2020
Authors
Durairaj Balasubramanian Wenjun Zhou Hongli Ji John Grace Xiaolong Bai Qinghai Song Yongtong Liu Liqing Sha Xuehai Fei Xiang Zhang Junbin Zhao Junfu Zhao Zhenghong Tan Yiping ZhangAbstract
No abstract has been registered
Authors
Shiori Koga Heidi Udnes Aamot Anne Kjersti Uhlen Till Seehusen Eva Veiseth-Kent Ingerd Skow Hofgaard Anette Moldestad Ulrike BöckerAbstract
This study aims to understand the environmental factors, focusing on rain and fungal infection, affecting the assembly of glutenin polymers during grain maturation. Spring wheat was grown in the field and grains were sampled from 50% grain moisture until maturity. Grain moisture content, protein content, size of glutenin polymers, the presence of proteases, and the amount of DNA from common wheat pathogenic fungi were analysed. Rain influenced the rate of grain desiccation that occurred parallel to the rate of glutenin polymer assembly. Rapid desiccation contributed to faster glutenin polymer assembly than gradual desiccation. Severe reduction in the glutenin polymer size coincided with increased grain moisture due to rain. Furthermore, increased fungal DNA followed by presence of gluten-degrading proteases was observed in the grain after humid conditions. The presence of gluten-degrading proteases was presumably involved in reducing the size of glutenin polymers in grain. Our study gave new insight into how environmental conditions could be associated with the assembly of glutenin polymers during grain maturation. The results suggest that rain and/or fungal proteases play an important role in reducing the molecular size of glutenin polymers.
Authors
Andreas TreuAbstract
Research activities in the field of wood protection in the marine environment in Europe have been limited and do not yet satisfy the need for new approaches to the problem of biodegradation of Wood in seawater. Alternatives to creosote treatment were tested in the marine environment in Moss harbour. Most of the treated products showed high potential as a successful treatment in this use class in the short-term, such as acetylation of wood, treatment with sorbitol and citric acid and encapsulation of wood poles with a plastic envelope. Long-term studies need to determine the service life of these products.
Authors
Anni Jašková Tatyana Yu. Braslavskaya Elena Tikhonova Jaanus Paal Solvita Rūsiņa Māris Laiviņš Ilya B. Kucherov Nadezhda V. Genikova Ilona Knollová Tatiana V. Chernenkova Elena Yu. Churakova Martin Diekmann Rune Halvorsen Elena I. Kirichok Vladimir N. Korotkov Alexander M. Kryshen Daria L. Lugovaya Olga V. Morozova Petr V. Potapov Tatiana S. Prokazina Fride Høistad Schei Yury A. Semenishchenkov Nikolai E. Shevchenko Oksana V. Sidorova Nikolai S. Smirnov Olga V. Smirnova Ruslan Tsvirko Svetlana A. Turubanova Milan ChytrýAbstract
The European Boreal Forest Vegetation Database (EBFVD, GIVD ID: EU-00-027) is a repository for vegetation-plot data from the forests of the boreal and hemiboreal zones of Europe. In this report, we describe its structure, current content and future perspectives opened up by the database. In February 2019, the database contained 13 037 vegetation-plot records from Belarus, Estonia, Finland, Latvia, Norway, Russia and Sweden that are not yet stored in the databases of the European Vegetation Archive (EVA). Consequently, this database significantly improves the availability of forest plant community data from Northern Europe. The database is managed by the Vegetation Science Group, Department of Botany and Zoology, Masaryk University, Brno (Czech Republic), in the TURBOVEG 2 program. It is registered in the Global Index of Vegetation Plot Databases (GIVD) and included in EVA. The whole database, or a subset of it, can be requested via EVA, or directly from the database custodian.
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Soil respiration is an important ecosystem process that releases carbon dioxide into the atmosphere. While soil respiration can be measured continuously at high temporal resolutions, gaps in the dataset are inevitable, leading to uncertainties in carbon budget estimations. Therefore, robust methods used to fill the gaps are needed. The process-based non-linear least squares (NLS) regression is the most widely used gap-filling method, which utilizes the established relationship between the soil respiration and temperature. In addition to NLS, we also implemented three other methods based on: 1) artificial neural networks (ANN), driven by temperature and moisture measurements, 2) singular spectrum analysis (SSA), relying only on the time series itself, and 3) the expectation-maximization (EM) approach, referencing to parallel flux measurements in the spatial vicinity. Six soil respiration datasets (2017–2019) from two boreal forests were used for benchmarking. Artificial gaps were randomly introduced into the datasets and then filled using the four methods. The time-series-based methods, SSA and EM, showed higher accuracies than NLS and ANN in small gaps (<1 day). In larger gaps (15 days), the performance was similar among NLS, SSA and EM; however, ANN showed large errors in gaps that coincided with precipitation events. Compared to the observations, gap-filled data by SSA showed similar degree of variances and those filled by EM were associated with similar first-order autocorrelation coefficients. In contrast, data filled by both NLS and ANN exhibited lower variance and higher autocorrelation than the observations. For estimations of the annual soil respiration budget, NLS, SSA and EM resulted in errors between −3.7% and 5.8% given the budgets ranged from 463 to 1152 g C m−2 year−1, while ANN exhibited larger errors from −11.3 to 16.0%. Our study highlights the two time-series-based methods which showed great potential in gap-filling carbon flux data, especially when environmental variables are unavailable.
Authors
Simo Maduna Adam Vivian-Smith ODB Jonsdottir Albert Imsland Cornelya Klutsch Tommi Nyman Hans Geir Eiken Snorre HagenAbstract
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Authors
Geir Wæhler GustavsenAbstract
No abstract has been registered