Unraveling the response of the apparent temperature sensitivity of ecosystem respiration to rising temperature
Global warming is expected to intensify carbon loss, as ecosystem respiration (RECO) rates increase exponentially with rising temperatures. However, a comprehensive analysis of the response of the apparent temperature sensitivity of RECO ( ${Q_{10}}$ ) to rising temperature is lacking. This study le...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
IOP Publishing
2025-01-01
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| Series: | Environmental Research Letters |
| Subjects: | |
| Online Access: | https://doi.org/10.1088/1748-9326/adad00 |
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| Summary: | Global warming is expected to intensify carbon loss, as ecosystem respiration (RECO) rates increase exponentially with rising temperatures. However, a comprehensive analysis of the response of the apparent temperature sensitivity of RECO ( ${Q_{10}}$ ) to rising temperature is lacking. This study leverages observational data from 254 sites from the FLUXNET2015 and AmeriFlux datasets to address this knowledge gap. We found a strong influence of non-temperature factors on the seasonality of RECO. The similar seasonality of this effect and temperature can lead to underestimating or overestimating ${Q_{10}}$ . In this study, ${Q_{10}}$ was quantified using a temporal moving window and a linear-mixed effect model to account for the effects of non-temperature factors on RECO. Our results show that ${Q_{10}}$ decreases from 1.55 ± 0.24 (mean ± one standard error) at 5 °C to 1.35 ± 0.18 at 25 °C over all sites. The mean slope of ${Q_{10}}$ to temperature across all sites is about −0.02 °C ^−1 . In this study, we found lower values of Q _10 and a lower decreasing rate of Q _10 with rising temperature compared to previous studies. Our study suggests that ${Q_{10}}$ might be systematically overestimated due to the confounding effect of non-temperature factors, potentially leading to overestimated simulation of RECO rate. Our study also emphasizes the necessity of developing a process-based model, rather than simply incorporating the influences of non-temperature factors into ${Q_{10}}$ . |
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| ISSN: | 1748-9326 |