Accounting for unresolved spatial variability in marine ecosystems using time lags
Accounting for unresolved spatial variability in marine ecosystems using time lags
The formulation and calibration of models is a vital method for probing and predicting the behavior of marine ecosystems. The ability to do this may suffer, however, if the calibrating data set is subject to significant spatial variability between samples that is not resolved in the model. We propose that some of this variability might be accounted for by variable time lags between sampled water masses which are otherwise assumed to follow a common pattern of ecosystem variability (dynamical trajectory). Using twin tests of fitting models to simulated data sets, we show that realistic levels of meso/sub-mesoscale variability in time lags may have significant distortion effects on the parameter fits from standard methods which do not account for it. The distortion is such as to 'smooth out' or underestimate the magnitude of temporal variability within sampled water masses, causing loss of accuracy and robustness of biological parameter estimates and functions thereof (e.g. gross primary production). A new method of model fitting is shown to avoid these effects, allowing improved estimates over a broad range of spatial time lag variability and measurement noise levels, assuming accurate estimation of the time lag variance, for which we also suggest a method.
881-914
Wallhead, P.
aba177b0-4a27-450e-bf5c-3d7dc3b4dd6c
Martin, A.P.
9d0d480d-9b3c-44c2-aafe-bb980ed98a6d
Srokosz, M.A.
1e0442ce-679f-43f2-8fe4-9a0f0174d483
Fasham, M.J.R.
7fb86485-8cfc-4199-bde4-2276abefdf2e
2006
Wallhead, P.
aba177b0-4a27-450e-bf5c-3d7dc3b4dd6c
Martin, A.P.
9d0d480d-9b3c-44c2-aafe-bb980ed98a6d
Srokosz, M.A.
1e0442ce-679f-43f2-8fe4-9a0f0174d483
Fasham, M.J.R.
7fb86485-8cfc-4199-bde4-2276abefdf2e
Wallhead, P., Martin, A.P., Srokosz, M.A. and Fasham, M.J.R.
(2006)
Accounting for unresolved spatial variability in marine ecosystems using time lags.
Journal of Marine Research, 64 (6), .
(doi:10.1357/002224006779698387).
Abstract
The formulation and calibration of models is a vital method for probing and predicting the behavior of marine ecosystems. The ability to do this may suffer, however, if the calibrating data set is subject to significant spatial variability between samples that is not resolved in the model. We propose that some of this variability might be accounted for by variable time lags between sampled water masses which are otherwise assumed to follow a common pattern of ecosystem variability (dynamical trajectory). Using twin tests of fitting models to simulated data sets, we show that realistic levels of meso/sub-mesoscale variability in time lags may have significant distortion effects on the parameter fits from standard methods which do not account for it. The distortion is such as to 'smooth out' or underestimate the magnitude of temporal variability within sampled water masses, causing loss of accuracy and robustness of biological parameter estimates and functions thereof (e.g. gross primary production). A new method of model fitting is shown to avoid these effects, allowing improved estimates over a broad range of spatial time lag variability and measurement noise levels, assuming accurate estimation of the time lag variance, for which we also suggest a method.
This record has no associated files available for download.
More information
Published date: 2006
Identifiers
Local EPrints ID: 42153
URI: http://eprints.soton.ac.uk/id/eprint/42153
ISSN: 0022-2402
PURE UUID: 541309b5-78d0-4a44-a785-5b6d1f4524b1
Catalogue record
Date deposited: 17 Nov 2006
Last modified: 15 Mar 2024 08:45
Export record
Altmetrics
Contributors
Author:
P. Wallhead
Author:
A.P. Martin
Author:
M.A. Srokosz
Author:
M.J.R. Fasham
Download statistics
Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.
View more statistics