Community-level natural selection modes: A quadratic framework to link multiple functional traits with competitive ability

Autores
Rolhauser, Andrés Guillermo; Nordenstahl, Marisa; Aguiar, Martin Roberto; Pucheta, Eduardo Raúl
Año de publicación
2018
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
Research linking functional traits to competitive ability of coexisting species has largely relied on rectilinear correlations, yielding inconsistent results. Based on concepts borrowed from natural selection theory, we propose that trait?competition relationships can generally correspond to three univariate selection modes: directional (a rectilinear relationship), stabilising (an n-shaped relationship), and disruptive (a u-shaped relationship). Moreover, correlational selection occurs when two traits interact in determining competitive ability and lead to an optimum trait combination (i.e., a bivariate nonlinear selection mode). We tested our ideas using two independent datasets, each one characterising a group of species according to (a) their competitive effect on a target species in a pot experiment and (b) species-level values of well-known functional traits extracted from existing databases. The first dataset comprised 10 annual plant species frequent in a summer-rainfall desert in Argentina, while the second consisted of 37 herbaceous species from cool temperate vegetation types in Canada. Both experiments had a replacement design where the identity of neighbours was manipulated holding total plant density in pots constant. We modelled the competitive ability of neighbours (i.e., the log inverse of target plant biomass) as a function of traits using normal multiple regression. Leaf dry matter content (LDMC) was consistently subjected to negative directional selection in both experiments as well as to stabilising selection among temperate species. Leaf size was subjected to stabilising selection among desert species while among temperate species, leaf size underwent correlational selection in combination with specific leaf area (SLA): selection on SLA was negative directional for large-leaved species, while it was slightly positive for small-leaved species. Synthesis. Multiple quadratic regression adds functional flexibility to trait-based community ecology while providing a standardised basis for comparison among traits and environments. Our analyses of two datasets from contrasting environmental conditions indicate (a) that leaf dry matter content can capture an important component of plant competitive ability not accounted for by widely used competitive traits, such as specific leaf area, leaf size, and plant height and (b) that optimum relationships (either univariate or bivariate) between competitive ability and plant traits may be more common than previously realised.
Fil: Rolhauser, Andrés Guillermo. Universidad Nacional de San Juan; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Investigaciones Fisiológicas y Ecológicas Vinculadas a la Agricultura. Universidad de Buenos Aires. Facultad de Agronomía. Instituto de Investigaciones Fisiológicas y Ecológicas Vinculadas a la Agricultura; Argentina
Fil: Nordenstahl, Marisa. Universidad Nacional de San Juan; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Aguiar, Martin Roberto. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Investigaciones Fisiológicas y Ecológicas Vinculadas a la Agricultura. Universidad de Buenos Aires. Facultad de Agronomía. Instituto de Investigaciones Fisiológicas y Ecológicas Vinculadas a la Agricultura; Argentina
Fil: Pucheta, Eduardo Raúl. Universidad Nacional de San Juan; Argentina
Materia
COMMUNITY ASSEMBLY
COMPETITION EXPERIMENT
CORRELATIONAL SELECTION
LEAF DRY MATTER CONTENT
LEAF SIZE
PHENOTYPIC SELECTION
PLANT–PLANT INTERACTIONS
QUADRATIC REGRESSION
SPECIFIC LEAF AREA
STABILISING SELECTION
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/148563

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oai_identifier_str oai:ri.conicet.gov.ar:11336/148563
network_acronym_str CONICETDig
repository_id_str 3498
network_name_str CONICET Digital (CONICET)
spelling Community-level natural selection modes: A quadratic framework to link multiple functional traits with competitive abilityRolhauser, Andrés GuillermoNordenstahl, MarisaAguiar, Martin RobertoPucheta, Eduardo RaúlCOMMUNITY ASSEMBLYCOMPETITION EXPERIMENTCORRELATIONAL SELECTIONLEAF DRY MATTER CONTENTLEAF SIZEPHENOTYPIC SELECTIONPLANT–PLANT INTERACTIONSQUADRATIC REGRESSIONSPECIFIC LEAF AREASTABILISING SELECTIONhttps://purl.org/becyt/ford/1.6https://purl.org/becyt/ford/1Research linking functional traits to competitive ability of coexisting species has largely relied on rectilinear correlations, yielding inconsistent results. Based on concepts borrowed from natural selection theory, we propose that trait?competition relationships can generally correspond to three univariate selection modes: directional (a rectilinear relationship), stabilising (an n-shaped relationship), and disruptive (a u-shaped relationship). Moreover, correlational selection occurs when two traits interact in determining competitive ability and lead to an optimum trait combination (i.e., a bivariate nonlinear selection mode). We tested our ideas using two independent datasets, each one characterising a group of species according to (a) their competitive effect on a target species in a pot experiment and (b) species-level values of well-known functional traits extracted from existing databases. The first dataset comprised 10 annual plant species frequent in a summer-rainfall desert in Argentina, while the second consisted of 37 herbaceous species from cool temperate vegetation types in Canada. Both experiments had a replacement design where the identity of neighbours was manipulated holding total plant density in pots constant. We modelled the competitive ability of neighbours (i.e., the log inverse of target plant biomass) as a function of traits using normal multiple regression. Leaf dry matter content (LDMC) was consistently subjected to negative directional selection in both experiments as well as to stabilising selection among temperate species. Leaf size was subjected to stabilising selection among desert species while among temperate species, leaf size underwent correlational selection in combination with specific leaf area (SLA): selection on SLA was negative directional for large-leaved species, while it was slightly positive for small-leaved species. Synthesis. Multiple quadratic regression adds functional flexibility to trait-based community ecology while providing a standardised basis for comparison among traits and environments. Our analyses of two datasets from contrasting environmental conditions indicate (a) that leaf dry matter content can capture an important component of plant competitive ability not accounted for by widely used competitive traits, such as specific leaf area, leaf size, and plant height and (b) that optimum relationships (either univariate or bivariate) between competitive ability and plant traits may be more common than previously realised.Fil: Rolhauser, Andrés Guillermo. Universidad Nacional de San Juan; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Investigaciones Fisiológicas y Ecológicas Vinculadas a la Agricultura. Universidad de Buenos Aires. Facultad de Agronomía. Instituto de Investigaciones Fisiológicas y Ecológicas Vinculadas a la Agricultura; ArgentinaFil: Nordenstahl, Marisa. Universidad Nacional de San Juan; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Aguiar, Martin Roberto. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Investigaciones Fisiológicas y Ecológicas Vinculadas a la Agricultura. Universidad de Buenos Aires. Facultad de Agronomía. Instituto de Investigaciones Fisiológicas y Ecológicas Vinculadas a la Agricultura; ArgentinaFil: Pucheta, Eduardo Raúl. Universidad Nacional de San Juan; ArgentinaWiley Blackwell Publishing, Inc2018-11-05info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/148563Rolhauser, Andrés Guillermo; Nordenstahl, Marisa; Aguiar, Martin Roberto; Pucheta, Eduardo Raúl; Community-level natural selection modes: A quadratic framework to link multiple functional traits with competitive ability; Wiley Blackwell Publishing, Inc; Journal of Ecology; 107; 3; 5-11-2018; 1457-14680022-0477CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/doi/10.1111/1365-2745.13094info:eu-repo/semantics/altIdentifier/url/https://besjournals.onlinelibrary.wiley.com/doi/10.1111/1365-2745.13094info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-29T10:17:31Zoai:ri.conicet.gov.ar:11336/148563instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-09-29 10:17:32.114CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Community-level natural selection modes: A quadratic framework to link multiple functional traits with competitive ability
title Community-level natural selection modes: A quadratic framework to link multiple functional traits with competitive ability
spellingShingle Community-level natural selection modes: A quadratic framework to link multiple functional traits with competitive ability
Rolhauser, Andrés Guillermo
COMMUNITY ASSEMBLY
COMPETITION EXPERIMENT
CORRELATIONAL SELECTION
LEAF DRY MATTER CONTENT
LEAF SIZE
PHENOTYPIC SELECTION
PLANT–PLANT INTERACTIONS
QUADRATIC REGRESSION
SPECIFIC LEAF AREA
STABILISING SELECTION
title_short Community-level natural selection modes: A quadratic framework to link multiple functional traits with competitive ability
title_full Community-level natural selection modes: A quadratic framework to link multiple functional traits with competitive ability
title_fullStr Community-level natural selection modes: A quadratic framework to link multiple functional traits with competitive ability
title_full_unstemmed Community-level natural selection modes: A quadratic framework to link multiple functional traits with competitive ability
title_sort Community-level natural selection modes: A quadratic framework to link multiple functional traits with competitive ability
dc.creator.none.fl_str_mv Rolhauser, Andrés Guillermo
Nordenstahl, Marisa
Aguiar, Martin Roberto
Pucheta, Eduardo Raúl
author Rolhauser, Andrés Guillermo
author_facet Rolhauser, Andrés Guillermo
Nordenstahl, Marisa
Aguiar, Martin Roberto
Pucheta, Eduardo Raúl
author_role author
author2 Nordenstahl, Marisa
Aguiar, Martin Roberto
Pucheta, Eduardo Raúl
author2_role author
author
author
dc.subject.none.fl_str_mv COMMUNITY ASSEMBLY
COMPETITION EXPERIMENT
CORRELATIONAL SELECTION
LEAF DRY MATTER CONTENT
LEAF SIZE
PHENOTYPIC SELECTION
PLANT–PLANT INTERACTIONS
QUADRATIC REGRESSION
SPECIFIC LEAF AREA
STABILISING SELECTION
topic COMMUNITY ASSEMBLY
COMPETITION EXPERIMENT
CORRELATIONAL SELECTION
LEAF DRY MATTER CONTENT
LEAF SIZE
PHENOTYPIC SELECTION
PLANT–PLANT INTERACTIONS
QUADRATIC REGRESSION
SPECIFIC LEAF AREA
STABILISING SELECTION
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.6
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv Research linking functional traits to competitive ability of coexisting species has largely relied on rectilinear correlations, yielding inconsistent results. Based on concepts borrowed from natural selection theory, we propose that trait?competition relationships can generally correspond to three univariate selection modes: directional (a rectilinear relationship), stabilising (an n-shaped relationship), and disruptive (a u-shaped relationship). Moreover, correlational selection occurs when two traits interact in determining competitive ability and lead to an optimum trait combination (i.e., a bivariate nonlinear selection mode). We tested our ideas using two independent datasets, each one characterising a group of species according to (a) their competitive effect on a target species in a pot experiment and (b) species-level values of well-known functional traits extracted from existing databases. The first dataset comprised 10 annual plant species frequent in a summer-rainfall desert in Argentina, while the second consisted of 37 herbaceous species from cool temperate vegetation types in Canada. Both experiments had a replacement design where the identity of neighbours was manipulated holding total plant density in pots constant. We modelled the competitive ability of neighbours (i.e., the log inverse of target plant biomass) as a function of traits using normal multiple regression. Leaf dry matter content (LDMC) was consistently subjected to negative directional selection in both experiments as well as to stabilising selection among temperate species. Leaf size was subjected to stabilising selection among desert species while among temperate species, leaf size underwent correlational selection in combination with specific leaf area (SLA): selection on SLA was negative directional for large-leaved species, while it was slightly positive for small-leaved species. Synthesis. Multiple quadratic regression adds functional flexibility to trait-based community ecology while providing a standardised basis for comparison among traits and environments. Our analyses of two datasets from contrasting environmental conditions indicate (a) that leaf dry matter content can capture an important component of plant competitive ability not accounted for by widely used competitive traits, such as specific leaf area, leaf size, and plant height and (b) that optimum relationships (either univariate or bivariate) between competitive ability and plant traits may be more common than previously realised.
Fil: Rolhauser, Andrés Guillermo. Universidad Nacional de San Juan; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Investigaciones Fisiológicas y Ecológicas Vinculadas a la Agricultura. Universidad de Buenos Aires. Facultad de Agronomía. Instituto de Investigaciones Fisiológicas y Ecológicas Vinculadas a la Agricultura; Argentina
Fil: Nordenstahl, Marisa. Universidad Nacional de San Juan; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Aguiar, Martin Roberto. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Investigaciones Fisiológicas y Ecológicas Vinculadas a la Agricultura. Universidad de Buenos Aires. Facultad de Agronomía. Instituto de Investigaciones Fisiológicas y Ecológicas Vinculadas a la Agricultura; Argentina
Fil: Pucheta, Eduardo Raúl. Universidad Nacional de San Juan; Argentina
description Research linking functional traits to competitive ability of coexisting species has largely relied on rectilinear correlations, yielding inconsistent results. Based on concepts borrowed from natural selection theory, we propose that trait?competition relationships can generally correspond to three univariate selection modes: directional (a rectilinear relationship), stabilising (an n-shaped relationship), and disruptive (a u-shaped relationship). Moreover, correlational selection occurs when two traits interact in determining competitive ability and lead to an optimum trait combination (i.e., a bivariate nonlinear selection mode). We tested our ideas using two independent datasets, each one characterising a group of species according to (a) their competitive effect on a target species in a pot experiment and (b) species-level values of well-known functional traits extracted from existing databases. The first dataset comprised 10 annual plant species frequent in a summer-rainfall desert in Argentina, while the second consisted of 37 herbaceous species from cool temperate vegetation types in Canada. Both experiments had a replacement design where the identity of neighbours was manipulated holding total plant density in pots constant. We modelled the competitive ability of neighbours (i.e., the log inverse of target plant biomass) as a function of traits using normal multiple regression. Leaf dry matter content (LDMC) was consistently subjected to negative directional selection in both experiments as well as to stabilising selection among temperate species. Leaf size was subjected to stabilising selection among desert species while among temperate species, leaf size underwent correlational selection in combination with specific leaf area (SLA): selection on SLA was negative directional for large-leaved species, while it was slightly positive for small-leaved species. Synthesis. Multiple quadratic regression adds functional flexibility to trait-based community ecology while providing a standardised basis for comparison among traits and environments. Our analyses of two datasets from contrasting environmental conditions indicate (a) that leaf dry matter content can capture an important component of plant competitive ability not accounted for by widely used competitive traits, such as specific leaf area, leaf size, and plant height and (b) that optimum relationships (either univariate or bivariate) between competitive ability and plant traits may be more common than previously realised.
publishDate 2018
dc.date.none.fl_str_mv 2018-11-05
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/148563
Rolhauser, Andrés Guillermo; Nordenstahl, Marisa; Aguiar, Martin Roberto; Pucheta, Eduardo Raúl; Community-level natural selection modes: A quadratic framework to link multiple functional traits with competitive ability; Wiley Blackwell Publishing, Inc; Journal of Ecology; 107; 3; 5-11-2018; 1457-1468
0022-0477
CONICET Digital
CONICET
url http://hdl.handle.net/11336/148563
identifier_str_mv Rolhauser, Andrés Guillermo; Nordenstahl, Marisa; Aguiar, Martin Roberto; Pucheta, Eduardo Raúl; Community-level natural selection modes: A quadratic framework to link multiple functional traits with competitive ability; Wiley Blackwell Publishing, Inc; Journal of Ecology; 107; 3; 5-11-2018; 1457-1468
0022-0477
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/doi/10.1111/1365-2745.13094
info:eu-repo/semantics/altIdentifier/url/https://besjournals.onlinelibrary.wiley.com/doi/10.1111/1365-2745.13094
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv Wiley Blackwell Publishing, Inc
publisher.none.fl_str_mv Wiley Blackwell Publishing, Inc
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
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