Spatial and temporal separation of toothed whales in the western North Atlantic ...
A diverse group of toothed whale species inhabits the pelagic habitats of the western North Atlantic, competing for overlapping prey resources. Historical data deficits have limited fundamental research into many of these species, such as establishing baselines of distribution and abundance, so thei...
| Main Authors: | , , , |
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| Format: | Dataset |
| Language: | English |
| Published: |
Dryad
2022
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| Subjects: | |
| Online Access: | https://dx.doi.org/10.6076/d1ws32 https://datadryad.org/stash/dataset/doi:10.6076/D1WS32 |
| Summary: | A diverse group of toothed whale species inhabits the pelagic habitats of the western North Atlantic, competing for overlapping prey resources. Historical data deficits have limited fundamental research into many of these species, such as establishing baselines of distribution and abundance, so their occurrence and habitat use patterns are not well characterized. Periodic cycles in activity have been reported at a range of temporal scales for odontocetes in other regions, such as seasonal movements, foraging activity modulated by lunar cycles, and diel activity patterns. A variety of spatial, temporal, and behavioral separation strategies have also been observed among predator guilds in both marine and terrestrial systems, and these may also contribute to ob served spatiotemporal patterns in activity. Re cently, passive acoustic data has been applied to monitor odontocete species continuously, with im proved detection and species discrimination for some cryptic species. We used a long-term passive acoustic ... : Time series of labeled odontocete echolocation clicks were derived by (1) from a large passive acoustic data set collected through repeated mooring deployments. Clicks were detected and classified to species using a machine learning workflow, and then classification error was quantified by manual verification of a subset of the labeled data. For each species/group we binned the time series of labeled clicks into 5-minute time bins, then scaled the number of clicks per bin by recording effort as well as the classifier error rates which were calculated on a per-species per-deployment basis. For analysis of temporal patterns in species presence and activity, we considered binomial presence/absence in each 5-minute bin to be a more reliable metric of species presence than the actual number of clicks labeled to that species, since some clicks were isolated by the clustering algorithm and therefore were unavailable to be labeled by the classifier. To remove spurious presence bins based on very few detections, we ... |
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