Spatial and temporal variability of soil water content in two regions of Southwest German

Soil water content (SWC) plays a key role in partitioning of energy and water fluxes on the land surface. Knowledge about spatial and temporal variability of topsoil water content is crucial for understanding land surface processes, improving climate and hydrology modeling. In recent study, we investigated SWC variability, its relation to the mean spatial soil water content (qm) and variability of rainfall on the regional spatial and event temporal scales. To accomplish this, we used a multi-year high resolution data set, obtained from two soil moisture sensor networks (spatial extent of 25 km ×25 km), set up at croplands in Kraichgau and Swabian Alb regions in Southwest Germany. The relationship of SWC standard deviation (sq) versus áqñ was studied (sq-qm). It was found that the initial location of sq in relation to the sq at the permanent wilting point (sq-qwp) and the sq at saturation (sq-qs) – the anchor points – as well as the upper and lower bounds of the sq-qm envelope determine whether SWC variability increases or decreases upon a change in qm. sq-qm relationship forms combinations of concave and convex hyperbolas reflecting the variability of soil texture and depending on sq in relation to the anchor points. The majority of sq-qm clockwise hysteresis cases were observed in intermediate and intermediate/wet state of SWC. The sq phase-space can be used to test whether hydrological or land surface models capture the reasonable range of soil water heterogeneity

Breeding of CMS-F1-Hybrids in \u3cem\u3eLolium Perenne\u3c/em\u3e With Improved Nitrogen Use Efficiency

The environmental pollution by nitrogen losses from dairy farms can be reduced by improving the nitrogen use efficiency (NUE) of grass varieties. The main goal is to develop varieties with a better nitrogen utilisation. These low input varieties can produce acceptable yields at a low level of N-fertilisation. High input varieties express their high yield potential only at high N-supply. These varieties are less preferable, because N- losses increase at higher levels of nitrogen application. The breeding of CMS-F1-Hybrids can be a successful strategy for developing varieties with a higher NUE. In F1-Hybrid varieties higher heterosis effects can be achieved than in populations or synthetic varieties

E-government and the digital divide: A study of English-as-a-Second-Language Users' Information Behaviour

Internet-based technologies are increasingly used by organisations and governments to offer services to consumers and the public in a quick and efficient manner, removing the need for face-to-face conversations and human advisors. Despite their obvious benefits for most users, these online systems may present barriers of access to certain groups in society which may lead to information poverty. In this study we consider the information behaviour of ten ESL (English as a Second Language) participants as they conduct four search tasks designed to reflect actual information seeking situations. Our results suggest that, despite a perception that they have a good understanding of English, they often choose documents that are only partially or tangentially relevant. There were significant differences in the behaviour of participants given their perceived confidence in using English to perform search tasks. Those who were confident took riskier strategies and were less thorough, leading to them bookmarking a larger proportion of non-relevant documents. The results of this work have potentially profound repercussions for how e-government services are provided and how second-language speakers are assisted in their use of these

Searching Data: A Review of Observational Data Retrieval Practices in Selected Disciplines

A cross-disciplinary examination of the user behaviours involved in seeking and evaluating data is surprisingly absent from the research data discussion. This review explores the data retrieval literature to identify commonalities in how users search for and evaluate observational research data. Two analytical frameworks rooted in information retrieval and science technology studies are used to identify key similarities in practices as a first step toward developing a model describing data retrieval

An explorative study of interface support for image searching

In this paper we study interfaces for image retrieval systems. Current image retrieval interfaces are limited to providing query facilities and result presentation. The user can inspect the results and possibly provide feedback on their relevance for the current query. Our approach, in contrast, encourages the user to group and organise their search results and thus provide more fine-grained feedback for the system. It combines the search and management process, which - according to our hypothesis - helps the user to onceptualise their search tasks and to overcome the query formulation problem. An evaluation, involving young design-professionals and di®erent types of information seeking scenarios, shows that the proposed approach succeeds in encouraging the user to conceptualise their tasks and that it leads to increased user satisfaction. However, it could not be shown to increase performance. We identify the problems in the current setup, which when eliminated should lead to more effective searching overall

Interactions of Generated Weather Raster and Soil Profiles in Simulating Adaptive Crop Management and Consequent Yields for Five Major Crops throughout a Region in Southern Germany

Klimaanpassung und MitigationThe ability of bioeconomic simulation modelling to realistically predict agricultural adaptation is limited by the degree of detail in crucial model components. Model robustness must be tested before localized calibrations can be applied to regions of heterogenous environmental conditions. The agent-based model FARMACTOR was used to simulate the timing of field management actions (planting, harvest etc.) in response to environmental conditions, and consequent yields of winter wheat, barley and rapeseed, spring barley and silage maize as the predominant crops in a distinct region of Germany, by linking weather data and the crop growth simulation model EXPERT-N. The integrated models were calibrated to observed experimental data and official phenological observations and then run from 1990 to 2009, forced with climate data from ERA-interim Reanalyses data which was downscaled with the Weather and Research Forecast (WRF) model to a 12 X 12 km² grid. Variability in regional soils was replicated with 10 different soil profiles mapped at 1/25,000 scale. The nature of the forcing climate data dictates temporal aggregation for analysis, so that validity is examined by comparing mean simulated planting and harvest dates and yields to official records in the area. The mean predicted planting dates are very close to observations over the period, within a few days of observations, but show less variance. Harvest dates are accurately predicted as well, within one to two weeks, and the variances are closer to observations. Predicted winter wheat yields are well simulated in comparison to observed data, but maize yields are underestimated, while winter and spring barley and winter rapeseed yields are greater than observed district ("Landkreis") yields. The degree of variance in simulated yields is acceptable in wheat, winter barley and maize, but excessive in spring barley and winter rapeseed. Cross-sectional examination of yields shows that the different soil profiles are responsible for more yield variance than simulated weather cells in all crops. While the coupled models appear accurate in predicting crop management dates and physiological development, the inaccuracy in yields in all crops except winter wheat calls into question the reliability of the integrated models when applied, as is, outside of calibration conditions. That soil parameterization is responsible for more variance than generated weather is helpful in seeking to improve performance and encouraging in terms of the method of weather generation. Reliable extension of the coupled models to include all soils in an area together with artificial spatial climatic variability may require regionalized calibration to increase crop model stability

Indicators for the Data Usage Index (DUI): an incentive for publishing primary biodiversity data through global information infrastructure

<p>Abstract</p> <p>Background</p> <p>A professional recognition mechanism is required to encourage expedited publishing of an adequate volume of 'fit-for-use' biodiversity data. As a component of such a recognition mechanism, we propose the development of the Data Usage Index (DUI) to demonstrate to data publishers that their efforts of creating biodiversity datasets have impact by being accessed and used by a wide spectrum of user communities.</p> <p>Discussion</p> <p>We propose and give examples of a range of 14 absolute and normalized biodiversity dataset usage indicators for the development of a DUI based on search events and dataset download instances. The DUI is proposed to include relative as well as species profile weighted comparative indicators.</p> <p>Conclusions</p> <p>We believe that in addition to the recognition to the data publisher and all players involved in the data life cycle, a DUI will also provide much needed yet novel insight into how users use primary biodiversity data. A DUI consisting of a range of usage indicators obtained from the GBIF network and other relevant access points is within reach. The usage of biodiversity datasets leads to the development of a family of indicators in line with well known citation-based measurements of recognition.</p

An adaptive technique for content-based image retrieval

We discuss an adaptive approach towards Content-Based Image Retrieval. It is based on the Ostensive Model of developing information needs—a special kind of relevance feedback model that learns from implicit user feedback and adds a temporal notion to relevance. The ostensive approach supports content-assisted browsing through visualising the interaction by adding user-selected images to a browsing path, which ends with a set of system recommendations. The suggestions are based on an adaptive query learning scheme, in which the query is learnt from previously selected images. Our approach is an adaptation of the original Ostensive Model based on textual features only, to include content-based features to characterise images. In the proposed scheme textual and colour features are combined using the Dempster-Shafer theory of evidence combination. Results from a user-centred, work-task oriented evaluation show that the ostensive interface is preferred over a traditional interface with manual query facilities. This is due to its ability to adapt to the user's need, its intuitiveness and the fluid way in which it operates. Studying and comparing the nature of the underlying information need, it emerges that our approach elicits changes in the user's need based on the interaction, and is successful in adapting the retrieval to match the changes. In addition, a preliminary study of the retrieval performance of the ostensive relevance feedback scheme shows that it can outperform a standard relevance feedback strategy in terms of image recall in category search

Monitoring retinal changes with optical coherence tomography predicts neuronal loss in experimental autoimmune encephalomyelitis.

BACKGROUND:Retinal optical coherence tomography (OCT) is a clinical and research tool in multiple sclerosis, where it has shown significant retinal nerve fiber (RNFL) and ganglion cell (RGC) layer thinning, while postmortem studies have reported RGC loss. Although retinal pathology in experimental autoimmune encephalomyelitis (EAE) has been described, comparative OCT studies among EAE models are scarce. Furthermore, the best practices for the implementation of OCT in the EAE lab, especially with afoveate animals like rodents, remain undefined. We aimed to describe the dynamics of retinal injury in different mouse EAE models and outline the optimal experimental conditions, scan protocols, and analysis methods, comparing these to histology to confirm the pathological underpinnings. METHODS:Using spectral-domain OCT, we analyzed the test-retest and the inter-rater reliability of volume, peripapillary, and combined horizontal and vertical line scans. We then monitored the thickness of the retinal layers in different EAE models: in wild-type (WT) C57Bl/6J mice immunized with myelin oligodendrocyte glycoprotein peptide (MOG35-55) or with bovine myelin basic protein (MBP), in TCR2D2 mice immunized with MOG35-55, and in SJL/J mice immunized with myelin proteolipid lipoprotein (PLP139-151). Strain-matched control mice were sham-immunized. RGC density was counted on retinal flatmounts at the end of each experiment. RESULTS:Volume scans centered on the optic disc showed the best reliability. Retinal changes during EAE were localized in the inner retinal layers (IRLs, the combination of the RNFL and the ganglion cell plus the inner plexiform layers). In WT, MOG35-55 EAE, progressive thinning of IRL started rapidly after EAE onset, with 1/3 of total loss occurring during the initial 2 months. IRL thinning was associated with the degree of RGC loss and the severity of EAE. Sham-immunized SJL/J mice showed progressive IRL atrophy, which was accentuated in PLP-immunized mice. MOG35-55-immunized TCR2D2 mice showed severe EAE and retinal thinning. MBP immunization led to very mild disease without significant retinopathy. CONCLUSIONS:Retinal neuroaxonal damage develops quickly during EAE. Changes in retinal thickness mirror neuronal loss and clinical severity. Monitoring of the IRL thickness after immunization against MOG35-55 in C57Bl/6J mice seems the most convenient model to study retinal neurodegeneration in EAE