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As the environments and tasks that teams (in both military and civilian settings) are faced with increase in complexity, standard statistical methods may not fully capture team dynamics and processes. Nonlinear analyses provide alternative, mathematically derived descriptions quantifying the level of complexity and variability inherent in a data set, and may provide a more accurate understanding of dynamic systems. The goal of the present study was to investigate changes in heart interbeat interval associated with task workload using one type of nonlinear analysis, power spectral density analysis. In this study, physical and mental workload were manipulated in separate tasks to explore the contributions of each to interbeat interval variability. Results indicated that spectral analysis can identify large changes in overall workload, but may be insensitive to small or medium changes. However, these conclusions are based on preliminary results; follow-up research is necessary to determine the veracity of these conclusions.