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.
1991
Forfattere
Jon DietrichsonSammendrag
Gran av mellomeuropeiske provenienser fra Syd-vest Tyskland og Østerrike plantet på Syd-Østlandet har på uheldige steder fått frostskader, stammesprekker og meget gankvist. Plantearbeidet foregikk i stor skala fra 1960-79, og har ført til at tre- fire prosent av granskogarealet, for eksempel i Østfold, er beregnet å være bestokket med slike provenienser. Senere, i den mest forplantningsdyktige alderen, vil andelen av trær med mellomeuropeisk opprinnelse kunne utgjøre ca 10-20 %. For genspredningen er det uheldig at det innførte materialet overensstemmer ganske godt med den stedegne granas blomstringstid. Videre er det uheldig at det samme ofte kan være tilfelle for blomstringsmengdene. Vindbestøvende skogstrær viser størst genspredning. Gran rangerer imidlertid lavt i forhold til furu (Fig. 1).Beregninger er gjennomført for befruktningsandeler utenfra på 50 % eller 30 % i alle bestand (Fig. 2 og 3 ). I tillegg til de rene krysningene innen bestandene av mellomeuropeisk opprinnelse vil det oppstå provenienskrysninger. Halvparten av disse vil komme fra mellomeuropeiske mødre og den andre halvparten fra de norske. Fordi genspredning ved frø er over meget kortere avstander enn ved pollen, vil den første type av provenienshybrider hovedsakelig vise seg i eller like i nærheten av bestand av mellomeuropeisk opprinnelse. Den andre halvparten vil bli spredd utover i skogene. Frekvensene for de sistnevnte vil etter beregningene bli lave (4.5 - 8 %). I de tilfellene hvor provenienshybridene er dårlig tilpasset til klimaet ventes de å bli borte på grunn av naturlig seleksjon eller ved avstandsregulering. For å redusere eventuelle negative effekter av genspredningen er det anbefalt å utelate tynning av bestand som er spesielt dårlige. Videre kan omløpstida senkes. Naturlig gjenvekst i og omkring bestandene er anbefalt fjernet for å bli erstattet med kjent godt plantemateriale. I alle tilfelle vil de innførte proveniensene øke den arvelige variasjonen i skogene.
Forfattere
Tron EidSammendrag
This work deals with some effects erroneous measurements might have for the inventory results, the forecasts and the priorities of treatments in forest stands. The following variables are evaluated; site quality, total age, tariff number, number of trees/ha, basal area, mean height, conditions for logging and hauling, hauling distance and timber quality. The consequences of errors are considered by means of sensitivity analysis for 14 different stands (Table 2). Some considerations on how and why erroneous measurements appear, are done in chapter 2.3.Incorrect site quality or total age influences the total production, partly because the increment changes and partly because the treatments change. Fig. 1 shows an example of how a 20% incorrect site quality during a period of 35 years makes the volume change by 7-9%. The increment and the volume also change if the total age is incorrectly estimated (10%). The volumes change by 1% and 9% depending on the number of years in the time period between the \"inventory\" and the final fellings (Table 5).Incorrect site quality or total age might also influence the treatments of a stand, e.g. changed rotations age because the value increment has changed. An incorrect site quality might also insert \"incorrect\" regeneration methods. This is most likely in stands of medium site quality. An example shows that the net present value decreases about 30% if planting is selected instead of natural regeneration because the decision-maker believe that the site quality is F17, instead of F14.Incorrectly estimated basal area or mean height directly influence the volume. 10% biased basal area means that the volume changes 10% (Table 9 and 10). Approximately the same bias for the volume appears with 10% error for the mean height (Table 11 and 13). There is, however, quite big differences between these two variables with respect to other consequences.A biased basal area has small (Table 9) or none (Table 10) effects on the prices and costs/m3 because the size of the \"mean tree\" is little or not effected. A biased mean height has larger effects because the size of the \"mean tree\" changes. Cases where the net revenue/ha increases by 30-40%, if the mean height is 10% too high, is quite likely (Table 11 and 13).Incorrect tariff number or number of trees/ha do not influence the volume. The changes of the net revenues/ha are accordingly quite small (Table 7 and 8). This is particularly the situation for Norway spruce where both prices and costs/m3 increase if the tariff number or the number of trees/ha are positively biased.The change for Scots pine is larger because the prices/m3 decrease while the costs/m3 increase. For the costs/m3, errors have similar effects for Norway spruce and Scots pine, i.e. a positively biased tariff number or number of trees/ha increase the costs/m3, while a positively biased basal area or mean height decrease them.For the prices/m3, however, there is an opposite effect for tariff number, number of trees/ha and basal area, i.e. if incorrect measurements for one of these variables make the mean diameter increase, the prices decrease for spruce while they increase for pine (Fig. 2). A positively biased mean height makes the prices higher for both tree species in the considered stands.Two procedures to decide the volume/ha, the \"mean tree\" and the number of trees/ha are described in chapter 2.3.3. (see Table 1). The selected procedure is irrelevant for the volume, because this volume in both cases are based on the basal area and the mean height. The differences between the procedures appear when the \"mean tree\" is decided; the effects of errors are different because the number of trees/ha is measured in \"the number of trees procedure\", while the tariff number is measured in \"the tariff number procedure\".With a 10% biased tariff number in a spruce stand, the mean diameter change about 10% and the number of trees/ha change about 15%. There are more significant changes for pine, i.e. examples where the mean diameter changes more than 30% (Table 6). With a 10% biased number of trees/ha, the mean diameter changes about 5% for both tree species. The big changes of the variables describing the \"mean tree\" of \"the tariff number procedure\", make the changes for prices and costs/m3, and accordingly also the net revenue/ha, larger than the changes of \"the number of trees procedure\" (Table 7 and 8).An incorrect basal area has a small effect on the \"mean tree\" in both procedures (Table 9 and 10). For an incorrectly estimated mean height, however, the consequences are severe for \"the tariff number procedure\". This is accordingly also the situation for the prices and costs/m3, and the net revenue/ha (Table 11 and 13). Effects of erroneous measurements in cutting class II (age class, i.e. young stands) are considered for the variables regulated number of trees/ha and site quality.If these variables are biased, the volume increment change, accordingly also the volume of the final fellings. With a positive bias of 30% for the regulated number of trees/ha, there are examples where the volume of the final felling is more than 15% too high (Fig. 3). If the site quality is one 3-meter class too high or low, the volume of the final felling might have a bias of 30% (Table 14).The changes of the costs/m3 and net revenues/m3 are quite small if the conditions for logging and hauling are incorrectly classified (Table 15). The changes are larger if the timber quality is incorrectly classified. A 10% bias for the share of pulpwood, means that the net revenue/m3 changes 5.5% and 15.6% for spruce and pine stands respectively (Table 16). The large change for pine is due to the big difference between the price/m3 for pulpwood and sawtimber.
Forfattere
Oddvar SkreSammendrag
Large differences were found in survival stratey among species and ecotypes. The maple and elm populations and the two southern birch populations all responded to high temperatures by rapid leaf expansion as a possible compensation for increased respiration loss, and themaple and birch also by increasing their stem elongation rates, thereby competing more efficiently for available light. In the northern subalpine birch population, however, the seedlings developed leaves with high net assimilation rates instead of increasing their leaf areas and stem elongation rates. In this population abiotic climatic factors rather than competition therefor seem to be the most important adaptive force.
Forfattere
Harald Kvaalen Sara von ArnoldSammendrag
Effects of various partial pressures of oxygen (5, 20 and 45 kPa) and carbon dioxide (0.03 and 6 kPa) on initiation, proliferation and maturation of somatic embryos in Picea abies were studied. The pO2 had a significant effect on the initiation of embryogenic tissue from mature zygotic embryos. However, the effect of pO2 was dependent on the strength of the basal medium.Low pO2 stimulated the formation of embryogenic tissue when the zygotic embryos were incubated on full strength medium, but was inhibitory when half-strength medium was used.Proliferation of embryogenic tissue was stimulated by higher partial pressures of both CO2 and O2. The effect of the gas phase on maturation of somatic embryos varied between different cell lines. However, there was a general tendency for 5 kPa O2 and 6 kPa CO2 to stimulate maturation.
Forfattere
Harald Eikeland Knut Rumohr BlingsmoSammendrag
I årene 1962 til 1966 anla Det norske Skogforsøksvesen fire proveniensforsøk med gran i Ringsaker kommune, Hedmark fylke. Formålet med forsøkene var å få produksjonstall for bestand av ulike provenienser. Det ble prøvd fire utenlandske provenienser, to østerrikske og to tyske, sammen med ni norske. De norske proveniensene strakte seg fra kyststrøkene på Sørlandet til midtre Trøndelag, og representerte et spenn på 6 breddegrader. Produksjonstallene fra oppmålingen av forsøkene i 1985-87 viste generelt små forskjeller mellom proveniensene. Mellom proveniensene med lavest og høyest produksjon var forskjellen omlag 10 prosent for diameter og 20 prosent for volum. Proveniensene varierte mye fra forsøk til forsøk, men jevnt over var de utenlandske proveniensene blant de høyest produserende, mens den nordligste av de norske, Trøndelag midtre, lå lavest. Den proveniensen som representerte den stedegne, lå hele tiden blant de med høyest produksjon. For et av forsøkene ble det foretatt toppskuddmålinger for 6-års perioden 1966-72. Det var svært god sammenheng mellom målingene av høydevekst for disse årene, og produksjonstallene fra 1985. Forklaringsprosentene lå mellom 70 og 80 prosent. Denne høye forklaringsprosenten var betinget av at en representativ andel av trærne ble høydemålt. De 1000 høyeste trær pr. ha gav best forklaring. Skader som gankvist, stammesprekk, krok og kløft ble registert på forsøkene. Gankvist var den vanligste skaden, og fantes hos omtrent 20 prosent av trærne. Stammesprekk fantes hos om lag 1 prosent av trærne. Det var små forskjeller mellom de ulike proveniensene. Årringbredden hos alle provenienser hadde det meste av tiden siden trærne nådde brysthøyde ligget over 4 mm. På grunnlag av disse forsøkene ble det konkludert med at hvis ikke lokalklimaet er ugunstig, er det lite grunnlag for å gi sentraleuropeiske provenienser noen særbehandling i takst- eller prognosesammenheng. Det tas forbehold om dette også gjelder for østeuropeiske provenienser og for foredlet materiale.
Forfattere
Erik NæssetSammendrag
Formålet med dette arbeidet er å undersøke nøyaktigheten ved bestandsvis bestemmelse av middeldiameter og høydeklasse ved tolking av flybilder. Dessuten beskrives en modell for bestemmelse av gjennomsnittlig bruttoverdi i bestand av hogstklasse IV-V ved hjelp av fotomålinger. Nøyaktigheten ved bruk av denne modellen blir undersøkt. 24 bestand i hogstklasse III i Gjøvik kommune og 128 bestand i hogstklasse IV-V i Gjøvik, Grue og Kongsvinger kommuner er totalklavet. Bestand med mer enn 10 % lauv er ikke representert, med unntak av 2 bestand i hogstklasse III. Høydeklasse, grunnflatemiddeldiameter (dg) og bruttoverdi er beregnet for hvert bestand på grunnlag av de markmålte dataene. Bruttoverdi er beregnet som volumveid gjennomsnittspris pr. kubikkmeter stammevolum uten bark. 5 trenede stereo-operatører har registrert bestandsmiddelhøyde, kronedekning og treslagsfordeling i hvert bestand i pankromatiske (svart-hvite) flybilder i målestokk 1:15000. Det er benyttet Wild B8 for alle registreringene. Bildene er tatt 0-4 år før totalklaving.Markmålt middeldiameter er korrigert til fotograferingstidspunktet. Grunnflatemiddeldiameter er beregnet på grunnlag av fotomålingene ved hjelp av funksjoner utviklet av Næsset (1988, 1990). Det er funnet et standardavvik til differansene mellom foto- og markmålt middeldiameter på 10-12 % (2,0-2,5 cm) i hogstklasse IV-V. Den systematiske feilen er på +8 til +19 %. Høydeklassen for gran og furu er beregnet ved hjelp av funksjoner utviklet av Næsset (1988). For gran er det funnet et standardavvik på 7-9 % (0,10-0,13 høydeklasse-enheter) i hogstklasse III-V, og en systematisk feil på mellom -7 % og -15 %. For furu er det funnet et standardavvik på 6-8 % (0,07-0,09 høydeklasse-enheter), og en systematisk feil på mellom -2 % og -9 %. Modellen for bestemmelse av gjennomsnittlig bruttoverdi i bestand av hogst klasse IV-V ved hjelp av fotomålinger er omtalt i kapittel 3. Modellen bygger på `middeltremetoden`. Bruttoverdien er beregnet ved hjelp av denne modellen i samtlige bestand av hogstklasse IV-V. Det er funnet et standardavvik på 3-6 % (11-20 kr/m3), og en systematisk feil på mellom -1 % og +3 %. På grunn av systematiske feil, er det grunn til å anbefale korreksjon av middeldiameter og høydeklasse mot en systematisk prøveflatetakst. Når fotomålingene benyttes for bestemmelse av bruttoverdi, bør dessuten også den fotomålte middelhøyden korrigeres før bruttoverdien beregnes.
Forfattere
Tron EidSammendrag
This work deals with some consequences erroneous data basis might have for the planning and the management of forest holdings. The way in which the data basis, which is divided into the inventory basis, the model basis and assumptions, influences the planning process, is showed in Fig. 1. The considerations are mainly concentrated on the inventory basis, and the variables site quality, stand age, basal area and mean height. Sensitivity analysis is carried out for 10 model forests (Table 1), where consequences for plan suggestions, decisions and accomplishment of decisions are considered. Examples of how erroneous measurements might influence the property value of a forest are also given. Incorrect site quality changes both the increment and the treatments. This means that the total production of a forest might change considerably. If the site quality is one class too high or low in all stands, the production levels of the forests change by 30-40%. The largest deviations are found when the site quality is overestimated, and in the pine forests (Table 3). Incorrect site quality also influences the relative age of a stand. Fig. 2 shows how the economically mature areas, and the corresponding volumes, change due to incorrect site quality. Examples where the share of economically mature areas and volumes decrease from 50%, when the site quality is overestimated by one class, to near zero when the site quality is underestimated by one class, are not unlikely. Such deviations do, of course, also influence the balance quantity and the fellings according to economical cutting maturity (Table 4). Especially the changed rotation ages might lead to large deviations. Incorrect site quality might also insert a silvicultural program which is too intensive or extensive according to correct site quality, and the interest rate. In such cases the net present value decreases (Table 5). Also the property value is influenced by an incorrect site quality. In the model forests these values change 15-20% if the site quality is over- or underestimated by one class (Table 6). An incorrect stand age influences the forecasts due to changed increment, and due to changed time for final fellings. The changes of the increment, as a result of an overestimated or an underestimated stand age, generally decrease the balance quantity in the first case, and increase it in the second case (Table 7). In forests where the share of old stands is low, the conclusion might be the opposite, i.e. the balance quantity increase when the age is overestimated, and decreases when the age is underestimated. This is due to a changed share of mature stands. The balance quantities change by 6-8%, and the fellings according to economical maturity change about 10%, if the basal area has a bias of 10% (Table 8). The net revenues change in the same way because the mean tree, and accordingly also the prices and costs/m3, remain the same, in spite of incorrect basal area. To accomplish felling suggestions based on incorrect data, e.g. 10% too large basal area, influence the possibilities of the future. There might, for example, be too few mature stands to accomplish the suggested balance quantity strategy in the future (Fig. 3). The fellings have to be reduced some years later. This is in conflict with the decision-makers goal. Also an incorrect basal area changes the property values of the forests. 10% incorrect basal area makes them change by 7-9% (Table 9). 10% too large mean height makes the balance quantities change by 6-9% in the spruce forests, while they change by 3-5% in the Scots pine forests (Fig. 4). The deviations for the net revenues are larger because the mean tree, and accordingly the prices and costs/m3, are changed. This is particularly the case in the pine forests where the net revenues change by 12-15%. Some examples of how errors in the model basis, and how incorrect assumptions might influence the balance quantity, are also given. The balance quantities increase by 4-6% if the diameter increment is overestimated by 10%, while the balance quantities increase by 3-6% if the lower limit of the rotation ages are assumed to be 10 years too low (Fig. 5). Combinations of different errors might either strengthen or hide effects. An overestimated site quality, basal area and diameter increment at the same time will, for example in forest no. 1, lead to an overestimation of the balance quantity by 19%, while there is a very small change if the site quality is overestimated and the diameter increment is underestimated at the same time (Table 10).Taking into account the relatively moderate systematic errors assumed in the examples, that combinations of errors might appear, and that also errors in functions or errors connected to the assumptions for the treatments are quite likely, the errors appearing in practical applications are probably larger than those considered in this study.
Forfattere
Jarle BerganSammendrag
Picea abies does not grow naturally north of the Polar circle in Norway (except for some sporadic occurrences in Finnmark). From 1973 to 1985 20 field tests were carried out at different vegetation types and altitudes in Nordland and Troms. The main objective of the investigation was to study survival, height growth and injuries to northern provenances of Norway spruce grown under various soil and climatic conditions. The climatic conditions at the experimental areas represent different kinds of heat and frost climate. According to Kielland-Lund (1981), the vegetation types represented in the investigation are: 13. ass.: Eu-Piceetum abietis a) Subass.: myrtilletosum b) Subass.: dryopteridetosum c) Subass.: athyrietosum 14. ass.: Melico nutantis-Piceetum abietis b) Subass.: typicum c) Subass.: aconitetosum The provenance codes are made up of a letter indicating the seed collection zone, and a number indicating the altitude (1=0-149 m a.s.l, 2= 150-249 m a.s.l. etc.). Fig. 1 shows the seed collection zones together with the geographical position of the field experiments. Particulars of plots and provenances are given in Tables 1 and 2. P2-Rana is used as standard provenance. The test fields are divided in two groups: 8 main fields including the 15 provenances shown in Table 2. 12 other fields includes a selection of the fifteen provenances listed in Table 2. In addition, three Finnish provenances are included in some of the experiments (see Chap. 2). The main results are given in Tables 59, 60 and 93. Provenances of Region 1 have in average for the eight main fields about 10% bigger heights than provenances from the regions 2, 3 and 4 (Table 60). As regards mean heights, P1 and P2 from Rana have turned out to be ranked among the best provenances at every experimental field, which is not always the case for P1-Drevja and P 1-Hemnes. At frosty sites and by unfavourable growth conditions at high altitudes, the results indicate that P2 from Rana is to be preferred to P1-Rana. At high levels not far from the timberline, P1 and P2 from Rana seem to be as well adapted to unfavourable local climatic conditions as local provenances in the southern part of Nordland (O4 and O5). At localities exposed to frost in the bottom of the valleys in Troms, the results show that provenances from high altitudes in the most southern part of Nordland (O4 and O5) are not to be preferred to P2-Rana. On the other hand, P3-Rana has achieved relatively good height growth and high survival at sites with unfavourable growth climate.At such areas, production of birch has to be considered instead of planting spruce. The height growth and survival of the three Finnish provenances have been good. However, there seems no reason to prefer theese provenances to P1 or P2 from Rana. At areas outside the natural bounderies of the provenances, Q1, Q2 and R1 has reached the relatively best heights and survival percentages at sites of favourable growth climate, preferentially in the outer districts of Nordland and Troms. The same can be said about O1-Vefsn and O1-Grane. The mean survival percentage of the plots varies between 80 to 90% for the different provenances (Tables 59, 60 and 93). The survival of the plants depends more on injuries by voles, vegetation pressure etc. rather than distinctions of provenances. Late summer frost is the most usual injuries by frost in North-Norway. All frost injuries specified in the tables are such injuries.
Sammendrag
Det er ikke registrert sammendrag
Forfattere
Arne Grønlund Rune SolbergSammendrag
Det er ikke registrert sammendrag