Publikasjoner
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.
2018
Forfattere
Trygve S. AamlidSammendrag
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Sammendrag
Productivity of a mechanized P. patula cut-to-length harvesting operation was estimated and modelled using two methods of data collection: manual time study and follow-up study using StanForD stem files. The objective of the study was to compare the productivity models derived using these two methods to test for equivalence. Manual time studies were completed on four different machines and their operators. Two Ponsse Bear harvesters fitted with H8 heads, and two Ponsse Beaver harvesters, fitted with H6 heads, were included. All machines were equipped with Ponsse Opti2 information system. All four operators had approximately 1 year of experience working with their respective machines. The four machines worked in separate four-tree-wide harvesting corridors, and they each harvested 200 trees. Individual tree diameter at breast height (DBH), and height measurements were made manually. Subsequently, data on the trees in each study were extracted from the StanForD stem reports from each of the harvesters. Cycle times in the stem reports were determined based on the difference between consecutive harvest timestamps. The two methods were compared in terms of their abilities to estimate equivalent measures for tree DBH, volume, and productivity. In all four cases, significant differences were found between the DBH and volume measures derived using the two methods. Subsequently, the volume measures from the manual methods were used as the basis for productivity calculations. Results of the productivity comparisons found no significant differences between the models developed from the two methods. These results suggest that equivalent productivity models can be developed in terms of time using either method, however volume discrepancies indicate a need to reconcile bark and volume functions with the high variability experienced in the country.
Forfattere
Bjørn Egil FløSammendrag
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Forfattere
Xiao Huang Chaoqing Yu Jiarui Fang Guorui Huang Shaoqiang Ni Jim Hall Conrad Zorn Xiaomeng Huang Wenyuan ZhangSammendrag
Crop models are widely used to evaluate the response of crop growth to drought. However, over large geographic regions, the most advanced models are often restricted by available computing resource. This limits capacity to undertake uncertainty analysis and prohibits the use of models in real-time ensemble forecasting systems. This study addresses these concerns by presenting an integrated system for the dynamic prediction and assessment of agricultural yield using the top-ranked Sunway TaihuLight supercomputer platform. This system enables parallelization and acceleration for the existing AquaCrop, DNDC (DeNitrification and DeComposition) and SWAP (Soil Water Atmosphere Plant) models, thus facilitating multi-model ensemble and parameter optimization and subsequent drought risk analysis in multiple regions and at multiple scales. The high computing capability also opens up the possibility of real-time simulation during droughts, providing the basis for more effective drought management. Initial testing with varying core group numbers shows that computation time can be reduced by between 2.6 and 3.6 times. Based on the powerful computing capacity, a county-level model parameter optimization (2043 counties for 1996–2007) by Bayesian inference and multi-model ensemble using BMA (Bayesian Model Average) method were performed, demonstrating the enhancements in predictive accuracy that can be achieved. An application of this system is presented predicting the impacts of the drought of May–July 2017 on maize yield in North and Northeast China. The spatial variability in yield losses is presented demonstrating new capability to provide high resolution information with associated uncertainty estimates.
Sammendrag
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Sammendrag
Forestry in coastal Norway has traditionally been a marginal activity with a low annual harvest rate. However, the region is now faced with large areas of spruce plantations that will reach harvest maturity within the next 25 years. Due to the poor infrastructure in the region, the current challenge is to harvest the maturing spruce plantations at an acceptable cost. Hence, there is considerable interest both from the forest sector and politicians to invest in infrastructure that can provide the basis for profitable forest sector development in coastal Norway. This paper presents a mathematical optimization model for timber transportation from stump to industry. The main decision variables are location of quays, upgrade of public road links, the length of new forest roads, and when the investments should happen. The main objective is to provide decision support for prioritization of infrastructure investments. The optimization model is combined with a dynamical forest resource model, providing details on available volumes and costs. A case study for coastal Norway is presented and solved to optimality. The instance includes 10 counties comprising more than 200 municipalities with forest resources, 53 possible new quays for timber export and 916 public road links that also can be upgraded. Compared with a no investment case, the optimal solution improved the objective by 23%. The study shows that consistent, informative and good analyses can be performed to evaluate trade-offs, prioritization, time and order of investment, and cost saving potentials of infrastructure investments in the forest industry. The solution seems reasonable based on present infrastructure and state of the forest.
Sammendrag
Freezing and thawing have large effects on water flow in soils since ice may block a large part of the pore space and thereby prevent infiltration and flow through the soil. This, in turn, may have consequences for contaminant transport. For example, transport of solutes contained at or close to the soil surface can be rapidly transported through frozen soils in large pores that were air filled at the time of freezing. Accounting for freezing and thawing could potentially improve model predictions used for risk assessment of contaminant leaching. A few numerical models of water flow through soil accounts for freezing by coupling Richards’ equation and the heat flow equation using of the generalized Clapeyron equation, which relates the capillary pressure to temperature during phase change. However, these models are not applicable to macroporous soils. The objective of this study was to develop and evaluate a dual-permeability approach for simulating water flow in soil under freezing and thawing conditions. To achieve this we extended the widely used MACRO-model for water flow and solute transport in macroporous soil. Richards’ equation and the heat flow equation were loosely coupled using the Clapeyron equation for the soil micropore domain. In accordance with the original MACRO model, capillary forces were neglected for the macropore domain and conductive heat flow in the macropores was not accounted for. Freezing and thawing of macropore water, hence, were solely governed by heat exchange between the pore domains. This exchange included a first-order heat conduction term depending on the temperature difference between domains and the diffusion pathlength (a proxy variable related to the distance between macropores) and convective heat flow. As far as we know, there are no analytical solutions available for water flow during freezing and thawing and laboratory data is limited for evaluation of water flow through macropores. In order to evaluate the new model approach we therefore first compared simulation results of water flows during freezing for the micropore domain to existing literature data. Our model was shown to give similar results as other available models. We then compared the first-order conductive heat exchange during freezing to a full numerical solution of heat conduction. Finally, simulations were run for water flow through frozen soil with initially air-filled macropores for different boundary conditions. Simulation results were sensitive to parameters governing the heat exchange between pore domains for both test cases.
Forfattere
Francesca Giannetti Gherardo Chirici Terje Gobakken Erik Næsset Davide Travaglini Stefano PulitiSammendrag
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Forfattere
Shinsaku Sasai Keisuke Tamura Motoaki Tojo Maria-Luz Herrero Tamotsu Hoshino Satoshi T. Ohki Tomofumi MochizukiSammendrag
We investigated virus infection in the oomycete Pythium polare from the Arctic. From 39 isolates investigated, 14 contained virus-like double-stranded RNA (dsRNA). Next generation sequencing revealed that the P. polare isolate OPU1176 contained three different virus-like sequences. We determined the full-length genome sequence of one of them. The 5397 nt-length genome had two overlapped open reading frames (ORFs) consistent with a toti and toti-like viruses, that we named Pythium polare RNA virus 1 (PpRV1). The ORF2 encoded an RNAdependent RNA polymerase (RdRp). The shifty heptamer motif and RNA pseudoknot were predicted near the stop codon of ORF1, implying that the RdRp could be translated as a fusion protein with the ORF1 protein. Phylogenetic analysis with deduced RdRp amino acid sequences indicated that oomycete virus PpRV1 was closely related to the unclassified arthropod toti-like viruses. The comparison of PpRV1-free and -infected lines suggested that PpRV1 infected in a symptomless manner.
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