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
Authors
Jorge Aldea Ricardo Ruiz-Peinado Miren del Río Hans Pretzsch Michael Heym Gediminas Brazaitis Aris Jansons Marek Metslaid Ignacio Barbeito Kamil Bielak Aksel Granhus Stig-Olof Holm Arne Nothdurft Roman Sitko Magnus LöfAbstract
Mixed forests are suggested as a strategic adaptation of forest management to climate change. Scots pine (Pinus sylvestris L.) and Norway spruce (Picea abies (L.) Karst.) are tree species of high economic and ecological value for European forestry. Both species coexist naturally in a large part of their distributions but there is a lack of knowledge on the ecological functioning of mixtures of these species and how to manage such stands. This paper analyses these species' intra-and inter-specific competition, including size-symmetric vs. size-asymmetric competition, and explore the effect of weather conditions on tree growth and competition. We studied basal area growth at tree level for Scots pine and Norway spruce in mixed versus pure stands in 22 triplets of fully-stocked plots along a broad range of ecological conditions across Europe. Stand inventory and increment cores provided insights into how species mixing modifies tree growth compared with neighbouring pure stands. Five different competition indices, weather variables and their interactions were included and checked in basal area growth models using a linear mixed model approach. Interspecific size-asymmetric competition strongly influenced growth for both tree species, and was modulated by weather conditions. However, species height stratification in mixed stands resulted in a greater tree basal area growth of Scots pine (10.5 cm 2 year − 1) than in pure stands (9.3 cm 2 year − 1), as this species occupies the upper canopy layer. Scots pine growth depended on temperature and drought, whereas Norway spruce growth was influenced only by drought. Interspecific site-asymmetric competition increased in cold winters for Scots pine, and decreased after a drought year for Nor-way spruce. Although mixtures of these species may reduce tree size for Norway spruce, our results suggest that this could be offset by faster growth in Scots pine. How inter-specific competition and weather conditions alter tree growth may have strong implications for the management of Scots pine-Norway spruce mixtures along the rotation period into the ongoing climate change scenario.
Authors
Irina Orestovna Averkina Ivan Paponov Jose J Sanchez-Serrano Cathrine LilloAbstract
Plant growth-promoting rhizobacteria (PGPR) stimulate plant growth, but the underlying mechanism is poorly understood. In this study, we asked whether PROTEIN PHOSPHATASE 2A (PP2A), a regulatory molecular component of stress, growth, and developmental signaling networks in plants, contributes to the plant growth responses induced by the PGPR Azospirillum brasilense (wild type strain Sp245 and auxin deficient strain FAJ0009) and Pseudomonas simiae (WCS417r). The PGPR were co-cultivated with Arabidopsis wild type (WT) and PP2A (related) mutants. These plants had mutations in the PP2A catalytic subunits (C), and the PP2A activity-modulating genes LEUCINE CARBOXYL METHYL TRANSFERASE 1 (LCMT1) and PHOSPHOTYROSYL PHOSPHATASE ACTIVATOR (PTPA). When exposed to the three PGPR, WT and all mutant Arabidopsis revealed the typical phenotype of PGPR-treated plants with shortened primary root and increased lateral root density. Fresh weight of plants generally increased when the seedlings were exposed to the bacteria strains, with the exception of catalytic subunit double mutant c2c5. The positive effect on root and shoot fresh weight was especially pronounced in Arabidopsis mutants with low PP2A activity. Comparison of different mutants indicated a significant role of the PP2A catalytic subunits C2 and C5 for a positive response to PGPR.
Authors
Francesco Maria Sabatini Jonathan Lenoir Tarek Hattab Elise Aimee Arnst Milan Chytrý Jürgen Dengler Patrice De Ruffray Stephan M. Hennekens Ute Jandt Florian Jansen Borja Jiménez-Alfaro Jens Kattge Aurora Levesley Valério D. Pillar Oliver Purschke Brody Sandel Fahmida Sultana Tsipe Aavik Svetlana Aćić Alicia T.R. Acosta Emiliano Agrillo Miguel Álvarez Iva Apostolova Mohammed A. S. Arfin Khan Luzmila Arroyo Fabio Attorre Isabelle Aubin Arindam Banerjee Marijn Bauters Yves Bergeron Erwin Bergmeier Idoia Biurrun Anne D. Björkman Gianmaria Bonari Viktoria Bondareva Jörg Brunet Andraž Čarni Laura Casella Luis Cayuela Tomas Cerny Victor Chepinoga János Csiky Renata Ćušterevska Els De Bie André Luis De Gasper Michele De Sanctis Panayotis Dimopoulos Jiri Dolezal Tetiana Dziuba Mohamed Abd El-Rouf Mousa El-Sheikh Brian Enquist Jörg Ewald Farideh Fazayeli Richard Field Manfred Finckh Sophie Gachet Antonio Galán-De-Mera Emmanuel Garbolino Hamid Gholizadeh Melisa Giorgis Valentin Golub Inger Greve Alsos John Arvid Grytnes Gregory Richard Guerin Alvaro G. Gutiérrez Sylvia Haider Mohamed Z. Hatim Bruno Herault Guillermo Hinojos Mendoza Norbert Holzel Jürgen Homeier Zygmunt Kącki Jutta Kapfer Dirk Nikolaus Karger Ali Kavgaci Elizabeth Kearsley Helge BruelheideAbstract
Motivation Assessing biodiversity status and trends in plant communities is critical for understanding, quantifying and predicting the effects of global change on ecosystems. Vegetation plots record the occurrence or abundance of all plant species co-occurring within delimited local areas. This allows species absences to be inferred, information seldom provided by existing global plant datasets. Although many vegetation plots have been recorded, most are not available to the global research community. A recent initiative, called ‘sPlot’, compiled the first global vegetation plot database, and continues to grow and curate it. The sPlot database, however, is extremely unbalanced spatially and environmentally, and is not open-access. Here, we address both these issues by (a) resampling the vegetation plots using several environmental variables as sampling strata and (b) securing permission from data holders of 105 local-to-regional datasets to openly release data. We thus present sPlotOpen, the largest open-access dataset of vegetation plots ever released. sPlotOpen can be used to explore global diversity at the plant community level, as ground truth data in remote sensing applications, or as a baseline for biodiversity monitoring. Main types of variable contained Vegetation plots (n = 95,104) recording cover or abundance of naturally co-occurring vascular plant species within delimited areas. sPlotOpen contains three partially overlapping resampled datasets (c. 50,000 plots each), to be used as replicates in global analyses. Besides geographical location, date, plot size, biome, elevation, slope, aspect, vegetation type, naturalness, coverage of various vegetation layers, and source dataset, plot-level data also include community-weighted means and variances of 18 plant functional traits from the TRY Plant Trait Database. Spatial location and grain Global, 0.01–40,000 m². Time period and grain 1888–2015, recording dates. Major taxa and level of measurement 42,677 vascular plant taxa, plot-level records. Software format Three main matrices (.csv), relationally linked.
Abstract
No abstract has been registered
Abstract
Large population increases of Arctic-breeding waterfowls over recent decades have intensified the conflict with agricultural interests in both Eurasia and North America. In the spring-staging region Vesterålen in sub-Arctic Norway, sheep, dairy and meat farmers have reported reduced agricultural grassland yields due to pink-footed geese Anser brachyrhynchus and barnacle geese Branta leucopsis that rest and forage in the region for 3–4 weeks in spring on their way to their breeding grounds on Svalbard. Here, we report from an experimental exclosure design where goose access to plots at three grassland fields in Vesterålen was prevented. The experiment was conducted over 3 years between 2012 and 2014. Goose abundance varied greatly between fields and years as a function of variable spring weather and forage quantity, facilitating evaluation of longer-term impacts under contrasting grazing intensities. First and second harvest yields across fields and years were 20% and 19% higher in exclosures than in plots open for grazing, while total yields (sum of first and second harvests) were on average 27% higher. Within-year effects on harvest yields varied substantially, primarily due to highly contrasting sward development during the spring-staging periods. Cool weather (2012) led to slow sward development and little or no effects on harvest yields, warmer weather (2013) resulted in generally large effects, while variable weather (2014) led to treatment effects varying across fields, with one field experiencing 61% higher yields in exclosures while there were no significant impacts on first-harvest yields at the two other fields. Goose grazing did not increase dry weight-based proportions of weeds. Overall, the farmers' reports on yield-loss due to goose grazing were confirmed, although impacts varied substantially between years. A novel finding is that second-harvest yields were also reduced. For the most affected farmers, it is unlikely that the current subsidy scheme is sufficient to cover all the their losses.
Authors
Ziyan Xu Yongjie Kuang Bin Ren Daqi Yan Fang Yan Carl Jonas Jorge Spetz Wenxian Sun Guirong Wang Xueping Zhou Huanbin ZhouAbstract
Background Plant genome engineering mediated by various CRISPR-based tools requires specific protospacer adjacent motifs (PAMs), such as the well-performed NGG, NG, and NNG, to initiate target recognition, which notably restricts the editable range of the plant genome. Results In this study, we thoroughly investigate the nuclease activity and the PAM preference of two structurally engineered SpCas9 variants, SpG and SpRY, in transgenic rice. Our study shows that SpG nuclease favors NGD PAMs, albeit less efficiently than the previously described SpCas9-NG, and that SpRY nuclease achieves efficient editing across a wide range of genomic loci, exhibiting a preference of NGD as well as NAN PAMs. Furthermore, SpRY-fused cytidine deaminase hAID*Δ and adenosine deaminase TadA8e are generated, respectively. These constructs efficiently induce C-to-T and A-to-G conversions in the target genes toward various non-canonical PAMs, including non-G PAMs. Remarkably, high-frequency self-editing events (indels and DNA fragments deletion) in the integrated T-DNA fragments as a result of the nuclease activity of SpRY are observed, whereas the self-editing of SpRY nickase-mediated base editor is quite low in transgenic rice lines. Conclusions The broad PAM compatibility of SpRY greatly expands the targeting scope of CRISPR-based tools in plant genome engineering.
Authors
Teresa Barreneche Maria Cárcamo de la Concepción Marine Blouin-Delmas Matthew Ordidge Hilde Nybom Gunars Lacis Daina Feldmane Jiri Sedlak Mekjell Meland Hedi Kaldmae Kersti Kahu Zsuzsanna Bekefi Sanda Stanivukovic Gordana Đurić Monika Høfer Martin Galik Elisabeth Schüller Andreas Spornberger Sorina Sirbu Pavlina Drogoudi Ana Christina Agulheiro-Santos Ossama Kodad Ales Vokurka Marc Lateur Felicidad Fernandez Fernandez Daniela Giovannini José Quero-GarcíaAbstract
Sweet cherry (Prunus avium L.) is a temperate fruit species whose production might be highly impacted by climate change in the near future. Diversity of plant material could be an option to mitigate these climate risks by enabling producers to have new cultivars well adapted to new environmental conditions. In this study, subsets of sweet cherry collections of 19 European countries were genotyped using 14 SSR. The objectives of this study were (i) to assess genetic diversity parameters, (ii) to estimate the levels of population structure, and (iii) to identify germplasm redundancies. A total of 314 accessions, including landraces, early selections, and modern cultivars, were monitored, and 220 unique SSR genotypes were identified. All 14 loci were confirmed to be polymorphic, and a total of 137 alleles were detected with a mean of 9.8 alleles per locus. The average number of alleles (N = 9.8), PIC value (0.658), observed heterozygosity (Ho = 0.71), and expected heterozygosity (He = 0.70) were higher in this study compared to values reported so far. Four ancestral populations were detected using STRUCTURE software and confirmed by Principal Coordinate Analysis (PCoA), and two of them (K1 and K4) could be attributed to the geographical origin of the accessions. A N-J tree grouped the 220 sweet cherry accessions within three main clusters and six subgroups. Accessions belonging to the four STRUCTURE populations roughly clustered together. Clustering confirmed known genealogical data for several accessions. The large genetic diversity of the collection was demonstrated, in particular within the landrace pool, justifying the efforts made over decades for their conservation. New sources of diversity will allow producers to face challenges, such as climate change and the need to develop more sustainable production systems.
Authors
Giorgia Carnovale Filipa Rosa Volha Shapaval Simona Dzurendova Achim Kohler Trude Wicklund Svein Jarle Horn Maria J. Barbosa Kari SkjånesAbstract
The use of microalgal starch has been studied in biorefinery frameworks to produce bioethanol or bioplastics, however, these products are currently not economically viable. Using starch-rich biomass as an ingredient in food applications is a novel way to create more value while expanding the product portfolio of the microalgal industry. Optimization of starch production in the food-approved species Chlorella vulgaris was the main objective of this study. High-throughput screening of biomass composition in response to multiple stressors was performed with FTIR spectroscopy. Nitrogen starvation was identified as an important factor for starch accumulation. Moreover, further studies were performed to assess the role of light distribution, investigating the role of photon supply rates in flat panel photobioreactors. Starch-rich biomass with up to 30% starch was achieved in cultures with low inoculation density (0.1 g L−1) and high irradiation (1800 µmol m−2 s−1). A final large-scale experiment was performed in 25 L tubular reactors, achieving a maximum of 44% starch in the biomass after 12 h in nitrogen starved conditions.
Authors
Giorgia Carnovale Filipa Rosa Volha Shapaval Simona Dzurendova Achim Kohler Trude Wicklund Svein Jarle Horn Maria Barbosa Kari SkjånesAbstract
ABSTRACT The use of microalgal starch has been studied in biorefinery frameworks to produce bioethanol or bioplastics, however, these products are currently not economically viable. Using starch−rich biomass as an ingredient in food applications is a novel way to create more value while expanding the product portfolio of the microalgal industry. Optimization of starch production in the food−approved species Chlorella vulgaris was the main objective of this study. High−throughput screening of biomass composition in response to multiple stressors was performed with FTIR spectroscopy and nitrogen starvation was identified as an important factor for starch accumulation. Further studies were subsequently performed to assess the role of light distribution, investigating photon supply rates in flat panel photobioreactors. Biomass specific photon supply rate proved to have a strong effect on the accumulation of storage compounds and starch−rich biomass with up to 30% starch was achieved in cultures with low inoculation density (0.1 g L−1) and high irradiation (1800 μmol m−2 s−1). A final large scale experiment was performed in 25 L tubular reactors, achieving a maximum of 44% starch in the biomass after 12 hours in nitrogen starved conditions. Keywords: Chlorella vulgaris, starch, FTIR, photon supply rate, microalgae
Authors
Michal Sposob Radziah Wahid Svein Jarle HornAbstract
No abstract has been registered