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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.
- ItemSPITFIRE within the MPI Earth system model: Model development and evaluation(Hoboken, NJ : Blackwell Publishing Ltd, 2014) Lasslop, G.; Thonicke, K.; Kloster, S.Quantification of the role of fire within the Earth system requires an adequate representation of fire as a climate-controlled process within an Earth system model. To be able to address questions on the interaction between fire and the Earth system, we implemented the mechanistic fire model SPITFIRE, in JSBACH, the land surface model of the MPI Earth system model. Here, we document the model implementation as well as model modifications. We evaluate our model results by comparing the simulation to the GFED version 3 satellite-based data set. In addition, we assess the sensitivity of the model to the meteorological forcing and to the spatial variability of a number of fire relevant model parameters. A first comparison of model results with burned area observations showed a strong correlation of the residuals with wind speed. Further analysis revealed that the response of the fire spread to wind speed was too strong for the application on global scale. Therefore, we developed an improved parametrization to account for this effect. The evaluation of the improved model shows that the model is able to capture the global gradients and the seasonality of burned area. Some areas of model-data mismatch can be explained by differences in vegetation cover compared to observations. We achieve benchmarking scores comparable to other state-of-the-art fire models. The global total burned area is sensitive to the meteorological forcing. Adjustment of parameters leads to similar model results for both forcing data sets with respect to spatial and seasonal patterns. Key Points The SPITFIRE fire model was evaluated within the JSBACH land surface model A modified wind speed response improved the spatial pattern of burned area Regional gradients in burned area are driven by vegetation and fuel properties.
- ItemVariation in stem mortality rates determines patterns of above-ground biomass in Amazonian forests: implications for dynamic global vegetation models(Hoboken, NJ : Blackwell Publishing Ltd, 2016) Johnson, M.O.; Galbraith, D.; Gloor, M.; De Deurwaerder, H.; Guimberteau, M.; Rammig, A.; Thonicke, K.; Verbeeck, H.; von Randow, C.; Monteagudo, A.; Phillips, O.L.; Brienen, R.J.W.; Feldpausch, T.R.; Lopez Gonzalez, G.; Fauset, S.; Quesada, C.A.; Christoffersen, B.; Ciais, P.; Sampaio, G.; Kruijt, B.; Meir, P.; Moorcroft, P.; Zhang, K.; Alvarez-Davila, E.; Alves de Oliveira, A.; Amaral, I.; Andrade, A.; Aragao, L.E.O.C.; Araujo-Murakami, A.; Arets, E.J.M.M.; Arroyo, L.; Aymard, G.A.; Baraloto, C.; Barroso, J.; Bonal, D.; Boot, R.; Camargo, J.; Chave, J.; Cogollo, A.; Cornejo Valverde, F.; Lola da Costa, A.C.; Di Fiore, A.; Ferreira, L.; Higuchi, N.; Honorio, E.N.; Killeen, T.J.; Laurance, S.G.; Laurance, W.F.; Licona, J.; Lovejoy, T.; Malhi, Y.; Marimon, B.; Marimon, B.H. Jr.; Matos, D.C.L.; Mendoza, C.; Neill, D.A.; Pardo, G.; Peña-Claros, M.; Pitman, N.C.A.; Poorter, L.; Prieto, A.; Ramirez-Angulo, H.; Roopsind, A.; Rudas, A.; Salomao, R.P.; Silveira, M.; Stropp, J.; ter Steege, H.; Terborgh, J.; Thomas, R.; Toledo, M.; Torres-Lezama, A.; van der Heijden, G.M.F.; Vasquez, R.; Guimarães Vieira, I.C.; Vilanova, E.; Vos, V.A.; Baker, T.R.
- 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.