Chlorophyll to carbon ratio derived from an ecosystem model with explicit photodamage


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eva.alvarez [ at ] awi.de

Abstract

Phytoplankton biomass is often inferred from chlorophyll (Chl), however, biogeochemistry in the ocean is coupled mostly to carbon. The Chl to carbon (Chl:C) ratio is variable and most of the variability is driven by acclimation to changing nutrient and light-conditions. Our current model, REcoM, is a global ecosystem model based on the phytoplankton growth model from Geider et al. (1998) which runs coupled to the MIT global circulation model. Geider’s model describes separately the dynamics of carbon, nitrogen and Chl, from temperature, light and nutrients. Hence, it allows to account for the effects of external conditions on cell quotas. Loss terms in phytoplankton growth need to be described within the ecosystem model. In one version, the degradation of Chl had been treated for simplicity as a constant rate. With this parameterization, although the Chl distribution correlated well with satellite Chl, Chla:C ratios deviated from previous reported values for global ocean. We therefore propose to regulate the degradation of Chl considering the degree of light saturation of the photosynthetic apparatus which, ultimately, reflects increased damage to Chl at high irradiances. This new parameterization provides Chl values highly correlated with satellite Chl and Chla:C ratios in a realistic range of values. We show that the modelled relationship of Chl:C with growth rate fits with results from lab experiments under balanced growth conditions. The question that remains is whether not only the range but also the patterns of Chla:C ratios at global scale are accurate. To asses that, we compare model output with new in situ and published data of Chl:C ratios.



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Event Details
ASLO Aquatic Sciences Meeting, 26 Feb 2017 - 03 Mar 2017, Honolulu-Hawaii, USA.
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47177
Cite as
Alvarez, E. and Völker, C. (2017): Chlorophyll to carbon ratio derived from an ecosystem model with explicit photodamage , ASLO Aquatic Sciences Meeting, Honolulu-Hawaii, USA, 26 February 2017 - 3 March 2017 .


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