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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.

2022

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Sammendrag

The latitudinal diversity gradient (LDG) is one of the most recognized global patterns of species richness exhibited across a wide range of taxa. Numerous hypotheses have been proposed in the past two centuries to explain LDG, but rigorous tests of the drivers of LDGs have been limited by a lack of high-quality global species richness data. Here we produce a high-resolution (0.025° × 0.025°) map of local tree species richness using a global forest inventory database with individual tree information and local biophysical characteristics from ~1.3 million sample plots. We then quantify drivers of local tree species richness patterns across latitudes. Generally, annual mean temperature was a dominant predictor of tree species richness, which is most consistent with the metabolic theory of biodiversity (MTB). However, MTB underestimated LDG in the tropics, where high species richness was also moderated by topographic, soil and anthropogenic factors operating at local scales. Given that local landscape variables operate synergistically with bioclimatic factors in shaping the global LDG pattern, we suggest that MTB be extended to account for co-limitation by subordinate drivers.

Sammendrag

Climate change results in longer growing season, benefitting forage crop production in northern Norway. Wild goose populations take advantage of the increased access to this high-quality feed. European goose populations are increasing, triggering conflicts and economical losses for farmers. A warmer climate may open for higher yielding seed mixtures, with better tolerance against goose grazing. We tested eight different seed mixtures by adding five forage species in various combinations to a traditional, commercial seed mixture in a randomized block design, three replicates. Goose grazing was simulated by weekly cutting small plots (0.25 m2) fixed within 10.5 m2 larger plots. Cumulated biomass in the weekly cut small plots was compared to total yields from the large plots, harvested twice according to normal practice. No significant differences in biomass accumulation between seed mixtures of the weekly cut plots were identified, possibly due to large variation between replicates, harvest years and cutting regime. However, results indicate that several of the new mixtures containing Dactylis glomerata are higher yielding and tolerate intensified cutting better than the traditional mixtures. This suggests that traditional, commercial seed mixtures are not the best for grasslands subjected to intensive geese grazing. goose grazing, Northern Norway, Dactylis glomerata, field study, simulated grazing

Sammendrag

The occurrence of freeze–thaw cycles modifies water infiltration processes and surface runoff generation. Related processes are complex and are not yet fully investigated at field scale. While local weather conditions and soil management practices are the most important factors in both runoff generation and surface erosion processes, local terrain heterogeneities may significantly influence soil erosion processes in catchments with undulating terrain. This paper presents a field-based investigation of spatial and temporal heterogeneities in subsurface soil moisture and soil temperature associated with freezing, thawing, and snowmelt infiltration. The field setup consists of a combination of traditional point measurements performed with frequency domain reflectometry (FDR) and electrical resistivity tomography (ERT). The transect was approximately 70 m long and spanned an entire depression with a north-facing slope (average slope of 11.5%) and a south-facing slope (average slope of 9.7%). The whole depression was entirely covered with stubble. Observed resistivity patterns correspond well to the measured soil moisture patterns. During the observation period, the north facing slope froze earlier and deeper compared with the south facing slope. Freeze–thaw cycles were less pronounced in the north-facing slope than in the south-facing slope. There were also differences in soil temperature and soil moisture patterns between lower and upper parts of the monitored depression. These indicate that initiation and development of runoff related processes, and consequently soil erosion, in regions with freeze–thaw cycles may differ significantly depending on local terrain characteristics. Consequently, it indicates that spatial terrain heterogeneities, especially slope aspects, may be important when studying soil erosion processes, water flow and nutrient leaching in lowlands where patchy snowpacks and dynamic freeze–thaw cycles are predominating.

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Sammendrag

Rapid methods allowing for non-destructive crop monitoring are imperative for accurate in-season nitrogen (N) status assessment and precision N management. The objectives of this paper were to (1) compare the performance of a leaf fluorescence sensor Dualex 4 and an active canopy reflectance sensor Crop Circle ACS-430 for estimating maize (Zea mays L.) N status indicators across growth stages; (2) evaluate the potential of N status prediction across growth stages using the reflectance parameters acquired from the canopy sensor at an early growth stage; and, (3) investigate the prospect of combining the active canopy sensor and leaf fluorescence sensor data to estimate N nutrition index (NNI) indirectly using a general model across growth stages. The results indicated that data from both sensors were closely related to NNI across stages. However, using the direct NNI estimation method, among the tested indices, only the N balance index (NBI) could diagnose N status satisfactorily, based on the Kappa statistics. The effect of growth stages on proximal sensing was reduced by incorporating the information of days after sowing. It was found that the leaf fluorescence sensor performed relatively better in estimating plant N concentration whereas the canopy reflectance sensor performed better in aboveground biomass estimation. Their combination significantly improved the reliability of N diagnosis, including NNI prediction. In addition, the study confirmed that N status can be assessed by predicting aboveground biomass at the later stages using the canopy reflectance measurements at an early stage. Furthermore, the integrated NBI was verified to be a more robust and sensitive N status indicator than the chlorophyll concentration index. It is concluded that combining active canopy sensor data, of an early growth stage (e.g. V8), with leaf fluorescence sensor data, modified using days after sowing, can improve the accuracy of corn N status diagnosis across growth stages.