Predicting and assessing the tree species survival and determining Physiographic factors affecting on it in Mazandaran province Forests using artificial neural networks

Document Type : Research Paper

Author

Abstract

Being able to quantify the probability of tree species survival is fundamental to the management of forests worldwide that is very hard. Because there are many processes and factors affecting on it. This paper examines the possible ecological controls probability of tree species survival and quantifying abiotic and biotic variables affecting on it by artificial neural networks in Hyrcanian Forests including growing-season-cumulated potential solar radiation, seasonal air temperature, topographic wetness index in representing soil water distribution, and wind velocity generated from simulation of fluid-flow dynamics in complex terrain. Biotic variables related to tree diameter increment involve averaged 2003 tree diameter and basal area measured in individual forest plots. Allometric equations of logarithmic multiple linear regressions transformed models of power functions which have different parameters were introduced to clarify the certainty of simulating process The predictors used in survival modelling described the influence of tree size, competition and species. The model shows that trees with dbh between 20 and 100 cm survive best. Increasing competition (BAL) decreases survival, and Carpinus betulus has a slightly lower survival rate than the other species. Also, the results of this investigation, it is understood that BAL, topographic wetness index in representing soil water distribution, and wind velocity had the strongest correlation with probability of tree species survival in the fixed sample plots.

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Volume 70, Issue 4
February 2018
Pages 771-782
  • Receive Date: 05 April 2017
  • Revise Date: 07 January 2018
  • Accept Date: 21 October 2017
  • First Publish Date: 22 December 2017