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Chlorophyll-normalized isoprene production in laboratory cultures of marine microalgae and implications for global models

Exton, DA and Suggett, DJ and McGenity, TJ and Steinke, M (2013) 'Chlorophyll-normalized isoprene production in laboratory cultures of marine microalgae and implications for global models.' Limnology and Oceanography, 58 (4). 1301 - 1311. ISSN 0024-3590

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Abstract

We used laboratory cultures of marine microalgae to investigate the effects of growth conditions and their taxonomic position on the production of isoprene, a gas that has major effects on atmospheric chemistry and provides stress tolerance to many primary producers. Isoprene was quantified from 21 microalgal strains sampled during exponential growth, using purge-and-trap pre-concentration and gas chromatography with flameionization detection. Isoprene production rates varied by two orders of magnitude between strains (0.03-1.34 μmol [g chlorophyll a]-1 h-1), and were positively correlated with temperature (r2 = 0.52, p < 0.001, n = 59). Three distinct sea surface temperature (SST)-dependent relationships were found between isoprene and chlorophyll a (μmol [g chlorophyll a]-1 h-1), an improvement in resolution over the single relationship used in previous models: for three polar strains grown at -1°C (slope = 0.03, R2 = 0.76, p < 0.05, n = 9), nine strains grown at 16°C (slope = 0.24, R2 = 0.43, p < 0.05, n = 27 with Dunaliella tertiolecta excluded), and eight strains grown at 26°C (slope = 0.39, R2 = 0.15, p < 0.05, n = 24). We then used a simple model that applied the SSTdependent nature of isoprene production to three representative bioregions for the growth temperatures used in this study. This approach yielded an estimate of global marine isoprene production that was 51% higher than previous attempts using an SST-independent single relationship. Taking into account the effect of temperature therefore potentially allows more precise modeling of marine isoprene production, and suggests that increasing the SST-based resolution of data beyond the three groups used here could further improve future modeling simulations. © 2013, by the Association for the Sciences of Limnology and Oceanography, Inc.

Item Type: Article
Subjects: Q Science > QH Natural history > QH301 Biology
Divisions: Faculty of Science and Health > Biological Sciences, School of
Depositing User: Jim Jamieson
Date Deposited: 23 Jul 2013 12:13
Last Modified: 23 Jan 2019 02:15
URI: http://repository.essex.ac.uk/id/eprint/7199

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