How eco-evolutionary principles can guide tree breeding and tree biotechnology for enhanced productivity.

Journal Article (Journal Article)

Tree breeding and biotechnology can enhance forest productivity and help alleviate the rising pressure on forests from climate change and human exploitation. While many physiological processes and genes are targeted in search of genetically improved tree productivity, an overarching principle to guide this search is missing. Here, we propose a method to identify the traits that can be modified to enhance productivity, based on the differences between trees shaped by natural selection and 'improved' trees with traits optimized for productivity. We developed a tractable model of plant growth and survival to explore such potential modifications under a range of environmental conditions, from non-water limited to severely drought-limited sites. We show how key traits are controlled by a trade-off between productivity and survival, and that productivity can be increased at the expense of long-term survival by reducing isohydric behavior (stomatal regulation of leaf water potential) and allocation to defense against pests compared with native trees. In contrast, at dry sites occupied by naturally drought-resistant trees, the model suggests a better strategy may be to select trees with slightly lower wood density than the native trees and to augment isohydric behavior and allocation to defense. Thus, which traits to modify, and in which direction, depend on the original tree species or genotype, the growth environment and wood-quality versus volume production preferences. In contrast to this need for customization of drought and pest resistances, consistent large gains in productivity for all genotypes can be obtained if root traits can be altered to reduce competition for water and nutrients. Our approach illustrates the potential of using eco-evolutionary theory and modeling to guide plant breeding and genetic technology in selecting target traits in the quest for higher forest productivity.

Full Text

Duke Authors

Cited Authors

  • Franklin, O; Palmroth, S; Näsholm, T

Published Date

  • November 2014

Published In

Volume / Issue

  • 34 / 11

Start / End Page

  • 1149 - 1166

PubMed ID

  • 25542897

Electronic International Standard Serial Number (EISSN)

  • 1758-4469

International Standard Serial Number (ISSN)

  • 0829-318X

Digital Object Identifier (DOI)

  • 10.1093/treephys/tpu111


  • eng