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
Authors
Jihong Liu ClarkeAbstract
No abstract has been registered
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Abstract
The Norwegian National Forest Inventory (NNFI) provides estimates of forest parameters on national and regional scales by means of a systematic network of permanent sample plots. One of the biggest challenges for the NNFI is the interest in forest attribute information for small sub-populations such as municipalities or protected areas. Frequently, too few sampled observations are available for such small areas to allow estimates with acceptable precision. However, if an auxiliary variable exists that is correlated with the variable of interest, small area estimation (SAE) techniques may provide means to improve the precision of estimates. The study aimed at estimating the mean above-ground forest biomass for small areas with high precision and accuracy, using SAE techniques. For this purpose, the simple random sampling (SRS) estimator, the generalized regression (GREG) estimator, and the unit-level empirical best linear unbiased prediction (EBLUP) estimator were compared. Mean canopy height obtained from a photogrammetric canopy height model (CHM) was the auxiliary variable available for every population element. The small areas were 14 municipalities within a 2,184 km2 study area for which an estimate of the mean forest biomass was sought. The municipalities were between 31 and 527 km2 and contained 1–35 NNFI sample plots located within forest. The mean canopy height obtained from the CHM was found to have a strong linear correlation with forest biomass. Both the SRS estimator and the GREG estimator result in unstable estimates if they are based on too few observations. Although this is not the case for the EBLUP estimator, the estimators were only compared for municipalities with more than five sample plots. The SRS resulted in the highest standard errors in all municipalities. Whereas the GREG and EBLUP standard errors were similar for small areas with many sample plots, the EBLUP standard error was usually smaller than the GREG standard error. The difference between the EBLUP and GREG standard error increased with a decreasing number of sample plots within the small area. The EBLUP estimates of mean forest biomass within the municipalities ranged between 95.01 and 153.76 Mg ha−1, with standard errors between 8.20 and 12.84 Mg ha−1.
Authors
Juliana PerminowAbstract
No abstract has been registered
Abstract
The objective of this paper is to examine a method for estimation of land cover statistics for local environments from available area frame surveys of larger, surrounding areas. The method is a simple version of the small-area estimation methodology. The starting point is a national area frame survey of land cover. This survey is post-stratified using a coarse land cover map based on topographic maps and segmentation of satellite images. The approach is to describe the land cover composition of each stratum and subsequently use the results to calculate land cover statistics for a smaller area where the relative distribution of the strata is known. The method was applied to a mountain environment in Gausdal in Eastern Norway and the result was compared to reference data from a complete in situ land cover map of the study area. The overall correlation (Pearson’s rho) between the observed and the estimated land cover figures was r = 0.95. The method does not produce a map of the target area and the estimation error was large for a few of the land cover classes. The overall conclusion is, however, that the method is applicable when the objective is to produce land cover statistics and the interest is the general composition of land cover classes – not the precise estimate of each class. The method will be applied in outfield pasture management in Norway, where it offers a cost-efficient way to screen the management units and identify local areas with a land cover composition suitable for grazing. The limited resources available for in situ land cover mapping can then be allocated efficiently to in-depth studies of the areas with the highest grazing potential. It is also expected that the method can be used to compile land cover statistics for other purposes as well, provided that the motivation is to describe the overall land cover composition and not to provide exact estimates for the individual land cover classes.
Abstract
Herbivorous insects use information about volatile substances to select their host plants. The possibility that insects use these volatiles to assess the infection status of a host plant has rarely been tested. The assessment of host status via olfaction may allow a more successful allocation of time and energy towards the procurement of valuable resources for the offspring. We hypothesized that olfactory cues play a role in providing an herbivorous insect with information about the health status of a potential host plant. To test this hypothesis, we compared the attraction and oviposition response of the grapevine moth, Lobesia botrana, to healthy grapes, Vitis vinifera, with the response to grapes infected with a phytopathogenic fungus, Botrytis cinerea. The fungal infection elicited substantial reductions in both attraction from a distance and oviposition on the host. By preventing contact with the fruits, we found that volatiles from the infected grapes were the signal eliciting the observed behaviour. Experiments with a synthetic compound, 3-methyl-1-butanol, identified in the odour of infected grapes, confirmed the essential function of olfactory cues in this process, both in the laboratory and in the field. In our system, the avoidance of a diseased plant supported the preference performance hypothesis in L. botrana. Results are discussed in relation to the role of fungal volatiles in plant–insect relationships.
Authors
Vigdis Vandvik Joachim Spindelböck Zöe Cook Matthew I. Daws Einar Heegaard Inger Elisabeth Måren Liv Guri VelleAbstract
No abstract has been registered
Authors
Arnstein Øvrum Kyrre RickertsenAbstract
No abstract has been registered
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Abstract
No abstract has been registered