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

Author

Listed:
  • Abotaleb Salehnasab

    (Department of Forestry and Forest Economics, University of Tehran, Karaj P.O. Box 6619-14155, Iran)

  • Harold E. Burkhart

    (Department of Forest Resources and Environmental Conservation, Virginia Polytechnic Institute and State University, 319 Cheatham Hall, 310 West Campus Drive, Blacksburg, VA 24061, USA)

  • Mahmoud Bayat

    (Research Institute of Forests and Rangelands, Agricultural Research, Education, and Extension Organization (AREEO), Tehran P.O. Box 14968-1311, Iran)

  • Bagher Khaleghi

    (Department of Forestry and Forest Economics, University of Tehran, Karaj P.O. Box 6619-14155, Iran)

  • Sahar Heidari

    (Department of Environment, University of Tehran, Karaj P.O. Box 6619-14155, Iran)

  • Hafiz Umair Masood Awan

    (Helclean Consultancy Services, Asiakkaankatu 6B 29, 00930 Helsinki, Finland
    Faculty of Agriculture and Forestry, University of Helsinki, Latokartanonkaari 7, 00014 Helsinki, Finland)

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.

Suggested Citation

  • Abotaleb Salehnasab & Harold E. Burkhart & Mahmoud Bayat & Bagher Khaleghi & Sahar Heidari & Hafiz Umair Masood Awan, 2022. "Projection Matrix Models: A Suitable Approach for Predicting Sustainable Growth in Uneven-Aged and Mixed Hyrcanian Forests," Sustainability, MDPI, vol. 14(11), pages 1-17, June.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:11:p:6777-:d:829793
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    References listed on IDEAS

    as
    1. Ghajar, Ismael & Najafi, Akbar, 2012. "Evaluation of harvesting methods for Sustainable Forest Management (SFM) using the Analytical Network Process (ANP)," Forest Policy and Economics, Elsevier, vol. 21(C), pages 81-91.
    2. Liang, Jingjing & Zhou, Mo, 2010. "A geospatial model of forest dynamics with controlled trend surface," Ecological Modelling, Elsevier, vol. 221(19), pages 2339-2352.
    3. Picard, Nicolas & Bar-Hen, Avner & Gourlet-Fleury, Sylvie, 2007. "Estimator of upgrowth transition rates for size-classified matrix from small samples," Ecological Modelling, Elsevier, vol. 204(1), pages 59-69.
    4. López Torres, I. & Fullana Belda, C. & Ortuño Pérez, S.F. & Martín Fernández, A.J., 2008. "Choosing Fagus sylvatica L. matrix model dimension by sensitivity analysis of the population growth rate with respect to the width of the diameter classes," Ecological Modelling, Elsevier, vol. 218(3), pages 307-314.
    5. Abotaleb Salehnasab & Mahmoud Bayat & Manouchehr Namiranian & Bagher Khaleghi & Mahmoud Omid & Hafiz Umair Masood Awan & Nadir Al-Ansari & Abolfazl Jaafari, 2022. "Machine Learning for the Estimation of Diameter Increment in Mixed and Uneven-Aged Forests," Sustainability, MDPI, vol. 14(6), pages 1-17, March.
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