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.
2011
Abstract
Experiments were set up over two winter seasons on golf greens i the Nordic countries. Two mowing heights in the autumn and one late application of 0.2 kg N /100 m2 were examined for effects on winter survival and turf performance in the spring. There were small effects from mowing height, but partly significant positive effects of fertilization. The results form annual meadow grass (Poa annua) were not consistent, but red fescue (Festuca rubra), creeping bentgrass (Agrostis stolonifera) and velvet bent grass (A.canina) accorded.
Abstract
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Authors
Jihong Liu Clarke Carl Jonas Jorge Spetz Sissel Haugslien Merete Dees Roar Moe Dag-Ragnar BlystadAbstract
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Authors
Trygve S. Aamlid Frank Enger Gudni Thorvaldsson Jan Tangsveen Trond Olav Pettersen Anne SteensohnAbstract
This report gives results from the entire evaluation period 2007-2010 for a project evaluating turfgrass species and varieties for use on Scandinavian golf greens.
Authors
Holger LangeAbstract
Spatial dependencies among environmental variables are often quantified by spatial autocorrelation functions. The latter basically assume linearity and isotropy, requirements usually not satisfied for measured data. Typical symptoms of violated assumptions are biased parameter estimations. Relaxing the assumptions of linear dependencies and isotropy, we present a conceptual generalization of spatial analysis where locally varying anisotropies in the geographical space are uncovered by investigating nonlinear dependencies among observations. The framework is illustrated by generalizing two examples: distance decay relations and spatial filtering. The proposed alternative is based on geodesic ecological and anisotropic spatial distances.
Abstract
Long-term monitoring of headwater semi-natural catchments is used to document persistence and changes in ecosystems. At three headwater catchments in the Bramke basin in Northern Germany, physical and chemical variables in rainfall, soil solution from various depths (20–300 cm) and streamwater have been monitored. The Lange Bramke catchment is largely covered by a Norway spruce (Picea abies, Karst.) stand planted in the 1950ies. Over 29 years, 4310 water samples from streamwater and 5475 soil water samples were analysed for major constituents. Both linear methods (principal component analysis (PCA) and cross correlation (CC)) as well as non-linear methods (isometric feature mapping (ISOMAP) and maximum variance unfolding (MVU)) were used to analyze the spatiotemporal patterns of dissolved major ion concentrations in soil solution and streamwater. This approach provides a multiscale characterisation of links between soil water and streamwater at the catchment scale. Pattern identification augments the interpretation of processes in terms of transport and storage. The long time scales were dominated by trends in ions implicated in soil acidification. This reflects the decreasing input of acid deposition. At the annual scale, where hydrological effects dominate, each of the three adjacent catchments showed different patterns. Various empirical and process-based models have been applied in the past to the Bramke catchments. Results of the data-oriented approach can be used to indicate the potential and limits of process-oriented models for this data set.
Abstract
Remote sensing of the activity of vegetation in relation to environmental conditions provides an invaluable basis for investigating the spatiotemporal dynamics and patterns of variability for ecosystem processes. We investigate the fraction of Absorbed Photosynthetically Active Radiation (fAPAR) using SeaWiFS satellite observations from 1998 to 2005 and ancillary meteorological variables from the CRU-PIK dataset with a global coverage at a spatial resolution of 0.5o x 0.5o. A pixel-by-pixel spectral decomposition using Singular System Analysis leads to a global “classification” of the terrestrial biosphere according to prevalent time-scale dependent dynamics of fAPAR and its relation to meteorology. A complexity analysis and a combined subsignal extraction and dimensionality reduction reveals a series of dominant geographical gradients, separately for different time scales. At the annual scale, which explains around 50% of the fAPAR variability as a global average, patterns largely resemble the biomes of the world as mapped by biogeographical methods, and are driven by temperature and by pronounced rain seasons in the tropics. On shorter time scales, fAPAR fluctuations are exclusively driven by water supply, inducing, e.g., semiannual cycles in the equatorial belt of Africa or the Indo-Gangetic Plain. For some regions however, in particular South America, altitude, mean temperature, drought probability and fire occurrences are parameters that seem to shape the spatial patterns of fAPAR across time scales. Overall, we provide a first global multiscale characterization of fAPAR and highlight different mechanisms in land-surface-climate couplings.
Abstract
There is a great demand for involving rapid, non destructive and less time consuming methods for quick control and prediction of soil quality, environmental monitoring, and other precision measurements in agriculture. Near infrared reflectance spectroscopy (NIRS) is considered as an appropriate alternative method to conventional analytical methods for large scale measurements. The objective of this study was to investigate the possibilities of NIRS for prediction of some chemical properties of soil samples. A total of 97 samples from Stara Zagora, Kazanlak and Gurkovo region taken from the 0-40 cm layer were collected. Soil types were Luvisols, Vertisols, Fluvisols and Rankers. The samples were analyzed for total phosphorus by spectrometric determination of phosphorus soluble in sodium hydrogen carbonate solution, total nitrogen by Kjeldahl method, pH (H O)-potentiometrically and electrical conductivity (EC). 2 The spectral data of all air dried samples were measured using an Perkin Elmer Spectrum One NTS, FT-NIR Spectrometer, within the range from 700 to 2500 nm. Partial Least Squares (PLS) regression was used to built models to determine soil chemical parameters from the NIR spectra. Two-third of the samples were used as a calibration set and the remaining samples as independent validation test set. The best model was obtained for total nitrogen with a coefficient of determination r=0,91, standard error of calibration SEP=336 mg/kg, and the ratio of the standard variation of the reference data to the SEP, indicating the performance of the calibration, of RPD=2,3. The accuracy of prediction was poor for electrical conductivity. The results obtained clearly indicated that NIRS had the potential to predict some soil components rapidly and without sample preparation.
Abstract
A changing climate will likely influence the selection of tree species in the future, and this may in turn affect the size of the pools and fluxes of carbon. Tree species differ in growth rate, fine-root turnover and quality of litter and tend to produce different types of understory vegetation. In Sweden three tree species (Norway spruce [Picea abies] 43%, Scots pine [Pinus sylvestris] 39% and birch [Betula spp.] 11%) dominate. In the present study we used field experiments in southern Sweden to test if these tree species differed in root distribution and turnover.