WK 8
COMPADRE: The Era of Comparative Plant Demography
Saturday, August 8, 2015: 12:00 PM-5:00 PM
302, Baltimore Convention Center
Organizer:
Roberto Salguero-Gomez, The University of Queensland
Co-organizers:
Owen Jones, University of Southern Denmark;
Judy P. Che-Castaldo, National Socio-Environmental Synthesis Center (SESYNC);
David Hodgson, University of Exeter;
C. Jessica E. Metcalf, Princeton;
Fernando Colchero, University of Southern Denmark;
Hal Caswell, Woods Hole Oceanographic Institution;
James Vaupel, Max Planck Institute for Demographic Research;
Iain Stott, University of Exeter; and
Ruth Archer, Max Planck Institute for Demographic Research
Moderator:
Owen Jones, University of Southern Denmark
Thousands of plant matrix population models have been parameterized from empirical data, but they are largely dispersed through peer reviewed and grey literature, and thus remain inaccessible for synthetic analysis. We have unified this information into a single repository: the COMPADRE Plant Matrix Database, an open-source online repository containing 468 studies from 598 species worldwide, with a total of 5,621 matrices. COMPADRE also contains relevant ancillary information (e.g. ecoregion, growth form, taxonomy, phylogeny, etc.) that facilitates interpretation of the numerous demographic metrics that can be derived from the matrices.
Attendees will learn how to access, query and run comparative analysis with phylogenetic corrections on the COMPADRE database using R and scripts developed by the organizers. Questions that will be addressed include (but are not limited to) (i) visual representation of quasi-risk of extinction of all species exerted to deforestation, (ii) evaluation of the correlations between growth form and mean life expectancy, (iii) links between demographic and stochastic environmental changes, (iv) interface between COMPADRE and other databases such as GBIF or GeneBank, (v) evaluation of the phylogenetic signal in the aforementioned examples, or (vi) comparative cost-effective sensitivity analyses. Users are expected to have at least an intro level to the R platform.
