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Nonlinear mixed-effects (NLME) is an important tool for explaining inter- and intra-plot/stand variations, especially when modelling height–diameter relationships. The NLME technique has not been used to model the height–diameter relationship of  Gmelina arborea  trees in Nigeria. Therefore, in this study, NLME model was developed for  G. arborea  stands in southwest Nigeria. A total of 1263 height-diameter pairs measured from 63 sample plots of 0.04 ha size were used to develop the NLME model. The model was calibrated using random effect predicted from the measured height of one to eight sampled trees of an independent dataset. Empirical best unbiased predictor technique was used to make predictions for the random component. Model evaluation was based on different indices such as root mean square error ( RMSE ), adjusted coefficient of determination. The results showed that the NLME model improved the accuracy of predicting heights of  G. arborea  trees with  RMSE  andvalues of 2.378 and 0.828. Calibration response of the model involved the selection of five sample trees per plot nearest to the quadratic mean diameter. This is the ideal compromise between maintaining accuracy and reducing sampling cost.

A mixed-effects height-diameter model for Gmelina arborea Roxb stands in Southwest Nigeria