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Responses to low salinity by the sea star <i>Pisaster ochraceus</i> from high‐ and low‐salinity populations

2009· article· en· W2034977895 on OpenAlexaffabout
Mirjam B.E. Held, Christopher D. G. Harley

Bibliographic record

VenueInvertebrate Biology · 2009
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine and fisheries research
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsSalinityBiologySeawaterEcologyPopulationPredationOceanographyGeology

Abstract

fetched live from OpenAlex

Abstract. In many coastal environments, variation in salinity and organismal responses to that variation are important determinants of the distribution and abundance of species. This study examined the effects of acute salinity changes on sea stars (Pisaster ochraceus) collected from a high‐salinity site (Bamfield, BC) and a low‐salinity site (Vancouver, BC). Sea stars from both sites were exposed to salinities ranging 15–30 psu. Following a 24‐h exposure, the osmolality, sodium concentrations, and chloride concentrations in the perivisceral fluid all varied directly with salinity and were very close to the treatment salinities in both the Bamfield and Vancouver sea stars. The righting response (measured as an activity coefficient) was salinity dependent, with the lowest activity levels at a salinity of 15 psu. Activity coefficients did not vary between the two source populations. Feeding rates on mussels were strongly salinity dependent, but the salinity pattern was population specific. Bamfield sea stars fed the most at 30 psu, whereas Vancouver sea stars fed the most at 20 psu. High post‐experimental mortalities were observed in Bamfield sea stars that had been exposed to a salinity of 15 psu; no such mortality was observed in Vancouver animals. This study provides evidence that the sea stars from the lower salinity environment had been able to acclimatize or adapt to low‐salinity conditions. However, the results also suggest that there are limits to this tolerance, and that future changes in salinity may have important consequences for marine communities via alteration of keystone predation.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.025
Threshold uncertainty score0.050

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 studies0.0010.000
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 head0.029
GPT teacher head0.284
Teacher spread0.255 · 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 designBench or experimental
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

Citations50
Published2009
Admission routes2
Has abstractyes

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