The Magellanic Woodpecker’s role in its assemblage: a case study of cavity provisioning and habitat selection in the world’s southernmost forests
Bibliographic record
Abstract
Woodpeckers are adept cavity excavators and various species, i.e., secondary cavity-users (SCUs), may depend on these cavities. Birds use specific habitat attributes to increase their likelihood of survival, but these attributes vary among cavity users. We examine the role of cavity provisioning by Magellanic Woodpeckers (Campephilus magellanicus, MAWO, 275–347 g), the largest woodpeckers in South America. From 2015–2017 on Navarino Island, Chile (55° 4' 0.12'' S, 67° 40' 1.2'' W), we (1) assessed SCU densities and richness; (2) compared assemblage cavity use between MAWO-excavated and non-excavated cavities; and (3) determined which habitat attributes influence cavity use by MAWOs and the SCU assemblage. We found 12 SCU species ranging from ~11–447 g; Thorn-tailed Rayadito (Aphrastura spinicauda, ~12 g) was the most abundant (i.e., 9.24 individuals/ha) and frequent SCU that used non-excavated cavities. Magellanic Woodpeckers selected taller and larger-diameter Nothofagus trees to excavate their cavities, which were placed higher off the ground and had wider cavity entrances compared to those used by SCUs. Of the used cavities, MAWOs provided a small proportion to the SCU assemblage in general. Specifically, small passerines rarely used cavities provided by this large woodpecker, matching findings elsewhere globally. However, their cavity provisioning may be an important resource for larger birds, particularly raptors and parakeets. Moreover, MAWOs may play a key part in other ecological roles, e.g., by providing foraging and oviposition sites for birds and insects, respectively, or by vectoring wood-decay fungi. Additionally, we found evidence that SCUs use MAWO-enlarged foraging holes as nesting cavities; therefore, MAWOs may provide an ecological service for the broader SCU assemblage, but via a different mechanism than simply cavity excavation. We suggest researchers determine if MAWO-provided cavities increase SCU fitness or reproductive success. Further, we suggest researchers check cavities to determine if they are internally excavated and provide accurate information on cavity use, particularly if management and conservation decisions are made based upon these data.
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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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".