4.8 Article

An empirical assessment of tree branching networks and implications for plant allometric scaling models

Journal

ECOLOGY LETTERS
Volume 16, Issue 8, Pages 1069-1078

Publisher

WILEY
DOI: 10.1111/ele.12127

Keywords

Allometry; hierarchical Bayesian; metabolic scaling theory; network topology; plant traits; WBE model

Categories

Funding

  1. NSF ATB [0742800]
  2. NSF Postdoctoral Fellowships in Bioinformatics [DBI-0906005, DBI-0905868]
  3. NSF-IBN-0743148
  4. Direct For Biological Sciences
  5. Division Of Integrative Organismal Systems [743148] Funding Source: National Science Foundation

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Several theories predict whole-tree function on the basis of allometric scaling relationships assumed to emerge from traits of branching networks. To test this key assumption, and more generally, to explore patterns of external architecture within and across trees, we measure branch traits (radii/lengths) and calculate scaling exponents from five functionally divergent species. Consistent with leading theories, including metabolic scaling theory, branching is area preserving and statistically self-similar within trees. However, differences among scaling exponents calculated at node- and whole-tree levels challenge the assumption of an optimised, symmetrically branching tree. Furthermore, scaling exponents estimated for branch length change across branching orders, and exponents for scaling metabolic rate with plant size (or number of terminal tips) significantly differ from theoretical predictions. These findings, along with variability in the scaling of branch radii being less than for branch lengths, suggest extending current scaling theories to include asymmetrical branching and differential selective pressures in plant architectures.

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