Complexities of nitrogen isotope biogeochemistry in plant-soil systems: implications for the study of ancient agricultural and animal management practices
Bibliographic record
Abstract
Nitrogen isotopic studies have the potential to shed light on the structure of ancient ecosystems, agropastoral regimes, and human-environment interactions. Until relatively recently, however, little attention was paid to the complexities of nitrogen transformations in ancient plant-soil systems and their potential impact on plant and animal tissue nitrogen isotopic compositions. This paper discusses the importance of understanding nitrogen dynamics in ancient contexts, and highlights several key areas of archaeology where a more detailed understanding of these processes may enable us to answer some fundamental questions. This paper explores two larger themes that are prominent in archaeological studies using stable nitrogen isotope analysis: (1) agricultural practices (use of animal fertilizers, burning of vegetation or shifting cultivation, and tillage) and (2) animal domestication and husbandry (grazing intensity/stocking rate and the foddering of domestic animals with cultigens). The paucity of plant material in ancient deposits necessitates that these issues are addressed primarily through the isotopic analysis of skeletal material rather than the plants themselves, but the interpretation of these data hinges on a thorough understanding of the underlying biogeochemical processes in plant-soil systems. Building on studies conducted in modern ecosystems and under controlled conditions, these processes are reviewed, and their relevance discussed for ancient contexts.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".