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Reconciling 14C and minirhizotron-based estimates of fine-root turnover with survival functions

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Ahrens,  Bernhard
Soil Processes, Dr. Marion Schrumpf, Department Biogeochemical Integration, Dr. M. Reichstein, Max Planck Institute for Biogeochemistry, Max Planck Society;

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Reichstein,  Markus
Department Biogeochemical Integration, Dr. M. Reichstein, Max Planck Institute for Biogeochemistry, Max Planck Society;

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Citation

Ahrens, B., & Reichstein, M. (2014). Reconciling 14C and minirhizotron-based estimates of fine-root turnover with survival functions. Journal of Plant Nutrition and Soil Science, 177(2), 287-296. doi:10.1002/jpln.201300110.


Cite as: https://hdl.handle.net/11858/00-001M-0000-0014-723C-0
Abstract
The turnover of fine-roots is a crucial component for the input of carbon to the soil. The amount of root litter input is depending on estimates of turnover times from different techniques. Turnover times from fine-root cameras (minirhizotrons) often yield 75% higher root litter input estimates than turnover times estimated with the bomb-radiocarbon signature of fine-roots. We introduce a generic framework for the analysis of fine-root 14C with different survival functions. So far, mostly an exponential function has been used to estimate the turnover time and mean age of fine-roots. In the context of the introduced survival function framework we clarify the terms turnover time, mean residence time, mean longevity and mean age commonly used in studies of root turnover. Using a unique time series of fine-root 14C (Fröberg 2012), we test if survival functions other than the exponential function are better in accordance with turnover time estimates commonly found with other methods. A survival function that corresponds to a two-pool model was best in agreement with minirhizotron-based estimates (mean residence time of 1.9 years). We argue that using fine-root 14C and minirhizotron time-to-death data together would give the best constraints on fine-root turnover. At the same time this could allow quantifying systematic biases inherent two both techniques.