24 research outputs found
PrĂ€ventionslĂŒcken in NRW schlieĂen: Beratungsarbeit gegen rechtsextremistische Radikalisierung strukturell und finanziell unterstĂŒtzen
Die Zunahme rechtextremistisch motivierter Straftaten in polizeilichen Kriminalstatistiken schlĂ€gt sich in den konkreten, alltĂ€glichen Erfahrungen der Beratungsstellen gegen Rechtsextremismus nieder. Beraterinnen und Berater können die hohe Nachfrage nach UnterstĂŒtzung kaum bewĂ€ltigen. Das Land Nordrhein-Westfalen (NRW) muss fĂŒr die Beratungsarbeit im Problemfeld Rechtsextremismus zusĂ€tzliche personelle und materielle KapazitĂ€ten zur VerfĂŒgung stellen. Wichtig ist hierbei, Regelstrukturen den Vorrang zu geben, statt auf zeitlich befristete Projekte zu setzen. Menschen, die sich am Anfang eines Hinwendungsprozesses zu rechtsextremen Ideologien und/oder Szenestrukturen befinden, stehen bisher nicht im Fokus der PrĂ€ventionsarbeit in NRW. Gerade in dieser frĂŒhen Phase stehen die Chancen jedoch mutmaĂlich gut, einer Radikalisierung erfolgreich entgegenwirken zu können. Das Land sollte zusĂ€tzliche finanzielle Mittel bereitstellen, um eine intensive und beratende Fallarbeit mit radikalisierungsgefĂ€hrdeten Personen zu ermöglichen. Beratungsstellen sollten auf das Problemfeld Rechtsextremismus konzentriert, lokal verankert und vernetzt sein. Das Land sowie die Kreise und kreisfreien StĂ€dte in NRW haben zu prĂŒfen, welche bestehenden Strukturen eine Grundlage fĂŒr den Aufbau einer solchen fallbezogenen PrĂ€ventionsarbeit bieten können. Dabei können sie ggf. aus den Erfahrungen mit lokalen Beratungsstellen in der Arbeit gegen Islamismus lernen
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Simulating the effect of tillage practices with the global ecosystem model LPJmL (version 5.0-tillage)
The effects of tillage on soil properties, crop productivity, and global greenhouse gas emissions have been discussed in the last decades. Global ecosystem models have limited capacity to simulate the various effects of tillage. With respect to the decomposition of soil organic matter, they either assume a constant increase due to tillage or they ignore the effects of tillage. Hence, they do not allow for analysing the effects of tillage and cannot evaluate, for example, reduced tillage or no tillage (referred to here as âno-tillâ) practises as mitigation practices for climate change. In this paper, we describe the implementation of tillage-related practices in the global ecosystem model LPJmL. The extended model is evaluated against reported differences between tillage and no-till management on several soil properties. To this end, simulation results are compared with published meta-analyses on tillage effects. In general, the model is able to reproduce observed tillage effects on global, as well as regional, patterns of carbon and water fluxes. However, modelled N fluxes deviate from the literature values and need further study. The addition of the tillage module to LPJmL5 opens up opportunities to assess the impact of agricultural soil management practices under different scenarios with implications for agricultural productivity, carbon sequestration, greenhouse gas emissions, and other environmental indicators
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The importance of management information and soil moisture representation for simulating tillage effects on N2O emissions in LPJmL5.0-tillage
No-tillage is often suggested as a strategy to reduce greenhouse gas emissions. Modeling tillage effects on nitrous oxide (N2O) emissions is challenging and subject to great uncertainties as the processes producing the emissions are complex and strongly nonlinear. Previous findings have shown deviations between the LPJmL5.0-tillage model (LPJmL: LundâPotsdamâJena managed Land) and results from meta-analysis on global estimates of tillage effects on N2O emissions. Here we tested LPJmL5.0-tillage at four different experimental sites across Europe and the USA to verify whether deviations in N2O emissions under different tillage regimes result from a lack of detailed information on agricultural management, the representation of soil water dynamics or both. Model results were compared to observational data and outputs from field-scale DayCent model simulations. DayCent has been successfully applied for the simulation of N2O emissions and provides a richer database for comparison than noncontinuous measurements at experimental sites. We found that adding information on agricultural management improved the simulation of tillage effects on N2O emissions in LPJmL. We also found that LPJmL overestimated N2O emissions and the effects of no-tillage on N2O emissions, whereas DayCent tended to underestimate the emissions of no-tillage treatments. LPJmL showed a general bias to overestimate soil moisture content. Modifications of hydraulic properties in LPJmL in order to match properties assumed in DayCent, as well as of the parameters related to residue cover, improved the overall simulation of soil water and N2O emissions simulated under tillage and no-tillage separately. However, the effects of no-tillage (shifting from tillage to no-tillage) did not improve. Advancing the current state of information on agricultural management and improvements in soil moisture highlights the potential to improve LPJmL5.0-tillage and global estimates of tillage effects on N2O emissions
Management-induced changes in soil organic carbon on global croplands
Soil 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 30âcm of mineral soils. We estimate that, due to arable farming, soils have lost around 34.6âGtC relative to a counterfactual hypothetical natural state in 1975. Within the period 1975â2010, this SOC debt continued to expand by 5âGtC (0.14âGtCâyrâ1) to around 39.6âGtC. However, accounting for historical management led to 2.1âGtC fewer (0.06âGtCâyrâ1) 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 â also within computationally demanding integrated (land use) assessment modeling.</p
Management-induced changes in soil organic carbon on global croplands
Funding Information: The work of Kristine Karstens has been funded by the DFG Priority Program âClimate Engineering: Risks, Challenges, Opportunities?â (SPP 1689), specifically the CEMICS2 project (grant no. ED78/3-2), and by the CDRSynTra project (grant no. 01LS2101G) funded by the German Federal Ministry of Education and Research (BMBF). The research leading to these results has received funding for Benjamin Leon Bodirsky from the European Union's Horizon 2020 Research And Innovation Programme (grant nos. 776479 (COACCH) and 821010 (CASCADES)). Benjamin Leon Bodirsky acknowledges support by the project ABCDR (grant no. 01LS2105A) funded by the BMBF. The work of Susanne Rolinski, Jens Heinke, and Isabelle Weindl has also been supported by CLIMASTEPPE (grant no. 01DJ8012), EXIMO (grant no. 01LP1903D), and FOCUS (grant no. 031B0787B), all funded by the BMBF. The input of Pete Smith, Matthias Kuhnert, and Marta Dondini contributes to the Soils-R-GGREAT project (grant no. NE/P019455/1) and CIRCASA (EU H2020; grant no. 774378). Publisher Copyright: Copyright © 2022 Kristine Karstens et al.Peer reviewedPublisher PD
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Management-induced changes in soil organic carbon on global croplands
Soil 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
Die Internationalisierung der deutschen Hochschule im Zeichen virtueller Lehr- und Lernszenarien
Der Einsatz von offenen und kostenlosen Onlinekursen, "Massive Open Online Courses" (MOOCs) wird seit einiger Zeit an Hochschulen diskutiert. Ob MOOCs die Internationalisierung der Hochschulen befördern können, hat eine Arbeitsgruppe des DAAD thematisiert. Der Band informiert ĂŒber AnfĂ€nge, Status Quo, Auswirkungen und das Internationalisierungspotenzial der virtuellen Lehr-/Lernszenarien und stellt die Ergebnisse und Schlussfolgerungen der Projektgruppe vor.Third level education institutes have been discussing the implementation of open access, free online study courses, aka "Massive Open Online Courses" (MOOCs) for quite some time. A work group of the DAAD looked at whether MOOCs could additionally promote the internationalisation of third level education institutes. The volume offers information about the starting points, status quo, effects and the internationalisation potential of virtual teaching/learning scenarios and presents the findings and conclusions of the project group
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Modelling the role of livestock grazing in C and N cycling in grasslands with LPJmL5.0-grazing
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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Generating a rule-based global gridded tillage dataset
Tillage 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