersal to predict the occupancy and abundance for large-body size carnivorous species (Panthera tigris, Panthera pardus) mid-sized and small carnivorous (Cuon alpinus, Felis chaus, Vulpes vulpes and Prionailurus bengalensis) and two Cetartiodactyla species (Sus scrofa and Gazella benetti) in Southern Asia. In addition, we estimated how species-richness changed through time. The model was projected to the period 1850 to 2100 under two socio-economic pathways, representing an intermediate scenario (SSP2-4.5) and a fossil-fueled development scenario (SSP5-8.5). We found mixed-response to land-use across species. We estimate the mean total proportion of remaining individuals to be 0.60 (SD = 0.24) under SSP2 and 0.64 (SD = 0.37) under SSP5 compared to baseline land use in 1850. The drop in the total number of occupied cells is of lower magnitude (SSP2: mean = 0.82, SD = 0.27; SSP5: mean = 0.84, SD = 0.32). Mean species richness per cell followed a decline throughout the 20th century (mean = 0.90, SD = 0.15) followed by increase from current time up to 2100 under both scenarios (SSP2: mean = 0.95, SD = 0.18; SSP5: mean = 0.97, SD = 0.22). Our results support biotic homogenization with spread of widespread species and restriction of forest-specialists. We confirm a disproportionate and negative influence of loss of non-disturbed patches, and lower landscape permeability in large mammals, potentially leading to considerable change in mammalian biomass in the ecosystem. These findings suggest that a middle-road socio-economic pathway (SSP2) is not enough to maintain or recover populations compared to pre-disturbance levels.

How to cite: Pinto da Silva, A., Thörn, F., Malchow, A.-K., Zurell, D., and Cabral, J.: Land-use following a middle-road socio-economic pathway (SSP2) is not enough to recover mammal populations in Southern-Asia, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-3539, https://doi.org/10.5194/egusphere-egu23-3539, 2023.

Posters virtual: Fri, 28 Apr, 08:30–10:15 | vHall BG

Chairpersons: Alan Di Vittorio, Thomas O'Halloran
vBG.6
|
EGU23-10587
|
BG3.17
Ermias Sisay Brhane and Koji Dairaku

Land use land cover (LULC) data are crucial for modeling a wide range of environmental conditions. So far, access to high-resolution LULC products at a global and regional scale for public use has been difficult, especially in developing countries/regions (Doelman et al., 2018). Land Use Land Cover (LULC) change simulation models are a powerful tool for analyzing the causes and effects of LULC dynamics under different scenarios. Scenario-based simulations of future land-use change can provide important information for evaluating the impacts of land strategies under different conditions. In this study, we project the future land use data at a 1-km resolution that comprises six land use types, adopting the newest integrated scenarios of the shared socioeconomic pathways and the representative concentration pathways (SSPs-RCPs) over Ethiopia. To generate this high-resolution land-use product, we use the FLUS model to simulate future land-use dynamics. The process of developing a future land dataset for Ethiopia can be divided into two parts. The first part is the estimation of the future area demands of different land use types under different SSP-RCP scenarios extracted from the LUH2 (Land-Use Harmonization 2) datasets which is available for free at http://luh.umd.edu/index.shtml. This dataset comprises a global projection of multiple land types for successive years from 2015 to 2100 under different SSP-RCP scenarios with a 0.25° resolution (approximately 25 km at the equator). The second part is conducting a 1-km spatial land simulation using the future land use simulation (FLUS) model under the macro constraints of the demands. In this sense, we select a series of relevant spatial driving factors, such as socioeconomic (GDP, population), distance factors (urban center, roads, and rivers), and natural factors (climate, topography, and soil quality). On this basis, a new set of land use projections, with a temporal resolution of 10 years and a spatial resolution of 1km, in eight SSP-RCP scenarios, comprising six land use types in Ethiopia is produced. This dataset shows good performance compared to remotely sensed ESA CCI-LC data. The results show that our land use simulation yields a satisfactory accuracy (Kappa = 0.8, OA = 0.9, and FoM = 0.1). Because of the advantages of the fine resolution, current scenarios, and multiple land types, our dataset provides powerful data support for environmental impact assessment and climate research, including but not limited to climate models.

How to cite: Brhane, E. S. and Dairaku, K.: Future Land Use Change projection under SSP-RCP scenarios over Ethiopia, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-10587, https://doi.org/10.5194/egusphere-egu23-10587, 2023.