the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
The distribution, dominance patterns and ecological niches of plankton functional types in Dynamic Green Ocean Models and satellite estimates
Abstract. We compare the spatial and temporal representation of phytoplankton functional types (pPFTs) in four different Dynamic Green Ocean Models (DGOMs; CCSM-BEC, NEMURO, PISCES and PlankTOM5) to derived phytoplankton distributions from two independent satellite estimates, with a particular focus on diatom distributions. Global annual mean surface biomass estimates for diatoms vary between 0.23 mmol C m−3 and 0.77 mmol C m−3 in the models, and are comparable to a satellite-derived estimate (0.41 mmol C m−3). All models consistently simulate a higher zonal mean diatom biomass contribution in the high latitudes than in the low latitudes, but the relative diatom contribution varies substantially between models with largest differences in the high latitudes (20% to 100% of total biomass). We investigate phytoplankton distribution in terms of annual and monthly mean dominance patterns, i.e. the distribution of locations where a given PFT contributes more than 50% to total biomass. In all models, diatoms tend to dominate large areas of the high latitudes of both hemispheres, and the area of the surface ocean dominated by diatoms is significantly higher in the models than in the satellite estimates. We estimate the realized ecological niches filled by the dominant pPFT at each location as a function of annual mean surface nitrate concentration (NO3), sea surface temperature (SST), and mixed layer depth. A general additive model (GAM) is used to map the probability of dominance of all pPFTs in niche and geographic space. Models tend to simulate diatom dominance over a wider temperature and nutrient range, whereas satellites confine diatom dominance to a narrower niche of low-intermediate annual mean temperatures (annual mean SST < 10 °C), but allow for niches in different ranges of surface NO3 concentrations. For annual mean diatom dominance, the statistically modelled probability of dominance explains the majority of the variance in the data (65.2–66.6%). For the satellite estimates, the explained deviance is much lower (44.6% and 32.7%). The differences in the representation of diatoms among models and compared to satellite estimates highlights the need to better resolve phytoplankton succession and phenology in the models. This work is part of the marine ecosystem inter-comparison project (MAREMIP).
- Preprint
(2413 KB) - Metadata XML
- BibTeX
- EndNote
- RC C7678: 'Referee comment', Anonymous Referee #1, 03 Jan 2014
- RC C7953: 'Referee's comments', Anonymous Referee #2, 14 Jan 2014
- RC C7678: 'Referee comment', Anonymous Referee #1, 03 Jan 2014
- RC C7953: 'Referee's comments', Anonymous Referee #2, 14 Jan 2014
Viewed
HTML | XML | Total | BibTeX | EndNote | |
---|---|---|---|---|---|
3,108 | 769 | 373 | 4,250 | 72 | 78 |
- HTML: 3,108
- PDF: 769
- XML: 373
- Total: 4,250
- BibTeX: 72
- EndNote: 78
Cited
15 citations as recorded by crossref.
- Projected decreases in future marine export production: the role of the carbon flux through the upper ocean ecosystem C. Laufkötter et al. 10.5194/bg-13-4023-2016
- A skill assessment of the biogeochemical model REcoM2 coupled to the Finite Element Sea Ice–Ocean Model (FESOM 1.3) V. Schourup-Kristensen et al. 10.5194/gmd-7-2769-2014
- Uncertainties in projecting climate-change impacts in marine ecosystems M. Payne et al. 10.1093/icesjms/fsv231
- On the Southern Ocean CO2 uptake and the role of the biological carbon pump in the 21st century J. Hauck et al. 10.1002/2015GB005140
- Diel light cycle as a key factor for modelling phytoplankton biogeography and diversity I. Tsakalakis et al. 10.1016/j.ecolmodel.2018.06.022
- Phytoplankton competition during the spring bloom in four plankton functional type models T. Hashioka et al. 10.5194/bg-10-6833-2013
- Long-term trends in ocean plankton production and particle export between 1960–2006 C. Laufkötter et al. 10.5194/bg-10-7373-2013
- Bridging the gap between omics and earth system science to better understand how environmental change impacts marine microbes T. Mock et al. 10.1111/gcb.12983
- Salinity shapes zooplankton communities and functional diversity and has complex effects on size structure in lakes M. Gutierrez et al. 10.1007/s10750-018-3529-8
- CMIP5 model analysis of future changes in ocean net primary production focusing on differences among individual oceans and models Y. Nakamura & A. Oka 10.1007/s10872-019-00513-w
- Explicit Planktic Calcifiers in the University of Victoria Earth System Climate Model, Version 2.9 K. Kvale et al. 10.1080/07055900.2015.1049112
- Obtaining Phytoplankton Diversity from Ocean Color: A Scientific Roadmap for Future Development A. Bracher et al. 10.3389/fmars.2017.00055
- Uncertainty in Ocean-Color Estimates of Chlorophyll for Phytoplankton Groups R. Brewin et al. 10.3389/fmars.2017.00104
- Drivers and uncertainties of future global marine primary production in marine ecosystem models C. Laufkötter et al. 10.5194/bg-12-6955-2015
- Analysis, Integration and Modeling of the Earth System (AIMES): Advancing the post-disciplinary understanding of coupled human–environment dynamics in the Anthropocene D. Schimel et al. 10.1016/j.ancene.2016.02.001