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.
2021
Authors
Qiuzhen Chen Karlheinz Knickel Mehreteab Tesfai John Sumelius Alice Turinawe Rosemary Emegu Isoto Galyna MedynaAbstract
An important goal across Sub-Saharan Africa (SSA), and globally, is to foster a healthy nutrition. A strengthening of the diversity, sustainability, resilience and connectivity of food systems is increasingly seen as a key leverage point. Governance arrangements play a central role in connecting sustainable, resilient farming with healthy nutrition. In this article, we elaborate a framework for assessing, monitoring and improving the governance of food systems. Our focus is on food chains in six peri-urban and urban regions in SSA. A literature review on food chain governance and a mapping of current agri-food chains in the six regions provide the basis for the elaboration of an indicator-based assessment framework. The framework is adapted to the specific conditions of SSA and related goals. The assessment framework is then used to identify the challenges and opportunities in food chain governance in the six regions. The first testing of the framework indicates that the approach can help to identify disconnects, conflicting goals and tensions in food systems, and to formulate strategies for empowering agri-food chain actors in transitioning toward more efficient, equitable and sustainable agri-food systems. The article is concluded with a brief reflection on the strengths and weaknesses of the framework and suggests further testing and refinement.
Authors
Daniel Powell Ewald Groβe-Wilde Paal Krokene Amit Roy Amrita Chakraborty Christer Löfstedt Heiko Vogel Martin N. Andersson Fredrik SchlyterAbstract
Conifer-feeding bark beetles are important herbivores and decomposers in forest ecosystems. These species complete their life cycle in nutritionally poor substrates and some can kill enormous numbers of trees during population outbreaks. The Eurasian spruce bark beetle (Ips typographus) can destroy >100 million m3 of spruce in a single year. We report a 236.8 Mb I. typographus genome assembly using PacBio long-read sequencing. The final phased assembly has a contig N50 of 6.65 Mb in 272 contigs and is predicted to contain 23,923 protein-coding genes. We reveal expanded gene families associated with plant cell wall degradation, including pectinases, aspartyl proteases, and glycosyl hydrolases. This genome sequence from the genus Ips provides timely resources to address questions about the evolutionary biology of the true weevils (Curculionidae), one of the most species-rich animal families. In forests of today, increasingly stressed by global warming, this draft genome may assist in developing pest control strategies to mitigate outbreaks.
Authors
Habtamu AlemAbstract
Previous application of the stochastic frontier model and subsequent measurement of the performance of the crop sector can be criticized for the estimated production function relying on the assumption that the underlying technology is the same for different agricultural systems. This paper contributes to estimating regional efficiency and the technological gap in Norwegian grain farms using the stochastic metafrontier approach. For this study, we classified the country into regions with district level of development and, hence, production technologies. The dataset used is farm-level balanced panel data for 19 years (1996–2014) with 1463 observations from 196 family farms specialized in grain production. The study used the true random effect model and stochastic metafrontier analysis to estimate region-level technical efficiency (TE) and technology gap ratio (TGR) in the two main grain-producing regions of Norway. The result of the analysis shows that farmers differ in performance and technology use. Consequently, the paper gives some regionally and farming system-based policy insights to increase grain production in the country to achieve self-sufficiency and small-scale farming in all regions.
Authors
Marie Vestergaard Henriksen Guillaume Latombe David G. Chapple Steven L. Chown Melodie A. McGeochAbstract
1. Ecological network structure is maintained by a generalist core of common species. However, rare species contribute substantially to both the species and functional diversity of networks. Capturing changes in species composition and interactions, measured as turnover, is central to understanding the contribution of rare and common species and their interactions. Due to a large contribution of rare interactions, the pairwise metrics used to quantify interaction turnover are, however, sensitive to compositional change in the interactions of, often rare, peripheral specialists rather than common generalists in the network. 2. Here we expand on pairwise interaction turnover using a multi-site metric that enables quantifying turnover in rare to common interactions (in terms of occurrence of interactions). The metric further separates this turnover into interaction turnover due to species turnover and interaction rewiring. 3. We demonstrate the application and value of this method using a host–parasitoid system sampled along gradients of environmental modification. 4. In the study system, both the type and amount of habitat needed to maintain interaction composition depended on the properties of the interactions considered, that is, from rare to common. The analyses further revealed the potential of host switching to prevent or delay species loss, and thereby buffer the system from perturbation. 5. Multi-site interaction turnover provides a comprehensive measure of network change that can, for example, detect ecological thresholds to habitat loss for rare to common interactions. Accurate description of turnover in common, in addition to rare, species and their interactions is particularly relevant for understanding how network structure and function can be maintained.
Abstract
No abstract has been registered
Authors
Stefano Puliti Grant D. Pearse Michael S. Watt Edward Mitchard Ian McNicol Magnus Bremer Martin Rutzinger Peter Surovy Luke Wallace Markus Hollaus Rasmus AstrupAbstract
Survey-grade laser scanners suitable for drones (UAV-LS) allow the efficient collection of finely detailed three-dimensional (3D) information on tree structures allowing to resolve the complexity of the forest into discrete individual trees and species as well as into different component of the tree. Current developments are hindered by the limited availability of survey-grade UAV-LS data and by the lack of a publicly available benchmark dataset for developing and validating methods. We present a new benchmarking dataset composed of manually labelled UAV-LS data covering forests in different continents and eco-regions. Such data consists in single-tree point clouds, with each point classified as either stem, branches, and leaves. This benchmark dataset offers new possibilities to develop single-tree segmentation algorithms and validate existing ones.
Authors
Stefano Puliti Grant Pearse Michael Watt Edward Mitchard Ian McNicol Magnus Bremer Martin Rutzinger Peter Surovy Luke Wallace Markus Hollaus Rasmus AstrupAbstract
No abstract has been registered
Abstract
No abstract has been registered
Abstract
This paper describes a tool that enables farmers to time harvests and target nitrogen (N) inputs in their forage production, according to the prevailing yield potential. Based on an existing grass growth model for forage yield estimation, a more detailed process-based model was developed, including a new nitrogen module. The model was tested using data from an experiment conducted in a grassland-rich region in central Norway and showed promising accuracy with estimated root mean square error (RMSE) of 50 and 130 g m-2 for dry matter yield in the trial. Three parameters were detected as highly sensitive to model output: initial value of organic N in the soil, fraction of humus in the initial organic N in the soil, and fraction of decomposed N mineralized. By varying these parameters within a range from 0.5 to 1.5 of their respective initial value, most of the within-field variation was captured. In a future step, remotely sensed information on model output will be included, and in-season model correction will be performed through re-calibration of the highly sensitive parameters.
Abstract
Late blight caused by Phytophthora infestans is a serious, worldwide disease on potato (Solanum tuberosum). Phytophthora infestans normally reproduces in a clonal manner, but in some areas, as the Nordic Countries, sexual reproduction has become the major determinant of the population structure. To improve the late blight forecasting in Norway, the process-based Nærstad model was developed. The model includes the structure of the underlying processes in the disease development, including spore production, spore release, spore survival and infection of P. infestans. It needs hourly weather records of air temperature, precipitation, relative humidity, leaf wetness and global radiation. The model contained 19 uncertain parameters, and from a sensitivity analysis, 12 were detected as weakly sensitive to model outputs and fixed to a nominal value within their prior boundaries. The remaining seven parameters were detected as more sensitive to model outputs and were parameterized using maximum a'posteriori (MAP) estimates, calculated through Bayesian calibration. The model was developed based on literature combined with field data of daily observed number of lesions on trap plants of the Bintje cultivar (late blight susceptible) at Ås during the seasons 2006-2008 and 2010-2011. It was further tested on daily observed number of lesions on trap plants of the cultivars Bintje, Saturna (medium susceptible) and Peik (medium resistant) at Ås during the seasons 2012-2015. For all three cultivars, the Nærstad model improved with a higher model accuracy compared to the existing HOSPO-model and the Førsund rules that both have shown relatively good correlation with blight development in field evaluations in Norway. The best accuracy was found for Bintje (0.83) closely followed by Saturna (0.79), whereas a much lower accuracy was detected for Peik (0.66).