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.
2021
Sammendrag
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Forfattere
Marit Skuterud VennatrøSammendrag
Formålet med kartleggingsprogrammet «Skadegjørere i potet» er å få kunnskap om status med hensyn til forekomst av planteskadegjørerne lys ringråte (Clavibacter michigaensis spp.), mørk ringråte (Rastonia solancearum), rotgallnematodene Meloidogyne chitwoodi og M. fallax samt potetkreft (Synchytrium endobioticum) i norsk produksjon av mat- og industripotet. Denne rapporten omhandler status for rotgallnematodene. Rotgallnematoder (Meloidogyne spp.) er en stor gruppe obligate planteparasittære som finnes over hele verden. Skadene etter rotgallnematoder forringer både kvalitet og avling, og gir store avlingstap på verdensbasis. M. chitwoodi og M. fallax har mange vertsplanter, og er vanskelige å bekjempe dersom de etablerer seg. Derfor ansees disse artene som alvorlige planteskadegjørere, og som en trussel mot europeisk potet og gulrot produksjon. Både M. chitwoodi og M. fallax er påvist i Europa i begrenset omfang. Begge artene de senere årene funnet i Sverige. M. chitwoodi og M. fallax er ikke påvist i Norge, men det er risiko for at begge artene kan etablere seg og gjøre omfattende skade i norsk potet- og gulrotproduksjon….
Forfattere
Tonje Økland Siri Lie Olsen Rune HalvorsenSammendrag
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Sammendrag
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Sammendrag
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Forfattere
Markus A. K. Sydenham Zander Venter Trond Reitan Claus Rasmussen Astrid Brekke Skrindo Daniel Skoog Kaj-Andreas Hanevik Stein Joar Hegland Yoko Dupont Anders Nielsen Joseph Chipperfield Graciela Monica RuschSammendrag
1. Predicting plant-pollinator interaction networks over space and time will improve our understanding of how environmental change is likely to impact the functioning of ecosystems. Here we propose a framework for producing spatially explicit predictions of the occurrence and number of pairwise plant-pollinator interactions and of the species richness, diversity, and abundance of pollinators visiting flowers. We call the framework ‘MetaComNet’ because it aims to link metacommunity dynamics to the assembly of ecological networks. 2. To illustrate the MetaComNet functionality, we used a dataset on bee-flower networks sampled at 16 sites in southeast Norway along with random forest models to predict bee-flower interactions. We included variables associated with climatic conditions (elevation) and habitat availability within a 250m radius of each site. Regional commonness, site-specific distance to conspecifics, social guild, and floral preference were included as bee traits. Each plant species was assigned a score reflecting its site-specific abundance, and four scores reflecting the bee species that the plant family is known to attract. We used leave-one-out cross-validations to assess the models’ ability to predict pairwise plant-bee interactions across the landscape. 3. The relationship between observed occurrence or absence of interactions and the predicted probability of interactions was nearly proportional (GLMlogistic regression slope = 1.09), matching the data well (AUC = 0.88), and explained 30% of the variation. Predicted probability of interactions was also correlated with the number of observed pairwise interactions (r = 0.32). The sum of predicted probabilities of bee-flower interactions were positively correlated with observed species richness (r = 0.50), diversity (r = 0.48), and abundance (r = 0.42) of wild bees interacting with plant species within sites. 4. Our findings show that the MetaComNet framework can be a useful approach for making spatially explicit predictions and mapping plant-pollinator interactions. Such predictions have the potential to identify areas where the pollination potential for wild plants is particularly high, and where conservation action should be directed to preserve this ecosystem function.
Forfattere
Markus A. K. Sydenham Zander Venter Trond Reitan Claus Rasmussen Astrid Brekke Skrindo Daniel Ingvar Jeuderan Skoog Kaj-Andreas Hanevik Stein Joar Hegland Yoko L. Dupont Anders Nielsen Joseph Chipperfield Graciela RuschSammendrag
1. Predicting plant–pollinator interaction networks over space and time will improve our understanding of how environmental change is likely to impact the functioning of ecosystems. Here we propose a framework for producing spatially explicit predictions of the occurrence and number of pairwise plant–pollinator interactions and of the species richness, diversity and abundance of pollinators visiting flowers. We call the framework ‘MetaComNet’ because it aims to link metacommunity dynamics to the assembly of ecological networks. 2. To illustrate the MetaComNet functionality, we used a dataset on bee–flower networks sampled at 16 sites in southeast Norway along with random forest models to predict bee–flower interactions. We included variables associated with climatic conditions (elevation) and habitat availability within a 250 m radius of each site. Regional commonness, site-specific distance to conspecifics, social guild and floral preference were included as bee traits. Each plant species was assigned a score reflecting its site-specific abundance, and four scores reflecting the bee species that the plant family is known to attract. We used leave-one-out cross-validations to assess the models' ability to predict pairwise plant–bee interactions across the landscape. 3. The relationship between observed occurrence or absence of interactions and the predicted probability of interactions was nearly proportional (GLMlogistic regression slope = 1.09), matching the data well (AUC = 0.88), and explained 30% of the variation. Predicted probability of interactions was also correlated with the number of observed pairwise interactions (r = 0.32). The sum of predicted probabilities of bee–flower interactions were positively correlated with observed species richness (r = 0.50), diversity (r = 0.48) and abundance (r = 0.42) of wild bees interacting with plant species within sites. 4. Our findings show that the MetaComNet framework can be a useful approach for making spatially explicit predictions and mapping plant–pollinator interactions. Such predictions have the potential to identify areas where the pollination potential for wild plants is particularly high, and where conservation action should be directed to preserve this ecosystem function. interactions, network, plants, pollinators, predict, random forest
Sammendrag
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Sammendrag
The ascomycete Hymenoscyphus fraxineus has spread across most of the host range of European ash with a high level of mortality, causing important economic, cultural and environmental effects. We present a novel method combining a Monte-Carlo approach with a generalised additive model that confirms the importance of meteorology to the magnitude and timing of H. fraxineus spore emissions. The variability in model selection and the relative degree to which our models are over- or under-fitting the data has been quantified. We find that both the daily magnitude and timing of spore emissions are affected by meteorology during and prior to the spore emission diurnal peak. We found the daily emission magnitude has the strongest associations to weekly average net radiation and leaf moisture before the emission, soil temperature during the day before emission and net radiation during the spore emission. The timing of the daily peak in spore emissions has the strongest associations to net radiation both during spore emission and in the day preceding the emission. The seasonal peak in spore emissions has a near-exponential increase/decrease, and the mean daily emission peak is approximately Gaussian.
Forfattere
Jan-Peter George Wei Yang Hideki Kobayashi Tobias Biermann Arnaud Carrara Edoardo Cremonese Matthias Cuntz Silvano Fares Giacomo Gerosa Thomas Grünwald Niklas Hase Michael Heliasz Andreas Ibrom Alexander Knohl Bart Kruijt Holger Lange Jean-Marc Limousin Denis Loustau Petr Lukeš Riccardo Marzuoli Meelis Mölder Leonardo Montagnani Johan Neirynck Matthias Peichl Corinna Rebmann Marius Schmidt Francisco Ramon Lopez Serrano Kamel Soudani Caroline Vincke Jan PisekSammendrag
Leaf area index (LAI) is a key ecological indicator for describing the structure of canopies and for modelling energy exchange between atmosphere and biosphere. While LAI of the forest overstory can be accurately assessed over large spatial scales via remote sensing, LAI of the forest understory (LAIu) is still largely ignored in ecological studies and ecosystem modelling due to the fact that it is often too complex to be destructively sampled or approximated by other site parameters. Additionally, so far only few attempts have been made to retrieve understory LAI via remote sensing, because dense canopies with high LAI are often hindering retrieval algorithms to produce meaningful estimates for understory LAI. Consequently, the forest understory still constitutes a poorly investigated research realm impeding ecological studies to properly account for its contribution to the energy absorption capacity of forest stands. This study aims to compare three conceptually different indirect retrieval methodologies for LAIu over a diverse panel of forest understory types distributed across Europe. For this we carried out near-to-surface measurements of understory reflectance spectra as well as digital surface photography over the extended network of Integrated Carbon Observation System (ICOS) forest ecosystem sites. LAIu was assessed by exploiting the empirical relationship between vegetation cover and light absorption (Beer-Lambert- Bouguer law) as well as by utilizing proposed relationships with two prominent vegetation indices: normalized difference vegetation index (NDVI) and simple ratio (SR). Retrievals from the three methods were significantly correlated with each other (r = 0.63–0.99, RMSE = 0.53–0.72), but exhibited also significant bias depending on the LAI scale. The NDVI based retrieval approach most likely overestimates LAI at productive sites when LAIu > 2, while the simple ratio algorithm overestimates LAIu at sites with sparse understory vegetation and presence of litter or bare soil. The purely empirical method based on the Beer-Lambert law of light absorption seems to offer a good compromise, since it provides reasonable LAIu values at both low and higher LAI ranges. Surprisingly, LAIu variation among sites seems to be largely decoupled from differences in climate and light permeability of the overstory, but significantly increased with vegetation diversity (expressed as species richness) and hence proposes new applications of LAIu in ecological modelling.