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Record W2102871527 · doi:10.1666/09018.1

Carcasses on the coastline: measuring the ecological fidelity of the cetacean stranding record in the eastern North Pacific Ocean

2010· article· en· W2102871527 on OpenAlexaff
Nicholas D. Pyenson

Bibliographic record

VenuePaleobiology · 2010
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine animal studies overview
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsGeographyMarine ecosystemAssemblage (archaeology)OceanographyFisheryTaphonomyInvertebrateMarine lifeEcologyEcosystemArchaeologyGeologyBiology

Abstract

fetched live from OpenAlex

To understand how well fossil assemblages represent original communities, paleoecologists seek comparisons between death assemblages and their source communities. These comparisons have traditionally used nearshore, marine invertebrate assemblages for their logistical ease, high abundance, and comparable census data from living communities. For large marine vertebrates, like cetaceans, measuring their diversity in ocean ecosystems is difficult and expensive. Cetaceans, however, often beach or strand themselves along the coast, and archived data on stranded cetaceans have been recorded, in some areas, over several decades. If the stranding record is interpreted as a death assemblage, then the stranding record may represent a viable alternative for measuring diversity in living communities on directly adjacent coastlines. This study assessed the fidelity of the cetacean stranding record in the eastern North Pacific Ocean. The living community in this region has been studied for over 100 years and, recently, extensive and systematic live transect surveys using ship-based observing platforms have produced a valuable source of live diversity data. Over this same period, the U.S. Marine Mammal Stranding Program has collected and archived a record of cetacean strandings along the U.S. Pacific coastline, providing an ideal death assemblage for comparison. Using fidelity metrics commonly used in marine invertebrate taphonomy, I determined that the stranding record samples the living cetacean community with high fidelity, across fine and coarse taxonomic ranks, and at large geographic scales (>1000 km of coastline). The stranding record is also richer than the live surveys, with live-dead ratios between 1.1 and 1.3. The stranding record recovers similar rank-order relative abundances as live surveys, with statistical significance. Also, I applied sample-based rarefaction methods to generate collector's curves for strandings along the U.S. Pacific Coast to better evaluate the spatiotemporal characteristics of the stranding record. Results indicate that saturation (i.e., sampling >95% assemblage) at species, genus, and family levels occurs in less than five years of sampling, with families accumulating faster than species, and larger geographic regions (i.e., longer coastlines) accumulating taxa the most rapidly. The high fidelity of the stranding record, measured both in richness and by ranked relative abundance, implies that ecological structure from living cetacean communities is recorded in the death assemblage, a finding that parallels marine invertebrate assemblages, though at far larger spatial scales. These results have implications for studying cetacean ecology in both modern and ancient environments: first, these results imply that the stranding record, over sufficiently long time intervals, yields a richer assemblage than using line-transect methods, and faithfully records aspects of community structure; and second, these results imply that geochronologically well-constrained fossil cetacean assemblages might preserve ecologically relevant features of community structure, depending on depositional and taphonomic conditions.

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)0.001
metaresearch head score (Gemma)0.004
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 score0.091

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
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 head0.039
GPT teacher head0.241
Teacher spread0.202 · 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

Citations72
Published2010
Admission routes1
Has abstractyes

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