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Record W2201068657 · doi:10.1111/ddi.12387

Bridging the gap: a genetic assessment framework for population‐level threatened plant conservation prioritization and decision‐making

2015· article· en· W2201068657 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueDiversity and Distributions · 2015
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetic diversity and population structure
Canadian institutionsDepartment of Environment and Conservation
FundersDepartment of Environment and Water
KeywordsThreatened speciesGenetic diversityConservation geneticsPopulationEnvironmental resource managementEcologyBiologyEnvironmental science

Abstract

fetched live from OpenAlex

Abstract Aim Maintaining genetic diversity and evolutionary processes are important goals in plant conservation. Genetic studies are increasingly undertaken but results from such studies are still rarely implemented as management actions in the field. We address this ‘research‐implementation gap’ by developing a plain‐language genetic assessment approach for population‐level conservation prioritization based on measurement of key genetic parameters. Our aim was to improve understanding between conservation researchers and practitioners, enabling practitioners to incorporate genetic information into conservation actions and conservation genetic researchers to address research explicitly resulting in conservation action. Location Applicable globally. Methods We derived a decision‐making framework that identifies appropriate management strategies for threatened populations based on the level of genetic differentiation ( F ST ), genetic diversity (expected heterozygosity, H E ) and inbreeding ( F IS ), characterized as ‘high’ or ‘low’ in comparison with a reference benchmark. We demonstrate the application of the framework in two case studies of threatened plants and more broadly from the literature. Results Applying the decision framework, we found that for Prostanthera eurybioides, the population of conservation concern does not currently require specialized genetic management and mitigation of ecological threats should be prioritized instead. For Allocasuarina robusta , we found connectivity was high and strategies should be put in place to maintain gene flow. In both cases, genetic information was important for designing restocking strategies accounting for the genetic structure and genetic diversity of source and recipient populations. From the literature, key examples of species types that fit each of the genetic management scenarios are given. Main conclusions We find that the application of our simplified genetic assessment framework helps to clarify management actions based on conservation genetic information for threatened flora, and should assist in bridging the gap between researchers and conservation practitioners for integrated conservation outcomes. Our framework could equally apply to fauna conservation with appropriate consideration of animal‐specific management issues.

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.417
Threshold uncertainty score0.930

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.058
GPT teacher head0.301
Teacher spread0.243 · 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