COS 75-3 - Species traits as drivers of food web structure: A new way to understand complex communities

Thursday, August 11, 2016: 8:20 AM
220/221, Ft Lauderdale Convention Center
Idaline Laigle, Biologie, Université de Sherbrooke, Sherbrooke, QC, Canada; QCBS, QC, Canada, Dominique Gravel, Départment de Biologie, University of Sherbrooke, Sherbrooke, QC, Canada and Isabelle Aubin, Great Lakes Forestry Centre, Canadian Forest Service, Natural Resources Canada, Sault Ste. Marie, ON, Canada

The mechanisms driving the relationships between species diversity, ecological
interactions, and ecosystem functioning remain largely unknown in multi-
trophic systems. The success of trait-based approaches at analyzing the
assembly, dynamics and functioning of plant communities has shown promising
generalities across systems. Their application to animal communities is how
not straightforward because of the diversity of the interactions and the
complexity of their arrangements. In addition to their direct effect on
ecosystems, animal traits also influence them indirectly because they
determine food web structure and consequently trophic regulation. The
objective in our study was to determine how and why functional structure was
related to food web structure. We considered that food web structure was the
result of i) trait-matching constraints determining the occurrence of
interactions among pairs of species and ii) the multivariate distribution of
functional traits in the community. Accordingly, we first tested with
different models if trophic interactions in soil food webs were
the outcome of trait-matching constraints between pairs of invertebrate
species. Secondly, we investigated the correlation between the functional
structure of the community (both the mean and diversity of the multivariate
trait distribution) and the network structure. Our dataset compiled records of
35,632 interactions among soil invertebrates from 48 different sites.


We found that the occurrence of trophic interactions (and their absence) is
well predicted by matching the traits of the resource and of the consumer. The
three models were successful at predicting the interactions among species. We
also found that functional composition and network properties were closely
related, which may lead to significant effect on communities functioning.
Above all, the species richness was the main property driving the network
structure. In one hand, it increases the functional richness because of a
sampling effect. In the other hand, it increases the chance of having
functionally redundant species, thus decreasing the functional evenness and
divergence. The functional diversity indices were negatively correlated to
network properties known to decrease with the communtiy productivity, and by
increasing the number of redundant species, they should increase the
resilience of the community. Our results reveal the largely unexplored
implications of functional trait composition for network structure and promise
new avenues to explore the relationship between functional diversity and
ecosystem functionning in multi-trophic systems.