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.
2019
Abstract
Laboratory screening tests are commonly used to indicate wood materials’ resistance or susceptibility to surface mould growth, but the results can deviate from what happens during outdoor exposure. In this study, the aim was to investigate how well agar plate screening tests and water uptake tests can predict mould growth on exterior wooden claddings. The tested wood materials included Norway spruce heartwood (Picea abies), sapwood and heartwood of Scots pine (Pinus sylvestris), aspen (Populus tremula), acetylated Radiata pine (Pinus radiata) and DMDHEU-modifed Scots pine sapwood. The agar plate test included four inoculation methods (two monoculture spore suspensions of Aureobasidium species, one mixed-culture spore suspension, and inoculation from outdoor air) and three incubation temperatures (5, 16 and 27 °C). Inoculation method and incubation temperature had signifcant efects on the mould rating in the agar plate screening test, but none of the agar plate test combinations gave good indications of outdoor performance. Results from the agar plate test gave signifcantly negative correlations or no signifcant correlation with results from the outdoor test. However, the water uptake test gave signifcantly positive correlations with outdoor mould rating, and could be a useful indicator of susceptibility of uncoated wooden claddings to surface mould growth.
Abstract
This study addresses changes in visual appearance of unpainted wood materials exposed outdoors. Specimens of aspen (Populus tremula), Norway spruce (Picea abies), untreated Scots pine (Pinus sylvestris), DMDHEU-modified Scots pine and acetylated Radiata pine (Pinus radiata) were exposed facing south in Ås, Norway for 62 weeks. During this period, mould growth coverage, lightness (L*) and the uniformity of the weather grey colour were assessed. Mould growth coverage was evaluated visually using a rating system. L* and the uniformity were evaluated using image analysis. The increase in mould rating of the wood materials developed in varying speed, but all specimens had reached the maximum rating after 42 weeks. Until then, the changes in L* correlated significantly with the mould rating. However, the specimens continued to darken after they had reached maximum mould rating. DMDHEU was the only material that obtained a more uniform colour as a consequence of the weathering.
Authors
Kaiguang Zhao Michael A. Wulder Tongxi Hu Ryan Bright Qiusheng Wu Haiming Qin Yang Li Elizabeth Toman Bani Mallick Xuesong Zhang Molly BrownAbstract
Satellite time-series data are bolstering global change research, but their use to elucidate land changes and vegetation dynamics is sensitive to algorithmic choices. Different algorithms often give inconsistent or sometimes conflicting interpretations of the same data. This lack of consensus has adverse implications and can be mitigated via ensemble modeling, an algorithmic paradigm that combines many competing models rather than choosing only a single “best” model. Here we report one such time-series decomposition algorithm for deriving nonlinear ecosystem dynamics across multiple timescales—A Bayesian Estimator of Abrupt change, Seasonal change, and Trend (BEAST). As an ensemble algorithm, BEAST quantifies the relative usefulness of individual decomposition models, leveraging all the models via Bayesian model averaging. We tested it upon simulated, Landsat, and MODIS data. BEAST detected changepoints, seasonality, and trends in the data reliably; it derived realistic nonlinear trends and credible uncertainty measures (e.g., occurrence probability of changepoints over time)—some information difficult to derive by conventional single-best-model algorithms but critical for interpretation of ecosystem dynamics and detection of low-magnitude disturbances. The combination of many models enabled BEAST to alleviate model misspecification, address algorithmic uncertainty, and reduce overfitting. BEAST is generically applicable to time-series data of all kinds. It offers a new analytical option for robust changepoint detection and nonlinear trend analysis and will help exploit environmental time-series data for probing patterns and drivers of ecosystem dynamics.
Abstract
Due to the potential for land-use–land-cover change (LULCC) to alter surface albedo, there is need within the LULCC science community for simple and transparent tools for predicting radiative forcings (ΔF) from surface albedo changes (Δαs). To that end, the radiative kernel technique – developed by the climate modeling community to diagnose internal feedbacks within general circulation models (GCMs) – has been adopted by the LULCC science community as a tool to perform offline ΔF calculations for Δαs. However, the codes and data behind the GCM kernels are not readily transparent, and the climatologies of the atmospheric state variables used to derive them vary widely both in time period and duration. Observation-based kernels offer an attractive alternative to GCM-based kernels and could be updated annually at relatively low costs. Here, we present a radiative kernel for surface albedo change founded on a novel, simplified parameterization of shortwave radiative transfer driven with inputs from the Clouds and the Earth's Radiant Energy System (CERES) Energy Balance and Filled (EBAF) products. When constructed on a 16-year climatology (2001–2016), we find that the CERES-based albedo change kernel – or CACK – agrees remarkably well with the mean kernel of four GCMs (rRMSE = 14 %). When the novel parameterization underlying CACK is applied to emulate two of the GCM kernels using their own boundary fluxes as input, we find even greater agreement (mean rRMSE = 7.4 %), suggesting that this simple and transparent parameterization represents a credible candidate for a satellite-based alternative to GCM kernels. We document and compute the various sources of uncertainty underlying CACK and include them as part of a more extensive dataset (CACK v1.0) while providing examples showcasing its application.
Abstract
Vegetation optical properties have a direct impact on canopy absorption and scattering and are thus needed for modeling surface fluxes. Although plant functional type (PFT) classification varies between different land surface models (LSMs), their optical properties must be specified. The aim of this study is to revisit the “time-invariant optical properties table” of the Simple Biosphere (SiB) model (later referred to as the “SiB table”) presented 30 years ago by Dorman and Sellers (1989), which has since been adopted by many LSMs. This revisit was needed as many of the data underlying the SiB table were not formally reviewed or published or were based on older papers or on personal communications (i.e., the validity of the optical property source data cannot be inspected due to missing data sources, outdated citation practices, and varied estimation methods). As many of today's LSMs (e.g., the Community Land Model (CLM), the Jena Scheme of Atmosphere Biosphere Coupling in Hamburg (JSBACH), and the Joint UK Land Environment Simulator (JULES)) either rely on the optical properties of the SiB table or lack references altogether for those they do employ, there is a clear need to assess (and confirm or correct) the appropriateness of those being used in today's LSMs. Here, we use various spectral databases to synthesize and harmonize the key optical property information of PFT classification shared by many leading LSMs. For forests, such classifications typically differentiate PFTs by broad geo-climatic zones (i.e., tropical, boreal, temperate) and phenology (i.e., deciduous vs. evergreen). For short-statured vegetation, such classifications typically differentiate between crops, grasses, and photosynthetic pathway. Using the PFT classification of the CLM (version 5) as an example, we found the optical properties of the visible band (VIS; 400–700 nm) to fall within the range of measured values. However, in the near-infrared and shortwave infrared bands (NIR and SWIR; e.g., 701–2500 nm, referred to as “NIR”) notable differences between CLM default and measured values were observed, thus suggesting that NIR optical properties are in need of an update. For example, for conifer PFTs, the measured mean needle single scattering albedo (SSA, i.e., the sum of reflectance and transmittance) estimates in NIR were 62 % and 78 % larger than the CLM default parameters, and for PFTs with flat leaves, the measured mean leaf SSA values in NIR were 20 %, 14 %, and 19 % larger than the CLM defaults. We also found that while the CLM5 PFT-dependent leaf angle values were sufficient for forested PFTs and grasses, for crop PFTs the default parameterization appeared too vertically oriented, thus warranting an update. In addition, we propose using separate bark reflectance values for conifer and deciduous PFTs and demonstrate how shoot-level clumping correction can be incorporated into LSMs to mitigate violations of turbid media assumption and Beer's law caused by the nonrandomness of finite-sized foliage elements.
Abstract
Deforestation influences surface properties such as surface roughness, resulting in changes in the surface energy balance and surface temperature. Recent studies suggest that the biogeophysical effects are dominated by changing roughness, and it remains unclear whether this can be reconciled with earlier modeling studies that highlighted the importance of a reduction of evapotranspiration in the low latitudes and a reduction of net shortwave radiation at the surface in the high latitudes. To clarify this situation, we analyze the local effects of deforestation on surface energy balance and temperature in the MPI‐ESM climate model by performing three separate experiments: switching from forest to grass all surface properties, only surface albedo, and only surface roughness. We find that the locally induced changes in surface temperature are dominated by changes in surface roughness for the annual mean, the response of the diurnal amplitude, and the seasonal response to deforestation. For these three quantities, the results of the MPI‐ESM lie within the range of observation‐based data sets. Deforestation‐induced decreases in surface roughness contribute substantially to winter cooling in the boreal regions and to decreases in evapotranspiration in the tropics. By comparing the energy balance decompositions from the three experiments, the view that roughness changes dominate the biogeophysical consequences of deforestation can be reconciled with the earlier studies highlighting the relevance of evapotranspiration.
Authors
Nick Hodgetts Marta Cálix Eve Englefield Nicholas Fettes M. García Criado Lea Patin Ana Nieto Ariel Bergamini Irene Bisang Elvira Baisheva Patrizio Campisi A Cogoni Tomas Hallingbäck Nadya A. Konstantinova Neil Lochhart Marko Sabovljevic Norbert Schnyder Christian Schröck Cecília Sérgio Manuela Sim-Sim Jaroslav Vrba Catarina C. Ferreira Olga M. Afonina T.L. Blockeel Hans Blom Steffen Caspari Rosalina Gabriel Cesar Garcia Ricardo Garilleti J González Mancebo Irina Goldberg Lars Hedenäs David T. Holyoak Vincent Hugonnot Sanna Huttunen Mikhail S. Ignatov Elena A. Ignatova Marta Infante Riikka Juutinen Thomas Kiebacher Heribert Köckinger Jan Kucera Niklas Lönnell Michael Lüth Anabela Martins Oleg Maslovsky Beata Papp Ron Porley Gordon Rothero Lars Söderström Sorin Ştefǎnuţ Kimmo Syrjänen Alain Untereiner Jíri Vána Alain Vanderpoorten Kai Vellak Michele Aleffi J. W. Bates Neil Bell Montserrat Brugués Nils Cronberg Jo Denyer J.G. Duckett Heinjo During Johannes Enroth Vladimir E. Fedosov Kjell Ivar Flatberg Anna Ganeva Piotr Gorski Urban Gunnarsson Kristian Hassel Helena Hespanhol Mark O. Hill Rory Hodd Kristoffer Hylander Nele Ingerpuu Sanna Laaka-Lindberg Francisco Lara Vicente Mazimpaka Anna Mežaka Frank Müller Jose David Orgaz Jairo Patiño Sharon Pilkington Felisa Puche Rosa Maria Ros Fred Rumsey José Gabriel Segarra-Moragues Ana Séneca Adam Stebel Risto Virtanen Henrik Weibull Jo Wilbraham Jan ZarnowiecAbstract
No abstract has been registered
Abstract
We distinguish five Xanthomendoza species in Norway, viz., X. borealis, X. fallax, X. fulva, X. oregana, and X. ulophyllodes, based on morphology and molecular evidence. This paper gives an updated taxonomy of the Norwegian species of Xanthomendoza, and addresses previous misconceptions. Xanthomendoza ulophyllodes is reported as occurring in Norway. The species was previously misunderstood in Norway and removed from the Nordic checklist. We show that the nuclear internal transcribed spacer (nrITS) is a useful barcode marker for the treated species. We provide a key and short descriptions of the species, with notes on specific issues, ecology, geographic distribution, illustrations, maps, and a DNA reference library (DNA barcoding).
Abstract
No abstract has been registered
Authors
O. Janne Kjønaas Ivika Ostonen Lars Vesterdal Raija Laiho Tuula Larmola Edda S. Oddsdóttir Zane Libiete Iveta Varnagirytė-KabašinskienėAbstract
No abstract has been registered