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    Understanding the uncertainty in global forest carbon turnover
    (Katlenburg-Lindau [u.a.] : Copernicus, 2020) Pugh, Thomas A.M.; Rademacher, Tim; Shafer, Sarah L.; Steinkamp, Jörg; Barichivich, Jonathan; Beckage, Brian; Haverd, Vanessa; Harper, Anna; Heinke, Jens; Nishina, Kazuya; Rammig, Anja; Sato, Hisashi; Arneth, Almut; Hantson, Stijn; Hickler, Thomas; Kautz, Markus; Quesada, Benjamin; Smith, Benjamin; Thonicke, Kirsten
    The length of time that carbon remains in forest biomass is one of the largest uncertainties in the global carbon cycle, with both recent historical baselines and future responses to environmental change poorly constrained by available observations. In the absence of large-scale observations, models used for global assessments tend to fall back on simplified assumptions of the turnover rates of biomass and soil carbon pools. In this study, the biomass carbon turnover times calculated by an ensemble of contemporary terrestrial biosphere models (TBMs) are analysed to assess their current capability to accurately estimate biomass carbon turnover times in forests and how these times are anticipated to change in the future. Modelled baseline 1985-2014 global average forest biomass turnover times vary from 12.2 to 23.5 years between TBMs. TBM differences in phenological processes, which control allocation to, and turnover rate of, leaves and fine roots, are as important as tree mortality with regard to explaining the variation in total turnover among TBMs. The different governing mechanisms exhibited by each TBM result in a wide range of plausible turnover time projections for the end of the century. Based on these simulations, it is not possible to draw robust conclusions regarding likely future changes in turnover time, and thus biomass change, for different regions. Both spatial and temporal uncertainty in turnover time are strongly linked to model assumptions concerning plant functional type distributions and their controls. Thirteen model-based hypotheses of controls on turnover time are identified, along with recommendations for pragmatic steps to test them using existing and novel observations. Efforts to resolve uncertainty in turnover time, and thus its impacts on the future evolution of biomass carbon stocks across the world's forests, will need to address both mortality and establishment components of forest demography, as well as allocation of carbon to woody versus non-woody biomass growth. © 2020 SPIE. All rights reserved.
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    Modelling the role of livestock grazing in C and N cycling in grasslands with LPJmL5.0-grazing
    (Katlenburg-Lindau : Copernicus, 2023) Heinke, Jens; Rolinski, Susanne; Müller, Christoph
    To represent the impact of grazing livestock on carbon (C) and nitrogen (N) dynamics in grasslands, we implement a livestock module into LPJmL5.0-tillage, a global vegetation and crop model with explicit representation of managed grasslands and pastures, forming LPJmL5.0-grazing. The livestock module uses lactating dairy cows as a generic representation of grazing livestock. The new module explicitly accounts for forage quality in terms of dry-matter intake and digestibility using relationships derived from compositional analyses for different forages. Partitioning of N into milk, feces, and urine as simulated by the new livestock module shows very good agreement with observation-based relationships reported in the literature. Modelled C and N dynamics depend on forage quality (C:N ratios in grazed biomass), forage quantity, livestock densities, manure or fertilizer inputs, soil, atmospheric CO2 concentrations, and climate conditions. Due to the many interacting relationships, C sequestration, GHG emissions, N losses, and livestock productivity show substantial variation in space and across livestock densities. The improved LPJmL5.0-grazing model can now assess the effects of livestock grazing on C and N stocks and fluxes in grasslands. It can also provide insights about the spatio-temporal variability of grassland productivity and about the trade-offs between livestock production and environmental impacts.
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    The Earth system model CLIMBER-X v1.0 - Part 2: The global carbon cycle
    (Katlenburg-Lindau : Copernicus, 2023) Willeit, Matteo; Ilyina, Tatiana; Liu, Bo; Heinze, Christoph; Perrette, Mahé; Heinemann, Malte; Dalmonech, Daniela; Brovkin, Victor; Munhoven, Guy; Börker, Janine; Hartmann, Jens; Romero-Mujalli, Gibran; Ganopolski, Andrey
    The carbon cycle component of the newly developed Earth system model of intermediate complexity CLIMBER-X is presented. The model represents the cycling of carbon through the atmosphere, vegetation, soils, seawater and marine sediments. Exchanges of carbon with geological reservoirs occur through sediment burial, rock weathering and volcanic degassing. The state-of-the-art HAMOCC6 model is employed to simulate ocean biogeochemistry and marine sediment processes. The land model PALADYN simulates the processes related to vegetation and soil carbon dynamics, including permafrost and peatlands. The dust cycle in the model allows for an interactive determination of the input of the micro-nutrient iron into the ocean. A rock weathering scheme is implemented in the model, with the weathering rate depending on lithology, runoff and soil temperature. CLIMBER-X includes a simple representation of the methane cycle, with explicitly modelled natural emissions from land and the assumption of a constant residence time of CH4 in the atmosphere. Carbon isotopes 13C and 14C are tracked through all model compartments and provide a useful diagnostic for model-data comparison. A comprehensive evaluation of the model performance for the present day and the historical period shows that CLIMBER-X is capable of realistically reproducing the historical evolution of atmospheric CO2 and CH4 but also the spatial distribution of carbon on land and the 3D structure of biogeochemical ocean tracers. The analysis of model performance is complemented by an assessment of carbon cycle feedbacks and model sensitivities compared to state-of-the-art Coupled Model Intercomparison Project Phase 6 (CMIP6) models. Enabling an interactive carbon cycle in CLIMBER-X results in a relatively minor slow-down of model computational performance by ∼ 20 % compared to a throughput of ∼ 10 000 simulation years per day on a single node with 16 CPUs on a high-performance computer in a climate-only model set-up. CLIMBER-X is therefore well suited to investigating the feedbacks between climate and the carbon cycle on temporal scales ranging from decades to >100000 years.