POP-CHANGE
Predicting and managing plant population responses in human altered ecosystems
| Coordinatore | THE PROVOST, FELLOWS, FOUNDATION SCHOLARS & THE OTHER MEMBERS OF BOARD OF THE COLLEGE OF THE HOLY & UNDIVIDED TRINITY OF QUEEN ELIZABETH NEAR DUBLIN
Organization address
address: College Green - contact info |
| Nazionalità Coordinatore | Ireland [IE] |
| Totale costo | 100˙000 € |
| EC contributo | 100˙000 € |
| 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-CIG |
| Funding Scheme | MC-CIG |
| Anno di inizio | 2014 |
| Periodo (anno-mese-giorno) | 2014-03-01 - 2018-02-28 |
Partecipanti
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|---|---|---|---|---|
| 1 |
THE PROVOST, FELLOWS, FOUNDATION SCHOLARS & THE OTHER MEMBERS OF BOARD OF THE COLLEGE OF THE HOLY & UNDIVIDED TRINITY OF QUEEN ELIZABETH NEAR DUBLIN
Organization address
address: College Green - contact info |
IE (DUBLIN) | coordinator | 100˙000.00 |
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Obiettivo del progetto (Objective)
'Humans are rapidly changing the environments that plant and animal populations exist in. In order to make predictions about which populations will persist, which we are likely to lose and where to best place our management efforts for biodiversity conservation and ecosystem services we need a fundamental understanding of how the environment affects population growth and decline in human altered ecosystems. The proposed research seeks to leverage existing data-sets on plant population dynamics and spatial locations to gain insight into how abiotic conditions affect the growth, survival and reproduction of 162 species of plants worldwide. New data will be collected to extensively sample the population dynamics of a widespread plant species to develop novel models of habitat suitability for population growth at the global scale. Statistical models will be developed from existing data on 86 plant species at >40 sites worldwide to determine whether plant population responses to nutrient addition can be predicted using known demographic attributes, these models will be tested using new data from approx. 30 sites worldwide. Ultimately we need to use our knowledge of ecology together with the efficacy and costs of management to determine cost effective interventions to achieve environmental or societal goals. I will use demographic data on >20 plant species together with new management data to develop comparative models of cost effective management strategies for problematic invasive plants. I will use these interlinked objectives to develop predictive models of plant population dynamics under altered environmental conditions, predictions of population response to nutrient addition and general guidelines on how best to manage damaging pest species. The CIG will enable this research programme to be undertaken at a global scale and put European research at the forefront of mitigating the threats to biodiversity and ecosystem services.'