Interactions between marine mammals and pelagic longline fishing gear in the U.S. Atlantic Ocean between 1992 and 2004

The U.S. East Coast pelagic longline fishery has a history of interactions with marine mammals, where animals are hooked and entangled in longline gear. Pilot whales (Globicephala spp.) and Risso’s dolphin (Grampus griseus) are the primary species that interact with longline gear. Logistic regression was used to assess the environmental and gear characteristics that influence interaction rates. Pilot whale inter-actions were correlated with warm water temperatures, proximity to the shelf break, mainline lengths greater than 20 nautical miles, and damage to swordfish catch. Similarly, Risso’s dolphin interactions were correlated with geographic location, proximity the shelf break, the length of the mainline, and bait type. The incidental bycatch of marine mammals is likely associated with depredation of the commercial catch and is increased by the overlap between marine mammal and target species habitats. Altering gear characteristics and fishery practices may mitigate incidental bycatch and reduce economic losses due to depredation

Population consequences of the Deepwater Horizon oil spill on pelagic cetaceans

This research was made possible by a grant from the Gulf of Mexico Research Initiative to the Consortium for Advanced Research on Marine Mammal Health Assessment (CARMMHA). T.A.M. acknowledges partial support by CEAUL (funded by FCT−Fundação para a Ciência e a Tecnologia, Portugal, through project UIDB/00006/2020).The Deepwater Horizon disaster resulted in the release of 490000 m3 of oil into the northern Gulf of Mexico. We quantified population consequences for pelagic cetaceans, including sperm whales, beaked whales and 11 species of delphinids. We used existing spatial density models to establish pre-spill population size and distribution, and overlaid an oil footprint to estimate the proportion exposed to oil. This proportion ranged from 0.058 (Atlantic spotted dolphin, 95% CI = 0.041-0.078) to 0.377 (spinner dolphin, 95% CI = 0.217-0.555). We adapted a population dynamics model, developed for an estuarine population of bottlenose dolphins, to each pelagic species by scaling demographic parameters using literature-derived estimates of gestation duration. We used expert elicitation to translate knowledge from dedicated studies of oil effects on bottlenose dolphins to pelagic species and address how density dependence may affect reproduction. We quantified impact by comparing population trajectories under baseline and oil-impacted scenarios. The number of lost cetacean years (difference between trajectories, summed over years) ranged from 964 (short-finned pilot whale, 95% CI = 385-2291) to 32584 (oceanic bottlenose dolphin, 95% = CI 13377-71967). Maximum proportional population decrease ranged from 1.3% (Atlantic spotted dolphin 95% CI = 0.5-2.3) to 8.4% (spinner dolphin 95% CI = 3.2-17.7). Estimated time to recover to 95% of baseline was >10 yr for spinner dolphin (12 yr, 95% CI = 0-21) and sperm whale (11 yr, 95% CI = 0-21), while 7 taxonomic units remained within 95% of the baseline population size (time to recover, therefore, as per its definition, was 0). We investigated the sensitivity of results to alternative plausible inputs. Our methods are widely applicable for estimating population effects of stressors in the absence of direct measurements.Publisher PDFPeer reviewe

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

This research was enabled partly by a grant from The Gulf of Mexico Research Initiative (GOMRI).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.Publisher PDFPeer reviewe

The Influence of Nutritional Stress and Physical Transport on Zoeae of Estuarine Crabs

This electronic version varies from the print copies available from the Hargis Library and Special Collections Research Center in the Swem Library. The print version is considered the official and archival copy of this dissertation or thesis. Researchers are encouraged to consult the archival copy of this dissertation or thesis when citing this work

Differences in Acoustic Signals from Marine Mammals in the Western North Atlantic and Northern Gulf of Mexico

Differences in whistle types between species and populations of dolphins may arise from differences in body size, environmental conditions, geographic separation, and vocal learning between animals. Assessing vocalization differences between populations of delphinids, as well as the mechanism of divergence, has become a subject of interest since acoustic differences may help to distinguish between populations at sea. In this study, bottlenose dolphin (Tursiops truncatus), Atlantic spotted dolphin (Stenella frontalis), and pilot whale (Globicephala sp.) populations in U.S. waters were quantitatively compared to determine if differences in whistle structure exist between both neighboring and geographically separated populations. Comparisons were made for nine whistle characteristics between northern Gulf of Mexico and western North Atlantic populations of bottlenose dolphins and pilot whales and between continental shelf and offshore populations of Atlantic spotted dolphins in the western North Atlantic. Whistle characteristics were measured for 3,836 pilot whale whistles, 1,703 Atlantic spotted dolphin whistles, and 2,715 bottlenose dolphin whistles recorded between 2002 and 2004. Differences between groups were evaluated using principal components analysis and discriminant analysis. Bottlenose dolphin whistles in the Atlantic were significantly different (Hotelling’s T-squared, p \u3c 0.0001) from those in the Gulf of Mexico, differing chiefly in the whistle characteristics of end frequency, duration, and the number of inflection points. Offshore Atlantic spotted dolphin whistles were significantly different (Hotelling’s T-squared, p \u3c 0.0003) from those of the continental shelf population, differing principally in high frequency, central frequency, and bandwidth. No significant difference was found between pilot whale whistles in the two ocean basins. The whistle differences demonstrated in this study indicate that acoustic divergence exists between distinct populations and may arise from geographic isolation or due to habitat separation between neighboring but genetically distinct groups. This study suggests that acoustic studies are an excellent and cost-efficient method to assess population structure

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

Abstract 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

Genetic structure of common bottlenose dolphins (Tursiops truncatus) inhabiting adjacent South Florida estuaries – Biscayne Bay and Florida Bay

Coastal common bottlenose dolphins show a variety of migration and residency patterns adding to the difficulty of defining stocks for management purposes. Genetic structure plays an important role in identifying population stocks of dolphins. This study examines genetic differentiation in common bottlenose dolphins both between two social groups occurring in Biscayne Bay, Florida and between Biscayne Bay and an adjacent group of dolphins in Florida Bay. Skin biopsy samples were sequenced at the mitochondrial DNA (mtDNA) control region and genotyped at microsatellite loci. Significant genetic differentiation was found between bottlenose dolphins in Biscayne Bay and Florida Bay (mtDNA FST = 0.139, p ≤ 0.001; microsatellite FST = 0.042, p ≤ 0.001) supporting independent management stock status for these two populations. Within Biscayne Bay, evidence of weak but significant population differentiation was found between the two social groups using microsatellite markers (FST = 0.0149, p ≤ 0.009); however, differentiation was not evident from the mtDNA-based estimates of FST and φST. The lack of differentiation at mtDNA coupled with field observations indicating overlapping home ranges for these two groups suggests ongoing, though perhaps low, levels of interbreeding. These data are insufficient to warrant splitting the Biscayne Bay management stock at this time

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