Evaluating diameter distribution models for coniferous forests in the northwestern Himalayas

Accurate modeling of tree diameter distribution is crucial for sustainable forest management, biomass estimation, and ecological conservation. This study evaluates the effectiveness of four probability distributions viz., Normal, Log-normal, Weibull, and Gamma in characterizing the diameter at breast height (DBH) distributions of Cedrus deodara, Pinus wallichiana, and Abies pindrow in the Shopian and Roamshi forest ranges of the North-Western Himalayas. A total of 750 trees were sampled using a stratified random approach, and their DBH measurements were analyzed using maximum likelihood estimation. Model performance was assessed using Kolmogorov–Smirnov (KS) tests, Akaike Information Criterion (AIC), Bayesian Information Criterion (BIC), and log-likelihood (LogL) values. Results indicate that the Gamma distribution provides the best fit across all species, outperforming other models in terms of statistical goodness-of-fit. The study encountered standard Himalayan field challenges, including rugged terrain and sites with restricted access, as well as the requisite truncation of diminutive stems (10 cm DBH), which may affect the lower tail of empirical DBH distributions. Even with these problems, we offer a species-resolved, multi-criteria benchmarking that shows the Gamma distribution gives the best overall fit for all species (by AIC/BIC/LogL) and points out species-specific differences that can be seen in KS diagnostics.These findings underscore the ecological importance of species-specific diameter distributions and provide a robust statistical framework for forest inventory, carbon stock assessments, and sustainable silvicultural planning.