2019
DOI: 10.3354/meps13109
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Spatial variability in responses to environmental conditions in Southern Hemisphere long-finned pilot whales

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Cited by 3 publications
(3 citation statements)
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“…Southern hemisphere long-finned pilot whales occur along the southern coastlines of South Africa, South America, New Zealand, and Australia 32 , 33 . Population estimates of long-finned pilot whales in the southern hemisphere do not exist 32 , 34 . The acoustic repertoire of northern hemisphere long-finned pilot whales has been described as highly diverse, repetitive, and physically complex 19 , 35 37 .…”
Section: Introductionmentioning
confidence: 99%
“…Southern hemisphere long-finned pilot whales occur along the southern coastlines of South Africa, South America, New Zealand, and Australia 32 , 33 . Population estimates of long-finned pilot whales in the southern hemisphere do not exist 32 , 34 . The acoustic repertoire of northern hemisphere long-finned pilot whales has been described as highly diverse, repetitive, and physically complex 19 , 35 37 .…”
Section: Introductionmentioning
confidence: 99%
“…In this sense, these splines effectively highlighted the climatic signal of all individuals, retaining the interannual variability and leaving aside noise‐related variance (Cook et al, 1990). Previous studies have also implemented cubic splines in the analysis of GLGs time series in the long‐finned pilot whale ( Globicephala melas ) and sperm whales ( Physeter macrocephalus ) in Australia and New Zealand obtaining satisfactory results (Hamilton & Evans, 2018; Hamilton et al, 2019). However, the EPS and truer¯ values obtained in our study were higher than those reported in previous studies, showing that the common environmental signal has been well represented by the chronologies obtained for South American sea lion of Patagonia.…”
Section: Discussionmentioning
confidence: 99%
“…In this sense, cubic smoothing splines are the most convenient for GLG time series, because they fit more flexibly to them. They also consider autocorrelation in the data and remove different amounts of variance depending on the spline rigidity (Hamilton & Evans, 2018; Hamilton et al, 2019). In this sense, three different cubic smoothing splines of 67%, 50%, and 30% frequency cutoff of the time series length (n) were applied in both sexes.…”
Section: Methodsmentioning
confidence: 99%