Thermal biology and growth of bison (Bison bison) along the Great Plains: testing four theories of endotherm body size: dataset
Bibliographic record
Abstract
This is the supporting dataset for: Martin and Barboza 2020-Thermal biology and growth of bison (Bison bison) along the Great Plains: testing four theories of endotherm body size Abstract-Body size of bison (Bison bison) declines with rising global temperature across the fossil record and rising annual temperatures across the Great Plains, but what are the underlying drivers? Body size depends on growth, which depends on maximizing net energy and nutrient flows for the production of tissues at seasonal scales across the range of the species. We measured thermoregulation costs of body surface temperature (°C) and heat exchanges (W and W•m˗2) of 350 adult and 345 adolescent Bison from 19 herds in summer and winter along the Great Plains from Saskatchewan (52 °N) to Texas (30 °N). At the smallest scale, daily body surface temperature increased with solar radiation and decreased with relative humidity and wind speed, which is consistent with Kooijman’s dynamic energy budget theory. Total surface heat transfer (W) increased with body mass (kg) at an exponent of 0.63 ± 0.03, which is consistent Schmidt-Nielsen’s principal of surface area to volume ratios (b=0.67). On an annual scale, growth (kg•y-1) of adolescent Bison decreased with increasing total surface heat transfer (W) during summer, which supports Speakman and Król’s heat dissipation limit theory. On the largest scale, heat flux was weakly related to latitude in summer and winter for adolescent Bison, which provides support for Bergmann’s rule and suggests a role for local primary production along the Great Plains. Cooler summers are more optimal for Bison growth because of reduced heat loads during the growing season. Rising temperatures are likely to constrain body size and productivity of Bison and other large endotherms in North America.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.009 | 0.004 |
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".