Objective
Species invasion is one of the prime threats to biodiversity, driving major changes in ecosystem structure and function. Identifying the traits associated with invasion has been largely restricted to comparing indigenous and invasive species or comparing invasive species that differ in abundance or impact. However, a more complete understanding may emerge when the entire pool of potentially invasive species is used as a control, information that is rarely available. Fish populations in the Mediterranean are faced with multiple stressors including overfishing, pollution, habitat loss and displacement by invasive species. The latter is of particular concern in the eastern Mediterranean where a large influx of Red Sea species has followed the opening of the Suez Canal in 1869. These invasive species make up a large percentage of total fish biomass in this region. However, it is generally unknown how these species impact the ecology of indigenous species. In addition, it has proven challenging to identify the traits that enhance invasion success. The proposed research will focus on this unique 'natural experiment', in which almost the entire pool of potentially alien species is known, to understanding the causes of fish invasion and its consequences for indigenous species. This work will combine two complementary approaches to study species invasion, focusing both on the impact of invasive species in the Mediterranean and on the traits that lead to a successful invasion. This combination provides a powerful strategy for evaluating the underlying ecological mechanisms. This study links local experimental manipulations, coarse-grained data compilation and detailed state-of-the-art approaches for estimating life-history traits under a single conceptual framework. Results will provide critical information for the appreciation of the risks facing indigenous fish, information which is necessary for mitigation efforts.
Fields of science
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques.
Call for proposal
FP7-PEOPLE-2013-CIG
See other projects for this call
Coordinator
69978 Tel Aviv
Israel