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Record W2094098368 · doi:10.1139/b07-118

Evaluating the influence of environmental and spatial variables on diatom species distributions from Melville Island (Canadian High Arctic)

2008· article· en· W2094098368 on OpenAlexaffvenueabout
Bronwyn E. Keatley, Marianne S. V. Douglas, John P. Smol

Bibliographic record

VenueBotany · 2008
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeology and Paleoclimatology Research
Canadian institutionsQueen's UniversityUniversity of Alberta
Fundersnot available
KeywordsDiatomArcticEcologyArchipelagoBiological dispersalTaxonArctic vegetationBiologySpecies richnessOceanographyPhysical geographyGeographyGeologyPopulationTundra

Abstract

fetched live from OpenAlex

Diatom species assemblages were identified and enumerated from the surface sediments of 45 lakes and ponds across a wide spectrum of spatial and environmental gradients on Melville Island, Nunavut/N.W.T, Arctic Canada. Whereas the most common taxa were similar to those recorded elsewhere in the Canadian High Arctic, significant differences in assemblages existed between sites located in the different bioclimatic zones of Melville Island. For example, taxa recorded in the most lushly vegetated bioclimatic zone were similar to those found in lushly vegetated regions elsewhere in the Canadian Arctic Archipelago, and generally different from diatoms in the poorly vegetated regions on Melville Island. Of the measured environmental variables, pH, specific conductivity, surface area, elevation, and chlorophyll a explained significant portions of the variance in diatom assemblage composition at the scale of the entire island. However, only total dissolved nitrogen was an important explanatory variable within the most lushly vegetated bioclimatic zone. The strongest ecological relationship was between diatoms and pH, and regression and calibration by weighted averaging produced predictive models with r 2 boot of 0.432 to 0.746 and RMSEP of 0.341 to 0.242. Spatial factors were of little importance, confirming that diatoms are not likely to be dispersal limited, at least at the landscape scale explored in this study.

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 score0.282
Threshold uncertainty score0.996

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 studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0050.000

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 head0.022
GPT teacher head0.232
Teacher spread0.210 · 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

Citations12
Published2008
Admission routes3
Has abstractyes

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