Complexity vs linearity: relations between functional traits in a heterotrophic protist.

Functional traits Linearity assumption Soft/hard traits framework Tetrahymena thermophila Trait relations

Journal

BMC ecology and evolution
ISSN: 2730-7182
Titre abrégé: BMC Ecol Evol
Pays: England
ID NLM: 101775613

Informations de publication

Date de publication:
11 01 2023
Historique:
received: 09 06 2022
accepted: 26 12 2022
entrez: 11 1 2023
pubmed: 12 1 2023
medline: 14 1 2023
Statut: epublish

Résumé

Functional traits are phenotypic traits that affect an organism's performance and shape ecosystem-level processes. The main challenge when using functional traits to quantify biodiversity is to choose which ones to measure since effort and money are limited. As one way of dealing with this, Hodgson et al. (Oikos 85:282, 1999) introduced the idea of two types of traits, with soft traits that are easy and quick to quantify, and hard traits that are directly linked to ecosystem functioning but difficult to measure. If a link exists between the two types of traits, then one could use soft traits as a proxy for hard traits for a quick but meaningful assessment of biodiversity. However, this framework is based on two assumptions: (1) hard and soft traits must be tightly connected to allow reliable prediction of one using the other; (2) the relationship between traits must be monotonic and linear to be detected by the most common statistical techniques (e.g. linear model, PCA). Here we addressed those two assumptions by focusing on six functional traits of the protist species Tetrahymena thermophila, which vary both in their measurement difficulty and functional meaningfulness. They were classified as: easy traits (morphological traits), intermediate traits (movement traits) and hard traits (oxygen consumption and population growth rate). We detected a high number (> 60%) of non-linear relations between the traits, which can explain the low number of significant relations found using linear models and PCA analysis. Overall, these analyses did not detect any relationship strong enough to predict one trait using another, but that does not imply there are none. Our results highlighted the need to critically assess the relations among the functional traits used as proxies and those functional traits which they aim to reflect. A thorough assessment of whether such relations exist across species and communities is a necessary next step to evaluate whether it is possible to take a shortcut in quantifying functional diversity by collecting the data on easily measurable traits.

Sections du résumé

BACKGROUND
Functional traits are phenotypic traits that affect an organism's performance and shape ecosystem-level processes. The main challenge when using functional traits to quantify biodiversity is to choose which ones to measure since effort and money are limited. As one way of dealing with this, Hodgson et al. (Oikos 85:282, 1999) introduced the idea of two types of traits, with soft traits that are easy and quick to quantify, and hard traits that are directly linked to ecosystem functioning but difficult to measure. If a link exists between the two types of traits, then one could use soft traits as a proxy for hard traits for a quick but meaningful assessment of biodiversity. However, this framework is based on two assumptions: (1) hard and soft traits must be tightly connected to allow reliable prediction of one using the other; (2) the relationship between traits must be monotonic and linear to be detected by the most common statistical techniques (e.g. linear model, PCA).
RESULTS
Here we addressed those two assumptions by focusing on six functional traits of the protist species Tetrahymena thermophila, which vary both in their measurement difficulty and functional meaningfulness. They were classified as: easy traits (morphological traits), intermediate traits (movement traits) and hard traits (oxygen consumption and population growth rate). We detected a high number (> 60%) of non-linear relations between the traits, which can explain the low number of significant relations found using linear models and PCA analysis. Overall, these analyses did not detect any relationship strong enough to predict one trait using another, but that does not imply there are none.
CONCLUSIONS
Our results highlighted the need to critically assess the relations among the functional traits used as proxies and those functional traits which they aim to reflect. A thorough assessment of whether such relations exist across species and communities is a necessary next step to evaluate whether it is possible to take a shortcut in quantifying functional diversity by collecting the data on easily measurable traits.

Identifiants

pubmed: 36631737
doi: 10.1186/s12862-022-02102-w
pii: 10.1186/s12862-022-02102-w
pmc: PMC9832698
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

1

Subventions

Organisme : European Research Council
ID : EvoComBac: 949208
Pays : International
Organisme : Université Catholique de Louvain
ID : ARC 10-15/31
Organisme : Université Catholique de Louvain
ID : ARC 18-23/095: DIVERCE

Informations de copyright

© 2023. The Author(s).

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Auteurs

Nils A Svendsen (NA)

Earth and Life Institute, Biodiversity Research Center, Université Catholique de Louvain, Louvain-La-Neuve, Belgium. nils.svendsen@uclouvain.be.

Viktoriia Radchuk (V)

Leibniz Institute for Zoo and Wildlife Research (IZW), Alfred-Kowalke-Straße 17, 10315, Berlin, Germany.

Thibaut Morel-Journel (T)

Earth and Life Institute, Biodiversity Research Center, Université Catholique de Louvain, Louvain-La-Neuve, Belgium.
Centre Interdisciplinaire de Recherche en Biologie (CIRB), Collège de France, PSL Research University, CNRS UMR 7241, Paris, France.

Virginie Thuillier (V)

Earth and Life Institute, Biodiversity Research Center, Université Catholique de Louvain, Louvain-La-Neuve, Belgium.

Nicolas Schtickzelle (N)

Earth and Life Institute, Biodiversity Research Center, Université Catholique de Louvain, Louvain-La-Neuve, Belgium.

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