Frequently, ecological monitoring programs are initiated for the purpose of surveillance with no a priori hypotheses in mind. No conceptual framework currently exists to guide the development of surveillance monitoring programs, resulting in substantial debate about program design. We view surveillance monitoring programs as providing information about system dynamics and focus on methods for extracting such information from time series of monitoring data. Our work invokes methods from the general field on nonlinear dynamics that we believe may be useful in extracting information about system dynamics. Our emphasis is on methods for assessing coupling between system components for use in understanding system dynamics and interactions and in detecting changes in system dynamics. More specifically, these methods hold promise for such ecological problems as identifying indicator species, developing informative spatial monitoring designs, detecting ecosystem change and damage, and investigating such topics as population synchrony, species interactions, and environmental drivers. We believe that these ideas and methods provide a useful conceptual framework for surveillance monitoring and can be used with model systems to draw inferences about the design of surveillance monitoring programs.

Monitoring is a fundamental component to assessment of status and change of any dynamical system (environmental, economic, physical, political), and yet there is little formalism to appeal to in order to guide robust monitoring programs. Our work attempts to address this fundamental problem by invoking methods based on information theory which are commonly applied in non-linear dynamical systems analysis.

As with much basic research, we do the research, and write the papers, and hope that people involved in application (in this instance, individuals and agencies involved with development and implementation of monitoring programs) read our work, and apply our basic results. However, as with a lot of basic research, there is often a high degree of technical disconnect between the `basic research` and `implementation`, owing principally to the technical abilities of many agencies to understand, let alone implement, some of the basic results.

Basic science is rarely directly involved in any "corporate" sense. Our work is no different. No demonstrable benefits to date, unless you consider contributing to our basic conceptual understanding of "how things work" as a benefit - as beneficial as a direct "implementation" (without basic research, there is nothing to implement, after all).

None - we do this on our own time. Much of this work involves "ideas", and "thinking" - with some computer time.

• Jim Nichols (Patuxent Wildlife Research Center)
• Jonathon Nichols (Naval Research Labs)
• Lou Pecora (Naval Research Labs)
• Linda Moniz (Patuxent Wildlife Research Center)