2018
DOI: 10.1186/s41610-018-0095-y
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Potential impact of climate change on the species richness of subalpine plant species in the mountain national parks of South Korea

Abstract: Background: Subalpine ecosystems at high altitudes and latitudes are particularly sensitive to climate change. In South Korea, the prediction of the species richness of subalpine plant species under future climate change is not well studied. Thus, this study aims to assess the potential impact of climate change on species richness of subalpine plant species (14 species) in the 17 mountain national parks (MNPs) of South Korea under climate change scenarios' representative concentration pathways (RCP) 4.5 and RC… Show more

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Cited by 34 publications
(32 citation statements)
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“…The current climate conditions were determined by averaging the data from 1950 to 2000. Similarly, the future climate conditions in 2050 and 2070 were estimated from the period of 2046 to 2055 and 2066 to 2075, respectively, similar to Adhikari et al (2018). In all climatic data, the spatial resolution was 0.01°(36 s) and approximately 1 km 2 .…”
Section: Environmental Variablesmentioning
confidence: 93%
“…The current climate conditions were determined by averaging the data from 1950 to 2000. Similarly, the future climate conditions in 2050 and 2070 were estimated from the period of 2046 to 2055 and 2066 to 2075, respectively, similar to Adhikari et al (2018). In all climatic data, the spatial resolution was 0.01°(36 s) and approximately 1 km 2 .…”
Section: Environmental Variablesmentioning
confidence: 93%
“…Because dispersal is included here as a constraining factor for future species distributions, the bioclimatic data were interpolated by decade to provide frequent steps to include dispersal limitations (Engler et al , 2012). To do so, simple linear regressions were used to obtain for each bioclimatic variable the 2010, 2020, 2030 and 2040 values using a coefficient calculated for the 2000–2050 period following a similar procedure to the one employed by Adhikari et al (2018). The same procedure was applied for 2060 based on the 2050–2070 period, and for decades 2080, 2090 and 2100, values were obtained by extrapolating the 2050–2070 regression coefficient into the future.…”
Section: Methodsmentioning
confidence: 99%
“…Islam et al (2021) showed positive relation of TBI1 with NDVI of Bangladesh. Adhikari et al (2018) showed that TBI1 determines the species richness in the mountainous region of South Korea. Sosa and Loera (2017) found the highest positive correlation of TBI1 with species richness in Mesoamerica among all other indicators.…”
Section: Annual Average Temperature (Tbi1)mentioning
confidence: 99%