Reduction of uncertainty in projection of growth and yield of Hyrcanian trees in Jabowa-۴ model by applying artificial neural network (Case study: kheyroud forest- Nowshahr)
Publish place: Central Asian Journal of Environmental Science and Technology Innovation، Vol: 2، Issue: 3
Publish Year: 1400
نوع سند: مقاله ژورنالی
زبان: English
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JR_CAS-2-3_004
تاریخ نمایه سازی: 16 مرداد 1400
Abstract:
Gap models have a long history in assessing the potential effects of climate change on forest structure and composition. In Hyrcanian forests, there is a lack of efficient models for predicting growth and yield. Therefore, to fill this gap in this study, we tried to use the Jabowa-۴ model, which has the ability to predict forest dynamics by considering climatic factors. To apply the model in Hyrcanian forests, the main species selected and parameterized in different modes using experimental models. After the simulation process over ۹۰ years, the values related to the observed and predicted BA, correlation coefficient and RMSE calculated and the species response to climate change evaluated. The results of this simulation show that climate change can have a negative impact on growth and yield by reducing rainfall and creating drought conditions in the studied forests. Due to these changes, the percentage of more resistant speciessuch as Oak increases.On the other hand, the results of this study showed that Jabowa-۴ is effective in providing forest performance predictions. However, it has a weak ability to explain the amount and height of trees in Hyrcanian forests.Keywords: Climate change, Forest dynamics, Forest management, Growth and yield model,
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Authors
Shirin Varkouhi
Department of Forestry and Forest Economics, Faculty of Natural Resources, University of Tehran, Karaj, Iran
Manoochehr Namiranian
Department of Forestry and Forest Economics, Faculty of Natural Resources, University of Tehran, Karaj, Iran
Pedram Atarod
Department of Forestry and Forest Economics, Faculty of Natural Resources, University of Tehran, Karaj, Iran
Mahmood Omid
Department of Agricultural Machinery Engineering, College of Agriculture & Natural Resources, University of Tehran, Karaj, Iran
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