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Enregistrement W2534635194 · doi:10.1093/biosci/biw134

A Coming of Age for the Trait-Based Approach in Plant Ecology

2016· article· en· W2534635194 sur OpenAlexaff
Martin J. Lechowicz

Notice bibliographique

RevueBioScience · 2016
Typearticle
Langueen
DomaineEnvironmental Science
ThématiqueEcology and Vegetation Dynamics Studies
Établissements canadiensMcGill University
Organismes subventionnairesnon disponible
Mots-clésTraitEcologyBiologyGeographyEvolutionary biologyComputer science

Résumé

récupéré en direct d'OpenAlex

Eric Garnier, at the Centre d'Ecologie Fonctionnelle et Evolutive (the premier French research institute in plant ecology), and Marie-Laure Navas, at Montpellier SupAgro (the French National Institute of Higher Education in Agricultural Sciences), have a long-standing and productive collaboration. They published a French-language monograph in 2013 on plant functional diversity. The present book, coauthored with Karl Grigulis, from the Université Joseph Fourier in Grenoble, is a ­significantly revised and updated translation of their original monograph. The book marks a coming of age for the trait-based approach in plant ecology, providing a concise summary of developments in the field as it has rapidly taken hold in the past decade. The trait-based approach follows from the premise that a focus on variation in the traits of plants can yield deeper insights into the scaling of function from individual plants to communities and ecosystems than can a simple tally of species diversity. In a sense, this book is a revision of the history of all plant ecology viewed through the prism of the trait-based perspective that breaks species into their functional parts. Themes come into discussion that can be traced back to nineteenth-century studies of plant form and function in Andreas Schimper's 1898 Pflanzengeographie auf Physiologischer Grundlage, but the traditional focus on comparisons among species is set aside in favor of an emphasis on the response of selected “functional traits” to environmental conditions and the consequent effects at the level of communities and ecosystems. An emphasis on traits over species certainly is not alien to biologists; it figures centrally in studies of evolutionary adaptation, quantitative genetics, and somewhat ironically in the context of the trait-based perspective, taxonomy. In these disciplines, any discussion of species is filtered through the study of variation in the characteristics of individuals. Taxonomists seek traits that are stable under individual and environmental variation, hence providing reliable markers of species identity. Conversely, evolutionary biologists identify the values of a trait that are differentially favored in an environment and the degree to which favored variation in traits is heritable and therefore subject to natural selection. In the context of evolutionary biology, the trait-based approach in functional ecology opens a path to a novel synthesis, with recent developments in both community ecology (Vellend 2016) and ecoevolutionary dynamics (Hendry 2016). For the moment, that potential is somewhat limited by a lack of data, because trait-based analyses draw largely on only mean trait values even though functional responses along environmental gradients are expressed through not only interspecific but also intraspecific trait variation. Trait data are compiled as species means from an eclectic mix of past studies using reasonably well-standardized methods but with considerable disparity in associated metadata on growing conditions, plant age, and other ­factors that can influence trait values. Most of the collated studies also report only one or a few traits, making it difficult to assess the coordinated interactions among a suite of traits affecting a particular function, such as establishment, growth, or fecundity. The authors recognize these limitations of available trait data and provide both a review of the existing compilations and an authoritative summary of ways to strengthen the database on which the trait-based approach depends. Despite the constraints imposed by the presently available data, the trait-based approach has established the existence of broadly consistent ­tradeoff relationships among traits that serve as markers of key plant functions. The most definitive of these is a trade-off between the construction cost of leaves and their rates of carbon gain (Wright et al. 2004), the trigger for a burgeoning literature on the intrinsic architecture of plant function (Reich 2014, Diaz et al. 2016). This book effectively summarizes the functional ecology that inspired the trait-based approach and then turns to the question of whether an understanding of how traits affect plant function can in turn reveal aspects of community assembly and ecosystem function. Patterns of abundance-weighted trait values of the species constituting a community are shown to provide insights into the degree to which abiotic versus biotic factors affect community assembly, as well as the degree to which dominance versus complementarity effects influence ecosystem properties and the provision of ecosystem services. A chapter on the management of rangeland and crop ecosystems nicely illustrates the reciprocal utilitarian and scientific value of the trait-based approach to plant functional diversity. Finally, a closing chapter on future prospects for plant functional diversity touches on perhaps one of the more exciting paths forward in the trait-based approach: trait driver theory (Enquist et al. 2015), which uses the frequency distribution of traits to predict shifts in community composition and ecosystem function in response to environmental change. In conclusion, this book lays out with impressive clarity, depth, and breadth the conceptual framework of plant functional diversity as it stands today. The central ideas of the trait-based approach are firmly in place, rooted in the comparative ecology of species but consistently focused on trait variation and its effects on community assembly and ecosystem function. The review of relevant ­literature is selective but broadly representative, informatively blending European and Anglo-American perspectives on plant function. It is clear that the trait-based approach is not yet fully formed—the available trait database is a work in progress, and there are unresolved issues even in the nature of traits and their relationship to function—but the authors do a good job laying out the ambiguities and uncertainties of the approach, providing a well-referenced summary of the key issues. The book provides a definitive reading for a graduate-level seminar on plant functional diversity and an excellent desk reference for any biologist interested in the evolutionary and ecological implications of trait variation. Garnier, Navas, and Grigulis have laid an admirably solid foundation for the lines of inquiry that will lead to the maturation of the trait-based approach and its integration into a larger synthesis of ecological and evolutionary theory.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,074
score de la tête « metaresearch » (Gemma)0,063
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Théorique ou conceptuel · Signal consensuel: Théorique ou conceptuel
GenreSignal candidat: Synthèse · Signal consensuel: aucune
Score de désaccord entre enseignants0,074
Score d'incertitude au seuil0,393

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0740,063
Méta-épidémiologie (sens strict)0,0020,001
Méta-épidémiologie (sens large)0,0080,003
Bibliométrie0,0040,003
Études des sciences et des technologies0,0040,048
Communication savante0,0150,050
Science ouverte0,0070,010
Intégrité de la recherche0,0160,030
Charge utile insuffisante (le modèle a refusé de juger)0,0130,002

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,022
Tête enseignante GPT0,236
Écart entre enseignants0,213 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeThéorique ou conceptuel
Domainenon disponible
GenreSynthèse

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations1
Publié2016
Routes d'admission1
Résumé présentnon

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