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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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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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 |
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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 |
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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 |
work_keys_str_mv |
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_version_ |
1792500623128657920 |