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Record W2849233339 · doi:10.1177/1940082918787376

Restoration Provides Hope for Faunal Recovery: Changes in Primate Abundance Over 45 Years in Kibale National Park, Uganda

2018· article· en· W2849233339 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

VenueTropical Conservation Science · 2018
Typearticle
Languageen
FieldPsychology
TopicPrimate Behavior and Ecology
Canadian institutionsMcGill University
Fundersnot available
KeywordsNational parkClearanceAbundance (ecology)Old-growth forestSecondary forestEcologyTropical forestPrimateHabitatPopulationNational forestGeographyAgroforestryHabitat destructionTropicsForest restorationBiologyForest ecologyForestryEcosystem

Abstract

fetched live from OpenAlex

In much of the tropics, the proportion of the land covered by regenerating forest surpasses than in primary forest, thus protecting regenerating forest could offer a valuable conservation opportunity, but only if those lands promote faunal recovery. Chapman et al. documented the recovery of populations of six primate species over up to 45 years in Kibale National Park, Uganda and discovered that in preexisting forest, populations of all species grew, except blue monkeys. Populations (except blue monkeys) also increased by colonizing regenerating forests at previously cleared sites. In many cases, populations in these regenerating areas were of comparable size to those in old-growth forest, and there was little evidence that this population increase corresponded with a decline in neighboring old-growth forests. This research demonstrates the potential for management of regenerating forest to be an effective conservation tool and illustrates the importance of conducting and funding long-term monitoring.

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 score0.044
Threshold uncertainty score0.367

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.078
GPT teacher head0.390
Teacher spread0.312 · 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