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Record W2534635194 · doi:10.1093/biosci/biw134

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

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

Bibliographic record

VenueBioScience · 2016
Typearticle
Languageen
FieldEnvironmental Science
TopicEcology and Vegetation Dynamics Studies
Canadian institutionsMcGill University
Fundersnot available
KeywordsTraitEcologyBiologyGeographyEvolutionary biologyComputer science

Abstract

fetched live from 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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.074
metaresearch head score (Gemma)0.063
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.074
Threshold uncertainty score0.393

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0740.063
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0080.003
Bibliometrics0.0040.003
Science and technology studies0.0040.048
Scholarly communication0.0150.050
Open science0.0070.010
Research integrity0.0160.030
Insufficient payload (model declined to judge)0.0130.002

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.022
GPT teacher head0.236
Teacher spread0.213 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations1
Published2016
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