Nesting In The Clouds: Evaluating And Predicting Sea Turtle Nesting Beach Parameters From Lidar Data

Humans' desire for knowledge regarding animal species and their interactions with the natural world have spurred centuries of studies. The relatively new development of remote sensing systems using satellite or aircraft-borne sensors has opened up a wide field of research, which unfortunately largely remains dependent on coarse-scale image spatial resolution, particularly for habitat modeling. For habitat-specialized species, such data may not be sufficient to successfully capture the nuances of their preferred areas. Of particular concern are those species for which topographic feature attributes are a main limiting factor for habitat use. Coarse spatial resolution data can smooth over details that may be essential for habitat characterization. Three studies focusing on sea turtle nesting beaches were completed to serve as an example of how topography can be a main deciding factor for certain species. Light Detection and Ranging (LiDAR) data were used to illustrate that fine spatial scale data can provide information not readily captured by either field work or coarser spatial scale sources. The variables extracted from the LiDAR data could successfully model nesting density for loggerhead (Caretta caretta), green (Chelonia mydas), and leatherback (Dermochelys coriacea) sea turtle species using morphological beach characteristics, highlight beach changes over time and their correlations with nesting success, and provide comparisons for nesting density models across large geographic areas. Comparisons between the LiDAR dataset and other digital elevation models (DEMs) confirmed that fine spatial scale data sources provide more similar habitat information than those with coarser spatial scales. Although these studies focused solely on sea turtles, the underlying principles are applicable for many other wildlife species whose range and behavior may be influenced by topographic features.

DUI program as OEF/OIF Veterans Outreach: Descriptive Data from Two Community-Based Outpatient Clinics

Although initially conceived as providing simply the preventive portion of an extended continuum of care for veterans, the Driving Under the Influence (DUI) program has turned out to be an important outreach service for active duty or recently discharged OEF/OIF (Operation Enduring Freedom/Operation Iraqi Freedom) veterans. Veterans receive empirically-based, state-mandated education and therapy under the only Department of Veterans Affairs (VA) - sponsored DUI program in the State of Colorado, with the advantage of having providers who are sensitive to symptoms of Post-Traumatic Stress Disorder (PTSD) and other relevant diagnoses specific to this population, including Traumatic Brain Injury (TBI). In this paper, the rapid growth of this program is described, as well as summary data regarding the completion, discontinuation, and augmentation of services from the original referral concern. Key results indicated that for nearly one third (31.9%) of the OEF/OIF veterans who were enrolled in the DUI program, this was their initial contact with the VA health care system. Furthermore, following their enrollment in the DUI program, more than one fourth (27.6%) were later referred to and attended other VA programs including PTSD rehabilitation and group therapy, anger management, and intensive inpatient or outpatient dual diagnosis programs. These and other findings from this study suggest that the DUI program may be an effective additional pathway for providing treatment that is particularly salient to the distinctive OEF/OIF population; one that may also result in earlier intervention for problem drinking and other problems related to combat. Relevant conclusions discussed herein primarily aim to improve providers' understanding of effective outreach, and to enhance the appropriate linkages between OEF/OIF veterans and existing VA services.

Recovery from Pediatric Brain Injury: A Preliminary Comparison of Longitudinal Data on Psychological Symptomology and Mental Health Treatment

Objective: To document the course of psychological symptomology, mental health treatment, and unmet psychological needs using caregiver reports in the first 18 months following pediatric brain injury (BI). Method: Participants included 28 children (aged 1-18 years) who were hospitalized at a children's hospital's rehabilitation unit. Caregiver reports of children's psychological symptoms, receipt of mental health treatment, and unmet psychological needs were assessed at one month, six months, 12 months, and 18 months post-BI. Results: Caregivers reported a general increase in psychological symptoms and receipt of mental health treatment over the 18 months following BI; however, there was a substantial gap between the high rate of reported symptoms and low rate of reported treatment. Across all four follow-up time points there were substantial unmet psychological needs (at least 60% of sample). Conclusions: Findings suggest that there are substantial unmet psychological needs among children during the first 18 months after BI. Barriers to mental health treatment for this population need to be addressed.

Identification of geostationary satellites using polarization data from unresolved images

In order to protect critical military and commercial space assets, the United States Space Surveillance Network must have the ability to positively identify and characterize all space objects. Unfortunately, positive identification and characterization of space objects is a manual and labor intensive process today since even large telescopes cannot provide resolved images of most space objects. Since resolved images of geosynchronous satellites are not technically feasible with current technology, another method of distinguishing space objects was explored that exploits the polarization signature from unresolved images. The objective of this study was to collect and analyze visible-spectrum polarization data from unresolved images of geosynchronous satellites taken over various solar phase angles. Different collection geometries were used to evaluate the polarization contribution of solar arrays, thermal control materials, antennas, and the satellite bus as the solar phase angle changed. Since materials on space objects age due to the space environment, it was postulated that their polarization signature may change enough to allow discrimination of identical satellites launched at different times. The instrumentation used in this experiment was a United States Air Force Academy (USAFA) Department of Physics system that consists of a 20-inch Ritchey-Chrétien telescope and a dual focal plane optical train fed with a polarizing beam splitter. A rigorous calibration of the system was performed that included corrections for pixel bias, dark current, and response. Additionally, the two channel polarimeter was calibrated by experimentally determining the Mueller matrix for the system and relating image intensity at the two cameras to Stokes parameters S0 and S1. After the system calibration, polarization data was collected during three nights on eight geosynchronous satellites built by various manufacturers and launched several years apart. Three pairs of the eight satellites were identical buses to determine if identical buses could be correctly differentiated. When Stokes parameters were plotted against time and solar phase angle, the data indicates that there were distinguishing features in S0 (total intensity) and S1 (linear polarization) that may lead to positive identification or classification of each satellite.

An Investigation of Ozone Related Data and Development of a Model to Evaluate Ozone Episodes for Exceptional Event Criteria

The EPA promulgated the Exceptional Events Rule codifying guidance regarding exclusion of monitoring data from compliance decisions due to uncontrollable natural or exceptional events. This capstone examines documentation systems utilized by agencies requesting data be excluded from compliance decisions due to exceptional events. A screening tool is developed to determine whether an event would meet exceptional event criteria. New data sources are available to enhance analysis but evaluation shows many are unusable in their current form. The EPA and States must collaborate to develop consistent evaluation methodologies documenting exceptional events to improve the efficiency and effectiveness of the new rule. To utilize newer sophisticated data, consistent, user-friendly translation systems must be developed.

Response of Catch-Per-Unit-Effort to Spatial and Environmental Factors: an Exploratory Data Analysis Using Generalized Additive Models

Understanding spatial distributions and how environmental conditions influence catch-per-unit-effort (CPUE) is important for increased fishing efficiency and sustainable fisheries management. This study investigated the relationship between CPUE, spatial factors, temperature, and depth using generalized additive models. Combinations of factors, and not one single factor, were frequently included in the best model. Parameters which best described CPUE varied by geographic region. The amount of variance, or deviance, explained by the best models ranged from a low of 29% (halibut, Charlotte region) to a high of 94% (sablefish, Charlotte region). Depth, latitude, and longitude influenced most species in several regions. On the broad geographic scale, depth was associated with CPUE for every species, except dogfish. Latitude and longitude influenced most species, except halibut (Areas 4 A/D), sablefish, and cod. Temperature was important for describing distributions of halibut in Alaska, arrowtooth flounder in British Columbia, dogfish, Alaska skate, and Aleutian skate. The species-habitat relationships revealed in this study can be used to create improved fishing and management strategies.