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Record W2272153000

Modeling habitat use of young-of-the-year Pacific sand lance (Ammodytes hexapterus) in the nearshore region of Barkley Sound, British Columbia

2006· dissertation· en· W2272153000 on OpenAlexaboutno aff
Trevor B. Haynes

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsnot available
Fundersnot available
KeywordsSound (geography)OceanographyHabitatGeologyGeographyFisheryArchaeologyEcologyBiology
DOInot available

Abstract

fetched live from OpenAlex

Successful management of coastal ecosystems requires an understanding of the distribution of key food web species through space and time relative to environmental predictors. Here, I examined the habitat use of an important forage species, the Pacific sand lance (Ammodytes hexapterus), using an inductive habitat modeling approach. I examined the presence/absence of Young-of-the-Year Pacific sand lance in the intertidal/shallow subtidal habitat of Barkley Sound, British Columbia. I determined sand lance occurrence using a beach seine at low tide, which was preferred to visual and intertidal digging detection methods due to its high detection frequency, ease of use, and ability to physically capture sand lance. I constructed models using environmental data measured at two different scales: 1) empirically measured environmental data (site-specific level) and 2) GIS derived environmental data extracted with a 200m buffer (landscape level). For each scale, I employed both logistic regression and classification tree modeling procedures to construct habitat models of sand lance occurrence at 55 study sites sampled during the summer of 2003. At the site-specific level, both logistic regression and classification tree models performed similar, however, classification trees were easier to construct and interpret as well as revealing interactions among variables undetected by logistic regression. Based on a deviance pruned classification tree, Grain Size Mean, Intertidal Eelgrass Presence, Absence, Major Substrate Low Intertidal, and Grain Size Sorting influenced sand lance occurrence at this scale, with importance values of 100, 79, 75, and 61 respectively. Standardized importance was based on the overall change in node impurity in the classification tree for each variable. At the landscape level, only Coastline Density was significantly related to sand lance occurrence, however, it was difficult to suggest this variables direct relation to sand lance habitat use. Overall, the habitat modeling approach identified important environmental variables influencing sand lance habitat selection at two different scales and stressed the utility of field data to construct and confirm these models.

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)0.001
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.046
Threshold uncertainty score0.093

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0010.000
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 head0.013
GPT teacher head0.203
Teacher spread0.190 · 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

Citations4
Published2006
Admission routes1
Has abstractno

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