The Holocene vegetation history of Isle Royale National Park, Michigan, U.S.A.
Bibliographic record
Abstract
A vegetation history for Isle Royale National Park, Michigan, U.S.A., is reconstructed using pollen and spores extracted from two lake sediment cores. Lily Lake is on the southwestern end of the main island of Isle Royale surrounded by northern hardwoods forest. Lake Ojibway is on the northeastern end of the main island surrounded by boreal forest. Pollen and spore records were analyzed using pollen percentage diagrams, nonmetric multidimensional scaling ordination, and modern analog analysis. Squared chord distances for temporally paired subsamples from each site were calculated to determine palynological dissimilarities between the sites through time. These analyses revealed an overall vegetation history that is consistent with other regional reconstructions. High percentages of spruce pollen, indicating a cool climate, are present in the early Holocene, whereas high percentages of pine pollen, indicating a dry climate, occur in the mid-Holocene. The pollen records from the two sites diverge with increased precipitation during the late Holocene. At this time, birch-dominated forest is established near Lily Lake on till-derived soils. At Lake Ojibway, a mixed birch, pine, spruce, and fir forest is established on bedrock-derived soils. The divergence in forest composition is most pronounced within the last 500 years, and this divergence is tentatively attributed to the response of taxa on different substrates to increasing precipitation. Other possible explanations for the recent divergence include changing microclimates or disturbance regimes.
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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 | 0.000 |
| 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) | 0.009 | 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".