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Record W3027136168 · doi:10.1111/csp2.203

The Protected Area Paradox and refugee species: The giant panda and baselines shifted towards conserving species in marginal habitats

2020· article· en· W3027136168 on OpenAlexaff
Graham I. H. Kerley, Mariska te Beest, Joris P. G. M. Cromsigt, Daniel Pauly, Susanne Shultz

Bibliographic record

VenueConservation Science and Practice · 2020
Typearticle
Languageen
FieldEnvironmental Science
TopicSpecies Distribution and Climate Change
Canadian institutionsUniversity of British ColumbiaFisheries and Oceans Canada
Fundersnot available
KeywordsThreatened speciesHabitatRefugeeEcologyGeographyHabitat destructionConservation statusProtected areaBiology

Abstract

fetched live from OpenAlex

Abstract Paradoxically, despite the growth in protected areas globally, many species remain threatened and continue to decline. Attempts to conserve species in suboptimal habitats (i.e., as refugee species) may in part explain this Protected Area Paradox. Refugee species yield poor conservation outcomes as they suffer lower densities and fitness. We suggest that the giant panda may serve as an iconic example, reflecting the contraction and shift in the giant panda's range, diet and habitat use over the past 3,500 years, coinciding with increasing human pressure, and now maintained by conservation efforts, this due to shifted baselines. The global bias of protected area location to less productive habitats indicates that this problem may be widespread. We urgently need efforts to identify victims of refugee species status to allow improved conservation management globally, reducing the paradoxical outcomes of our conservation efforts.

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)0.002
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.006
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.006
Scholarly communication0.0020.002
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0050.000

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 head0.090
GPT teacher head0.296
Teacher spread0.205 · 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 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

Citations39
Published2020
Admission routes1
Has abstractyes

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