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MOSES – A tree growth simulator for modelling stand response in Central Europe

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  • Thurnher, Christopher
  • Klopf, Mario
  • Hasenauer, Hubert

Abstract

Moses (MOdelling Stand rESponse) is a distance and potential-dependent single-tree growth simulator. It consists of a diameter and height increment model, a dynamic crown model and models that calculate mortality and regeneration. It was originally calibrated for spruce, beech and pine forests in Austria and has been recalibrated several times throughout the years. In this study, we recalibrated and validated the increment models and the mortality model within MOSES using the latest large and holistic dataset based on monitoring and permanent inventory plots for seven of the most common tree species in Europe (five for the mortality model). These plots were mainly from Austria and Switzerland, as well as Germany. In addition, we calibrated sets of coefficients for the “species groups” (i) other broadleaf and (ii) other conifer trees. The total dataset comprises 278,979 repeated tree measurements, 56,312 of them were used for calibration and 222,667 for validation. The validation of the newly parameterized growth and mortality models exhibit consistent and unbiased estimates for tree growth in central European forests using the MOSES simulator.

Suggested Citation

  • Thurnher, Christopher & Klopf, Mario & Hasenauer, Hubert, 2017. "MOSES – A tree growth simulator for modelling stand response in Central Europe," Ecological Modelling, Elsevier, vol. 352(C), pages 58-76.
    • Handle: RePEc:eee:ecomod:v:352:y:2017:i:c:p:58-76
    DOI: 10.1016/j.ecolmodel.2017.01.013
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    References listed on IDEAS

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    1. Young, Derek S., 2010. "tolerance: An R Package for Estimating Tolerance Intervals," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 36(i05).
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    1. Hanyue Zhang & Zhongke Feng & Shan Wang & Wenxu Ji, 2022. "Disentangling the Factors That Contribute to the Growth of Betula spp. and Cunninghami lanceolata in China Based on Machine Learning Algorithms," Sustainability, MDPI, vol. 14(14), pages 1-15, July.

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