Acorn number modeling of Brant`s oak (Quercus brantii Lindl.) in Zagros forests in support of seed trees conservation

Document Type : Research Paper

Authors

1 Research Institute of Forests and Rangelands, Agricultural Research, Education and Extension Organization (AREEO), Tehran, Iran

2 Fars Agricultural and Natural Resources Research and Education Center, AREEO, Shiraz, Iran

3 Kermanshah Agricultural and Natural Resources Research and Education Center, AREEO, Kermanshah, Iran

Abstract

The increasing degradation of Zagros forests has affected the potential of acorn production of different oak species. There is concern that continuing of this process will destroy the valuable individuals of oaks. Unfortunately, there is no adequate information about acorn productions of Zagros native oaks because of the measurement difficulties. In this research, Koenig method as one of the most common and accurate visual survey techniques, was evaluated on Brant`s oak (Quercus brantii Lindl.) trees in forests of Dasht-e Arjan, Fars province, and Darbadam, Kermanshah province during 2009 to 2011. The aim of the research was to test the Koenig method for native oaks of Iran and to present the best regression model for estimation of acorn number of Brant`s oaks in the studied areas. Forty sample trees were selected in each study area using stratified random sampling method. For each tree, all of acorns were counted with two methods of crown counting and Koenig visual estimation method. The same procedure was used for acorn counting in the other studied years. Based on the results, the values of R2 and RMSE for estimated simple linear regression were 0.68 and 0.292 for Dasht-e Arjan, while the values of R2 and RMSE were 0.82 and 0.230 in Darbadam. Totally, efficiency of Koenig method was confirmed. This method is applicable for an easy estimation of acorn number of other Brant`s oak trees in the studied forests in the  following years thus, enhancing the ability for easily identifying seed and valuable oak trees.

Keywords

References

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History

  • Receive Date: 13 November 2016
  • Revise Date: 28 February 2017
  • Accept Date: 10 March 2017

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