Summer vegetation, deglaciation and the anomalous bird diversity gradient in eastern North America
Bibliographic record
Abstract
ABSTRACT Aim Geographic variation in the species richness of birds has been shown to be strongly associated with annual water and energy levels (actual evapotranspiration, AET) at the global scale. However, the gradient in eastern North America appears to be anomalous, because richness is greatest around the Great Lakes, whereas AET is highest in the south‐eastern US. Here I examine if birds may be responding to vegetation produced during the breeding season rather than to annual production. Location North America east of longitude 98° W. Methods The bird richness pattern was examined using climatic variables, remotely sensed estimates of annual and seasonal plant biomass, and time since areas were exposed by the retreating Laurentide ice sheet from 20,000 to 6000 yr bp. Results Average summer GVI (Global Vegetation Index, derived from NDVI) was found to be positively linearly associated with richness, explaining 82% of the variance, whereas the relationships between richness and annual measures of both AET and GVI were curvilinear. The pattern of retreat of the Laurentide ice sheet explained an additional 6% of the variance in richness, consistent with a previous analysis of Canadian birds. Main conclusions In eastern North America, a seasonal variable associated with plant production explains the diversity gradient rather than the annual measures, but it does not undermine a general conclusion that bird diversity is closely linked with plant biomass. Further, both contemporary and historical factors appear to influence the gradient, and an association between bird richness and the geographic pattern of glacial retreat is detectable in both climatic and plant‐biomass models of bird diversity.
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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".