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
Abstract
Introductions of the pine wood nematode (PWN), which causes Pine Wilt Disease (PWD), have devastating effects on pine forests in regions with susceptible host trees under suitable climate conditions. Norwegian authorities have proposed a contingency plan if PWN is detected in Norway. We compare the costs of implementing this plan with the costs of further spread and damage of PWN under two climate change scenarios: present and the most likely future climate. With the present climate, PWD will not occur in Norway. Under climatic change, the cost of PWD damage is approximately 0.078–0.157 million NOK (0.01–0.02 million Euros) estimated as net present value with 2 and 4% p.a. discount rate. In contrast, the corresponding costs of implementing the suggested contingency plan will be 1.7–2.2 billion NOK (0.2–0.25 billion Euros). These costs are caused by reduced income from industrial timber production and the costs of the eradication measures. Costs related to reduced recreation or biodiversity are expected to be very high, but are not included in the above estimates. Many of the factors in the analysis are burdened with high uncertainty, but sensitivity analyses indicate that the results are rather robust even for drastic changes in assumptions. The results suggest that there is a need to revise the current PWN contingency plan in Norway.
Authors
Dan Johan Weydahl Knut Eldhuset Svein Solberg Ole Morten OlsenAbstract
No abstract has been registered
Authors
Asbjørn Moen Liv Sigrid NilsenAbstract
No abstract has been registered
Authors
Merete DeesAbstract
No abstract has been registered
Abstract
The overall goal is to professionalize and strengthen the disseminating and communicating elements of protected areas in Vietnam in order to increase the impacts of projects, and to establish a set of “best practise” recommendations/manual that can be common protected areas. A workshop and a training course has been conducted, and the manual is planned to be completed and tested late 2013.
Abstract
No abstract has been registered
Authors
Stehane Dray Raphaël Pélissier Pierre Couteron Marie-Josée Fortin Pierre Legendre Pedro R. Peres-Neto Edwige Bellier Roger Bivand F. Guillaume Blanchet Miquel De Cáceres Anne-Béatrice Dufour Einar Heegaard Thibaut Jombart François Munoz Jari Oksanen Jean Thioulouse Helene H. WagnerAbstract
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.
Authors
Klaus Mittenzwei Tim JoslingAbstract
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.
Authors
Jari Vauhkonen Liviu Theodor Ene Sandeep Gupta Johannes Heinzel Johan Holmgren Juho Pitkänen Svein Solberg Yunsheng Wang Holger Weinacker Marius Hauglin Vegard Lien Petteri Packalén Terje Gobakken Barbara Koch Erik Næsset Timo Tokola Matti MaltamoAbstract
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.
Authors
Paul Eric AspholmAbstract
No abstract has been registered