How does trait variance partitioning help us to understand plant
community assembly? The example of pond communities at the Kerguelen
Islands.
Abstract
In the current context of biodiversity erosion, functional approaches
have emerged to study community assembly mechanisms and to better
predict the fate of plant species. Assessing patterns of trait variation
should be a powerful tool to determine community assembly mechanisms.
Yet, studies on trait variations and their consequences on individual
performance are usually incomplete as they focus on a single ecological
scale or filter, and do not include relationships between traits,
resulting in a fragmented view of plant community assembly. We focused
on the macrophyte communities living in particular freshwater ecosystems
i.e. the ponds of the Iles Kerguelen, in the sub-Antarctic region. We
measured different categories of traits (aerial, root, and clonal) on
all occurring species to study trait variations across years, sites and
phylogeny scale (between species and within species), and in response to
multiple habitat abiotic and biotic variables. The consequences of these
traits variations and the effects of their correlations for plant
individual performance were also explored. Our results first highlighted
a filter operating on the overall distribution of trait values within
the region, whereas we observed a high amount of intraspecific trait
variation allowing individuals to better resist to filters. Second,
traits responses to biotic and/or abiotic factors were trait-dependent,
and this combination of simultaneous trait responses should allow the
plant as a whole to face several simultaneous constraints. Lastly,
almost all traits have either direct or indirect effects on individual
performance. As a conclusion, partitioning trait variance is a relevant
approach to detect at which scale operate the most decisive processes in
plant community assembly without scale dependency issues, and then
orient further researches. Furhtermore, we plead to consider
multi-traits approach, and several biotic and abiotic variables in
future studies to better understand the effects of environmental changes
on plant communities.