AI Article Synopsis

  • Bottlenose dolphins are migratory mammals found in both open-ocean and coastal areas, yet their patterns in the Chesapeake Bay are under-researched.
  • The study analyzed three years of dolphin sightings using citizen science reports, finding that dolphins are most frequently seen during the summer, peaking in July, a trend confirmed by acoustic data.
  • Statistical models identified that dolphin presence is linked to specific environmental conditions, such as spring tidal phases, warm water temperatures, and salinity levels, and could be used as a tool to predict dolphin occurrences in the Bay for better conservation management.

Article Abstract

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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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8130941PMC
http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0251637PLOS

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