바로가기메뉴

본문 바로가기 주메뉴 바로가기

logo

Search Word: Random forest, Search Result: 2
1
Yong-Su Kwon(Ecobank Team, Division of Ecological Information, National Institute of Ecology) ; Man-Seok Shin(Ecobank Team, Division of Ecological Information, National Institute of Ecology) ; Hee-Nam Yoon(Ecobank Team, Division of Ecological Information, National Institute of Ecology) 2022, Vol.3, No.2, pp.84-96 https://doi.org/10.22920/PNIE.2022.3.2.84
초록보기
Abstract

Most of the islands of Korea are distributed in the South and West Sea, and it consists of independent small stream. As a result, the fish community that inhabits the island's stream is isolated from the mainland and other island. This study utilized a Self-Organizing Map (SOM) and a random forest model to analyze the relationship between environmental variables and fish communities inhabiting islands in South Korea. Through the SOM analysis, the fish communities were divided into three clusters, and there were differences in biotic and abiotic factors between these groups. Cluster I consisted of sites with relatively larger island areas and a higher number of species and population. It was found that 15 out of 16 indicator species were included. Meanwhile, the remaining clusters had fewer species and populations. Cluster II, especially, showed the lowest impact from physical variables such as water width and depth. As a result of predicting the species richness using the random forest model, physical variables in habitats, such as stream width and water depth, had a relatively higher importance on species richness. On the other hand, forest area was the most important variables for predicting Shannon diversity, followed by maximum water depth, and gravel. The results suggest that this study can be used as basic data for establishing a stream ecosystem management strategy in terms of conservation and protection of biological resources in streams of islands.


2
Jeong Soo Park(National Institute of Ecology) ; Donghui Choi(National Institute of Ecology) ; Youngha Kim(National Institute of Ecology) 2020, Vol.1, No.1, pp.74-82 https://doi.org/10.22920/PNIE.2020.1.1.74
초록보기
Abstract

Predictions of suitable habitat areas can provide important information pertaining to the risk assessment and management of alien plants at early stage of their establishment. Here, we predict the invasion potential of Muhlenbergia capillaris (pink muhly) in South Korea using five bioclimatic variables. We adopt four models (generalized linear model, generalized additive model, random forest (RF), and artificial neural network) for projection based on 630 presence and 600 pseudo-absence data points. The RF model yielded the highest performance. The presence probability of M. capillaris was highest within an annual temperature range of 12 to 24°C and with precipitation from 800 to 1,300 mm. The occurrence of M. capillaris was positively associated with the precipitation of the driest quarter. The projection map showed that suitable areas for M. capillaris are mainly concentrated in the southern coastal regions of South Korea, where temperatures and precipitation are higher than in other regions, especially in the winter season. We can conclude that M. capillaris is not considered to be invasive based on a habitat suitability map. However, there is a possibility that rising temperatures and increasing precipitation levels in winter can accelerate the expansion of this plant on the Korean Peninsula.


Proceedings of the National Institute of Ecology of the Republic of Korea