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Testing the importance of patch scale on forest birds

2005· article· en· W2101770466 on OpenAlexaff
Kai M. A. Chan, Jai Ranganathan

Bibliographic record

VenueOikos · 2005
Typearticle
Languageen
FieldEnvironmental Science
TopicAvian ecology and behavior
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsHabitatAbundance (ecology)Population densityEcologyDensity dependenceRelative species abundanceNull hypothesisPopulationRobustness (evolution)Null modelGeographyBiologyStatisticsMathematics

Abstract

fetched live from OpenAlex

The relationship between population density and habitat area is of central importance to conservation biology, particularly for species dependent on declining habitat. A recent study by Lee et al. in Oikos in 2002 found that the densities of three forest interior bird species (ovenbirds, wood thrushes, and red‐eyed vireos) decline with increasing patch size, contradicting many other studies that demonstrate a positive correlation between area and density for these species. The authors’ argument is based on a misapplied criticism of the prevailing approach based on density‐and on an inappropriate statistical methodology, caused by incorrect specification of the null hypothesis after log–transformation. We use three different methods of testing area‐dependence: a corrected log–abundance log–area regression; a similar abundance–area regression; and the prevailing density‐area approach. For each species, all three methods agree broadly, suggesting the robustness of each approach. For ovenbirds and wood thrushes, we do not find that population density is negatively correlated to patch size. While our analyses of the red‐eyed vireo data find a negative correlation between the two factors, the strength of the correlation is far weaker than that of Lee et al. and may derive from landscape factors unconsidered in the original data. Nevertheless, we do not find positive density–area relationships for any of these forest‐interior species, further underscoring the site‐specificity of the underlying mechanisms of area‐ sensitivity.

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 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 score0.016
Threshold uncertainty score1.000

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)0.0010.001

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 head0.018
GPT teacher head0.242
Teacher spread0.224 · 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

Citations6
Published2005
Admission routes1
Has abstractyes

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