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.
2019
Sammendrag
Det er ikke registrert sammendrag
Sammendrag
Short-day (SD) treatment is used by forest nurseries to induce growth cessation in Picea abies seedlings. SD treatment may however increase the risk of reflushing in autumn and earlier bud break the following spring. When the start of the SD treatment is early in order to control seedling height, the duration of the SD treatment should be longer in order to prevent reflushing in autumn. However, due to the amount of manual work involved in the short-day treatment, increasing the number of days is undesirable from a practical point of view. Splitting the SD treatment could be a way to achieve both early height control and at the same time avoid autumn bud break with less workload. We tested how different starting dates and durations of SD treatment influenced on morphological and phenological traits. Regardless of timing and duration of the SD treatment, height growth was reduced compared to the untreated controls. Seedlings given split SD (7+7 days interrupted with two weeks in long days) had less height growth than all other treatments. Root collar diameter growth was significantly less in control seedlings than in seedlings exposed to early (7 or 14 days) or split (7+7 days) SD treatment. There were also differences in the frequency of reflushing and bud break timing among the SD treated seedlings, dependent on duration and starting date. If the SD treatment started early, a continuous 14-day SD treatment was not sufficient to avoid high frequencies of reflushing. However, by splitting the SD treatment into two periods of 7+7 days these negative effects were largely avoided, although spring bud break occurred earlier than in the controls.
Forfattere
O. Janne Kjønaas Teresa Gómez de la Bárcena Ryan Bright Mette Hansen Gro Hylen Håvard Kauserud Sunil Mundra Jørn-Frode Nordbakken Tonje Økland Carlo AallSammendrag
Det er ikke registrert sammendrag
Forfattere
O. Janne Kjønaas Teresa Gómez de la Bárcena Ryan Bright Mette Hansen Gro Hylen Håvard Kauserud Sunil Mundra Jørn-Frode Nordbakken Tonje Økland Carlo AallSammendrag
Det er ikke registrert sammendrag
Forfattere
O. Janne Kjønaas Teresa Gómez de la Bárcena Ryan Bright Mette Hanssen Gro Hylen Håvard Kauserud Tonje Økland Mundra Sunil Jørn-Frode Nordbakken Carlo AallSammendrag
Det er ikke registrert sammendrag
Forfattere
Siri Svendgård-Stokke Hege Ulfeng Lise Dalsgaard Stephanie Eisner Roar Lågbu Ove Mindor Klakegg Eivind Solbakken Gunnhild Søgaard Geir-Harald StrandSammendrag
Denne rapporten skal gi grunnlag for å vurdere en eventuell leveranse av et kart som viser organisk karbon i norsk jordsmonn til FAO. Rapporten redegjør for bestillingen fra FAO, inkludert FAOs beskrivelse av formål og nytte av et Global Soil Organic Carbon Map (GSOCmap). Rapporten gir også en kort oversikt over hvordan GSOCmap er utarbeidet i våre naboland, og hvordan arbeidet med et nytt kart kan ses i sammenheng med Global Soil Partnership (GSP) og annet relevant arbeid NIBIO er involvert i. Rapporten skisserer fire alternativer for hvordan et SOC kart for Norge til bruk i GSOCmap kan utarbeides.
2018
Sammendrag
Forest management affects the distribution of tree species and the age class of a forest, shaping its overall structure and functioning and in turn the surface–atmosphere exchanges of mass, energy, and momentum. In order to attribute climate effects to anthropogenic activities like forest management, good accounts of forest structure are necessary. Here, using Fennoscandia as a case study, we make use of Fennoscandic National Forest Inventory (NFI) data to systematically classify forest cover into groups of similar aboveground forest structure. An enhanced forest classification scheme and related lookup table (LUT) of key forest structural attributes (i.e., maximum growing season leaf area index (LAImax), basal-area-weighted mean tree height, tree crown length, and total stem volume) was developed, and the classification was applied for multisource NFI (MSNFI) maps from Norway, Sweden, and Finland. To provide a complete surface representation, our product was integrated with the European Space Agency Climate Change Initiative Land Cover (ESA CCI LC) map of present day land cover (v.2.0.7). Comparison of the ESA LC and our enhanced LC products (https://doi.org/10.21350/7zZEy5w3) showed that forest extent notably (κ = 0.55, accuracy 0.64) differed between the two products. To demonstrate the potential of our enhanced LC product to improve the description of the maximum growing season LAI (LAImax) of managed forests in Fennoscandia, we compared our LAImax map with reference LAImax maps created using the ESA LC product (and related cross-walking table) and PFT-dependent LAImax values used in three leading land models. Comparison of the LAImax maps showed that our product provides a spatially more realistic description of LAImax in managed Fennoscandian forests compared to reference maps. This study presents an approach to account for the transient nature of forest structural attributes due to human intervention in different land models.
Forfattere
Ryan Bright Stephanie Eisner Marianne Tronstad Lund Titta Majasalmi Gunnar Myhre Rasmus AstrupSammendrag
Predicting the surface albedo of a forest of a given species composition or plant functional type is complicated by the wide range of structural attributes it may display. Accurate characterizations of forest structure are therefore essential to reducing the uncertainty of albedo predictions in forests, particularly in the presence of snow. At present, forest albedo parameterizations remain a nonnegligible source of uncertainty in climate models, and the magnitude attributable to insufficient characterization of forest structure remains unclear. Here we employ a forest classification scheme based on the assimilation of Fennoscandic (i.e., Norway, Sweden, and Finland) national forest inventory data to quantify the magnitude of the albedo prediction error attributable to poor characterizations of forest structure. For a spatial domain spanning ~611,000 km2 of boreal forest, we find a mean absolute wintertime (December–March) albedo prediction error of 0.02, corresponding to a mean absolute radiative forcing ~0.4 W/m2. Further, we evaluate the implication of excluding albedo trajectories linked to structural transitions in forests during transient simulations of anthropogenic land use/land cover change. We find that, for an intensively managed forestry region in southeastern Norway, neglecting structural transitions over the next quarter century results in a foregone (undetected) radiatively equivalent impact of ~178 Mt‐CO2‐eq. year−1 on average during this period—a magnitude that is roughly comparable to the annual greenhouse gas emissions of a country such as The Netherlands. Our results affirm the importance of improving the characterization of forest structure when simulating surface albedo and associated climate effects.
Forfattere
Ryan Bright Stephanie Eisner Titta Majasalmi Marianne Tronstad Lund Gunnar Myhre Rasmus AstrupSammendrag
Det er ikke registrert sammendrag
Sammendrag
Det er ikke registrert sammendrag