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| Titel |
Inverse method for estimating respiration rates from decay time series |
| VerfasserIn |
D. C. Forney, D. H. Rothman |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
1726-4170
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| Digitales Dokument |
URL |
| Erschienen |
In: Biogeosciences ; 9, no. 9 ; Nr. 9, no. 9 (2012-09-07), S.3601-3612 |
| Datensatznummer |
250007290
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| Publikation (Nr.) |
 copernicus.org/bg-9-3601-2012.pdf |
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| Zusammenfassung |
| Long-term organic matter decomposition experiments typically measure the mass lost from decaying organic matter as a function
of time. These experiments can provide information about the dynamics of carbon dioxide input to the atmosphere and controls
on natural respiration processes. Decay slows down with time, suggesting that organic matter is composed of components (pools)
with varied lability. Yet it is unclear how the appropriate rates, sizes, and number of pools vary with organic matter type,
climate, and ecosystem. To better understand these relations, it is necessary to properly extract the decay rates from
decomposition data. Here we present a regularized inverse method to identify an optimally-fitting distribution of decay rates
associated with a decay time series. We motivate our study by first evaluating a standard, direct inversion of the data. The
direct inversion identifies a discrete distribution of decay rates, where mass is concentrated in just a small number of
discrete pools. It is consistent with identifying the best fitting "multi-pool" model, without prior assumption of the
number of pools. However we find these multi-pool solutions are not robust to noise and are over-parametrized. We therefore
introduce a method of regularized inversion, which identifies the solution which best fits the data but not the noise. This
method shows that the data are described by a continuous distribution of rates, which we find is well approximated by
a lognormal distribution, and consistent with the idea that decomposition results from a continuum of processes at different
rates. The ubiquity of the lognormal distribution suggest that decay may be simply described by just two parameters: a mean
and a variance of log rates. We conclude by describing a procedure that estimates these two lognormal parameters from decay
data. Matlab codes for all numerical methods and procedures are provided. |
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