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Record W2045380921 · doi:10.1111/1365-2656.12255

Ecological generalism and behavioural innovation in birds: technical intelligence or the simple incorporation of new foods?

2014· article· en· W2045380921 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueJournal of Animal Ecology · 2014
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAnimal Behavior and Reproduction
Canadian institutionsMcGill University
FundersNatural Sciences and Engineering Research Council of CanadaFondation FyssenCanadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada
KeywordsEcologySimple (philosophy)BiologyGeographyEpistemology

Abstract

fetched live from OpenAlex

Generalist species are more successful than specialists in anthropogenically modified environments or in environments in which they have been introduced, but the nature of the link between generalism and establishment success is unclear. A higher feeding innovation rate has previously been reported in habitat generalist birds from North America. By allowing them to exploit new resources, this higher feeding innovation rate might explain the generalists' advantage. This result might be due to generalists being more likely to find new resources because they are exposed to more diverse environmental conditions. Alternatively, they might differ from specialists in other traits, in particular cognitive skills that might allow them to innovate more complex food searching and handling techniques. To test these hypotheses, we separated avian feeding innovations into a 'technical' (novel searching and handling behaviour) and a 'food type' (incorporation of a new food in a species' diet) category. Technical innovations, but not food type innovations, have previously been shown to correlate with avian brain size, suggesting they reflect cognitive ability. We used a world-wide data base of 2339 feeding innovations recorded in the literature, covering a total of 765 avian species and assessed the correlations between brain size and feeding innovation rates on one side and habitat and diet generalism on the other. Habitat generalism was positively related with food type innovation rate, but not technical innovation rate or brain size. This suggests that habitat generalist species are more likely to incorporate new food types in their diet because of higher chances to find new food resources in their environment, or of a higher opportunism, but not enhanced cognitive skills. In contrast, diet generalist species had higher food type and technical innovation rates, as well as larger brains, suggesting that cognitive skills might help species expand their diet breadth or that an increase in diet breadth might favour the evolution of enhanced cognitive abilities. Our results provide new insights into the nature of the generalists' advantage in the face of environmental changes, and suggest that dietary and habitat generalism are different, but convergent, routes to feeding flexibility and adaptation to changed environments.

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.687
Threshold uncertainty score0.133

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.073
GPT teacher head0.294
Teacher spread0.221 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it