Individual, ecological, and anthropogenic influences on activity budgets of long-finned pilot whales
The authors would like to thank sponsors, NL Ministry of Defence, NOR Ministry of Defence, U.S. Office of Naval Research (N00014-08-1-0984, N00014-10-1-0355, N00014-14-1-0390), FR Ministry of Defence (DGA; public market no. 15860052), World Wildlife Fund Norway (9E0682), and French Total Foundation...
Published in: | Ecosphere |
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Main Authors: | , , , , , , , |
Other Authors: | , , , , , , , , , |
Format: | Article in Journal/Newspaper |
Language: | English |
Published: |
2018
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Subjects: | |
Online Access: | https://hdl.handle.net/10023/12408 https://doi.org/10.1002/ecs2.2044 |
Summary: | The authors would like to thank sponsors, NL Ministry of Defence, NOR Ministry of Defence, U.S. Office of Naval Research (N00014-08-1-0984, N00014-10-1-0355, N00014-14-1-0390), FR Ministry of Defence (DGA; public market no. 15860052), World Wildlife Fund Norway (9E0682), and French Total Foundation and Bleustein-Blanchet Foundation. The statistical development work was supported by a separate grant from the U.S. Office of Naval Research (N00014-12-1-0204), under the project entitled Multi-study OCean acoustics Human effects Analysis (MOCHA). Time allocation to different activities and habitats enables individuals to modulate their perceived risks and access to resources, and can reveal important trade-offs between fitness-enhancing activities (e.g., feeding vs. social behavior). Species with long reproductive cycles and high parental investment, such as marine mammals, rely on such behavioral plasticity to cope with rapid environmental change, including anthropogenic stressors. We quantified activity budgets of free-ranging long-finned pilot whales in order to assess individual time trade-offs between foraging and other behaviors in different individual and ecological contexts, and during experimental sound exposures. The experiments included 1-2 and 6-7 kHz naval sonar exposures (a potential anthropogenic stressor), playback of killer whale (a potential predator/competitor) vocalizations, and negative controls. We combined multiple time series data from digital acoustic recording tags (DTAG) as well as group-level social behavior data from visual observations of tagged whales at the surface. The data were classified into near-surface behaviors and dive types (using a hidden Markov model for dive transitions) and aggregated into time budgets. On average, individuals (N=19) spent most of their time (69%) resting and transiting near surface, 21% in shallow dives (depth <40m), and only 10% of their time in deep foraging dives, of which 65% reached a depth 10m from the sea bottom. Individuals in the largest of ... |
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