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In this study, it is aimed that the dynamic site index models for scots pine (Pinus sylvestris L.) stands in Çankırı forests were developed by using Generalized Algebraic Difference Approach, GADA, and Autoregresive Modeling Approach which are up-to-date and complex methods for site index modeling. In this aiming, the model structures of Bertalanffy-Richards, M1, ve Hossfeld, M2-M3, based on Generalized Algebraic Difference Approach were developed and compared with both Nonlinear regression analysis and Autoregresive modeling approach by using 112 stem analysis obtained from studied area. The best predictive model, Hossfeld model, M3, produced the R 2 value of 0.9336 with D.W. of 1.2890 for nonlinear regression analysis and the R 2 value of 0.9449 with D.W. of 1.9903 for Autoregressive modeling, approach, thus this modeling approach has provided a solutions for serial-correlations, autocorrelations, originating from stem analysis data being as time series property. Additionally, the dynamic site index model developed has produced compatible predictions with the expected growth laws, e.g. polymorphism, multiple asymptote and base-age invariable properties in modeling relationships between dominant height and ages.

Çankırı yöresi sarıçam meşcereleri için dinamik bonitet endeks modellerinin otoregresif modelleme ile geliştirilmesi