Die lebensdaten des Glaubensstifters Nānak

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Measuring Relative Sustainability of Regions Using Regional Sustainability Assessment Methodology

Scientists analyze sustainability at the regional level with a combination of multiple indicators which reflect different characteristics of regions without combining the results in a single comparative unit. Moreover, the assessment of interdependencies between different characteristics requires experts' analyses, which makes sustainability analysis subjective, time consuming, and limited in use. This article analyzes the relative sustainability of subnational level regions through the application of regional sustainability assessment methodology (RSAM) based on accounting of resources capital and its internal and external transfers. This approach allows for assessment of regional sustainability as a function of resource quantity, quality, and interchangeability. The comparison of the two case study regions presented in the paper indicates the difference between a more sustainable region and a region of “weak sustainability.” First, the article indicates the discussion of the relevant geographic, economic, and social literature for both sustainability assessment and regional comparison. This discussion is followed by a conceptual representation of proposed RSAM and its application to various regions. Next, the article covers the data used and applied methods to test the proposed methodology and compare the two case study regions. The article concludes with a discussion of findings and recommendations for further application and testing.     

Estimation of Spatio-Temporal Correlations of Prehistoric Population and Vegetation in North America

We discuss a simple methodology to enable a statistical comparison of human population with the vegetation of North America over the past 13,000 years. Nonparametric kernel methods are applied for temporal and spatial smoothing of point data obtained from the Neotoma Paleoecology Database and the Canadian Archaeological Radiocarbon Database, which results in sequences of maps showing the development of population and different plant taxa during the Holocene. The estimation of smooth spatial and spatio-temporal cross-correlation functions is proposed in order to detect relationships between population and vegetation in fixed time intervals. Furthermore, the effects of varying environment on demographic changes as well as potential impacts of populations on plant taxa over time are analyzed. Pointwise confidence bands for cross-correlation functions are computed and a robustness analysis is performed to assess the significance of obtained results. Considering the example of oak, an interpretation of our results for eastern North America shows the value of this methodology.