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- ItemA probabilistic risk assessment for the vulnerability of the European carbon cycle to weather extremes: The ecosystem perspective(München : European Geopyhsical Union, 2015) Rolinski, S.; Rammig, A.; Walz, A.; von Bloh, W.; van Oijen, M.; Thonicke, K.Extreme weather events are likely to occur more often under climate change and the resulting effects on ecosystems could lead to a further acceleration of climate change. But not all extreme weather events lead to extreme ecosystem response. Here, we focus on hazardous ecosystem behaviour and identify coinciding weather conditions. We use a simple probabilistic risk assessment based on time series of ecosystem behaviour and climate conditions. Given the risk assessment terminology, vulnerability and risk for the previously defined hazard are estimated on the basis of observed hazardous ecosystem behaviour. We apply this approach to extreme responses of terrestrial ecosystems to drought, defining the hazard as a negative net biome productivity over a 12-month period. We show an application for two selected sites using data for 1981–2010 and then apply the method to the pan-European scale for the same period, based on numerical modelling results (LPJmL for ecosystem behaviour; ERA-Interim data for climate). Our site-specific results demonstrate the applicability of the proposed method, using the SPEI to describe the climate condition. The site in Spain provides an example of vulnerability to drought because the expected value of the SPEI is 0.4 lower for hazardous than for non-hazardous ecosystem behaviour. In northern Germany, on the contrary, the site is not vulnerable to drought because the SPEI expectation values imply wetter conditions in the hazard case than in the non-hazard case. At the pan-European scale, ecosystem vulnerability to drought is calculated in the Mediterranean and temperate region, whereas Scandinavian ecosystems are vulnerable under conditions without water shortages. These first model-based applications indicate the conceptual advantages of the proposed method by focusing on the identification of critical weather conditions for which we observe hazardous ecosystem behaviour in the analysed data set. Application of the method to empirical time series and to future climate would be important next steps to test the approach.
- ItemConsistent negative response of US crops to high temperatures in observations and crop models(London : Nature Publishing Group, 2017) Schauberger, B.; Archontoulis, S.; Arneth, A.; Balkovic, J.; Ciais, P.; Deryng, D.; Elliott, J.; Folberth, C.; Khabarov, N.; Müller, C.; Pugh, T.A.M.; Rolinski, S.; Schaphoff, S.; Schmid, E.; Wang, X.; Schlenker, W.; Frieler, K.High temperatures are detrimental to crop yields and could lead to global warming-driven reductions in agricultural productivity. To assess future threats, the majority of studies used process-based crop models, but their ability to represent effects of high temperature has been questioned. Here we show that an ensemble of nine crop models reproduces the observed average temperature responses of US maize, soybean and wheat yields. Each day >30 °C diminishes maize and soybean yields by up to 6% under rainfed conditions. Declines observed in irrigated areas, or simulated assuming full irrigation, are weak. This supports the hypothesis that water stress induced by high temperatures causes the decline. For wheat a negative response to high temperature is neither observed nor simulated under historical conditions, since critical temperatures are rarely exceeded during the growing season. In the future, yields are modelled to decline for all three crops at temperatures >30 °C. Elevated CO 2 can only weakly reduce these yield losses, in contrast to irrigation.
- ItemThe theory of virtual water: Why it can help to understand local water scarcity(München : Oekom - Gesellschaft fuer Oekologische Kommunikation mbH, 2012) Biewald, A.; Rolinski, S.[No abstract available]
- ItemN2O emissions from the global agricultural nitrogen cycle – current state and future scenarios(München : European Geopyhsical Union, 2012) Bodirsky, B.L.; Popp, A.; Weindl, I.; Dietrich, J.P.; Rolinski, S.; Scheiffele, L.; Schmitz, C.; Lotze-Campen, H.Reactive nitrogen (Nr) is not only an important nutrient for plant growth, thereby safeguarding human alimentation, but it also heavily disturbs natural systems. To mitigate air, land, aquatic, and atmospheric pollution caused by the excessive availability of Nr, it is crucial to understand the long-term development of the global agricultural Nr cycle. For our analysis, we combine a material flow model with a land-use optimization model. In a first step we estimate the state of the Nr cycle in 1995. In a second step we create four scenarios for the 21st century in line with the SRES storylines. Our results indicate that in 1995 only half of the Nr applied to croplands was incorporated into plant biomass. Moreover, less than 10 per cent of all Nr in cropland plant biomass and grazed pasture was consumed by humans. In our scenarios a strong surge of the Nr cycle occurs in the first half of the 21st century, even in the environmentally oriented scenarios. Nitrous oxide (N2O) emissions rise from 3 Tg N2O-N in 1995 to 7–9 in 2045 and 5–12 Tg in 2095. Reinforced Nr pollution mitigation efforts are therefore required.
- ItemImpact of droughts on the carbon cycle in European vegetation: A probabilistic risk analysis using six vegetation models(München : European Geopyhsical Union, 2014) Van Oijen, M.; Balkovi, J.; Beer, C.; Cameron, D.R.; Ciais, P.; Cramer, W.; Kato, T.; Kuhnert, M.; Martin, R.; Myneni, R.; Rammig, A.; Rolinski, S.; Soussana, J.-F.; Thonicke, K.; Van der Velde, M.; Xu, L.We analyse how climate change may alter risks posed by droughts to carbon fluxes in European ecosystems. The approach follows a recently proposed framework for risk analysis based on probability theory. In this approach, risk is quantified as the product of hazard probability and ecosystem vulnerability. The probability of a drought hazard is calculated here from the Standardized Precipitation–Evapotranspiration Index (SPEI). Vulnerability is calculated from the response to drought simulated by process-based vegetation models. We use six different models: three for generic vegetation (JSBACH, LPJmL, ORCHIDEE) and three for specific ecosystems (Scots pine forests: BASFOR; winter wheat fields: EPIC; grasslands: PASIM). The periods 1971–2000 and 2071–2100 are compared. Climate data are based on gridded observations and on output from the regional climate model REMO using the SRES A1B scenario. The risk analysis is carried out for ~ 18 000 grid cells of 0.25 × 0.25° across Europe. For each grid cell, drought vulnerability and risk are quantified for five seasonal variables: net primary and ecosystem productivity (NPP, NEP), heterotrophic respiration (Rh), soil water content and evapotranspiration. In this analysis, climate change leads to increased drought risks for net primary productivity in the Mediterranean area: five of the models estimate that risk will exceed 15%. The risks increase mainly because of greater drought probability; ecosystem vulnerability will increase to a lesser extent. Because NPP will be affected more than Rh, future carbon sequestration (NEP) will also be at risk predominantly in southern Europe, with risks exceeding 0.25 g C m−2 d−1 according to most models, amounting to reductions in carbon sequestration of 20 to 80%.
- ItemModeling vegetation and carbon dynamics of managed grasslands at the global scale with LPJmL 3.6(Göttingen : Copernicus GmbH, 2018) Rolinski, S.; Müller, C.; Heinke, J.; Weindl, I.; Biewald, A.; Leon Bodirsky, B.; Bondeau, A.; Boons-Prins, E.R.; Bouwman, A.F.; Leffelaar, P.A.; Roller, J.A.T.; Schaphoff, S.; Thonicke, K.Grassland management affects the carbon fluxes of one-third of the global land area and is thus an important factor for the global carbon budget. Nonetheless, this aspect has been largely neglected or underrepresented in global carbon cycle models. We investigate four harvesting schemes for the managed grassland implementation of the dynamic global vegetation model (DGVM) Lund-Potsdam-Jena managed Land (LPJmL) that facilitate a better representation of actual management systems globally. We describe the model implementation and analyze simulation results with respect to harvest, net primary productivity and soil carbon content and by evaluating them against reported grass yields in Europe.We demonstrate the importance of accounting for differences in grassland management by assessing potential livestock grazing densities as well as the impacts of grazing, grazing intensities and mowing systems on soil carbon stocks. Grazing leads to soil carbon losses in polar or arid regions even at moderate livestock densities ( <0.4 livestock units per hectare-LSUha-1) but not in temperate regions even at much higher densities (0.4 to 1.2 LSUha-1). Applying LPJmL with the new grassland management options enables assessments of the global grassland production and its impact on the terrestrial biogeochemical cycles but requires a global data set on current grassland management.
- ItemTo what extent is climate change adaptation a novel challenge for agricultural modellers?(Amsterdam [u.a.] : Elsevier Science, 2019) Kipling, R.P.; Topp, C.F.E.; Bannink, A.; Bartley, D.J.; Blanco-Penedo, I.; Cortignani, R.; del Prado, A.; Dono, G.; Faverdin, P.; Graux, A.-I.; Hutchings, N.J.; Lauwers, L.; Özkan Gülzari, Ş.; Reidsma, P.; Rolinski, S.; Ruiz-Ramos, M.; Sandars, D.L.; Sándor, R.; Schönhart, M.; Seddaiu, G.; van Middelkoop, J.; Shrestha, S.; Weindl, I.; Schönhart, M.; Seddaiu, G.; van Middelkoop, J.; Shrestha, S.; Weindl, I.; Eory, V.Modelling is key to adapting agriculture to climate change (CC), facilitating evaluation of the impacts and efficacy of adaptation measures, and the design of optimal strategies. Although there are many challenges to modelling agricultural CC adaptation, it is unclear whether these are novel or, whether adaptation merely adds new motivations to old challenges. Here, qualitative analysis of modellers’ views revealed three categories of challenge: Content, Use, and Capacity. Triangulation of findings with reviews of agricultural modelling and Climate Change Risk Assessment was then used to highlight challenges specific to modelling adaptation. These were refined through literature review, focussing attention on how the progressive nature of CC affects the role and impact of modelling. Specific challenges identified were: Scope of adaptations modelled, Information on future adaptation, Collaboration to tackle novel challenges, Optimisation under progressive change with thresholds, and Responsibility given the sensitivity of future outcomes to initial choices under progressive change. © 2019 The Authors
- ItemLPJmL4 - A dynamic global vegetation model with managed land - Part 1: Model description(Göttingen : Copernicus GmbH, 2018) Schaphoff, S.; Von Bloh, W.; Rammig, A.; Thonicke, K.; Biemans, H.; Forkel, M.; Gerten, D.; Heinke, J.; Jägermeyr, J.; Knauer, J.; Langerwisch, F.; Lucht, W.; Müller, C.; Rolinski, S.; Waha, K.This paper provides a comprehensive description of the newest version of the Dynamic Global Vegetation Model with managed Land, LPJmL4. This model simulates - internally consistently - the growth and productivity of both natural and agricultural vegetation as coherently linked through their water, carbon, and energy fluxes. These features render LPJmL4 suitable for assessing a broad range of feedbacks within and impacts upon the terrestrial biosphere as increasingly shaped by human activities such as climate change and land use change. Here we describe the core model structure, including recently developed modules now unified in LPJmL4. Thereby, we also review LPJmL model developments and evaluations in the field of permafrost, human and ecological water demand, and improved representation of crop types. We summarize and discuss LPJmL model applications dealing with the impacts of historical and future environmental change on the terrestrial biosphere at regional and global scale and provide a comprehensive overview of LPJmL publications since the first model description in 2007. To demonstrate the main features of the LPJmL4 model, we display reference simulation results for key processes such as the current global distribution of natural and managed ecosystems, their productivities, and associated water fluxes. A thorough evaluation of the model is provided in a companion paper. By making the model source code freely available at https://gitlab.pik-potsdam.de/lpjml/LPJmL we hope to stimulate the application and further development of LPJmL4 across scientific communities in support of major activities such as the IPCC and SDG process.
- ItemGlobal food demand scenarios for the 21st century(San Francisco, CA : Public Library of Science (PLoS), 2015) Bodirsky, B.L.; Rolinski, S.; Biewald, A.; Weindl, I.; Popp, A.; Lotze-Campen, H.