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.
2017
Authors
Monica Suarez Korsnes Reinert KorsnesAbstract
The marine toxin yessotoxin (YTX) can cause various cytotoxic effects depending on cell type and cell line. It is well known to trigger distinct mechanisms for programmed cell death which may overlap or cross-talk. The present contribution provides the first evidence that YTX can cause genotoxicity and induce mitotic catastrophe which can lead to different types of cell death. This work also demonstrates potential information gain from non-intrusive computer-based tracking of many individual cells during long time. Treatment of BC3H1 cells at their exponential growth phase causes atypical nuclear alterations and formation of giant cells with multiple nuclei. These are the most prominent morphological features of mitotic catastrophe. Giant cells undergo slow cell death in a necrosis-like manner. However, apoptotic-like cell death is also observed in these cells. Electron microscopy of treated BC3H1 cells reveal uncondensed chromatin and cells with double nuclei. Activation of p-p53, p-H2AX, p-Chk1, p-ATM, and p-ATR and down-regulation of p-Chk2 indicate DNA damage response and cell cycle deregulation. Micronuclei formation further support this evidence. Data from tracking single cells reveal that YTX treatment suppresses a second round of cell division in BC3H1 cells. These findings suggest that YTX can induce genomic alterations or imperfections in chromosomal segregation leading to permanent mitotic failure. This understanding extends the list of effects from YTX and which are of interest to control cancer and tumor progression.
Abstract
Forest stands are important units of management. A stand-by-stand estimation of the mean and variance of an attribute of interest (Y) remains a priority in forest enterprise inventories. The advent of powerful and cost effective remotely sensed auxiliary variables (X) correlated with Y means that a census of X in the forest enterprise is increasingly available. In combination with a probability sample of Y, the census affords a modeldependent stand-level inference. It is important, however, that the sampling design affords an estimation of possible stand-effects in the model linking X to Y.We demonstrate, with simulated data, that failing to quantify non-zero stand-effects in the intercept of a linear population-level model can lead to a serious underestimation of the uncertainty in a model-dependent estimate of a stand mean, and by extension a confidence interval with poor coverage.We also provide an approximation to the variance of stand-effects in an intercept for the case when a sampling design does not afford estimation. Furthermore, we propose a method to correct a potential negative bias in an estimate of the variance of stand-effects when a sampling design prescribes few stands with small within-stand sample sizes.
Abstract
Phenological observations are considered to be sensitive tools for identifying plant responses to climatic changes. Over the last 10 years, the onset of the phenophases of sweet cherry (Prunus avium L.) during spring tended to be earlier than the previous two decades in Ullensvang, western Norway. The effects of air temperature during the winter and spring months were evaluated during two quinquennia (5-year periods), 1996-2000 (Q1) and 2003-2007 (Q2) selected due to similar mean winter and early summer temperatures, but markedly different spring temperatures. Average January-February temperatures were similar (3.3°C) in both of these two 5-year periods. However, average March and April temperatures were slightly warmer (4.0 vs. 3.2°C) and (7.3 vs. 6.9°C), respectively, in Q2 vs. Q1. These increases resulted in significantly earlier flower development. Average temperatures during the first half of May were similar for both quinquennia (10.2 vs. 10.1°C). The start of flowering (first bloom) of early maturing ‘Burlat’ and mid-season ‘Van’ were significantly different. Timing of flowering phenophases were statistically different between Q1 and Q2 for both cultivars. Mean data for ‘Burlat’ and ‘Van’ first bloom were 8 days earlier during Q2, May 2 for ‘Burlat’ and May 1 for ‘Van’. Full bloom occurred 3 days after first bloom and flowering ended 14 days after first bloom. First bloom during Q2 required 221 Baskerville-Emin Growing degree days (GDD) using a base temperature of 2°C. For the same time period in Q1, only 197 GDD were accumulated, which supports the observed temperature differences. Furthermore, we propose a flowering model for full bloom of both ‘Burlat’ and ‘Van’ in Ullensvang, which requires 254 Baskerville-Emin GDD using a base of 2°C starting on March 1.
Authors
Xiaobo Zhu Mingguo Ma Hong Yang Wei GeAbstract
Nighttime light data derived from the Defense Meteorological Satellite Program’s Operational Linescan System (DMSP-OLS) in conjunction with the Soumi National Polar-Orbiting Partnership Visible Infrared Imaging Radiometer Suite (NPP-VIIRS) possess great potential for measuring the dynamics of Gross Domestic Product (GDP) at large scales. The temporal coverage of the DMSP-OLS data spans between 1992 and 2013, while the NPP-VIIRS data are available from 2012. Integrating the two datasets to produce a time series of continuous and consistently monitored data since the 1990s is of great significance for the understanding of the dynamics of long-term economic development. In addition, since economic developmental patterns vary with physical environment and geographical location, the quantitative relationship between nighttime lights and GDP should be designed for individual regions. Through a case study in China, this study made an attempt to integrate the DMSP-OLS and NPP-VIIRS datasets, as well as to identify an optimal model for long-term spatiotemporal GDP dynamics in different regions of China. Based on constructed regression relationships between total nighttime lights (TNL) data from the DMSP-OLS and NPP-VIIRS data in provincial units (R 2 = 0.9648, P < 0.001), the temporal coverage of nighttime light data was extended from 1992 to the present day. Furthermore, three models (the linear model, quadratic polynomial model and power function model) were applied to model the spatiotemporal dynamics of GDP in China from 1992 to 2015 at both the country level and provincial level using the extended temporal coverage data. Our results show that the linear model is optimal at the country level with a mean absolute relative error (MARE) of 11.96%. The power function model is optimal in 22 of the 31 provinces and the quadratic polynomial model is optimal in 7 provinces, whereas the linear model is optimal only in two provinces. Thus, our approach demonstrates the potential to accurately and timely model long-term spatiotemporal GDP dynamics using an integration of DMSP-OLS and NPP-VIIRS data.
Authors
Stefano Puliti Svein Solberg Erik Næsset Terje Gobakken Eliakimu Zahabu Ernest William Mauya Rogers Ernest MalimbwiAbstract
The use of Interferometric Synthetic Aperture Radar (InSAR) data has great potential for monitoring large scale forest above ground biomass (AGB) in the tropics due to the increased ability to retrieve 3D information even under cloud cover. To date; results in tropical forests have been inconsistent and further knowledge on the accuracy of models linking AGB and InSAR height data is crucial for the development of large scale forest monitoring programs. This study provides an example of the use of TanDEM-X WorldDEM data to model AGB in Tanzanian woodlands. The primary objective was to assess the accuracy of a model linking AGB with InSAR height from WorldDEM after the subtraction of ground heights. The secondary objective was to assess the possibility of obtaining InSAR height for field plots when the terrain heights were derived from global navigation satellite systems (GNSS); i.e., as an alternative to using airborne laser scanning (ALS). The results revealed that the AGB model using InSAR height had a predictive accuracy of RMSE = 24.1 t·ha−1 ; or 38.8% of the mean AGB when terrain heights were derived from ALS. The results were similar when using terrain heights from GNSS. The accuracy of the predicted AGB was improved when compared to a previous study using TanDEM-X for a sub-area of the area of interest and was of similar magnitude to what was achieved in the same sub-area using ALS data. Overall; this study sheds new light on the opportunities that arise from the use of InSAR data for large scale AGB modelling in tropical woodlands.
Abstract
No abstract has been registered
Authors
C. F. E. Topp Vera Eory André Bannink Dave J. Bartley Isabel Blanco-Penedo R Cortignani Agustin del Prado G Dono P. Faverdin A.-I. Graux Nick Hutchings L. Lauwers Şeyda Özkan Gülzari S. Rolinski M Ruiz Ramos Daniel Sandars R Sándor M Schoenhart G. Seddaiu Jantine van Middelkoop Isabelle Weindl Richard P. KiplingAbstract
No abstract has been registered
Authors
Hans Thodsen Csilla Farkas Jaroslaw Chormanski Dennis Trolle Gitte Blicher-Mathiesen Ruth Grant Alexander Melvold Engebretsen Ignacy Kardel Hans Estrup AndersenAbstract
The main environmental stressor of the Baltic Sea is elevated riverine nutrient loads, mainly originating from diffuse agricultural sources. Agricultural practices, intensities, and nutrient losses vary across the Baltic Sea drainage basin (1.75 × 106 km2 , 14 countries and 85 million inhabitants). Six “Soil and Water Assessment Tool” (SWAT) models were set up for catchments representing the major agricultural systems, and covering the different climate gradients in the Baltic Sea drainage basin. Four fertilizer application scenarios were run for each catchment to evaluate the sensitivity of changed fertilizer applications. Increasing sensitivity was found for catchments with an increasing proportion of agricultural land use and increased amounts of applied fertilizers. A change in chemical fertilizer use of ±20% was found to affect watershed NO3-N loads between zero effect and ±13%, while a change in manure application of ±20% affected watershed NO3-N loads between zero effect and −6% to +7%.
Abstract
This work focuses on modelling soil water reserves using an Artificial Neural Net-work (ANN). Four model variants were established based on 843 records (verifiedthrough 268 measurements) of soil water content (SWC) measured at full-scale fieldsites located in Southwest Poland. It is revealed that commonly recorded climaticdata (precipitation and temperature) linked with SWC and field water capacity(FWC) are applicable in the ANN modelling. The basic model (utilising the meteoro-logical data) was the most suitable for soil profiles with thicknesses of 0–25 cm,while in profiles with thicknesses of 0–50 cm and 0–100 cm the comprehensiveANN model (linking climatic data, FWC and SWC) was the most appropriate. Fur-thermore, comparative studies of the measured and modelled data indicated theirstatistical convergence, thus providing support for the practical implementation ofthe proposed ANN modelling.
Authors
Nina Sylvia Liland Irene Biancarosa Pedro Araujo Daan Biemans Christian Guido Bruckner Rune Waagbø Bente Elisabeth Torstensen Erik-Jan LockAbstract
Black soldier fly (Hermetia illucens) larvae are a promising source of protein and lipid for animal feeds. The nutritional composition of the BSF larvae depend partly on the composition of the feeding medium. The BSF lipid profile in part mimics the feeding media lipid profile, and micronutrients, like minerals and vitamins, can readily accumulate in black soldier fly larvae. However, investigative studies on bioconversion and accumulation of nutrients from media to black soldier fly larvae are scarce. Here we show that inclusion of the brown algae Ascophyllum nodosum in the substrate for black soldier fly larvae can introduce valuable nutrients, commonly associated with the marine environment, into the larvae. The omega-3 fatty acid eicosapentaenoic acid (20:5n-3), iodine and vitamin E concentrations increased in the larvae when more seaweed was included in the diet. When the feeding media consisted of more than 50% seaweed, the larvae experienced poorer growth, lower nutrient retention and lower lipid levels, compared to a pure plant based feeding medium. Our results confirm the plasticity of the nutritional make-up of black soldier fly larvae, allowing it to accumulate both lipid- and water-soluble compounds. A broader understanding of the effect of the composition of the feeding media on the larvae composition can help to tailor black soldier fly larvae into a nutrient profile more suited for specific feed or food purposes.