编号 010021705
推送时间 20191216
研究领域 森林生态
年份 2019
类型 期刊
语种 英语
标题 Contemporary forest carbon dynamics in the northern U.S. associated with land cover changes
来源期刊 Forests
期 第217期
发表时间 20191104
关键词 Forest; Landsat; Spatial distribution; Uncertainty; Carbon;
摘要 Dry Afromontane forests form the largest part of the existing natural vegetation in Ethiopia. Nevertheless, models for quantifying aboveground tree biomass (AGB) of these forests are rare. The objective of this study was, therefore, to develop local multispecies and species-specific AGB models for dry Afromontane forests in northern Ethiopia and to test the accuracy of some potentially relevant, previously developed AGB models. A total of 86 sample trees consisting of ten dominant tree species were harvested to develop the models. A set of models relating AGB to diameter at breast height (DBH) or at stump height (DSH), height (H), crown area (CA), and wood basic density (ρ) were fitted. Model evaluation and selection was based on statistical significance of model parameter estimates, relative mean root-square-error (rMRSE), relative bias (rBias), and Akaike Information Criterion (AIC). A leave-one-out cross-validation procedure was used to compute rMRSE and rBias. The best multispecies model, which includes DSH, CA, and ρ as predictors, explained more than 95% of the variability in AGB. The best species-specific models for the two dominant species, with DBH or DSH as the sole predictor, also explained more than 96% of the variability in AGB. Higher biases from the previously published models compared to the best models from this study show the need to develop local models for more accurate biomass estimation. The developed models allow to quantify AGB with a high level of accuracy for our site, and they can potentially be applied in dry Afromontane forests elsewhere in Ethiopia if species composition and growing conditions are carefully evaluated before an application is done.
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