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Sich ändernde Klima- und Wetterbedingungen in Verbindung mit einer begrenzt ausdehnbaren Ackerfläche werden den Druck auf Nahrungsmittelproduktionssysteme weiter erhöhen. Um dieser Herausforderung gerecht zu werden, ist eine Erhöhung und Stabilisierung der Ernteerträge unverzichtbar. Dies erfordert aber ein tieferes Verständnis der Einflussfaktoren, die auf die Ertragsvariabilität wirken. Diese Dissertation leistet einen Forschungsbeitrag zu Ertragsmodellen in Deutschland, Tansania und auf globaler Ebene. Dazu analysiere und kombiniere ich statistische und prozessbasierte Ertragsmodelle in fünf Schritten: (i) Zunächst entwickele ich einen statistischen Modellansatz, um den Einfluss von Wetter und agronomischem Management auf Winterweizenerträge in Deutschland zu separieren. (ii) Auf der Grundlage dieses Modells erweitere ich die statistischen Methoden und wende sie für Winterweizen und Silomais auf regionale Ebene an. (iii) Diesen erweiterten Modellansatz verwende ich daraufhin zum Testen einer Kreuz-Validierung um zukünftige Ertragsänderungen unter Klimawandel zu projizieren. (iv) Anschließend wird in einer globalen statistischen Anwendung dieses Modell für kurzfristige Ertragsprognosen getestet. (v) Schließlich kombiniere ich für das Fallbeispiel Mais in Tansania statistische und prozessbasierte Ertragsmodelle, um wetterbedingte Ertragsverluste von nicht-wetterbedingten Ertragsverlusten zu separieren. Als Ergebnis lässt sich zusammenfassen, dass der Anteil der wetterbedingten Ertragsvariabilität in Deutschland höher ist als in Tansania. Dementsprechend sind die Ertragsschwankungen in Tansania eher auf das agronomische Management und sozioökonomische Einflüsse zurückzuführen. Für beide Länder stelle ich fest, dass der Anteil der wetterbedingte Ertragsvariabilität auf aggregierter Ebene höher ist als auf regionaler Ebene. Der kombinierte statistisch-prozessbasierte Ansatz zur Bewertung von wetterbedingten Ertragsverlusten kann für Versicherungszwecke genutzt werden., Due to changing climate and weather patterns in combination with limitations to extend global arable land area, the pressure on food production systems will increase. To cope with this challenge, it will be indispensable to increase and stabilize crop yields. This requires, however, a deeper understanding of the factors influencing crop yield variability. This dissertation contributes to that research need as I further develop and apply crop models to assess regional wheat and maize yield variability in Germany, Tanzania and on a global scale. For this, I analyze and combine statistical and process-based crop models within five steps: (i) First, I develop a statistical crop modeling approach to decompose the influence of weather and agronomic management on winter wheat yields in Germany. (ii) Based on the first step, I expand the statistical methods and apply augmented models for winter wheat and silage maize on a disaggregated level. (iii) Then this model approach is used to investigate an out-of-sample cross validation to demonstrate the models’ capability to project future yield changes under climate change. (iv) In a global statistical application, this models’ capability of projecting yields is tested for short-term yield forecasts. (v) Finally, I combine statistical and process-based crop modeling to decompose weather-related maize yield losses from losses caused by non-weather factors for the case of Tanzania. Across these five steps, I find that the share of weather-related yield variability is higher in Germany than in Tanzania. Accordingly, crop yield variability in Tanzania is to a higher share attributable to agronomic management and socio-economic influences. For both countries, I find that the share of explained weather-related yield variability is higher on an aggregated level than on the regional level. Finally, this combined statistical-process-based approach can be used for assessing weather-related crop yield losses for insurance purposes.

Quantifying the economic effects of climate change is a crucial step for planning adaptation in developing countries. This study assesses the economy-wide and regional effects of climate change-induced productivity and labor supply shocks in Ethiopian agriculture. We pursue a structural approach that blends biophysical and economic models. We consider different crop yield projections and add a regionalization to the country-wide CGE results. The study shows, in the worst case scenario, the effects on country-wide GDP may add up to −8%. The effects on regional value-added GDP are uneven and range from −10% to +2.5%. However, plausible cost-free exogenous structural change scenarios in labor skills and marketing margins may offset about 20–30% of these general equilibrium effects. As such, the ongoing structural transformation in the country may underpin the resilience of the economy to climate change. This can be regarded as a co-benefit of structural change in the country. Nevertheless, given the role of the sector in the current economic structure and the potency of the projected biophysical impacts, adaptation in agriculture is imperative. Otherwise, climate change may make rural livelihoods unpredictable and strain the country’s economic progress., Peer Reviewed

Systematic model inter-comparison helps to narrow discrepancies in the analysis of the future impact of climate change on agricultural production. This paper presents a set of alternative scenarios by five global climate and agro-economic models. Covering integrated assessment (IMAGE), partial equilibrium (CAPRI, GLOBIOM, MAgPIE) and computable general equilibrium (MAGNET) models ensures a good coverage of biophysical and economic agricultural features. These models are harmonized with respect to basic model drivers, to assess the range of potential impacts of climate change on the agricultural sector by 2050. Moreover, they quantify the economic consequences of stringent global emission mitigation efforts, such as non-CO2 emission taxes and land-based mitigation options, to stabilize global warming at 2 °C by the end of the century under different Shared Socioeconomic Pathways. A key contribution of the paper is a vis-à-vis comparison of climate change impacts relative to the impact of mitigation measures. In addition, our scenario design allows assessing the impact of the residual climate change on the mitigation challenge. From a global perspective, the impact of climate change on agricultural production by mid-century is negative but small. A larger negative effect on agricultural production, most pronounced for ruminant meat production, is observed when emission mitigation measures compliant with a 2 °C target are put in place. Our results indicate that a mitigation strategy that embeds residual climate change effects (RCP2.6) has a negative impact on global agricultural production relative to a no-mitigation strategy with stronger climate impacts (RCP6.0). However, this is partially due to the limited impact of the climate change scenarios by 2050. The magnitude of price changes is different amongst models due to methodological differences. Further research to achieve a better harmonization is needed, especially regarding endogenous food and feed demand, inclu

In Paris, France, December 2015, the Conference of the Parties (COP) to the United Nations Framework Convention on Climate Change (UNFCCC) invited the Intergovernmental Panel on Climate Change (IPCC) to provide a "special report in 2018 on the impacts of global warming of 1.5°C above pre-industrial levels and related global greenhouse gas emission pathways". In Nairobi, Kenya, April 2016, the IPCC panel accepted the invitation. Here we describe the response devised within the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP) to provide tailored, cross-sectorally consistent impact projections to broaden the scientific basis for the report. The simulation protocol is designed to allow for (1) separation of the impacts of historical warming starting from pre-industrial conditions from impacts of other drivers such as historical land-use changes (based on pre-industrial and historical impact model simulations); (2) quantification of the impacts of additional warming up to 1.5°C, including a potential overshoot and long-term impacts up to 2299, and comparison to higher levels of global mean temperature change (based on the low-emissions Representative Concentration Pathway RCP2.6 and a no-mitigation pathway RCP6.0) with socio-economic conditions fixed at 2005 levels; and (3) assessment of the climate effects based on the same climate scenarios while accounting for simultaneous changes in socio-economic conditions following the middle-of-the-road Shared Socioeconomic Pathway (SSP2, Fricko et al., 2016) and in particular differential bioenergy requirements associated with the transformation of the energy system to comply with RCP2.6 compared to RCP6.0. With the aim of providing the scientific basis for an aggregation of impacts across sectors and analysis of cross-sectoral interactions that may dampen or amplify sectoral impacts, the protocol is designed to facilitate consistent impact projections from a range of impact models across different sectors (global an

PR, CRP2; ISI; IFPRI3; CRP7; 1 Fostering Climate-Resilient and Sustainable Food Supply; Global Futures and Strategic Foresight, EPTD; PIM, 5 pages, CGIAR Research Program on Policies, Institutions, and Markets (PIM); CGIAR Research Program on Climate Change, Agriculture and Food Security (CCAFS)

This paper presents the overview of the Shared Socioeconomic Pathways (SSPs) and their energy, land use, and emissions implications. The SSPs are part of a new scenario framework, established by the climate change research community in order to facilitate the integrated analysis of future climate impacts, vulnerabilities, adaptation, and mitigation. The pathways were developed over the last years as a joint community effort and describe plausible major global developments that together would lead in the future to different challenges for mitigation and adaptation to climate change. The SSPs are based on five narratives describing alternative socio-economic developments, including sustainable development, regional rivalry, inequality, fossil-fueled development, and middle-of-the-road development. The long-term demographic and economic projections of the SSPs depict a wide uncertainty range consistent with the scenario literature. A multi-model approach was used for the elaboration of the energy, land-use and the emissions trajectories of SSP-based scenarios. The baseline scenarios lead to global energy consumption of 400–1200 EJ in 2100, and feature vastly different land-use dynamics, ranging from a possible reduction in cropland area up to a massive expansion by more than 700 million hectares by 2100. The associated annual CO2 emissions of the baseline scenarios range from about 25 GtCO2 to more than 120 GtCO2 per year by 2100. With respect to mitigation, we find that associated costs strongly depend on three factors: (1) the policy assumptions, (2) the socio-economic narrative, and (3) the stringency of the target. The carbon price for reaching the target of 2.6 W/m2 that is consistent with a temperature change limit of 2 °C, differs in our analysis thus by about a factor of three across the SSP marker scenarios. Moreover, many models could not reach this target from the SSPs with high mitigation challenges. While the SSPs were designed to represent differ

In the future, the land system will be facing new intersecting challenges. While food demand, especially for resource-intensive livestock based commodities, is expected to increase, the terrestrial system has large potentials for climate change mitigation through improved agricultural management, providing biomass for bioenergy, and conserving or even enhancing carbon stocks of ecosystems. However, uncertainties in future socio-economic land use drivers may result in very different land-use dynamics and consequences for land-based ecosystem services. This is the first study with a systematic interpretation of the Shared Socio-Economic Pathways (SSPs) in terms of possible land-use changes and their consequences for the agricultural system, food provision and prices as well as greenhouse gas emissions. Therefore, five alternative Integrated Assessment Models with distinctive land-use modules have been used for the translation of the SSP narratives into quantitative projections. The model results reflect the general storylines of the SSPs and indicate a broad range of potential land-use futures with global agricultural land of 4900 mio ha in 2005 decreasing by 810 mio ha until 2100 at the lower (SSP1) and increasing by 1080 mio ha (SSP3) at the upper end. Greenhouse gas emissions from land use and land use change, as a direct outcome of these diverse land-use dynamics, and agricultural production systems differ strongly across SSPs (e.g. cumulative land use change emissions between 2005 and 2100 range from −54 to 402 Gt CO2). The inclusion of land-based mitigation efforts, particularly those in the most ambitious mitigation scenarios, further broadens the range of potential land futures and can strongly affect greenhouse gas dynamics and food prices. In general, it can be concluded that low demand for agricultural commodities, rapid growth in agricultural productivity and globalized trade, all most pronounced in a SSP1 world, have the potential to enhance the

This paper presents a set of energy and resource intensive scenarios based on the concept of Shared Socio-Economic Pathways (SSPs). The scenario family is characterized by rapid and fossil-fueled development with high socio-economic challenges to mitigation and low socio-economic challenges to adaptation (SSP5). A special focus is placed on the SSP5 marker scenario developed by the REMIND-MAgPIE integrated assessment modeling framework. The SSP5 baseline scenarios exhibit very high levels of fossil fuel use, up to a doubling of global food demand, and up to a tripling of energy demand and greenhouse gas emissions over the course of the century, marking the upper end of the scenario literature in several dimensions. These scenarios are currently the only SSP scenarios that result in a radiative forcing pathway as high as the highest Representative Concentration Pathway (RCP8.5). This paper further investigates the direct impact of mitigation policies on the SSP5 energy, land and emissions dynamics confirming high socio-economic challenges to mitigation in SSP5. Nonetheless, mitigation policies reaching climate forcing levels as low as in the lowest Representative Concentration Pathway (RCP2.6) are accessible in SSP5. The SSP5 scenarios presented in this paper aim to provide useful reference points for future climate change, climate impact, adaption and mitigation analysis, and broader questions of sustainable development.

Ethiopia is one of the most vulnerable countries to climate change. This is because its important economic sector, agriculture, is virtually rain-fed. The role of the sector in the current economic structure and the potency of the anticipated biophysical impacts of climate change necessitates proactive adaptation in agriculture. This, however, breeds questions of adaptation costs and adaptation finance. This study attempts to derive plausible range of planned adaptation costs in agriculture along with their economy-wide and regional effects in Ethiopia. It also assess the economy-wide and regional effects of the likely options available to a government of a least-developed country to finance adaptation in agriculture. The results show that planned public adaptation in agriculture puts pressure on government surplus, impedes on manufacturing and private services, and GDP of urbanized regions. As such, it may strain the current macroeconomic endeavors of the country which puts government driven structural transformation and reducing fiscal deficit relative to GDP at the center. Government of Ethiopia may reconcile this by laying out incentives to urban agriculture and private investment in agriculture. Besides, foreign support in the form of biotechnology transfer and debt-relief may help to control the side effects of grants on foreign exchange market and trade balance.

Energie und Rohstoffe auf Basis von Biomasse gelten als wichtiger Beitrag, um den anthropogen begründeten Klimawandel zu mindern. Diese publikationsbasierte Arbeit analysiert, inwiefern Aussagen über Vorzüglichkeit von Biomassenutzung im direkten Vergleich oder auch in komplexeren wirtschaftlichen Nutzungssystemen durch Unsicherheiten in den Treibhausgasemissionen (THG) oder durch die Anwendung der Bewertungsmethodik beeinflusst werden. Eine Fallstudie zur stationären Biostromerzeugung aus der Vergasung von Pappelhackschnitzeln zeigte mittels Monte-Carlo-Analyse, dass dieser Biostrom trotz Unsicherheiten weniger THG emittiert bzw. sogar Kohlendioxid sequestrieren könnte. Die zweite Fallstudie analysierte Biomassenutzung im Systemzusammenhang. Sie bezog neben THG-Emissionen als Bewertungskriterien sowohl den Bedarf an Agrarfläche als auch an fossilen Ressourcen mit ein. Für das Beispiel der Häuserdämmung mittels Hanffasern oder Styropor konnte aus den drei Kriterien auch unter Berücksichtigung mehrerer Szenarien keine eindeutige Vorzugslösung der Biomassenutzung abgeleitet werden. Basierend auf dem Produktivitätskonzept stellt der dritte Beitrag mit CUDe (Carbon Utilization Degree) einen Ansatz vor, wie die Nutzungseffizienz des in der Biomasse bereitgestellten Kohlenstoffs bewertet werden könnte. THG-Minderungsrechnungen erfordern eine fundierte Kenntnis der Methode als auch des Produktionssystems in seinem regionalen Kontext. Als Landnutzungseffekte sollten neben Änderungen im Bodenkohlenstoffgehalt auch Unterschiede in Lachgas-Hintergrundemissionen von annuellen gegenüber mehrjährigen Kulturen berücksichtigt werden. Trade-Offs sprechen dafür, Biomassenutzungssysteme nicht nur hinsichtlich Klimawirksamkeit zu optimieren. Ergänzend könnte Kohlenstoff auch als Ressource betrachtet und mit Effizienzkriterien bewertet werden. Biomassenutzung ließe sich so optimieren, dass gemeinsam mit Klimaschutz weitere aktuelle Handlungsfelder adressiert werden., Biomass-based energy and materials are considered important for the mitigation of human-induced climate change and as relevant bioeconomic feedstock. This publication-based dissertation aims to contribute to the discussion about the reliability of mitigation assessment of biomass applications in an increasingly bio-based, low-carbon economy that also fulfils sustainability constraints of resource conservation. It analysed how preference of biomass use in direct comparison as well as in larger economic context is affected by single uncertainties as well as by mitigation calculation methods. A case study on stationary bioelectricity generation from poplar wood chip gasification with a Monte Carlo approach showed that such bioelectricity could emit less greenhouse gases (GHG) or even sequester carbon despite existing uncertainties. The second case study analysed biomass use in a systemic context. Besides GHG emissions also resource demand of cropland and fossil fuels were used to assess two strategies to isolate buildings. From the three criteria, none of the strategies would clearly be preferred. The third case study presented an approach to assess the efficiency of biomass carbon use (CUDe; Carbon Utilization Degree) and applied it exemplarily to a biogas and a hemp insulation system. GHG mitigation analyses of biomass use must be performed with profound knowledge of the methodology and the biomass system in its regional context. In land use change assessment, emissions resulting from deviating nitrous oxide baselines from annual and perennial crops should be considered in addition to carbon stock changes. Optimization of biomass applications only with respect to GHG emissions (or other single criteria) might overlook trade-offs. However, multi-criteria analyses might yield ambiguous results. A resource-efficient viewpoint on biogenic carbon use instead of its sole GHG implications might help to foster a transformation to bio-based, low-carbon economies.

In Paris, France, December 2015, the Conference of the Parties (COP) to the United Nations Framework Convention on Climate Change (UNFCCC) invited the Intergovernmental Panel on Climate Change (IPCC) to provide a special report in 2018 on the impacts of global warming of 1.5 °C above pre-industrial levels and related global greenhouse gas emission pathways. In Nairobi, Kenya, April 2016, the IPCC panel accepted the invitation. Here we describe the response devised within the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP) to provide tailored, cross-sectorally consistent impact projections to broaden the scientific basis for the report. The simulation protocol is designed to allow for (1) separation of the impacts of historical warming starting from pre-industrial conditions from impacts of other drivers such as historical land-use changes (based on pre-industrial and historical impact model simulations); (2) quantification of the impacts of additional warming up to 1.5 °C , including a potential overshoot and long-term impacts up to 2299, and comparison to higher levels of global mean temperature change (based on the low-emissions Representative Concentration Pathway RCP2.6 and a no-mitigation pathway RCP6.0) with socio-economic conditions fixed at 2005 levels; and (3) assessment of the climate effects based on the same climate scenarios while accounting for simultaneous changes in socio-economic conditions following the middle-of-the-road Shared Socioeconomic Pathway (SSP2, Fricko et al., 2016) and in particular differential bioenergy requirements associated with the transformation of the energy system to comply with RCP2.6 compared to RCP6.0. With the aim of providing the scientific basis for an aggregation of impacts across sectors and analysis of cross-sectoral interactions that may dampen or amplify sectoral impacts, the protocol is designed to facilitate consistent impact projections from a range of impact models across diff, Physical and Space Geodesy

In Paris, France, December 2015, the Conference of the Parties (COP) to the United Nations Framework Convention on Climate Change (UNFCCC) invited the Intergovernmental Panel on Climate Change (IPCC) to provide a special report in 2018 on the impacts of global warming of 1.5ĝ€°C above pre-industrial levels and related global greenhouse gas emission pathways. In Nairobi, Kenya, April 2016, the IPCC panel accepted the invitation. Here we describe the response devised within the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP) to provide tailored, cross-sectorally consistent impact projections to broaden the scientific basis for the report. The simulation protocol is designed to allow for (1) separation of the impacts of historical warming starting from pre-industrial conditions from impacts of other drivers such as historical land-use changes (based on pre-industrial and historical impact model simulations); (2) quantification of the impacts of additional warming up to 1.5ĝ€°C, including a potential overshoot and long-term impacts up to 2299, and comparison to higher levels of global mean temperature change (based on the low-emissions Representative Concentration Pathway RCP2.6 and a no-mitigation pathway RCP6.0) with socio-economic conditions fixed at 2005 levels; and (3) assessment of the climate effects based on the same climate scenarios while accounting for simultaneous changes in socio-economic conditions following the middle-of-the-road Shared Socioeconomic Pathway (SSP2, Fricko et al., 2016) and in particular differential bioenergy requirements associated with the transformation of the energy system to comply with RCP2.6 compared to RCP6.0. With the aim of providing the scientific basis for an aggregation of impacts across sectors and analysis of cross-sectoral interactions that may dampen or amplify sectoral impacts, the protocol is designed to facilitate consistent impact projections from a range of impact models across different sectors (global

This paper presents the overview of the Shared Socioeconomic Pathways (SSPs) and their energy, land use, and emissions implications. The SSPs are part of a new scenario framework, established by the climate change research community in order to facilitate the integrated analysis of future climate impacts, vulnerabilities, adaptation, and mitigation. The pathways were developed over the last years as a joint community effort and describe plausible major global developments that together would lead in the future to different challenges for mitigation and adaptation to climate change. The SSPs are based on five narratives describing alternative socio-economic developments, including sustainable development, regional rivalry, inequality, fossil-fueled development, and middle-of-the-road development. The long-term demographic and economic projections of the SSPs depict a wide uncertainty range consistent with the scenario literature. A multi-model approach was used for the elaboration of the energy, land-use and the emissions trajectories of SSP-based scenarios. The baseline scenarios lead to global energy consumption of 400–1200 EJ in 2100, and feature vastly different land-use dynamics, ranging from a possible reduction in cropland area up to a massive expansion by more than 700 million hectares by 2100. The associated annual CO2 emissions of the baseline scenarios range from about 25 GtCO2 to more than 120 GtCO2 per year by 2100. With respect to mitigation, we find that associated costs strongly depend on three factors: (1) the policy assumptions, (2) the socio-economic narrative, and (3) the stringency of the target. The carbon price for reaching the target of 2.6 W/m2 that is consistent with a temperature change limit of 2 °C, differs in our analysis thus by about a factor of three across the SSP marker scenarios. Moreover, many models could not reach this target from the SSPs with high mitigation challenges. While the SSPs were designed to represent different mitig