Distance software: design and analysis of distance sampling surveys for estimating population size

1. Distance sampling is a widely used technique for estimating the size or density of biological populations. Many distance sampling designs and most analyses use the software Distance. 2. We briefly review distance sampling and its assumptions, outline the history, structure and capabilities of Distance, and provide hints on its use. 3. Good survey design is a crucial prerequisite for obtaining reliable results. Distance has a survey design engine, with a built-in geographic information system, that allows properties of different proposed designs to be examined via simulation, and survey plans to be generated. 4. A first step in analysis of distance sampling data is modeling the probability of detection. Distance contains three increasingly sophisticated analysis engines for this: conventional distance sampling, which models detection probability as a function of distance from the transect and assumes all objects at zero distance are detected; multiple-covariate distance sampling, which allows covariates in addition to distance; and mark–recapture distance sampling, which relaxes the assumption of certain detection at zero distance. 5. All three engines allow estimation of density or abundance, stratified if required, with associated measures of precision calculated either analytically or via the bootstrap. 6. Advanced analysis topics covered include the use of multipliers to allow analysis of indirect surveys (such as dung or nest surveys), the density surface modeling analysis engine for spatial and habitat-modeling, and information about accessing the analysis engines directly from other software. 7. Synthesis and applications. Distance sampling is a key method for producing abundance and density estimates in challenging field conditions. The theory underlying the methods continues to expand to cope with realistic estimation situations. In step with theoretical developments, state-of- the-art software that implements these methods is described that makes the methods accessible to practicing ecologists.

Fire History at the Eastern Great Plains Margin, Missouri River Loess Hills

The purpose of this paper is to provide quantitative fire history information for a geographically unique region, the Loess Hills of northwest Missouri. We sampled 33 bur oak (Quercus macrocarpa Michx.), chinkapin oak (Q. muehlenbergii Engelm.), and black oak (Q. velutina Lam.) trees from the Brickyard Hill Conservation Area in northwest Missouri. The period of tree-ring record ranged in calendar years from 1671 to 2004 and fire-scar dates (n = 97) ranged from 1672 to 1980. Fire intervals for individual trees ranged from 1 to 87 years. The mean fire interval was 6.6 years for the pre-Euro-American settlement period (1672-1820), and 5.2 years for the entire record (1672-1980). A period of more frequent fire (mean fire interval = 1.6 for 1825 to 1850) coincided with Euro-American settlement of the area. The average percentage of trees scarred at the site was 16.8%, or about 1 in 7 trees sampled per fire. No significant relationship between fire years and drought conditions was found; however, events prior to 1820 may have been associated with wet to dry mode transitions.

MATERIAL MODELING AND ANALYSIS FOR THE DEVELOPMENT OF A REALISTIC BLAST HEADFORM

Blast traumatic brain injury (BTBI) has become an important topic of study because of the increase of such incidents, especially due to the recent growth of improvised explosive devices (IEDs). This thesis discusses a project in which laboratory testing of BTBI was made possible by performing blast loading on experimental models simulating the human head. Three versions of experimental models were prepared – one having a simple geometry and the other two having geometry similar to a human head. For developing the head models, three important parts of the head were considered for material modeling and analysis – the skin, skull and brain. The materials simulating skin, skull and brain went through many testing procedures including dynamic mechanical analysis (DMA). For finding a suitable brain simulant, several materials were tested under low and high frequencies. Step response analysis, rheometry and DMA tests were performed on materials such as water based gels, oil based mixtures and silicone gels cured at different temperatures. The gelatins and silicone gels showed promising results toward their use as brain surrogate materials. Temperature degradation tests were performed on gelatins, indicating the fast degradation of gelatins at room temperature. Silicone gels were much more stable compared to the water based gels. Silicone gels were further processed using a thinner-type additive gel to bring the dynamic modulus values closer to those of human brain matter. The obtained values from DMA were compared to the values for human brain as found in literature. Then a silicone rubber brain mold was prepared to give the brain model accurate geometry. All the components were put together to make the entire head model. A steel mount was prepared to attach the head for testing at the end of the shock tube. Instrumentation was implemented in the head model to obtain effective results for understanding more about the possible mechanisms of BTBI. The final head model was named the Realistic Explosive Dummy Head or the “RED Head.” The RED Head offered potential for realistic experimental testing in blast loading conditions by virtue of its material properties and geometrical accuracy.