title: Trait assembly in plant assemblages and its modulation by productivity and disturbance.
abstract: Understanding how communities assemble is a key challenge in ecology. Conflicting hypotheses suggest that plant traits within communities should show divergence to reflect strategies to reduce competition or convergence to reflect strong selection for the environmental conditions operating. Further hypotheses suggest that plant traits related to productivity show convergence within communities, but those related to disturbance show divergence. Data on functional diversity (FD(var)) of 12 traits from 30 communities ranging from arable fields, mown and grazed grasslands to moorland and woodland were employed to test this using randomisations tests and correlation and regression analysis. No traits showed consistent significant convergence or divergence in functional diversity. When correlated to measures of the environment, the most common pattern was for functional diversity to decline (7 out of 12 traits) and the degree of convergence (7 out of 12 traits) to increase as the levels of productivity (measured as primary productivity, soil nitrogen release and vegetation C:N) and disturbance increased. Convergence or a relationship between functional diversity and the environment was not seen for a number of important traits, such as LDMC and SLA, which are considered as key predictors of ecosystem function. The analysis indicates that taking into account functional diversity within a system may be a necessary part of predicting the relationship between plant traits and ecosystem function, and that this may be of particular importance within less productive and less disturbed systems.
authors.affiliation: The James Hutton Institute, Craigiebuckler, Aberdeen, UK. robin.pakeman@hutton.ac.uk
authors.forename: Robin J
authors.initials: RJ
authors.lastname: Pakeman
authors.forename: Jack J
authors.initials: JJ
authors.lastname: Lennon
authors.forename: Rob W
authors.initials: RW
authors.lastname: Brooker
mesh_terms: D000465:Algorithms; D017753:Ecosystem; D008954:Models, Biological; D010944:Plants; D012606:Scotland