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CLIMB SIGNED

Calibrating and Improving Mechanistic models of Biodiversity

Total Cost €

0

EC-Contrib. €

0

Partnership

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Project "CLIMB" data sheet

The following table provides information about the project.

Coordinator
UNIVERSITAET REGENSBURG 

Organization address
address: UNIVERSITATSSTRASSE 31
city: REGENSBURG
postcode: 93053
website: http://www.uni-regensburg.de/

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 Germany [DE]
 Total cost 247˙020 €
 EC max contribution 247˙020 € (100%)
 Programme 1. H2020-EU.1.3.2. (Nurturing excellence by means of cross-border and cross-sector mobility)
 Code Call H2020-MSCA-IF-2018
 Funding Scheme MSCA-IF-GF
 Starting year 2019
 Duration (year-month-day) from 2019-10-01   to  2022-09-30

 Partnership

Take a look of project's partnership.

# participants  country  role  EC contrib. [€] 
1    UNIVERSITAET REGENSBURG DE (REGENSBURG) coordinator 247˙020.00
2    UNIVERSITY OF CANTERBURY NZ (CHRISTCHURCH) partner 0.00

Map

 Project objective

Mechanistic community models have been advocated as a response to the conceptual and practical limitations of correlative approaches to modeling biodiversity. Building from ecological theory, there are multiple frameworks that could potentially act as a basis for such mechanistic models. However, these options often include a the large number of demographic rates to estimate in species-rich ecosystems, and their direct connection to empirical data has often been limited to simplified settings, something that strongly limits their use for ambitious biodiversity-modeling projects. With CLIMB, we propose an innovative statistical methodology to overcome this challenge: we will connect community data with functional trait data in an array of carefully designed mechanistic community models. More precisely, CLIMB aims to propose and test adequate transfer function(s) that allow rapid calibration of mechanistic models with available trait data and make these models suitable for reliable biodiversity predictions. The CLIMB framework will be developed and tested with simulations and two empirical study cases of temporal dynamics of grassland plant communities dynamics in two different biomes. CLIMB consists in an outgoing phase focused on (1) studying the theoretical fundations of the framework and developing appropriate mechanistic community models; and (2) collecting functional data for local grassland plant species. The return phase will focus on (3) completing the development of the modelling framework and (4) analyzing empirical data. Ultimately, CLIMB will answer pressing fundamental questions of ecology and biodiversity modelling and will offer the ground-breaking perspectives necessary to meet key environmental challenges faced by society today.

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

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lastchecktime (2020-08-14 4:33:56) correctly updated