Article citations

    Loetsch, F., Zohrer, F., & Haller, K. E. (1973). Forest Inventory, Volume II. München: BLV Verlagsgesellschaft.

has been cited by the following article:

  • TITLE: Estimation of Tree Biomass, Carbon Stocks, and Error Propagation in Mecrusse Woodlands
  • AUTHORS: Tarquinio Mateus Magalh?es, Thomas Seifert
  • KEYWORDS: Aboveground Production, Additivity, <i>Androstachys johnsonii</i> Prain, Belowground Carbon Allocation, Error Margins, Root Growth
  • JOURNAL NAME: Open Journal of Forestry DOI: 10.4236/ojf.2015.54041 Apr 24, 2015
  • ABSTRACT: We performed a biomass inventory using two-phase sampling to estimate biomass and carbon stocks for mecrusse woodlands and to quantify errors in the estimates. The first sampling phase involved measurement of auxiliary variables of living Androstachys johnsonii trees; in the second phase, we performed destructive biomass measurements on a randomly selected subset of trees from the first phase. The second-phase data were used to fit regression models to estimate below and aboveground biomass. These models were then applied to the first-phase data to estimate biomass stock. The estimated forest biomass and carbon stocks were 167.05 and 82.73 Mg·ha-1, respectively. The percent error resulting from plot selection and allometric equations for whole tree biomass stock was 4.55% and 1.53%, respectively, yielding a total error of 4.80%. Among individual variables in the first sampling phase, diameter at breast height (DBH) measurement was the largest source of error, and tree-height estimates contributed substantially to the error. Almost none of the error was attributable to plot variability. For the second sampling phase, DBH measurements were the largest source of error, followed by height measurements and stem-wood density estimates. Of the total error (as total variance) of the sampling process, 90% was attributed to plot selection and 10% to the allometric biomass model. The total error of our measurements was very low, which indicated that the two-phase sampling approach and sample size were effective for capturing and predicting biomass of this forest type.