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
Det er ikke registrert sammendrag
Sammendrag
Det er ikke registrert sammendrag
Sammendrag
Det er ikke registrert sammendrag
Forfattere
Anita SønstebySammendrag
Det er ikke registrert sammendrag
Forfattere
Per Jarle MøllerhagenSammendrag
Det er ikke registrert sammendrag
Forfattere
Divina Gracia P. RodriguezSammendrag
Det er ikke registrert sammendrag
Sammendrag
Rapporten utforsker og diskuterer potensialet for økt bruk av Stordata (engelsk: big data) teknologi og metode innenfor instituttets arbeidsområder. I dag benyttes Stordata-tilnærminger til å løse forvaltningsstøtteoppgaver, samt til forskningsformål, særlig i sentrene for presisjonslandbruk og presisjonsjordbruk. Potensialet for økt bruk av Stordata innenfor instituttet er stort. For å realisere potensialet er det behov for god samordning mellom organisasjonsenhetene og utvikling av strategisk kompetanse på fagområdet.
Sammendrag
Rapporten dokumenterer utvalgte eksempler på bruk av stordata (engelsk: big data) teknologi og metode i NIBIO. Det første eksemplet er knyttet til oppdatering av arealressurskartet AR5, hvor det undersøkes om stordata-tilnærming kan benyttes for å identifisere lokaliteter der kartet må oppdateres. De neste eksemplene er hentet fra fagområdet plantehelse og tar for seg mulighetene for å bruke stordata-metode for å bedre prediksjonsmodeller og gjenkjenning av for skadegjørere.
Forfattere
Atle Mysterud Isa Nergård Skjelbostad Inger Maren Rivrud Øystein Brekkum Erling MeisingsetSammendrag
Simple Summary Chronic Wasting Disease is a deadly infectious disease affecting cervids that was discovered in Norway in 2016. CWD can transmit through environmental reservoirs and aggregation and spatial clustering of animals may affect transmission. Deer usually forage on scattered forage, but anthropogenic food sources are often concentrated in space, leading to spatial aggregation. We determined what caused red deer to revisit the same locations in the environment, and the extent to which this was caused by anthropogenic food sources. We document that the most visited sites were indeed anthropogenic, which opens potential avenues to disease mitigation. Abstract Herbivores like cervids usually graze on widely scattered forage, but anthropogenic food sources may cause spatial revisitation and aggregation, posing a risk for transmission of infectious diseases. In 2016, chronic wasting disease (CWD) was first detected in Norway. A legal regulation to ban supplemental feeding of cervids and to fence stored hay bales was implemented to lower aggregation of cervids. Knowledge of further patterns and causes of spatial revisitation can inform disease management. We used a recently developed revisitation analysis on GPS-positions from 13 red deer (Cervus elaphus) to identify the pattern of spatial clustering, and we visited 185 spatial clusters during winter to identify the causes of clustering. Anthropogenic food sources were found in 11.9% of spatial clusters, which represented 31.0% of the clusters in agricultural fields. Dumping of silage and hay bales were the main anthropogenic food sources (apart from agricultural fields), and unfenced hay bales were available despite the regulation. The probability of the clusters being in agricultural fields was high during winter. It may be necessary to find other ways of disposing of silage and enforcing the requirement of fencing around hay bales to ensure compliance, in particular during winters with deep snow.
Forfattere
Marian Schönauer Kari Väätäinen Robert Prinz Harri Lindeman Dariusz Pszenny Martin Jansen Joachim Maack Bruce Talbot Rasmus Astrup Dirk JaegerSammendrag
The utilization of detailed digital terrain models entails an enhanced basis for supporting sustainable forest management, including the reduction of soil impacts through predictions of site trafficability during mechanized harvesting operations. Since wet soils are prone to traffic-induced damages, soil moisture is incorporated into several systems for spatial predictions of trafficability. Yet, only few systems consider temporal dynamics of soil moisture, impeding the accuracy and practical value of predictions. The depth-to-water (DTW) algorithm calculates a cartographic index which indicates wet areas. Temporal dynamics of soil moisture are simulated by different DTW map-scenarios derived from set flow initiation areas (FIA). However, the concept of simulating seasonal moisture conditions by DTW map-scenarios was not analyzed so far. Therefore, we conducted field campaigns at six study sites across Europe, capturing time-series of soil moisture and soil strength along several transects which crossed predicted wet areas. Assuming overall dry conditions (FIA = 4.00 ha), DTW predicted 20% of measuring points to be wet. When a FIA of 1.00 ha (moist conditions) or 0.25 ha (wet conditions) were applied, DTW predicted 29% or 58% of points to be wet, respectively. De facto, 82% of moisture measurements were predicted correctly by the map-scenario for overall dry conditions – with 44% of wet measurements deviating from predictions made. The prediction of soil strength was less successful, with 66% of low values occurring on areas where DTW indicated dryer soils and subsequently a sufficient trafficability. The condition-specific usage of different map-scenarios did not improve the accuracy of predictions, as compared to static map-scenarios, chosen for each site. We assume that site-specific and non-linear hydrological processes compromise the generalized assumptions of simulating overall moisture conditions by different FIA.