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TROPHY SIGNED

The consequences of temperature-resource interactions for the future of marine phytoplankton communities

Total Cost €

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EC-Contrib. €

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Partnership

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Project "TROPHY" data sheet

The following table provides information about the project.

Coordinator
DANMARKS TEKNISKE UNIVERSITET 

Organization address
address: ANKER ENGELUNDSVEJ 1 BYGNING 101 A
city: KGS LYNGBY
postcode: 2800
website: www.dtu.dk

contact info
title: n.a.
name: n.a.
surname: n.a.
function: n.a.
email: n.a.
telephone: n.a.
fax: n.a.

 Coordinator Country Denmark [DK]
 Total cost 212˙194 €
 EC max contribution 212˙194 € (100%)
 Programme 1. H2020-EU.1.3.2. (Nurturing excellence by means of cross-border and cross-sector mobility)
 Code Call H2020-MSCA-IF-2017
 Funding Scheme MSCA-IF-EF-ST
 Starting year 2018
 Duration (year-month-day) from 2018-04-01   to  2020-03-31

 Partnership

Take a look of project's partnership.

# participants  country  role  EC contrib. [€] 
1    DANMARKS TEKNISKE UNIVERSITET DK (KGS LYNGBY) coordinator 212˙194.00

Map

 Project objective

Temperature, nutrients and light drive the growth of phytoplankton, aquatic photosynthetic microbes responsible for nearly half of global primary production. Because phytoplankton influence global biogeochemical cycles, carbon sequestration and climate, accurately modelling their growth is vital to forecasting our future. However, the models we use for global ecosystem forecasts do not consider how these factors interact, even though the interactions lead to qualitative and quantitative differences in outcomes. My goal is to therefore build a mechanistic understanding of how temperature and resources interact to influence phytoplankton growth, productivity and biogeochemical cycles.

This project has three objectives (i) develop statistical models describing how phytoplankton growth changes as a joint function of temperature, nutrients and light, (ii) develop mechanistic models characterising how temperature and resources influence cellular processes in phytoplankton, and ultimately their growth, and (iii) implement dynamic versions of the mechanistic model to forecast how marine phytoplankton communities will respond to future changes in temperature, resources and predation.

My work will involve applying machine learning techniques to published laboratory and field datasets to understand complex interactions between the three factors. By combining this understanding with insights from ecological theory, I will generate an accurate mechanistic model of growth, and then test the power of this model to predict patterns in the ocean using independent field datasets. Finally, I will use the validated mechanistic model to forecast changes to global patterns in phytoplankton growth and primary productivity.

This project will enable us to generate credible forecasts of phytoplankton productivity and biogeochemical cycles in a warming ocean, and improve our understanding of fundamental ecological processes by uniting major fields of ecological theory.

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The information about "TROPHY" are provided by the European Opendata Portal: CORDIS opendata.

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