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Articles by Thomas R. Anderson
Total Records ( 5 ) for Thomas R. Anderson
  Daniel J. Mayor , Thomas R. Anderson , David W. Pond and Xabier Irigoien
  We present concurrent data on ingestion, egg production and the loss of maternal biomass in pre-spring bloom female Calanus finmarchicus incubated under conditions representative of those in situ in the North Atlantic. A balanced metabolic budget was constructed and used to examine the relative importance of ingestion and biomass for fuelling egg production during the incubations. Ingested carbon was not sufficient to meet the observed demands for egg production. More than 80% of the carbon utilised by the females was instead derived from their biomass. Fatty acid analysis demonstrated that the storage reserves, 20:1 (n−9) and 22:1 (n−11), were virtually absent before experimentation began, and therefore could not have been used to supply the carbon required for egg production during the incubations. The C:N mass-specific ratio of the biomass utilised was 4.1, suggesting that the females had instead catabolised protein in order to meet their metabolic demands. These results suggest that C. finmarchicus adopts a sacrificial reproductive strategy when food availability is low.
  Daniel J. Mayor , Thomas R. Anderson , David W. Pond and Xabier Irigoien
  The egg production of marine copepods correlates with a range of variables, including the availability of organic carbon (C), nitrogen (N) and the polyunsaturated fatty acids (PUFAs) 20:5(n−3) (EPA) and 22:6(n−3) (DHA). However, an understanding of which substrates limit egg production in the natural environment has yet to be reached. The quantities of C, N, EPA and DHA ingested, derived from parental biomass, and invested in eggs by female Calanus finmarchicus during a 5-day incubation experiment were examined using stoichiometric theory to determine which substrate was limiting. The majority of each substrate was derived from parental biomass, and therefore the existing stoichiometric theory is developed to include this route of supply. The females were essentially devoid of lipid reserves, as evidenced by the lack of the storage fatty acids 20:1(n−9) and 22:1(n−11), and carbon limitation was predicted under most of the scenarios examined. Nitrogen limitation was only apparent when carbon and nitrogen utilisation efficiencies were assumed to be high (0.5) and low (0.4) respectively. PUFAs were assumed to be utilised with high efficiency (0.9), and were never predicted to limit production. This work highlights the need for a more detailed understanding of the maintenance requirements that marine copepods have for C, N, EPA, and DHA and hence the efficiencies with these substrates can be utilised for growth.
  Thomas R. Anderson
  Modelling methodology, it is argued, is primarily about providing explanations of data which, if sufficiently convincing, provide a basis for prediction and forecasting. Models allow us to synthesise our knowledge and explore its ramifications, leading to insight and discovery. As such, modelling is invaluable to the progress of marine science, the development and implementation of ever more complex models moving in tandem with our expanding knowledge base. It is possible to argue, however, that mathematics can be “unreasonably effective” at describing phenomena, particularly for complex models where there are often many free parameters to tune against limited data. Errors become difficult to pinpoint and correct, and creativity may be stifled as models become entrenched within the prevailing paradigm. Indiscriminately adding layer upon layer of complexity in models may therefore be counter productive, particularly if prediction of future scenarios such as changing climate is the ultimate goal. The inclusion of additional complexity in models is nevertheless desirable, where relevant and practicable. New modelling approaches that are coming to the fore likely hold the key to future progress such as targeting complexity in key species and trophic levels, adaptive parameterisations and the representation of physiological trade-offs, providing the potential to simulate emergent community structure.
  J. Icarus Allen , James Aiken , Thomas R. Anderson , Erik Buitenhuis , Sarah Cornell , Richard J. Geider , Keith Haines , Takafumi Hirata , Jason Holt , Corinne Le Quere , Nicholas Hardman-Mountford , Oliver N. Ross , Bablu Sinha and James While
  The MarQUEST (Marine Biogeochemistry and Ecosystem Modelling Initiative in QUEST) project was established to develop improved descriptions of marine biogeochemistry, suited for the next generation of Earth system models. We review progress in these areas providing insight on the advances that have been made as well as identifying remaining key outstanding gaps for the development of the marine component of next generation Earth system models. The following issues are discussed and where appropriate results are presented; the choice of model structure, scaling processes from physiology to functional types, the ecosystem model sensitivity to changes in the physical environment, the role of the coastal ocean and new methods for the evaluation and comparison of ecosystem and biogeochemistry models. We make recommendations as to where future investment in marine ecosystem modelling should be focused, highlighting a generic software framework for model development, improved hydrodynamic models, and better parameterisation of new and existing models, reanalysis tools and ensemble simulations. The final challenge is to ensure that experimental/observational scientists are stakeholders in the models and vice versa.
  Ben A. Ward , Marjorie A. M. Friedrichs , Thomas R. Anderson and Andreas Oschlies
  Parameter values in marine biogeochemical models can strongly affect model performance, but can be hard to define accurately and precisely. When making quantitative comparisons between models it is helpful to objectively assign optimal parameter values, so it is the best model performance rather than the degree (or lack) of tuning which is assessed. The efficacy of two optimisation techniques, a variational adjoint (VA) and a micro genetic algorithm (μGA), was studied with respect to the calibration of two simple one-dimensional models for Arabian Sea data. Optimisations were randomly initialised a number of times, and given the level of uncertainty in the data, the two techniques performed equally well in terms of reducing model-data misfits. When ten parameters were optimised for either model, the Arabian Sea data were insufficient to constrain unique solutions; several parameters could be set anywhere across a wide range of values while providing a similarly good fit to the data. The significance of this underdetermination was assessed by evaluating model solutions against unassimilated equatorial Pacific data. When no prior information was used to assist the optimisation, the underdetermined solutions led to highly variable and often poor performance at the equatorial Pacific. Prior information was used to gain a more reliable solution in two ways: (1) by fixing all poorly-constrained parameters to their default prior values, optimising only parameters that were well-constrained by the data; or (2) by placing broad limits on the search to exclude unrealistic parameter values. Using the first approach the optimisation routines could constrain unique solutions and model performance in the equatorial Pacific was very consistent. The precise results were however sensitive to the uncertain a priori values of the fixed parameters. The second approach was less prescriptive, and consequently led to a more variable performance in the equatorial Pacific. It is argued that the first approach is unrealistically precise as it ignores any uncertainty in the unconstrained parameters, while solutions from the second approach may be unnecessarily broad. In conclusion, unconstrained parameter optimisation procedures should be assisted by stating all that is known a priori about the parameters, but no more.
 
 
 
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