Applying trait-based models to achieve functional targets for theory-driven ecological restoration.
Manipulating community assemblages to achieve functional targets is a key component of restoring degraded ecosystems. The response-and-effect trait framework provides a conceptual foundation for translating restoration goals into functional trait targets, but a quantitative framework has been lacking for translating trait targets into assemblages of species that practitioners can actually manipulate. This study describes new trait-based models that can be used to generate ranges of species abundances to test theories about which traits, which trait values and which species assemblages are most effective for achieving functional outcomes. These models are generalisable, flexible tools that can be widely applied across many terrestrial ecosystems. Examples illustrate how the framework generates assemblages of indigenous species to (1) achieve desired community responses by applying the theories of environmental filtering, limiting similarity and competitive hierarchies, or (2) achieve desired effects on ecosystem functions by applying the theories of mass ratios and niche complementarity. Experimental applications of this framework will advance our understanding of how to set functional trait targets to achieve the desired restoration goals. A trait-based framework provides restoration ecology with a robust scaffold on which to apply fundamental ecological theory to maintain resilient and functioning ecosystems in a rapidly changing world.
Environmental Research Institute and Department of Biological Sciences, University of Waikato, Private Bag 3105, Hamilton, 3240, New Zealand.
Daniel C
DC
Laughlin
D000818:Animals; D044822:Biodiversity; D003163:Competitive Behavior; D017753:Ecosystem; D052918:Environmental Restoration and Remediation; D058865:Introduced Species; D008954:Models, Biological
Community assembly; ecosystem management; environmental filtering; functional diversity; functional traits; limiting similarity; mass ratio; novel ecosystems; reference conditions; trait hierarchies