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One critical tool for creating an environmentally literate citizenry is to reach students other than those in environmental-related majors in the form of the university-level large introductory environmental studies course. In this study, we relate student academic background to initial and final environmental awareness results. We found that students from a wide range of backgrounds begin with similar motivation for taking the class and uniformly low environmental knowledge. Our results indicate that a low-credit, engaging introductory environmental studies class can strongly impact student awareness independent of diverse learner academic backgrounds. For example, results suggest that students taking the course primarily to meet science breadth requirements and students with a strong previous science background had equivalent initial awareness and course outcomes. The lack of a correlation with background suggests that students are not learning about environmental studies in other classes and reinforces the importance of investing in nonmajors-focused environmental education. Additionally, our findings support the importance of affective learning gains, such as attitude changes, which we term "learning to care".

A proliferation of data gathered to predict a critically important, urgent and social-policy related question often leads to debate and divergent model results. This classic feature of complex systems is currently being evidenced in assessing a potentially serious feedback response of soil respiration with increased temperatures due to global climate change. Here we apply soft systems modelling (SSM) for a detailed analysis of the 'soft' aspects of the topic. Supported by a literature review, we conclude that that varied perspectives on the system's dynamics and its web of controlling factors have led to seemingly conflicting results. We present a simplified hierarchy organizing the comprehensive universe of interacting controls across scales. This model is implemented as a relational database, including relationships between factors such as nesting and feedbacks. We conclude that although this model is currently limited to pairwise interactions, it provides a useful tool to assess potential interactions and factors of interest. Copyright © 2009 John Wiley & Sons, Ltd. Keywords soft systems modelling; complexity; global climate change; modelling; soil carbon, INTRODUCTION With many current environmental challenges, a web of confounding factors acting at different scales complicates the coherent synthesis of experimental results. The relationship between temperature and soil carbon decomposition [...]