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.
2011
Forfattere
Alastair James Ward Anne-Kristin LøesSammendrag
No abstract has been registered
Forfattere
Sverre KobroSammendrag
No abstract has been registered
Forfattere
J. Pozdisêk Britt Henriksen B. Ponizil Anne-Kristin LøesSammendrag
No abstract has been registered
Forfattere
Espen Govasmark Jessica Stäb Børge Holen Douwe Hoornstra Tommy Nesbakk Mirja Salkinoja-SalonenSammendrag
No abstract has been registered
Forfattere
Erik Næsset Terje Gobakken Svein Solberg Timothy Gregoire Ross Nelson Göran Ståhl Dan Johan WeydahlSammendrag
There is a need for accurate inventory methods that produce relevant and timely information on the forest resources and carbon stocks for forest management planning and for implementation of national strategies under the United Nations Collaborative Program on Reduced Emissions from Deforestation and Forest Degradation in Developing Countries (REDD). Such methods should produce information that is consistent across various geographical scales. Airborne scanning Light Detection and Ranging (LiDAR) is among the most promising remote sensing technologies for estimation of forest resource information such as timber volume and biomass, while acquisition of three dimensional data with Interferometric Synthetic Aperture Radar (InSAR) from space is seen as a relevant option for inventory in the tropics because of its ability to “see through the clouds” and its potential for frequent updates at low costs. Based on a stratified probability sample of 201 field survey plots collected in a 960 km2 boreal forest area in Norway, we demonstrate how total above-ground biomass (AGB) can be estimated at three distinct geographical levels in such a way that the estimates at a smaller level always sum up to the estimate at a larger level. The three levels are (1) a district (the entire study area), (2) a village, local community or estate level, and (3) a stand or patch level. The LiDAR and InSAR data were treated as auxiliary information in the estimation. At the two largest geographical levels model-assisted estimators were employed. A model-based estimation was conducted at the smallest level. Estimates of AGB and corresponding error estimates based on (1) the field sample survey were compared with estimates obtained by using (2) LiDAR and (3) InSAR data as auxiliary information. For the entire study area, the estimates of AGB were 116.0, 101.2, and 111.3 Mg ha−1, respectively. Corresponding standard error estimates were 3.7, 1.6, and 3.2 Mg ha−1. At the smallest geographical level (stand) an independent validation on 35 large field plots was carried out. RMSE values of 17.1–17.3 Mg ha−1 and 42.6–53.2 Mg ha−1 were found for LiDAR and InSAR, respectively. A time lag of six years between acquisition of InSAR data and field inventory has introduced some errors. Significant differences between estimates and reference values were found, illustrating the risk of using pure model-based methods in the estimation when there is a lack of fit in the models. We conclude that the examined remote sensing techniques can provide biomass estimates with smaller estimated errors than a field-based sample survey. The improvement can be highly significant, especially for LiDAR.
Sammendrag
No abstract has been registered
Sammendrag
No abstract has been registered
Forfattere
Ram Prasad Sharma Andreas Brunner Tron Haakon Eid Bernt-Håvard ØyenSammendrag
We developed dominant height growth models for Norway spruce (Picea abies (L.) Karst.) and Scots pine (Pinus sylvestris L.) in Norway using national forest inventory (NFI) data. The data were collected for a different purpose which potentially causes problems for dominant height growth modelling due to short time series and large age errors. We used the generalized algebraic difference approach and fitted 15 different models using nested regression techniques. Despite the potential problems of NFI data the models fitted to these data were unbiased for most of the age and site index range covered by the NFI data when tested against independent data from long-term experiments (LTE). Biased predictions for young stands and better site indices that are better represented in the LTE data, led us to fit models to a combined data set for unbiased predictions across the total data range. The models fitted to the combined data that were unbiased with little residual variation when tested against an independent data set based on stem analysis of 73 sample trees from southeastern Norway. No indications of regional differences in dominant height growth across Norway were detected. We tested whether the better growing conditions during the short time series (22 years) of the NFI data had affected our dominant height growth models relative to long-term growing conditions, but found only minor bias. The combination with LTE data that have been collected during a longer period (91 years) reduced this potential bias. The dominant height growth models presented here can be used as potential height growth models in individual tree-based forest growth models or as site index models.
Sammendrag
1. Surrogate species measures of biodiversity (SSB) are used worldwide in conservation prioritisations. We address the important question whether the ideas behind SSB are consistent with current knowledge on distribution patterns of species, as reflected in theories of community assembly. 2. We investigated whether assumptions necessary for successful functioning of SSB (nested species assemblages, cross-taxon congruence, spatio-temporal consistency) were supported by predictions from either niche or neutral community models. 3. We found a general mismatch between ideas behind SSB and ecological community theory, except that SSB based on complementarity may be consistent with niche-based theory when gradients in species composition are strong. 4. Synthesis and applications. The lack of a necessary scientific foundation may explain the disappointing results of empirical tests of SSB. We argue that site selection should be based on costs and opportunities within complementary environmental/land units, rather than expensive inventories of unfounded surrogate species.
Sammendrag
No abstract has been registered