Are forest birds categorised as “edge species” strictly associated with edges?
Bibliographic record
Abstract
In recent years, studies of bird‐habitat relationships undertaken in the context of habitat fragmentation have led to the widespread use of species categorisation according to their response to edge alongside mature forest patches (edge species, interior species, interior‐edge generalist species). In other research contexts, especially in less fragmented landscapes dominated by a forested land base in various age classes, bird‐habitat relationships are often described in relation to their use of various successional stages (early‐successional species, mature forest species, generalist species). A simple comparison of these two commonly‐used classifications schemes in a close geographical range for 60 species in eastern North America as well as for 36 species in north‐western Europe clearly reveals that in these two particular biomes the two classifications are not independent. We believe that this association is not only a semantic issue and has important ecological consequences. For example, almost all edge species are associated with early‐successional habitats when a wide range of forest age‐classes are found in a given area. Accordingly, we suggest that most species considered to prefer edge habitats in agricultural landscapes are in fact only early‐successional species that could not find shrubland conditions apart from the exposed edges of mature forest fragments. To be considered a true edge species, a given species should require the simultaneous availability of more than one habitat type and consequently should be classified as a habitat generalist in its use of successional stages. However, 28 out of 30 recognised edge species were considered habitat specialists in terms of successional status. Based on these results, we conclude that “real edge species” are probably quite rare and that we should make a difference between true edge species and species which in some landscapes, happen to find their habitat requirements on edges.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".