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NIBIOs ansatte publiserer flere hundre vitenskapelige artikler og forskningsrapporter hvert år. Her finner du referanser og lenker til publikasjoner og andre forsknings- og formidlingsaktiviteter. Samlingen oppdateres løpende med både nytt og historisk materiale. For mer informasjon om NIBIOs publikasjoner, besøk NIBIOs bibliotek.

2019

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Introduction Blackcurrant (Ribes nigrum L.) is an excellent example of a “super fruit” with potential health benefits. Both genotype and cultivation environment are known to affect the chemical composition of blackcurrant, especially ascorbic acid and various phenolic compounds. Environmental conditions, like temperature, solar radiation and precipitation can also have significant impact on fruit chemical composition. The relevance of the study is further accentuated by the predicted and ongoing changes in global climate. Objectives The aim of the present study was to provide new knowledge and a deeper understanding of the effects of post flowering environmental conditions, namely temperature and day length, on fruit quality and chemical composition of blackcurrant using an untargeted high performance liquid chromatography–photo diode array–mass spectrometry (HPLC– PDA–MS) metabolomics approach. Methods A phytotron experiment with cultivation of single-stemmed potted plants of blackcurrant cv. Narve Viking was conducted using constant temperatures of 12, 18 or 24 °C and three different photoperiods (short day, short day with night interruption, and natural summer daylight conditions). Plants were also grown under ambient outdoor conditions. Ripe berries were analysed using an untargeted HPLC–PDA–MS metabolomics approach to detect the presence and concentration of molecules as affected by controlled climatic factors. Results The untargeted metabolomics dataset contained a total of 7274 deconvolved retention time-m/z pairs across both electrospray ionisation (ESI) positive and negative polarities, from which 549 metabolites were identified or minimally annotated based upon accurate mass MS. Conventional principal component analysis (PCA) in combination with the Friedman significance test were applied to first identify which metabolites responded to temperature in a linear fashion. Multi-block hierarchical PCA in combination with the Friedman significance test was secondly applied to identify metabolites that were responsive to different day length conditions. Temperature had significant effect on a total of 365 metabolites representing a diverse range of chemical classes. It was observed that ripening of the blackcurrant berries under ambient conditions, compared to controlled conditions, resulted in an increased accumulation of 34 annotated metabolites, mainly anthocyanins and flavonoids. 18 metabolites were found to be regulated differentially under the different daylength conditions. Moreover, based upon the most abundant anthocyanins, a comparison between targeted and untargeted analyses, revealed a close convergence of the two analytical methods. Therefore, the study not just illustrates the value of non-targeted metabolomics approaches with respect to the huge diversity and numbers of significantly changed metabolites detected (and which would be missed by conventional targeted analyses), but also shows the validity of the non-targeted approach with respect to its precision compared to targeted analyses. Conclusions Blackcurrant maturation under controlled ambient conditions revealed a number of insightful relationships between environment and chemical composition of the fruit. A prominent reduction of the most abundant anthocyanins under the highest temperature treatments indicated that blackcurrant berries in general may accumulate lower total anthocyanins in years with extreme hot summer conditions. HPLC–PDA–MS metabolomics is an excellent method for broad analysis of chemical composition of berries rich in phenolic compounds. Moreover, the experiment in controlled phytotron conditions provided additional knowledge concerning plant interactions with the environment.

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The belowground environment is heterogeneous and complex at fine spatial scales. Physical structures, biotic components and abiotic conditions create a patchwork mosaic of potential niches for microbes. Questions remain about mechanisms and patterns of community assembly belowground, including: Do fungal and bacterial communities assemble differently? How do microbes reach the roots of host plants? Within a 4 m2 plot in alpine vegetation, high throughput sequencing of the 16S (bacteria) and ITS1 (fungal) ribosomal RNA genes was used to characterise microbial community composition in roots and adjacent soil of a viviparous host plant (Bistorta vivipara). At fine spatial scales, beta-diversity patterns in belowground bacterial and fungal communities were consistent, although compositional change was greater in bacteria than fungi. Spatial structure and distance-decay relationships were also similar for bacteria and fungi, with significant spatial structure detected at <50 cm among root- but not soil-associated microbes. Recruitment of root microbes from the soil community appeared limited at this sampling and sequencing depth. Possible explanations for this include recruitment from low-abundance populations of soil microbes, active recruitment from neighbouring plants and/or vertical transmission of symbionts to new clones, suggesting varied methods of microbial community assembly for viviparous plants. Our results suggest that even at relatively small spatial scales, deterministic processes play a significant role in belowground microbial community structure and assembly.

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This paper describes the development and utility of the Norwegian forest resources map (SR16). SR16 is developed using photogrammetric point cloud data with ground plots from the Norwegian National Forest Inventory (NFI). First, an existing forest mask was updated with object-based image analysis methods. Evaluation against the NFI forest definitions showed Cohen's kappa of 0.80 and accuracy of 0.91 in the lowlands and a kappa of 0.73 and an accuracy of 0.96 in the mountains. Within the updated forest mask, a 16×16 m raster map was developed with Lorey's height, volume, biomass, and tree species as attributes (SR16-raster). All attributes were predicted with generalized linear models that explained about 70% of the observed variation and had relative RMSEs of about 50%. SR16-raster was segmented into stand-like polygons that are relatively homogenous in respect to tree species, volume, site index, and Lorey's height (SR16-vector). When SR16 was utilized in a combination with the NFI plots and a model-assisted estimator, the precision was on average 2–3 times higher than estimates based on field data only. In conclusion, SR16 is useful for improved estimates from the Norwegian NFI at various scales. The mapped products may be useful as additional information in Forest Management Inventories.

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Advantages of low input livestock production on large pastures, including animal welfare, biodiversity and low production costs are challenged by losses due to undetected disease, accidents and predation. Precision livestock farming (PLF) enables remote monitoring on individual level with potential for predictive warning. Body temperature (Tb) and heart rate (HR) could be used for early detection of diseases, stress or death. We tested physiological sensors in free-grazing Norwegian white sheep in Norway. Forty Tb sensors and thirty HR sensors were surgically implanted in 40 lambs and 10 ewes. Eight (27%) of the HR and eight (20%) of the Tb sensors were lost during the study period. Two Tb sensors migrated from the abdominal cavity in to the digestive system. ECG based validation of the HR sensors revealed a measurement error of 0.2 bpm (SD 5.2 bpm) and correct measurement quality was assigned in 90% of the measurements. Maximum and minimum HR confirmed by ECG was 197 bpm and 68 bpm respectively. Mean passive HR was 90 bpm (SD=13 bpm) for ewes and 112 bpm (SD=13 bpm) for lambs. Mean Tb for all animals was 39.6°C (range 36.9 to 41.8°C). Tb displayed 24-hour circadian rhythms during 80.7 % but HR only during 41.0 % of the studied period. We established baseline values and conclude that these sensors deliver good quality. For a wide agricultural use, the sensor implantation method has to be further developed and real-time communication technology added.

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Early detection provides the best way to prevent introduction and establishment of alien plant pathogens. Amplification of DNA by PCR has revolutionized the detection and monitoring of plant pathogens. Most of those assays rely on the amplification of a fraction of the genome of the targeted species. With the availability of whole genomes for a growing number of fungi and oomycetes it is becoming possible to compare genomes and discover regions that are unique to a target organism. This study has applied this pipeline to develop a set of hierarchical TaqMan real‐time PCR detection assays targeting DNA of all four Phytophthora ramorum lineages, and a closely related species, P. lateralis. Nine assays were generated: three targeting DNA of all P. ramorum lineages, one for each lineage of P. ramorum, one for P. lateralis and one targeting DNA of P. ramorum and P. lateralis. These assays were very accurate and sensitive, ranging from 98.7% to 100% detection accuracy of 2–10 gene copies of the targeted taxa from pure cultures or inoculated tissues. This level of sensitivity is within the lowest theoretical limit of detection of DNA. It is expected that these assays will be useful because of their high level of specificity and the ease with which they can be multiplexed because of the inherent flexibility in primer and probe design afforded by their lack of conservation in non‐target species.

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Purpose of Review The adoption of Structure from Motion photogrammetry (SfM) is transforming the acquisition of three-dimensional (3D) remote sensing (RS) data in forestry. SfM photogrammetry enables surveys with little cost and technical expertise. We present the theoretical principles and practical considerations of this technology and show opportunities that SfM photogrammetry offers for forest practitioners and researchers. Recent Findings Our examples of key research indicate the successful application of SfM photogrammetry in forestry, in an operational context and in research, delivering results that are comparable to LiDAR surveys. Reviewed studies have identified possibilities for the extraction of biophysical forest parameters from airborne and terrestrial SfM point clouds and derived 2D data in area-based approaches (ABA) and individual tree approaches. Additionally, increases in the spatial and spectral resolution of sensors available for SfM photogrammetry enable forest health assessment and monitoring. The presented research reveals that coherent 3D data and spectral information, as provided by the SfM workflow, promote opportunities to derive both structural and physiological attributes at the individual tree crown (ITC) as well as stand levels. Summary We highlight the potential of using unmanned aerial vehicles (UAVs) and consumer-grade cameras for terrestrial SfM-based surveys in forestry. Offering several spatial products from a single sensor, the SfM workflow enables foresters to collect their own fit-for-purpose RS data. With the broad availability of non-expert SfM software, we provide important practical considerations for the collection of quality input image data to enable successful photogrammetric surveys.

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The extent of land lease is increasing in many countries, including Norway. This paper develops a von Thünen type model of optimal land plots to lease from a farm’s center. For a single farm setting, the optimality principle is that land is leased as long as the expected marginal value of leasing a tract of land is greater than or equal to the expected marginal costs of leasing the land. The single farm model setting captures land lease at the extensive margin, i.e., under absence of competition for leasing land. Land lease at the intensive margin, i.e., when there is competition for leasing farm fields, is more interesting. We distinguish between two cases. In the first case, continued farm operations do not depend on being able to lease more land. Then we show that optimal land lease results when the expected profits for each farm of leasing its least profitable field is equal among farms competing for the same farm field. This also corresponds to an economically efficient allocation of leased land. Our second case at the intensive margin is more complicated. Here, farm survival depends on attracting acreage of leased land to allow for investment in cost saving technology. We show that the resulting allocation of leased land corresponds to the solution of a game involving bidding for land in order to prevent other farmers from getting land, which in turn leads to farmer exit and therefore increases the future supply of land available at the land lease market. In the first round of the game, winners of the land lease auction pay more for the leased land than they would have done in the absence of preventive bidding. The model framework is applicable for other settings where locking out competitors are parts of agents’ strategy space.

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Biodiversity of ecosystems is an important driver for the supply of ecosystem services to people. Soils often have a larger biodiversity per unit surface area than what can be observed aboveground. Here, we present what is to our knowledge, the most extensive literature-based key-word assessment of the existing information about the relationships between belowground biodiversity and ecosystem services in European forests. The belowground diversity of plant roots, fungi, prokaryota, soil fauna, and protists was evaluated in relation to the supply of Provisioning, Regulating, Cultural, and Supporting Services. The soil biota were divided into 14 subgroups and the ecosystem services into 37 separate services. Out of the 518 possible combinations of biotic groups and ecosystem services, no published study was found for 374 combinations (72%). Of the remaining 144 combinations (28%) where relationships were found, the large majority (87%) showed a positive relationship between biodiversity of a belowground biotic group and an associated ecosystem service. However, for the majority of the combinations (102) there were only three or fewer studies. The percentage of cases for which a relationship was detected varied strongly between ecosystem service categories with 23% for Provisioning, 8% for Regulating, 40% for Cultural, and 48% for Supporting Services.We conclude that (1) soil biodiversity is generally positively related to ecosystem services in European forests; (2) the links between soil biodiversity and Cultural or Supporting services are better documented than those relating to Provisioning and Regulating services; (3) there is a huge knowledge gap for most possible combinations of soil biota and ecosystem services regarding how a more biodiverse soil biota is associated with a given ecosystem service. Given the drastically increasing societal demand for knowledge of the role of biodiversity in the functioning of ecosystems and the supply of ecosystem services, we strongly encourage the scientific community to conduct well-designed studies incorporating the belowground diversity and the functions and services associated with this diversity.

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Satellite telemetry is an increasingly utilized technology in wildlife research, and current devices can track individual animal movements at unprecedented spatial and temporal resolutions. However, as we enter the golden age of satellite telemetry, we need an in-Depth understanding of the main technological, species-specific and environmental factors that determine the success and failure of satellite tracking devices across species and habitats. Here, we assess the relative influence of such factors on the ability of satellite telemetry units to provide the expected amount and quality of data by analyzing data from over 3,000 devices deployed on 62 terrestrial species in 167 projects worldwide. We evaluate the success rate in obtaining GPS fixes as well as in transferring these fixes to the user and we evaluate failure rates. Average fix success and data transfer rates were high and were generally better predicted by species and unit characteristics, while environmental characteristics influenced the variability of performance. However, 48% of the unit deployments ended prematurely, half of them due to technical failure. Nonetheless, this study shows that the performance of satellite telemetry applications has shown improvements over time, and based on our findings, we provide further recommendations for both users and manufacturers.

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With the ongoing climate change, African rainforests are expected to experience severe drought events in the future. In Africa, the tropical genus Erythrophleum (Fabaceae) includes two forest sister timber tree species displaying contrasting geographical distributions. Erythrophleum ivorense is adapted to wet evergreen Guineo-Congolian forests, whereas E. suaveolens occurs in a wider range of climates, being found in moist dense forests but also in gallery forests under a relatively drier climate. This geographical distribution pattern suggests that the two species might cope differently to drought at the genomic level. Yet, the genetic basis of tolerance response to drought stress in both species is still uncharacterized. To bridge this gap, we performed an RNA-seq approach on seedlings from each species to monitor their transcriptional responses at different levels of drought stress (0, 2 and 6 weeks after stopping watering seedlings). Monitoring of wilting symptoms revealed that E. suaveolens displayed an earlier phenotypic response to drought stress than E. ivorense. At the transcriptomic level, results revealed 2020 (1204 down-regulated/816 up-regulated) and 1495 differentially expressed genes (DEGs) in response to drought stress from a total of 67,432 and 66,605 contigs assembled in E. ivorense and E. suaveolens, respectively. After identifying 30,374 orthologs between species, we found that only 7 of them were DEGs shared between species, while 587 and 458 were differentially expressed only in E. ivorense or E. suaveolens, respectively. GO and KEGG enrichment analysis revealed that the two species differ in terms of significantly regulated pathways as well as the number and expression profile of DEGs (Up/Down) associated with each pathway in the two stress stages. Our results suggested that the two studied species react differently to drought. E. suaveolens seems displaying a prompt response to drought at its early stage strengthened by the down-regulation of many DEGs encoding for signaling and metabolism-related pathways. A considerable up-regulation of these pathways was also found in E. ivorense at the late stage of drought, suggesting this species may be a late responder. Overall, our data may serve as basis for further understanding the genetic control of drought tolerance in tropical trees and favor the selection of crucial genes for genetically enhancing drought resistance.