Publications
NIBIOs employees contribute to several hundred scientific articles and research reports every year. You can browse or search in our collection which contains references and links to these publications as well as other research and dissemination activities. The collection is continously updated with new and historical material.
2012
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Groundwater pollution by agrochemicals, degradation of soil quality and pollution of aquatic ecosystems by agricultural drainage waters have become an issue in the last decades. Flow processes in the vadose zone are closely related to these problems. In general, water flow in soils can be classified into two major categories: uniform and non-uniform (preferential) flow (In: U.S. National Committee for Rock Mechanics, Conceptual Models of Flow and Transport in the Fractured Vadose Zone, 2001, pp.149-187). The former describes a relatively slow movement of water through the porous soil matrix and can be modelled by Richard”s equation. The latter comprises all flow types where water bypasses a portion of the soil matrix and flows through localised (i.e. preferential) paths. Unlike uniform flow, preferential flow is hardly predictable because the assumptions of Richard”s equation of a homogeneous representative elementary volume characterised by a single value of water potential, water content and hydraulic conductivity are frequently violated (Eur J Soil Sci, 2007; 58:523-546)....
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A crucial process of the terrestrial carbon cycle is photosynthetic uptake through plants. This may be quantified by calculating the fraction of absorbed photosynthetic active radiation (fapar), based on multispectral reflectance properties of the earth surface. The fapar index is available with global coverage from satellite sensors.Here, we combine two satellite missions, SeaWifs on board OrbView2 and MERIS on board Envisat, to produce time series with 10 days resolution for a period of 14 years (19982011) at a spatial resolution of 0.5 latitude x 0.5 longitude. These more than 50000 individual time series represent a huge range of dynamical behavior with respect to variability, periodicities and correlation structure.To characterize differences as a function of spatial location or distance, we employ Recurrence Quantification Analysis (RQA) and Recurrence Network Analysis (RNA). Two strategies are followed. On one hand, RQA and network variables are calculated for individual time series using identical recurrence parameters, and compared to see whether differences between them resemble different climate regimes, biomes, plant functional types or landuse classes. On the other hand, a multivariate extension of RNA will be exploited to see whether networks within networks occur, i.e. whether RNA provides sufficient contrasts to discern different clusters of pixels on the globe.Taken together, the recurrence analysis might lead to a new classification of the terrestrial biosphere which in turn can be compared to existing partitioning based on climate and/or vegetation properties. A number of technical issues will be addressed as well, such as the impact of the finite length of the series (504 values each), the necessity to gapfill parts of the data, the stability of network variables against changes in the recurrence parameters, or the computational challenges involved in the multinetwork analysis of many series. http://dames.pik-potsdam.de/Abstracts.pdf
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Our aim is to investigate the temporal dynamics of the Fraction of Absorbed Photosynthetically Active Radiation (fAPAR) on a global scale and its relation to the main meteorological variables across space. We focus on complex patterns in time, which are neither regular (trend and seasonality) nor random (noise), but somewhere in between. We quantify complexity and information content or entropy using methods from order statistics and complexity sciences.Time series with high entropy are difficult to predict, whereas time series with high complexity are difficult to describe. This leads to a spatially explicit characterization of complex patterns in a very sensitive way. We use FAPAR observations (SeaWiFS and MERIS, 1998 to 2012) along with gridded global surface air temperature, precipitation and shortwave radiation.All these time series are explored on a pixelbypixel basis and clustered according to a very recent classification system of the land surface. In addition, we quantify the time reversal asymmetry of these data. We compare environmental time series with data from a stochastic candidate process temporally symmetric and long range correlated artificial knoise.Results were plotted in the ComplexityversusEntropy plane (CH plane), showing the particular footprint of each variable in a very sensitive way. Visualized in world maps, results revealed unexpected complex pattern in some dry regions, in particular on pixels surrounding deserts and in eastern Sahara. In this respect, the results provide a new classification of the climate and the biosphere. http://dames.pik-potsdam.de/Abstracts.pdf
Authors
Holger LangeAbstract
We calculate entropy and complexity of runoff time series and artificially generated series with long-range correlations. Entropy and complexity of data series may be represented against each other in a two-dimensional diagram which we will refer to as Complexity-Entropy Causality Plane, or CECP. We use a recently developed framework for these two indicators based on order statistics. It is well-known that runoff, as all other environmental time series actually measured, is a mixture of deterministic (signal) and stochastic (noise) parts, the latter due to noise inherent in the measurement process and externally induced by natural processes. The distinction between signal and noise is notoriously difficult and subject to much debate. In our approach, the observed series are compared to purely stochastic but long-range correlated processes, the k noise, where k is a parameter determining the strength of the correlations. Although these processes resemble runoff series in their correlation behavior and may be even tuned to any runoff series by changing the value of k, the CECP locations and in particular the order pattern statistics reveals qualitative differences between runoff and k noise. We use these differences to conclude on the deterministic nature of the (short-term) dynamics of the runoff time series. The proposed methodology also represents a stringent test bed for hydrological models.
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Arne Sæbø Robert Popek Barbara Nawrot Hans Martin Hanslin Helena Gawronska Stanislaw W GawronskiAbstract
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Camilla Østerud M. Ashraful Islam Jorunn Elisabeth Olsen Dag-Ragnar Blystad Sissel Torre Anne Kathrine Hvoslef-Eide Jihong Liu ClarkeAbstract
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Even Riiser Ingrid Holtsmark Hege Særvold Steen S. Swaminathan Navin Khanna Ralph Bock Jihong Liu ClarkeAbstract
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Even Riiser Ingrid Holtsmark Hege Særvold Steen S. Swaminathan Navin Khanna Ralph Bock Jihong Liu ClarkeAbstract
The global spread of dengue fever threatens a large percentage of the world’s population. The disease causes great human suffering, a high mortality from dengue haemorrhagic fever and its complications, and major costs. There is currently no vaccine to prevent dengue virus infection. Our project aims to express a tetravalent vaccine candidate in tobacco chloroplasts, a cost effective system, and hence to contribute to innovation and bio-economy as a long term goal.