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Implications of differing input data sources and approaches upon forest carbon stock estimation.
Wulder, Michael A; White, Joanne C; Stinson, Graham; Hilker, Thomas; Kurz, Werner A; Coops, Nicholas C; St-Onge, Benôit; Trofymow, J A Tony.
Afiliación
  • Wulder MA; Canadian Forest Service (Pacific Forestry Center), Natural Resources Canada, 506 West Burnside Rd., Victoria, BC, V8Z 1M5, Canada. mwulder@nrcan.gc.ca
Environ Monit Assess ; 166(1-4): 543-61, 2010 Jul.
Article en En | MEDLINE | ID: mdl-19517261
Site index is an important forest inventory attribute that relates productivity and growth expectation of forests over time. In forest inventory programs, site index is used in conjunction with other forest inventory attributes (i.e., height, age) for the estimation of stand volume. In turn, stand volumes are used to estimate biomass (and biomass components) and enable conversion to carbon. In this research, we explore the implications and consequences of different estimates of site index on carbon stock characterization for a 2,500-ha Douglas-fir-dominated landscape located on Eastern Vancouver Island, British Columbia, Canada. We compared site index estimates from an existing forest inventory to estimates generated from a combination of forest inventory and light detection and ranging (LIDAR)-derived attributes and then examined the resultant differences in biomass estimates generated from a carbon budget model (Carbon Budget Model of the Canadian Forest Sector (CBM-CFS3)). Significant differences were found between the original and LIDAR-derived site indices for all species types and for the resulting 5-m site classes (p < 0.001). The LIDAR-derived site class was greater than the original site class for 42% of stands; however, 77% of stands were within +/-1 site class of the original class. Differences in biomass estimates between the model scenarios were significant for both total stand biomass and biomass per hectare (p < 0.001); differences for Douglas-fir-dominated stands (representing 85% of all stands) were not significant (p = 0.288). Overall, the relationship between the two biomass estimates was strong (R(2) = 0.92, p < 0.001), suggesting that in certain circumstances, LIDAR may have a role to play in site index estimation and biomass mapping.
Asunto(s)

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Árboles / Carbono / Monitoreo del Ambiente / Biomasa / Contaminantes Atmosféricos Tipo de estudio: Risk_factors_studies Idioma: En Revista: Environ Monit Assess Asunto de la revista: SAUDE AMBIENTAL Año: 2010 Tipo del documento: Article País de afiliación: Canadá Pais de publicación: Países Bajos

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Árboles / Carbono / Monitoreo del Ambiente / Biomasa / Contaminantes Atmosféricos Tipo de estudio: Risk_factors_studies Idioma: En Revista: Environ Monit Assess Asunto de la revista: SAUDE AMBIENTAL Año: 2010 Tipo del documento: Article País de afiliación: Canadá Pais de publicación: Países Bajos