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

Exton, Daniel A and Suggett, David J and McGenity, Terry J and Steinke, Michael (2013) 'Chlorophyll-normalized isoprene production in laboratory cultures of marine microalgae and implications for global models.' Limnology and Oceanography, 58 (4). pp. 1301-1311. ISSN 0024-3590

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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 flame-ionization 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 SST-dependent 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.

Item Type: Article
Subjects: Q Science > QH Natural history > QH301 Biology
Divisions: Faculty of Science and Health
Faculty of Science and Health > Life Sciences, School of
SWORD Depositor: Elements
Depositing User: Elements
Date Deposited: 23 Jul 2013 12:13
Last Modified: 21 Feb 2022 17:31

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