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Variability in Coastal Shark Populat...

Benavides, Martin Tomas.

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Variability in Coastal Shark Populations Across Multiple Spatiotemporal Scales.

Record Type:	Electronic resources : Monograph/item
Title/Author:	Variability in Coastal Shark Populations Across Multiple Spatiotemporal Scales./
Author:	Benavides, Martin Tomas.
Published:	Ann Arbor : ProQuest Dissertations & Theses, : 2020,
Description:	128 p.
Notes:	Source: Dissertations Abstracts International, Volume: 82-01, Section: B.
Contained By:	Dissertations Abstracts International82-01B.
Subject:	Ecology. -
Online resource:	https://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=27963703
ISBN:	9781083558602

Variability in Coastal Shark Populations Across Multiple Spatiotemporal Scales.
Benavides, Martin Tomas.

Variability in Coastal Shark Populations Across Multiple Spatiotemporal Scales. - Ann Arbor : ProQuest Dissertations & Theses, 2020 - 128 p.

Source: Dissertations Abstracts International, Volume: 82-01, Section: B.

Thesis (Ph.D.)--The University of North Carolina at Chapel Hill, 2020.

This item must not be sold to any third party vendors.

Variability across spatiotemporal scales has been recognized by ecologists as a fundamental issue in understanding ecosystem dynamics. Sharks emerged as a conservation concern as their populations declined and their influence on marine ecosystem dynamics became apparent. Efforts to better manage and understand shark populations and their response to anthropogenic pressures have been hindered by a lack of understanding of patterns across multiple scales of time and space. This dissertation aimed to describe patterns of variability in coastal shark populations across multiple spatiotemporal scales.Chapter 1 exploits a 45-year time series of shark monitoring to describe patterns of seasonality in the coastal shark community in Onslow Bay, North Carolina, and how seasonality shifted over long timescales (interannual-decadal). Seasonal turnover in coastal shark community composition was correlated with temperature changes, with spring/autumn species appearing first and subsequently being replaced by summer species before appearing again in autumn; both transitions occurred at approximately 25 °C. On interannual scales, this seasonal pattern was overshadowed by increases in abundance of the Atlantic sharpnose shark (Rhizoprionodon terraenovae), a non-seasonal species caught during all months of sampling. Chapter 2 utilizes the long-term data set to investigate within-species size structure over four decades. My analyses suggest declining trends in size for all species analyzed, with the strongest evidence for sizedeclines in two small coastal shark species, Atlantic sharpnose shark and blacknose shark (Carcharhinus acronotus). These results provide insight on assemblage-level responses to anthropogenic pressure via environmental or genetic mechanisms.Chapter 3 employs acoustic telemetry to decipher bonnethead shark (Sphyrna tiburo) movement and behavior (e.g., residency and habitat use) over multiple spatiotemporal scales. My results suggest individual bonnethead sharks show fidelity across years to specific areas within estuaries in North Carolina and Georgia during seasonal residency and have affinity for areas nearest inlets. Finally, Chapter 4 evaluates shark detection probabilities from aerial drone surveys and how these were affected by environmental conditions in a temperate estuary. Shark detection from drone surveys was most influenced by depth, wind speed, and time of day; the highest detection probabilities occurred at shallow depth, low wind speed, and mid-day flight times.

ISBN: 9781083558602Subjects--Topical Terms:

516476
Ecology.
Subjects--Index Terms:

Bonnethead shark

Variability in Coastal Shark Populations Across Multiple Spatiotemporal Scales.
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520 $a Variability across spatiotemporal scales has been recognized by ecologists as a fundamental issue in understanding ecosystem dynamics. Sharks emerged as a conservation concern as their populations declined and their influence on marine ecosystem dynamics became apparent. Efforts to better manage and understand shark populations and their response to anthropogenic pressures have been hindered by a lack of understanding of patterns across multiple scales of time and space. This dissertation aimed to describe patterns of variability in coastal shark populations across multiple spatiotemporal scales.Chapter 1 exploits a 45-year time series of shark monitoring to describe patterns of seasonality in the coastal shark community in Onslow Bay, North Carolina, and how seasonality shifted over long timescales (interannual-decadal). Seasonal turnover in coastal shark community composition was correlated with temperature changes, with spring/autumn species appearing first and subsequently being replaced by summer species before appearing again in autumn; both transitions occurred at approximately 25 °C. On interannual scales, this seasonal pattern was overshadowed by increases in abundance of the Atlantic sharpnose shark (Rhizoprionodon terraenovae), a non-seasonal species caught during all months of sampling. Chapter 2 utilizes the long-term data set to investigate within-species size structure over four decades. My analyses suggest declining trends in size for all species analyzed, with the strongest evidence for sizedeclines in two small coastal shark species, Atlantic sharpnose shark and blacknose shark (Carcharhinus acronotus). These results provide insight on assemblage-level responses to anthropogenic pressure via environmental or genetic mechanisms.Chapter 3 employs acoustic telemetry to decipher bonnethead shark (Sphyrna tiburo) movement and behavior (e.g., residency and habitat use) over multiple spatiotemporal scales. My results suggest individual bonnethead sharks show fidelity across years to specific areas within estuaries in North Carolina and Georgia during seasonal residency and have affinity for areas nearest inlets. Finally, Chapter 4 evaluates shark detection probabilities from aerial drone surveys and how these were affected by environmental conditions in a temperate estuary. Shark detection from drone surveys was most influenced by depth, wind speed, and time of day; the highest detection probabilities occurred at shallow depth, low wind speed, and mid-day flight times.
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