Plankton functional type modelling : running before we can walk?

By Thomas R. Anderson. 2005

412 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/2789acb22d446c0718c9c3885ac77424e4ee8f8f

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In Ecology

In Oceanography

Citations in the corpus

Contrasting photoacclimation costs in ecotypes of the marine eukaryotic picoplankter Ostreococcus (2008, methodology): “…photosynthetic prokaryotes Synechococcus and Prochlorococcus often dominate the picophytoplankton biomass, and have often been used as type organisms to characterize the physiological responses of picophytoplankton to support ecological or biogeochemical models (Gregg et al. 2003; Anderson 2005).”
Castles built on sand : dysfunctionality in plankton models and the inadequacy of dialogue between biologists and modellers (2005, background): “By the same token, modellers should not increase complexity by just adding poorly justified biological detail in an attempt to improve ‘realism’ (Anderson, 2005).”
Misuse of the phytoplankton-zooplankton dichotomy : the need to assign organisms as mixotrophs within plankton functional types (2013, background): “Flynn, K. J. (2006) Reply to Horizons Article “Plankton functional type modelling: running before we can walk” Anderson (2005): II.”
A trait-based approach to ocean ecology (2018, background): “…than describing the many species and how they interact with each other and their environment, trait ecological approaches consider interacting individuals characterized by a few essential traits that are interrelated through trade-offs (Anderson, 2005; Litchman et al., 2013a; Pawar et al., 2015).”
Environmental control of open‐ocean phytoplankton groups: Now and in the future (2010, background): “In our view, this quote from Anderson (2005) highlights some of the potential limitations of this modeling approach rather than pointing to the co-evolution of phytoplankton traits to optimize with regard to several selective pressures (Litchman and Klausmeier 2008).”
A trait-based approach for downscaling complexity in plankton ecosystem models (2009, background): “The early and simple so-called NPZD (Ni-7 trogen, Phytoplankton, Zooplankton and Detritus) models have ”evolved” into8 more complex models representing many plankton functional types (PFTs)9 (Anderson, 2005).”
Phytoplankton niches estimated from field data (2012, background): “The characterization of phytoplankton in these models relies heavily on physiological parameters obtained from laboratory experiments and may not be representative of the niches occupied by phytoplankton functional groups (Anderson 2005).”
A biodiversity‐inspired approach to aquatic ecosystem modeling (2007, background): “Confronted with a reality fraught with species, dependencies, and physiological detail, one cannot help but think that simple models cannot do it justice (Anderson 2005).”
Current understanding of Phaeocystis ecology and biogeochemistry, and perspectives for future research (2007, background): “While empiricists and modelers often speak diVerent languages (Anderson 2005; Flynn 2005), the eVort to design and implement such models can integrate research and teach us more about ecosystems than the outcomes or predictions of the models themselves.”
Phytoplankton community composition can be predicted best in terms of morphological groups (2011, background): “Furthermore, the high number of groups in such refined classification systems (40 sensu Padisák et al. 2009) may pose difficulties when it comes to modeling their dynamics because it may be challenging to objectively assign parameter values for each group (Anderson 2005; Le Quéré et al. 2005).”
Towards a better understanding of microbial carbon flux in the sea (2008, background): “…of functional groups included heterotro- 30 Gasol et al.: Understanding microbial carbon flux in the sea phic bacteria (Le Quéré et al. 2005), leading Anderson (2005) to question if we as microbial ecologists had sufficient understanding and data to create detailed models of bacterial processes…”
End-To-End Models for the Analysis of Marine Ecosystems: Challenges, Issues, and Next Steps (2010, positive): “However, recent advances in physical and LTL modeling have partially shifted the emphasis from inadequate modeling methods to the lack of appropriate data for parameterization and validation (see Anderson 2005; Flynn 2005).”
Prochlorococcus contributes to new production in the Sargasso Sea deep chlorophyll maximum (2007, background): “However, our ability to properly integrate these boxes into ocean biogeochemical models is still in its infancy due to a paucity of biogeochemical ecology data [Anderson, 2005; Flynn, 2005], such as presented in this manuscript.”