Assessing late Holocene variability in sea otter prevalence in two areas of coastal British Columbia using archaeological and isotopic data
Bibliographic record
Abstract
The historic extirpation and subsequent recovery of sea otters, a well-recognized keystone predator, has generated far-reaching changes in nearshore ecosystems across the Northeast Pacific. What remains unclear, is how coastal food webs were structured over the Holocene, when people and sea otters co-existed. Mounting archaeological evidence indicates that sea otter populations were lower in the vicinity of human shellfish harvesting sites and that their prevalence varied across regional scales. We used zooarchaeological data, stable isotope analysis, and a social-ecological lens to investigate differences in late Holocene sea otter prevalence in two areas of coastal British Columbia: Barkley Sound and southern Gwaii Haanas. We assessed differences in the isotopic signatures of ancient coastal consumers, sea otter diets, and shellfish prey assemblages to draw inferences on their relative abundance and how nearshore food webs differed in these two areas over the late Holocene. We show that the size and consistency of archaeological shellfish prey, as well as the overall low-trophic level of sea otter diets, suggest that sea otters were reduced or absent in the vicinity of harvesting sites in both southern Gwaii Haanas and Barkley Sound. Moreover, several lines of evidence suggest a greater prevalence of sea otters in southern Gwaii Haanas with coastal consumers showing enriched levels of 13C and 15N and sea otter diets exhibiting a more diverse prey base compared to Barkley Sound. Other lines of evidence were inconclusive or suggested the opposite with no difference in the size of some shellfish between areas and with the relatively greater occurrence of urchins, a preferred sea otter prey, in Gwaii Haanas archaeological deposits. Our findings add to the large body of evidence documenting thousands of years of interactions and coexistence between people and sea otters while revealing a degree of geographic variation in this relationship. This work emphasizes the need for spatially explicit sea otter recovery targets that account for the longstanding role of humans as interacting components of coastal ecosystems and offers insights into practices that could support the coexistence between people, sea otters, and seafood.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".