Preface Environmental monitoring is of fundamental importance to natural resource managers, scientists, and human society in general – consider the inarguable importance of quantifying changes in climate, air and water quality, surface and ground water dynamics, and similar attributes. However, monitoring studies also have the potential to be a significant waste of time and money (see, for example, discussions by Legg and Nagy 2006). To have value, a monitoring program needs to produce information of sufficient accuracy relevant to a clearly defined purpose, and to do so cost-effectively. Yet, even in the short term, natural populations and systems are inherently variable and usually difficult to study. Adding in a multi-year (usually multi-decade) focus creates many additional challenges and scales of uncertainty – and increases the potential amount of time and money wasted if these challenges are not adequately addressed. Many monitoring efforts have failed or will fail due to poorly defined objectives and inadequate designs (Yoccoz et al. 2001, Noon 2003, Legg and Nagy 2006, Lindenmayer and Likens 2010a). Yet, statisticians and ecologists have developed, and continue to develop, a rich body of knowledge and practical methods for addressing these challenges, and have applied these methods successfully at a variety of scales for a diversity of attributes. Our goal for this volume is to help make some key components of this knowledge base, as well as new extensions, readily available and accessible to quantitative and applied natural resource scientists and managers, program managers, students, and consulting biometricians involved with environmental monitoring worldwide.