Our results resolve conflicting assumptions about the nature of tree growth, inform efforts to undertand and model forest carbon dynamics, and have additional implications for theories of resource allocation11 and plant senescence12.
Other initiatives include ITTO demonstration areas and its Model Forest Management Area in Sarawak, the ITTO/CIFOR/Indonesia model forest in Bulungan, Indonesia, and China's network of eight experimental and demonstration areas covering the main eco-zones of the country.
Three of the estimators rely to varying degrees on maps that were constructed using a nonlinear logistic regression model, forest inventory data, and lidar data.
The model forest that the Department of Environmental Conservation and its forestry partners want to establish at Mount Nimham would cover 415 acres of land, though logging activity would initially be conducted on 85 acres, said Matt Burns, a spokesman for the department.
The three logistic regression models, random forests, and boosted regression trees of depth four resulted in calibration slopes closest to one (Table 2).
In nonlinear nonparametric modeling, random forests and their variants, extra-trees (Huynh-Thu et al., 2010), have recently won the DREAM5 challenge devoted to static data by solving p regression problems.
Systematic misclassification of forest age classes and harvest history has serious implications for studies focused on wildlife habitat modeling, forest inventory, and biomass or carbon stock estimation.
Two process-based models, Forest-DNDC and Biome-BGC, with different spatial modeling scales were evaluated to estimate the potential effect of climate change on carbon sequestration in a tropical dry semi-deciduous forest in the Yucatan Peninsula of Mexico.
Based on piecewise linear models, forest-interior and interior-edge guilds' relative abundance harvest thresholds were 28% total harvests (all harvests combined), 10% clear-cut harvests, and 18% light partial harvests, after which abundances declined.
This resulted in three prediction models; a model developed using logistic regression, a model developed using random forests and a model developed using k nearest neighbours.
