Species–energy theory, pulsed resources, and regulation of avian richness during a mountain pine beetle outbreak
Bibliographic record
Abstract
Species–energy theory provides a framework through which to link two features commonly noted in local communities: episodic production of resources (i.e., resource pulses) and the regulation of local species richness through time. We examined the pathways through which a resource pulse, a large-scale outbreak of mountain pine beetles, was borne out in six foraging guilds comprising a forest bird community in British Columbia, Canada, 1997–2007. We investigated statistical relationships between richness and abundance in each guild to evaluate the prediction that the outbreak should be manifested in species most reliant upon bark beetles (i.e., the bark insectivore guild). We then employed randomization methods to evaluate whether the beetle outbreak obscured evidence for local regulation for the six foraging guilds. Density and richness of bark insectivores increased over the course of the outbreak. More species of bark insectivores were detected for a given number of individuals following the outbreak, consistent with an increase in the number and types of resources. Richness of bark insectivores showed no evidence of regulation. In contrast, densities of most other foraging guilds were not strongly correlated with the habitat changes resulting from the beetle outbreak and displayed only weak evidence of regulation of richness. We suggest that such weak regulation of richness may be a general feature of forest bird communities. Coupled with long-term data, resource pulses provide exceptional opportunities through which to test predictions of species–energy theory.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".