Infaunal community responses to ancient clam gardens
Bibliographic record
Abstract
Abstract Aquatic ecosystems have been managed for millennia. Indigenous communities in North America pioneered numerous marine resource management strategies to ensure food security and support thriving economies, which have been active throughout the Northwest Coast of North America for over 14 000 years. Developed to increase shellfish productivity, clam gardens have been active for millennia. The diverse infaunal communities within these ecosystems can act as indicators of habitat alterations and provide an opportunity to study ecological community responses to seascapes shaped by millennia-old resource management structures. To determine how community structure differs between clam gardens and unmodified areas, we assessed infaunal diversity and density between intertidal mudflats, sandflats, and clam gardens. Differences in community composition were found among site types, with certain taxa, including culturally important species increasing within clam gardens. Per cent similarity analyses indicated that infaunal communities were more dissimilar among, than within site types. Furthermore, regression trees indicated that increases in diversity and density were closely correlated with the amount of shell and gravel within each habitat, which are associated with clam garden function and management practices. Species-specific and environmental responses to clam gardens indicate that human modifications in nearshore habitats created novel and distinct types of soft sediment communities.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".