Prehistorical record of cultural eutrophication from Crawford Lake, Canada
Bibliographic record
Abstract
Cultural eutrophication--the process by which human activities increase nutrient input rates to aquatic ecosystems and thereby cause undesirable changes in surface-water quality--is generally thought to have begun with the start of the industrial era. The prehistoric dimension of human impacts on aquatic ecosystems remains relatively undescribed, particularly in North America. Here we present fossil plankton data (diatoms and rotifers), organic and inorganic carbon accumulations, and carbon isotope ratios from a 1000-yr sediment core record from Crawford Lake, Ontario, Canada. The data documents increased nutrient input to Crawford Lake caused by Iroquoian horticultural activity from A.D. 1268 to 1486 and shows how this increased nutrient input elevated lake productivity, caused bottom-water anoxia, and irreversibly altered diatom community structure within just a few years. Iroquoian settlement in the region declined in the fifteenth century, yet diatom communities and lake circulation never recovered to the predisturbance state. A second phase of cultural eutrophication starting in A.D. 1867, initiated by Canadian agricultural disturbance, increased lake productivity but had comparatively less of an impact on diatom assemblages and carbon-storage pathways than the initial Iroquoian disturbance. This study deepens our understanding of the impact of cultural eutrophication on lake systems, highlights the lasting influence of initial environmental perturbation, and contributes to the debate on the ecological impacts of density and agricultural practices of native North American inhabitants.
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 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 | 0.004 | 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) | 0.002 | 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".