| 1. |
- Blanke, Jan Hendrik, et al.
(författare)
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Assessing the impact of changes in land-use intensity and climate on simulated trade-offs between crop yield and nitrogen leaching
- 2017
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Ingår i: Agriculture, Ecosystems and Environment. - : Elsevier BV. - 0167-8809. ; 239, s. 385-398
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Tidskriftsartikel (refereegranskat)abstract
- In this study, a global vegetation model (LPJ-GUESS) is forced with spatial information (Nomenclature of Units for Territorial Statistics (NUTS) 2 level) of land-use intensity change in the form of nitrogen (N) fertilization derived from a model chain which informed the Common Agricultural Policy Regionalized Impact (CAPRI) model. We analysed the combined role of climate change and land-use intensity change for trade-offs between agricultural yield and N leaching in the European Union under two plausible scenarios up until 2040. Furthermore, we assessed both driver importance and uncertainty in future trends based on an alternative land-use intensity dataset derived from an integrated assessment model. LPJ-GUESS simulated an increase in wheat and maize yield but also N leaching for most regions when driven by changes in land-use intensity and climate under RCP 8.5. Under RCP 4.5, N leaching is reduced in 53% of the regions while there is a trade-off in crop productivity. The most important factors influencing yield were CO2 (wheat) and climate (maize), but N application almost equaled these in importance. For N leaching, N application was the most important factor, followed by climate. Therefore, using a constant N application dataset in the absence of future projections has a substantial effect on simulated ecosystem responses, especially for maize yield and N leaching. This study is a first assessment of future N leaching and yield responses based on projections of climate and land-use intensity. It further highlights the importance of accounting for changes in future N applications and land-use intensity in general when evaluating environmental impacts over long time periods.
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| 2. |
- Blanke, Jan Hendrik, et al.
(författare)
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Effect of climate data on simulated carbon and nitrogen balances for Europe
- 2016
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Ingår i: Journal of Geophysical Research - Biogeosciences. - 2169-8953. ; 121:5, s. 1352-1371
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Tidskriftsartikel (refereegranskat)abstract
- In this study, we systematically assess the spatial variability in carbon and nitrogen balance simulations related to the choice of global circulation models (GCMs), representative concentration pathways (RCPs), spatial resolutions, and the downscaling methods used as calculated with LPJ-GUESS. We employed a complete factorial design and performed 24 simulations for Europe with different climate input data sets and different combinations of these four factors. Our results reveal that the variability in simulated output in Europe is moderate with 35.6%–93.5% of the total variability being common among all combinations of factors. The spatial resolution is the most important factor among the examined factors, explaining 1.5%–10.7% of the total variability followed by GCMs (0.3%–7.6%), RCPs (0%–6.3%), and downscaling methods (0.1%–4.6%). The higher-order interactions effect that captures nonlinear relations between the factors and random effects is pronounced and accounts for 1.6%–45.8% to the total variability. The most distinct hot spots of variability include the mountain ranges in North Scandinavia and the Alps, and the Iberian Peninsula. Based on our findings, we advise to conduct the application of models such as LPJ-GUESS at a reasonably high spatial resolution which is supported by the model structure. There is no notable gain in simulations of ecosystem carbon and nitrogen stocks and fluxes from using regionally downscaled climate in preference to bias-corrected, bilinearly interpolated CMIP5 projections.
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| 3. |
- Blanke, Jan Hendrik
(författare)
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European ecosystems on a changing planet : Integrating climate change and land-use intensity data
- 2017
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Dynamic global vegetation models are mathematical models that provide a bottom-up description of plant communities. They explicitly model physiological and population-level processes such as growth, photosynthesis, carbon allocation, regeneration and mortality.However, there are a number of challenges to meet in the context of mechanistic vegetation models which can be extrapolated to new environmental conditions.This thesis aims to advance our knowledge of the vegetation model LPJ-GUESS by analyzing both sensitivity and uncertainty towards input datasets such as climate and land-use intensity data and their derivation. It further aims to improve the model performance by including former neglected processes like land-use intensity and daily management for grasslands. Beyond these rather technical aims, this thesis also investigates possible trade-offs between society relevant ecosystem functions like crop yield and carbon storage via integrating climate data and up-to-date land-use intensity information.The results show that simulations with LPJ-GUESS for Europe were most sensitive to the spatial resolution of the input climate data followed by the choice of the climate model. When driven with projections of climate and land-use intensity in form of nitrogen fertilizer, simulations of maize yield and nitrogen leaching were most sensitive to nitrogen applications followed by climate while wheat yield was most sensitive to changes in carbon dioxide followed by nitrogen applications.While future yields of wheat and maize increased in Europe under representative concentration pathways 4.5 and 8.5, these increases were accompanied with increases of nitrogen leaching in many regions. However, leaching decreased in about 53% of the regions under pathway 4.5 while it increased in 76% of the regions under pathway 8.5.It is also shown in this thesis that grassland productivity cannot be adequately captured without including land-use intensity data in form of nitrogen fertilizer. Incorporating daily grassland management and fertilizer applications into LPJ-GUESS improved the model significantly. Finally, afforestation had overall positive effects both on plant species richness and carbon storage in Saxony, Germany. However, a number of locations were identified for which afforestation would lead to a decrease in plant species richness.
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