  The rise of trait-based ecology has led to an increased focus on the
distribution and dynamics of traits in communities. However, a general theory
of trait-based ecology, that can apply across different scales (e.g., species
that differ in size) and gradients (e.g., temperature), has yet to be
formulated. While research focused on metabolic and allometric scaling theory
provides the basis for such a theory it does not explicitly account for
differences traits within and across taxa, such as variation in the optimal
temperature for growth. Here we synthesize trait-based and metabolic scaling
approaches into a framework that we term Trait Drivers Theory or TDT. It shows
that the shape and dynamics of trait distributions can be uniquely linked to
fundamental drivers of community assembly and how the community will respond to
future drivers. To assess predictions and assumptions of TDT, we review several
theoretical studies, recent empirical studies spanning local and biogeographic
gradients. Further, we analyze how the shift in trait distributions influences
ecosystem productivity across an elevational gradient and a 140-year long
ecological experiment. We argue that our general TDT provides a baseline for
(i) recasting the predictions of ecological theories based on species richness
in terms of the shape of trait distributions; and (ii) integrating how specific
traits, including body size, and functional diversity scale up to influence the
dynamics of species assemblages across climatic gradients and how shifts in
functional composition influences ecosystem functioning. Further, it offers a
novel framework to integrate trait, metabolic/allometric, and species-richness
based approaches in order to build a more predictive functional biogeography to
show how assemblages of species have and will respond to climate change.
