Linking epigenetics and biological conservation: Towards a <i>conservation epigenetics</i> perspective
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
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.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it