Species traits drive responses of forest birds to agriculturally‐modified habitats throughout the annual cycle
Bibliographic record
Abstract
The conversion of forest to agriculture is considered one of the greatest threats to avian biodiversity, yet how species respond to habitat modification throughout the annual cycle remains unknown. We examined whether forest bird associations with agricultural habitats vary throughout the year, and if species traits influence these relationships. Using data from the eBird community‐science program, we investigated associations between agriculturally‐modified land cover and the occurrence of 238 forest bird species based on three sets of avian traits: migratory strategy, dietary guild, and foraging strategy. We found that the influence of agriculturally‐modified land cover on species distributions varied widely across periods and trait groups but highlighting several broad findings. First, migratory species showed strong seasonal differences in their response to agricultural land cover while resident species did not. Second, there was a migratory strategy by season interaction; Neotropical migrants were most negatively influenced by agricultural land cover during the breeding period while short‐distance migrants were most negatively influenced during the non‐breeding period. Third, regardless of season, some dietary (e.g. insectivores) and foraging guilds (e.g. bark foragers) consistently responded more negatively to agricultural land cover than others (e.g. omnivores and ground foragers, respectively). Fourth, there were greater differences among dietary guilds in their responses to agricultural land cover during the breeding period than during the non‐breeding period, perhaps reflecting how different habitat and ecological requirements enhance the susceptibility of some guilds during reproduction. These results suggest that management efforts across the annual cycle may be oversimplified and thus ineffective when based on broad ecological generalisations that are static in space and time.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".