Least Cost Path (LCP) analysis allows a user to define a cost parameter through which cost of movement can be assessed using Geographical Information Systems (GIS). These analyses are commonly used to construct theoretical movement through a landscape, which has been useful for creating hypotheses concerning prehistoric archaeology and landscape genomics. However, LCP analysis is commonly employed without testing the generated LCP(s), complicating its usefulness as a methodological tool. This paper proposes a model for analyzing movement in ArcGIS by using topography data to calculate slope. This slope data is then then used to calculate LCPs based on travel time and kilocalorie expenditure. LCPs were constructed in the Nature Preserve at Binghamton University, a 182-acre area that consists of wetland and mountainous terrain, and a Fitbit® Surge activity monitor was used to test the accuracy of the model's predictions. Paired sample t-tests show a lack of significant difference between calculated and walked time in our analysis (p = .953), suggesting that our model can estimate travel time between two points based solely on slope of the region. Paired sample t-tests also show a lack of significant difference between calculated and observed kilocalorie expenditure (p = .930), suggesting that our model is also capable of estimating kilocalorie expenditure associated with movement between two points. Finally, paired sample t-tests confirm that straight line distances do not reflect real movement through a terrain (p = .009), highlighting the need for alternate measures of movement when analyzing the effects of local landscape on movement. Our current model shows strength in its estimations of travel time and kilocalorie expenditure based on topography of a region-future iterations of the model need to establish the statistical similarity between our model's estimations and recorded values for walking time and kilocalorie expenditure.

Objectives: The island of New Guinea was settled by modern human over 50,000 years ago, and is currently characterized by a complex landscape and contains one-seventh of the world's languages. The Eastern Highlands of New Guinea were also the home to the devastating prion disease called kuru that primarily affected Fore-speaking populations, with some 68% of cases involving adult females. We characterized the mitochondrial DNA (mtDNA) diversity of highlanders from Papua New Guinea (PNG) to: (a) gain insight into the coevolution of genes and languages in situ over mountainous landscapes; and (b) evaluate the recent influence of kuru mortality on the pattern of female gene flow. Materials and Methods: We sequenced the mtDNA hypervariable segment 1 of 870 individuals from the Eastern and Southern Highlands of PNG using serums collected in the 1950s to 1960s. These highlanders were selected from villages representing 15 linguistic groups within the Trans-New Guinea phylum. Genetic, linguistic, and geographic distances were calculated separately and correlations among those distance matrices were assessed using the Mantel test. Results: Geographic, genetic, and linguistic patterns were independently correlated with each other (p < .05). Increased mtDNA diversity in kuru-affected populations and low Fst estimates between kuru-affected linguistic groups were observed.Discussion: In general, the genetic structure among the Highland populations was shaped by both geography and language, and language is a good predictor of mtDNA affinity in the PNG Highlands. High kuru female mortality increased female gene flow locally, disrupting coevolutionary pattern among genes, languages, and geography.