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

2021

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Abstract

Quaking aspen (Populus tremuloides) is a valued, minor component on northeastern California landscapes. It provides a wide range of ecosystem services and has been in decline throughout the region for the last century. This decline may be explained partially by the lack of fire on the landscape due to heavier fire suppression, as aspen benefit from fire that eliminates conifer competition and stimulates reproduction through root suckering. However, there is little known about how aspen stand area changes in response to overlapping fire. Our study area in northeastern California on the Lassen, Modoc and Plumas National Forests has experienced recent large mixed-severity wildfires where aspen was present, providing an opportunity to study the re-introduction of fire. We observed two time periods; a 52-year absence of fire from 1941 to 1993 preceding a 24-year period of wildfire activity from 1993 to 2017. We utilized aerial photos and satellite imagery to delineate aspen stands and assess conifer cover percent. We chose aspen stands in areas where wildfires overlapped (twice-burned), where only a single wildfire burned, and areas that did not burn within the recent 24-year period. We observed these same stands within the first period of fire exclusion for comparison (i.e., 1941–1993). In the absence of fire, all aspen stand areas declined and all stands experienced increases in conifer composition. After wildfire, stands that burned experienced a release from conifer competition and increased in stand area. Stands that burned twice or at high severity experienced a larger removal of conifer competition than stands that burned once at low severity, promoting expansion of aspen stand area. Stands with less edge:area ratio also expanded in area more with fire present. Across both time periods, stand movement, where aspen stand footprints were mostly in new areas compared to footprints of previous years, was highest in smaller stands. In the fire exclusion period, smaller stands exhibited greater loss of area and changes in location (movement) than in the return of fire period, highlighting their vulnerability to loss via succession to conifers in the absence of disturbances that provide adequate growing space for aspen over time.

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Abstract

Simple Summary: Many techniques exist to quantify enteric methane (CH4) emissions from dairy cows. Since measurement on the entire national cow populations is not possible, it is necessary to use estimates for national inventory reporting. This study aimed to develop (1) a basic equation of enteric CH4 emissions from individual animals based on feed intake and nutrient contents of the diet, and (2) to update the operational way of calculation used in the Norwegian National Inventory Report based on milk yield and concentrate share of the diet. An international database containing recently published data was used for this updating process. By this the accuracy of the CH4 production estimates included in the national inventory was improved. Abstract: The aim of this study was to develop a basic model to predict enteric methane emission from dairy cows and to update operational calculations for the national inventory in Norway. Development of basic models utilized information that is available only from feeding experiments. Basic models were developed using a database with 63 treatment means from 19 studies and were evaluated against an external database (n = 36, from 10 studies) along with other extant models. In total, the basic model database included 99 treatment means from 29 studies with records for enteric CH4 production (MJ/day), dry matter intake (DMI) and dietary nutrient composition. When evaluated by low root mean square prediction errors and high concordance correlation coefficients, the developed basic models that included DMI, dietary concentrations of fatty acids and neutral detergent fiber performed slightly better in predicting CH4 emissions than extant models. In order to propose country-specific values for the CH4 conversion factor Ym (% of gross energy intake partitioned into CH4 ) and thus to be able to carry out the national inventory for Norway, the existing operational model was updated for the prediction of Ym over a wide range of feeding situations. A simulated operational database containing CH4 production (predicted by the basic model), feed intake and composition, Ym and gross energy intake (GEI), in addition to the predictor variables energy corrected milk yield and dietary concentrate share were used to develop an operational model. Input values of Ym were updated based on the results from the basic models. The predicted Ym ranged from 6.22 to 6.72%. In conclusion, the prediction accuracy of CH4 production from dairy cows was improved with the help of newly published data, which enabled an update of the operational model for calculating the national inventory of CH4 in Norway.

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Abstract

Transport cost calculations are fundamental for most types of transport research. Applications can range from estimating the cost benefits of developing transport technologies (e.g. increased truck GVWs) to comparing profitability between alternative infrastructure investments (e.g. rail or sea terminals). Most stakeholders rely on a favourite spreadsheet, however these vary considerably with respect to functionality, resolution and transparency. During 2019 and 2020 the NB Nord Road and Transport group has worked towards a common Nordic-Baltic costing framework for road, rail and sea transport. The goal has been to propose a general model per transport method which is user-friendly, while retaining the necessary resolution and functionality to model actual costs for specific transport orders or contracts. The handbook provides: a) complete explanation of its formulas, b) calculation examples and c) a corresponding Excel spreadsheet...

Abstract

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Abstract

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.

Abstract

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.

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.