[PDF] Development Of A Species Distribution Model For The East Pacific Green Sea Turtle Using Ecological Geoprocessing Tools eBook
Development Of A Species Distribution Model For The East Pacific Green Sea Turtle Using Ecological Geoprocessing Tools Book in PDF, ePub and Kindle version is available to download in english. Read online anytime anywhere directly from your device. Click on the download button below to get a free pdf file of Development Of A Species Distribution Model For The East Pacific Green Sea Turtle Using Ecological Geoprocessing Tools book. This book definitely worth reading, it is an incredibly well-written.
East Pacific green sea turtles, Chelonia mydas, play ecologically important roles in marine habitats which range from grazing (and thus regularly "mowing") algae and seagrass beds to cycling nutrients between the ocean and land. However, these important grazers have been hunted to ecological extinction in some places for their eggs, meat, and skin. The conservation initiative for the survival of sea turtles requires the protection of their primary habitats in conjunction with a decrease in their interaction with humans. One way these objectives can be met is through the creation of species distribution maps (SDMs). For this thesis, a SDM was created from a generalized additive model used to identify major feeding areas for East Pacific green turtles residing in the Galapagos Islands. The input for the model was green turtle sighting locations during a June 2010 marine life observation survey and remotely sensed values of four oceanographic parameters obtained from satellite sensors (Bathymetry, Sea Surface Temperature, Chlorophyll a, and Current Speed). Line transects of intertidal and subtidal shoreline regions of the islands of Isabela, San Cristobal, and Floreana were also completed, to describe similarities and differences in macroalgal abundance between the locations. A generalized additive model (GAM) explained 56% of the data's null deviance and had a true positive rate of 0.83. The corresponding species distribution map indicated that East Pacific green sea turtles prefer to forage in warm, low chlorophyll a, slow moving waters at depths mostly less than 250m throughout the archipelago. ANOVA analyses showed that macroalgal abundance was statistically different (p-value
Sea turtles are flagship species for the world's oceans. They traverse international boundaries during their migrations, serve as vehicles for marine nutrients to terrestrial habitats, and embody the often tenuous relationship between human action and ecosystem health. The East Pacific Ocean is home to some of the most dynamic marine ecosystems, and the most unique sea turtles. Marine biodiversity within this massive ocean region abounds in mangrove estuaries, seagrass pastures, coral reefs, the open ocean, and many other habitats, with sea turtles often the most conspicuous species present. The distinctive traits of the Eastern Pacific have resulted in the smallest leatherbacks, a singular morph of the green turtle, dark and steeply domed olive ridleys, and the most cryptic hawksbills on the planet. Only now are we beginning to understand how these varieties have evolved. However, the oceanographic conditions that make this an epicenter of sea turtle activity also promote massive artisanal and industrial fishing efforts that, coupled with illegal harvesting of eggs and turtles, have led to declines of several turtle populations in the region. The essays and stories in Sea Turtles of the Eastern Pacific describe for the first time the history of this exploitation, as well as recent sea turtle conservation initiatives and scientific research in the region. The first third of the book considers the biology of the turtles, focusing on general overviews of current ecological management challenges facing the turtles' survival. The second third treats issues of marine policy related to turtle conservation. In conclusion, the book offers six compelling stories of conservation success. By the end, readers will have gained a in-depth view not only of these magnificent creatures, but also the people involved in research and conservation efforts in one of the most remarkable regions of our planet.
All six species of sea turtles found in U.S. waters are listed as endangered or threatened, but the exact population sizes of these species are unknown due to a lack of key information regarding birth and survival rates. The U.S. Endangered Species Act prohibits the hunting of sea turtles and reduces incidental losses from activities such as shrimp trawling and development on beaches used for nesting. However, current monitoring does not provide enough information on sea turtle populations to evaluate the effectiveness of these protective measures. Sea Turtle Status and Trends reviews current methods for assessing sea turtle populations and finds that although counts of sea turtles are essential, more detailed information on sea turtle biology, such as survival rates and breeding patterns, is needed to predict and understand changes in populations in order to develop successful management and conservation plans.
Green sea turtles, Chelonia mydas, utilize coastal areas as foraging grounds for the majority of their lives. Human development of coastlines is increasing, but the effects of the urbanization of foraging grounds on green turtles are poorly understood. I used both manual and automated acoustic telemetry to determine the home ranges, movement behavior, and temporal patterns of site visitation of green turtles during 2009-2011 in San Diego Bay, California, a highly urbanized temperate foraging area. The home ranges of all tracked turtles were restricted to the southern portion of San Diego Bay, where eelgrass (Zostera marina) is abundant and where human activity is the lowest within the bay. Core activity areas coincided with eelgrass distribution or occurred adjacent to the warm water-effluent outfall of a waterfront power plant. Automated monitoring of sites throughout south San Diego Bay confirmed this finding, showing that green turtles most frequently visited the outfall of the power plant and areas known to contain eelgrass. This method also elucidated that turtle presence at the power plant was strongest during the winter and at night, whereas visitation to eelgrass areas was strongest during the spring and in the daytime. Turtle visitation to a high boat traffic shipping terminal was rare but occurred almost exclusively during the daytime, the period during which human activities in the area are also the highest. Manual tracking of green turtles similarly demonstrated that individuals ranged across larger portions of south San Diego Bay during the day, during which they exhibited high swimming speeds but highly non-linear movement. Turtle activity at night was primarily restricted to the power plant's effluent outfall channel and adjacent jetty. Nighttime movement was characterized by long periods of inactivity sporadically interrupted by brief, linear movements to new resting locations. Collectively, the results of this study paint a robust picture of the spatial, diel, and seasonal patterns of habitat use by green turtles in San Diego Bay. All data support the hypothesis that south San Diego Bay serves as important turtle habitat within the bay. Further, a combination of manual and automated acoustic telemetry enables a more complete understanding of turtle spatial ecology that would not have been possible with exclusive use of one technique. Future monitoring and modeling is required to document the potential effects of changing environmental conditions, including power plant closure, on green turtles resident to San Diego Bay. This study helps to assess the data gap of how turtles use urbanized foraging areas and changing coastal ecosystems, a currently novel scenario that will likely become commonplace in the face of increasing coastal development worldwide.
Project Overview. Thermal characteristics of marine environments are changing rapidly on both global and local scales. Worldwide, ocean temperatures are increasing -- a trend expected to continue (Meehl et al. 2005; Bindoff et al. 2007; IPCC 2007). However, at the local level water temperature is more variable, demonstrating both warming and cooling through space and time (Hoegh-Guldberg and Bruno 2010; Kosaka and Xie 2013). Many marine organisms are adapted to specific, often highly constrained, thermal ranges. Global climate change and anthropogenic influences have already had dramatic effects on marine species (Harley et al. 2006; IPCC 2007; Hoegh-Guldberg and Bruno 2010). While large-scale changes in temperature can be attributed to shifts in the global climate regime, there are other human-mediated factors that influence local thermal conditions. One major anthropogenic influence on local marine environments is thermal effluent from power plants and industry that utilize once-through cooling (OTC) systems. The stations that use OTC systems generate waste heat, a by-product of the cooling process, which must be released into the environment (either via cooling towers or natural water source). Thus, OTC system stations alter the thermal environment proximate to their locations. Although local and global scale changes may be driven by different factors, changes to the thermal environment at the local level can provide a model system to study the effects of largescale climate change. Characterizing the responses of coastal fauna to rapid shifts in thermal conditions addresses a key gap in ecological knowledge -- understanding how populations of longlived marine vertebrates will be affected by a thermally dynamic environment that is changing at rapid rate. The fossil fuel-based South Bay Power Plant (SBPP) in San Diego, California was in operation from 1960 to 2010 and discharged warm-water effluent into southern San Diego Bay (SDB) and utilized an OTC system. East Pacific green sea turtles (Chelonia mydas), resident in SDB since at least the 1890's (Parsons 1962), have been routinely observed in the power plant outfall area since the 1960s (Stinson 1984; McDonald and Dutton 1990). Previous research suggests that these turtles used the outfall area to reduce metabolic costs and exhibit higher growth rates than other populations of green turtles (Eguchi et al. 2010, Eguchi et al. 2012). On December 31, 2009, two of the plant's four generators were permanently shut down; complete decommissioning of the plant occurred on December 31, 2010. This power plant closure provided a rare experimental opportunity to assess how rapid changes in the thermal environment will affect a resident marine turtle population in a coastal foraging area. The first chapter of my dissertation represents a review of the scientific studies that demonstrated physiological and behavioral changes across mobile aquatic reptiles utilizing these areas with heated effluent. I identify key responses to thermal effluent in reptiles in both marine and freshwater environments and present a case study from green turtles in SDB. The second chapter of my dissertation reflects my research using acoustic telemetry to monitor the changes in distribution and behavior of green turtles in response to the closure of the SBPP. The third and final chapter of my dissertation summarizes the changes of dive behavior by green turtles before and after the closure of the SBPP.
Green sea turtles, Chelonia mydas, have endangered and threatened populations globally, but several populations show signs of population recovery. In Hawaii, nesting female green turtles have increased 5.7% year−1 since 1973, but wide fluctuations in census counts of nesting females make recovery diagnosis difficult. For effective management planning, it is critical to have the best information possible on vital rates, and to determine the best tools and practices for incorporating vital rate information, particularly variability, into population models to assess population size and status. Process and observation errors, compounded by late maturity, obscure the relationship between trends on the nesting beach and the entire population. Using sea turtle nesting beach surveys as a population index for assessment is problematic, yet often pragmatic because this is the only population index that is easily accessible. It is advantageous to use a modelling approach that estimates interannual variability in life history traits, accounts for uncertainty from individual-level variability, and allows for population dynamics to emerge from individual behaviors. To this end, I analyzed a long-term data set of marked green sea turtles to determine the degree of temporal variability in key life history traits. From this analysis, I built an agent-based model (ABM) to form the basis of a new assessment tool -- Monitoring Strategy Evaluation. In Chapter 2, I evaluated annual changes in demographic indicators (DIs) of 3,677 nesting green turtles from a 38-year tagging program in the Hawaiian Islands to determine if key life history traits are changing over time and in response to nester density. I used linear mixed models and multistate open robust design models to estimate several DIs and correlated them with nesting female counts. Mean nester carapace length and breeding probability were highly variable over time, suggesting shifts in age structure that could be due to recruitment. The top-ranked model predicted constant female survival over time. A significant positive relationship between the nesting population and breeding probability was evident, and breeding probability shows promise as an indicator of population recovery. This work contributes to a growing set of studies evaluating sea turtle demography for temporal variability and is the first for Hawaiian green turtles. In Chapter 3, I develop the Green Sea Turtle Agent-Based Model (GSTABM) to evaluate how recovery processes differ across disturbance types. The GSTABM incorporates individually variable age-at-maturity, clutch frequency and clutch size, annually variable breeding probability, environmental stochasticity and density dependence in hatchling production. The GSTABM simulates the process of population impact and recovery and the monitoring process, with observation error, on the nesting beach. The GSTABM captures the emergent patterns of interannual nesting variation, nester recruitment, and realistic population growth rates. Changes in survival rates of the nearshore age-stage classes directly affected adult and nester abundance, population growth rate and nester recruitment more than any of the other input parameters. In simulating 100 years of recovery, experimentally disturbed populations began to increase but did not fully return to pre-disturbance levels in adult and nester abundance, population growth or nester recruitment. In simulations with different levels of monitoring effort, adult abundance was poorly estimated, was influenced by population trajectory and disturbance type, and showed marginal improvements in accuracy with increased detection probability. Estimating recruitment showed improvements with increasing detection levels. In the GSTABM, variability in the nesting beach does not mirror variability in adult abundance. The GSTABM is an important tool to determine relationships with monitoring, population assessment, and the underlying biological processes driving changes in the population, and especially, changes on the nesting beach. In Chapter 4, I develop a new simulation-based tool: Monitoring Strategy Evaluation (MoSE) to determine which data source yields the most useful information for population assessments. The MoSE has three main components: the simulated "true" operating, observation, and estimation models. To explore this first use of MoSE, I apply different treatments of disturbance, sampling, and detection to the virtual "true" population, and then sample the nests or nesters, with observation error, to test if the observation "data" accurately diagnose population status indicators. Based on the observed data, I estimated adult abundance, nester recruitment, and population trend and compare them to the known values. I tested the accuracy of the estimated abundance when annually varying inputs of breeding probability, detection and clutch frequency were used instead of constants. I also explored the improvement of trend accuracy with increased study duration. Disturbance type and severity can have important and persistent effects on the accuracy of population assessments drawn from monitoring rookeries. Accuracy in abundance estimates may be most improved by avoiding clutch frequency bias in sampling and including annually varying inputs in the estimation model. Accuracy of nester recruitment may be most improved by increasing detection level and avoiding age-bias in sampling. The accuracy of estimating population trend is most influenced by the underlying population trajectory, disturbance type and disturbance severity. At least 10 years of monitoring data are necessary to accurately estimate population trend, and longer if juvenile age classes were disturbed and trend estimates occur during the recovery phase. The MoSE is an important tool for sea turtle biologists and conservation managers and allows biologists to make informed decisions regarding the best monitoring strategies to employ for sea turtles. This modeling framework is designed to provide an evaluation of monitoring program effectiveness to assist in planning future programs for sea turtles. Altogether, my research suggests certain life history traits of green sea turtles have important temporal variation that should be accounted for in population models, understanding the relationships between nesting and the total population is essential, and basing population assessments from nesting beach data alone is likely to result in incorrect or biased estimates of status indicators. The quantitative tools employed here can be applied to other sea turtle populations and will improve monitoring, and result in better estimates of current population trends and enhance conservation for all species of sea turtles.
"Thirty years ago when interest in sea turtles was beginning to spread, the ,habitat of the post-hatchlings for all the species was unknown. After they left the nest and made their way through the surf, they simply disappeared. Very slowly, data to suggest a pelagic life in a sargassum weed habitat accumulated, and eventually I received support to investigate that idea intensively. By the end of that research period it was clear that when sargassum rafts are present in longshore arrays within the swimming range of the hatchlings, they do in fact enter them (Carr 1982). It followed that the early developmental stages are pelagic, with the corollary that, because sargassum accumulates along convergences, the adjacent currents may carry the rafts and their occupants on journeys of either local or oceanic extent or both"--Introduction.