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Record W2747281842 · doi:10.1111/btp.12485

Crossing the (Wallace) line: local abundance and distribution of mammals across biogeographic barriers

2017· article· en· W2747281842 on OpenAlexafffund
Jedediah F. Brodie, Olga E. Helmy, Margaretha Pangau‐Adam, Giyarto Ugiek, Graden Froese, Alys Granados, Jayasilan Mohd‐Azlan, Henry Bernard, Anthony J. Giordano, Muhammad Agil, Abdul Haris Mustari

Bibliographic record

VenueBiotropica · 2017
Typearticle
Languageen
FieldEnvironmental Science
TopicWildlife Ecology and Conservation
Canadian institutionsUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of CanadaCanada Foundation for Innovation
KeywordsAbundance (ecology)EcologyMammalArchipelagoMalayBiologyGeographyBiodiversity

Abstract

fetched live from OpenAlex

Abstract Past and ongoing vertebrate introductions threaten to rearrange ecological communities in the Indo‐Malay Archipelago, one of Earth's most biodiverse regions. But the consequences of these translocations are difficult to predict. We compared local abundance and distributions in four tropical mammal lineages that have crossed from Asia to Wallacea or New Guinea. The local abundance of macaques ( Macaca spp.), which naturally crossed Wallace's Line, was higher in Sulawesi (east of the line; mean = 3.7 individuals per camera station, 95% CI = 2.2: 5.1) than in Borneo (west of the line; mean = 1.1, CI = 0.8: 1.4), but the local abundance of Malay civets ( Viverra tangalunga ), Rusa deer, and Sus pigs was similar in their native ranges and where they had been introduced by humans east of Wallace's Line. Proximity to rivers increased Malay Civet local abundance and decreased the local abundance of pigs in parts of their introduced ranges (Maluku and New Guinea, respectively), while having no effect on local abundance in their native ranges (Borneo) or other areas where they have been introduced (Sulawesi). That local abundance was higher east of Wallace's Line in just one of four mammal lineages is consistent with findings from plant invasions, where most species have similar abundance in their native and introduced ranges. However, species’ ecology may change as they enter new communities, for example, their patterns of abundance at local scales. This could make it difficult to predict community structure in the face of ongoing species introductions.

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 score0.007
Threshold uncertainty score0.991

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 studies0.0010.002
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 head0.009
GPT teacher head0.251
Teacher spread0.242 · 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

Citations16
Published2017
Admission routes2
Has abstractyes

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