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Record W2166386908 · doi:10.1139/z07-061

Effect of corridors on the movement behavior of the jumping spider <i>Phidippus princeps</i> (Araneae, Salticidae)

2007· article· en· W2166386908 on OpenAlexvenueno aff
Liv Baker

Bibliographic record

VenueCanadian Journal of Zoology · 2007
Typearticle
Languageen
FieldEnvironmental Science
TopicWildlife-Road Interactions and Conservation
Canadian institutionsnot available
Fundersnot available
KeywordsJumping spiderHabitatSpiderBiologyEcologyJumpingPredationGeography

Abstract

fetched live from OpenAlex

Corridors are a common conservation strategy intended to increase the spatial connectivity among isolated habitat patches. Corridors, however, are not always effective. This study demonstrates that corridors increase movement to new patches for the jumping spider Phidippus princeps (Peckham and Peckham, 1883) (Araneae, Salticidae), a visually oriented predator. I assigned spiders to one of three microlandscape treatments, created in an old field dominated by alsike clover ( Trifolium hybridum L.) and alfalfa ( Medicago sativa L.), in which patches were connected to (i) vegetated corridors and bare pathways, (ii) only vegetated corridors, and (iii) only bare pathways. The movement of P. princeps was effectively directed by corridors. When given a choice of paths, spiders invariably chose vegetated corridors over bare pathways to emigrate from and to immigrate to new patches. Spiders rarely moved between patches when only bare pathways were available. In the absence of corridors, P. princeps did not risk open ground to move to new habitat even though conspecific density was high. The corridors facilitated the interpatch movement of P. princeps, suggesting that P. princeps is restricted in its habitat use. Thus, a higher degree of spatial connectivity is likely to increase the exchange of individuals for species that are restricted in their movements by unsuitable habitat.

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)0.000
metaresearch head score (Gemma)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.008
GPT teacher head0.226
Teacher spread0.218 · 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

Citations12
Published2007
Admission routes1
Has abstractyes

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