Project

Understanding species’ invasions: a mechanistic view on the invasion success of the common waxbill, a prolific avian invader.

Duration
01 November 2020 → Ongoing
Funding
Research Foundation - Flanders (FWO)
Promotor
Research disciplines
  • Natural sciences
    • Animal ecology
    • Invasion biology
    • Terrestrial ecology
    • Biogeography and phylogeography
    • Conservation and biodiversity
Keywords
invasion biology mechanistic modelling global change ecology avian ecology niche modelling ornithology process-based modelling
 
Project description

Invasive species are among the main global threats to biodiversity, economy and human well-being. Preventing their introduction is paramount but requires being able to reliably predict invasion risks. Currently, forecasts of where introduced species can invade strongly rely on extrapolating native-range realized niche characteristics onto new areas. Frequent mismatches between predicted and actual invasive occurrences however raise concern for the validity of such forecasts. Therefore, here, I will use the invasion of Iberia by common waxbills (Estrilda astrild) as a case study for examining the efficacy of alternative frameworks that aim to directly characterize species’ fundamental niches. By linking species’ behavioural, morphological and physiological traits with spatial environmental data, such ‘mechanistic’ approaches should be uniquely suited to delineate areas that are within a species’ fundamental environmental tolerance. Common waxbills constitute an interesting challenge, as they only show little overlap between native (i.e. sub-Saharan) and invasive range climate conditions. Functional traits data can readily be collected from museum specimens, captive populations and from the wild, as waxbills are the most widespread avian invader across Iberia. This project is among the first to apply a fully mechanistic framework to study the invasion of an endothermic vertebrate and will deliver new insights in the processes underlying biological invasions.