Climatic Change

, Volume 119, Issue 2, pp 421–434 | Cite as

Temperature change and macroinvertebrate biodiversity: assessments of organism vulnerability and potential distributions

  • Fengqing Li
  • Namil Chung
  • Mi-Jung Bae
  • Yong-Su Kwon
  • Tae-Sung Kwon
  • Young-Seuk Park


Peninsular environments are ecosystems that are one of the most vulnerable to global warming. Despite the importance of conserving regional biodiversity, peninsular environments are among the least studied with respect to the influences of global warming. In this study, we used data on benthic macroinvertebrate communities from 521 sites across Korea (a nationwide scale) to evaluate the potential impact of temperature increases on river ecosystems. Weighted averaging regression models (WARMs) were used to project the relationships between relative macroinvertebrate abundance and water temperature, based on the temperature data of the Intergovernmental Panel on Climate Change (IPCC) A1B scenario. Maximum tolerance water temperatures were used to quantify the risks to macroinvertebrates at the catchment and national scales. Ambient air temperatures in the 2090s were projected to increase by an average of 3.4 ºC relative to the baseline of the 2000s at the national scale. Mayflies, stoneflies and caddisflies were identified as potentially the most sensitive taxa to global warming. The impact of global warming on macroinvertebrates was predicted to be minimal prior to the 2060s; however, by the 2080s, species loss was predicted to be 55 %. Potential distribution ranges of cold water species in the future decades were expected to decrease continuously over time, while those of warm species were expected to increase from the 2000s to the 2040s and then decrease until the 2080s. Our projections may be useful for understanding how climate parameters affect the biogeographical patterns of aquatic biodiversity from a thermal-preference perspective.


Global Warming Korean Peninsula National Scale Benthic Macroinvertebrates Warm Water Species 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korean government (MEST) (No. 2010-0027360).


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Copyright information

© Springer Science+Business Media Dordrecht 2013

Authors and Affiliations

  • Fengqing Li
    • 1
  • Namil Chung
    • 1
  • Mi-Jung Bae
    • 1
  • Yong-Su Kwon
    • 1
  • Tae-Sung Kwon
    • 2
  • Young-Seuk Park
    • 1
  1. 1.Department of Biology and The Korea Institute of OrnithologyKyung Hee UniversitySeoulRepublic of Korea
  2. 2.Division of Forest EcologyKorea Forest Research InstituteSeoulRepublic of Korea

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