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
Authors
Jordi Doltra Patricia Gallejones Jørgen E. Olesen Sissel Hansen Randi Berland Frøseth Maike Krauss Jarosław Stalenga Krzysztof Jończyk Adela Martínez-Fernández Gaio Cesare PaciniAbstract
Soil fertility building measures should be explored at the short and long-term for an adequate evaluation of their impact on sustaining yields and of its environmental consequences in crop rotations under organic farming. For such a purpose, process-based crop models are potential useful tools to complement and upscale field observations under a range of soil and climatic conditions. Organic rotations differ in soil fertility dynamics in comparison to conventional farming but very few modelling studies have explicitly considered this specific situation. Here, we evaluate the FASSET model to predict the effects of different fertility management options in organic crop rotations on dry matter (DM) and nitrogen (N) yield, and soil N dynamics, including N2O emissions. For that, we used data from seven short and long-term field experiments in different agro-climatic environments in Europe (Norway, Denmark, Poland, Switzerland, Italy and Spain) including climate, soil and management data. Soil fertility building measures covered fertilization type, green manures, cover crops, tillage, crop rotation composition and management (organic or conventional). Model performance was evaluated by comparing observed and simulated values of crop DM and N yield, soil mineral N and nitrous oxide (N2O) emissions using five complementary statistical indices. The model closely reproduced most observed DM and N yield trends and effects of soil fertility building measures in arable crops, particularly in cereals. Contrary, yields of grass-clover, especially N, were generally reproduced with low degree of accuracy. Model performance for simulating soil mineral N depended on site and the availability of soil and management information. Although high uncertainty was associated to the simulation of soil N dynamics, differences of cumulative N2O emissions between fertility building measures were reflected in model outputs. Aspects for modelling improvement include cover crop growth and decomposition, biological N fixation (BNF) or weed and pest soil-crop interactions. It is concluded that FASSET can be successfully used to investigate the impact of fertilization type, green manures, tillage and management (organic or conventional) on crop productivity and to a certain extent on soil N dynamics including soil N2O emissions at different soils and climates in organic farming in Europe.
Abstract
No abstract has been registered
Authors
Fen Qiao Ling-An Kong Huan Peng Wen-Kun Huang Du-Qing Wu Shi-Ming Liu Jihong Liu Clarke De-Wen Qiu De-Liang PengAbstract
No abstract has been registered
Abstract
No abstract has been registered
Authors
Roger Holten Frederik Bøe Marit Almvik Sheela Katuwal Marianne Stenrød Mats Larsbo Nicholas Jarvis Ole Martin EkloAbstract
No abstract has been registered
Abstract
Interspecific brood parasitism is common in many animal systems. Brood parasites enter the nests of other species and divert host resources for producing their own offspring, which can lead to strong antagonistic parasite–host coevolution. Here, we look at commonalities among social insect species that are victims of brood parasites, and use phylogenetic data and information on geographical range size to predict which species are most probably to fall victims to brood parasites in the future. In our analyses, we focus on three eusocial hymenopteran groups and their brood parasites: (i) bumblebees, (ii) Myrmica ants, and (iii) vespine and polistine wasps. In these groups, some, but not all, species are parasitized by obligate workerless inquilines that only produce reproductive-caste descendants.We find phylogenetic signals for geographical range size and the presence of parasites in bumblebees, but not in ants and wasps. Phylogenetic logistic regressions indicate that the probability of being attacked by one or more brood parasite species increases with the size of the geographical range in bumblebees, but the effect is statistically only marginally significant in ants. However, non-phylogenetic logistic regressions suggest that bumblebee species with the largest geographical range sizes may have a lower likelihood of harbouring social parasites than do hosts with medium-sized ranges. Our results provide new insights into the ecology and evolution of host–social parasite systems, and indicate that host phylogeny and geographical range size can be used to predict threats posed by social parasites, as well to design efficient conservation measures for both hosts and their parasites. This article is part of the theme issue ‘The coevolutionary biology of brood parasitism: from mechanism to pattern’.
Abstract
Surface mould growth contributes to the colour changes of outdoor exposed wood over time. Modelling mould growth can thus help visualize wooden facades’ colour development, which can improve facade design and service life. However, existing wood mould models do not consider transient wetting effects that occur outdoors due to precipitation and condensation. To address this, four mould models were evaluated using laboratory experimental data that included exposure to transient wetting. First, the models (the original and the updated VTT model, the biohygrothermal model and the mould resistance design (MRD) model) were evaluated for Scots pine sapwood. For this evaluation, the transient wetting effect was implemented in the models by using hourly wood surface relative humidity (RH), calculated from electrical resistance measurements, as input. This showed that the original and the updated VTT model gave best fit to the experimental data. However, further evaluation of these two models for more wood materials showed that the updated VTT model was sensitive to the choice of material parameters. Large discrepancies occurred when varying the material parameters in the updated VTT model. Finally, different estimates of RH were tested in the original VTT model. Using wood surface RH as input gave best fit to the experimental data, and ambient air RH gave poorest fit. Overall, the results indicate that the original VTT model is fairly reliable and can be used to predict mould growth on wooden claddings exposed to transient wetting as long as the wood surface climate is used as climatic input data.
Authors
Tao Zhao Suresh Ganji Christian Schiebe Björn Bohman Philip Weinstein Paal Krokene Anna-Karin Borg-Karlson C. Rikard UneliusAbstract
No abstract has been registered
Authors
Fernanda Canassa Susanna Tall Rafael de Andrade Moral Idemauro A.R. de Lara Italo Delalibera Jr. Nicolai Vitt MeylingAbstract
No abstract has been registered
Authors
Jamal Zaherpour Nick Mount Simon N. Gosling Rutger Dankers Stephanie Eisner Dieter Gerten Xingcai Liu Yoshimitsu Masaki Hannes Müller Schmied Qiuhong Tang Yoshihide WadaAbstract
This study presents a novel application of machine learning to deliver optimised, multi-model combinations (MMCs) of Global Hydrological Model (GHM) simulations. We exemplify the approach using runoff simulations from five GHMs across 40 large global catchments. The benchmarked, median performance gain of the MMC solutions is 45% compared to the best performing GHM and exceeds 100% when compared to the ensemble mean (EM). The performance gain offered by MMC suggests that future multi-model applications consider reporting MMCs, alongside the EM and intermodal range, to provide end-users of GHM ensembles with a better contextualised estimate of runoff. Importantly, the study highlights the difficulty of interpreting complex, non-linear MMC solutions in physical terms. This indicates that a pragmatic approach to future MMC studies based on machine learning methods is required, in which the allowable solution complexity is carefully constrained.