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.
2022
Sammendrag
Norway’s most common tree species, Picea abies (L.) Karst. (Norway spruce), is often infected with Heterobasidion parviporum Niemelä & Korhonen and Heterobasidion annosum (Fr.) Bref.. Because Pinus sylvestris L. (Scots pine) is less susceptible to rot, it is worth considering if converting rot-infested spruce stands to pine improves economic performance. We examined the economically optimal choice between planting Norway spruce and Scots pine for previously spruce-dominated clear-cut sites of different site indexes with initial rot levels varying from 0% to 100% of stumps on the site. While it is optimal to continue to plant Norway spruce in regions with low rot levels, shifting to Scots pine pays off when rot levels get higher. The threshold rot level for changing from Norway spruce to Scots pine increases with the site index. We present a case study demonstrating a practical method (“Precision forestry”) for determining the tree species in a stand at the pixel level when the stand is heterogeneous both in site indexes and rot levels. This method is consistent with the concept of Precision forestry, which aims to plan and execute site-specific forest management activities to improve the quality of wood products while minimising waste, increasing profits, and maintaining environmental quality. The material for the study includes data on rot levels and site indexes in 71 clear-cut stands. Compared to planting the entire stand with a single species, pixel-level optimised species selection increases the net present value in almost every stand, with average increase of approximately 6%.
Forfattere
Christer Moe Rolandsen Erling Meisingset Olav Strand Erling Johan Solberg Roy Andersen Øystein Brekkum Morten Heim Bram Van Moorter Atle MysterudSammendrag
I september 2020 ble det påvist klassisk skrantesjuke (CWD) på en villreinbukk felt på Hardangervidda. Dette skapte en ny situasjon for forvaltningen av CWD og reiste en rekke nye spørsmål og behov for kunnskap. Derfor startet NINA, i samarbeid med UiO og NIBIO, et merkeprosjekt for villrein, elg og hjort på Hardangervidda og i omkringliggende områder. Prosjektet gjennomføres på oppdrag fra Miljødirektoratet. Formålet er å kunne samle data og utvide kunnskapen om dyras arealbruk og risiko for smittespredning, samt å bidra til mer effektiv bestandsovervåking. Vintrene 2021 og 2022 ble til sammen 70 villrein, 47 elg og 21 hjort GPS-merket.
Forfattere
Christer Moe Rolandsen Roy Andersen Olav Strand Erling Johan Solberg Erling Meisingset Atle Mysterud Morten Heim Øystein Brekkum Bram Van MoorterSammendrag
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Forfattere
Erling Meisingset Joar Gusevik Atle Skjørestad Øystein Brekkum Atle Mysterud Frank Narve RosellSammendrag
Many wild animals perceive humans as predators, and human disturbance,especially in the form of hunting, triggers antipredatory behavior among prey.Yet, knowledge of how game species react to different types of human distur-bance and adapt to repeated disturbances is limited. We investigated howdisturbance in the form of a solitary human approacher (stalker) impactedbehavior (flight response and short-term habitat use) of 28 GPS-collared reddeer (Cervus elaphus) in two populations with contrasting population densitiesin Norway. We studied how the behavioral response differed: (1) with season(pre-hunting vs. hunting); (2) by consecutive approaches within a day;(3) among replicated experiments within the same season; and (4) betweentwo regions with contrasting densities of red deer. The average flight initiationdistance (FID) increased by 15% during the hunting season, and consecutiveapproaches within the same day caused the red deer to move 49% longerdistances. Flight initiation distance was longer in the high-density population,while escape distance was longer in the low-density population. Red deermoved out of their weekly home range after 52% approaches, and after theonset of hunting season, time spent outside the home range increased by 89%.Red deer preferred denser resting sites after the disturbance and animal siteshad shorter sighting distance and higher canopy cover than control plots.Tree density and canopy cover at animal sites increased at the onset of huntingseason, from first to second approach within day, and after replicated experi-ments within season. Our results suggest that red deer preferred dense restingsites, especially in the hunting season. However, these animal sites had thesame amount of the favorable forage plant bilberry (Vaccinium myrtillus), indi-cating no clear food–cover trade-off in selection of habitat. Our study showedthat onset of hunting initiates stronger fear responses in red deer, which mayin turn affect red deer distribution and harvesting efficiency
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Transpiration makes up the bulk of total evaporation in forested environments yet remains challenging to predict at landscape-to-global scales. We harnessed independent estimates of daily transpiration derived from co-located sap flow and eddy-covariance measurement systems and applied the triple collocation technique to evaluate predictions from big leaf models requiring no calibration. In total, four models in 608 unique configurations were evaluated at 21 forested sites spanning a wide diversity of biophysical attributes and environmental backgrounds. We found that simpler models that neither explicitly represented aerodynamic forcing nor canopy conductance achieved higher accuracy and signal-to-noise levels when optimally configured (rRMSE = 20%; R2 = 0.89). Irrespective of model type, optimal configurations were those making use of key plant functional type dependent parameters, daily LAI, and constraints based on atmospheric moisture demand over soil moisture supply. Our findings have implications for more informed water resource management based on hydrological modeling and remote sensing.
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