Vol17 No.5: 1084-1095
【Title】Some non-linear height–diameter models performance for mixed stand in forests in Northwest Iran
【Author】Roya ABEDI1*; Tooba ABEDI2
【Addresses】1 Department of Forestry, Ahar Faculty of Agriculture and Natural Resources, University of Tabriz, Ahar 5451645857, Iran; 2 Environmental Research Institute, Academic Center for Education, Culture and Research, Rasht 41635-3114, Iran
【Corresponding author】Roya ABEDI
【Citation】Abedi R, Abedi T (2020) Some non-linear height–diameter models performance for mixed stand in forests in Northwest Iran. Journal of Mountain Science 17(5). https://doi.org/10.1007/s11629-019-5870-4
【Abstract】This study evaluated the total height of trees based on diameter at breast height by using 23widely used height-diameter non-linear regression models for mixed-species forest stands consisting of Caucasian oak, field maple, and hornbeam from forests in Northwest Iran. 1920 trees were measured in 6 sampling plots (every sampling plot has 1 ha area). The fit of the best height–diameter models for each species were compared based on R2, Root Mean Square Error (RMSE), Akaike information criterion (AIC), standard error, and relative ranking performance criteria. In the final step, verification of results was performed by paired sample t-test to compare the observed height and estimated height. Results showed that among 23 height-diameter models, the best models were obtained from the top five ones including Modified-logistic, Prodan, Sibbesen, Burkhart, and Exponential. Comparison between the actual observed height and estimated height for Caucasian oak showed that Modified–Logistic, Prodan, Sibbesen, Burkhart, and Exponential performed better than the others, respectively (There were no statistically significant differences between observed heights and predicted height (p≥0.05)). Prodan, Modified-Logistic, Burkhart, and Loetch evaluated field maple tree height correctly, and Modified-Logistic, Burkhart, and Loetch had better fitness compared to the others for hornbeam, respectively. Although other models were introduced as appropriate criteria, they could not reliably predict the height of trees. Using the Rank analysis, the Modified-Logistic model for the Caucasian oak and Prodan model for field maple and hornbeam had the best performance. Finally, to complement the results of this study, it is suggested toassess how environmental factors such as elevation, climate parameters, forest protection policy and forest structure will modify height-diameter allometry models and will enhance the prediction accuracy of tree heights prediction in mixed stands.
【Keywords】Arasbaran; Forest inventory; Height prediction; Model validation; Non-linear modeling; Rank analysis