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Examining The Influence Of Beach Morphology On Sea Turtle Nesting Behavior In The Years 2010, 2016, And 2020 On Santa Rosa Island And Perdido Key, Fl
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Examining The Influence Of Beach Morphology On Sea Turtle Nesting Behavior In The Years 2010, 2016, And 2020 On Santa Rosa Island And Perdido Key, Fl

Divina Yolanda Cox
University of West Florida Libraries
Master of Science (MS), University of West Florida
2024

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Abstract

The sea turtle nesting population has been declining at a rapid rate. The decline is due to climate change, rising sea levels, and human destruction. When locating the perfect nest site sea turtles search for specific morphological characteristics such as elevation and beach slope. It is essential to comprehend the connection between nest site selection and morphological characteristics. In the Florida Panhandle, Loggerhead nesting sites are among the least abundant in the region. Both Pensacola Beach and Gulf Islands National Seashore have witnessed alterations in their natural beach composition, influenced by a combination of natural phenomena and human activities. These alterations may potentially impact the nesting preferences of sea turtles in the region. Nesting preferences were assessed through the utilization of historical LiDAR flight data, extracting specific beach and dune morphological characteristics from Santa Rosa Island to Perdido Key, Florida. The influence of geomorphic features on sea turtle nesting habitat was evaluated by examining LiDAR data from 2010, 2016, and 2020. The similarities and differences between these years were studied to comprehend the evolving geomorphic characteristics. Calculation for the characteristic was produce in relation to the data of the National Tidal Datum in 2018; the Mean Higher High Water (MHHW) is 0.25 meters. In relation to the National Tidal Datum in 2018, the Mean Lower Low Water (MLLW) is -0.14 meters. DEM for each year was collected from NOAA Digital Coast and converted into a polygon using ArcGIS. Following layering the matching nest point onto the polygon, a profile line segment that runs from the waterline to the polygon's end was created to determine each point's distance from the seashore. To display data and provide a deeper understanding of nesting site preferences, pseudo-absence points were produced at a 1:1 ratio. Logistic regression was used to ascertain substantial variations between beach morphology at the nest and pseudo-absence locations. A model of logistical regression was developed to investigate pseudo-absence and nested points. To represent the median and interquartile range, 1st quartile and 3rd quartile, box plots were generated. A logistic regression model was created to examine nested and pseudo-absence points. The data were utilized to analyze variances and similarities among historical years and geomorphic traits, aiming to comprehend the nesting preferences of loggerhead turtles. The findings revealed that only foredune height and nest elevation exhibited significance in the model. This suggests that sea turtles show a preference for nesting at higher elevations on tall foredunes rather than lower elevations on low foredunes within the study dataset. Furthermore, the data also indicated that foreshore slope and nest elevation were the only factors that demonstrated statistical significance when subjected to variance testing using ANOVA. This study offers valuable insights into sea turtle nesting preferences concerning beach morphology, potentially aiding environmental managers in devising targeted conservation strategies to safeguard nesting sites.
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