Predictive Modelling of Height and Diameter Relationships of Himalayan Chir Pine

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