Introduction

Most environmental scientists and natural resource managers view long-term monitoring as a good thing. To fulfill their mandates and meet their goals, natural resource management and conservation organizations need information on the current status and patterns of change in high-priority resources, critical ecological processes, and stressors of high concern. To inform policy makers and the general public as well as management organizations, government agencies may have mandates for assessing the condition of selected natural resources in perpetuity because of the special importance of these resources to society and because of the possibility of both suspected and unforeseen changes to these resources. More directly, these organizations need information for assessing whether current management is effectively maintaining the state of managed systems and populations within the desired range of conditions, and for reducing uncertainty affecting management performance.

Moreover, there is incredibly high scientific value in many long-term data sets collected for management and conservation purposes, as well as data collected as part of long-term ecological research programs. Natural systems usually are characterized by complex temporal dynamics and interactions often not evident from a collection of short-term research studies. Data from long-term monitoring can be invaluable for empirical examination of hypotheses about spatial and temporal dynamics – for example, about community dynamics, population growth and density dependence, and influences of infrequent extreme climatic events. With the possibility of rapid and major changes to the Earth's climate, there is unprecedented recognition of the importance of existing long-term data sets and demand for new monitoring studies (e.g. see Chapter 22).

Preface

Environmental monitoring is of fundamental importance to natural resourcemanagers, scientists, and human society in general – consider theinarguable importance of quantifying changes in climate, air and water quality,surface and ground water dynamics, and similar attributes. However, monitoringstudies 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, amonitoring program needs to produce information of sufficient accuracy relevantto a clearly defined purpose, and to do so cost-effectively. Yet, even in theshort term, natural populations and systems are inherently variable and usuallydifficult to study. Adding in a multi-year (usually multi-decade) focus createsmany additional challenges and scales of uncertainty – and increases thepotential amount of time and money wasted if these challenges are not adequatelyaddressed. Many monitoring efforts have failed or will fail due to poorlydefined objectives and inadequate designs (Yoccoz et al. 2001,Noon 2003, Legg and Nagy 2006, Lindenmayer and Likens 2010a). Yet, statisticiansand ecologists have developed, and continue to develop, a rich body of knowledgeand practical methods for addressing these challenges, and have applied thesemethods successfully at a variety of scales for a diversity of attributes.Our goal for this volume is to help make some key components of thisknowledge base, as well as new extensions, readily available and accessibleto quantitative and applied natural resource scientists and managers,program managers, students, and consulting biometricians involved withenvironmental monitoring worldwide.