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
Abstract
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.
Abstract
The preservation of the functionality of forest soil is a key aspect in planning mechanized harvesting operations. Therefore, knowledge and information about stand and soil characteristics are vital to the planning process. In this respect, depth-to-water (DTW) maps were reviewed with regard to their potential use as a prediction tool for wheel ruts. To test the applicability of open source DTW maps for prediction of rutting, the ground surface conditions of 20 clear-cut sites were recorded post harvesting, using an unmanned aerial vehicle (UAV). In total, 80 km of machine tracks were categorized by the severity of occurring rut-formations to investigate whether: i) operators intuitively avoid areas with low DTW values, ii) a correlation exists between decreasing DTW values and increasing rut severity, and iii) DTW maps can serve as reliable decision-making tool in minimizing the environmental effects of big machinery deployment. While the machine operators did not have access to these predictions (DTW maps) during the operations, there was no visual evidence that driving through these areas was actively avoided, resulting in a higher density of severe rutting within areas with DTW values <1 m. A logistic regression analysis confirmed that the probability of severe rutting rapidly increases with decreasing DTW values. However, significant differences between sites exist which might be attributed to a series of other factors such as soil type, weather conditions, number of passes and load capacity. Monitoring these factors is hence highly recommended in any further follow-up studies on soil trafficability.
Abstract
SiTree is a flexible, cross-platform, open-source framework for individual-tree simulators intended to facilitate accurate and flexible analyses of forest growth and yield, or more generally forest dynamics simulations. SiTree provides generic functionality to build customized individual-tree simulators using additional user-written code. In the forestry literature there are a wide variety of individual models that describe the different parts of forest growth and dynamics and new models are continuously developed and published. The aim of SiTree is to provide a broad community of R-users within forestry with an easily adaptable individual-tree simulator framework and an easily accessible tool for testing and combining new and existing models describing parts of forest growth dynamics.
Authors
Anne Catriona Mehlhoop Bram Van Moorter Christer Moe Rolandsen Dagmar Hagen Aksel Granhus Rune Eriksen Thor Harald Ringsby Erling Johan SolbergAbstract
Like large carnivores, hunters both kill and scare ungulates, and thus might indirectly affect plant performance through trophic cascades. In this study, we hypothesized that intensive hunting and enduring fear of humans have caused moose and other forest ungulates to partly avoid areas near human infrastructure (perceived hunting risk), with positive cascading effects on recruitment of trees. Using data from the Norwegian forest inventory, we found decreasing browsing pressure and increasing tree recruitment in areas close to roads and houses, where ungulates are more likely to encounter humans. However, although browsing and recruitment were negatively related, reduced browsing was only responsible for a small proportion of the higher tree recruitment near human infrastructure. We suggest that the apparently weak cascading effect occurs because the recorded browsing pressure only partly reflects the long-term browsing intensity close to humans. Accordingly, tree recruitment was also related to the density of small trees 5–10 years earlier, which was higher close to human infrastructure. Hence, if small tree density is a product of the browsing pressure in the past, the cascading effect is probably stronger than our estimates suggest. Reduced browsing near roads and houses is most in line with risk avoidance driven by fear of humans (behaviorally mediated), and not because of excessive hunting and local reduction in ungulate density (density mediated).
Abstract
1. Spatial resources accessible for the derivation of biodiversity indicators of the class ecosystem structure are sparse and disparate, and their integration into computer algorithms for biodiversity monitoring remains problematic. We describe ecochange as an R-package that integrates spatial analyses with a monitoring workflow for computing routines necessary for biodiversity monitoring. 2. The ecochange comprises three modules for data integration, statistical analysis and graphics. The first module currently downloads and integrates diverse remote sensing products belonging to the essential biodiversity class of structure. The module for statistical analysis calculates RasterStack ecosystem-change representations across areas of interest; this module also allows focusing on species habitats while deriving changes in a variety of indicators, including ecosystem areas, conditional entropy and fractal dimension indices. The graphics module produces level and bar plots that ease the development of indicator reports. 3. Its functionality is described with an example workflow to calculate ecosystem-class areas and conditional entropy across an area of interest contained in the package documentation. 4. We conclude that ecochange features procedures necessary to derive ecosystem structure indicators integrating the retrieval of spatially explicit data with the use of workflows to calculate/visualize biodiversity indicators at the national/regional scales.
Abstract
To meet international and national commitments to decrease emissions of fossil fuels, cities around the world must obtain information on their historical levels of emissions, identifying hotspots that require special attention. Direct atmospheric measurements of pollution sources are almost impossible to obtain retrospectively. However, tree rings serve as an archive of environmental information for reconstructing the temporal and spatial distribution of fossil-fuel emissions in urban areas. Here, we present a novel methodology to reconstruct the spatial and temporal contribution of fossil-fuel CO2 concentration ([CO2F]) in the urban area of Medellin, Colombia. We used a combination of dendrochronological analyses, radiocarbon measurements, and statistical modeling. We obtained annual maps of [CO2F] from 1977 to 2018 that describe changes in its spatial distribution over time. Our method was successful at identifying hotspots of emissions around industrial areas, and areas with high traffic density. It also identified temporal trends that may be related to socioeconomic and technological factors. We observed an important increase in [CO2F] during the last decade, which suggests that efforts of city officials to reduce traffic and emissions did not have a significant impact on the contribution of fossil fuels to local air. The method presented here could be of significant value for city planners and environmental officials from other urban areas around the world. It allows identifying hotspots of fossil fuels emissions, evaluating the impact of previous environmental policies, and planning new interventions to reduce emissions.
Authors
Pekka E. Kauppi Gustav Stål Lina Arnesson-Ceder Isabella Hallberg Sramek Hans Fredrik Hoen Arvid Svensson Iddo K. Wernick Peter Högberg Tomas Lundmark Annika NordinAbstract
Planting new forests has received scientific and political attention as a measure to mitigate climate change. Large, new forests have been planted in places like China and Ethiopia and, over time, a billion hectares could become available globally for planting new forests. Sustainable management of forests, which are available to wood production, has received less attention despite these forests covering at least two billion hectares globally. Better management of existing forests would improve forest growth and help mitigate climate change by increasing the forest carbon (C) stock, by storing C in forest products, and by generating wood-based materials substituting fossil C based materials or other CO2-emission-intensive materials. Some published research assumes a trade-off between the timber harvested from existing forests and the stock of C in those forest ecosystems, asserting that both cannot increase simultaneously. We tested this assumption using the uniquely detailed forest inventory data available from Finland, Norway and Sweden, hereafter denoted northern Europe. We focused on the period 1960 – 2017, that saw little change in the total area covered by forests in northern Europe. At the start of the period, rotational forestry practices began to diffuse, eventually replacing selective felling management systems as the most common management practice. Looking at data over the period we find that despite significant increases in timber and pulp wood harvests, the growth of the forest C stock accelerated. Over the study period, the C stock of the forest ecosystems in northern Europe increased by nearly 70%, while annual timber harvests increased at the about 40% over the same period. This increase in the forest C stock was close to on par with the CO2-emissions from the region (other greenhouse gases not included). Our results suggest that the important effects of management on forest growth allows the forest C stock and timber harvests to increase simultaneously. The development in northern Europe raises the question of how better forest management can improve forest growth elsewhere around the globe while at the same time protecting biodiversity and preserving landscapes.
Abstract
No abstract has been registered