Landscape influence on the spatial and temporal distribution of the Kirtland's warbler at the Bald Hill burn, northern Lower Michigan, U.S.A.
Bibliographic record
Abstract
The Kirtland's warbler (Dendroica kirtlandii Baird) is an endangered songbird that nests in northern Lower Michigan in ecosystems dominated by young jack pine (Pinus banksiana Lamb.). We used the landscape ecosystem approach to identify two adjacent landform-level ecosystems located at different elevations within the area burned by the 1975 Bald Hill fire in Crawford County, Michigan. Eighty-five percent of the warblers occupied the high-elevation landform from 1982 to 1987 compared with only 25% from 1992 to 1997, indicating a shift in warbler occupancy of the burn from the high- to the low-elevation landform by 1991. Although similar in soil, the landforms have significantly different microclimates as mediated by physiography. Because of a warmer microclimate, jack pines in the high-elevation landform exhibited faster growth and were colonized first by the warbler; the trees in the cooler low-elevation landform grew more slowly and were colonized later. We suggest that the presence of two adjacent landform-level ecosystems within a single burned area prolonged the warbler occupancy of the burn. Thus, a broad-scale ecosystem approach that considers physical site factors as well as vegetative characteristics is useful for understanding the complex interactions that affect spatial and temporal species distributions across the landscape. Such an approach may benefit the management of particular endangered species, especially when the size of management areas is considered to be a crucial element of species preservation.
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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 | 0.000 | 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".