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.
2013
Authors
Joachim Paul Spindelbøck Zöe Cook Matthew I. Daws Einar Heegaard Inger Elisabeth Måren Vigdis VandvikAbstract
Background and Aims: Across their range, widely distributed species are exposed to a variety of climatic and other environmental conditions, and accordingly may display variation in life history strategies. For seed germination in cold climates, two contrasting responses to variation in winter temperature have been documented: first, an increased ability to germinate at low temperatures (cold tolerance) as winter temperatures decrease, and secondly a reduced ability to germinate at low temperatures (cold avoidance) that concentrates germination towards the warmer parts of the season. Methods: Germination responses were tested for Calluna vulgaris, the dominant species of European heathlands, from ten populations collected along broad-scale bioclimatic gradients (latitude, altitude) in Norway, covering a substantial fraction of the species' climatic range. Incubation treatments varied from 10 to 25 °C, and germination performance across populations was analysed in relation to temperature conditions at the seed collection locations. Key Results: Seeds from all populations germinated rapidly and to high final percentages under the warmer incubation temperatures. Under low incubation temperatures, cold-climate populations had significantly lower germination rates and percentages than warm-climate populations. While germination rates and percentages also increased with seed mass, seed mass did not vary along the climatic gradients, and therefore did not explain the variation in germination responses. Conclusions: Variation in germination responses among Calluna populations was consistent with increased temperature requirements for germination towards colder climates, indicating a cold-avoidance germination strategy conditional on the temperature at the seeds' origin. Along a gradient of increasing temperatures this suggests a shift in selection pressures on germination from climatic adversity (i.e. low temperatures and potential frost risk in early or late season) to competitive performance and better exploitation of the entire growing season.
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Stefanos Xenarios Paul PavelicAbstract
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Authors
Ghislain Tchoromi Tepa-Yotto Trond Hofsvang Ignace Godonou Ingrid Tchibozo May SæthreAbstract
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When calculating the Bandt and Pompe ordinal pattern distribution from given time series at depth D, some of the D! patterns might not appear. This could be a pure finite size effect (missing patterns) or due to dynamical properties of the observed system (forbidden patterns). For pure noise, no forbidden patterns occur, contrary to deterministic chaotic maps. We investigate long time series of river runoff for missing patterns and calculate two global properties of their pattern distributions: the Permutation Entropy and the Permutation Statistical Complexity. This is compared to purely stochastic but long-range correlated processes, the k-noise (noise with power spectrum f−k), where k is a parameter determining the strength of the correlations. Although these processes closely resemble runoff series in their correlation behavior, the ordinal pattern statistics reveals qualitative differences, which can be phrased in terms of missing patterns behavior or the temporal asymmetry of the observed series. For the latter, an index is developed in the paper, which may be used to quantify the asymmetry of natural processes as opposed to artificially generated data.
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The distribution of Leiopus nebulosus (Linnaeus, 1758) and L. linnei Wallin, Nylander & Kvamme, 2009, in Norway is discussed and depicted. Observations of host trees as well as information of substrate qualities and phenology are included.
Abstract
An 11-year remotely sensed surface albedo dataset coupled with historical meteorological and stand-level forest management data for a variety of stands in Norway’s most productive logging region is used to develop regression models describing temporal changes in forest albedo following clear-cut harvest disturbance events. Datasets are grouped by dominant tree species, and two alternate multiple regression models are developed and tested following a potential-modifier approach. This result in models with statistically significant parameters (p < 0.05) that explain a large proportion of the observed variation, requiring a single canopy modifier predictor coupled with either monthly or annual mean air temperature as a predictor of a stand’s potential albedo. Models based on annual mean temperature predict annual albedo with errors (RMSE) in the range of 0.025–0.027, while models based on monthly mean temperature predict monthly albedo with errors ranging between of 0.057–0.065 depending on the dominant tree species. While both models have the potential to be transferable to other boreal regions with similar forest management regimes, further validation efforts are required. As active management of boreal forests is increasingly seen as a means to mitigate climate change, the presented models can be used with routine forest inventory and meteorological data to predict albedo evolution in managed forests throughout the region, which, together with carbon cycle modeling, can lead to more holistic climate impact assessments of alternative forest harvest scenarios and forest product systems.