Publikasjoner
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2023
Forfattere
Ralf RautenbergerSammendrag
Aquaculture of marine macroalgae is an important part of the world’s food production. In Norway, the fast-growing kelp Saccharina latissima has the highest potential for industrial biomass production. Aquaculture in the country’s fjords is economically more viable for SMEs, supports the development of IMTA and could allow the industry to approach the projected 20 million tons by 2050. However, S. latissima is exposed to a considerable decline in seawater salinity during the growth season, which affects the biomass production. This presentation shows results of industrial R&D projects in which the presence of “low-salinity tolerant” strains of S. latissima in a North Norwegian fjord and their responses to the seasonal salinity decline was studied. In a laboratory-based common garden experiment, sporophytes of S. latissima from different locations in Skjerstadfjorden were cultivated under different salinities for six weeks. Growth and photosynthetic parameters were measured to understand their physiological responses to salinity stress. Then their F1 generation were seeded on ropes and deployed at a commercial aquaculture site in Skjerstadfjorden to study strain-specific differences in biomass production and yield, optimal growth depths and biochemical composition of S. latissima. In addition, the aquaculture site was characterised by measurements of physical and chemical parameters. The projects’ results will help North Norwegian macroalgae producers to improve the biomass production and biochemical composition of S. latissima. These findings could lay the foundation for the development of breeding programmes in Norway and could demonstrate the macroalgae producers in Norway the possibility of establishing aquaculture in fjords.
Sammendrag
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Sammendrag
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Sammendrag
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Forfattere
Chloé GrieuSammendrag
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Forfattere
Chloé GrieuSammendrag
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Forfattere
Yi Zhang Yijing Feng Zhonghao Ren Runguo Zuo Tianhui Zhang Yeqing Li Yajing Wang Zhiyang Liu Ziyan Sun Yongming Han Lu Feng Mortaza Aghbashlo Meisam Tabatabaei Junting PanSammendrag
The ideal conditions for anaerobic digestion experiments with biochar addition are challenging to thoroughly study due to different experimental purposes. Therefore, three tree-based machine learning models were developed to depict the intricate connection between biochar properties and anaerobic digestion. For the methane yield and maximum methane production rate, the gradient boosting decision tree produced R2 values of 0.84 and 0.69, respectively. According to feature analysis, digestion time and particle size had a substantial impact on the methane yield and production rate, respectively. When particle sizes were in the range of 0.3–0.5 mm and the specific surface area was approximately 290 m2/g, corresponding to a range of O content (>31%) and biochar addition (>20 g/L), the maximum promotion of methane yield and maximum methane production rate were attained. Therefore, this study presents new insights into the effects of biochar on anaerobic digestion through tree-based machine learning.
Forfattere
Adam Eindride Naas Rune Halvorsen Peter Horvath Anders Kvalvåg Wollan Harald Bratli Katrine Marie Brynildsrud Eirik Aasmo Finne Lasse Torben Keetz Eva Lieungh Christine Olson Trond Simensen Olav Skarpaas Hilde Tandstad Michal Torma Espen Sommer Værland Anders BrynSammendrag
Questions Field-based ecosystem mapping is prone to observer bias, typically resulting in a mismatch between maps made by different mappers, that is, inconsistency. Experimental studies testing the influence of site, mapping scale, and differences in experience level on inconsistency in field-based ecosystem mapping are lacking. Here, we study how inconsistencies in field-based ecosystem maps depend on these factors. Location Iškoras and Guollemuorsuolu, northeastern Norway, and Landsvik and Lygra, western Norway. Methods In a balanced experiment, four sites were field-mapped wall-to-wall to scales 1:5000 and 1:20,000 by 12 mappers, representing three experience levels. Thematic inconsistency was calculated by overlay analysis of map pairs from the same site, mapped to the same scale. We tested for significant differences between sites, scales, and experience-level groups. Principal components analysis was used in an analysis of additional map inconsistencies and their relationships with site, scale and differences in experience level and time consumption were analysed with redundancy analysis. Results On average, thematic inconsistency was 51%. The most important predictor for thematic inconsistency, and for all map inconsistencies, was site. Scale and its interaction with site predicted map inconsistencies, but only the latter were important for thematic inconsistency. The only experience-level group that differed significantly from the mean thematic inconsistency was that of the most experienced mappers, with nine percentage points. Experience had no significant effect on map inconsistency as a whole. Conclusion Thematic inconsistency was high for all but the dominant thematic units, with potentially adverse consequences for mapping ecosystems that are fragmented or have low coverage. Interactions between site and mapping system properties are considered the main reasons why no relationships between scale and thematic inconsistency were observed. More controlled experiments are needed to quantify the effect of other factors on inconsistency in field-based mapping.
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