Kinematics and energetics of foraging behavior in Rice's whales of the Gulf of Mexico.

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.

Critically endangered Rice's whales (Balaenoptera ricei) selectively feed on high-quality prey in the Gulf of Mexico.

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.

Acoustic localization, validation, and characterization of Rice's whale calls.

The recently named Rice's whale in the Gulf of Mexico is one of the most endangered whales in the world, and improved knowledge of spatiotemporal occurrence patterns is needed to support their recovery and conservation. Passive acoustic monitoring methods for determining spatiotemporal occurrence patterns require identifying the species' call repertoire. Rice's whale call repertoire remains unvalidated though several potential call types have been identified. This study uses sonobuoys and passive acoustic tagging to validate the source of potential call types and to characterize Rice's whale calls. During concurrent visual and acoustic surveys, acoustic-directed approaches were conducted to obtain visual verifications of sources of localized sounds. Of 28 acoustic-directed approaches, 79% led to sightings of balaenopterid whales, of which 10 could be positively identified to species as Rice's whales. Long-moan calls, downsweep sequences, and tonal-sequences are attributed to Rice's whales based on these matches, while anthropogenic sources are ruled out. A potential new call type, the low-frequency downsweep sequence, is characterized from tagged Rice's whale recordings. The validation and characterization of the Rice's whale call repertoire provides foundational information needed to use passive acoustic monitoring for better understanding and conservation of these critically endangered whales.

The distribution of manta rays in the western North Atlantic Ocean off the eastern United States.

In 2018, the giant manta ray was listed as threatened under the U.S. Endangered Species Act. We integrated decades of sightings and survey effort data from multiple sources in a comprehensive species distribution modeling (SDM) framework to evaluate the distribution of giant manta rays off the eastern United States, including the Gulf of Mexico. Manta rays were most commonly detected at productive nearshore and shelf-edge upwelling zones at surface thermal frontal boundaries within a temperature range of approximately 20-30 °C. SDMs predicted highest nearshore occurrence off northeastern Florida during April, with the distribution extending northward along the shelf-edge as temperatures warm, leading to higher occurrences north of Cape Hatteras, North Carolina from June to October, and then south of Savannah, Georgia from November to March as temperatures cool. In the Gulf of Mexico, the highest nearshore occurrence was predicted around the Mississippi River delta from April to June and again from October to November. SDM predictions will allow resource managers to more effectively protect manta rays from fisheries bycatch, boat strikes, oil and gas activities, contaminants and pollutants, and other threats.

Modeling population effects of the Deepwater Horizon oil spill on a long-lived species.

The 2010 Deepwater Horizon (DWH) oil spill exposed common bottlenose dolphins (Tursiops truncatus) in Barataria Bay, Louisiana to heavy oiling that caused increased mortality and chronic disease and impaired reproduction in surviving dolphins. We conducted photographic surveys and veterinary assessments in the decade following the spill. We assigned a prognostic score (good, fair, guarded, poor, or grave) for each dolphin to provide a single integrated indicator of overall health, and we examined temporal trends in prognostic scores. We used expert elicitation to quantify the implications of trends for the proportion of the dolphins that would recover within their lifetime. We integrated expert elicitation, along with other new information, in a population dynamics model to predict the effects of observed health trends on demography. We compared the resulting population trajectory with that predicted under baseline (no spill) conditions. Disease conditions persisted and have recently worsened in dolphins that were presumably exposed to DWH oil: 78% of those assessed in 2018 had a guarded, poor, or grave prognosis. Dolphins born after the spill were in better health. We estimated that the population declined by 45% (95% CI 14-74) relative to baseline and will take 35 years (95% CI 18-67) to recover to 95% of baseline numbers. The sum of annual differences between baseline and injured population sizes (i.e., the lost cetacean years) was 30,993 (95% CI 6607-94,148). The population is currently at a minimum point in its recovery trajectory and is vulnerable to emerging threats, including planned ecosystem restoration efforts that are likely to be detrimental to the dolphins' survival. Our modeling framework demonstrates an approach for integrating different sources and types of data, highlights the utility of expert elicitation for indeterminable input parameters, and emphasizes the importance of considering and monitoring long-term health of long-lived species subject to environmental disasters. Article impact statement: Oil spills can have long-term consequences for the health of long-lived species; thus, effective restoration and monitoring are needed.

El derrame de petróleo Deepwater Horizon (DWH) en 2010 expuso gravemente a este hidrocarburo a los delfines (Tursiops truncatus) de la Bahía Barataria, Luisiana, causando un incremento en la mortalidad y en las enfermedades crónicas, y deteriorando la reproducción de los delfines sobrevivientes. Realizamos censos fotográficos y evaluaciones veterinarias durante la década posterior al derrame. Asignamos un puntaje pronóstico (bueno, favorable, moderado, malo, o grave) a cada delfín para proporcionar un indicador integrado único de la salud en general. También examinamos las tendencias temporales de estos puntajes. Usamos información de expertos para cuantificar las implicaciones de las tendencias para la proporción de delfines que se recuperaría dentro de su periodo de vida. Integramos esta información, junto con información nueva, a un modelo de dinámica poblacional para predecir los efectos sobre la demografía de las tendencias observadas en la salud. Comparamos la trayectoria poblacional resultante con aquella pronosticada bajo condiciones de línea base (sin derrame). Las condiciones de enfermedad persistieron y recientemente han empeorado en los delfines que supuestamente estuvieron expuestos al petróleo de DWH: 78% de aquellos evaluados en 2018 tuvieron un pronóstico moderado, malo o grave. Los delfines que nacieron después del derrame contaron con mejor salud. Estimamos que la población declinó en un 45% (95% CI 14-74) relativo a la línea base y tardará 35 años (95% CI 18-67) en recuperar el 95% de los números de línea base. La suma de las diferencias anuales entre el tamaño poblacional de línea base y el dañado (es decir, los años cetáceos perdidos) fue de 30,993 (95% CI 6,607-94,148). La población actualmente está en un punto mínimo de su trayectoria de recuperación y es vulnerable a las amenazas emergentes, incluyendo los esfuerzos de restauración ambiental planeada que probablemente sean nocivos para la supervivencia de los delfines. Nuestro marco de modelado demuestra una estrategia para la integración de diferentes fuentes y tipos de datos, resalta la utilidad de la información de expertos para los parámetros de aportación indeterminable, y enfatiza la importancia de la consideración y el monitoreo de la salud a largo plazo de las especies longevas sujetas a los desastres ambientales. Modelado de los Efectos Poblacionales del Derrame de Petróleo Deepwater Horizon sobre Especies Longevas.

Cetacean distribution models based on visual and passive acoustic data.

Distribution models are needed to understand spatiotemporal patterns in cetacean occurrence and to mitigate anthropogenic impacts. Shipboard line-transect visual surveys are the standard method for estimating abundance and describing the distributions of cetacean populations. Ship-board surveys provide high spatial resolution but lack temporal resolution and seasonal coverage. Stationary passive acoustic monitoring (PAM) employs acoustic sensors to sample point locations nearly continuously, providing high temporal resolution in local habitats across days, seasons and years. To evaluate whether cross-platform data synthesis can improve distribution predictions, models were developed for Cuvier's beaked whales, sperm whales, and Risso's dolphins in the oceanic Gulf of Mexico using two different methods: generalized additive models and neural networks. Neural networks were able to learn unspecified interactions between drivers. Models that incorporated PAM datasets out-performed models trained on visual data alone, and joint models performed best in two out of three cases. The modeling results suggest that, when taken together, multiple species distribution models using a variety of data types may support conservation and management of Gulf of Mexico cetacean populations by improving the understanding of temporal and spatial species distribution trends.

Environmental predictors of habitat suitability and occurrence of cetaceans in the western North Atlantic Ocean.

The objective of this study was to identify the main environmental covariates related to the abundance of 17 cetacean species/groups in the western North Atlantic Ocean based on generalized additive models, to establish a current habitat suitability baseline, and to estimate abundance that incorporates habitat characteristics. Habitat models were developed from dedicated sighting survey data collected by NOAA- Northeast and Southeast Fisheries Science Centers during July 2010 to August 2013. A group of 7 static physiographic characteristics and 9 dynamic environmental covariates were included in the models. For the small cetacean models, the explained deviance ranged from 16% to 69%. For the large whale models, the explained deviance ranged from 32% to 52.5%. Latitude, sea surface temperature, bottom temperature, primary productivity and distance to the coast were the most common covariates included and their individual contribution to the deviance explained ranged from 5.9% to 18.5%. The habitat-density models were used to produce seasonal average abundance estimates and habitat suitability maps that provided a good correspondence with observed sighting locations and historical sightings for each species in the study area. Thus, these models, maps and abundance estimates established a current habitat characterization of cetacean species in these waters and have the potential to be used to support management decisions and conservation measures in a marine spatial planning context.

Automated classification of dolphin echolocation click types from the Gulf of Mexico.

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.

Habitat-based cetacean density models for the U.S. Atlantic and Gulf of Mexico.

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.

Passive acoustic monitoring of beaked whale densities in the Gulf of Mexico.

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.

Review of historical unusual mortality events (UMEs) in the Gulf of Mexico (1990-2009): providing context for the multi-year northern Gulf of Mexico cetacean UME declared in 2010.

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.

Fine-scale spatial variation of persistent organic pollutants in bottlenose dolphins (Tursiops truncatus) in Biscayne Bay, Florida.

Bottlenose dolphins (Tursiops truncatus) are long-term residents and apex predators in southeast U.S. estuaries and are vulnerable to bioaccumulation of persistent organic pollutants (POPs). Dart biopsy samples were collected from 45 dolphins in Biscayne Bay (Miami, FL), 34 of which were matched using fin markings to a photo identification catalogue. Blubber samples were analyzed for 73 polychlorinated biphenyl (PCB) congeners, six polybrominated diphenyl ether (PBDE) congeners, and organochlorine pesticides including dichloro-diphenyl-trichloroethane (DDT) and metabolites, chlordanes, and dieldrin. Total PCBs (sigma 73PCBs) were present in the highest concentrations and were 5 times higher in males with sighting histories in the northern, metropolitan area of Biscayne Bay than males with sighting histories in the southern, more rural area [geometric mean: 43.3 (95% confidence interval: 28.0-66.9) vs 8.6 (6.3-11.9) microg/g wet mass, respectively]. All compound classes had higher concentrations in northern animals than southern. The differences in POP concentrations found on this small geographic scale demonstrate that differential habitat use can strongly influence pollutant concentrations and should be considered when interpreting bottlenose dolphin POP data. The PCB concentrations in northern Bay dolphins are high as compared to other studies of estuarine dolphins and may place these animals at risk of reproductive failure and decreased immune function.