Do inverse ecosystem models accurately reconstruct plankton trophic flows? Comparing two solution methods using field data from the California Current

Despite the increasing use of linear inverse modeling techniques to elucidate fluxes in undersampled marine ecosystems, the accuracy with which they estimate food web flows has not been resolved. New Markov Chain Monte Carlo (MCMC) solution methods have also called into question the biases of the co...

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Veröffentlicht in:Journal of marine systems 2012-03, Vol.91 (1), p.20-33
Hauptverfasser: Stukel, Michael R., Landry, Michael R., Ohman, Mark D., Goericke, Ralf, Samo, Ty, Benitez-Nelson, Claudia R.
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Sprache:eng
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Zusammenfassung:Despite the increasing use of linear inverse modeling techniques to elucidate fluxes in undersampled marine ecosystems, the accuracy with which they estimate food web flows has not been resolved. New Markov Chain Monte Carlo (MCMC) solution methods have also called into question the biases of the commonly used L 2 minimum norm (L 2MN) solution technique. Here, we test the abilities of MCMC and L 2MN methods to recover field-measured ecosystem rates that are sequentially excluded from the model input. For data, we use experimental measurements from process cruises of the California Current Ecosystem (CCE-LTER) Program that include rate estimates of phytoplankton and bacterial production, micro- and mesozooplankton grazing, and carbon export from eight study sites varying from rich coastal upwelling to offshore oligotrophic conditions. Both the MCMC and L 2MN methods predicted well-constrained rates of protozoan and mesozooplankton grazing with reasonable accuracy, but the MCMC method overestimated primary production. The MCMC method more accurately predicted the poorly constrained rate of vertical carbon export than the L 2MN method, which consistently overestimated export. Results involving DOC and bacterial production were equivocal. Overall, when primary production is provided as model input, the MCMC method gives a robust depiction of ecosystem processes. Uncertainty in inverse ecosystem models is large and arises primarily from solution under-determinacy. We thus suggest that experimental programs focusing on food web fluxes expand the range of experimental measurements to include the nature and fate of detrital pools, which play large roles in the model. ► Compared 2 inverse ecosystem methods ( L 2 min norm and Markov Chain Monte Carlo). ► L 2MN more accurately predicted primary production when it was not a model input. ► MCMC more accurately predicted vertical carbon export and ecosystem properties. ► Uncertainty due to under-determinacy was high (C.V. > 0.5) for most trophic flows.
ISSN:0924-7963
1879-1573
DOI:10.1016/j.jmarsys.2011.09.004