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Temperature Sensitivity of Soil Respiration Probed by Numerical Analysis of Field-Observed Data Sets

Temperature Sensitivity of Soil Respiration Probed by Numerical Analysis of Field-Observed Data Sets
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摘要 Temperature sensitivity of soil respiration is essential to predict possible changes in terrestrial carbon budget on various scenarios about atmospheric and soil climates. Although it is often evaluated by using respiratory quotient “Q<sub>10</sub>”, Q<sub>10</sub> values of soil respiration seem to vary depending on methods or scales of evaluation. Aiming at probing how Q<sub>10</sub> values of soil respiration are evaluated differently for a field, this study used a model of soil respiration rate, and numerically evaluated soil respiration rates along depth by fitting the model to depth distributions of CO<sub>2</sub> concentration measured in a field. And temperature sensitivity of soil respiration rate was evaluated by comparing the determined soil respiration rates with atmospheric and soil temperatures measured in the field. The results showed that the relation between surface CO<sub>2</sub> emission rates and atmospheric temperatures was represented by lower Q<sub>10</sub> values than that between soil respiration rates and soil temperatures, presumably because the top soil layers had acclimatized in more extent to the existing thermal regime than the underlying deeper layers. Thus, for evaluating effects of long-term rise in atmospheric temperature on soil respiration, it is necessary to precisely predict the long-term change in depth distribution of soil temperature as well as to quantify temperature sensitivity of soil respiration along depth. The evaluated sensitivity of surface CO<sub>2</sub> emission rate to atmospheric temperature showed hysteresis, implying the needs for more knowledge about temperature sensitivity of soil respiration evaluated in both warming and cooling processes for better understandings and predictions about terrestrial carbon cycling. Temperature sensitivity of soil respiration is essential to predict possible changes in terrestrial carbon budget on various scenarios about atmospheric and soil climates. Although it is often evaluated by using respiratory quotient “Q<sub>10</sub>”, Q<sub>10</sub> values of soil respiration seem to vary depending on methods or scales of evaluation. Aiming at probing how Q<sub>10</sub> values of soil respiration are evaluated differently for a field, this study used a model of soil respiration rate, and numerically evaluated soil respiration rates along depth by fitting the model to depth distributions of CO<sub>2</sub> concentration measured in a field. And temperature sensitivity of soil respiration rate was evaluated by comparing the determined soil respiration rates with atmospheric and soil temperatures measured in the field. The results showed that the relation between surface CO<sub>2</sub> emission rates and atmospheric temperatures was represented by lower Q<sub>10</sub> values than that between soil respiration rates and soil temperatures, presumably because the top soil layers had acclimatized in more extent to the existing thermal regime than the underlying deeper layers. Thus, for evaluating effects of long-term rise in atmospheric temperature on soil respiration, it is necessary to precisely predict the long-term change in depth distribution of soil temperature as well as to quantify temperature sensitivity of soil respiration along depth. The evaluated sensitivity of surface CO<sub>2</sub> emission rate to atmospheric temperature showed hysteresis, implying the needs for more knowledge about temperature sensitivity of soil respiration evaluated in both warming and cooling processes for better understandings and predictions about terrestrial carbon cycling.
作者 Ippei Iiyama Ippei Iiyama(School of Agriculture, Utsunomiya University, Utsunomiya, Tochigi, Japan)
机构地区 School of Agriculture
出处 《Journal of Geoscience and Environment Protection》 2023年第8期65-84,共34页 地球科学和环境保护期刊(英文)
关键词 Air-Filled Porosity Inverse Analysis Mass Balance Potentially Maximum CO2 Production Rate Soil Gas Diffusion Water Content Air-Filled Porosity Inverse Analysis Mass Balance Potentially Maximum CO2 Production Rate Soil Gas Diffusion Water Content
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