The common bottlenose dolphin (Tursiops truncatus) is a key marine mammal species in the Gulf of Mexico, playing an essential role as a top predator. This study investigates the genetic diversity and population structure of bottlenose dolphins stranded in the Mississippi Sound from 2010 to 2021. Tissue samples (muscle, liver, lung, kidney, and brain) were collected from 511 stranded dolphins, and mitochondrial DNAs (mtDNA) were extracted for analysis. A total of 417 samples were successfully amplified and sequenced using high throughput sequencing, yielding 386 complete mitogenomes. Genetic diversity metrics, such as nucleotide and haplotype diversity, were calculated, and population structure was inferred for both mitochondrial control region (mtCR) and whole mitogenome sequences. Using the whole mitogenome, the study identified four genetically distinct populations within the Mississippi Sound, demonstrating regional variation in dolphin populations. Notably, two stranded individuals likely originated from populations outside the sampled area. The use of whole mitogenomes allowed for improved resolution of genetic diversity and population differentiation compared to previous studies using partial mtDNA sequences. These findings enhance our understanding of bottlenose dolphin population structure in the region and underscore the value of stranded animals for population genetic studies.
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Spatial and temporal variation in the occurrence of bottlenose dolphins in the Chesapeake Bay, USA, using citizen science sighting data
Bottlenose dolphins ( Tursiops truncatus ) are migratory marine mammals that live in both open-ocean and coastal habitats. Although widely studied, little is known about their occurrence patterns in the highly urbanized estuary of the Chesapeake Bay, USA. The goal of this study was to establish the spatial and temporal distribution of bottlenose dolphins throughout this large estuarine system and use statistical modeling techniques to determine how their distribution relates to environmental factors. Three years (April-October 2017–2019) of dolphin sighting reports from a citizen-science database, Chesapeake DolphinWatch, were analyzed. The dolphins had a distinct temporal pattern, most commonly sighted during summer months, peaking in July. This pattern of observed occurrence was confirmed with systematic, passive acoustic detections of dolphin echolocation clicks from local hydrophones. Using spatially-exclusive Generalized Additive Models (GAM), dolphin presence was found to be significantly correlated to spring tidal phase, warm water temperature (24–30°C), and salinities ranging from 6–22 PPT. We were also able to use these GAMs to predict dolphin occurrence in the Bay. These predictions were statistically correlated to the actual number of dolphin sighting reported to Chesapeake DolphinWatch during that time. These models for dolphin presence can be implemented as a predictive tool for species occurrence and inform management of this protected species within the Chesapeake Bay.
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- Award ID(s):
- 1756244
- PAR ID:
- 10250320
- Editor(s):
- Caballero, Susana
- Date Published:
- Journal Name:
- PLOS ONE
- Volume:
- 16
- Issue:
- 5
- ISSN:
- 1932-6203
- Page Range / eLocation ID:
- e0251637
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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