Unifying species distributions, community science and the ‘natural removal experiment' to explore species interactions at broad geographic scales
Bibliographic record
Abstract
To understand the distribution of avian biodiversity, it is crucial to understand the interspecific interactions present in avian communities. The ‘natural removal experiment', which explores patterns consistent with competition by comparing a species' habitat relationships in sympatry and allopatry with those of a potential competitor, has held promise, but has thus far had limited general replicability. We offer an adaptation of this method applicable to many study systems and over broad geographic scales, without requiring a prioriknowledge of an interaction. We use this method to ask whether the distribution of the chestnut‐backed chickadee Poecile rufescens (CBCH) is consistent with competition with the black‐capped chickadee Poecile atricapillus (BCCH) in urban areas in the Pacific Northwest. Using data from eBird, we compared relationships of CBCH relative abundance to urban‐ and forest‐related variables in different local urban centres and across region‐wide areas of allopatry and sympatry with the BCCH. As predicted under competition, we found that in allopatry, the CBCH adopted habitat relationships similar to the BCCH, inhabiting less forested, more urban habitats, both in local urban centres and at the region‐wide scale. When examining the potential consequences of absence or ubiquity of BCCH across the region, we found when model predictions were made as if BCCH were ubiquitous, CBCH abundance was lower in urban areas, and that when predictions were made as if BCCH were absent CBCH abundance increased, consistent with competitive release. These lines of evidence suggest that the distribution of CBCH is consistent with that expected under competition with the BCCH in urban areas. As the BCCH expands its range further into the Pacific Northwest, our assessment foreshadows the eventual replacement of CBCH from urbanized areas. Expanding beyond this case study, we discuss considerations in the application of this method to offer researchers a broadly applicable tool to study species interactions.
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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 | 0.016 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".