Modeling the effect of FWD on plant species richness using BRT

Articles in Press

Document Type : Scientific article

Authors

1 golestan agricultural and natural resources research and education center

2 Mazandaran Agricultural and Natural Resources Research and Education Center, Agricultural Research Education & Extension Organization (AREEO). P.O. Box: 48175-556, Sari, Iran.

Abstract

Plant Species Richness (PSR) plays an important role in forest ecosystem functions and services. Fine Woody Debris (FWD) is a component of natural forests, with an important function in plant understory richness with the enhanced function of newly developing microhabitats. Therefore, Boosted Regression Tree (BRT) machine learning technique was used to model the PSR in an unmanaged forest stands the east Golestan province, Iran. For this purpose, 30 sample plots (400 m2) were set, and the number of plant species in each sample plot was used as species richness. The characteristics of the FWD crossed with the perimeter of the sample plot were measured. To measure the percentage of soil moisture and organic matter, the soil was taken from the center of each soil sample to a depth of 15 cm. Based on the final model of the BRT, the highest amount of species richness was recorded with the increase of soil organic matter to > 2.15% and in a soil moisture percentage >30%. Furtheremore, a high amount of FWD from the first diameter class and with the decay class 2 (rotten) led to an increase in plant richness in the studied area. In the present study, the adjusted R squared > 0.99 with the Root Mean Square Error (RMSE) < 0.039 shows the high accuracy of the BRT model. These findings show that the FWD increases the plant richness by creating favorable habitat conditions and maintaining this component is important in improving the organic matter of the forest soil.

Keywords

Main Subjects

Forest Research and Development

Articles in Press, Accepted Manuscript
Available Online from 13 April 2024

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