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Author Fürst, C.; Helming, K.; Lorz, C.; Müller, F.; Verburg, P.H.
Title Integrated land use and regional resource management--a cross-disciplinary dialogue on future perspectives for a sustainable development of regional resources Type Journal Article
Year 2013 Publication (up) Journal of Environmental Management Abbreviated Journal J. Environ. Manage.
Volume 127 Suppl Issue Pages S1-S5
Keywords Conservation of Natural Resources/*methods; Analytical framework for integrated planning; Integrated land use; Regional planning; Regional resource management; Sustainable regional development
Abstract Our paper introduces objectives and ideas of the special issue “Integrated land use and regional resource management – A cross-disciplinary dialogue on future perspectives for a sustainable development of regional resources” and provides an overview on the contributions of the single papers in the special issue to this topic. Furthermore, we discuss and present major challenges and demands on integrated land use and regional resource management and we come up with an analytical framework how to correspond these demands.
Address
Corporate Author Thesis
Publisher Place of Publication Editor
Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 0301-4797 ISBN Medium
Area Expedition Conference
Notes TradeM, ftnotmacsur Approved no
Call Number MA @ admin @ Serial 4826
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Author Hamidov, A.; Helming, K.; Bellocchi, G.; Bojar, W.; Dalgaard, T.; Ghaley, B.B.; Hoffmann, C.; Holman, I.; Holzkämper, A.; Krzeminska, D.; Kværnø, S.H.; Lehtonen, H.; Niedrist, G.; Øygarden, L.; Reidsma, P.; Roggero, P.P.; Rusu, T.; Santos, C.; Seddaiu, G.; Skarbøvik, E.; Ventrella, D.; Żarski, J.; Schönhart, M.
Title Impacts of climate change adaptation options on soil functions: A review of European case-studies Type Journal Article
Year 2018 Publication (up) Land Degradation & Development Abbreviated Journal Land Degradation & Development
Volume 29 Issue 8 Pages 2378-2389
Keywords agricultural adaptation; DPSIR; regional case-studies; soil degradation; Sustainable Development Goals; Agricultural Practices; Ecosystem Services; Land Management; Netherlands; Farm; Environment; Challenges; Catchments; Framework; Nitrogen
Abstract Soils are vital for supporting food security and other ecosystem services. Climate change can affect soil functions both directly and indirectly. Direct effects include temperature, precipitation, and moisture regime changes. Indirect effects include those that are induced by adaptations such as irrigation, crop rotation changes, and tillage practices. Although extensive knowledge is available on the direct effects, an understanding of the indirect effects of agricultural adaptation options is less complete. A review of 20 agricultural adaptation case-studies across Europe was conducted to assess implications to soil threats and soil functions and the link to the Sustainable Development Goals (SDGs). The major findings are as follows: (a) adaptation options reflect local conditions; (b) reduced soil erosion threats and increased soil organic carbon are expected, although compaction may increase in some areas; (c) most adaptation options are anticipated to improve the soil functions of food and biomass production, soil organic carbon storage, and storing, filtering, transforming, and recycling capacities, whereas possible implications for soil biodiversity are largely unknown; and (d) the linkage between soil functions and the SDGs implies improvements to SDG 2 (achieving food security and promoting sustainable agriculture) and SDG 13 (taking action on climate change), whereas the relationship to SDG 15 (using terrestrial ecosystems sustainably) is largely unknown. The conclusion is drawn that agricultural adaptation options, even when focused on increasing yields, have the potential to outweigh the negative direct effects of climate change on soil degradation in many European regions.
Address 2018-10-16
Corporate Author Thesis
Publisher Place of Publication Editor
Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 1085-3278 ISBN Medium
Area Expedition Conference
Notes XC, TradeM, ft_macsur Approved no
Call Number MA @ admin @ Serial 5210
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Author Kraus, D.; Weller, S.; Klatt, S.; Haas, E.; Wassmann, R.; Kiese, R.; Butterbach-Bahl, K.
Title A new LandscapeDNDC biogeochemical module to predict CH4 and N2O emissions from lowland rice and upland cropping systems Type Journal Article
Year 2015 Publication (up) Plant and Soil Abbreviated Journal Plant Soil
Volume 386 Issue 1-2 Pages 125-149
Keywords methane; nitrous oxide; paddy rice; maize; model; nitrous-oxide emissions; process-based model; methane transport capacity; process-oriented model; pnet-n-dndc; forest soils; paddy soils; sensitivity-analysis; residue management; organic-matter
Abstract Replacing paddy rice by upland systems such as maize cultivation is an on-going trend in SE Asia caused by increasing water scarcity and higher demand for meat. How such land management changes will feedback on soil C and N cycles and soil greenhouse gas emissions is not well understood at present. A new LandscapeDNDC biogeochemical module was developed that allows the effect of land management changes on soil C and N cycle to be simulated. The new module is applied in combination with further modules simulating microclimate and crop growth and evaluated against observations from field experiments. The model simulations agree well with observed dynamics of CH (4) emissions in paddy rice depending on changes in climatic conditions and agricultural management. Magnitude and peak emission periods of N (2) O from maize cultivation are simulated correctly, though there are still deficits in reproducing day-to-day dynamics. These shortcomings are most likely related to simulated soil hydrology and may only be resolved if LandscapeDNDC is coupled to more complex hydrological models. LandscapeDNDC allows for simulation of changing land management practices in SE Asia. The possibility to couple LandscapeDNDC to more complex hydrological models is a feature needed to better understand related effects on soil-atmosphere-hydrosphere interactions.
Address
Corporate Author Thesis
Publisher Place of Publication Editor
Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 0032-079x ISBN Medium Article
Area Expedition Conference
Notes CropM, ft_macsur Approved no
Call Number MA @ admin @ Serial 4530
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Author Mansouri, M.; Dumont, B.; Leemans, V.; Destain, M.-F.
Title Bayesian methods for predicting LAI and soil water content Type Journal Article
Year 2014 Publication (up) Precision Agriculture Abbreviated Journal Precision Agric.
Volume 15 Issue 2 Pages 184-201
Keywords crop model; bayes; data assimilation; extended kalman filtering; particle filtering; variational filtering; leaf-area index; parameter-estimation; crop models; moisture; instruments; management; sensors; state
Abstract LAI of winter wheat (Triticum aestivum L.) and soil water content of the topsoil (200 mm) and of the subsoil (500 mm) were considered as state variables of a dynamic soil-crop system. This system was assumed to progress according to a Bayesian probabilistic state space model, in which real values of LAI and soil water content were daily introduced in order to correct the model trajectory and reach better future evolution. The chosen crop model was mini STICS which can reduce the computing and execution times while ensuring the robustness of data processing and estimation. To predict simultaneously state variables and model parameters in this non-linear environment, three techniques were used: extended Kalman filtering (EKF), particle filtering (PF), and variational filtering (VF). The significantly improved performance of the VF method when compared to EKF and PF is demonstrated. The variational filter has a low computational complexity and the convergence speed of states and parameters estimation can be adjusted independently. Detailed case studies demonstrated that the root mean square error of the three estimated states (LAI and soil water content of two soil layers) was smaller and that the convergence of all considered parameters was ensured when using VF. Assimilating measurements in a crop model allows accurate prediction of LAI and soil water content at a local scale. As these biophysical properties are key parameters in the crop-plant system characterization, the system has the potential to be used in precision farming to aid farmers and decision makers in developing strategies for site-specific management of inputs, such as fertilizers and water irrigation.
Address
Corporate Author Thesis
Publisher Place of Publication Editor
Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 1385-2256 ISBN Medium Article
Area Expedition Conference
Notes CropM, ftnotmacsur Approved no
Call Number MA @ admin @ Serial 4629
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Author Dumont, B.; Basso, B.; Leemans, V.; Bodson, B.; Destain, J.-P.; Destain, M.-F.
Title Systematic analysis of site-specific yield distributions resulting from nitrogen management and climatic variability interactions Type Journal Article
Year 2015 Publication (up) Precision Agriculture Abbreviated Journal Precision Agric.
Volume 16 Issue 4 Pages 361-384
Keywords nitrogen management; climatic variability; lars-wg weather generator; stics soil-crop model; pearson system; probability risk assessment; crop model stics; fertilizer nitrogen; generic model; wheat yield; maize; simulation; skewness; field; agriculture; scenarios
Abstract At the plot level, crop simulation models such as STICS have the potential to evaluate risk associated with management practices. In nitrogen (N) management, however, the decision-making process is complex because the decision has to be taken without any knowledge of future weather conditions. The objective of this paper is to present a general methodology for assessing yield variability linked to climatic uncertainty and variable N rate strategies. The STICS model was coupled with the LARS-Weather Generator. The Pearson system and coefficients were used to characterise the shape of yield distribution. Alternatives to classical statistical tests were proposed for assessing the normality of distributions and conducting comparisons (namely, the Jarque-Bera and Wilcoxon tests, respectively). Finally, the focus was put on the probability risk assessment, which remains a key point within the decision process. The simulation results showed that, based on current N application practice among Belgian farmers (60-60-60 kgN ha(-1)), yield distribution was very highly significantly non-normal, with the highest degree of asymmetry characterised by a skewness value of -1.02. They showed that this strategy gave the greatest probability (60 %) of achieving yields that were superior to the mean (10.5 t ha(-1)) of the distribution.
Address
Corporate Author Thesis
Publisher Place of Publication Editor
Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 1385-2256 ISBN Medium Article
Area Expedition Conference
Notes CropM, ft_macsur Approved no
Call Number MA @ admin @ Serial 4519
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