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.
2017
Abstract
Forest stands are important units of management. A stand-by-stand estimation of the mean and variance of an attribute of interest (Y) remains a priority in forest enterprise inventories. The advent of powerful and cost effective remotely sensed auxiliary variables (X) correlated with Y means that a census of X in the forest enterprise is increasingly available. In combination with a probability sample of Y, the census affords a modeldependent stand-level inference. It is important, however, that the sampling design affords an estimation of possible stand-effects in the model linking X to Y.We demonstrate, with simulated data, that failing to quantify non-zero stand-effects in the intercept of a linear population-level model can lead to a serious underestimation of the uncertainty in a model-dependent estimate of a stand mean, and by extension a confidence interval with poor coverage.We also provide an approximation to the variance of stand-effects in an intercept for the case when a sampling design does not afford estimation. Furthermore, we propose a method to correct a potential negative bias in an estimate of the variance of stand-effects when a sampling design prescribes few stands with small within-stand sample sizes.
Abstract
Estimates of stand averages are needed by forest management for planning purposes. In forest enterprise inventories supported by remotely sensed auxiliary data, these estimates are typically derived exclusively from a model that does not consider stand effects in the study variable. Variance estimators for these means may seriously underestimate uncertainty, and confidence intervals may be too narrow when a model used for computing a stand mean omits a nontrivial stand effect in one or more of the model parameters, a nontrivial spatial distance dependent autocorrelation in the model residuals, or both. In simulated sampling from 36 populations with stands of different sizes and differing with respect to (i) the correlation between a study variable (Y) and two auxiliary variables (X), (ii) the magnitude of stand effects in the intercept of a linear population model linking X to Y, and (iii) a first-order autoregression in Y and X, we learned that none of the tested designs provided reliable estimates of the within-stand autocorrelation among model residuals. More-reliable estimates were possible from stand-wide predictions of Y. The anticipated bias in an estimated autoregression parameter had a modest influence on estimates of variance and coverage of nominal 95% confidence intervals for a synthetic stand mean.
Abstract
No abstract has been registered
Authors
Arne SteffenremAbstract
No abstract has been registered
Abstract
Tick-borne fever (TBF) is stated as one of the main disease challenges in Norwegian sheep farming during the grazing season. TBF is caused by the bacterium Anaplasma phagocytophilum that is transmitted by the tick Ixodes ricinus. A sustainable strategy to control tick-infestation is to breed for genetically robust animals. In order to use selection to genetically improve traits we need reliable estimates of genetic parameters. The standard procedures for estimating variance components assume a Gaussian distribution of the data. However, tick-count data is a discrete variable and, thus, standard procedures using linear models may not be appropriate. Thus, the objectives of this study were twofold: 1) to compare four alternative non-linear models: Poisson, negative binomial, zero-inflated Poisson and zero-inflated negative binomial based on their goodness of fit for quantifying genetic variation, as well as heritability for tick-count and 2) to investigate potential response to selection against tick-count based on truncation selection given the estimated genetic parameters from the best fit model. Our results showed that zero-inflated Poisson was the most parsimonious model for the analysis of tick count data. The resulting estimates of variance components and high heritability (0.32) led us to conclude that genetic determinism is relevant on tick count. A reduction of the breeding values for tick-count by one sire-dam genetic standard deviation on the liability scale will reduce the number of tick counts below an average of 1. An appropriate breeding scheme could control tick-count and, as a consequence, probably reduce TBF in sheep.
Authors
Gry AlfredsenAbstract
No abstract has been registered
Authors
Yuka Kojima Aniko Varnai Takuya Ishida Naoki Sunagawa Dejan Petrovic Kiyohiko Igarashi Jody Jellison Barry Goodell Gry Alfredsen Bjørge Westereng Vincent Eijsink Makoto YoshidaAbstract
No abstract has been registered
Authors
Aniko Varnai Olav Aaseth Hegnar Dejan Petrovic Barry Goodell Gry Alfredsen Vincentius Gerardus Henricus EijsinkAbstract
No abstract has been registered
Authors
Linda Meyer-Veltrup Christian Brischke Gry Alfredsen Miha Humar Per Otto Flæte Tord Isaksson Pia Larsson Brelid Mats Westin Jöran JermerAbstract
Comprehensive approaches to predict performance of wood products are requested by international standards, and the first attempts have been made in the frame of European research projects. However, there is still an imminent need for a methodology to implement the durability and moisture performance of wood in an engineering design method and performance classification system. The aim of this study was therefore to establish an approach to predict service life of wood above ground taking into account the combined effect of wetting ability and durability data. A comprehensive data set was obtained from laboratory durability tests and still ongoing field trials in Norway, Germany and Sweden. In addition, four different wetting ability tests were performed with the same material. Based on a dose– response concept, decay rates for specimens exposed above ground were predicted implementing various indicating factors. A model was developed and optimised taking into account the resistance of wood against soft, white and brown rot as well as relevant types of water uptake and release. Decay rates from above-ground field tests at different test sites in Norway were predicted with the model. In a second step, the model was validated using data from laboratory and field tests performed in Germany and Sweden. The model was found to be fairly reliable, and it has the advantage to get implemented into existing engineering design guidelines. The approach at hand might furthermore be used for implementing wetting ability data into performance classification as requested by European standardisation bodies.
Abstract
No abstract has been registered