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- ItemLandInG 1.0: a toolbox to derive input datasets for terrestrial ecosystem modelling at variable resolutions from heterogeneous sources(Katlenburg-Lindau : Copernicus, 2023) Ostberg, Sebastian; Müller, Christoph; Heinke, Jens; Schaphoff, SibyllWe present the Land Input Generator (LandInG) version 1.0, a new toolbox for generating input datasets for terrestrial ecosystem models (TEMs) from diverse and partially conflicting data sources. While LandInG 1.0 is applicable to process data for any TEM, it is developed specifically for the open-source dynamic global vegetation, hydrology, and crop growth model LPJmL (Lund-Potsdam-Jena with managed Land). The toolbox documents the sources and processing of data to model inputs and allows for easy changes to the spatial resolution. It is designed to make inconsistencies between different sources of data transparent so that users can make their own decisions on how to resolve these should they not be content with the default assumptions made here. As an example, we use the toolbox to create input datasets at 5 and 30 arcmin spatial resolution covering land, country, and region masks, soil, river networks, freshwater reservoirs, irrigation water distribution networks, crop-specific annual land use, fertilizer, and manure application. We focus on the toolbox describing the data processing rather than only publishing the datasets as users may want to make different choices for reconciling inconsistencies, aggregation, spatial extent, or similar. Also, new data sources or new versions of existing data become available continuously, and the toolbox approach allows for incorporating new data to stay up to date.
- ItemGenerating a rule-based global gridded tillage dataset(Katlenburg-Lindau : Copernics Publications, 2020) Porwollik, Vera; Rolinski, Susanne; Heinke, Jens; Müller, ChristophTillage is a central element in agricultural soil management and has direct and indirect effects on processes in the biosphere. Effects of agricultural soil management can be assessed by soil, crop, and ecosystem models, but global assessments are hampered by lack of information on the type of tillage and their spatial distribution. This study describes the generation of a classification of tillage practices and presents the spatially explicit mapping of these crop-specific tillage systems for around the year 2005. Tillage practices differ by the kind of equipment used, soil surface and depth affected, timing, and their purpose within the cropping systems. We classified the broad variety of globally relevant tillage practices into six categories: no-tillage in the context of Conservation Agriculture, traditional annual, traditional rotational, rotational, reduced, and conventional annual tillage. The identified tillage systems were allocated to gridded crop-specific cropland areas with a resolution of 5 arcmin. Allocation rules were based on literature findings and combine area information on crop type, water management regime, field size, water erosion, income, and aridity. We scaled reported national Conservation Agriculture areas down to grid cells via a probability-based approach for 54 countries. We provide area estimates of the six tillage systems aggregated to global and country scale. We found that 8.67Mkm2 of global cropland area was tilled intensively at least once a year, whereas the remaining 2.65Mkm2 was tilled less intensely. Further, we identified 4.67Mkm2 of cropland as an area where Conservation Agriculture could be expanded to under current conditions. The tillage classification enables the parameterization of different soil management practices in various kinds of model simulations. The crop-specific tillage dataset indicates the spatial distribution of soil management practices, which is a prerequisite to assess erosion, carbon sequestration potential, as well as water, and nutrient dynamics of cropland soils. The dynamic definition of the allocation rules and accounting for national statistics, such as the share of Conservation Agriculture per country, also allow for derivation of datasets for historical and future global soil management scenarios. The resulting tillage system dataset and source code are accessible via an open-data repository (DOIs: https://doi.org/10.5880/PIK.2019.009 and https://doi.org/10.5880/PIK.2019.010, Porwollik et al., 2019a, b). © Author(s) 2019.
- ItemWater Use in Global Livestock Production—Opportunities and Constraints for Increasing Water Productivity([New York] : Wiley, 2020) Heinke, Jens; Lannerstad, Mats; Gerten, Dieter; HavlÃk, Petr; Herrero, Mario; Notenbaert, An Maria Omer; Hoff, Holger; Müller, ChristophIncreasing population, change in consumption habits, and climate change will likely increase the competition for freshwater resources in the future. Exploring ways to improve water productivity especially in food and livestock systems is important for tackling the future water challenge. Here we combine detailed data on feed use and livestock production with Food and Agriculture Organization of the United Nations (FAO) statistics and process-based crop-water model simulations to comprehensively assess water use and water productivity in the global livestock sector. We estimate that, annually, 4,387 km3 of blue and green water is used for the production of livestock feed, equaling about 41% of total agricultural water use. Livestock water productivity (LWP; protein produced per m3 of water) differs by several orders of magnitude between livestock types, regions, and production systems, indicating a large potential for improvements. For pigs and broilers, we identify large opportunities to increase LWP by increasing both feed water productivity (FWP; feed produced per m3 of water) and feed use efficiency (FUE; protein produced per kg of feed) through better crop and livestock management. Even larger opportunities to increase FUE exist for ruminants, while the overall potential to increase their FWP is low. Substantial improvements of FUE can be achieved for ruminants by supplementation with feed crops, but the lower FWP of these feed crops compared to grazed biomass limits possible overall improvements of LWP. Therefore, LWP of ruminants, unlike for pigs and poultry, does not always benefit from a trend toward intensification, as this is often accompanied by increasing crop supplementation.
- ItemManagement-induced changes in soil organic carbon on global croplands(Katlenburg-Lindau [u.a.] : Copernicus, 2022) Karstens, Kristine; Bodirsky, Benjamin Leon; Dietrich, Jan Philipp; Dondini, Marta; Heinke, Jens; Kuhnert, Matthias; Müller, Christoph; Rolinski, Susanne; Smith, Pete; Weindl, Isabelle; Lotze-Campen, Hermann; Popp, AlexanderSoil organic carbon (SOC), one of the largest terrestrial carbon (C) stocks on Earth, has been depleted by anthropogenic land cover change and agricultural management. However, the latter has so far not been well represented in global C stock assessments. While SOC models often simulate detailed biochemical processes that lead to the accumulation and decay of SOC, the management decisions driving these biophysical processes are still little investigated at the global scale. Here we develop a spatially explicit data set for agricultural management on cropland, considering crop production levels, residue returning rates, manure application, and the adoption of irrigation and tillage practices. We combine it with a reduced-complexity model based on the Intergovernmental Panel on Climate Change (IPCC) tier 2 method to create a half-degree resolution data set of SOC stocks and SOC stock changes for the first 30 cm of mineral soils. We estimate that, due to arable farming, soils have lost around 34.6 GtC relative to a counterfactual hypothetical natural state in 1975. Within the period 1975-2010, this SOC debt continued to expand by 5 GtC (0.14 GtCyr-1) to around 39.6 GtC. However, accounting for historical management led to 2.1 GtC fewer (0.06 GtCyr-1) emissions than under the assumption of constant management. We also find that management decisions have influenced the historical SOC trajectory most strongly by residue returning, indicating that SOC enhancement by biomass retention may be a promising negative emissions technique. The reduced-complexity SOC model may allow us to simulate management-induced SOC enhancement - also within computationally demanding integrated (land use) assessment modeling.
- ItemUnderstanding 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, KirstenThe 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.
- ItemModelling 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, ChristophTo 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.
- ItemVariable tree rooting strategies are key for modelling the distribution, productivity and evapotranspiration of tropical evergreen forests(Katlenburg-Lindau : European Geosciences Union, 2021) Sakschewski, Boris; Bloh, Werner von; Drüke, Markus; Sörensson, Anna Amelia; Ruscica, Romina; Langerwisch, Fanny; Billing, Maik; Bereswill, Sarah; Hirota, Marina; Oliveira, Rafael Silva; Heinke, Jens; Thonicke, KirstenA variety of modelling studies have suggested tree rooting depth as a key variable to explain evapotranspiration rates, productivity and the geographical distribution of evergreen forests in tropical South America. However, none of those studies have acknowledged resource investment, timing and physical constraints of tree rooting depth within a competitive environment, undermining the ecological realism of their results. Here, we present an approach of implementing variable rooting strategies and dynamic root growth into the LPJmL4.0 (Lund-Potsdam-Jena managed Land) dynamic global vegetation model (DGVM) and apply it to tropical and sub-tropical South America under contemporary climate conditions. We show how competing rooting strategies which underlie the trade-off between above- and below-ground carbon investment lead to more realistic simulation of intra-annual productivity and evapotranspiration and consequently of forest cover and spatial biomass distribution. We find that climate and soil depth determine a spatially heterogeneous pattern of mean rooting depth and below-ground biomass across the study region. Our findings support the hypothesis that the ability of evergreen trees to adjust their rooting systems to seasonally dry climates is crucial to explaining the current dominance, productivity and evapotranspiration of evergreen forests in tropical South America.