Functions for estimating aboveground biomass of birch in Norway

References

• Antón-Fernández C, Astrup R. 2012. Empirical harvest models and their use in regional business-as-usual scenarios of timber supply and carbon stock development. Scand J For Res. 27:379–392. 10.1080/02827581.2011.644576
   Web of Science ®Google Scholar
• Atkinson MD. 1992. Betula pendula Roth (B. verrucosa Ehrh.) and B. pubescens Ehrh. Biological flora of the British Isles. J Ecol. 80:837–870. 10.2307/2260870
   Web of Science ®Google Scholar
• Atkinson MD, Jervis AP, Sangha RS. 1997. Discrimination between Betula pendula, Betula pubescens, and their hybrids using near-infrared reflectance spectroscopy. Can J For Res. 27:1896–1900. 10.1139/cjfr-27-11-1896
   Web of Science ®Google Scholar
• Baskerville GL. 1972. Use of logarithmic regression in the estimation of plant biomass. Can J For. 2:49–53.
   Google Scholar
• Bates DM, Watts, DG. 1988. Nonlinear regression analysis and its applications. New York (NY): Wiley.
   Google Scholar
• Bollandsås OM, Rekstad I, Næsset E, Røsberg I. 2009. Models for predicting above-ground biomass of Betula pubescens spp. czerepanóvii in mountain areas of southern Norway. Scand J For Res. 24:318–332. 10.1080/02827580903117412
   Web of Science ®Google Scholar
• Bylund H, Nordell KO. 2001. Biomass proportion, production and leaf nitrogen distribution in a polycormic mountain birch stand (Betula pubescens spp. czerepanóvii) in northern Sweden. In: Wielgolaski FE, editor. Nordic mountain birch ecosystems. Man and the biosphere series. Vol. 27. New York (NY): Parthenon; p. 115–126.
   Google Scholar
• Claesson S, Sahlén K, Lundmark T. 2001. Functions for biomass estimation of young Pinus sylvestris, Picea abies, and Betula spp. from stands in northern Sweden with high stand densities. Scand J For Res. 16:138–146. 10.1080/028275801300088206
   Web of Science ®Google Scholar
• Dahlberg U, Berge TW, Petersson H, Vencatasawmy CP. 2004. Modelling biomass leaf area index in a sub-arctic Scandinavian mountain area. Scand J For Res. 19:60–71. 10.1080/02827580310019266
   Web of Science ®Google Scholar
• de Wit HA, Palosuo T, Hylen G, Liski J. 2006. A carbon budget of forest biomass and soils in southeast Norway calculated using a widely applicable method. For Ecol Manag. 225:15–26. 10.1016/j.foreco.2005.12.023
   Web of Science ®Google Scholar
• Duan N. 1983. Smearing estimate: a nonparametric retransformation method. J Am Stat Assoc. 78:605–610. 10.1080/01621459.1983.10478017
   Web of Science ®Google Scholar
• Flewelling JW, Pienaar LV. 1981. Multiplicative regression with lognormal errors. For Sci. 27:281–289.
   Google Scholar
• Global Forest Resources Assessment (GFRA). 2010. Country Reports. Rome (Italy): Food and Agriculture Organization of the United Nations, Forestry Department (FRA2010/155). Reports for Belarus, Canada, Estonia, Finland, Iceland, Latvia, Lithuania, Norway, Russia, Sweden, and United States of America. Available from: http://www.fao.org/forestry/fra/67090/en/
   Google Scholar
• Granhus A, Hylen G, Nilsen J-E. 2012. Statistikk over skogforhold og skogressurser i Norge registrert i perioden 2005–2009 [Statistics of forest conditions and forest resources in Norway registered in 2005–2009]. Ås (Norway): Ressursoversikt fra Skog og landskap [Overview of resources from forest and landscape].
   Google Scholar
• Jenkins JC, Chojnacky DC, Heath LS, Birdsey RA. 2003. National-scale biomass estimators for United States tree species. For Sci. 49:12–35.
   Google Scholar
• Johansson T. 2007. Biomass production and allometric above-and below-ground relations for young birch stands planted at four spacings on abandoned farmland. Forestry. 80:41–52. 10.1093/forestry/cpl049
   Web of Science ®Google Scholar
• Kjelvik S. 1974. Primærproduksjon i en subalpin bjørkskog på Maurset i Øvre-Eidfjord, Hordaland [Primary production in a subalpine birch forest in Maurset in Øvre-Eidfjord municipality, Hordaland county] [ dissertation]. Ås: Norwegian Agricultural University. Norwegian with English summary.
   Google Scholar
• Korsmo H. 1995. Weight equations for determining biomass fractions of young hardwoods from natural regenerated stands. Scand J For Res. 10:333–346. 10.1080/02827589509382900
   Web of Science ®Google Scholar
• Lambert MC, Ung C-H, Raulier F. 2005. Canadian national tree aboveground biomass equations. Can J For Res. 35:1996–2018. 10.1139/x05-112
   Web of Science ®Google Scholar
• Marklund LG. 1987. Biomass functions for Norway spruce (Picea abies (L.) Karst.) in Sweden (Rapport 43). Umeå: Department of Forest Survey, Swedish University of Agricultural Sciences,.
   Google Scholar
• Marklund LG. 1988. Biomassafunktioner för tall, gran och björk I Sverige [Biomass functions for pine, spruce and birch in Sweden (Report 45)]. Umeå: Department of Forest Survey, Swedish University of Agricultural Sciences. Swedish with summary in English.
   Google Scholar
• Norwegian National Forest Inventory (NNFI). 2009. Norwegian National Forest Inventory: 9th Inventory Cycle. Ås (Norway): Norwegian Forest and Landscape Institute.
   Google Scholar
• Opdahl H. 1987. Bjørkeskog til energiformål I Nord-Østerdalen [Birch forests for energy purposes in the north of Østerdalen]. Norsk Skogbruk. 2:28–30. Norwegian.
   Google Scholar
• Parresol BR. 1999. Assessing tree and stand biomass: a review with examples and critical comparisons. For Sci. 45:573–593.
   Google Scholar
• Parresol BR. 2001. Additivity of nonlinear biomass equations. Can J For Res. 31:865–878. 10.1139/x00-202
   Web of Science ®Google Scholar
• Pastor J, Aber JD, Melillo JM. 1984. Biomass prediction using generalized allometric regressions for some northeast tree species. For Ecol Manage. 7:265–274. 10.1016/0378-1127(84)90003-3
   Web of Science ®Google Scholar
• Pinheiro JC, Bates DM. 2000. Mixed-effects models in S and S-PLUS. New York (NY): Springer Verlag.
   Google Scholar
• Pinheiro J, Bates D, DebRoy S, Sarkar D, The R Development Core Team. 2012. nlme: linear and nonlinear mixed effects models. R package version 3. 1–104.
   Google Scholar
• Repola J. 2008. Biomass equations for birch in Finland. Silva Fennica. 42:605–624. 10.14214/sf.236
   Web of Science ®Google Scholar
• Robinson AP, Hamann JD. 2010. Forest analytics with R: an Introduction. New York (NY): Springer.
   Google Scholar
• R Core Team. R: A language and environment for statistical computing [Internet]. 2012. R Foundation for Statistical Computing, Vienna (Austria). Available from: http://www.R-project.org/
   Google Scholar
• Sit V, Poulin-Costello M. 1994. Catalog of curves for curve fitting (Biometrics Information handbook series, No. 4). Victoria (BC): British Columbia Ministry of Forests.
   Google Scholar
• Snorrason A, Einarsson SF. 2006. Single-tree biomass and stem volume functions for eleven tree species used in Icelandic forestry. Icel Agric Sci. 19:15–24.
   Google Scholar
• Strand L. 1967. Høydekurver for bjørk [Height curves for birch]. Meddelelser fra det Norske Skogforsøksvesen. 22, Kapittel IX, side 291. Calculator. Available from: http://www.skogoglandskap.no/kalkulator/bonitering_og_produksjonsevne/bonitering_og_produksjonsevne/ny_bonitets_kalkulator?calculator_mode=True
   Google Scholar
• Taylor J. 1986. The retransformed mean after a fitted power transformation. J Am Stat Assoc. 81:114–118. 10.1080/01621459.1986.10478246
   Web of Science ®Google Scholar
• Tveito OE, Førland EJ, Dahlström B, Elomaa E, Frich P, Hanssen-Bauer I, Jónsson T, Madsen H, Perälä J, Rissanen P, Vedin H. 1997. Nordic precipitation maps. Oslo: Det Norske Meteorologiske Institutt. (Report no. 22/97 Klima, pp. 22).
   Google Scholar
• Tveito OE, Førland E, Heino R, Hanssen-Bauer I, Alexandersson H, Dahlström B, Drebs A, Kern-Hansen C, Jónsson T, Vaarby Laursen E, Westman Y. 2000. Nordic temperature maps. Oslo: Det Norske Meteorologiske Institutt (Report no. 09/00 Klima, pp. 54).
   Google Scholar
• Ung C-H, Bernier P, Guo X-J. 2008. Canadian national biomass equations: new parameter estimates that include British Columbia data. Can J For Res. 38:1123–1132. 10.1139/X07-224
   Web of Science ®Google Scholar
• Wirth C, Schumacher J, Schulze ED. 2004. Generic biomass functions for Norway spruce in Central Europe—a meta-analysis approach toward prediction and uncertainty estimation. Tree Physiol. 24:121–139. 10.1093/treephys/24.2.121
   PubMed Web of Science ®Google Scholar
• Wutzler T, Wirth C, Schumacher J. 2008. Generic biomass functions for Common beech (Fagus sylvatica) in Central Europe: predictions and components of uncertainty. Can J For Res. 38:1661–1675. 10.1139/X07-194
   Web of Science ®Google Scholar