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Now showing 1 - 5 of 5
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    Quantifying uncertainties in soil carbon responses to changes in global mean temperature and precipitation
    (München : European Geopyhsical Union, 2014) Nishina, K.; Ito, A.; Beerling, D.J.; Cadule, P.; Ciais, P.; Clark, D.B.; Friend, A.D.; Kahana, R.; Kato, E.; Keribin, R.; Lucht, W.; Lomas, M.; Rademacher, T.T.; Pavlick, R.; Schaphoff, S.; Vuichard, N.; Warszawaski, L.; Yokohata, T.
    Soil organic carbon (SOC) is the largest carbon pool in terrestrial ecosystems and may play a key role in biospheric feedbacks with elevated atmospheric carbon dioxide (CO2) in a warmer future world. We examined the simulation results of seven terrestrial biome models when forced with climate projections from four representative-concentration-pathways (RCPs)-based atmospheric concentration scenarios. The goal was to specify calculated uncertainty in global SOC stock projections from global and regional perspectives and give insight to the improvement of SOC-relevant processes in biome models. SOC stocks among the biome models varied from 1090 to 2650 Pg C even in historical periods (ca. 2000). In a higher forcing scenario (i.e., RCP8.5), inconsistent estimates of impact on the total SOC (2099–2000) were obtained from different biome model simulations, ranging from a net sink of 347 Pg C to a net source of 122 Pg C. In all models, the increasing atmospheric CO2 concentration in the RCP8.5 scenario considerably contributed to carbon accumulation in SOC. However, magnitudes varied from 93 to 264 Pg C by the end of the 21st century across biome models. Using the time-series data of total global SOC simulated by each biome model, we analyzed the sensitivity of the global SOC stock to global mean temperature and global precipitation anomalies (ΔT and ΔP respectively) in each biome model using a state-space model. This analysis suggests that ΔT explained global SOC stock changes in most models with a resolution of 1–2 °C, and the magnitude of global SOC decomposition from a 2 °C rise ranged from almost 0 to 3.53 Pg C yr−1 among the biome models. However, ΔP had a negligible impact on change in the global SOC changes. Spatial heterogeneity was evident and inconsistent among the biome models, especially in boreal to arctic regions. Our study reveals considerable climate uncertainty in SOC decomposition responses to climate and CO2 change among biome models. Further research is required to improve our ability to estimate biospheric feedbacks through both SOC-relevant and vegetation-relevant processes.
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    Decomposing uncertainties in the future terrestrial carbon budget associated with emission scenarios, climate projections, and ecosystem simulations using the ISI-MIP results
    (München : European Geopyhsical Union, 2015) Nishina, K.; Ito, A.; Falloon, P.; Friend, A.D.; Beerling, D.J.; Ciais, P.; Clark, D.B.; Kahana, R.; Kato, E.; Lucht, W.; Lomas, M.; Pavlick, R.; Schaphoff, S.; Warszawaski, L.; Yokohata, T.
    We examined the changes to global net primary production (NPP), vegetation biomass carbon (VegC), and soil organic carbon (SOC) estimated by six global vegetation models (GVMs) obtained from the Inter-Sectoral Impact Model Intercomparison Project. Simulation results were obtained using five global climate models (GCMs) forced with four representative concentration pathway (RCP) scenarios. To clarify which component (i.e., emission scenarios, climate projections, or global vegetation models) contributes the most to uncertainties in projected global terrestrial C cycling by 2100, analysis of variance (ANOVA) and wavelet clustering were applied to 70 projected simulation sets. At the end of the simulation period, changes from the year 2000 in all three variables varied considerably from net negative to positive values. ANOVA revealed that the main sources of uncertainty are different among variables and depend on the projection period. We determined that in the global VegC and SOC projections, GVMs are the main influence on uncertainties (60 % and 90 %, respectively) rather than climate-driving scenarios (RCPs and GCMs). Moreover, the divergence of changes in vegetation carbon residence times is dominated by GVM uncertainty, particularly in the latter half of the 21st century. In addition, we found that the contribution of each uncertainty source is spatiotemporally heterogeneous and it differs among the GVM variables. The dominant uncertainty source for changes in NPP and VegC varies along the climatic gradient. The contribution of GVM to the uncertainty decreases as the climate division becomes cooler (from ca. 80 % in the equatorial division to 40 % in the snow division). Our results suggest that to assess climate change impacts on global ecosystem C cycling among each RCP scenario, the long-term C dynamics within the ecosystems (i.e., vegetation turnover and soil decomposition) are more critical factors than photosynthetic processes. The different trends in the contribution of uncertainty sources in each variable among climate divisions indicate that improvement of GVMs based on climate division or biome type will be effective. On the other hand, in dry regions, GCMs are the dominant uncertainty source in climate impact assessments of vegetation and soil C dynamics.
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    Comparing projections of future changes in runoff from hydrological and biome models in ISI-MIP
    (München : European Geopyhsical Union, 2013) Davie, J.C.S.; Falloon, P.D.; Kahana, R.; Dankers, R.; Betts, R.; Portmann, F.T.; Wisser, D.; Clark, D.B.; Ito, A.; Masaki, Y.; Nishina, K.; Fekete, B.; Tessler, Z.; Wada, Y.; Liu, X.; Tang, Q.; Hagemann, S.; Stacke, T.; Pavlick, R.; Schaphoff, S.; Gosling, S.N.; Franssen, W.; Arnell, N.
    Future changes in runoff can have important implications for water resources and flooding. In this study, runoff projections from ISI-MIP (Inter-sectoral Impact Model Intercomparison Project) simulations forced with HadGEM2-ES bias-corrected climate data under the Representative Concentration Pathway 8.5 have been analysed for differences between impact models. Projections of change from a baseline period (1981–2010) to the future (2070–2099) from 12 impacts models which contributed to the hydrological and biomes sectors of ISI-MIP were studied. The biome models differed from the hydrological models by the inclusion of CO2 impacts and most also included a dynamic vegetation distribution. The biome and hydrological models agreed on the sign of runoff change for most regions of the world. However, in West Africa, the hydrological models projected drying, and the biome models a moistening. The biome models tended to produce larger increases and smaller decreases in regionally averaged runoff than the hydrological models, although there is large inter-model spread. The timing of runoff change was similar, but there were differences in magnitude, particularly at peak runoff. The impact of vegetation distribution change was much smaller than the projected change over time, while elevated CO2 had an effect as large as the magnitude of change over time projected by some models in some regions. The effect of CO2 on runoff was not consistent across the models, with two models showing increases and two decreases. There was also more spread in projections from the runs with elevated CO2 than with constant CO2. The biome models which gave increased runoff from elevated CO2 were also those which differed most from the hydrological models. Spatially, regions with most difference between model types tended to be projected to have most effect from elevated CO2, and seasonal differences were also similar, so elevated CO2 can partly explain the differences between hydrological and biome model runoff change projections. Therefore, this shows that a range of impact models should be considered to give the full range of uncertainty in impacts studies.
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    Critical impacts of global warming on land ecosystems
    (München : European Geopyhsical Union, 2013) Ostberg, S.; Lucht, W.; Schaphoff, S.; Gerten, D.
    Globally increasing temperatures are likely to have impacts on terrestrial, aquatic and marine ecosystems that are difficult to manage. Quantifying impacts worldwide and systematically as a function of global warming is fundamental to substantiating the discussion on climate mitigation targets and adaptation planning. Here we present a macro-scale analysis of climate change impacts on terrestrial ecosystems based on newly developed sets of climate scenarios featuring a step-wise sampling of global mean temperature increase between 1.5 and 5 K by 2100. These are processed by a biogeochemical model (LPJmL) to derive an aggregated metric of simultaneous biogeochemical and structural shifts in land surface properties which we interpret as a proxy for the risk of shifts and possibly disruptions in ecosystems. Our results show a substantial risk of climate change to transform terrestrial ecosystems profoundly. Nearly no area of the world is free from such risk, unless strong mitigation limits global warming to around 2 degrees above preindustrial level. Even then, our simulations for most climate models agree that up to one-fifth of the land surface may experience at least moderate ecosystem change, primarily at high latitudes and high altitudes. If countries fulfil their current emissions reduction pledges, resulting in roughly 3.5 K of warming, this area expands to cover half the land surface, including the majority of tropical forests and savannas and the boreal zone. Due to differences in regional patterns of climate change, the area potentially at risk of major ecosystem change considering all climate models is up to 2.5 times as large as for a single model.
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    Integrated crop water management might sustainably halve the global food gap
    (Bristol : IOP Publishing, 2016) Jägermeyr, J.; Gerten, D.; Schaphoff, S.; Heinke, J.; Lucht, W.; Rockström, J.
    As planetary boundaries are rapidly being approached, humanity has little room for additional expansion and conventional intensification of agriculture, while a growing world population further spreads the food gap. Ample evidence exists that improved on-farm water management can close water-related yield gaps to a considerable degree, but its global significance remains unclear. In this modeling study we investigate systematically to what extent integrated crop water management might contribute to closing the global food gap, constrained by the assumption that pressure on water resources and land does not increase. Using a process-based bio-/agrosphere model, we simulate the yield-increasing potential of elevated irrigation water productivity (including irrigation expansion with thus saved water) and optimized use of in situ precipitation water (alleviated soil evaporation, enhanced infiltration, water harvesting for supplemental irrigation) under current and projected future climate (from 20 climate models, with and without beneficial CO2 effects). Results show that irrigation efficiency improvements can save substantial amounts of water in many river basins (globally 48% of non-productive water consumption in an 'ambitious' scenario), and if rerouted to irrigate neighboring rainfed systems, can boost kcal production significantly (26% global increase). Low-tech solutions for small-scale farmers on water-limited croplands show the potential to increase rainfed yields to a similar extent. In combination, the ambitious yet achievable integrated water management strategies explored in this study could increase global production by 41% and close the water-related yield gap by 62%. Unabated climate change will have adverse effects on crop yields in many regions, but improvements in water management as analyzed here can buffer such effects to a significant degree.