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Record W2891885515 · doi:10.1139/facets-2018-0007

Small to large-scale patterns of ground-dwelling spider (Araneae) diversity across northern Canada

2018· article· en· W2891885515 on OpenAlexaffvenueabout
Sarah Loboda, Christopher M. Buddle

Bibliographic record

VenueFACETS · 2018
Typearticle
Languageen
FieldEnvironmental Science
TopicSpecies Distribution and Climate Change
Canadian institutionsMcGill University
Fundersnot available
KeywordsGeographySpiderEcologyBiodiversitySpecies richnessBiological dispersalSpatial ecologyArcticGamma diversityMetacommunityBorealSpecies diversityLatitudeBeta diversityPhysical geographyBiologyPopulation

Abstract

fetched live from OpenAlex

We examined how Arctic spider (Araneae) biodiversity is distributed at multiple spatial scales in northern Canada using a standardized hierarchical sampling design. We investigated which drivers, environmental or spatial, influence the patterns observed. Spatial patterns of Arctic spider species richness and composition were assessed in 12 sites located in arctic, subarctic, and north boreal ecoclimatic regions, spanning 30 degrees of latitude and 80 degrees of longitude. Variation in diversity was partitioned in relation to multiple environmental and spatial drivers of diversity patterns. Over 23 000 adult spiders, representing 306 species in 14 families, were collected in northern Canada, with 107 species (35% of the total species collected) representing new territorial or provincial records. Spider diversity was structured at the regional scale across ecoclimatic regions but was not structured with latitude. Longitudinal patterns of spider diversity across Canada may be explained by post-glacial dispersal. At local scales, diversity was non-randomly distributed and possibly limited by biotic interactions. We recommend the use of ecoclimatic regions as a framework for conservation of biodiversity in northern Canada and spiders as useful bioindicators that can help us understand the effects of climate change across ecoclimatic regions of northern Canada.

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 categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.376
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 science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0220.001

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 head0.032
GPT teacher head0.239
Teacher spread0.206 · 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; both teacher heads agree on what is shown here.

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

Citations7
Published2018
Admission routes3
Has abstractyes

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