Spatial overlap and effect of fishing effort on the foraging behavior of the Great Shearwater (Ardenna gravis) on the Argentine Continental Shelf
Bibliographic record
Abstract
Abstract: Fishing is the main economic activity in waters of the Argentinian Continental Shelf (ACS). Various seabird species attend trawlers and longliners seeking food facilitated by the fishing operation as well as discards and offal as a byproduct of the catch and processing. During the austral spring, large numbers of Great Shearwaters (GSH, Ardenna gravis) forage over the ACS. This species has been registered interacting with longliners targeting skates or toothfish Dissostichus eleginoides, ice-chilling and freezer trawlers that target hake Merluccius hubbsi and has high rates of bycatch in coastal pelagic trawlers targeting anchovy Engraulis anchoita. This study analyzes the overlap between the distributions of adult (2009-2010 period) and immature (2006, 2008-2009, 2009-2010 periods) GSHs and a range of fishing fleets, as well as assessing the effect of fishing effort on shearwater foraging behavior. The database comprised fisheries effort for 9 fleets, and 21 GSH tracked by satellite telemetry. The tracking data were analyzed with switching state-space models (SSSM) to infer behavior (transitory or foraging) at each location. The overlap was analyzed using the UDOI index (no overlapping = 0, complete overlap UDOI ≥ 1), while the effect of fisheries on foraging behavior was analyzed using GLMM (individual identity as random factors). The largest overlap for all years and age pooled was observed with the pelagic trawlers (UDOI ≥ 0.45), demersal coastal fleets (≥ 0.32), and ice-trawlers target hake (≥ 0.25). For immatures ice-trawlers target hake (2006 and 2008-2009 periods), freezer longiners (2006) and coastal demersal trawlers (2009-2010 period) were the fisheries that showed positive effect in the foraging behavior (i.e. foraging was most likely with increased fishing effort), while for adults ice-trawlers target hake was the only fishery with effect significantly positive. This preliminary analysis as a proxy of risk of interaction constitutes the basis for further studies to define areas and times of higher sensitivity for shearwaters attending fisheries. Authors: Jesica Paz¹, Robert Ronconi², Juan Seco Pon¹, Sofía Copello¹, Peter Ryan³, Marco Favero¹ ¹Instituto de Investigaciones Marinas y Costeras (IIMyC), Universidad Nacional de Mar del Plata, CONI, ²Canadian Wildlife Service, Environment and Climate Change Canada, ³FitzPatrick Institute of African Ornithology, DST-NRF Centre of Excellence, University of Cape Town
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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 | 0.000 |
| 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) | 0.001 | 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".