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Record W3127352398 · doi:10.1111/aje.12844

Distribution of the critically endangered Coquerel's sifaka (<i>Propithecus coquereli</i>) across a fragmented landscape in NW Madagascar

2021· article· en· W3127352398 on OpenAlexafffund
Miarisoa L. Ramilison, Bertrand Andriatsitohaina, Coral Chell, Romule Rakotondravony, Ute Radespiel, Malcolm S. Ramsay

Bibliographic record

VenueAfrican Journal of Ecology · 2021
Typearticle
Languageen
FieldPsychology
TopicPrimate Behavior and Ecology
Canadian institutionsUniversity of Toronto
FundersUniversity of TorontoBundesministerium für Bildung und ForschungNottingham Trent University
KeywordsGeographyDeforestation (computer science)Critically endangeredEcologyRainforestHabitatEndangered speciesDisturbance (geology)Habitat destructionFragmentation (computing)Biology

Abstract

fetched live from OpenAlex

Abstract Habitat loss and fragmentation affect species occurrence and distribution in rapidly changing ecosystems. These issues are especially relevant on the Island of Madagascar where modern deforestation has been widespread and is ongoing. We investigated the occurrence of the critically endangered Coquerel's sifaka ( Propithecus coquereli ) in an anthropogenically modified landscape: the Mariarano region of north‐western Madagascar. We surveyed four large forest sites from 500 to 5,000 ha and 16 forest fragments ranging from 1.5 to 19.2 ha in size. We recorded various attributes of the visited sites such as area, distance to nearest large forest and anthropogenic disturbance. We encountered sifakas in 10 of 16 fragments and in all large forest sites, with the majority of encounters occurring in habitat edge zones. Furthermore, we encountered 19 sifakas in the matrix such as in villages and fields. We found that neither human disturbance, area nor distance to a large forest predicts the presence of sifakas in the Mariarano region. Our results suggest that Coquerel's sifakas are able to persist in highly degraded and small forests fragments, but further research is needed on their long‐term viability in anthropogenically modified landscapes.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.027
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.016
GPT teacher head0.301
Teacher spread0.285 · 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.

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

Citations10
Published2021
Admission routes2
Has abstractyes

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