To harness traits for ecology, let's abandon 'functionality'

Streit, Robert P., and Bellwood, David R. (2023) To harness traits for ecology, let's abandon 'functionality'. Trends in Ecology and Evolution, 38 (5). pp. 402-411.

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Abstract

Traits are measurable features of organisms. Functional traits aspire to more. They quantify an organism's ecology and, ultimately, predict ecosystem functions based on local communities. Such predictions are useful, but only if ‘functional’ really means ‘ecologically relevant’. Unfortunately, many ‘functional’ traits seem to be characterized primarily by availability and implied importance – not by their ecological information content. Better traits are needed, but a prevailing trend is to ‘functionalize’ existing traits. The key may be to invert the process, that is, to identify functions of interest first and then identify traits as quantifiable proxies. We propose two distinct, yet complementary, perspectives on traits and provide a ‘taxonomy of traits’, a conceptual compass to navigate the diverse applications of traits in ecology.

Item ID: 77649
Item Type: Article (Research - C1)
ISSN: 1872-8383
Keywords: ecosystem function, functional trait, global change, resilience, trait ecology
Copyright Information: Published Version: © 2022 Elsevier Ltd. All rights reserved. Author accepted manuscript may be made open access in an Institutional Repository under a CC BY-NC-ND license after a 12 month embargo.
Funders: Australian Research Council (ARC)
Date Deposited: 15 Feb 2023 00:31
FoR Codes: 31 BIOLOGICAL SCIENCES > 3103 Ecology > 310302 Community ecology (excl. invasive species ecology) @ 30%
41 ENVIRONMENTAL SCIENCES > 4102 Ecological applications > 410203 Ecosystem function @ 30%
31 BIOLOGICAL SCIENCES > 3103 Ecology > 310399 Ecology not elsewhere classified @ 40%
SEO Codes: 28 EXPANDING KNOWLEDGE > 2801 Expanding knowledge > 280102 Expanding knowledge in the biological sciences @ 60%
28 EXPANDING KNOWLEDGE > 2801 Expanding knowledge > 280111 Expanding knowledge in the environmental sciences @ 40%
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