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

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BAYAT MAHMMOD; SHEKARCHIAN ARSALAN; OMID MAHMOUD

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Journal: Journal of Natural Environment Year:2018 | Volume:70 | Issue:4 Page(s): 771-782

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Information Journal Paper

Title

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

Author(s)

BAYAT MAHMMOD | SHEKARCHIAN ARSALAN | OMID MAHMOUD | Issue Writer Certificate

Keywords

Artificial neural networksQ1

Physiographic factorsQ1

Hyrcanian ForestsQ1

survivalQ1

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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APA: Copy

BAYAT, MAHMMOD, SHEKARCHIAN, ARSALAN, & OMID, MAHMOUD. (2018). Predicting and assessing the tree species survival and determining Physiographic factors affecting on it in Mazandaran province Forests using artificial neural networks. JOURNAL OF NATURAL ENVIRONMENT (IRANIAN JOURNAL OF NATURAL RESOURCES), 70(4 ), 771-782. SID. https://sid.ir/paper/195004/en

Vancouver: Copy

BAYAT MAHMMOD, SHEKARCHIAN ARSALAN, OMID MAHMOUD. Predicting and assessing the tree species survival and determining Physiographic factors affecting on it in Mazandaran province Forests using artificial neural networks. JOURNAL OF NATURAL ENVIRONMENT (IRANIAN JOURNAL OF NATURAL RESOURCES)[Internet]. 2018;70(4 ):771-782. Available from: https://sid.ir/paper/195004/en

IEEE: Copy

MAHMMOD BAYAT, ARSALAN SHEKARCHIAN, and MAHMOUD OMID, “Predicting and assessing the tree species survival and determining Physiographic factors affecting on it in Mazandaran province Forests using artificial neural networks,” JOURNAL OF NATURAL ENVIRONMENT (IRANIAN JOURNAL OF NATURAL RESOURCES), vol. 70, no. 4 , pp. 771–782, 2018, [Online]. Available: https://sid.ir/paper/195004/en

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