Yue Xue

© Cambridge University Press, 2011.The Alpert–Stein Factor Separation Methodology method has been utilized in the study of the biophysical response to changes in the environment to assess the relative contribution of different atmospheric factors to the biological system. In this chapter we will discuss crop simulation and land surface model-based assessments of the sensitivity to past and future changes in climatic conditions: increasing CO 2, soil moisture, temperature and radiative conditions, and crop management procedures. FS is applied to discern specific contributions to plant responses by single variables or combinations of environmental conditions. Our FS analysis has shown that it is important to understand that biological responses are inherently dependent on multiple variables in the natural world and should not be limited to assessments of single specific parameters. Introduction In this chapter we demonstrate how the FS analysis technique is a useful tool for crop–climate change studies. Important interactions between the atmosphere and biophysical processes occur under land surface and atmospheric carbon dioxide level changes. We employ the Alpert–Stein FS Methodology to investigate the direct as well as the interactive effects of soil moisture, temperature, and radiative changes on the direct effects of CO 2 doubling for different land-use/vegetation types, including agricultural production.

The Ultimatum Game (UG) is one of the widely studied games in experimental economics. Past data shows a consistent deviation from the classical game theory prediction, which suggests a self-interested money maximizing rational agent would accept any nonzero offer as a responder. However, in reality, people often reject low offers that are less than 30% and above zero. Research from neuro-economics claims that such behavior is mostly emotion driven. However an important cross-cultural study shows that the results in these small-scaled societies deviate drastically from the industrialized societies. In addition, there is a high correlation between the deviations and the social systems. Economists call for a better understanding of how people apply social rules when they make economic decision. We believe that we need a framework that can show the following: 1. Preferences are constructed on demand. 2. Social rules are numerous and complex, and tend to trigger non-monotonic reasoning. Formally, we developed the Closed-World Reasoning in Games framework (CWRiG) adopted from Closed-World Reasoning framework (CWR) by van Lambalgen and Stenning. We defined what can be considered a monotone game process. More importantly we show how an agent can make a rational decision change through a non-monotonic reasoning process that brings social rules into the game process. Experimentally, we ran a modified ultimatum game. The results confirms that people's general, even ranked, attitudes towards some social matters are not necessarily equivalent to their preferences of the same kind of matter during the game. We also discover many instances of non-monotonic reasoning patterns used during the game