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
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Divina Gracia P. RodriguezAbstract
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Rasmus AstrupAbstract
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Background The Norwegian forest resource map (SR16) maps forest attributes by combining national forest inventory (NFI), airborne laser scanning (ALS) and other remotely sensed data. While the ALS data were acquired over a time interval of 10 years using various sensors and settings, the NFI data are continuously collected. Aims of this study were to analyze the effects of stratification on models linking remotely sensed and field data, and assess the accuracy overall and at the ALS project level. Materials and methods The model dataset consisted of 9203 NFI field plots and data from 367 ALS projects, covering 17 Mha and 2/3 of the productive forest in Norway. Mixed-effects regression models were used to account for differences among ALS projects. Two types of stratification were used to fit models: 1) stratification by the three main tree species groups spruce, pine and deciduous resulted in species-specific models that can utilize a satellite-based species map for improving predictions, and 2) stratification by species and maturity class resulted in stratum-specific models that can be used in forest management inventories where each stand regularly is visually stratified accordingly. Stratified models were compared to general models that were fit without stratifying the data. Results The species-specific models had relative root-mean-squared errors (RMSEs) of 35%, 34%, 31%, and 12% for volume, aboveground biomass, basal area, and Lorey’s height, respectively. These RMSEs were 2–7 percentage points (pp) smaller than those of general models. When validating using predicted species, RMSEs were 0–4 pp. smaller than those of general models. Models stratified by main species and maturity class further improved RMSEs compared to species-specific models by up to 1.8 pp. Using mixed-effects models over ordinary least squares models resulted in a decrease of RMSE for timber volume of 1.0–3.9 pp., depending on the main tree species. RMSEs for timber volume ranged between 19%–59% among individual ALS projects. Conclusions The stratification by tree species considerably improved models of forest structural variables. A further stratification by maturity class improved these models only moderately. The accuracy of the models utilized in SR16 were within the range reported from other ALS-based forest inventories, but local variations are apparent.
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Pia Heltoft ThomsenAbstract
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Many greenkeepers and authorities are concerned about the environmental risks resulting from pesticide use on golf courses. We studied leaching and surface runoff of fungicides and metabolites during two winter seasons after fall application of boscalid, pyraclostrobin, prothioconazole, trifloxystrobin and fludioxonil in field lysimeters at NIBIO Landvik, Norway. The applications were made on creeping bentgrass greens (5% slope) that had been established from seed or sod (26 mm mat) on USGA‐spec. root zones amended with Sphagnum peat or garden compost, both with 0.3‐0.4% organic carbon in the root zone. The proportions of the winter precipitation recovered as surface and drainage water varied from 3 and 91% in 2016‐17 to 33 and 55% in 2017‐18 due to differences in soil freezing, rainfall intensity and snow and ice cover. Detections of fungicides and their metabolites in drainage water were mostly within the Environmental Risk Limits (ERLs) for aquatic organisms. In contrast, concentrations in surface runoff exceeded ERLs by up to 1000 times. Greens established from sod usually had higher fungicide losses in surface runoff but lower losses in drainage water than greens established from seed. Presumably because of higher microbial activity and a higher pH that made prothioconazole‐desthio more polar, fungicide and metabolite losses in drainage water were usually higher from greens containing compost that from greens containing peat. Leaching of fungicides and metabolites occurred even from frozen greens. The results are discussed in a practical context aiming for reduced environmental risks from spraying fungicides against turfgrass winter diseases.
Abstract
Sustainability learning is gaining popularity as an important field within sustainability research, where farm sustainability can be understood as a learning process. In this study, we seek to reveal the sustainability learning process of farmers, utilizing a framework distinguishing contextual factors (where? and when?), knowledge (what?), motivation (why?), and process (how?). The article presents a participatory inquiry mixed-methods approach, utilizing results from sustainability assessments on five farms with the SMART-farm tool as a unifying starting point for further discussions on sustainability learning in farmers' interviews and stakeholder workshops. Empirically the study is set in the horticultural production in Arctic Norway, where few studies on sustainability have been undertaken. The study shows how both the complexity of the concept of farm sustainability and contextual factors influence the sustainability learning process, for instance by giving rise to a vast number of conflicting issues while working toward farm sustainability. The sustainability learning process is found to be predominantly a social learning process. The theoretic contribution of the study lies in its novel framework that can be used to reveal important aspects of the sustainability learning process, as well as to contribute to the literature on how to proceed from sustainability assessments to implementation. A key finding from the study is that farmers will require continuous assistance in their processes toward farm sustainability, but for this to be possible, knowledge, sources of knowledge, and learning platforms for holistic sustainability need to be established.