Sentence examples for predictions of tree from inspiring English sources

Cao ([2006]) found that while the two constrained models performed slightly better than the unconstrained tree model in predicting tree and stand attributes, the disaggregation method provided the best predictions of tree- and stand-level survival and growth.

The disaggregation method provided the best predictions of tree- and stand-level survival and growth.

The adjusted model also provided comparable predictions of tree diameter, height, and survival probability.

Predictions of tree total volume and aboveground biomass were within the expected range for these plots.

Methods for validating short-term predictions of tree or stand change are documented in numerous sources.

Most predictions of tree species' distributions at broad spatial scales are based only on one possible characterization of environmental heterogeneity.

Not only does this limit the interpretability and usage of the scientific model, but it also leads to underestimating the variation associated with prediction of tree height.

Site assessment has been mainly used for the prediction of tree performance but it can be extended to form the basis for site-specific management.

Due to its importance on long term simulations, the prediction of tree mortality was handled in two ways, namely an expansion factor method and a fixed cutpoint (Weiskittel et al. 2011a).

The prediction of tree height is of central importance, not only for the calculation of growing stock from sample inventories, but also in the prognosis of middle and long-term forest development for forest planning and in the analysis of timber supply.

While empirical growth & yield models (G&YMs) provide good estimations of tree growth at the stand level on a yearly to decennial scale, process-based models (PBMs) use LAI dynamics as a key variable for enabling the accurate prediction of tree growth over short time scales.