Publikasjoner
NIBIOs ansatte publiserer flere hundre vitenskapelige artikler og forskningsrapporter hvert år. Her finner du referanser og lenker til publikasjoner og andre forsknings- og formidlingsaktiviteter. Samlingen oppdateres løpende med både nytt og historisk materiale. For mer informasjon om NIBIOs publikasjoner, besøk NIBIOs bibliotek.
2018
Forfattere
Signe Kynding Borgen Gry Alfredsen Johannes Breidenbach Lise Dalsgaard Gunnhild Søgaard Aaron SmithSammendrag
Det er ikke registrert sammendrag
Forfattere
Andreas Treu Katrin Zimmer Christian Brischke Erik Larnøy Lone Ross Foued Aloui Simon M Cragg Per Otto Flæte Miha Humar Mats Westin Luisa M. S. Borges John WilliamsSammendrag
Det er ikke registrert sammendrag
Sammendrag
Denne rapporten sammenstiller informasjon om tilstand og utviklingstendenser for foryngelse i skog, med utgangspunkt i data fra Resultatkartleggingen, Landsskogtakseringen og Økonomisystem for Skogordningene (ØKS). Oppdraget har videre omfattet å vurdere styrker og svakheter ved dagens systemer for innhenting av tilstandsdata om foryngelsesaktiviteten i Norge, og foreslå metoder og eventuelle verktøy som vil gi bedre oversikt over foryngelsestilstanden på årlig basis...
Sammendrag
Uganda designated 16% of its land as Protected Area (PA). The original goal was natural resources, habitat and biodiversity conservation. However, PAs also offer great potential for carbon conservation in the context of climate change mitigation. Drawing on a wall-to-wall map of forest carbon change for the entire Uganda, that was developed using two Digital Elevation Model (DEM) datasets for the period 2000–2012, we (1) quantified forest carbon gain and loss within 713 PAs and their external buffer zones, (2) tested variations in forest carbon change among management categories, and (3) evaluated the effectiveness of PAs and the prevalence of local leakage in terms of forest carbon. The net annual forest carbon gain in PAs of Uganda was 0.22 ± 1.36 t/ha, but a significant proportion (63%) of the PAs exhibited a net carbon loss. Further, carbon gain and loss varied significantly among management categories. About 37% of the PAs were “effective”, i.e., gained or at least maintained forest carbon during the period. Nevertheless, carbon losses in the external buffer zones of those effective PAs significantly contrast with carbon gains inside of the PA boundaries, providing evidence of leakage and thus, isolation. The combined carbon losses inside the boundaries of a large number of PAs, together with leakage in external buffer zones suggest that PAs, regardless of the management categories, are threatened by deforestation and forest degradation. If Uganda will have to benefit from carbon conservation from its large number of PAs through climate change mitigation mechanisms such as REDD+, there is an urgent need to look into some of the current PA management approaches, and design protection strategies that account for the surrounding landscapes and communities outside of the PAs.
Sammendrag
Det er ikke registrert sammendrag
Sammendrag
Det er ikke registrert sammendrag
Sammendrag
Økende etterspørsel etter bioenergi, biodrivstoff og andre biobaserte produkter, har gitt økt interesse for utnyttelse av sekundærråstoff fra trebaserte verdikjeder. Denne rapporten kartlegger hvilke sekundærråstoff som er tilgjengelige innenfor denne industrien, kvantifiserer årlig produksjonsvolum samt kartlegger kvalitet og anvendelsesområder for råvaren i Norge per i dag. Det finnes ikke detaljert nok statistikk tilgjengelig for å sette opp årlig mengdeutvikling for alle de ulike sekundærråstoffene fra trebaserte verdikjeder. For seks av kategoriene, anngitt med * under, er data derfor estimert for 2016 basert på data fra Tellnes et al. (2011). For mer presise data må flere detaljerte undersøkelser utføres.
Sammendrag
Det er ikke registrert sammendrag
Forfattere
Svein Solberg Johannes May Wiley Steven Bogren Johannes Breidenbach Torfinn Torp Belachew Gizachew ZelekeSammendrag
Monitoring changes in forest height, biomass and carbon stock is important for understanding the drivers of forest change, clarifying the geography and magnitude of the fluxes of the global carbon budget and for providing input data to REDD+. The objective of this study was to investigate the feasibility of covering these monitoring needs using InSAR DEM changes over time and associated estimates of forest biomass change and corresponding net CO2 emissions. A wall-to-wall map of net forest change for Uganda with its tropical forests was derived from two Digital Elevation Model (DEM) datasets, namely the SRTM acquired in 2000 and TanDEM-X acquired around 2012 based on Interferometric SAR (InSAR) and based on the height of the phase center. Errors in the form of bias, as well as parallel lines and belts having a certain height shift in the SRTM DEM were removed, and the penetration difference between X- and C-band SAR into the forest canopy was corrected. On average, we estimated X-band InSAR height to decrease by 7 cm during the period 2000–2012, corresponding to an estimated annual CO2 emission of 5 Mt for the entirety of Uganda. The uncertainty of this estimate given as a 95% confidence interval was 2.9–7.1 Mt. The presented method has a number of issues that require further research, including the particular SRTM biases and artifact errors; the penetration difference between the X- and C-band; the final height adjustment; and the validity of a linear conversion from InSAR height change to AGB change. However, the results corresponded well to other datasets on forest change and AGB stocks, concerning both their geographical variation and their aggregated values.
Sammendrag
In many applications, estimates are required for small sub-populations with so few (or no) sample plots that direct estimators that do not utilize auxiliary variables (e.g. remotely sensed data) are not applicable or result in low precision. This problem is overcome in small area estimation (SAE) by linking the variable of interest to auxiliary variables using a model. Two types of models can be distinguished based on the scale on which they operate: i) Unit-level models are applied in the well-known area-based approach (ABA) and are commonly used in forest inventories supported by fine-resolution 3D remote sensing data such as airborne laser scanning (ALS) or digital aerial photogrammetry (AP); ii) Area-level models, where the response is a direct estimate based on a sample within the domain and the explanatory variables are aggregated auxiliary variables, are less frequently applied. Estimators associated with these two model types can make use of sample plots within domains if available and reduce to so-called synthetic estimators in domains where no sample plots are available. We used both model types and their associated model-based estimators in the same study area with AP data as auxiliary variables. Heteroscedasticity, i.e. for continuous dependent variables typically an increasing dispersion of re- siduals with increasing predictions, is often observed in models linking field- and remotely sensed data. This violates the model assumption that the distribution of the residual errors is constant. Complying with model assumptions is required for model-based methods to result in reliable estimates. Addressing heteroscedasticity in models had considerable impacts on standard errors. When complying with model assumptions, the precision of estimates based on unit-level models was, on average, considerably greater (29%–31% smaller standard errors) than those based on area-level models. Area-level models may nonetheless be attractive because they allow the use of sampling designs that do not easily link to remotely sensed data, such as variable radius plots.