Renaud McKinnon
Université du Québec à Rimouski
M.Sc. candidate
Supervisor: Dominique Gravel
Steven Kembel, Timothée Poisot
Start: 2013-09-01
End: 2014-12-16
M.Sc. candidate
Supervisor: Dominique Gravel
Steven Kembel, Timothée Poisot
Start: 2013-09-01
End: 2014-12-16
Project
Exploring tree species complementarity trough root bacterial and fungal communities: a next generation BEF study.Biodiversity and ecosystem functioning (BEF) studies have traditionally looked at diversity in terms of species richness and clearly demonstrated its benefits on productivity. A need for a mechanistic way of understanding this relationship led to the development of the functional diversity concept. Based on direct interactions through resource use, this approach fails to embrace the importance of indirect interactions such as apparent competition. My project aims to integrate indirect interactions in a BEF framework as to close the gap between BEF studies and food web ecology. We want to test the hypothesis that trees reach complementarity (i.e. reduce apparent competition) by sharing less fungal or (bacterial pathogens (trophic complementarity) in common or more fungal or bacterial symbionts (mutualistic complementarity). We will then determine if tree species complementarity added to functional trait diversity can better predict tree growth than functional trait diversity by itself. For this purpose, we will use 3 experimental tree plantations of the IDENT network (International Diversity Experiment Network with Trees) were twelve tree species were paired in different combinations based on a functional diversity gradient. Fungal and bacterial communities will be identified with the high throughput genetic sequencing Illumina platform. Tree species mixtures that have better growth should have less pathogen overlap and more mutualist overlap. Species pairs that show better complementarity should be more productive. A more in-depth understanding of the role that biodiversity plays in ecosystem functioning will thus help forest managers to identify tree species mixtures to favor as to increase forest productivity.
