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Record W2965553517 · doi:10.1111/1365-2435.13429

Linking epigenetics and biological conservation: Towards a <i>conservation epigenetics</i> perspective

2019· article· en· W2965553517 on OpenAlexaff
Olivier Rey, Christophe Eizaguirre, Bernard Angers, Miguel Baltazar‐Soares, Κostas Sagonas, Jérôme G. Prunier, Simon Blanchet

Bibliographic record

VenueFunctional Ecology · 2019
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicEpigenetics and DNA Methylation
Canadian institutionsUniversité de Montréal
FundersAgence Nationale de la Recherche
KeywordsEpigeneticsBiologyBiodiversityConservation psychologyConservation biologyEpigenomeEcologyDNA methylationAdaptation (eye)Environmental resource managementEvolutionary biologyGeneticsNeuroscienceGene

Abstract

fetched live from OpenAlex

Abstract Biodiversity conservation is a global issue where the challenge is to integrate all levels of biodiversity to ensure the long‐term evolutionary potential and resilience of biological systems. Genetic approaches have largely contributed to conservation biology by defining “conservation entities” accounting for their evolutionary history and adaptive potential, the so‐called evolutionary significant units (ESUs). Yet, these approaches only loosely integrate the short‐term ecological history of organisms. Here, we argue that epigenetic variation, and more particularly DNA methylation, represents a molecular component of biodiversity that directly links the genome to the environment. As such, it provides the required information on the ecological background of organisms for an integrative field of conservation biology. We synthesize knowledge about the importance of epigenetic mechanisms in (a) orchestrating fundamental development alternatives in organisms, (b) enabling individuals to respond in real‐time to selection pressures and (c) improving ecosystem stability and functioning. Using practical examples in conservation biology, we illustrate the relevance of DNA methylation (a) as biomarkers of past and present environmental stress events as well as biomarkers of physiological conditions of individuals; (b) for documenting the ecological structuring/clustering of wild populations and hence for better integrating ecology into ESUs; (c) for improving conservation translocations; and (d) for studying landscape functional connectivity. We conclude that an epigenetic conservation perspective will provide environmental managers the possibility to refine ESUs, to set conservation plans taking into account the capacity of organisms to rapidly cope with environmental changes, and hence to improve the conservation of wild populations. A free Plain Language Summary can be found within the Supporting Information of this article.

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)0.005
metaresearch head score (Gemma)0.004
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: Empirical · Consensus signal: none
Teacher disagreement score0.006
Threshold uncertainty score0.027

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0010.014
Scholarly communication0.0060.008
Open science0.0010.005
Research integrity0.0040.006
Insufficient payload (model declined to judge)0.0050.001

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 head0.021
GPT teacher head0.249
Teacher spread0.228 · 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
GenreEmpirical

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".

Quick stats

Citations123
Published2019
Admission routes1
Has abstractyes

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