Comparison of Modeling Approaches for the Height–diameter Relationship: An Example with Planted Mongolian Pine (Pinus sylvestris var. mongolica) Trees in Northeast China

In the process of modeling height–diameter models for Mongolian pine (Pinus sylvestris var. mongolica), fitting abilities six were compared: (1) a basic model with only diameter at breast height (D) as predictor (BM); (2) plot-level mixed-effects (BMM); (3) quantile regression nine quantiles based on BM (BQR); (4) generalized stand or competition covariates (GM); (5) (GMM); and (6) GM (GQR). The prediction bias developed was assessed in cases total tree (H) predictions calibration without calibration. results showed that extending Chapman–Richards function dominant relative size individual trees improved accuracy. Prediction accuracy significantly when H calibrated all models, among which GMM performed best because random effect provided lowest bias. When least 8% selected from new plot, relatively accurate low-cost obtained by models. predicting values stand, BMM preferable if there available measurements calibration; otherwise, GQR choice.