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.
2020
Sammendrag
Aim: Distribution modelling is a useful approach to obtain knowledge about the spatial distribution of biodiversity, required for, for example, red-list assessments. While distribution modelling methods have been applied mostly to single species, modelling of communities and ecosystems (EDM; ecosystem-level distribution modelling) produces results that are more directly relevant for management and decision-making. Although the choice of predictors is a pivotal part of the modelling process, few studies have compared the suitability of different sets of predictors for EDM. In this study, we compare the performance of 50 single environmental variables with that of 11 composite landscape gradients (CLGs) for prediction of ecosystem types. The CLGs represent gradients in landscape element composition derived from multivariate analyses, for example “inner-outer coast” and “land use intensity.” Location: Norway. Methods: We used data from field-based ecosystem-type mapping of nine ecosystem types, and environmental variables with a resolution of 100 × 100 m. We built nine models for each ecosystem type with variables from different predictor sets. Logistic regression with forward selection of variables was used for EDM. Models were evaluated with independently collected data. Results: Most ecosystem types could be predicted reliably, although model performance differed among ecosystem types. We identified significant differences in predictive power and model parsimony across models built from different predictor sets. Climatic variables alone performed poorly, indicating that the current climate alone is not sufficient to predict the current distribution of ecosystems. Used alone, the CLGs resulted in parsimonious models with relatively high predictive power. Used together with other variables, they consistently improved the models. Main conclusions: Our study highlights the importance of variable selection in EDM. We argue that the use of composite variables as proxies for complex environmental gradients has the potential to improve predictions from EDMs and thus to inform conservation planning as well as improve the precision and credibility of red lists and global change assessments.conservation planning, distribution modelling, ecosystem classification, ecosystem types, IUCN Red List of Ecosystems, landscape gradients, spatial prediction, species response curves
Forfattere
Yngve RekdalSammendrag
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Forfattere
Yngve RekdalSammendrag
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Yngve RekdalSammendrag
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Yngve RekdalSammendrag
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Yngve RekdalSammendrag
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Forfattere
Yngve RekdalSammendrag
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Sammendrag
Beitekartlegger Yngve Rekdal mener de beste beitearealene trenger beskyttelse fra nedbygging på samme måte som matjord.
Sammendrag
Young forest stands and clearcuts in the boreal forest created by modern forestry practices along with meadows of abandoned summer farms may contribute as feeding areas for beef cattle. The patchy distribution and varying quality and diversity of forage on such unimproved lands may affect cattle productivity. Weight gain of 336 beef cows and 270 calves free-ranging during three summer grazing seasons was monitored in boreal forests of southeastern Norway, stocked at either high (0.16 cows ha-1) and low (0.04 cows ha-1) stocking densities. We used linear mixed effect models for assessing intrinsic correlates of weight gain in cows and calves in the two areas. Habitat use and home range size of a subsample of 53 cows were monitored by using GPS collars programmed to log locations at 5 min. intervals during the grazing season. Additional extrinsic correlates of weight gain for the subsampled cows using a linear mixed model were also tested. Average weight gain of beef cows grazing at the low stocking density was positive among cows of early maturing breeds (represented by Hereford) gaining 24 ± 2.8 kg ( ± SE), while cows of late maturing breeds (mainly represented by Charolais) had an average weight loss of 9 ± 8.4 kg. The average weight gain was negative for beef cows of both early (Herefords) and late maturing breeds (mainly represented by Charolais but also Limousin and Simmental) at the high stocking density. Within both breed groups, there was a negative relationship between breed-specific average weight of cows at turnout and weight gain during the grazing period, while a prolonged grazing period was slightly positively related to weight gain. There was no relationship between weight gain and home range size and proportion of grazing habitat for the 53 cows fitted with GPS collars. Higher weight gains in calves of the low compared to the high stocking density area was found. However, there was no breed effect of weight gain in calves. Across study areas, spring-born suckler calves gained more weight than autumn-born calves (92 ± 1.7 kg vs. 65 ± 4.4 kg). Also, there were higher weight gains for springborn bull-calves than spring-born heifers (100 ± 2.4 kg vs. 94 ± 2.2 kg). Overall, the results indicate that it is possible to achieve acceptable weight gains for cattle grazing coniferous forest by finding breeds suitable for these extensive areas and stocking at moderate densities.
Sammendrag
Rapporten gir status for husdyrrasene som er med i Produksjonstilskudd for bevaringsverdige husdyrraser. Rapporten trekker fram aktuelle problemstillinger for utviklingen av disse rasene. Alle de aktuelle rasene viser en økende trend, samtidig som hver art har ulike problemstillinger som det kan være aktuelt å få mer kunnskap om for å opprettholde den positive trender.