Plant community development of Isle Royale’s moose-spruce savannas
Bibliographic record
Abstract
In Isle Royale National Park, heavy moose browsing over the past 100 years has suppressed the regeneration of many tree species, gradually resulting in a shift towards more open forests and savannas. By 1996, 16% of the forests at the southwestern end of Isle Royale had become savanna and another 20% of forests were starting to have canopy breakup. The changes in understory vegetation brought about by savanna formation have received little attention, even though the future of moose and wolf populations on Isle Royale is tied to these vegetation changes. This study examined the vegetation of savannas ranging in age (date since formation) from <10 years to 80 years to examine how the ground flora changes over time from initial forest canopy breakup, to extensive grassland, and finally to a zootic subclimax dubbed “moose-spruce savanna.” Ordination techniques were used to describe plant communities and to identify environmental variables that influence vegetation development. Nonparametric multiplicative regression was used to predict how these variables influenced individual plants and structure within the communities. Plant communities had a notable shift from forest herbs to ruderal species, especially non-native plants. This succession was influenced strongly by the underlying bedrock and hydrology-altering moisture regimes and plant communities. Picea glauca (Moench) Voss. and Poa pratensis L. competed in a dynamic inhibitory relationship. The former facilitated forest plants while the latter out-competed other plants and promoted open swards. These interactions are dramatically changing the character of Isle Royale’s upland plant communities and will have important trophic consequences for the island.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".