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  • 1
    Online Resource
    Online Resource
    Copernicus GmbH ; 2022
    In:  Geoscientific Model Development Vol. 15, No. 17 ( 2022-09-06), p. 6709-6745
    In: Geoscientific Model Development, Copernicus GmbH, Vol. 15, No. 17 ( 2022-09-06), p. 6709-6745
    Abstract: Abstract. Land biosphere processes are of central importance to the climate system. Specifically, ecosystems interact with the atmosphere through a variety of feedback loops that modulate energy, water, and CO2 fluxes between the land surface and the atmosphere across a wide range of temporal and spatial scales. Human land use and land cover modification add a further level of complexity to land–atmosphere interactions. Dynamic global vegetation models (DGVMs) attempt to capture land ecosystem processes and are increasingly incorporated into Earth system models (ESMs), which makes it possible to study the coupled dynamics of the land biosphere and the climate. In this work we describe a number of modifications to the LPJ-GUESS DGVM, aimed at enabling direct integration into an ESM. These include energy balance closure, the introduction of a sub-daily time step, a new radiative transfer scheme, and improved soil physics. The implemented modifications allow the model (LPJ-GUESS/LSM) to simulate the diurnal exchange of energy, water, and CO2 between the land ecosystem and the atmosphere and thus provide surface boundary conditions to an atmospheric model over land. A site-based evaluation against FLUXNET2015 data shows reasonable agreement between observed and modelled sensible and latent heat fluxes. Differences in predicted ecosystem function between standard LPJ-GUESS and LPJ-GUESS/LSM vary across land cover types. We find that the emerging ecosystem composition and carbon fluxes are sensitive to both the choice of stomatal conductance model and the response of plant water uptake to soil moisture. The new implementation described in this work lays the foundation for using the well-established LPJ-GUESS DGVM as an alternative land surface model (LSM) in coupled land–biosphere–climate studies, where an accurate representation of ecosystem processes is essential.
    Type of Medium: Online Resource
    ISSN: 1991-9603
    Language: English
    Publisher: Copernicus GmbH
    Publication Date: 2022
    detail.hit.zdb_id: 2456725-5
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  • 2
    In: Biogeosciences, Copernicus GmbH, Vol. 19, No. 8 ( 2022-04-22), p. 2145-2169
    Abstract: Abstract. Improved agricultural management plays a vital role in protecting soils from degradation in eastern Africa. Changing practices such as reducing tillage, fertilizer use, or cover crops are expected to enhance soil organic carbon (SOC) storage, with climate change mitigation co-benefits, while increasing crop production. However, the quantification of cropland management effects on agricultural ecosystems remains inadequate in this region. Here, we explored seven management practices and their potential effects on soil carbon (C) pools, nitrogen (N) losses, and crop yields under different climate scenarios, using the dynamic vegetation model LPJ-GUESS. The model performance is evaluated against observations from two long-term maize field trials in western Kenya and reported estimates from published sources. LPJ-GUESS generally produces soil C stocks and maize productivity comparable with measurements and mostly captures the SOC decline under some management practices that is observed in the field experiments. We found that for large parts of Kenya and Ethiopia, an integrated conservation agriculture practice (no-tillage, residue and manure application, and cover crops) increases SOC levels in the long term (+11 % on average), accompanied by increased crop yields (+22 %) in comparison to the conventional management. Planting nitrogen-fixing cover crops in our simulations is also identified as a promising individual practice in eastern Africa to increase soil C storage (+4 %) and crop production (+18 %), with low environmental cost of N losses (+24 %). These management impacts are also sustained in simulations of three future climate pathways. This study highlights the possibilities of conservation agriculture when targeting long-term environmental sustainability and food security in crop ecosystems, particularly for those with poor soil conditions in tropical climates.
    Type of Medium: Online Resource
    ISSN: 1726-4189
    Language: English
    Publisher: Copernicus GmbH
    Publication Date: 2022
    detail.hit.zdb_id: 2158181-2
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  • 3
    In: Biogeosciences, Copernicus GmbH, Vol. 14, No. 21 ( 2017-11-03), p. 4829-4850
    Abstract: Abstract. Land management for carbon storage is discussed as being indispensable for climate change mitigation because of its large potential to remove carbon dioxide from the atmosphere, and to avoid further emissions from deforestation. However, the acceptance and feasibility of land-based mitigation projects depends on potential side effects on other important ecosystem functions and their services. Here, we use projections of future land use and land cover for different land-based mitigation options from two land-use models (IMAGE and MAgPIE) and evaluate their effects with a global dynamic vegetation model (LPJ-GUESS). In the land-use models, carbon removal was achieved either via growth of bioenergy crops combined with carbon capture and storage, via avoided deforestation and afforestation, or via a combination of both. We compare these scenarios to a reference scenario without land-based mitigation and analyse the LPJ-GUESS simulations with the aim of assessing synergies and trade-offs across a range of ecosystem service indicators: carbon storage, surface albedo, evapotranspiration, water runoff, crop production, nitrogen loss, and emissions of biogenic volatile organic compounds. In our mitigation simulations cumulative carbon storage by year 2099 ranged between 55 and 89 GtC. Other ecosystem service indicators were influenced heterogeneously both positively and negatively, with large variability across regions and land-use scenarios. Avoided deforestation and afforestation led to an increase in evapotranspiration and enhanced emissions of biogenic volatile organic compounds, and to a decrease in albedo, runoff, and nitrogen loss. Crop production could also decrease in the afforestation scenarios as a result of reduced crop area, especially for MAgPIE land-use patterns, if assumed increases in crop yields cannot be realized. Bioenergy-based climate change mitigation was projected to affect less area globally than in the forest expansion scenarios, and resulted in less pronounced changes in most ecosystem service indicators than forest-based mitigation, but included a possible decrease in nitrogen loss, crop production, and biogenic volatile organic compounds emissions.
    Type of Medium: Online Resource
    ISSN: 1726-4189
    Language: English
    Publisher: Copernicus GmbH
    Publication Date: 2017
    detail.hit.zdb_id: 2158181-2
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  • 4
    In: Global Change Biology, Wiley, Vol. 24, No. 7 ( 2018-07), p. 3025-3038
    Abstract: Most climate mitigation scenarios involve negative emissions, especially those that aim to limit global temperature increase to 2°C or less. However, the carbon uptake potential in land‐based climate change mitigation efforts is highly uncertain. Here, we address this uncertainty by using two land‐based mitigation scenarios from two land‐use models ( IMAGE and MA g PIE ) as input to four dynamic global vegetation models ( DGVM s; LPJ ‐ GUESS , ORCHIDEE , JULES , LPJ mL). Each of the four combinations of land‐use models and mitigation scenarios aimed for a cumulative carbon uptake of ~130 GtC by the end of the century, achieved either via the cultivation of bioenergy crops combined with carbon capture and storage ( BECCS ) or avoided deforestation and afforestation ( ADAFF ). Results suggest large uncertainty in simulated future land demand and carbon uptake rates, depending on the assumptions related to land use and land management in the models. Total cumulative carbon uptake in the DGVM s is highly variable across mitigation scenarios, ranging between 19 and 130 GtC by year 2099. Only one out of the 16 combinations of mitigation scenarios and DGVM s achieves an equivalent or higher carbon uptake than achieved in the land‐use models. The large differences in carbon uptake between the DGVM s and their discrepancy against the carbon uptake in IMAGE and MA g PIE are mainly due to different model assumptions regarding bioenergy crop yields and due to the simulation of soil carbon response to land‐use change. Differences between land‐use models and DGVM s regarding forest biomass and the rate of forest regrowth also have an impact, albeit smaller, on the results. Given the low confidence in simulated carbon uptake for a given land‐based mitigation scenario, and that negative emissions simulated by the DGVM s are typically lower than assumed in scenarios consistent with the 2°C target, relying on negative emissions to mitigate climate change is a highly uncertain strategy.
    Type of Medium: Online Resource
    ISSN: 1354-1013 , 1365-2486
    URL: Issue
    Language: English
    Publisher: Wiley
    Publication Date: 2018
    detail.hit.zdb_id: 2020313-5
    SSG: 12
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  • 5
    Online Resource
    Online Resource
    Copernicus GmbH ; 2022
    In:  Geoscientific Model Development Vol. 15, No. 2 ( 2022-01-28), p. 815-839
    In: Geoscientific Model Development, Copernicus GmbH, Vol. 15, No. 2 ( 2022-01-28), p. 815-839
    Abstract: Abstract. Biological nitrogen fixation (BNF) from grain legumes is of significant importance in global agricultural ecosystems. Crops with BNF capability are expected to support the need to increase food production while reducing nitrogen (N) fertilizer input for agricultural sustainability, but quantification of N fixing rates and BNF crop yields remains inadequate on a global scale. Here we incorporate two legume crops (soybean and faba bean) with BNF into a dynamic vegetation model LPJ-GUESS (Lund–Potsdam–Jena General Ecosystem Simulator). The performance of this new implementation is evaluated against observations from a range of water and N management trials. LPJ-GUESS generally captures the observed response to these management practices for legume biomass production, soil N uptake, and N fixation, despite some deviations from observations in some cases. Globally, simulated BNF is dominated by soil moisture and temperature, as well as N fertilizer addition. Annual inputs through BNF are modeled to be 11.6±2.2 Tg N for soybean and 5.6±1.0 Tg N for all pulses, with a total fixation of 17.2±2.9 Tg N yr−1 for all grain legumes during the period 1981–2016 on a global scale. Our estimates show good agreement with some previous statistical estimates but are relatively high compared to some estimates for pulses. This study highlights the importance of accounting for legume N fixation process when modeling C–N interactions in agricultural ecosystems, particularly when it comes to accounting for the combined effects of climate and land-use change on the global terrestrial N cycle.
    Type of Medium: Online Resource
    ISSN: 1991-9603
    Language: English
    Publisher: Copernicus GmbH
    Publication Date: 2022
    detail.hit.zdb_id: 2456725-5
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  • 6
    In: Geoscientific Model Development, Copernicus GmbH, Vol. 15, No. 16 ( 2022-08-30), p. 6495-6519
    Abstract: Abstract. Understanding uncertainties and sensitivities of projected ecosystem dynamics under environmental change is of immense value for research and climate change policy. Here, we analyze sensitivities (change in model outputs per unit change in inputs) and uncertainties (changes in model outputs scaled to uncertainty in inputs) of vegetation dynamics under climate change, projected by a state-of-the-art dynamic vegetation model (LPJ-GUESS v4.0) across European forests (the species Picea abies, Fagus sylvatica and Pinus sylvestris), considering uncertainties of both model parameters and environmental drivers. We find that projected forest carbon fluxes are most sensitive to photosynthesis-, water-, and mortality-related parameters, while predictive uncertainties are dominantly induced by environmental drivers and parameters related to water and mortality. The importance of environmental drivers for predictive uncertainty increases with increasing temperature. Moreover, most of the interactions of model inputs (environmental drivers and parameters) are between environmental drivers themselves or between parameters and environmental drivers. In conclusion, our study highlights the importance of environmental drivers not only as contributors to predictive uncertainty in their own right but also as modifiers of sensitivities and thus uncertainties in other ecosystem processes. Reducing uncertainty in mortality-related processes and accounting for environmental influence on processes should therefore be a focus in further model development.
    Type of Medium: Online Resource
    ISSN: 1991-9603
    Language: English
    Publisher: Copernicus GmbH
    Publication Date: 2022
    detail.hit.zdb_id: 2456725-5
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  • 7
    In: Earth's Future, American Geophysical Union (AGU), Vol. 11, No. 5 ( 2023-05)
    Abstract: Cover crops (CCs) can increase soil carbon sequestration by 0.11–0.15 Pg C per year while reducing N leaching by 34%–41% in global croplands compared with fallow management The influence of CCs on cash crop yields varies widely among crop rotations, climates, management duration, and N fertilizer applications Legume CCs in no‐tillage system is overall identified as a promising practice to achieve environmental sustainability without compromising crop production in agricultural ecosystems
    Type of Medium: Online Resource
    ISSN: 2328-4277 , 2328-4277
    Language: English
    Publisher: American Geophysical Union (AGU)
    Publication Date: 2023
    detail.hit.zdb_id: 2746403-9
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