Scaling from Traits to Ecosystems: Developing a General Trait Driver Theory via Integrating Trait-Based and Metabolic Scaling Theories

By Brian J. Enquist, J. Norberg, S. Bonser, C. Violle, Colleen Webb, A. Henderson, L. Sloat, Van M. Savage. 2015

330 citations recorded by the source corpus.

Aim: More powerful tests of biodiversity theories need to move beyond species richness and explicitly focus on mechanisms generating diversity via trait composition. The rise of trait-based ecology has led to an increased focus on the distribution and dynamics of traits across broad geographic and climatic gradients and how these distributions influence ecosystem function. 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 in 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 Driver Theory’ or TDT. It shows that the shape and dynamics of trait and size distributions can be 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 and recent empirical studies spanning local and biogeographic gradients. Further, we analyze how the shift in trait distributions influences ecosystem processes across an elevational gradient and a 140-year-long ecological experiment. We show that 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 then ‘scale up’ to influence ecosystem functioning and the dynamics of species assemblages across climate gradients. Further, TDT offers a novel framework to integrate trait, metabolic/allometric, and species-richness-based approaches to better predict functional biogeography and how assemblages of species have and may respond to climate change.

Subfields: Global and Planetary Change, Nature and Landscape Conservation

View Paper: https://www.semanticscholar.org/paper/73427199ddcb7090334f9825ae7d7212b0bd8080

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In Global and Planetary Change

In Nature and Landscape Conservation

Citations in the corpus

sPlot – A new tool for global vegetation analyses (2019, unknown): “…trait j and plot k, we calculated the community- weighted mean (CWM) and the community- weighted variance (CWV) for each of the 18 traits in a plot (Enquist et al., 2015): where nk is the number of species with trait information in plot k, pi,k is the relative abundance of species i in plot k…”
AVONET: morphological, ecological and geographical data for all birds. (2022, background): “…of theory, including the mechanisms underlying community assembly (Mayfield & Levine, 2010), species coexistence (Kraft et al., 2008) and the scaling from traits to ecosystems (Enquist et al., 2015), it is difficult to know whether these results can be applied more generally to non-plant systems.”
Spatial patterns and climate relationships of major plant traits in the New World differ between woody and herbaceous species (2018, background): “This will enable us to evaluate the relative importance of both in driving ecosystem processes, a long-standing goal of functional ecology (D ıaz et al., 2007; Enquist et al., 2015; Lavorel, 2013).”
A global meta-analysis of the relative extent of intraspecific trait variation in plant communities. (2015, unknown): “Beyond quantifying the extent of ITV, the next step for trait-based plant community ecology is to more systematically test how this variation influences community and ecosystem processes and dynamics (Enquist et al. 2015).”