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Long‐term collar deployment leads to bias in soil respiration measurements

2023; Wiley; Volume: 14; Issue: 3 Linguagem: Inglês

10.1111/2041-210x.14056

2041-210X

Xiaoliang Ma, Shengjing Jiang, Zhi‐Qi Zhang, Hao Wang, Chao Song, Jin He,

Plant Water Relations and Carbon Dynamics

Abstract Accurate measurements of soil respiration ( R s ) are critical for understanding how soil carbon will respond to environmental changes. However, a commonly used method for R s measurements, the collar deployment method, may introduce artefacts that cause bias in R s measurements. Our objective was to quantify the effect of long‐term collar deployment on R s and to unravel potential causes due to changes in the soil environment. A field experiment (2017–2019) including short‐term (2–3 days before the measurement) and long‐term collar deployment (lasting three consecutive growing seasons) was conducted to assess the methodological effect on R s in an alpine grassland of the northeastern Tibetan Plateau. Soil incubation was used to further explore the mechanisms underlying the effects of collar deployment. The effect of long‐term collar deployment on R s varied over time. In the first one and a half growing seasons, no significant difference in R s was noted under short‐ and long‐term collar deployment. This may be attributed to the negative effects of lower root biomass inside long‐term collars and the positive effects of higher temperature and pulse input of dead roots following collar deployment. Under the long‐term collar, R s decreased rapidly in the middle of the second growing season and remained low until the end of the experiment, resulting in an 18.2% decrease relative to short‐term collar deployment in the third growing season. Higher soil bulk density and lower root and microbial biomass inside long‐term collars may explain the decrease in R s and temperature sensitivity ( Q 10 ). Soil incubation experiments revealed that the soil organic carbon (SOC) decomposition rate and Q 10 were significantly reduced after long‐term collar deployment. Long‐term collars led to substantial underestimates of R s after more than 2 years. Our findings suggest that such potential artefacts should be considered when interpreting R s data based on long‐term collar deployment. Long‐term collars should be relocated every 1–2 years to avoid artefacts if feasible. Alternatively, periodic measurements using short‐term collars are recommended to quantify the magnitude of collar artefacts.