Complexities of Stable Carbon and Nitrogen Isotope Biogeochemistry in Ancient Freshwater Ecosystems: Implications for the Study of Past Subsistence and Environmental Change
Bibliographic record
Abstract
Stable carbon and nitrogen isotope analyses of human and animal tissues have become an important means of studying both anthropogenic and natural food webs in aquatic ecosystems. Within the rapidly expanding field of human and animal paleodietary analyses, archaeologists routinely incorporate isotopic data from fish, birds, and aquatic mammals into their interpretations of ancient freshwater resources use; however, these studies rarely consider the complex and dynamic nature of the carbon and nitrogen cycles that give structure to nutrient regimes and their isotopic compositions in freshwater ecosystems. This review outlines two thematic areas in which this surge in stable isotope applications to the study of ancient human societies could be enhanced by incorporating concepts from limnology, ecology, and biology. First, building on studies conducted in modern ecosystems, this paper outlines key aspects of the stable isotope ecology of freshwater environments, highlighting the importance of considering physical and biological processes associated with ancient biogeochemical cycles when conducting human paleodietary reconstructions. Second, this paper discusses areas where isotopic analyses of archaeological freshwater animal remains could contribute to broader research fields including climate change and cultural eutrophication research, human impacts on long-term food web dynamics and animal behaviour, and by providing novel approaches to reconstructing ancient fish management practices.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.006 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".