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.
2020
Authors
Leonardo H. Teixeira Florencia A. Yannelli Gislene Ganade Johannes KollmannAbstract
Ecosystem properties can be positively affected by plant functional diversity and compromised by invasive alien plants. We performed a community assembly study in mesocosms manipulating different functional diversity levels for native grassland plants (communities composed by 1, 2 or 3 functional groups) to test if functional dispersion could constrain the impacts of an invasive alien plant (Solidago gigantea) on soil fertility and plant community biomass via complementarity. Response variables were soil nutrients, soil water nutrients and aboveground biomass. We applied linear mixed-effects models to assess the effects of functional diversity and S. gigantea on plant biomass, soil and soil water nutrients. A structural equation model was used to evaluate if functional diversity and invasive plants affect soil fertility directly or indirectly via plant biomass and soil pH. Invaded communities had greater total biomass but less native plant biomass than uninvaded ones. While functional diversity increased nutrient availability in the soil solution of uninvaded communities, invasive plants reduced nutrient concentration in invaded soils. Functional diversity indirectly affected soil water but not soil nutrients via plant biomass, whereas the invader reduced native plant biomass and disrupted the effects of diversity on nutrients. Moreover, invasive plants reduced soil pH and compromised phosphate uptake by plants, which can contribute to higher phosphate availability and its possible accumulation in invaded soils. We found little evidence for functional diversity to constrain invasion impacts on nutrients and plant biomass. Restoration of such systems should consider other plant community features than plant trait diversity to reduce establishment of invasive plants.
Authors
Radosav Cerovic Milica Fotiric Akšic Milena Dordevic Mekjell MelandAbstract
Since the European pear (Pyrus communis L.) is a self-incompatible fruit species, synchrony and compatibility between female parts of the mother plant and male gametes from the pollen donor must be fulfilled. Besides pollination and fertilization, normal embryo and zygote development is one of the prerequisites for the satisfactory yields in pears. The main goal of this experiment was to investigate the functionality of embryo sacs and the embryo’s early stages of growth in relation to the fruit set of diploid (‘Celina’) and the triploid (‘Ingeborg’) pear cultivars under specific Norwegian climatic conditions. For this purpose, flowers were collected at the beginning of flowering, and on the third, sixth, ninth, and twelfth days after the beginning of this phenophase for two consecutive years. Ovaries were dehydrated, embedded in paraffin wax, sectioned, stained, and observed under the light microscope. In the analyzed cultivars, results showed different tendencies in embryo sac development and degradation processes, in both experimental years, which is probably due to the genetic background of the examined cultivars. Also, fertilization success and fruit set were higher in the second year of study due to the higher average temperature during the flowering period. Diploid cultivar ‘Celina’ showed much better adaptation to high temperatures in relation to triploid cultivar ‘Ingeborg’.
Authors
Nanna Bjerregaard Pedersen Henning Matthiesen Robert A. Blanchette Gry Alfredsen Benjamin W. Held Andreas Westergaard‑Nielsen Jørgen HollesenAbstract
Climate change is expected to accelerate the microbial degradation of the many extraordinary well-preserved organic archaeological deposits found in the Arctic. This could potentially lead to a major loss of wooden artefacts that are still buried within the region. Here, we carry out the first large-scale investigation of wood degradation within archaeological deposits in the Arctic. This is done based on wooden samples from 11 archaeological sites that are located along a climatic gradient in Western Greenland. Our results show that Ascomycota fungi are causing extensive soft rot decay at all sites regardless of climate and local environment, but the group is diverse and many of the species were only found once. Cadophora species known to cause soft rot in polar environments were the most abundant Ascomycota found and their occurrence in native wood samples underlines that they are present locally. Basidiomycota fungi were also present at all sites. In the majority of samples, however, these aggressive and potentially very damaging wood degraders have caused limited decay so far, probably due to unfavorable growth conditions. The presence of these wood degrading fungi suggests that archaeological wooden artefacts may become further endangered if climate change leads to more favorable growth conditions.
Authors
Ingerd Skow Hofgaard Heidi Udnes Aamot Till Seehusen Hugh Riley Ruth Dill-Macky Børge Holen Guro BrodalAbstract
To mitigate the risk of erosion and nutrient runoff, reduced tillage has become more prevalent in Norway. Within within recent decades, there have been some years with relatively high occurrence of Fusarium head blight and mycotoxins in Norwegian cereal grain. This is thought to have been caused by an increased inoculum potential (IP) of Fusarium spp. due to larger amount of crop residues remaining on the soil surface, in combination with weather conditions promoting fungal growth and infection of cereal plants. The objective of this work was to elucidate the influence of different tillage practices on the IP of Fusarium spp. and the subsequent Fusarium-infection and mycotoxin contamination of spring wheat grain at harvest. Tillage trials were conducted at two locations in southeast Norway (Solør and Toten) over three years, 2010-2012. Residues of wheat from the previous year were collected in spring. Fusarium avenaceum and Fusarium graminearum were the most common Fusarium species recorded on wheat straw residues. IP was calculated as the percentage of the residues infested with Fusarium spp. multiplied by the proportion of the soil surface covered with residues. The IP of Fusarium spp. was lower in ploughed plots compared to those tilled with harrowing only. Ploughing in spring resulted in a similarly low IP as autumn ploughing. In contrast, harrowing in autumn generally reduced IP more than did spring harrowing. The mycotoxin levels in the harvested wheat were generally low, except for deoxynivalenol at high levels in Solør 2011. Despite a lower IP of ploughed versus harrowed plots, this was not reflected in the content of Fusarium and mycotoxins in harvested grain. The Fusarium species that dominated in the residues examined in this study were the same as those detected in the harvested grain, supporting the finding that residues are an important source of inoculum.
Authors
Han Zhang Sabine Andert Lars Olav Brandsæter Jesper Rasmussen M-H. Robin Jukka Salonen Kirsten Tørresen Muriel Valantin-Morison Bärbel GerowittAbstract
No abstract has been registered
Abstract
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.
Abstract
No abstract has been registered
Authors
Xiao Huang Shaoqiang Ni Chao Wu Conrad Zorn Wenyuan Zhang Chaoqing YuAbstract
Agroecosystem modelling has increasingly focused on the integration of soil biogeochemical processes and crop growth. However, few models are available that offer high computing efficiencies for region-scale simulations, integrated decision support tools, and a structure that allows for easy extension. This paper introduces a new modeling tool to fill this gap: the GDNDC (Gridded DNDC) system for gridded agro-biogeochemical simulations. Based on the established DeNitrification and DeComposition (DNDC) model version-95, its main advancements include (i) implementation of parallel computation to significantly reduce computation time across multiple scales; (ii) a built-in parameter optimization algorithm to improve the predictive accuracy, and (iii) several decision support tools. We demonstrate each of these for county-level maize growth simulations in Liaoning Province (China) and reveal the potential of this new modeling tool to guide both long-term policy decisions regarding optimal fertilizer application and near-term crop yield forecasting for reactive decisions required in times of drought.
Authors
Lélis A. Carlos-Júnior Joel C. Creed Rob Marrs Rob J. Lewis Timothy P. Moulton Rafael Feijó-Lima Matthew SpencerAbstract
Background Ecological communities tend to be spatially structured due to environmental gradients and/or spatially contagious processes such as growth, dispersion and species interactions. Data transformation followed by usage of algorithms such as Redundancy Analysis (RDA) is a fairly common approach in studies searching for spatial structure in ecological communities, despite recent suggestions advocating the use of Generalized Linear Models (GLMs). Here, we compared the performance of GLMs and RDA in describing spatial structure in ecological community composition data. We simulated realistic presence/absence data typical of many β-diversity studies. For model selection we used standard methods commonly used in most studies involving RDA and GLMs. Methods We simulated communities with known spatial structure, based on three real spatial community presence/absence datasets (one terrestrial, one marine and one freshwater). We used spatial eigenvectors as explanatory variables. We varied the number of non-zero coefficients of the spatial variables, and the spatial scales with which these coefficients were associated and then compared the performance of GLMs and RDA frameworks to correctly retrieve the spatial patterns contained in the simulated communities. We used two different methods for model selection, Forward Selection (FW) for RDA and the Akaike Information Criterion (AIC) for GLMs. The performance of each method was assessed by scoring overall accuracy as the proportion of variables whose inclusion/exclusion status was correct, and by distinguishing which kind of error was observed for each method. We also assessed whether errors in variable selection could affect the interpretation of spatial structure. Results Overall GLM with AIC-based model selection (GLM/AIC) performed better than RDA/FW in selecting spatial explanatory variables, although under some simulations the methods performed similarly. In general, RDA/FW performed unpredictably, often retaining too many explanatory variables and selecting variables associated with incorrect spatial scales. The spatial scale of the pattern had a negligible effect on GLM/AIC performance but consistently affected RDA’s error rates under almost all scenarios. Conclusion We encourage the use of GLM/AIC for studies searching for spatial drivers of species presence/absence patterns, since this framework outperformed RDA/FW in situations most likely to be found in natural communities. It is likely that such recommendations might extend to other types of explanatory variables.
Abstract
The Norwegian coastal goat is a national and endangered breed. Coastal goat populations are mainly divided with a large mainland and two small island populations. The objective of this study is to describe genetic diversity in the feral Skorpa island population and its relationship to the mainland coastal goat population (Selje) using the Norwegian milk goat population as a reference. Analyses were based on 96 samples genotyped by the CaprineSNP50 Beadchip from three populations; 7 Skorpa (SK), 37 Selje (SE) and 52 Norwegian milk goats (MG). The SK population had significantly less genetic variation and higher levels of inbreeding than the two other populations. It was more distant from the two mainland populations than they were from each other. The marginal contribution of the SK population to genetic diversity was small. Means of introducing genetic diversity into the SK population should be considered if the population is prioritized for conservation.