Abstract

Background: In this study 11 height and diameter prediction models were fitted and evaluated for Himalayan Chir pine (Pinus roxburghii) in Jammu region of UT J and K (India). The data were collected from 50 permanent sample plots in uneven aged stands of Pinus roxburghii and total of 500 individual tree height and diameter measurement were used for this study. At initial stage all the models fitted resulted in significant coefficients, besides various selection criteria’s were also used to test the predictive performance of fitted models. The results of these criteria were generated from various libraries of R studio (version 3.5.1, 2018). The models were further cross validated and results revealed Manfred (MG) and Michaelis-Menten2 (MJ) models described the highest amount of height variation in terms of fit statistics and more crucially with lowest prediction error rate as compared to other models. Methods: The study was carried out in Jammu region of UT J and K (India). Data used in this study were collected on 50 permanent sample plots of 0.25 ha in size.In order to achieve stipulated objectives, Height diameter data on 500 trees from Jammu forest division was utilized in this study. Result: The summary statistics of height and diameter variable and the overall summary of the coefficients of various height and diameter models in Jammu forest division are presented. Almost all the coefficients of the statistical models were statistically significant which is an indication that fitted models are capturing the height diameter relationship an important aspect in context to biological realism.

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