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Potential climate change effects on tree distributions in the Korean Peninsula: Understanding model & climate uncertainties

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  • Koo, Kyung Ah
  • Park, Seon Uk
  • Kong, Woo-Seok
  • Hong, Seungbum
  • Jang, Inyoung
  • Seo, Changwan

Abstract

The projections of species distribution models (SDMs) have provided critical knowledge for conservation planning under climate change in the Republic of Korea. However, uncertainty about the SDM projections has been criticized as a major challenge to reliable projections. The present research investigated uncertainty among competing models (Model uncertainty) and uncertainty of future climate conditions (climate uncertainty) driving from different GCMs and CO2 emission scenarios in predicting the future distributions of plants. For this purpose, using nine single-model algorithms and the pre-evaluation weighted ensemble method, we modeled the geographical distributions of Silver Magnolia (Machilus thunbergii Siebold & Zucc.), a warm-adapted evergreen broadleaved tree; furthermore, we predicted its future distributions under 20 climate change scenarios (5 global circulation models (GCMs)×4 CO2 emission scenarios (RCPs)). The results showed a great variation in the accuracies of nine single-model projections: the mean AUC values of nine single-models ranged from 0.764 (SER) to 0.970 (RF), and the mean TSS ranged from 0.529 (SRE) to 0.852 (RF). RF (mean AUC=0.970, mean TSS=0.852) and the ensemble forecast (AUC=0.968, TSS=0.804) showed the highest predictive power, while SRE showed the lowest. The future distributions of Silver Magnolia projected with the ensemble SDM clearly varied according to GCMs and RCPs. The twenty climate scenarios produced twenty different projections of the magnolia prospective distribution. GCMs commonly projected the maximum range expansion under RCP 8.5 in 2050 and 2070, but CO2 emission scenarios explaining the minimum expansions differed according to GCMs. In conclusion, our results show that GCMs, CO2 emission scenarios and SDM algorithms produce considerable variations in the SDM projections. Therefore, this research suggests that understanding of model and climate uncertainties is critical for an effective conservation planning in forest management under climate change on the Korean Peninsula.

Suggested Citation

  • Koo, Kyung Ah & Park, Seon Uk & Kong, Woo-Seok & Hong, Seungbum & Jang, Inyoung & Seo, Changwan, 2017. "Potential climate change effects on tree distributions in the Korean Peninsula: Understanding model & climate uncertainties," Ecological Modelling, Elsevier, vol. 353(C), pages 17-27.
    • Handle: RePEc:eee:ecomod:v:353:y:2017:i:c:p:17-27
    DOI: 10.1016/j.ecolmodel.2016.10.007
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    Cited by:

    1. Pecchi, Matteo & Marchi, Maurizio & Burton, Vanessa & Giannetti, Francesca & Moriondo, Marco & Bernetti, Iacopo & Bindi, Marco & Chirici, Gherardo, 2019. "Species distribution modelling to support forest management. A literature review," Ecological Modelling, Elsevier, vol. 411(C).
    2. Seungbum Hong & Inyoung Jang & Daegeun Kim & Suhwan Kim & Hyun Su Park & Kyungeun Lee, 2022. "Predicting Potential Habitat Changes of Two Invasive Alien Fish Species with Climate Change at a Regional Scale," Sustainability, MDPI, vol. 14(10), pages 1-12, May.
    3. Jia-Min Jiang & Lei Jin & Lei Huang & Wen-Ting Wang, 2022. "The Future Climate under Different CO 2 Emission Scenarios Significantly Influences the Potential Distribution of Achnatherum inebrians in China," Sustainability, MDPI, vol. 14(8), pages 1-15, April.
    4. Xumin Li & Zhiwen Yao & Qing Yuan & Rui Xing & Yuqin Guo & Dejun Zhang & Israr Ahmad & Wenhui Liu & Hairui Liu, 2023. "Prediction of Potential Distribution Area of Two Parapatric Species in Triosteum under Climate Change," Sustainability, MDPI, vol. 15(6), pages 1-23, March.

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