Mastodons and Mammoths in the Great Lakes Region, USA and Canada: New Insights into their Diets as they Neared Extinction
Bibliographic record
Abstract
Abstract The conventional image of Ice Age environments of North America includes mammoths feeding on grasses in open tundra or steppe habitats and mastodons browsing on spruce branches in forests. However, re‐examination of plant and animal fossil research in the Great Lakes region of the USA and adjacent Ontario, Canada provides new insights into the changing diets of mammoths and mastodons in this region, particularly as these animals neared extinction between 13,500 and 13,000 calendar years Before Present (cal yr BP). This paper reconstructs the following scenario at the end of the Ice Age. Woolly mammoths primarily inhabited tundra adjacent to the northward receding margin of the Laurentide ice sheet. Meanwhile, to the immediate south, Jefferson mammoths grazed on grasses, sedges and herbs around the edges of wetlands, while American mastodons consumed mainly the leaves and branches of spruce and other trees in first an anomalous spruce parkland/sedge wetland environment and later in spruce‐dominated forest. However, mammoth and mastodon populations began to dwindle at a time when the succeeding vegetation became a closed forest with a lesser amount of spruce trees, grasses and sedges and a greater abundance of invading deciduous trees. The last mammoths and mastodons in the Great Lakes region bear signs of stress and competition for the same foods in dense coniferous‐deciduous forest, which contributed to the extinction of these magnificent beasts by ∼13,000 cal yr BP. This extinction event highlights the fragility of mammal populations under stress; an important lesson given that numerous species today are similarly challenged by climate and landscape change.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".