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Record W2331198162 · doi:10.3354/meps10332

Overcoming difficult times: the behavioural resilience of a marine predator when facing environmental stochasticity

2013· article· en· W2331198162 on OpenAlexaboutno aff
Vítor H. Paiva, Pedro Geraldes, Iván Ramírez, AC Werner, Stefan Garthe, Jaime A. Ramos

Bibliographic record

VenueMarine Ecology Progress Series · 2013
Typearticle
Languageen
FieldEnvironmental Science
TopicAvian ecology and behavior
Canadian institutionsnot available
FundersInterreg
KeywordsForagingApex predatorPredatorEcologyMarine ecosystemGeographyPredationProductivityMarine protected areaMarine conservationResilience (materials science)FisheryEcosystemHabitatBiology

Abstract

fetched live from OpenAlex

Annual changes in the behaviour and distribution of top predators at sea may be linked to environmental variability. Here we report, for the first time to our knowledge, the interannual (2007)(2008)(2009)(2010)(2011) foraging ecology during the pre-laying period of female Cory's shearwaters Calonectris diomedea from Berlenga (Portugal), based on biotelemetry data. Our aim was to examine the degree of flexibility in the at-sea distribution, behaviour and habitat selection of foraging birds, and relate this with marine environmental stochasticity. Productivity proxies in the closer foraging areas decreased noticeably between 2007 and 2011 (i.e. an increase of sea surface temperature and a decrease of primary productivity). Female Cory's shearwaters perceived the oceanic changes, and shifted their distribution to an area that could have the food resources required for egg formation. In 2011, in order to exploit the productive Grand Banks and Newfoundland Shelf domains, female Cory's shearwaters embarked on one of the largest foraging excursions of the prelaying period when compared to other seabird species (nearly 4000 km). The option to forage on such a distant area in 2011 decreased the females' body condition and reduced their hatching success, which may be interpreted as an adaptation to local productivity during this energetically highly demanding period to favour their own survival. Long-term monitoring of the foraging behaviour of top predators such as Cory's shearwaters in years to come may serve as a 'sensitive' proxy to help understand the medium-to long-term effects of environmental stochasticity in marine ecological systems.

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 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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.025
Threshold uncertainty score0.976

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.002
Scholarly communication0.0000.001
Open science0.0010.002
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0250.000

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 head0.007
GPT teacher head0.204
Teacher spread0.197 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations34
Published2013
Admission routes1
Has abstractyes

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