Elsevier

Biological Conservation

Volume 143, Issue 6, June 2010, Pages 1317-1328
Biological Conservation

Review
The science and application of ecological monitoring

https://doi.org/10.1016/j.biocon.2010.02.013Get rights and content

Abstract

We provide a broad overview of the underlying philosophy of ecological monitoring. We argue that the major characteristics of effective monitoring programs typically include: (1) Good questions. (2) A conceptual model of an ecosystem or population. (3) Strong partnerships between scientists, policy-makers and managers. (4) Frequent use of data collected.

We classify monitoring programs into three categories – (1) Passive monitoring, which is devoid of specified questions or underlying study design and has limited rationale other than curiosity. (2) Mandated monitoring where environmental data are gathered as a stipulated requirement of government legislation or a political directive. The focus is usually to identify trends. (3) Question-driven monitoring, which is guided by a conceptual model and by a rigorous design that will typically result in a priori predictions that can be tested.

There are advantages and disadvantages of mandated monitoring programs, which are typically large-scaled, and generally smaller-scaled, question-driven monitoring programs. For example, while question-driven monitoring programs can provide insights into the ecological processes giving rise to emergent environmental patterns, spatial generalization from them is difficult because results may not extrapolate well to other regions, states or to a national level. Conversely, while mandated monitoring can be useful for producing coarse level summaries of temporal changes in a target population or resource condition they may not identify the mechanism influencing a change in an ecosystem or an entity. A key remaining challenge is to develop much improved mandated monitoring programs through more widespread adoption of the features of successful question-driven monitoring programs in efforts to enhance biodiversity conservation and environmental management.

Introduction

Countless scientific articles, books, management plans and other documents have been written about the need to do long-term ecological monitoring (e.g. Franklin et al., 1999, Goldsmith, 1991, Krebs et al., 2008, Likens, 1989, Likens, 1992, Lovett et al., 2007, Spellerberg, 1994, Strayer et al., 1986, Thompson et al., 1998). Indeed, as part of writing this review, a search of the ecological literature published between 1985 and mid-2009 produced more than 5500 articles with the term ‘monitoring’ in the title or abstract. Within this very large literature are some distinct biases in subject material. First, much has been written about specific methods of monitoring a particular entity, but we believe that these will often be relevant only to that entity (e.g. a species or group of species) or to a given place; they may not be readily transferable to other entities or landscapes. A second bias in the literature is toward generic lists of entities that are advocated as “mandatory” to monitor and generic frameworks to guide the measurement of these entities. However, we believe that the transferability of these approaches to other ecosystems can be problematic. Third, much of the monitoring literature focuses on statistical methods. While these approaches are valuable, they may not be relevant to specific questions or problems that any given particular monitoring program aims to address. Fourth, much of the monitoring literature focuses on “indicators” and claims that entity X or species Y is an “indicator”. Often these claims are unsubstantiated. Where they are substantiated, the generality of the indicator function can be limited – either spatially, taxonomically or both, and this approach may not be helpful for those proposing to establish new monitoring programs.

In this paper, we do not revisit these already well-covered themes and advocate, for example, particular field techniques, statistical methods, or target entities for long-term ecological monitoring. We have not undertaken a meta-analysis or systematic review of world-wide, monitoring programs, nor do we provide summary statistics on different kinds of monitoring programs or the range of entities targeted in monitoring programs. Rather, our focus is on the underlying philosophy of monitoring for ecological knowledge. First, we provide a definition of long-term monitoring. We then classify long-term monitoring into three broad categories – (1) curiosity-driven or passive monitoring, (2) mandated monitoring, and (3) question-driven monitoring. We then discuss the key characteristics of each category and present a short treatise on the kinds of ecological values that can be derived from data gathered in long-term, ecological monitoring programs. Our assessment of the vast literature on monitoring suggests that monitoring programs are often ineffective or fail completely and we present a series of reasons for these problems. As a counter to that section, we then present a description of the key characteristics of effective ecological monitoring programs. The concluding section of this paper focuses on two topics: (1) some important impediments to be overcome in improving monitoring programs – particularly given current attributes of the culture of science and society and (2) the challenges of integrating data from different kinds of monitoring programs that are undertaken at different spatial scales and with different approaches.

Our aim in writing a set of general philosophical perspectives on long-term monitoring is to foster a renewed interest in, and an improvement of, ecological monitoring. We consider that it is now increasingly critical to undertake high-quality, question-driven, statistically-designed monitoring, given the rapid increase in the effects of climate change (Lawler, 2009, Heller and Zavaleta, 2009), other human-accelerated environmental changes (Likens, 1991), and the need to reverse current, widespread environmental degradation (Millennium Ecosystem Assessment, 2005). We believe that given the increasing seriousness of environmental problems throughout the world, there never has been a more important time to establish effective and interacting monitoring programs.

Section snippets

A definition of long-term monitoring

For the purposes of this review, we use a practical, operational definition of long-term monitoring efforts that is:

Repeated field-based empirical measurements are collected continuously and then analyzed for at least 10 years.

Some in the scientific community view monitoring as a management activity unrelated to scientific research (e.g. Hellawell, 1991). Conversely, we believe that long-term monitoring is both science and research (Nichols and Williams, 2006, Yoccoz et al., 2001). Good science

Three broad kinds of monitoring

We believe there are three broad types of long-term monitoring within the general definition we have proposed above. These are curiosity-driven or passive monitoring, mandated monitoring and question-driven monitoring. We further discuss these kinds of monitoring in the remainder of this section.

Some ecological values and uses of datasets from long-term monitoring

All organisms, including humans, depend upon the functioning of ecosystems for their well being and survival. High-quality ecological information collected over long periods provides critical insights into changes in these ecosystem services. Without this information, we would have no knowledge about the changing status of the life-support system of the planet. Therefore, data from long-term monitoring programs are fundamentally valuable for many purposes, including:

  • Documenting and providing

Poor record of long-term ecological monitoring

Although there have been some highly successful long-term research and monitoring programs (e.g. Goldman, 1981, Lawes Agricultural Trust, 1984, Likens, 1985, Lund, 1978, Schindler et al., 1985), there is a prolonged history of poorly planned and unfocused monitoring programs that are either ineffective or fail completely (see Allen, 1993, Krebs, 1991, Legg and Nagy, 2006, Norton, 1996, Orians, 1986, Stankey et al., 2003). For example, Allen, 1993, Norton, 1996 have described how nearly half of

Characteristics of effective monitoring programs

From our extensive assessment of the very large literature on ecological monitoring, we believe that it is possible to identify some key features of effective or successful monitoring programs. We summarize these in Table 2 and discuss several of them in more detail in the remainder of this section. It is important to identify such factors to improve public perspectives of ecological monitoring and provide policy-makers with reasons to continue funding investments in monitoring programs.

The methodology of effective monitoring

Based on some of the salient features that should accompany effective monitoring programs, we have previously proposed an “Adaptive Monitoring” framework (Lindenmayer and Likens, 2009). A fundamental part of this framework is that question-setting, study design, data collection, data analysis, and data interpretation are iterative steps. A monitoring program can then evolve and develop in response to new information or new questions. For example, it may be appropriate to alter the frequency of

Impediments to developing more and better monitoring programs

The two preceding sections of this review contrasted the characteristics of ineffective monitoring programs with the features of effective or successful ones. Our review of the scientific literature suggests that the former are more common than the latter and we believe there are at least four substantial impediments that must be overcome to develop more and better long-term ecological monitoring.

A major challenge – integrating knowledge from different kinds of monitoring

We have shown that there are several kinds of long-term monitoring programs and crudely assigned them into three broad categories: question-driven monitoring, mandated monitoring, and curiosity-driven or passive monitoring. These kinds of monitoring programs are often conducted in different ways and usually at different spatial scales. In this section we argue that fundamentally important challenges remain about how to: (1) better integrate data, approaches and insights from different kinds of

Concluding remarks

We argue that there is a suite of kinds of monitoring programs and that these are often conducted in different ways and at different scales with the most effective ones being those focused on well-crafted questions resulting in a study design, a set of attributes and an implementation approach that will be different in each monitoring program. Thus, there is clearly not a one-size-fits-all approach to monitoring.

Various kinds of long-term ecological monitoring will be fundamental to

Acknowledgments

Parts of this review draws on our book, “Effective Ecological Monitoring” (CSIRO Publishing and Earthscan). We thank the Commonwealth Environment Research Facilities CERF) program of the Australian Government for financial support and encouragement with our work. We thank R. Primack for encouraging the writing of this review. R. Muntz assisted with the preparation of many key aspects of this paper.

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