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- ItemModeling forest plantations for carbon uptake with the LPJmL dynamic global vegetation model(Göttingen : Copernicus Publ., 2019) Braakhekke, Maarten C.; Doelman, Jonathan C.; Baas, Peter; Müller, Christoph; Schaphoff, Sibyll; Stehfest, Elke; van Vuuren, Detlef P.We present an extension of the dynamic global vegetation model, Lund-Potsdam-Jena Managed Land (LPJmL), to simulate planted forests intended for carbon (C) sequestration. We implemented three functional types to simulate plantation trees in temperate, tropical, and boreal climates. The parameters of these functional types were optimized to fit target growth curves (TGCs). These curves represent the evolution of stemwood C over time in typical productive plantations and were derived by combining field observations and LPJmL estimates for equivalent natural forests. While the calibrated model underestimates stemwood C growth rates compared to the TGCs, it represents substantial improvement over using natural forests to represent afforestation. Based on a simulation experiment in which we compared global natural forest versus global forest plantation, we found that forest plantations allow for much larger C uptake rates on the timescale of 100 years, with a maximum difference of a factor of 1.9, around 54 years. In subsequent simulations for an ambitious but realistic scenario in which 650Mha (14% of global managed land, 4.5% of global land surface) are converted to forest over 85 years, we found that natural forests take up 37PgC versus 48PgC for forest plantations. Comparing these results to estimations of C sequestration required to achieve the 2°C climate target, we conclude that afforestation can offer a substantial contribution to climate mitigation. Full evaluation of afforestation as a climate change mitigation strategy requires an integrated assessment which considers all relevant aspects, including costs, biodiversity, and trade-offs with other land-use types. Our extended version of LPJmL can contribute to such an assessment by providing improved estimates of C uptake rates by forest plantations. © 2019 American Institute of Physics Inc.. All rights reserved.
- ItemMulti-model climate impact assessment and intercomparison for three large-scale river basins on three continents(München : European Geopyhsical Union, 2015) Vetter, T.; Huang, S.; Aich, V.; Yang, T.; Wang, X.; Krysanova, V.; Hattermann, F.Climate change impacts on hydrological processes should be simulated for river basins using validated models and multiple climate scenarios in order to provide reliable results for stakeholders. In the last 10–15 years, climate impact assessment has been performed for many river basins worldwide using different climate scenarios and models. However, their results are hardly comparable, and do not allow one to create a full picture of impacts and uncertainties. Therefore, a systematic intercomparison of impacts is suggested, which should be done for representative regions using state-of-the-art models. Only a few such studies have been available until now with the global-scale hydrological models, and our study is intended as a step in this direction by applying the regional-scale models. The impact assessment presented here was performed for three river basins on three continents: the Rhine in Europe, the Upper Niger in Africa and the Upper Yellow in Asia. For that, climate scenarios from five general circulation models (GCMs) and three hydrological models, HBV, SWIM and VIC, were used. Four representative concentration pathways (RCPs) covering a range of emissions and land-use change projections were included. The objectives were to analyze and compare climate impacts on future river discharge and to evaluate uncertainties from different sources. The results allow one to draw some robust conclusions, but uncertainties are large and shared differently between sources in the studied basins. Robust results in terms of trend direction and slope and changes in seasonal dynamics could be found for the Rhine basin regardless of which hydrological model or forcing GCM is used. For the Niger River, scenarios from climate models are the largest uncertainty source, providing large discrepancies in precipitation, and therefore clear projections are difficult to do. For the Upper Yellow basin, both the hydrological models and climate models contribute to uncertainty in the impacts, though an increase in high flows in the future is a robust outcome ensured by all three hydrological models.
- ItemA framework for the cross-sectoral integration of multi-model impact projections: Land use decisions under climate impacts uncertainties(München : European Geopyhsical Union, 2015) Frieler, K.; Levermann, A.; Elliott, J.; Heinke, J.; Arneth, A.; Bierkens, M.F.P.; Ciais, P.; Clark, D.B.; Deryng, D.; Döll, P.; Falloon, P.; Fekete, B.; Folberth, C.; Friend, A.D.; Gellhorn, C.; Gosling, S.N.; Haddeland, I.; Khabarov, N.; Lomas, M.; Masaki, Y.; Nishina, K.; Neumann, K.; Oki, T.; Pavlick, R.; Ruane, A.C.; Schmid, E.; Schmitz, C.; Stacke, T.; Stehfest, E.; Tang, Q.; Wisser, D.; Huber, V.; Piontek, F.; Warszawski, L.; Schewe, J.; Lotze-Campen, H.; Schellnhuber, H.J.Climate change and its impacts already pose considerable challenges for societies that will further increase with global warming (IPCC, 2014a, b). Uncertainties of the climatic response to greenhouse gas emissions include the potential passing of large-scale tipping points (e.g. Lenton et al., 2008; Levermann et al., 2012; Schellnhuber, 2010) and changes in extreme meteorological events (Field et al., 2012) with complex impacts on societies (Hallegatte et al., 2013). Thus climate change mitigation is considered a necessary societal response for avoiding uncontrollable impacts (Conference of the Parties, 2010). On the other hand, large-scale climate change mitigation itself implies fundamental changes in, for example, the global energy system. The associated challenges come on top of others that derive from equally important ethical imperatives like the fulfilment of increasing food demand that may draw on the same resources. For example, ensuring food security for a growing population may require an expansion of cropland, thereby reducing natural carbon sinks or the area available for bio-energy production. So far, available studies addressing this problem have relied on individual impact models, ignoring uncertainty in crop model and biome model projections. Here, we propose a probabilistic decision framework that allows for an evaluation of agricultural management and mitigation options in a multi-impact-model setting. Based on simulations generated within the Inter-Sectoral Impact Model Intercomparison Project (ISI-MIP), we outline how cross-sectorally consistent multi-model impact simulations could be used to generate the information required for robust decision making. Using an illustrative future land use pattern, we discuss the trade-off between potential gains in crop production and associated losses in natural carbon sinks in the new multiple crop- and biome-model setting. In addition, crop and water model simulations are combined to explore irrigation increases as one possible measure of agricultural intensification that could limit the expansion of cropland required in response to climate change and growing food demand. This example shows that current impact model uncertainties pose an important challenge to long-term mitigation planning and must not be ignored in long-term strategic decision making.
- ItemTowards representing human behavior and decision making in Earth system models - An overview of techniques and approaches(München : European Geopyhsical Union, 2017) Müller-Hansen, Finn; Schlüter, Maja; Mäs, Michael; Donges, Jonathan F.; Kolb, Jakob J.; Thonicke, Kirsten; Heitzig, JobstToday, humans have a critical impact on the Earth system and vice versa, which can generate complex feedback processes between social and ecological dynamics. Integrating human behavior into formal Earth system models (ESMs), however, requires crucial modeling assumptions about actors and their goals, behavioral options, and decision rules, as well as modeling decisions regarding human social interactions and the aggregation of individuals' behavior. Here, we review existing modeling approaches and techniques from various disciplines and schools of thought dealing with human behavior at different levels of decision making. We demonstrate modelers' often vast degrees of freedom but also seek to make modelers aware of the often crucial consequences of seemingly innocent modeling assumptions. After discussing which socioeconomic units are potentially important for ESMs, we compare models of individual decision making that correspond to alternative behavioral theories and that make diverse modeling assumptions about individuals' preferences, beliefs, decision rules, and foresight. We review approaches to model social interaction, covering game theoretic frameworks, models of social influence, and network models. Finally, we discuss approaches to studying how the behavior of individuals, groups, and organizations can aggregate to complex collective phenomena, discussing agent-based, statistical, and representative-agent modeling and economic macro-dynamics. We illustrate the main ingredients of modeling techniques with examples from land-use dynamics as one of the main drivers of environmental change bridging local to global scales.
- ItemModelling mineral dust in the Central Asian region(Les Ulis : EDP Sciences, 2019) Heinold, Bernd; Tegen, InaIn Central Asia, climate and air quality are largely affected by local and long-travelled mineral dust. For the last century, the area has experienced severe land-use changes and water exploitation producing new dust sources. Today global warming causes rapid shrinking of mountain glaciers with yet unknow consequences for dust and its climate effects. Despite the importance for a growing population, only little is known about sources, transport pathways and properties of Central Asian dust. A transport study with a global aerosol-climate model is undertaken to investigate the life cycle of mineral dust in Central Asia for the period of a remote-sensing campaign in Tajikistan in 2015-2016. An initial evaluation with sun photometer measurements shows reasonable agreement for the average amount of dust, but a significant weakness of the model in reproducing the seasonality of local dust with maximum activity in summer. Source apportionment reveals a major contribution from Arabia throughout the year in accordance with observations. In the model, local sources mainly contribute in spring and autumn while summer-time dust production is underestimated. The results underline the importance of considering long-range transport and, locally, a detailed representation of atmospheric dynamics and surface characteristics for modelling dust in Central Asia. © 2019 The Authors, published by EDP Sciences.
- ItemGlobal and country-level data of the biodiversity footprints of 175 crops and pasture(Amsterdam [u.a.] : Elsevier, 2021) Beyer, Robert; Manica, AndreaThe destruction of natural habitat for cropland and pasture represents a major threat to global biodiversity. Despite widespread societal concern about biodiversity loss associated with food production, consumer access to quantitative estimates of the impact of crop production on the world's species has been very limited compared to assessments of other environmental variables such as greenhouse gas emissions or water use. Here, we present a consistent dataset of the biodiversity footprints of pasture and 175 crops at the global and national level. The data were generated by combining maps of the global distribution of agricultural areas in the year 2000 with spatially explicit estimates of the biodiversity loss associated with the conversion of natural habitat to farmland. Estimates were derived for three common alternative measures of biodiversity - species richness, threatened species richness, and range rarity - of the world's mammals, birds, and amphibians. Our dataset provides important quantitative information for food consumers and policy makers, allowing them to take evidence-based decisions to reduce the biodiversity footprint of global food production.
- ItemDeforestation in Amazonia impacts riverine carbon dynamics(München : European Geopyhsical Union, 2016) Langerwisch, Fanny; Walz, Ariane; Rammig, Anja; Tietjen, Britta; Thonicke, Kirsten; Cramer, WolfgangFluxes of organic and inorganic carbon within the Amazon basin are considerably controlled by annual flooding, which triggers the export of terrigenous organic material to the river and ultimately to the Atlantic Ocean. The amount of carbon imported to the river and the further conversion, transport and export of it depend on temperature, atmospheric CO2, terrestrial productivity and carbon storage, as well as discharge. Both terrestrial productivity and discharge are influenced by climate and land use change. The coupled LPJmL and RivCM model system (Langerwisch et al., 2016) has been applied to assess the combined impacts of climate and land use change on the Amazon riverine carbon dynamics. Vegetation dynamics (in LPJmL) as well as export and conversion of terrigenous carbon to and within the river (RivCM) are included. The model system has been applied for the years 1901 to 2099 under two deforestation scenarios and with climate forcing of three SRES emission scenarios, each for five climate models. We find that high deforestation (business-as-usual scenario) will strongly decrease (locally by up to 90%) riverine particulate and dissolved organic carbon amount until the end of the current century. At the same time, increase in discharge leaves net carbon transport during the first decades of the century roughly unchanged only if a sufficient area is still forested. After 2050 the amount of transported carbon will decrease drastically. In contrast to that, increased temperature and atmospheric CO2 concentration determine the amount of riverine inorganic carbon stored in the Amazon basin. Higher atmospheric CO2 concentrations increase riverine inorganic carbon amount by up to 20% (SRES A2). The changes in riverine carbon fluxes have direct effects on carbon export, either to the atmosphere via outgassing or to the Atlantic Ocean via discharge. The outgassed carbon will increase slightly in the Amazon basin, but can be regionally reduced by up to 60% due to deforestation. The discharge of organic carbon to the ocean will be reduced by about 40% under the most severe deforestation and climate change scenario. These changes would have local and regional consequences on the carbon balance and habitat characteristics in the Amazon basin itself as well as in the adjacent Atlantic Ocean.
- ItemThe mutual dependence of negative emission technologies and energy systems(Cambridge : RSC Publ., 2019) Creutzig, Felix; Breyer, Christian; Hilaire, Jérôme; Minx, Jan; Peters, Glen P.; Socolow, RobertWhile a rapid decommissioning of fossil fuel technologies deserves priority, most climate stabilization scenarios suggest that negative emission technologies (NETs) are required to keep global warming well below 2 °C. Yet, current discussions on NETs are lacking a distinct energy perspective. Prominent NETs, such as bioenergy with carbon capture and storage (BECCS) and direct air carbon capture and storage (DACCS), will integrate differently into the future energy system, requiring a concerted research effort to determine adequate means of deployment. In this perspective, we discuss the importance of energy per carbon metrics, factors of future cost development, and the dynamic response of NETs in intermittent energy systems. The energy implications of NETs deployed at scale are massive, and NETs may conceivably impact future energy systems substantially. DACCS outperform BECCS in terms of primary energy required per ton of carbon sequestered. For different assumptions, DACCS displays a sequestration efficiency of 75–100%, whereas BECCS displays a sequestration efficiency of 50–90% or less if indirect land use change is included. Carbon dioxide removal costs of DACCS are considerably higher than BECCS, but if DACCS modularity and granularity helps to foster technological learning to <100$ per tCO2, DACCS may remove CO2 at gigaton scale. DACCS also requires two magnitudes less land than BECCS. Designing NET systems that match intermittent renewable energies will be key for stringent climate change mitigation. Our results contribute to an emerging understanding of NETs that is notably different to that derived from scenario modelling.
- ItemThe LEGATO cross-disciplinary integrated ecosystem service research framework: an example of integrating research results from the analysis of global change impacts and the social, cultural and economic system dynamics of irrigated rice production(Heidelberg : Springer Verlag, 2017) Spangenberg, J.H.; Beaurepaire, A.L.; Bergmeier, E.; Burkhard, B.; van Chien, H.; Cuong, L.Q.; Görg, C.; Grescho, V.; Hai, L.H.; Heong, K.L.; Horgan, F.G.; Hotes, S.; Klotzbücher, A.; Klotzbücher, T.; Kühn, I.; Langerwisch, F.; Marion, G.; Moritz, R.F.A.; Nguyen, Q.A.; Ott, J.; Sann, C.; Sattler, C.; Schädler, M.; Schmidt, A.; Tekken, V.; Thanh, T.D.; Thonicke, K.; Türke, M.; VáclavÃk, T.; Vetterlein, D.; Westphal, C.; Wiemers, M.; Settele, J.In a cross-disciplinary project (LEGATO) combining inter- and transdisciplinary methods, we quantify the dependency of rice-dominated socio-ecological systems on ecosystem functions (ESF) and the ecosystem services (ESS) the integrated system provides. In the collaboration of a large team including geo- and bioscientists, economists, political and cultural scientists, the mutual influences of the biological, climate and soil conditions of the agricultural area and its surrounding natural landscape have been analysed. One focus was on sociocultural and economic backgrounds, another on local as well as regional land use intensity and biodiversity, and the potential impacts of future climate and land use change. LEGATO analysed characteristic elements of three service strands defined by the Millennium Ecosystem Assessment (MA): (a) provisioning services: nutrient cycling and crop production; (b) regulating services: biocontrol and pollination; and (c) cultural services: cultural identity and aesthetics. However, in line with much of the current ESS literature, what the MA called supporting services is treated as ESF within LEGATO. As a core output, LEGATO developed generally applicable principles of ecological engineering (EE), suitable for application in the context of future climate and land use change. EE is an emerging discipline, concerned with the design, monitoring and construction of ecosystems and aims at developing strategies to optimise ecosystem services through exploiting natural regulation mechanisms instead of suppressing them. Along these lines LEGATO also aims to create the knowledge base for decision-making for sustainable land management and livelihoods, including the provision of the corresponding governance and management strategies, technologies and system solutions.
- ItemBio-IGCC with CCS as a long-term mitigation option in a coupled energy-system and land-use model(Amsterdam [u.a.] : Elsevier, 2011) Klein, D.; Bauer, N.; Bodirsky, B.; Dietrich, J.P.; Popp, A.This study analyses the impact of techno-economic performance of the BIGCC process and the effect of different biomass feedstocks on the technology's long term deployment in climate change mitigation scenarios. As the BIGCC technology demands high amounts of biomass raw material it also affects the land-use sector and is dependent on conditions and constraints on the land-use side. To represent the interaction of biomass demand and supply side the global energy-economy-climate model ReMIND is linked to the global land-use model MAgPIE. The link integrates biomass demand and price as well as emission prices and land-use emissions. Results indicate that BIGCC with CCS could serve as an important mitigation option and that it could even be the main bioenergy conversion technology sharing 33% of overall mitigation in 2100. The contribution of BIGCC technology to long-term climate change mitigation is much higher if grass is used as fuel instead of wood, provided that the grass-based process is highly efficient. The capture rate has to significantly exceed 60 % otherwise the technology is not applied. The overall primary energy consumption of biomass reacts much more sensitive to price changes of the biomass than to technoeconomic performance of the BIGCC process. As biomass is mainly used with CCS technologies high amounts of carbon are captured ranging from 130 GtC to 240 GtC (cumulated from 2005-2100) in different scenarios.