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
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Elena Albertsen Øystein H. Opedal Geir Hysing Bolstad Rocio Perez-Barrales Thomas F Hansen Christophe Pelabon William Scott ArmbrusterAbstract
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Authors
Elena Albertsen Øystein Hjorthol Opedal Geir Hysing Bolstad Rocío Pérez-Barrales Thomas F Hansen Christophe Pelabon William Scott ArmbrusterAbstract
Spatiotemporal variation in natural selection is expected, but difficult to estimate. Pollinator‐mediated selection on floral traits provides a good system for understanding and linking variation in selection to differences in ecological context. We studied pollinator‐mediated selection in five populations of Dalechampia scandens (Euphorbiaceae) in Costa Rica and Mexico. Using a nonlinear path‐analytical approach, we assessed several functional components of selection, and linked variation in pollinator‐mediated selection across time and space to variation in pollinator assemblages. After correcting for estimation error, we detected moderate variation in net selection on two out of four blossom traits. Both the opportunity for selection and the mean strength of selection decreased with increasing reliability of cross‐pollination. Selection for pollinator attraction was consistently positive and stronger on advertisement than reward traits. Selection on traits affecting pollen transfer from the pollinator to the stigmas was strong only when cross‐pollination was unreliable and there was a mismatch between pollinator and blossom size. These results illustrate how consideration of trait function and ecological context can facilitate both the detection and the causal understanding of spatiotemporal variation in natural selection.
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Red-listed species are often used as target species in selection of sites for conservation. However, limitations to their use have been pointed out, and here we address the problem of expected high spatio-temporal dynamics of red-listed species. We used species data (vascular plants, bryophytes, macrolichens and polypore fungi) from two inventories 17 years apart to estimate temporal turnover of red-listed and non-red-listed species in two forest areas (147 and 195 ha) and of plots (0.25 ha) within each area. Furthermore, we investigated how turnover of species afected the rank order of plots regarding richness of red-listed species, using two diferent national Red List issues (1998 and 2015). In both study areas, temporal turnover was substantial, despite minor changes in the overall number of species. At plot level, temporal turnover in red-listed species was higher than in non-red-listed species, but similar to non-red-listed species of the same frequency of occurrence. Adding the efect of changing identities of species red-listed according to the two Red List issues, further increased the estimated spatio-temporal dynamics. Recorded spatio-temporal turnover also resulted in substantial changes in the rank order of plots regarding richness of red-listed species. Using rare red-listed species for site selection may therefore be accompanied by a higher loss of conservation efectiveness over time than for more common species, and particularly at fner scales. Red-listed species · Site selection · Spatio-temporal dynamics · Temporal turnover
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Authors
Lise Nistrup Jørgensen Niels Matzen Andrea Ficke Ghita C. Nielsen Marja Jalli Antanas Ronis Björn Andersson Annika DjurleAbstract
Risk models for decisions on fungicide use based on weather data, disease monitoring, and control thresholds are used as important elements in a sustainable cropping system. The need for control of leaf blotch diseases in wheat (caused by Zymoseptoria tritici, Parastagonospora nodorum and Pyrenophora tritici-repentis) vary significantly across years and locations. Disease development is mainly driven by humidity events during stem elongation and heading. Two risk models were tested in field trials in order to identify situations favourable for the development of leaf blotch diseases in Lithuania, Norway, Sweden, Finland and Denmark. The Crop Protection Online (CPO) model uses days with precipitation (>1 mm), while the humidity model (HM) uses 20 continuous hours with relative humidity (RH) ≥ 85% as criteria for the need of a fungicide application. Forty-seven field trials were carried out during two seasons to validate these two risk-models against reference fungicide treatments. The season 2018 was dry and 2019 had an average precipitation profile. The two risk models with few exceptions provided acceptable disease control. In 2018, very few treatments were recommended by the models, saving 85–98% of treatments compared to the reference treatments, while in the wetter season 2019, 31% fewer applications were recommended. Based on specific criteria including fungicide input and net yield responses the models gave correct recommendations in 95% of the trials in 2018 and in 54–58% of the trials in 2019 compared with reference treatments dominated by 2–3 sprays. In comparison with single spray references, the models gave correct recommendations in 54–69% of the situations.
Authors
Karin Juul Hesselsøe K. Sintorn Koert Donkers N. Dokkuma Yajun Chen Trond Olav Pettersen Wolfgang Prämassing M. Woods D. Cleaver Anne Falk Øgaard Tore Krogstad Trygve S. AamlidAbstract
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Authors
Stine Samsonstuen Bente Aspeholen Åby Paul Crosson Karen A. Beauchemin Marit Smith Wetlesen Helge Bonesmo Laila AassAbstract
Emission intensities from beef production vary both among production systems (countries) and farms within a country depending upon use of natural resources and management practices. A whole-farm model developed for Norwegian suckler cow herds, HolosNorBeef, was used to estimate GHG emissions from 27 commercial beef farms in Norway with Angus, Hereford, and Charolais cattle. HolosNorBeef considers direct emissions of methane (CH4), nitrous oxide (N2O) and carbon dioxide (CO2) from on-farm livestock production and indirect N2O and CO2 emissions associated with inputs used on the farm. The corresponding soil carbon (C) emissions are estimated using the Introductory Carbon Balance Model (ICBM). The farms were distributed across Norway with varying climate and natural resource bases. The estimated emission intensities ranged from 22.5 to 45.2 kg CO2 equivalents (eq) (kg carcass)−1. Enteric CH4 was the largest source, accounting for 44% of the total GHG emissions on average, dependent on dry matter intake (DMI). Soil C was the largest source of variation between individual farms and accounted for 6% of the emissions on average. Variation in GHG intensity among farms was reduced and farms within region East, Mid and North re-ranked in terms of emission intensities when soil C was excluded. Ignoring soil C, estimated emission intensities ranged from 21.5 to 34.1 kg CO2 eq (kg carcass)−1. High C loss from farms with high initial soil organic carbon (SOC) content warrants further examination of the C balance of permanent grasslands as a potential mitigation option for beef production systems.