Description
Biodiversity is shrinking rapidly and despite our efforts, only a small part of it has been redlisted. Identifying the traits that make species vulnerable might help us predict the outcome for those less known. I used machine learning algorithms to filter relevant publications among 2700 potential ones and collected a final list of 559 statistical models within 122 publications, from which I gathered information on trait responses to extinction risk, across all taxa, spatial scales and biogeographical realms, in what I think it is the most complete compilation up to date. In this talk I will try to find gaps in the research: are taxa, or biogeographical regions equally sampled? Then I will answer to the question in the title by identifying which traits have been tested and which of those have been successful in explaining extinction risk patterns. In the end, I will propose an alternative way to understand which traits should we be looking for, without having to deal with the lack of data and methodological constraints that current statistical models impose.Period | 7 Mar 2018 |
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Event title | Spring Symposium 2018: Organized by the LUOVA doctoral school |
Event type | Conference |
Location | Helsinki, FinlandShow on map |
Degree of Recognition | Local |
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Projects
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Trait-based prediction of extinction risk
Project: Research project