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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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Sammendrag

Species spatial distributions are the result of population demography, behavioral traits, and species interactions in spatially heterogeneous environmental conditions. Hence the composition of species assemblages is an integrative response variable, and its variability can be explained by the complex interplay among several structuring factors. The thorough analysis of spatial variation in species assemblages may help infer processes shaping ecological communities. We suggest that ecological studies would benefit from the combined use of the classical statistical models of community composition data, such as constrained or unconstrained multivariate analyses of site-by-species abundance tables, with rapidly emerging and diversifying methods of spatial pattern analysis. Doing so allows one to deal with spatially explicit ecological models of beta diversity in a biogeographic context through the multiscale analysis of spatial patterns in original species data tables, including spatial characterization of fitted or residual variation from environmental models. We summarize here the recent progress for specifying spatial features through spatial weighting matrices and spatial eigenfunctions in order to define spatially constrained or scale-explicit multivariate analyses. Through a worked example on tropical tree communities, we also show the potential of the overall approach to identify significant residual spatial patterns that could arise from the omission of important unmeasured explanatory variables or processes. ecological community; multivariate spatial data; ordination; spatial autocorrelation; spatial connectivity; spatial eigenfunction; spatial structure; spatial weight.

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Sammendrag

Both the OECD and the WTO have accumulated systematic data on the magnitude of support going to farmers as a result of farm policies. The datasets are collected for different purposes but both give a detailed picture of the evolution of these policies. This paper extends recent work on the compatibility or otherwise of these two attempts at policy monitoring by considering the categorization of individual policy instruments in Norway, Switzerland, the US and the EU. The results show how the OECD data set, particularly with respect to the link between direct payments and production requirements, complements that of the WTO. Many payments classified as in the WTO Green Box require production, raising the possibility that they may not be trade‐neutral. Though the issue of correct notifications to the WTO is the province of lawyers the implications for modeling and policy analysis is more interesting to economists. And the broader question of improving the consistency of the two datasets is of importance in the quest for transparency.

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Sammendrag

Airborne laser scanning data and corresponding field data were acquired from boreal forests in Norway and Sweden, coniferous and broadleaved forests in Germany and tropical pulpwood plantations in Brazil. Treetop positions were extracted using six different algorithms developed in Finland, Germany, Norway and Sweden, and the accuracy of tree detection and height estimation was assessed. Furthermore, the weaknesses and strengths of the methods under different types of forest were analyzed. The results showed that forest structure strongly affected the performance of all algorithms. Particularly, the success of tree detection was found to be dependent on tree density and clustering. The differences in performance between methods were more pronounced for tree detection than for height estimation. The algorithms showed a slightly better performance in the conditions for which they were developed, while some could be adapted by different parameterization according to training with local data. The results of this study may help guiding the choice of method under different forest types and may be of great value for future refinement of the single-tree detection algorithms.

Sammendrag

This study examines already existing guidelines for the sustainable removal of slash from forests for bioenergy use. Existing guidelines from some countries, states and provinces with forest ecosystems comparable to Norways (Sweden, Finland, the U.K., Ireland, Minnesota, New Hampshire and British Columbia) are compared with the Norwegian Living Forests (LF) and Debio (ecological forestry) guidelines. The aim is to identify areas where the Norwegian guidelines could be further developed.

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Sammendrag

Thirteen Nordic stand growth models have been validated by use of a test data set from long-term research plots in Norway. The evaluated data was from time-series of even-aged, pure stands of Norway spruce, Scots pine and birch (silver birch and downy birch). In selected models from Finland, Norway and Sweden measures of site productivity, mean tree size and various stand characteristics are represented. Different models display both strengths and weaknesses in their predicting ability. Several measures of precision and bias have been calculated and the models are ranked due to their performance. We observed site quality, stand density and average tree size as the three main components in the models. Basal area increment model for spruce from Sweden had the lowest standard deviation with 23%. The mean R2 between residuals and stand characteristics from this model was also low (1.3%), which indicates that independent variables are well included. For Scots pine and birch, Finnish volume increment models showed the best fit to the Norwegian test data, with a R2 between residuals and stand characteristics of 2.8 and 6.7%, respectively. Several of the models from Sweden and Finland predicted the growth as well as stand models frequently in use in Norway. The results indicated that similar forest conditions and traditional even-aged forest management practice in the Nordic countries could be seen as a suitable basis for developing a joint family of growth models. By careful recalibration of existing models, a reasonable accuracy could be achieved and the prediction bias could be reduced.

Sammendrag

Selective cutting and other continuous cover forestry systems may be used in spruce forests where for instance environmental or recreational considerations are more important than forest production. However, in order for this system to be sustainable, successful regeneration must be achieved. The supply of both light and below-ground resources may influence the growth and development of seedlings. If a diverse tree species composition is desirable, knowledge of the gap sizes necessary to sustain seedling survival and growth of different species is important. We studied the growth of Norway spruce (Picea abies) and Scots pine (Pinus sylvestris) seedlings in the understory, using two Norway spruce sites with selective cutting and group fellings in SE Norway. 4-week old seedlings (henceforth: mini seedlings) were planted in plots with and without trenching in gaps of four different sizes, ranging from 20 to 500 m2. In addition, commercial seedlings of the two species were planted pairwise across the sites. After three years the mini seedlings were dug up and measured, while the survival and growth of the commercial seedlings were followed for eight years. Differences in seedling survival and growth characteristics due to gap size and (for mini seedlings) trenching were analysed using GLM. Mortality was high, especially for pine seedlings. This was due to grazing as well as competition for light and nutrients. Growth of both species was positively correlated with increasing gap size. This applied for height, diameter, shoot volume and needle biomass as well as total dry weight for both spruce and pine seedlings. However, trenching had a significant positive effect on growth too, also in the smallest gaps.