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.
2013
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Syngenta’s GREENCAST model was used to predict timing of fungicide application against microdochium patch and pink snow mold caused by Microdochium nivale on an experimental golf green with annual bluegrass (Poa annua) at Bioforsk Landvik, Southern Norway from 5 Oct. 2012 until 1 June 2013. From 5 Oct. until snow covered the green on 2 Dec. 2012, application of the fungicides Headway (azoxystrobin + propiconazole) or Medallion (fludioxonil) only at GREENCAST high risk warnings resulted in equal control of microdohium patch with one less fungicide application than prophylactic application every third week, application at first sign of disease or application at GREENCAST medium risk warnings. The consequences for pinks snow mold in spring could not be evaluated as the turf was killed by the combination of ice encasement and low freezing temperatures during winter.
Abstract
Modelling stem taper and volume is crucial in many forest management and planning systems. Taper models are used for diameter prediction at any location along the stem of a sample tree. Furthermore, taper models are flexible means to provide information on the stem volume and assortment structure of a forest stand or other management units. Usually, taper functions are mean functions of multiple linear or nonlinear regression models with diameter at breast height and tree height as predictor variables. In large-scale inventories, an upper diameter is often considered as an additional predictor variable to improve the reliability of taper and volume predictions. Most studies on stem taper focus on accurately modelling the mean function; the error structure of the regression model is neglected or treated as secondary. We present a semi-parametric linear mixed model where the population mean diameter at an arbitrary stem location is a smooth function of relative height. Observed tree-individual diameter deviations from the population mean are assumed to be realizations of a smooth Gaussian process with the covariance depending on the sampled diameter locations. In addition to the smooth random deviation from the population average, we consider independent zero mean residual errors in order to describe the deviations of the observed diameter measurements from the tree-individual smooth stem taper. The smooth model components are approximated by cubic spline functions with a B-spline basis and a small number of knots. The B-spline coefficients of the population mean function are treated as fixed effects, whereas coefficients of the smooth tree-individual deviation are modelled as random effects with zero mean and a symmetric positive definite covariance matrix. The taper of a tree is predicted using an arbitrary number of diameter and corresponding height measurements at arbitrary positions along the stem to calibrate the tree-individual random deviation from the population mean estimated by the fixed effects. This allows a flexible application of the method in practice. Volume predictions are calculated as the integral over cross-sectional areas estimated from the calibrated taper curve. Approximate estimators for the mean squared errors of volume estimates are provided. If the tree height is estimated or measured with error, we use the “law of total expectation and variance” to derive approximate diameter and volume predictions with associated confidence and prediction intervals. All methods presented in this study are implemented in the R-package TapeR.
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Ievina SturiteAbstract
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Belen Cotes Linda-Marie Rännbäck Peter Andersson Nicolai Vitt Meyling Maria Björkman Birgitta RämertAbstract
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Authors
Alina Danielewska Nicholas Clarke Janusz Olejnik Karin Hansen Wim de Vries Lars Lundin Juha Pekka Tuovinen Richard Fischer Marek Urbaniak Elena PaolettiAbstract
Of a wide variety of international forest research and monitoring networks, several networks are dedicated to the effects of climate change on forests, while the effects of anthropogenic pollutants on forests have been a major area for both monitoring and research for decades. The large amounts of data already obtained within existing monitoring programmes and large-scale international projects can be used to increase understanding of the state and potential of forest mitigation and adaptation to climate change in a polluted environment, and a major challenge now is to evaluate and integrate the presently available databases. We present a meta-database with the main goal to highlight available data and integrate the information about research and monitoring of selected European Research and Monitoring Networks (ERMNs). Depending on the selected ERMNs, the list of variables and the measurement units differ widely in the databases. As a result, activities related to the identification, evaluation and integration of the presently available databases are important for the scientific community. Furthermore, and equally important, the recognition of current knowledge gaps and future needed research is made easier. This analysis suggests that: ground-level ozone is under-investigated, although it is one of the pollutants of greatest concern to forests; in addition to CO2, long-term other greenhouse gasses (GHG) flux measurements should be carried out; there is still a need of improving links between monitoring of atmospheric changes and impacts on forests; research-oriented manipulative experiments in the forests are missing.
Authors
Peder Gjerdrum Birger EikenesAbstract
Density is a fundamental softwood quality trait. The aim of this paper is to identify a spatial model for wood density variation in spruce stems, with the main focus on basic density. Six thousand 20-mm-wide cubes systematically sampled from 85 trees in western Norway were analysed. The overall radial density pattern was the J shape with local maximum in the pith and increasing density outwards from a minimum at some distance from the pith. The minimum appeared closer to the pith further up in the tree. The stochastic nature of the six tree-wise parameters defining density gradients from pith to surface and from base to top was analysed and described. The results provide information needed to simulate density variation inside stems and between stems in a population. Considering the fundamental influence of density on a range of wood traits, such simulation should be of great significance for scientific and industrial analyses.
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Human–bear conflicts occur frequently in the Pasvik Valley, Norway. We used a variantof the hair-trapping method with higher densities of traps (2.5 x 2.5 km grid) todetect brown bears moving near human settlements and livestock. We distributed 20hair traps for one month close to a farm with frequent observations of grazing bears.The study area consisted of one area close to the farm, and one adjacent area withoutsettlements. We collected 85 hair samples and identified 13 different individuals bySTR analysis. In the farm area, we detected 4 different males once, and a female thatwas detected in both areas. In comparison, nine bears (2 males and 7 females) weredetected for more than one week in the area without settlements, suggesting lowerroaming activity. Conclusively, hair trapping has the potential to survey bears at specificlocations of importance to the wildlife management.