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Title
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Monoculture-based consumer-resource models predict species dominance in mixed batch cultures of dinoflagellates
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Author
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Abstract
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| Global change will disturb the frequency, scale and distribution of harmful algal blooms (HABs), but we are unable to predict future HABs due to our limited understanding of how physicochemical changes in the envi-ronment affect interspecific competition between dinoflagellates. Trait-based mechanistic modelling is an important tool to unravel and quantify various direct and indirect interactions between species. The present study explores whether MacArthur's consumer-resource model can be used as a viable base model to predict dinoflagellate growth in closed multispecies systems. To this end, two batch culture experiments (294 cultures in total) with monocultures and multispecies cultures of Alexandrium minutum, Prorocentrum lima, P. micans, Protoceratium reticulatum and Scrippsiella trochoidea were performed. Despite changes to the relative (different nitrate concentrations) and absolute nutrient availability (dilutions of L1 medium), P. micans outcompeted all other species in mixed cultures. Consumer-resource modelling parameterized using monoculture growth correctly predicted this species dominance (R-2 between 0.80 and 0.95). Parameter estimates revealed that P. micans had a faster uptake of nitrogen when compared to its competitors, but did not differ in resource efficiency and natural mortality rate. Yet, while the model accurately predicted community dynamics during the growth phase, it was not able to predict their dynamics beyond the point of quiescence. Consumer-resource modelling was shown to differentiate the roles of resource assimilation, resource efficiency, and natural mortality rates in batch culture experiments with minimal data requirements beyond common measurements. The results suggest that consumer resource models provide a promising basis for trait-based modelling of interspecific competition between (harmful) algae. |
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Language
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English
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Source (journal)
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Harmful algae. - Amsterdam
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Publication
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Amsterdam
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2020
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ISSN
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1568-9883
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DOI
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10.1016/J.HAL.2020.101921
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Volume/pages
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99
(2020)
, 10 p.
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Article Reference
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101921
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ISI
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000592393500001
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Pubmed ID
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33218445
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Medium
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E-only publicatie
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Full text (Publisher's DOI)
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Full text (open access)
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Full text (publisher's version - intranet only)
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