2017
DOI: 10.3389/fmars.2017.00358
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Editorial: Modeling the Plankton–Enhancing the Integration of Biological Knowledge and Mechanistic Understanding

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Cited by 9 publications
(3 citation statements)
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“…As the quantitative relationship between cell size and physiological rates is key to models of phytoplankton productivity and community structure (e.g. Andersen et al ., 2016 ; Lindemann et al ., 2017 ; O’Brien et al ., 2016 ), determining the relationship for the coccolithophore clade is needed to accurately model their growth and responses to environmental conditions.…”
Section: Introductionmentioning
confidence: 99%
“…As the quantitative relationship between cell size and physiological rates is key to models of phytoplankton productivity and community structure (e.g. Andersen et al ., 2016 ; Lindemann et al ., 2017 ; O’Brien et al ., 2016 ), determining the relationship for the coccolithophore clade is needed to accurately model their growth and responses to environmental conditions.…”
Section: Introductionmentioning
confidence: 99%
“…There is substantial need to understand the relative importance of biotic interactions for the function and stability of ecosystems (Ives and Carpenter 2007). Given the fundamental role of plankton in aquatic systems, there is a need to better represent plankton population dynamics and variability in current food web models and other ecosystem model approaches (Lindemann et al 2017). A first step in this direction is to characterize interactions within the plankton community while accounting for environmental conditions to identify the relative importance of direct environmental effects, density‐dependent processes and trophic interactions.…”
Section: Discussionmentioning
confidence: 99%
“…Models were run off-line using the daily (24 hr) velocity fields from the hydrodynamic model. Advection of the virtual larvae was simulated using a fourth order Runge-Kutta integration scheme and a random walk was applied using a dissipation rate of 1 × 10 -9 m 2 /s 3 for individual virtual larvae to account for turbulent motion not captured at the resolution of the oceanographic data (Lindemann, Aksnes, Flynn, & Menden-Deuer, 2017). We used Mercator Ocean's Global ocean physical reanalysis GLORYS2V1 (Ferry et al, 2012) at grid size of 1/4 and a temporal scope of daily from January 1, 2000 to December 31, 2010 as input to the model.…”
Section: Dispersal Modelingmentioning
confidence: 99%