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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.

2019

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Abstract

Boreal and temperate forests cover a large part of the Earth. Forest ecosystems are a key focus for research because of their role in the carbon (C) balance and cycle. Increasing atmospheric temperatures, different disturbances (fire, storm and insects) and forest management (clear-cutting) will change considerably the C status of forest ecosystems. Using the eddy covariance (EC) method, we can define interactions among environmental factors that influence the C-balance and whether a forest ecosystem is functioning as a C-sink or C-source or possibly is C-neutral. In our review of published studies of different disturbances, we found that most of the post-disturbance studies based on EC method focused on the effects of forest fire and clear-cutting, only a few studies studies focused on the effects of storms and insects. Generally a forest is a C-source until several years after disturbance and then a forest is able to absorb C and become a C-sink. Recovery to C-sink status required up to 20 years in clear-cut areas. Recovery following wildfire disturbance was much longer, possibly more than 50 years. Recovery to C-sink status required approximately 5 years after storm and insect outbreak, however we can not predict overall recovery period because of the missing data.

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Abstract

Aim: Many countries lack informative, high‐resolution, wall‐to‐wall vegetation or land cover maps. Such maps are useful for land use and nature management, and for input to regional climate and hydrological models. Land cover maps based on remote sensing data typically lack the required ecological information, whereas traditional field‐based mapping is too expensive to be carried out over large areas. In this study, we therefore explore the extent to which distribution modelling (DM) methods are useful for predicting the current distribution of vegetation types (VT) on a national scale. Location: Mainland Norway, covering ca. 324,000 km2. Methods: We used presence/absence data for 31 different VTs, mapped wall‐to‐wall in an area frame survey with 1081 rectangular plots of 0.9 km2. Distribution models for each VT were obtained by logistic generalised linear modelling, using stepwise forward selection with an F‐ratio test. A total of 116 explanatory variables, recorded in 100 m × 100 m grid cells, were used. The 31 models were evaluated by applying the AUC criterion to an independent evaluation dataset. Results: Twenty‐one of the 31 models had AUC values higher than 0.8. The highest AUC value (0.989) was obtained for Poor/rich broadleaf deciduous forest, whereas the lowest AUC (0.671) was obtained for Lichen and heather spruce forest. Overall, we found that rare VTs are predicted better than common ones, and coastal VTs are predicted better than inland ones. Conclusions: Our study establishes DM as a viable tool for spatial prediction of aggregated species‐based entities such as VTs on a regional scale and at a fine (100 m) spatial resolution, provided relevant predictor variables are available. We discuss the potential uses of distribution models in utilizing large‐scale international vegetation surveys. We also argue that predictions from such models may improve parameterisation of vegetation distribution in earth system models.

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Abstract

In many areas where spring is wet, fungicides are applied in relation to rain events that trigger ejection of ascospores of Venturia inaequalis, which cause primary infections of apple scab. Past studies established the rate of ejection during rain in relation to light and temperature, and determined the wetting time required for infection. Simulation software uses this information to calculate risk and help time sprays accordingly. However, the distribution of the infection time required by a population of spores landed on leaves was never studied, and assumptions were used. To estimate this, we inoculated ascospores of V. inaequalis on potted trees at different temperatures for specific wetting times. Lesions were enumerated after incubation. Lesions increased with wetness time and leveled off once the slowest spores infected the host, closely matching the monomolecular model. Wetness hours were best adjusted for temperature using the Yin equation. The minimum infection time on the youngest leaves was about 5 h, matching results from previous studies, whereas half the lesions appeared after 7 h of infection. Infection times for leaves with ontogenic resistance were longer. Our results improve current software estimates and may improve spraying decisions.