ArticleMovement ecology2019
Ecological correlates of blue whale movement behavior and its predictability in the California Current Ecosystem during the summer-fall feeding season.
Article in Movement ecology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed.
- Microbial and small zooplankton communities predict density of baleen whales in the southern California Current Ecosystem.PloS one · 2026Article
- Ecological drivers of movement for two sympatric marine predators in the California current large marine ecosystem.Movement ecology · 2025Article
- Insights into Blue Whale (Animals : an open access journal from MDPI · 2024Article
- Predicting suitable habitats for foraging and migration in Eastern Indian Ocean pygmy blue whales from satellite tracking data.Movement ecology · 2024Article
- Blue whales increase feeding rates at fine-scale ocean features.Proceedings. Biological sciences · 2022Article
- Temporal and spatial lags between wind, coastal upwelling, and blue whale occurrence.Scientific reports · 2021Article
- Where did they not go? Considerations for generating pseudo-absences for telemetry-based habitat models.Movement ecology · 2021Article
- Defining priority areas for blue whale conservation and investigating overlap with vessel traffic in Chilean Patagonia, using a fast-fitting movement model.Scientific reports · 2021Article
- Movements and behaviour of blue whales satellite tagged in an Australian upwelling system.Scientific reports · 2020Article
- Performance evaluation of cetacean species distribution models developed using generalized additive models and boosted regression trees.Ecology and evolution · 2020Article
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Authors and funding
9 authors.
Funding
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Abstract
backgroundSpecies distribution models have shown that blue whales (
methodsWe investigated the association between blue whale behavioral state and environmental predictors in the coastal environments of the CCE using a long-term satellite tracking data set (72 tagged whales; summer-fall months 1998-2008), and predicted the likelihood of ARS behavior at tracked locations using nonparametric multiplicative regression models. The models were built using data from years of cool, productive conditions and validated against years of warm, low-productivity conditions.
resultsThe best model contained four predictors: chlorophyll-
conclusionsWe showed that blue whale behavioral state in the CCE was predictable from environmental correlates and that ARS behavior was most prevalent in regions of known high whale density, likely reflecting where large prey aggregations consistently develop in summer-fall. Our models of whale movement behavior enhanced our understanding of species distribution by further indicating where foraging was more likely, which could be of value in the identification of key regions of importance for endangered species in management considerations. The models also provided evidence that decadal-scale environmental fluctuations can drive shifts in the distribution and foraging success of this blue whale population.
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