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.
2012
Forfattere
Kjell Andreassen Bernt-Håvard ØyenSammendrag
Growth conditions in Fennoscandia are characterized by relatively short growth seasons and cold winters, from 130 growth days (T 5C) in the far north high mountains to more than 200 in south Sweden and Norway. Growth models from different regions predict different forest growth.In this study, we compare some models commonly applied in forest growth prognosis in pure even aged stands of Norway spruce, Scots pine and birch in Finland, Sweden and Norway. The objectives is to identify behavioural properties, accuracy and bias in selected Nordic growth models using a wide-ranging test data set from permanent research plots in Norway.Present tentative conclusions about the accuracy of growth outside the geographical range of the original base materials. With four different response variables in the tested models we emphasized relative deviations rather than absolute values as most suitable for comparisons. The models were compared by statistical tests, a visual inspection of the smoothed curve of the relative deviations in different stand properties and ranked due to their performance.We observed site index, stand density and mean tree size as the three main components in the models. For Norway spruce a basal area increment model 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 variables are well included in the model. For Scots pine and birch, Finnish percent volume growth 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 predict the growth as well as stand models frequently in use in Norway.
Forfattere
Kjell Andreassen Volkmar Timmermann Nicholas Clarke Erik Framstad Per Arild Aarrestad Vegar Bakkestuen Tonje Økland Jørn-Frode Nordbakken Ingvald Røsberg Inga E. Bruteig Marianne Evju John Atle Kålås Torgeir NygårdSammendrag
The report presents results for 2011 from three national monitoring programmes on long-range transboundary air pollution.
Sammendrag
Spredning er en grunnleggende egenskap hos alle levende organismer som gjør det mulig å kolonisere nye levesteder når de gamle forsvinner. Det har vært uttrykt bekymring for at skoglevende kryptogamer er begrenset av dårlig spredningsevne slik at de ikke overlever i dagens skoglandskap med korte omløpstider og store avvirkninger. De siste syv årene har vi gjennomført feltundersøkelser av sopp, lav og moser for å studere deres evne til å kolonisere nye miljøer i kulturskogen. Hovedfokus har vært på skogbruk i Skandinavia, og feltinnsatsen har vært konsentrert til Vestlandet og Østlandet. Komparative studier har vært gjort i Nord-Amerika, med feltturer til Island og Ny-Caledonia. I denne rapporten presenterer vi resultatene fra fi re delprosjekter, initiert og ledet av Biomangfold- gruppen ved Norsk institutt for skog og landskap. Prosjektene har hovedsakelig vært fi nansiert gjennom Norges forskningsråd (Spredningsprosjektet, 158848/I10) med forvaltningsstøtte fra Landbruks- og matdepartementet (MiS-prosjektet). [...]
Sammendrag
Det er ikke registrert sammendrag
Sammendrag
Phytosociological studies can be an important tool to detect temporal vegetation changes in response to global climate change. In this study, we present the results of a resurvey of a plot-based phytosociological study from Sikkilsdalen, central Norway, originally executed between 1922 and 1932. By using a detailed phytosociological study we are able to investigate several aspects of elevational shifts in species ranges. Here we tested for upward and downward shifts in observed upper and lower distribution limits of species, as well as changes in species optima along an elevational gradient, and related the observed range shifts to species traits that could explain the observed trends. More species shifted upwards than downwards, independently of whether we were investigating shifts in species\" upper or lower distribution ranges or in species optima. However, shifts in species upper range margins changed independently of their lower range margins. Linking different species traits to the magnitude of shifts we found that species with a higher preference for prolonged snow cover shifted upwards more in their upper elevational limits and in their optima than species that prefer a shorter snow cover, whereas no species traits were correlated with the magnitude of changes in lower limits. The observed change in species ranges concord both with studies on other mountains in the region and with studies from other alpine areas. Furthermore, our study indicates that different factors are influencing species ranges at the upper and lower range limits. Increased precipitation rates and increased temperatures are considered the most important factors for the observed changes, probably mainly through altering the pattern in snow cover dynamics in the area.
Sammendrag
Det er ikke registrert sammendrag
Sammendrag
Groundwater pollution by agrochemicals, degradation of soil quality and pollution of aquatic ecosystems by agricultural drainage waters have become an issue in the last decades. Flow processes in the vadose zone are closely related to these problems. In general, water flow in soils can be classified into two major categories: uniform and non-uniform (preferential) flow (In: U.S. National Committee for Rock Mechanics, Conceptual Models of Flow and Transport in the Fractured Vadose Zone, 2001, pp.149-187). The former describes a relatively slow movement of water through the porous soil matrix and can be modelled by Richard”s equation. The latter comprises all flow types where water bypasses a portion of the soil matrix and flows through localised (i.e. preferential) paths. Unlike uniform flow, preferential flow is hardly predictable because the assumptions of Richard”s equation of a homogeneous representative elementary volume characterised by a single value of water potential, water content and hydraulic conductivity are frequently violated (Eur J Soil Sci, 2007; 58:523-546)....
Sammendrag
A crucial process of the terrestrial carbon cycle is photosynthetic uptake through plants. This may be quantified by calculating the fraction of absorbed photosynthetic active radiation (fapar), based on multispectral reflectance properties of the earth surface. The fapar index is available with global coverage from satellite sensors.Here, we combine two satellite missions, SeaWifs on board OrbView2 and MERIS on board Envisat, to produce time series with 10 days resolution for a period of 14 years (19982011) at a spatial resolution of 0.5 latitude x 0.5 longitude. These more than 50000 individual time series represent a huge range of dynamical behavior with respect to variability, periodicities and correlation structure.To characterize differences as a function of spatial location or distance, we employ Recurrence Quantification Analysis (RQA) and Recurrence Network Analysis (RNA). Two strategies are followed. On one hand, RQA and network variables are calculated for individual time series using identical recurrence parameters, and compared to see whether differences between them resemble different climate regimes, biomes, plant functional types or landuse classes. On the other hand, a multivariate extension of RNA will be exploited to see whether networks within networks occur, i.e. whether RNA provides sufficient contrasts to discern different clusters of pixels on the globe.Taken together, the recurrence analysis might lead to a new classification of the terrestrial biosphere which in turn can be compared to existing partitioning based on climate and/or vegetation properties. A number of technical issues will be addressed as well, such as the impact of the finite length of the series (504 values each), the necessity to gapfill parts of the data, the stability of network variables against changes in the recurrence parameters, or the computational challenges involved in the multinetwork analysis of many series. http://dames.pik-potsdam.de/Abstracts.pdf
Sammendrag
Our aim is to investigate the temporal dynamics of the Fraction of Absorbed Photosynthetically Active Radiation (fAPAR) on a global scale and its relation to the main meteorological variables across space. We focus on complex patterns in time, which are neither regular (trend and seasonality) nor random (noise), but somewhere in between. We quantify complexity and information content or entropy using methods from order statistics and complexity sciences.Time series with high entropy are difficult to predict, whereas time series with high complexity are difficult to describe. This leads to a spatially explicit characterization of complex patterns in a very sensitive way. We use FAPAR observations (SeaWiFS and MERIS, 1998 to 2012) along with gridded global surface air temperature, precipitation and shortwave radiation.All these time series are explored on a pixelbypixel basis and clustered according to a very recent classification system of the land surface. In addition, we quantify the time reversal asymmetry of these data. We compare environmental time series with data from a stochastic candidate process temporally symmetric and long range correlated artificial knoise.Results were plotted in the ComplexityversusEntropy plane (CH plane), showing the particular footprint of each variable in a very sensitive way. Visualized in world maps, results revealed unexpected complex pattern in some dry regions, in particular on pixels surrounding deserts and in eastern Sahara. In this respect, the results provide a new classification of the climate and the biosphere. http://dames.pik-potsdam.de/Abstracts.pdf
Forfattere
Holger LangeSammendrag
We calculate entropy and complexity of runoff time series and artificially generated series with long-range correlations. Entropy and complexity of data series may be represented against each other in a two-dimensional diagram which we will refer to as Complexity-Entropy Causality Plane, or CECP. We use a recently developed framework for these two indicators based on order statistics. It is well-known that runoff, as all other environmental time series actually measured, is a mixture of deterministic (signal) and stochastic (noise) parts, the latter due to noise inherent in the measurement process and externally induced by natural processes. The distinction between signal and noise is notoriously difficult and subject to much debate. In our approach, the observed series are compared to purely stochastic but long-range correlated processes, the k noise, where k is a parameter determining the strength of the correlations. Although these processes resemble runoff series in their correlation behavior and may be even tuned to any runoff series by changing the value of k, the CECP locations and in particular the order pattern statistics reveals qualitative differences between runoff and k noise. We use these differences to conclude on the deterministic nature of the (short-term) dynamics of the runoff time series. The proposed methodology also represents a stringent test bed for hydrological models.