Document Type

Article

Department/Program

Virginia Institute of Marine Science

Publication Date

10-2020

Journal

Marine and Coastal Fisheries

Volume

12

Issue

5

First Page

348

Last Page

363

Abstract

Highly mobile species can be challenging for fisheries management and conservation due to large home ranges combined with dependence on discrete habitat areas where they can be easily targeted or vulnerable to anthropogenic disturbances. Management of the Dusky Shark Carcharhinus obscurus in the northwest Atlantic Ocean has been particularly challenging due to the species' inherent vulnerability to overfishing and poorly understood habitat associations. To better understand habitat associations and seasonal distributions, we combined telemetry and remotely sensed environmental data to spatially model juvenile Dusky Shark presence probability in the northwest Atlantic Ocean. To accomplish this, 22 juvenile Dusky Sharks (107-220 cm TL) that were tagged with acoustic transmitters at different locations within the U.S. Middle Atlantic Bight region were tracked through networked arrays of acoustic receivers. Tag detections were summarized as daily presence records, and data describing environmental conditions, including depth, chlorophyll-a concentration, salinity, and sea surface temperature, were extracted at detection locations. These data were used in boosted regression tree models to predict juvenile Dusky Shark presence probability based on environmental parameters during fall 2017 and summer 2018. Telemetry observations and modeled presence probability showed consistent associations with temperatures between 16 degrees C and 26 degrees C and chlorophyll-a concentrations between 2 and 7 mg/m(3), which were associated with seasonal migration timing and monthly spatial distributions. Dusky Shark tag detections and predicted distributions during summer and early fall overlapped areas in the Middle Atlantic Bight that were affected by fisheries and potential offshore energy development. Our methodology provides a framework for assessing climate change effects on distribution.

DOI

DOI: 10.1002/mcf2.10120

Creative Commons License

Creative Commons Attribution 4.0 License
This work is licensed under a Creative Commons Attribution 4.0 License.

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