Abstract
Forest stand management often depends on data from a single fixed area inventory plot located at random in a forest stand. The plot provides detailed information about tree size distribution but not about per unit area tree frequency distribution unless one assumes a Poisson (POI) distribution. The POI assumption ignores any relationship between a tree's size and its demand for growing space. This study argues for the Inverse Gaussian (IG) distribution as a more realistic model. Maximum likelihood estimates of the IG parameters are obtained from a transformation of tree size data (diameter) to proxies of tree counts. Data from two stands indicated that an IG model was better at predicting the tree frequency distribution than a POI model.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
