Temperate grassland songbird species accumulate incrementally along a gradient of primary productivity
Bibliographic record
Abstract
Global analyses of bird communities along elevation gradients suggest that bird diversity on arid mountains is primarily limited by water availability, not temperature or altitude. However, the mechanism by which water availability, and subsequently primary productivity, increases bird diversity is still unclear. Here we evaluate two possible mechanisms from species-energy theory. The more individuals hypothesis proposes that a higher availability of resources increases the total number of individuals that can be supported, and therefore the greater number of species that will be sampled. By contrast, the more specialization hypothesis proposes that increasing resource availability will permit specialists to exploit otherwise rare resources, thus increasing total diversity. We used 5 years of surveys of grassland songbird communities along an elevational gradient in British Columbia, Canada, to distinguish between these hypotheses. Vegetation changed markedly in composition along the gradient and contrary to the expectations of the more specialization hypothesis, bird community composition was remarkably constant. However, both total abundance and species richness of birds increased with increasing water availability to plants. When we used rarefaction to correct species richness for differences in total abundance, much of the increase in bird diversity was lost, consistent with the expectations of the more individuals hypothesis. Furthermore, high species richness was associated with reductions in territory size of common bird species, rather than the fine-scale spatial partitioning of the landscape. This suggests that bird diversity increases when greater resource availability allows higher densities rather than greater habitat specialization. These results help explain a pervasive global pattern in bird diversity on arid mountains, and suggest that in such landscapes conservation of grassland birds is strongly linked to climate and hydrology.
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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 | 0.001 |
| 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) | 0.001 | 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".