FORECOMM
FORECASTING COMMUNITY-LEVEL RESPONSES TO GLOBAL CHANGE
| Coordinatore | IMPERIAL COLLEGE OF SCIENCE, TECHNOLOGY AND MEDICINE
Organization address
address: SOUTH KENSINGTON CAMPUS EXHIBITION ROAD contact info |
| Nazionalità Coordinatore | United Kingdom [UK] |
| Totale costo | 221˙606 € |
| EC contributo | 221˙606 € |
| Programma | FP7-PEOPLE
Specific programme "People" implementing the Seventh Framework Programme of the European Community for research, technological development and demonstration activities (2007 to 2013) |
| Code Call | FP7-PEOPLE-2013-IEF |
| Funding Scheme | MC-IEF |
| Anno di inizio | 2014 |
| Periodo (anno-mese-giorno) | 2014-10-01 - 2016-09-30 |
Partecipanti
| # | ||||
|---|---|---|---|---|
| 1 |
IMPERIAL COLLEGE OF SCIENCE, TECHNOLOGY AND MEDICINE
Organization address
address: SOUTH KENSINGTON CAMPUS EXHIBITION ROAD contact info |
UK (LONDON) | coordinator | 221˙606.40 |
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Obiettivo del progetto (Objective)
'Climatic change ranks amongst the greatest threats to biodiversity across the Earth’s biomes. This climatic change is accompanied by unprecedented anthropogenic impacts through habitat loss, overexploitation of natural resources, spread of invasive species and disease, which have reduced and homogenised biodiversity affecting ecosystem goods and services at regional and global scales. Predicting how natural communities will cope with anticipated changes is one of the greatest challenges for ecologists and has prompted them to develop predictive models that forecast changes in the geographic distribution of species, communities and phylogenetic diversity. Most predictive models, however, do not incorporate biotic interactions and thus are unlikely to be sufficiently equipped to make accurate ecological predictions of how natural communities will respond to climatic change. This is problematic because biotic interactions (e.g. predation, competition, resource-consumer interactions, host-parasite interactions, mutualism and facilitation) have been shown to affect large-scale distribution patterns of species and thus mediate their ability to cope with climatic change. The FORECOMM project – Forecasting community-level responses to global change – will help address this gap by using a modelling framework to integrate existing data about climatic change, species distributions, community composition and biotic interactions to synthesize new understanding about how communities will respond to a changing world. This project will 1) build upon existing methods and develop new approaches to infer and integrate biotic interactions into predictive models; 2) develop novel procedures to test model predictions; 3) Assess the impact of incorporating biotic interactions in predictive models by re-analysing a series of key published case studies assessing the potential impacts of climate change on species distributions.'