Abstract
Freshwater insects are sensitive indicators of climate change, yet long-term, multi-species analyses remain limited. This study investigated altitudinal distribution shifts of three Korean mayflies (Ephemera separigata, E. strigata, E. orientalis) using 27 years of nationwide biomonitoring (1997–2023) across 4741 georeferenced sites. Average temperature (AT), total precipitation (P), and precipitation variability (PV) were assigned to occurrence records by region and year. Multiple linear regression (MLR) was applied to assess linear relationships between climatic variables and altitude, while random forest (RF) models captured nonlinear effects and evaluated variable importance. All three species exhibited significant downslope shifts, with E. separigata showing the greatest decline (−173.9 m). MLR models had low explanatory power (R2 = 0.037–0.150), identifying PV as significant for E. separigata and E. orientalis (p < 0.05). RF models provided improved explanatory power (R2 = 0.297–0.412) and revealed that precipitation-related variables (P or PV) were generally the most influential, though the leading predictor differed among species. Notably, Phase 5 coincided with a marked increase in PV, aligning with the most pronounced downslope shifts. These results suggest that PV destabilizes headwater habitats and promotes persistence in lower, hydrologically stable reaches. Our findings highlight the importance of hydrological variability, alongside temperature, in predicting climate-driven range shifts and refining bioindicator-based conservation strategies for freshwater ecosystems.
| Original language | English |
|---|---|
| Article number | 102490 |
| Journal | Journal of Asia-Pacific Entomology |
| Volume | 28 |
| Issue number | 4 |
| DOIs | |
| Publication status | Published - 2025 Dec |
Bibliographical note
Publisher Copyright:© 2025 Korean Society of Applied Entomology
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 13 Climate Action
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SDG 15 Life on Land
Keywords
- Altitudinal shift
- Climate change
- Long-term ecological monitoring
- Machine learning
- Precipitation variability
- Stream insects
ASJC Scopus subject areas
- Insect Science
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