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2.
Sci Rep ; 13(1): 8996, 2023 06 02.
Article in English | MEDLINE | ID: mdl-37268677

ABSTRACT

Rorqual foraging behavior varies with species, prey type and foraging conditions, and can be a determining factor for their fitness. Little is known about the foraging ecology of Rice's whales (Balaenoptera ricei), an endangered species with a population of fewer than 100 individuals. Suction cup tags were attached to two Rice's whales to collect information on their diving kinematics and foraging behavior. The tagged whales primarily exhibited lunge-feeding near the sea bottom and to a lesser extent in the water-column and at the sea surface. During 6-10 min foraging dives, the whales typically circled their prey before executing one or two feeding lunges. Longer duration dives and dives with more feeding-lunges were followed by an increase in their breathing rate. The median lunge rate of one lunge per dive of both animals was much lower than expected based on comparative research on other lunge-feeding baleen whales, and may be associated with foraging on fish instead of krill or may be an indication of different foraging conditions. Both animals spent extended periods of the night near the sea surface, increasing the risk for ship strike. Furthermore, their circling before lunging may increase the risk for entanglement in bottom-longline fishing gear. Overall, these data show that Rice's whale foraging behavior differs from other lunge feeding rorqual species and may be a significant factor in shaping our understanding of their foraging ecology. Efforts to mitigate threats to Rice's whales will benefit from improved understanding of patterns in their habitat use and fine-scale ecology.


Subject(s)
Balaenoptera , Oryza , Animals , Feeding Behavior , Biomechanical Phenomena , Gulf of Mexico
3.
Sci Rep ; 13(1): 6710, 2023 04 25.
Article in English | MEDLINE | ID: mdl-37185970

ABSTRACT

Determining the drivers of prey selection in marine predators is critical when investigating ecosystem structure and function. The newly recognized Rice's whale (Balaenoptera ricei) is one of the most critically endangered large whales in the world and endemic to the industrialized Gulf of Mexico. Here, we investigated the drivers of resource selection by Rice's whales in relation to prey availability and energy density. Bayesian stable isotope (δ13C, δ15N) mixing models suggest that Rice's whales feed primarily on a schooling fish, Ariomma bondi (66.8% relative contribution). Prey selection using the Chesson's index revealed that active prey selection was found to be positive for three out of the four potential prey identified in the mixing model. A low degree of overlap between prey availability and diet inferred from the mixing model (Pianka Index: 0.333) suggests that prey abundance is not the primary driver of prey selection. Energy density data suggest that prey selection may be primarily driven by the energy content. Results from this study indicate that Rice's whales are selective predators consuming schooling prey with the highest energy content. Environmental changes in the region have the potential to influence prey species that would make them less available to Rice's whales.


Subject(s)
Balaenoptera , Oryza , Animals , Ecosystem , Gulf of Mexico , Bayes Theorem , Cetacea
4.
PLoS Comput Biol ; 13(12): e1005823, 2017 Dec.
Article in English | MEDLINE | ID: mdl-29216184

ABSTRACT

Delphinids produce large numbers of short duration, broadband echolocation clicks which may be useful for species classification in passive acoustic monitoring efforts. A challenge in echolocation click classification is to overcome the many sources of variability to recognize underlying patterns across many detections. An automated unsupervised network-based classification method was developed to simulate the approach a human analyst uses when categorizing click types: Clusters of similar clicks were identified by incorporating multiple click characteristics (spectral shape and inter-click interval distributions) to distinguish within-type from between-type variation, and identify distinct, persistent click types. Once click types were established, an algorithm for classifying novel detections using existing clusters was tested. The automated classification method was applied to a dataset of 52 million clicks detected across five monitoring sites over two years in the Gulf of Mexico (GOM). Seven distinct click types were identified, one of which is known to be associated with an acoustically identifiable delphinid (Risso's dolphin) and six of which are not yet identified. All types occurred at multiple monitoring locations, but the relative occurrence of types varied, particularly between continental shelf and slope locations. Automatically-identified click types from autonomous seafloor recorders without verifiable species identification were compared with clicks detected on sea-surface towed hydrophone arrays in the presence of visually identified delphinid species. These comparisons suggest potential species identities for the animals producing some echolocation click types. The network-based classification method presented here is effective for rapid, unsupervised delphinid click classification across large datasets in which the click types may not be known a priori.


Subject(s)
Computational Biology/methods , Dolphins/physiology , Echolocation/classification , Pattern Recognition, Automated/methods , Signal Processing, Computer-Assisted , Vocalization, Animal/classification , Algorithms , Animals , Gulf of Mexico , Sound Spectrography
5.
Sci Rep ; 6: 22615, 2016 Mar 03.
Article in English | MEDLINE | ID: mdl-26936335

ABSTRACT

Cetaceans are protected worldwide but vulnerable to incidental harm from an expanding array of human activities at sea. Managing potential hazards to these highly-mobile populations increasingly requires a detailed understanding of their seasonal distributions and habitats. Pursuant to the urgent need for this knowledge for the U.S. Atlantic and Gulf of Mexico, we integrated 23 years of aerial and shipboard cetacean surveys, linked them to environmental covariates obtained from remote sensing and ocean models, and built habitat-based density models for 26 species and 3 multi-species guilds using distance sampling methodology. In the Atlantic, for 11 well-known species, model predictions resembled seasonal movement patterns previously suggested in the literature. For these we produced monthly mean density maps. For lesser-known taxa, and in the Gulf of Mexico, where seasonal movements were less well described, we produced year-round mean density maps. The results revealed high regional differences in small delphinoid densities, confirmed the importance of the continental slope to large delphinoids and of canyons and seamounts to beaked and sperm whales, and quantified seasonal shifts in the densities of migratory baleen whales. The density maps, freely available online, are the first for these regions to be published in the peer-reviewed literature.


Subject(s)
Biodiversity , Cetacea/physiology , Models, Biological , Animals , Atlantic Ocean , Gulf of Mexico , Humans
6.
Sci Rep ; 5: 16343, 2015 Nov 12.
Article in English | MEDLINE | ID: mdl-26559743

ABSTRACT

Beaked whales are deep diving elusive animals, difficult to census with conventional visual surveys. Methods are presented for the density estimation of beaked whales, using passive acoustic monitoring data collected at sites in the Gulf of Mexico (GOM) from the period during and following the Deepwater Horizon oil spill (2010-2013). Beaked whale species detected include: Gervais' (Mesoplodon europaeus), Cuvier's (Ziphius cavirostris), Blainville's (Mesoplodon densirostris) and an unknown species of Mesoplodon sp. (designated as Beaked Whale Gulf - BWG). For Gervais' and Cuvier's beaked whales, we estimated weekly animal density using two methods, one based on the number of echolocation clicks, and another based on the detection of animal groups during 5 min time-bins. Density estimates derived from these two methods were in good general agreement. At two sites in the western GOM, Gervais' beaked whales were present throughout the monitoring period, but Cuvier's beaked whales were present only seasonally, with periods of low density during the summer and higher density in the winter. At an eastern GOM site, both Gervais' and Cuvier's beaked whales had a high density throughout the monitoring period.


Subject(s)
Acoustics , Echolocation , Vocalization, Animal , Whales , Animals , Geography , Gulf of Mexico , Population Density , Sound Spectrography
7.
Dis Aquat Organ ; 112(2): 161-75, 2014 Dec 02.
Article in English | MEDLINE | ID: mdl-25449327

ABSTRACT

An unusual mortality event (UME) was declared for cetaceans in the northern Gulf of Mexico (GoM) for Franklin County, Florida, west through Louisiana, USA, beginning in February 2010 and was ongoing as of September 2014. The 'Deepwater Horizon' (DWH) oil spill began on 20 April 2010 in the GoM, raising questions regarding the potential role of the oil spill in the UME. The present study reviews cetacean mortality events that occurred in the GoM prior to 2010 (n = 11), including causes, durations, and some specific test results, to provide a historical context for the current event. The average duration of GoM cetacean UMEs prior to 2010 was 6 mo, and the longest was 17 mo (2005-2006). The highest number of cetacean mortalities recorded during a previous GoM event was 344 (in 1990). In most previous events, dolphin morbillivirus or brevetoxicosis was confirmed or suspected as a causal factor. In contrast, the current northern GoM UME has lasted more than 48 mo and has had more than 1000 reported mortalities within the currently defined spatial and temporal boundaries of the event. Initial results from the current UME do not support either morbillivirus or brevetoxin as primary causes of this event. This review is the first summary of cetacean UMEs in the GoM and provides evidence that the most common causes of previous UMEs are unlikely to be associated with the current UME.


Subject(s)
Cetacea , Environmental Monitoring/methods , Animals , Ecosystem , Gulf of Mexico
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