Projection Matrix Models: A Suitable Approach for Predicting Sustainable Growth in Uneven-Aged and Mixed Hyrcanian Forests

Abstract

The Hyrcanian forests of Iran are mainly managed with the single-selection silvicultural technique. Despite significant ecological benefits associated with selection cutting, this type of forest management leads towards more challenging situations where it is difficult to maintain and practice successful forestry than in even-aged systems. Therefore, this study provides relevant management tools in the form of models to estimate low growth levels in Hyrcanian forests. In the present study, estimation of the population growth rate and then the allowable cut rate of these forests using a matrix model have been calculated in the Gorazbon district. For this purpose, the data of 256 permanent sample plots measured during the years between 2003 and 2012, as well as the data recorded about the trees harvested according to the forestry plan, have been used. As a first step, the most frequently occurring tree species were divided into four groups (beech, hornbeam, chestnut-leaved oak, and other species). Compartments of the district were divided into two groups of logged and unlogged compartments. The purpose of this division was to estimate the allowable cut and compare its volume with the volumes of observed and predicted allowable cuts obtained from forestry plans. The results showed that the total operated allowable cut (OAC) in logged compartments was more than the estimated allowable cut (EAC). In unlogged compartments, the total predicted allowable cut (PAC) was more than EAC. A comparison of EAC and OAC showed that hornbeam has been harvested more than its potential. However, chestnut-leaved oak and other species group have depicted opposite trends. Our models provide important advancements for estimating allowable cut that can enhance the goal of practicing sustainable forestry.

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Citation

Salehnasab, A.; Burkhart, H.E.; Bayat, M.; Khaleghi, B.; Heidari, S.; Masood Awan, H.U. Projection Matrix Models: A Suitable Approach for Predicting Sustainable Growth in Uneven-Aged and Mixed Hyrcanian Forests. Sustainability 2022, 14, 6777.