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Record W2980919312 · doi:10.1007/s10531-019-01866-w

Evidence of a further emerging threat to lion conservation; targeted poaching for body parts

2019· article· en· W2980919312 on OpenAlexfundno aff
Kristoffer T. Everatt, Rae Kokés, Charlaine Pereira

Bibliographic record

VenueBiodiversity and Conservation · 2019
Typearticle
Languageen
FieldEnvironmental Science
TopicWildlife Ecology and Conservation
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of CanadaU.S. Fish and Wildlife ServiceNelson Mandela UniversityNational Geographic SocietyPanthera
KeywordsPoachingPantheraThreatened speciesBushmeatGeographyHabitat destructionLivestockTrophyBiodiversityNational parkPopulationEcologyFisheryHabitatPredationWildlifeBiologyArchaeologyForestry

Abstract

fetched live from OpenAlex

Abstract The African lion, Panthera leo , has, like many of the world’s megafauna, become threatened with extinction over the past century. Loss of habitat and prey, persecution in retaliation of livestock depredation, by-catch by bushmeat poachers and unsustainable trophy hunting are all documented anthropogenic caused threats to lion conservation. Here we present data that indicate the emergence of a further threat to lion conservation: the targeted poaching of lions for body parts. We present lion abundance and mortality data from field surveys in southern Africa between 2011 and 2018 of a resident lion population. The targeted poaching of lions for body parts accounted for 35% of known human caused mortalities across the landscape and 61% of mortalities within Limpopo National Park with a clear increase in this pressure in 2014. Retaliatory killing for livestock conflict accounted for 51% of total mortalities, however in 48% of conflict cases body parts were also removed, suggesting that a demand for body parts may incentivize conflict related killing of lions. The use of poison was the most common means of killing lions and was recorded in 61% of mortalities. Teeth and claws were the body parts harvested most often from illegally killed animals in the study area, with an increase from 2014 onwards. This pressure threatens the viability of the species in our study area and the success of current conservation initiatives. We suggest that the results of this study be viewed as a warning to the global conservation community to be vigilant of the impact that illegal wildlife trade can have on the conservation of lions, just as a similar pressure has already had on other big cat populations.

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 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 score0.011
Threshold uncertainty score0.500

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 studies0.0000.000
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 head0.027
GPT teacher head0.228
Teacher spread0.201 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations56
Published2019
Admission routes1
Has abstractyes

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