Opendata, web and dolomites

ARCDIV

Up-scaling Arctic diversity analysis to link community organisation and ecosystem functioning

Total Cost €

0

EC-Contrib. €

0

Partnership

0

Views

0

 ARCDIV project word cloud

Explore the words cloud of the ARCDIV project. It provides you a very rough idea of what is the project "ARCDIV" about.

periods    arctic    polychaetes    practically    limited    crustaceans    runoff    first    interplay    live    pan    undergoing    holding    impacts    patterns    locations    full    oceans    biodiversity    function    anthropogenic    corner    ecosystem    imperative    local    nature    models    marine    environmental    structure    functioning    feasible    webs    services    functions    employing    quantitative    functional    communities    scales    soft    food    bottoms    community    shift    influencing    masses    root    polar    structuring    profound    4th    stressors    water    link    inference    fundamental    alteration    organisation    biological    ecosystems    indirect    seascapes    chemical    changing    macrofauna    physical    ice    financially    building    environment    exploratory    5000    structural    abundance    diversity    covered    warming    equation    data    bivalves    ing    broad    look    understand    characterise    species    constituents    distributions    traits    interactions    freshwater    larger    translates    fine    macrobenthic    feedbacks    ecological    shorter    benthic    spatial    promise   

Project "ARCDIV" data sheet

The following table provides information about the project.

Coordinator
ALFRED-WEGENER-INSTITUT HELMHOLTZ-ZENTRUM FUR POLAR- UND MEERESFORSCHUNG 

Organization address
address: AM HANDELSHAFEN 12
city: BREMERHAVEN
postcode: 27570
website: www.awi.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]
 Project website https://www.researchgate.net/profile/Casper_Kraan
 Total cost 171˙460 €
 EC max contribution 171˙460 € (100%)
 Programme 1. H2020-EU.1.3.2. (Nurturing excellence by means of cross-border and cross-sector mobility)
 Code Call H2020-MSCA-IF-2015
 Funding Scheme MSCA-IF-EF-ST
 Starting year 2016
 Duration (year-month-day) from 2016-06-01   to  2018-10-15

 Partnership

Take a look of project's partnership.

# participants  country  role  EC contrib. [€] 
1    ALFRED-WEGENER-INSTITUT HELMHOLTZ-ZENTRUM FUR POLAR- UND MEERESFORSCHUNG DE (BREMERHAVEN) coordinator 171˙460.00

Map

 Project objective

Arctic oceans are undergoing major changes in many of its fundamental physical constituents, such as a shift from multi- to first-year ice, shorter ice-covered periods, increasing freshwater runoff, and warming and alteration in the distribution of water masses. Such changes, often resulting from anthropogenic stressors, have profound impacts on the chemical and biological processes that are at the root of Arctic marine food webs, influencing their structure, function and biodiversity. Yet, much research addressing these on-going changes is practically and financially limited to local scales or rather exploratory by nature, making it imperative to better characterise and understand the structural and functional diversity of ecological systems that contribute to the marine Arctic across larger scales. We aim to offer more insight in the distributions and abundance of macrobenthic species in Arctic seascapes, e.g. bivalves, polychaetes, and crustaceans that live in marine soft bottoms. Building on recent pan-Arctic community data from ~5000 locations, we address a fundamental challenge in Arctic ecological research by employing quantitative methods thus far not feasible. We will use multi-species distribution models that allow determining interactions between species; link functions to environmental characteristics using 4th-corner models. Key is that such approaches link traits and environment without the necessity of including sample locations, holding promise for an approach that translates ecosystem function directly to services; look for indirect interactions and feedbacks between polar benthic macrofauna and ecosystem functioning by employing structural equation models. This enables full inference of spatial diversity patterns of Arctic benthic communities and link community organisation and ecosystem functioning, allowing us to understand the interplay between fine- and broad-scale patterns and processes structuring rapidly changing polar benthic ecosystems.

 Publications

year authors and title journal last update
List of publications.
2018 Renate Degen, Magnus Aune, Bodil A. Bluhm, Camilla Cassidy, Monika Kędra, Casper Kraan, Leen Vandepitte, Maria Włodarska-Kowalczuk, Irina Zhulay, Paolo G. Albano, Julie Bremner, Jacqueline M. Grebmeier, Heike Link, Nathalie Morata, Marie C. Nordström, Mehdi Ghodrati Shojaei, Lauren Sutton, Martin Zuschin
Trait-based approaches in rapidly changing ecosystems: A roadmap to the future polar oceans
published pages: 722-736, ISSN: 1470-160X, DOI: 10.1016/j.ecolind.2018.04.050
Ecological Indicators 91 2019-05-09

Are you the coordinator (or a participant) of this project? Plaese send me more information about the "ARCDIV" project.

For instance: the website url (it has not provided by EU-opendata yet), the logo, a more detailed description of the project (in plain text as a rtf file or a word file), some pictures (as picture files, not embedded into any word file), twitter account, linkedin page, etc.

Send me an  email (fabio@fabiodisconzi.com) and I put them in your project's page as son as possible.

Thanks. And then put a link of this page into your project's website.

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

More projects from the same programme (H2020-EU.1.3.2.)

DGLC (2019)

Domain-general language control: Evidence from the switching paradigm

Read More  

OSeaIce (2019)

Two-way interactions between ocean heat transport and Arctic sea ice

Read More  

LearningEmotions (2020)

Emotion Recognition: A Statistical Learning Approach

Read More