Predictive utility of trait-separated phytoplankton groups : A robust approach to modeling population dynamics

dc.contributor.authorReynolds, Colin S.
dc.contributor.authorElliott, J. Alex
dc.contributor.authorFrassl, Marieke A.
dc.date.accessioned2018-03-02T08:25:20Z
dc.date.available2018-03-02T08:25:20Z
dc.date.issued2014eng
dc.description.abstractWe explore here the sensitivity and predictive power of quantified morphological and physiological properties of phytoplankton. We have adopted groups of species, distinguished by the clear morphological- and physiological-traits (Kruk et al., 2010; Litchman et al., 2010), and simulated their growth in various environments, using the model PROTECH (Phytoplankton RespOnses To Environmental CHange). This well-tested model uses equations fitted to optimal growth performances of various (“real”) phytoplankton species, described in terms of their functional attributes. Thus, we are able to reconstruct successional series in a range of shallow and deep lakes, situated at set latitudes (temperate or “Mediterranean”). All sequences are initiated at equal biomass levels but they soon become dominated by Groups which responded positively to the changing environmental conditions. We show the selection of small algae under conditions of good light and resource abundance and their subsequent collapse, especially as a consequence of zooplankton consumption. We show the advantages accruing to larger organisms that escape grazing but may also be motile and better defend assembled biomass against loss. Lengthening of cells or filaments of many cells increases organismic size but preserves the high surface-to-volume ratios that aid optimal interception of underwater light in turbid, mixed layers. Nitrogen-fixing capability confers to appropriately adapted species the opportunity to dominate when diminishing supplies of nitrogen limit the growth of other algae. Models founded on trait-separated phytoplankton demonstrate the value of these properties to the description and interpretation of phytoplankton succession.eng
dc.description.versionpublishedde
dc.identifier.doi10.1016/j.jglr.2014.02.005eng
dc.identifier.urihttps://kops.uni-konstanz.de/handle/123456789/41671
dc.language.isoengeng
dc.subject.ddc570eng
dc.titlePredictive utility of trait-separated phytoplankton groups : A robust approach to modeling population dynamicseng
dc.typeJOURNAL_ARTICLEde
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kops.citation.bibtex
@article{Reynolds2014Predi-41671,
  year={2014},
  doi={10.1016/j.jglr.2014.02.005},
  title={Predictive utility of trait-separated phytoplankton groups : A robust approach to modeling population dynamics},
  number={Supplement 3},
  volume={40},
  issn={0380-1330},
  journal={Journal of Great Lakes Research},
  pages={143--150},
  author={Reynolds, Colin S. and Elliott, J. Alex and Frassl, Marieke A.}
}
kops.citation.iso690REYNOLDS, Colin S., J. Alex ELLIOTT, Marieke A. FRASSL, 2014. Predictive utility of trait-separated phytoplankton groups : A robust approach to modeling population dynamics. In: Journal of Great Lakes Research. 2014, 40(Supplement 3), pp. 143-150. ISSN 0380-1330. Available under: doi: 10.1016/j.jglr.2014.02.005deu
kops.citation.iso690REYNOLDS, Colin S., J. Alex ELLIOTT, Marieke A. FRASSL, 2014. Predictive utility of trait-separated phytoplankton groups : A robust approach to modeling population dynamics. In: Journal of Great Lakes Research. 2014, 40(Supplement 3), pp. 143-150. ISSN 0380-1330. Available under: doi: 10.1016/j.jglr.2014.02.005eng
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