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.