Consistent functional clusters explain the effects of biodiversity on ecosystem productivity in a long-term experiment

Biomass production in ecosystems is a complex process regulated by several facets of biodiversity and species identity, but also species interactions such as competition or complementarity between species. For studying these different facets separately, ecosystem biomass is generally partitioned in two biodiversity effects. The composition effect is a simple, linear effect, and the interaction effect is a more subtle, nonlinear effect. Here we used a clustering approach (1) to separately and comprehensively capture all linear and nonlinear effects induced by both biodiversity effects on ecosystem functioning, and (2) to determine the functional composition at the origin of each biodiversity effect. We used data from the longterm Cedar Creek BioDIV experiment carried out over 22 yr, and we partitioned multiplicatively the biomass in composition and interaction effects. Both biodiversity effects were weakly correlated. Our clustering approach accurately explains and predicts each diversity effect over time: each one is modeled by a different functional composition. Even if environmental conditions and the strength of interaction effect strongly varied over time, the functional clusters of species that govern the interaction effect do not change over the 22 yr of the experiment. The functional composition governing the interaction effect is therefore very robust. In contrast, the functional clusters of species that govern the composition effect are less robust and change with environmental conditions. Understanding ecosystem functioning therefore requires that ecological properties are first partitioned by type, then each type of property is analyzed and modeled separately. Approaches without a priori groupings of species, such as functional clustering, appear particularly efficient and robust to unravel the web of species interactions, and identify the role played by species on biodiversity effects.

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Main Authors: Jaillard, Benoît, Deleporte, Philippe, Isbell, Forest, Loreau, Michel, Violle, Cyrille
Format: article biblioteca
Language:eng
Subjects:biodiversité, impact sur l'environnement, facteur du milieu, écosystème, biomasse, gouvernance, expérience de longue durée, http://aims.fao.org/aos/agrovoc/c_33949, http://aims.fao.org/aos/agrovoc/c_24420, http://aims.fao.org/aos/agrovoc/c_2594, http://aims.fao.org/aos/agrovoc/c_2482, http://aims.fao.org/aos/agrovoc/c_926, http://aims.fao.org/aos/agrovoc/c_37882, http://aims.fao.org/aos/agrovoc/c_4f8733aa,
Online Access:http://agritrop.cirad.fr/606246/
http://agritrop.cirad.fr/606246/1/606246.pdf
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spelling dig-cirad-fr-6062462024-01-29T06:10:46Z http://agritrop.cirad.fr/606246/ http://agritrop.cirad.fr/606246/ Consistent functional clusters explain the effects of biodiversity on ecosystem productivity in a long-term experiment. Jaillard Benoît, Deleporte Philippe, Isbell Forest, Loreau Michel, Violle Cyrille. 2021. Ecology, 102 (9):e03441, 13 p.https://doi.org/10.1002/ecy.3441 <https://doi.org/10.1002/ecy.3441> Consistent functional clusters explain the effects of biodiversity on ecosystem productivity in a long-term experiment Jaillard, Benoît Deleporte, Philippe Isbell, Forest Loreau, Michel Violle, Cyrille eng 2021 Ecology biodiversité impact sur l'environnement facteur du milieu écosystème biomasse gouvernance expérience de longue durée http://aims.fao.org/aos/agrovoc/c_33949 http://aims.fao.org/aos/agrovoc/c_24420 http://aims.fao.org/aos/agrovoc/c_2594 http://aims.fao.org/aos/agrovoc/c_2482 http://aims.fao.org/aos/agrovoc/c_926 http://aims.fao.org/aos/agrovoc/c_37882 http://aims.fao.org/aos/agrovoc/c_4f8733aa Biomass production in ecosystems is a complex process regulated by several facets of biodiversity and species identity, but also species interactions such as competition or complementarity between species. For studying these different facets separately, ecosystem biomass is generally partitioned in two biodiversity effects. The composition effect is a simple, linear effect, and the interaction effect is a more subtle, nonlinear effect. Here we used a clustering approach (1) to separately and comprehensively capture all linear and nonlinear effects induced by both biodiversity effects on ecosystem functioning, and (2) to determine the functional composition at the origin of each biodiversity effect. We used data from the longterm Cedar Creek BioDIV experiment carried out over 22 yr, and we partitioned multiplicatively the biomass in composition and interaction effects. Both biodiversity effects were weakly correlated. Our clustering approach accurately explains and predicts each diversity effect over time: each one is modeled by a different functional composition. Even if environmental conditions and the strength of interaction effect strongly varied over time, the functional clusters of species that govern the interaction effect do not change over the 22 yr of the experiment. The functional composition governing the interaction effect is therefore very robust. In contrast, the functional clusters of species that govern the composition effect are less robust and change with environmental conditions. Understanding ecosystem functioning therefore requires that ecological properties are first partitioned by type, then each type of property is analyzed and modeled separately. Approaches without a priori groupings of species, such as functional clustering, appear particularly efficient and robust to unravel the web of species interactions, and identify the role played by species on biodiversity effects. article info:eu-repo/semantics/article Journal Article info:eu-repo/semantics/publishedVersion http://agritrop.cirad.fr/606246/1/606246.pdf text Cirad license info:eu-repo/semantics/restrictedAccess https://agritrop.cirad.fr/mention_legale.html https://doi.org/10.1002/ecy.3441 10.1002/ecy.3441 info:eu-repo/semantics/altIdentifier/doi/10.1002/ecy.3441 info:eu-repo/semantics/altIdentifier/purl/https://doi.org/10.1002/ecy.3441 info:eu-repo/semantics/dataset/purl/https://doi.org/10.15454/DD9J5T info:eu-repo/grantAgreement/EC/H2020/ANR-10-LABX-0001//(FRA) Agricultural Sciences for sustainable Development/AGRO info:eu-repo/grantAgreement/ERC/H2020/ANR-10-LABX-0001//(FRA) Agricultural Sciences for sustainable Development/AGRO
institution CIRAD FR
collection DSpace
country Francia
countrycode FR
component Bibliográfico
access En linea
databasecode dig-cirad-fr
tag biblioteca
region Europa del Oeste
libraryname Biblioteca del CIRAD Francia
language eng
topic biodiversité
impact sur l'environnement
facteur du milieu
écosystème
biomasse
gouvernance
expérience de longue durée
http://aims.fao.org/aos/agrovoc/c_33949
http://aims.fao.org/aos/agrovoc/c_24420
http://aims.fao.org/aos/agrovoc/c_2594
http://aims.fao.org/aos/agrovoc/c_2482
http://aims.fao.org/aos/agrovoc/c_926
http://aims.fao.org/aos/agrovoc/c_37882
http://aims.fao.org/aos/agrovoc/c_4f8733aa
biodiversité
impact sur l'environnement
facteur du milieu
écosystème
biomasse
gouvernance
expérience de longue durée
http://aims.fao.org/aos/agrovoc/c_33949
http://aims.fao.org/aos/agrovoc/c_24420
http://aims.fao.org/aos/agrovoc/c_2594
http://aims.fao.org/aos/agrovoc/c_2482
http://aims.fao.org/aos/agrovoc/c_926
http://aims.fao.org/aos/agrovoc/c_37882
http://aims.fao.org/aos/agrovoc/c_4f8733aa
spellingShingle biodiversité
impact sur l'environnement
facteur du milieu
écosystème
biomasse
gouvernance
expérience de longue durée
http://aims.fao.org/aos/agrovoc/c_33949
http://aims.fao.org/aos/agrovoc/c_24420
http://aims.fao.org/aos/agrovoc/c_2594
http://aims.fao.org/aos/agrovoc/c_2482
http://aims.fao.org/aos/agrovoc/c_926
http://aims.fao.org/aos/agrovoc/c_37882
http://aims.fao.org/aos/agrovoc/c_4f8733aa
biodiversité
impact sur l'environnement
facteur du milieu
écosystème
biomasse
gouvernance
expérience de longue durée
http://aims.fao.org/aos/agrovoc/c_33949
http://aims.fao.org/aos/agrovoc/c_24420
http://aims.fao.org/aos/agrovoc/c_2594
http://aims.fao.org/aos/agrovoc/c_2482
http://aims.fao.org/aos/agrovoc/c_926
http://aims.fao.org/aos/agrovoc/c_37882
http://aims.fao.org/aos/agrovoc/c_4f8733aa
Jaillard, Benoît
Deleporte, Philippe
Isbell, Forest
Loreau, Michel
Violle, Cyrille
Consistent functional clusters explain the effects of biodiversity on ecosystem productivity in a long-term experiment
description Biomass production in ecosystems is a complex process regulated by several facets of biodiversity and species identity, but also species interactions such as competition or complementarity between species. For studying these different facets separately, ecosystem biomass is generally partitioned in two biodiversity effects. The composition effect is a simple, linear effect, and the interaction effect is a more subtle, nonlinear effect. Here we used a clustering approach (1) to separately and comprehensively capture all linear and nonlinear effects induced by both biodiversity effects on ecosystem functioning, and (2) to determine the functional composition at the origin of each biodiversity effect. We used data from the longterm Cedar Creek BioDIV experiment carried out over 22 yr, and we partitioned multiplicatively the biomass in composition and interaction effects. Both biodiversity effects were weakly correlated. Our clustering approach accurately explains and predicts each diversity effect over time: each one is modeled by a different functional composition. Even if environmental conditions and the strength of interaction effect strongly varied over time, the functional clusters of species that govern the interaction effect do not change over the 22 yr of the experiment. The functional composition governing the interaction effect is therefore very robust. In contrast, the functional clusters of species that govern the composition effect are less robust and change with environmental conditions. Understanding ecosystem functioning therefore requires that ecological properties are first partitioned by type, then each type of property is analyzed and modeled separately. Approaches without a priori groupings of species, such as functional clustering, appear particularly efficient and robust to unravel the web of species interactions, and identify the role played by species on biodiversity effects.
format article
topic_facet biodiversité
impact sur l'environnement
facteur du milieu
écosystème
biomasse
gouvernance
expérience de longue durée
http://aims.fao.org/aos/agrovoc/c_33949
http://aims.fao.org/aos/agrovoc/c_24420
http://aims.fao.org/aos/agrovoc/c_2594
http://aims.fao.org/aos/agrovoc/c_2482
http://aims.fao.org/aos/agrovoc/c_926
http://aims.fao.org/aos/agrovoc/c_37882
http://aims.fao.org/aos/agrovoc/c_4f8733aa
author Jaillard, Benoît
Deleporte, Philippe
Isbell, Forest
Loreau, Michel
Violle, Cyrille
author_facet Jaillard, Benoît
Deleporte, Philippe
Isbell, Forest
Loreau, Michel
Violle, Cyrille
author_sort Jaillard, Benoît
title Consistent functional clusters explain the effects of biodiversity on ecosystem productivity in a long-term experiment
title_short Consistent functional clusters explain the effects of biodiversity on ecosystem productivity in a long-term experiment
title_full Consistent functional clusters explain the effects of biodiversity on ecosystem productivity in a long-term experiment
title_fullStr Consistent functional clusters explain the effects of biodiversity on ecosystem productivity in a long-term experiment
title_full_unstemmed Consistent functional clusters explain the effects of biodiversity on ecosystem productivity in a long-term experiment
title_sort consistent functional clusters explain the effects of biodiversity on ecosystem productivity in a long-term experiment
url http://agritrop.cirad.fr/606246/
http://agritrop.cirad.fr/606246/1/606246.pdf
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AT loreaumichel consistentfunctionalclustersexplaintheeffectsofbiodiversityonecosystemproductivityinalongtermexperiment
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