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McGinley E, Cogley A, Palmer L, McCaul P, Longo L, Silvennoinen J, Martin A, Gomez J, Bachmaier S, Mackey M, Kao C, Eastman S, Eastman C. Marina Observation of Sea Turtles: Establishing a Database of Intracoastal Waterway Green Sea Turtles in Northeast Florida. Animals (Basel) 2023; 13:ani13020279. [PMID: 36670819 PMCID: PMC9854553 DOI: 10.3390/ani13020279] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2022] [Revised: 01/09/2023] [Accepted: 01/11/2023] [Indexed: 01/15/2023] Open
Abstract
As conservation efforts regarding green sea turtles, Chelonia mydas, continue, it is imperative to document behaviors and foraging habits/habitats of understudied populations. We have conducted an 18-month study dedicated to photographing the local population feeding alongside floating docks within the Guana Tolomato Matanzas estuary to determine the capability of matching head scale patterns efficiently through a pattern matching program: HotSpotter. To date, 195 unique sea turtles have been identified between two different marinas located in St. Augustine, FL. Of these, 98 were spotted more than once, with 39 of them being "tracked" for longer than a year. Temperature trends were also monitored in conjunction, showing that more individuals appeared during the warmer months of the year. The evidence, overall, indicates that these locations host a resident population of green sea turtles, leading to the need for a discussion on potential threats originating from the usage of these marinas by humans.
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Affiliation(s)
- Edward McGinley
- Department of Natural Sciences, Flagler College, St. Augustine, FL 32084, USA
- Correspondence:
| | - Avery Cogley
- Department of Natural Sciences, Flagler College, St. Augustine, FL 32084, USA
| | - Leslie Palmer
- Department of Natural Sciences, Flagler College, St. Augustine, FL 32084, USA
| | - Patricia McCaul
- Department of Natural Sciences, Flagler College, St. Augustine, FL 32084, USA
| | - Lilli Longo
- Department of Natural Sciences, Flagler College, St. Augustine, FL 32084, USA
| | | | - Angela Martin
- Department of Natural Sciences, Flagler College, St. Augustine, FL 32084, USA
| | - Josalyn Gomez
- Department of Natural Sciences, Flagler College, St. Augustine, FL 32084, USA
| | - Sydney Bachmaier
- Department of Natural Sciences, Flagler College, St. Augustine, FL 32084, USA
| | - Michaela Mackey
- Department of Natural Sciences, Flagler College, St. Augustine, FL 32084, USA
| | - Chris Kao
- Department of Mathematics and Technology, Flagler College, St. Augustine, FL 32084, USA
| | - Scott Eastman
- Office of Resilience and Coastal Protection, Florida Department of Environmental Protection, St. Augustine, FL 32080, USA
| | - Catherine Eastman
- Whitney Laboratory, University of Florida, St. Augustine, Fl 32080, USA
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Thomas‐Walters L, Vieira S, Jiménez V, Monteiro D, Ferreira B, Smith RJ, Veríssimo D. Challenges in the impact evaluation of behaviour change interventions: The case of sea turtle meat and eggs in São Tomé. PEOPLE AND NATURE 2020. [DOI: 10.1002/pan3.10162] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022] Open
Affiliation(s)
- Laura Thomas‐Walters
- Durrell Institute of Conservation and Ecology School of Anthropology and Conservation University of Kent Canterbury UK
| | - Sara Vieira
- Programa Tatô Largo do Bom Despacho Cidade de São Tomé São Tomé Sao Tome and Principe
| | - Victor Jiménez
- Programa Tatô Sítio da Pedragosa Barão de São João Portugal
| | - Domingas Monteiro
- Programa Tatô Largo do Bom Despacho Cidade de São Tomé São Tomé Sao Tome and Principe
| | | | - Robert J. Smith
- Durrell Institute of Conservation and Ecology School of Anthropology and Conservation University of Kent Canterbury UK
| | - Diogo Veríssimo
- Department of Zoology University of Oxford Oxford UK
- San Diego Zoo Institute for Conservation Research Escondido CA USA
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Ceriani SA, Casale P, Brost M, Leone EH, Witherington BE. Conservation implications of sea turtle nesting trends: elusive recovery of a globally important loggerhead population. Ecosphere 2019. [DOI: 10.1002/ecs2.2936] [Citation(s) in RCA: 36] [Impact Index Per Article: 7.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022] Open
Affiliation(s)
- S. A. Ceriani
- Florida Fish and Wildlife Conservation Commission Fish and Wildlife Research Institute Saint Petersburg Florida 33701 USA
| | - P. Casale
- Department of Biology University of Pisa Pisa Italy
| | - M. Brost
- Florida Fish and Wildlife Conservation Commission Fish and Wildlife Research Institute Saint Petersburg Florida 33701 USA
| | - E. H. Leone
- Florida Fish and Wildlife Conservation Commission Fish and Wildlife Research Institute 1105 SW Williston Road Gainesville Florida 32601 USA
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Hatch JM, Haas HL, Richards PM, Rose KA. Life-history constraints on maximum population growth for loggerhead turtles in the northwest Atlantic. Ecol Evol 2019; 9:9442-9452. [PMID: 31534667 PMCID: PMC6745678 DOI: 10.1002/ece3.5398] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2019] [Revised: 05/31/2019] [Accepted: 06/04/2019] [Indexed: 11/07/2022] Open
Abstract
Conservation planning for protected species often relies on estimates of life-history parameters. A commonly used parameter is the instantaneous maximum population growth rate (r max) that can be used to limit removals and design recovery targets. Estimation of r max can be challenging because of limited availability of species- and population-specific data and life-history information. We applied a method proposed by Neil and Lebreton, originally developed for birds, to loggerhead turtles. The method uses age-at-first-reproduction and adult survival to estimate r max. We used a variety of datasets and matrix population models to confirm an allometric assumption required by the method, and to generate estimates of age-at-first-reproduction and adult survival. A meta-analysis was applied to parameters from reported growth curves, which were then combined with the size distribution of neophyte nesters to derive estimates of age-at-first-reproduction. Adult survival rates were obtained from an existing matrix population model. Monte Carlo simulation was then used to combine the estimates of the allometric coefficients, age-at-first-reproduction, and adult survival to obtain a probability distribution of approximate r max values. Estimated annual maximum population growth rates averaged 0.024, with a mode of 0.017 and a 95% highest density interval of 0.006-0.047. These estimates were similar to values reported by others using different methods and captured the variability in positive, annual change estimates across nesting beach sites for the northwest Atlantic loggerhead population. The use of life-history parameters has a long history in wildlife and fisheries management and conservation planning. Our estimates of r max, while having some biases and uncertainty, encompassed values presently used in recovery planning for loggerhead turtles and offer additional information for the management of endangered and threatened species.
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Affiliation(s)
- Joshua M. Hatch
- NOAA National Marine Fisheries Service, NEFSCWoods HoleMAUSA
| | - Heather L. Haas
- NOAA National Marine Fisheries Service, NEFSCWoods HoleMAUSA
| | | | - Kenneth A. Rose
- Horn Point LaboratoryUniversity of Maryland Center for Environmental ScienceCambridgeMDUSA
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Piacenza SE, Richards PM, Heppell SS. Fathoming sea turtles: monitoring strategy evaluation to improve conservation status assessments. ECOLOGICAL APPLICATIONS : A PUBLICATION OF THE ECOLOGICAL SOCIETY OF AMERICA 2019; 29:e01942. [PMID: 31267602 PMCID: PMC6851787 DOI: 10.1002/eap.1942] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/05/2018] [Revised: 04/18/2019] [Accepted: 04/23/2019] [Indexed: 06/09/2023]
Abstract
Population monitoring must be accurate and reliable to correctly classify population status. For sea turtles, nesting beach surveys are often the only population-level surveys that are accessible. However, process and observation errors, compounded by delayed maturity, obscure the relationship between trends on the nesting beach and the population. We present a simulation-based tool, monitoring strategy evaluation (MoSE), to test the relationships between monitoring data and assessment accuracy, using green sea turtles, Chelonia mydas, as a case study. To explore this first application of MoSE, we apply different treatments of population impacts to virtual true populations, and sample the nests or nesters, with observation error, to test if the observation data can be used to diagnose population status accurately. Based on the observed data, we examine population trend and compare it to the known values from the operating model. We ran a series of scenarios including harvest impacts, cyclical breeding probability, and sampling biases, to see how these factors impact accuracy in estimating population trend. We explored the necessary duration of monitoring for accurate trend estimation and the probability of a false trend diagnosis. Our results suggest that disturbance type and severity can have important and persistent effects on the accuracy of population assessments drawn from monitoring nesting beaches. The underlying population phase, age classes disturbed, and impact severity influenced the accuracy of estimating population trend. At least 10 yr of monitoring data is necessary to estimate population trend accurately, and >20 yr if juvenile age classes were disturbed and the population is recovering. In general, there is a greater probability of making a false positive trend diagnosis than a false negative, but this depends on impact type and severity, population phase, and sampling duration. Improving detection rates to 90% does little to lower probability of a false trend diagnosis with shorter monitoring spans. Altogether, monitoring strategies for specific populations may be tailored based on the impact history, population phase, and environmental drivers. The MoSE is an important framework for analysis through simulation that can comprehensively test population assessments for accuracy and inform policy recommendations regarding the best monitoring strategies.
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Affiliation(s)
- Susan E. Piacenza
- Department of Fisheries and WildlifeOregon State UniversityCorvallisOregon97330USA
- Present address:
Department of BiologyUniversity of West FloridaPensacolaFlorida32514USA
| | - Paul M. Richards
- NOAA NMFS, Southeast Fisheries Science CenterMiamiFlorida33149USA
| | - Selina S. Heppell
- Department of Fisheries and WildlifeOregon State UniversityCorvallisOregon97330USA
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