Browsing Gund Institute for Ecological Economics by Subject "aboveground biomass"

CTL DSpace Repository

Browsing Gund Institute for Ecological Economics by Subject "aboveground biomass"

Sort by: Order: Results:

  • Main-Knorn, M.; Moisen, G. G.; Healey, S. P.; Keeton, W. S.; Freeman, E. A.; Hostert, P. (Remote Sensing, 2011
      Understanding the potential of forest ecosystems as global carbon sinks requires a thorough knowledge of forest carbon dynamics, including both sequestration and fluxes among multiple pools. The accurate quantification of biomass is important to better understand forest productivity and carbon cycling dynamics. Stand-based inventories (SBIs) are widely used for quantifying forest characteristics and for estimating biomass, but information may quickly become outdated in dynamic forest environments. Satellite remote sensing may provide a supplement or substitute. We tested the accuracy of aboveground biomass estimates modeled from a combination of Landsat Thematic Mapper (TM) imagery and topographic data, as well as SBI-derived variables in a Picea abies forest in the Western Carpathian Mountains. We employed Random Forests for non-parametric, regression tree-based modeling. Results indicated a difference in the importance of SBI-based and remote sensing-based predictors when estimating aboveground biomass. The most accurate models for biomass prediction ranged from a correlation coefficient of 0.52 for the TM- and topography-based model, to 0.98 for the inventory-based model. While Landsat-based biomass estimates were measurably less accurate than those derived from SBI, adding tree height or stand-volume as a field-based predictor to TM and topography-based models increased performance to 0.36 and 0.86, respectively. Our results illustrate the potential of spectral data to reveal spatial details in stand structure and ecological complexity.
  • Keeton, W. S.; Whitman, A. A.; McGee, G. C.; Goodale, C. L. (Forest Science, 2011
      Managing the contribution of forest ecosystems to global carbon cycles requires accurate predictions of biomass dynamics in relation to stand development. Our study evaluated competing hypotheses regarding late-successional biomass dynamics in northern hardwood-conifer forests using a data set spanning the northeastern United States, including 48 mature and 46 old-growth stands. Continuous data on dominant tree ages were available for 29 of these and were used as an indicator of stand development. Aboveground live biomass was significantly (P < 0.001) different between mature (195 Mg/ha) and old-growth (266 Mg/ha) sites. Aboveground biomass was positively (P < 0.001) and logarithmically correlated with dominant tree age; this held for live trees (r(2) = 0.52), standing dead trees (r(2) = 0.36), total trees (r(2) = 0.63), and downed woody debris (r(2) = 0.24). In a Classification and Regression Tree analysis, stand age class was the strongest predictor of biomass, but ecoregion and percent conifer accounted for similar to 25-33% of intraregional variability. Biomass approached maximum values in stands with dominant tree ages of similar to 350-400 years. Our results support the hypothesis that aboveground biomass can accumulate very late into succession in northern hardwood-conifer forests, recognizing that early declines are also possible in secondary forests as reported previously. Empirical studies suggest a high degree of variability in biomass development pathways and these may differ from theoretical predictions. Primary forest systems, especially those prone to partial disturbances, may have different biomass dynamics compared with those of secondary forests. These differences have important implications for both the quantity and temporal dynamics of carbon storage in old-growth and recovering secondary forests. FOR. SCI 57(6):489-505.

Search DSpace

Advanced Search


My Account