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
Forfattere
Nina SvartedalSammendrag
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Forfattere
Torbjørn HaukåsSammendrag
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Forfattere
Grete StokstadSammendrag
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Forfattere
Grete StokstadSammendrag
Rapporten dokumenterer status og endringer i jordbrukslandskapet i Nord-Norge. I tillegg til å presentere tall for fylker er det brukt en inndeling av kommuner etter dominerende jordbruksregion. I rapporten er det benyttet endringsdata basert på tolkning av flyfoto i regi av overvåkingsprogrammet «Tilstandsovervåking og resultatkontroll i jordbrukets kulturlandskap» (3Q) ved NIBIO. Det rapporterer på arealendringer med hensyn til jordbruksareal, endringer i arealstruktur og forekomsten av ulike elementer i jordbrukslandskapet som for eksempel åkerholmer og steingjerder. Informasjon fra søknad om produksjonstilskudd er brukt til å undersøke bruksstruktur og hva arealene brukes til.
Forfattere
Christian PedersenSammendrag
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Sammendrag
A major challenge in predicting species’ distributional responses to climate change involves resolving interactions between abiotic and biotic factors in structuring ecological communities. This challenge reflects the classical conceptualization of species’ regional distributions as simultaneously constrained by climatic conditions, while by necessity emerging from local biotic interactions. A ubiquitous pattern in nature illustrates this dichotomy: potentially competing species covary positively at large scales but negatively at local scales. Recent theory poses a resolution to this conundrum by predicting roles of both abiotic and biotic factors in covariation of species at both scales, but empirical tests have lagged such developments. We conducted a 15-y warming and herbivore-exclusion experiment to investigate drivers of opposing patterns of covariation between two codominant arctic shrub species at large and local scales. Climatic conditions and biotic exploitation mediated both positive covariation between these species at the landscape scale and negative covariation between them locally. Furthermore, covariation between the two species conferred resilience in ecosystem carbon uptake. This study thus lends empirical support to developing theoretical solutions to a long-standing ecological puzzle, while highlighting its relevance to understanding community compositional responses to climate change.
Forfattere
Christian PedersenSammendrag
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Forfattere
Christian PedersenSammendrag
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Sammendrag
Distribution modeling methods are used to provide occurrence probability surfaces for modeled targets. While most often used for modeling species, distribution modeling methods can also be applied to vegetation types. However, surfaces provided by distribution modeling need to be transformed into classified wall-to-wall maps of vegetation types to be useful for practical purposes, such as nature management and environmental planning. The paper compares the performance of three methods for assembling predictions for multiple vegetation types, modeled individually, into a wall-to-wall map. The authors used grid-cell based probability surfaces from distribution models of 31 vegetation types to test the three assembly methods. The first, a probability-based method, selected for each grid cell the vegetation type with the highest predicted probability of occurrence in that cell. The second, a performance-based method, assigned the vegetation types, ordered from high to low model performance, to a fraction of the grid cells given by the vegetation type’s prevalence in the study area. The third, a prevalence-based method, differed from the performance-based method by assigning vegetation types in the order from low to high prevalence. Thus the assembly methods worked in two principally different ways: the probability-based method assigned vegetation types to grid cells in a cell-by-cell manner, and both the performance-based method and prevalence-based method assigned them in a type-by-type manner. All methods were evaluated by use of reference data collected in the field, more or less independently of the data used to parameterize the vegetation-type models. Quantity, allocation, and total disagreement, as well as proportional dissimilarity metrics, were used for evaluation of assembly methods. Overlay analysis showed 38.1% agreement between all three assembly methods. The probability-based method had the lowest total disagreement with, and proportional dissimilarity from, the reference datasets, but the differences between the three methods were small. The three assembly methods differed strongly with respect to the distribution of the total disagreement on its quantity and allocation components: the cell-by-cell assignment method strongly favored allocation disagreement and the type-by-type methods strongly favored quantity disagreement. The probability-based method best reproduced the general pattern of variation across the study area, but at the cost of many rare vegetation types, which were left out of the assembled map. By contrast, the prevalence-based and performance-based methods represented vegetation types in accordance with nationwide area statistics. The results show that maps of vegetation types with wall-to-wall coverage can be assembled from individual distribution models with a quality acceptable for indicative purposes, but all the three tested methods currently also have shortcomings. The results also indicate specific points in the methodology for map assembly that may be improved. area frame survey, assembly strategies, distribution modeling, spatial probabilities, vegetation mapping, vegetation types
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