Ecological Niche Modeling, Index Standardization, And Recovery Times For Data-Limited Coastal Sharks
ORCID ID
https://orcid.org/0009-0003-2175-0636
Date Awarded
2024
Document Type
Dissertation
Degree Name
Doctor of Philosophy (Ph.D.)
Department
Virginia Institute of Marine Science
Advisor
Robert J Latour
Committee Member
John Graves
Committee Member
Marjy Friedrichs
Committee Member
Ross Iaci
Committee Member
Enric Cortés
Abstract
Coastal sharks, as part of the class Chondrichthyes, are one of the most threatened species groups in the world. Observation, assessment, and management are particularly challenging for these species due to their large distributions, complex migratory behaviors, low economic value, slow-growth rates and low-reproducive output (i.e., K-selected) life history strategies, and data limitations. Coastal sharks are also still recovering from overexploitation in the 1970s through 1990s, though recovery times are unknown for many species as most are too data-limited for species-specific stock assessments. Further, anthropogenic climate change is anticipated to impact coastal sharks in various ways and could affect shark management and assessments. Multiple risk assessments have reported that coastal shark species have a high potential to shift distributions in response to climate change. In this study, ecological niche models quantified baseline habitat associations for several small and large coastal shark species along the southeast US Atlantic and Gulf of Mexico across multiple sizes. Output from models indicated that impacts of anthropogenic climate change on environmental conditions, such as increased water temperature, impacted the quantity and quality of available habitat for coastal sharks. Evidence suggested that multiple species could shift distributions north along the Atlantic and/or to deeper offshore waters in the Atlantic and Gulf of Mexico. Additionally, species have the potential to redistribute in response to multidecadal climate variability for multiple species. Changes in species distributions and migration times for coastal shark species likely affect survey catchability and index interpretation. A spatiotemporal index standardization method was investigated for six different data-limited species and compared to two index driven standardization methods currently implemented in stock assessments. Previous studies noting a preliminary recovery of coastal shark populations may have been over-optimistic as only two of the six species examined displayed increasing abundance trends over time. Index standardization methods largely agreed with each other, but positive trends in density and increased variability in density anomalies in the spatiotemporal models suggested a northward expansion or a timing discrepancy between migration onset and sampling efforts for multiple species. Finally, using a stochastic Leslie matrix and Schaefer surplus production simulation, a framework was designed to estimate potential recovery times for data-limited and unassessed species, such as coastal sharks. Twenty-six shark stocks, consisting of small and large coastal sharks as well as dogfishes, were investigated as a case study. Estimated recovery times were compared to a data-moderate age-structured simulation that accounts for nuances specific to shark life history. Recovery times estimated from the Schaefer surplus production simulations were considered viable as a "best-case scenario" since this method routinely underestimated data-moderate simulations. Levels of stock depletion significantly impacted recovery estimates, highlighting the importance of early detection and quick response. Large coastal sharks recovered slower than small coastal sharks and dogfish recovery times varied. While most coastal shark stocks are unlikely to recover within 10 years, conservative estimates for the recovery of collapsed stocks of most large coastal sharks begin around 30 years, coinciding with the duration that shark management has been in place. Collectively, the results of this dissertation help address how anthropogenic climate change impacts coastal shark populations and their management while also providing valuable information regarding the recovery of data-limited and overexploited stocks.
DOI
https://dx.doi.org/10.25773/v5-zhar-2124
Rights
© The Author
Recommended Citation
O'Brien, Kaitlyn, "Ecological Niche Modeling, Index Standardization, And Recovery Times For Data-Limited Coastal Sharks" (2024). Dissertations, Theses, and Masters Projects. William & Mary. Paper 1725391385.
https://dx.doi.org/10.25773/v5-zhar-2124
