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Record W2274652769 · doi:10.1186/s13104-015-1797-1

Molecular forensics in avian conservation: a DNA-based approach for identifying mammalian predators of ground-nesting birds and eggs

2016· article· en· W2274652769 on OpenAlex
Matthew W. Hopken, Elizabeth K. Orning, Julie K. Young, Antoinette J. Piaggio

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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueBMC Research Notes · 2016
Typearticle
Languageen
FieldEnvironmental Science
TopicEnvironmental DNA in Biodiversity Studies
Canadian institutionsnot available
FundersNational Wildlife Research CenterU.S. Department of Agriculture
KeywordsPredationEndangered speciesBiologyPredatorNest (protein structural motif)ZoologyThreatened speciesEcologyHabitat

Abstract

fetched live from OpenAlex

BACKGROUND: The greater sage-grouse (Centrocercus urophasianus) is a ground-nesting bird from the Northern Rocky Mountains and a species at risk of extinction in in multiple U.S. states and Canada. Herein we report results from a proof of concept that mitochondrial and nuclear DNAs from mammalian predator saliva could be non-invasively collected from depredated greater sage-grouse eggshells and carcasses and used for predator species identification. Molecular forensic approaches have been applied to identify predators from depredated remains as one strategy to better understand predator-prey dynamics and guide management strategies. This can aid conservation efforts by correctly identifying predators most likely to impact threatened and endangered species. DNA isolated from non-invasive samples around nesting sites (e.g. fecal or hair samples) is one method that can increase the success and accuracy of predator species identification when compared to relying on nest remains alone. RESULTS: Predator saliva DNA was collected from depredated eggshells and carcasses using swabs. We sequenced two partial fragments of two mitochondrial genes and obtained microsatellite genotypes using canid specific primers for species and individual identification, respectively. Using this multilocus approach we were able to identify predators, at least down to family, from 11 out of 14 nests (79%) and three out of seven carcasses (47%). Predators detected most frequently were canids (86%), while other taxa included rodents, a striped skunk, and cattle. We attempted to match the genotypes of individual coyotes obtained from eggshells and carcasses with those obtained from fecal samples and coyotes collected in the areas, but no genotype matches were found. CONCLUSION: Predation is a main cause of nest failure in ground-nesting birds and can impact reproduction and recruitment. To inform predator management for ground-nesting bird conservation, accurate identification of predator species is necessary. Considering predation can have a high impact on recruitment, predation events are very difficult to observe, and predator species are difficult to identify visually from nest remains, molecular approaches that reduce the need to observe or handle animals offer an additional tool to better understand predator-prey dynamics at nesting sites.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.045
Threshold uncertainty score0.378

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.145
GPT teacher head0.345
Teacher spread0.200 · 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