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Book (series)Wood volume and woody biomass: review of FRA 2000 estimates 2003
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No results found.Wood volume and woody biomass levels are important indicators of the forests’ potential to provide wood and to sequester carbon: the role of forests as major terrestrial sinks and sources of carbon dioxide has received significant additional attention since the adoption of the 1997 Kyoto Protocol to the United Nations Framework Convention on Climate Change (UNFCC). Volume and biomass statistics were among the most important parameters for FRA 2000. Statistics were compiled country by country fol lowing standard terms and definitions. Information to support estimates was not always available for all the countries, and assumptions and extrapolations were necessary in many cases. In attempt to clarify the resulting information and to improve its reliability and accuracy, FRA carried out a systematic review of the calculations underlying the volume and biomass figures (for developing countries), as presented in table 7 Annex 3 of the FAO Forestry Paper 140, Global Forest Resources Assessmen t 2000, Main Report. Industrialized countries were considered separately and estimates for these counties were taken from the UNECE 2000 Main report for Europe, CIS, North America, Australia, Japan and New Zealand. This working paper describes the main steps of the review process, from the data collection and the descriptions of the methodology used, to the presentation and explanations of the results. Conclusions and recommendations are also included in the last section of the working paper. Finally, detailed appendices provide comprehensive tables and an example of country brief lay out where results are presented and explained country by country. -
DocumentManuel de construction d’équations allométriques pour l’estimation du volume et la biomasse des arbres
De la mesure de terrain à la prédiction
2012 -
DocumentThe effects of ignoring clustered data structure in allometric biomass models on large forest area biomass estimation
XV World Forestry Congress, 2-6 May 2022
2022Also available in:
No results found.The aim of this study was to assess the effects of ignoring the clustered data structure on large area biomass estimation, when model uncertainty is included or not in the biomass prediction process. We used a Monte Carlo error propagation procedure to combine the uncertainty from allometric model predictions with the uncertainty from plot-to-plot variation, to produce estimates of mean AGB per hectare and standard error of the mean. An alternative procedure that ignores model prediction uncertainty was also used, therefore, showing only uncertainty due to differences between plots. Ignoring the clustered data structure, (i.e., fitting allometric models using ordinary least squares), the estimates of mean biomass per hectare were approximately 11% less than the estimates based on mixed effects models (that accounted for the clustered data structure), regardless of including or not the model prediction uncertainty. The estimates of uncertainty were also affected by ignoring the clustered data structure. When including model prediction uncertainty, ignoring the clustered data structure resulted in underestimation of standard error by 30%, whereas when model uncertainty was not included, the underestimation was 13%. Therefore, ignoring the clustered data structure, may affect both, the accuracy and the precision of biomass estimations over large forest areas. Keywords: Monitoring and data collection, Climate change ID: 3616826
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