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.
2022
Authors
Daniel Liptzin Jens Boy John L. Campbell Nicholas Clarke Jean-Paul Laclau Roberto Godoy Sherri L. Johnson Klaus Kaiser Gene E. Likens Gunilla Pihl Karlsson Daniel Markewitz Michela Rogora Stephen D. Sebestyen James B. Shanley Elena Vanguelova Arne Verstraeten Wolfgang Wilcke Fred Worrall William H. McDowellAbstract
No abstract has been registered
Authors
Abdelhameed Elameen Denis Tourvieille de Labrouhe Emmanuelle Bret-Mestries Francois DelmotteAbstract
No abstract has been registered
Authors
Markus A. K. Sydenham Joseph Chipperfield Yoko L. Dupont Katrine Eldegard Stein Joar Hegland Henning Bang Madsen Anders Nielsen Jens M* Olesen Claus Rasmussen Trond Reitan Graciela Rusch Astrid Brekke Skrindo Zander VenterAbstract
No abstract has been registered
Authors
Vilde Lytskjold Haukenes Mikael Ohlson Johan Asplund Line Nybakken Ken Olaf Storaunet Jørund Rolstad Lisa ÅsgårdAbstract
No abstract has been registered
Authors
Vilde Lytskjold Haukenes Lisa Åsgård Johan Asplund Line Nybakken Jørund Rolstad Ken Olaf Storaunet Mikael OhlsonAbstract
Knowledge about the spatial variation of boreal forest soil carbon (C) stocks is limited, but crucial for establishing management practices that prevent losses of soil C. Here, we quantified the surface soil C stocks across small spatial scales, and aim to contribute to an improved understanding of the drivers involved in boreal forest soil C accumulation. Our study is based on C analyses of 192 soil cores, positioned and recorded systematically within a forest area of 11 ha. The study area is a south-central Norwegian boreal forest landscape, where the fire history for the past 650 years has been reconstructed. Soil C stocks ranged from 1.3 to 96.7 kg m−2 and were related to fire frequency, ecosystem productivity, vegetation attributes, and hydro-topography. Soil C stocks increased with soil nitrogen concentration, soil water content, Sphagnum- and litter-dominated forest floor vegetation, and proportion of silt in the mineral soil, and decreased with fire frequency in site 1, feathermoss- and lichen-dominated forest floor vegetation and increasing slope. Our results emphasize that boreal forest surface soil C stocks are highly variable in size across fine spatial scales, shaped by an interplay between historical forest fires, ecosystem productivity, forest floor vegetation, and hydro-topography.
Authors
Marian Schönauer Robert Prinz Kari Väätäinen Rasmus Astrup Dariusz Pszenny Harri Lindeman Dirk JaegerAbstract
Milder winters and extended wetter periods in spring and autumn limit the amount of time available for carrying out ground-based forest operations on soils with satisfactory bearing capacity. Thus, damage to soil in form of compaction and displacement is reported to be becoming more widespread. The prediction of trafficability has become one of the most central issues in planning of mechanized harvesting operations. The work presented looks at methods to model field measured spatio-temporal variations of soil moisture content (SMC, [%vol]) – a crucial factor for soil strength and thus trafficability. We incorporated large-scaled maps of soil characteristics, high-resolution topographic information – depth-to-water (DTW) and topographic wetness index – and openly available temporal soil moisture retrievals provided by the NASA Soil Moisture Active Passive mission. Time-series measurements of SMC were captured at six study sites across Europe. These data were then used to develop linear models, a generalized additive model, and the machine learning algorithms Random Forest (RF) and eXtreme Gradient Boosting (XGB). The models were trained on a randomly selected 10% subset of the dataset. Predictions of SMC made with RF and XGB attained the highest R2 values of 0.49 and 0.51, respectively, calculated on the remaining 90% test set. This corresponds to a major increase in predictive performance, compared to basic DTW maps (R2 = 0.022). Accordingly, the quality for predicting wet soils was increased by 49% when XGB was applied (Matthews correlation coefficient = 0.45). We demonstrated how open access data can be used to clearly improve the prediction of SMC and enable adequate trafficability mappings with high spatial and temporal resolution. Spatio-temporal modelling could contribute to sustainable forest management.
Abstract
No abstract has been registered
Abstract
Norway’s most common tree species, Picea abies (L.) Karst. (Norway spruce), is often infected with Heterobasidion parviporum Niemelä & Korhonen and Heterobasidion annosum (Fr.) Bref.. Because Pinus sylvestris L. (Scots pine) is less susceptible to rot, it is worth considering if converting rot-infested spruce stands to pine improves economic performance. We examined the economically optimal choice between planting Norway spruce and Scots pine for previously spruce-dominated clear-cut sites of different site indexes with initial rot levels varying from 0% to 100% of stumps on the site. While it is optimal to continue to plant Norway spruce in regions with low rot levels, shifting to Scots pine pays off when rot levels get higher. The threshold rot level for changing from Norway spruce to Scots pine increases with the site index. We present a case study demonstrating a practical method (“Precision forestry”) for determining the tree species in a stand at the pixel level when the stand is heterogeneous both in site indexes and rot levels. This method is consistent with the concept of Precision forestry, which aims to plan and execute site-specific forest management activities to improve the quality of wood products while minimising waste, increasing profits, and maintaining environmental quality. The material for the study includes data on rot levels and site indexes in 71 clear-cut stands. Compared to planting the entire stand with a single species, pixel-level optimised species selection increases the net present value in almost every stand, with average increase of approximately 6%.
Abstract
No abstract has been registered
Abstract
Book of Abstracts p. 225: Perennial sow-thistle (Sonchus arvensis L.) is a problematic weed in arable crops in northern Europe. To control S. arvensis, strategies which reduce both seeds and creeping root production are essential. Inducing repeated sprouting should result in depleting root reserves and reduction in the subsequent shoot emergence. Earlier studies of S. arvensis in the northern European countries have shown a restricted sprouting ability from July/August/ September to October/November. To better understand the sprouting patterns, we conducted joint outdoor pot experiments from March 2020 until July 2021 in three northern European regions: Northern Germany, Norway, and Finland. In each pot, root pieces of 5 cm from local plant material were planted at 5cm depth. Above-ground plants were cut at the soil surface in the growing season of 2020 at 1) flower-bud stage, 2) first visible open flowers, 3) start of seed production, and 4) withering stage. Shoots were counted monthly in 2020 and 2021. In the year 2020, in Germany, sprouting, flowering, seed-set, and withering started earlier than at the other two sites. Significantly more shoots showed up at the flower-bud stage in Germany and Finland compared to Norway. In Finland, significantly more shoots were observed at the later cutting stages compared to the first counts at the flower bud stage. As a subsequent effect, fewest shoots showed up in 2021 at the German and Finnish sites after cutting at flower bud and early flowering stage. The lowest emerged shoot number in 2021 for Norway tended to occur after cutting at the flower bud stage and the start of seed production. Accordingly, cutting at the flower-bud stage decreases the ability to produce shoots in the next year. Keywords: Perennial sow-thistle, sprouting, cutting, shoots Acknowledgements: This research was part of the project “AC/DC-weeds” which is funded by ERA-Net Cofund SusCrop/EU Horizon 2020, Grant no. 771134