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.
2014
Forfattere
Aksel GranhusSammendrag
For å kontrollere at miljøhensyn ivaretas i forbindelse med hogst har skogbruksmyndighetene siden 1994 gjennomført en årlig resultatkontroll blant et tilfeldig utvalg skogeiere. En gjennomgang av status og utviklingstrekk fra kontrollen tyder på en positiv utvikling for enkelte miljøhensynsindikatorer, slik som gjensetting av livsløpstrær og omfang av arealer med miljøregistreringer før hogst. For andre parametere, slik som bruk av lukkede hogster, er det vanskelig å peke på tydelige endringer.
Forfattere
Aksel GranhusSammendrag
Det er ikke registrert sammendrag
Sammendrag
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Sammendrag
In an attempt to discern stochastic and deterministic parts of measured signals, we analyze time series from the viewpoint of ordinal pattern statistics. After choosing a suitable embedding dimension $D$, the occurrencies of all $D!$ patterns form a probability distribution $P$. The latter is input to information and complexity functionals describing, e.g., chaotic regimes or stochastic properties due to long-range correlations. Here, we use an information quantifier which is local in pattern probability space, the Fisher information $F$. This is calculable only after fixing a pattern coding scheme, i.e. numbering each and every pattern. It has been demonstrated that $F$ discerns different dynamic regimes for the logistic map to a certain extent; however, this depends on the details of the coding scheme. Here, we seek to find an optimal coding scheme for long-range correlated stochastic processes, mimicking many records e.g. from the geosciences. To increase the contrast between colored noise and deterministic processes, $F$ should be minimal for the former. Structurally similar ordinal patterns should be located adjacent to each other. Similarity is related to the number of inversions in the respective patterns. In practical terms, it is impossible to try all $D!!$ coding schemes whenever$D > 3$; however, we demonstrate a classification of coding schemes into equivalence classes based on the number of "jumps" in the patterns. These are used to improve the Keller and Lehmer coding schemes. The approach has a potential to provide an analytical understanding of the Fisher information for stochastic processes. Results for these optimizations will be shown for both the logistic map and colored ($k$-) noise. As a byproduct, an innovative method to estimate the scaling exponent $k$ emerges. Finally, we comment shortly on the importance of finite size effects, which is always an issue when dealing with observed data.
Sammendrag
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Sammendrag
The analysis of temporal geospatial data has provided important insights into global vegetation dynamics, particularly the interaction among different variables such as precipitation and vegetation indices. Nevertheless, this analysis is not a straightforward task due to the complex relationships among different systems driving the dynamics of the observed variables. Aiming at automatically extracting information from temporal geospatial data, we propose a new approach to detect stochastic and deterministic patterns embedded into time series and illustrate its effectiveness through an analysis of global geospatial precipitation and vegetation data captured over a 14 year period. By knowing such patterns, we can find similarities in the behavior of different systems even if these systems are characterized by different dynamics. In addition, we developed a novel determinism measure to evaluate the relative contribution of stochastic and deterministic patterns in a time series. Analyses showed that this measure permitted the detection of regions on the global map where the radiation absorbed by the vegetation and the incidence of rain occur with similar patterns of stochasticity. The methods developed in this study are generally applicable to any spatiotemporal data set and may be of particular interest for the analysis of the vast amount of remotely sensed geospatial data currently being collected routinely as part of national and international monitoring programs.
Foredrag – Hva forteller modellene våre?
Silje Skår, Susanne Eich-Greatorex, Trine Aulstad Sogn, ...
Sammendrag
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Sammendrag
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