Publikasjoner
NIBIOs ansatte publiserer flere hundre vitenskapelige artikler og forskningsrapporter hvert år. Her finner du referanser og lenker til publikasjoner og andre forsknings- og formidlingsaktiviteter. Samlingen oppdateres løpende med både nytt og historisk materiale. For mer informasjon om NIBIOs publikasjoner, besøk NIBIOs bibliotek.
2019
Forfattere
Manuel Jonas Steinbauer John Arvid Grytnes Gerald Jurasinski Aino Kulonen Jonathan Lenoir Harald Pauli Christian Rixen Manuela Winkler Manfred Bardy-Durchhalter Elena Barni Anne D. Bjorkman Frank T. Breiner Sarah Burg Patryk Czortek Melissa A. Dawes Anna Delimat Stefan Dullinger Brigitta Erschbamer Vivian Astrup Felde Olatz Fernández-Arberas Kjetil Farsund Fossheim Daniel Gómez-García D. Georges Erlend T. Grindrud Sylvia Haider Siri Vatsø Haugum Hanne Henriksen Maria J. Herreros Bogdan Jaroszewicz Francesca Orinda Holl Jaroszynska R. Kanka Jutta Kapfer Kari Klanderud Ingolf Kühn Andrea Lamprecht Magali Matteodo Umberto Morra di Cella Signe Normand Arvid Odland Siri Lie Olsen Sara Palacio Martina Petey Veronika Piscová Blazena Sedlakova Klaus Steinbauer Veronika Stöckli Jens-Christian Svenning Guido Teppa Jean-Paul Theurillat Pascal Vittoz Sarah J. Woodin Niklaus E. Zimmermann Sonja WipfSammendrag
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Sammendrag
The predicted and ongoing climate warming is expected to affect many aspects of plant development. We analysed data from a 31-year series of observations (1985–2016) on spring phenology and flowering and fruiting performance of three plum cultivars in an experimental orchard at Ås in southeast Norway (59° 40′N; 10° 50′E). Regression analyses revealed a trend of increasing March and April temperature during the study period that was highly significantly (P < 0.001) negatively correlated with the date of full bloom (FB). On average for all cultivars, blooming was advanced by 10 days over the study period. August and September temperature, which also increased significantly during the study period, was closely positively correlated with the amount of flowering in the subsequent spring and also interacted with early spring temperature in advancing blooming time. Investigation of the time of floral initiation in two of the studied plum cultivars revealed that the transition to reproductive development took place in early to mid-August. This finding strongly suggests that the close positive correlation between August-September temperature and the amount of flowering in plum observed in this and other studies, is causally linked to a specific physiological effect of elevated temperature on the flower bud formation process. Increasing March and April temperatures during the last 30 years has advanced blooming and spring phenology in plum and the resulting extension of the growing season has led to increasing fruit size at harvest. We conclude that so far, the ongoing climate warming appears to have been positive for plum production in the cool Nordic environment. However, an increasing risk of frost associated with earlier blooming will represent a potential negative effect of continued warming.
Sammendrag
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Forfattere
B. S. Steidinger T. W. Crowther J. Liang M. E. Van Nuland G. D. A. Werner P. B. Reich G. J. Nabuurs S. de-Miguel M. Zhou N. Picard B. Herault X. Zhao C. Zhang D. Routh Meinrad Abegg C. Yves Adou Yao Giorgio Alberti Angelica Almeyda Zambrano Esteban Alvarez-Davila Patricia Alvarez-Loayza Luciana F. Alves Christian Ammer Clara Antón Fernández Alejandro Araujo-Murakami Luzmila Arroyo Valerio Avitabile Gerardo Aymard Timothy Baker Radomir Bałazy Olaf Bánki Jorcely Barroso Meredith Bastian Jean-Francois Bastin Luca Birigazzi Philippe Birnbaum Robert Bitariho Pascal Boeckx Frans Bongers Olivier Bouriaud Pedro H. S. Brancalion Susanne Brandl Francis Q. Brearley Roel Brienen Eben Broadbent Helge Bruelheide Filippo Bussotti Roberto Cazzolla Gatti Ricardo Cesar Goran Cesljar Robin Chazdon Han Y. H. Chen Douglas Sheil K. G. PeaySammendrag
The identity of the dominant root-associated microbial symbionts in a forest determines the ability of trees to access limiting nutrients from atmospheric or soil pools1,2, sequester carbon3,4 and withstand the effects of climate change5,6. Characterizing the global distribution of these symbioses and identifying the factors that control this distribution are thus integral to understanding the present and future functioning of forest ecosystems. Here we generate a spatially explicit global map of the symbiotic status of forests, using a database of over 1.1 million forest inventory plots that collectively contain over 28,000 tree species. Our analyses indicate that climate variables—in particular, climatically controlled variation in the rate of decomposition—are the primary drivers of the global distribution of major symbioses. We estimate that ectomycorrhizal trees, which represent only 2% of all plant species7, constitute approximately 60% of tree stems on Earth. Ectomycorrhizal symbiosis dominates forests in which seasonally cold and dry climates inhibit decomposition, and is the predominant form of symbiosis at high latitudes and elevation. By contrast, arbuscular mycorrhizal trees dominate in aseasonal, warm tropical forests, and occur with ectomycorrhizal trees in temperate biomes in which seasonally warm-and-wet climates enhance decomposition. Continental transitions between forests dominated by ectomycorrhizal or arbuscular mycorrhizal trees occur relatively abruptly along climate-driven decomposition gradients; these transitions are probably caused by positive feedback effects between plants and microorganisms. Symbiotic nitrogen fixers—which are insensitive to climatic controls on decomposition (compared with mycorrhizal fungi)—are most abundant in arid biomes with alkaline soils and high maximum temperatures. The climatically driven global symbiosis gradient that we document provides a spatially explicit quantitative understanding of microbial symbioses at the global scale, and demonstrates the critical role of microbial mutualisms in shaping the distribution of plant species.
Sammendrag
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Forfattere
Oda Marie Kjørlaug Svennevik Greeley Beck Ester Rus Bjørge Westereng Matthew Higgins Odd Egil Solheim Pål Jahre Nilsen Svein Jarle HornSammendrag
Efficient digestate dewatering is crucial to reduce the volume and transportation cost of solid residues from anaerobic digestion (AD) plants. Large variations in dewatered cake solids have been reported and predictive models are therefore important in design and operation of such plants. However, current predictive models lack validation across several digestion substrates, pre-treatments and full-scale plants. In this study, we showed that thermogravimetric analysis is a reliable prediction model for dewatered cake solids using digestates from 15 commercial full-scale plants. The tested digestates originated from different substrates, with and without the pre-AD thermal hydrolysis process (THP). Moreover, a novel combined physicochemical parameter (C/N•ash) characterizing different digestate blends was identified by multiplying the C/N ratio with ash content of the dried solids. Using samples from 22 full-scale wastewater, food waste and co-waste plants, a linear relationship was found between C/N•ash and predicted cake solids for digestates with and without pre-AD THP. Pre-AD THP improved predicted cake solids by increasing the amount of free water. However, solids characteristics like C/N ratio and ash content had a more profound influence on the predicted cake solids than pre-AD THP and type of dewatering device. Finally, C/N•ash was shown to have a linear relationship to cake solids and reported polymer dose from eight full-scale pre-AD THP plants. In conclusion, we identified the novel parameter C/N•ash which can be used to predict dewatered cake solids regardless of dewatering device and sludge origin.
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Sammendrag
Multi-temporal Sentinel 2 optical images and 3D photogrammetric point clouds can be combined to enhance the accuracy of timber volume models on large spatial scale. Information on the proportion of broadleaf and conifer trees improves timber volume models obtained from 3D photogrammetric point clouds. However, the broadleaf-conifer information cannot be obtained from photogrammetric point clouds alone. Furthermore, spectral information of aerial images is too inconsistent to be used for automatic broadleaf-conifer classification over larger areas. In this study we combined multi-temporal Sentinel 2 optical satellite images, 3D photogrammetric point clouds from digital aerial stereo photographs, and forest inventory plots representing an area of 35,751 km2 in south-west Germany for (1) modelling the percentage of broadleaf tree volume (BL%) using Sentinel 2 time series and (2) modelling timber volume per hectare using 3D photogrammetric point clouds. Forest inventory plots were surveyed in the same years and regions as stereo photographs were acquired (2013–2017), resulting in 11,554 plots. Sentinel 2 images from 2016 and 2017 were corrected for topographic and atmospheric influences and combined with the same forest inventory plots. Spectral variables from corrected multi-temporal Sentinel 2 images were calculated, and Support VectorMachine (SVM) regressions were fitted for each Sentinel 2 scene estimating the BL% for corresponding inventory plots. Variables from the photogrammetric point clouds were calculated for each inventory plot and a non-linear regression model predicting timber volume per hectare was fitted. Each SVMregression and the timber volume model were evaluated using ten-fold cross-validation (CV). The SVMregression models estimating the BL% per Sentinel 2 scene achieved overall accuracies of 68%–75% and a Root Mean Squared Error (RMSE) of 21.5–26.1. The timber volumemodel showed a RMSE% of 31.7%, amean bias of 0.2%, and a pseudo-R2 of 0.64. Application of the SVMregressions on Sentinel 2 scenes covering the state of Baden-Württemberg resulted in predictions of broadleaf tree percentages for the entire state. These predicted values were used as additional predictor in the timber volume model, allowing for predictions of timber volume for the same area. Spatially high-resolution information about growing stock is of great practical relevance for forest management planning, especially when the timber volume of a smaller unit is of interest, for example of a forest stand or a forest districtwhere not enough terrestrial inventory plots are available to make reliable estimations. Here, predictions from remote-sensing based models can be used. Furthermore, information about broadleaf and conifer trees improves timber volume models and reduces model errors and, thereby, prediction uncertainties.
Sammendrag
Surface albedo is an important physical attribute of the climate system and satellite retrievals are useful for understanding how it varies in time and space. Surface albedo is sensitive to land cover and structure, which can vary considerably within the area comprising the effective spatial resolution of the satellite-based retrieval. This is particularly true for MODIS products and for topographically complex regions, such as Norway, which makes it difficult to separate the environmental drivers (e.g., temperature and snow) from those related to land cover and vegetation structure. In the present study, we employ high resolution datasets of Norwegian land cover and structure to spectrally unmix MODIS surface albedo retrievals (MCD43A3 v6) to study how surface albedo varies with land cover and structure. Such insights are useful for constraining land cover-dependent albedo parameterizations in models employed for regional climate or hydrological research and for developing new empirical models. At the scale of individual land cover types, we found that the monthly surface albedo can be predicted at a high accuracy when given additional information about forest structure, snow cover, and near surface air temperature. Such predictions can provide useful empirical benchmarks for climate model predictions made at the land cover level, which is critical for instilling greater confidence in the albedo-related climate impacts of anthropogenic land use/land cover change (LULCC).