Population Viability: Evolving Tools for Declining Species


Population Viability Analysis. Beissinger, S. R., and D. R. McCullouch , editors . 2002 . University of Chicago Press , Chicago . 577 pp. $95.00 (hardcover). ISBN 0-226-04177-8 . $dollar;35.00 (paperback). ISBN 0–226–04178–6.

The visibility of books and review articles on population viability is clearly high. A recent book by Beissinger and McCullough will achieve high visibility by virtue of its impressive author lineup and title. What does it deliver?

The book is as heterogeneous in topics as are the organisms whose viability needs attention, but in general the book is skewed toward technical descriptions of various tools—mainly statistical and modeling—that can inform population viability analyses ( PVAs ). The chapters are well written and treat topics that many will find interesting. Still, it is a slow read and may be most useful for readers to dip into for reference material. As Michael Soulé points out in an unusual forward ( except perhaps for him ), the book is a technical leap forward, although it may neglect some conservation practicalities in favor of greater mathematical rigor.

Many narrowly oriented chapters are likely to appeal mainly to specialists, and some do not provide clear connections to conservation practice. But there is a wealth of information on such topics as effective population size ( Waples ), mark/recapture statistics ( White et al. ), sensitivity analyses ( Mills & Lindberg ), and pedigree analysis ( Haig & Ballou ). As one who has lamented the difficulties of obtaining realistic seed-bank data ( Menges 2000 ), I was encouraged to see Doak et al. push the envelope in exploring how seed banks may ( not ) provide populations with resiliency in the face of uncertainty and how simulations may be used as an admittedly incomplete replacement for data that are generally simply missing.

One theme that provides a lot of rigor to this book is improving our understanding of variation and uncertainty and how various types of variation may make predictions of PVAs imprecise (see also Brook et al. 2000; Coulson et al. 2001; McCarthy et al. 2001; Ellner et al. 2002 ). Chapters on stochasticity and variation range from the familiar and theoretical ( Lande on stochasticity ) to the unfamiliar and somewhat applied (chapters by Wade and Taylor et al. on Bayesian approaches to dealing with uncertainty, Saether et al. on including uncertainties in a non-Bayesian world by using simple models based on very long-term data on population dynamics ) to an empirical test of how brine shrimp microcosms do (or in this case do not ) behave as predicted by published demographic models. Point-estimate PVAs that may ignore uncertainty are hung out to dry. As a practical matter, however, the alternative approaches require either extensive data on uncertainty or simplification of models that don't seem very close to real-world life histories. A chapter by Goodman on using Bayesian approaches to inform recovery plans is interesting and well-written, although probably not too practical ( in its current level of detail ) to those agency people writing those plans. All these technical chapters on uncertainty are quite well-written, so readers can decide for themselves which approaches might be helpful for their situation.

Another theme is better integration of habitat analyses and demographically based PVAs. Boyce's short essay introduces the subject, but I found some of the case histories more compelling. Studies on the Florida panther and Cape Sable Seaside Sparrow (see below ) were particularly illustrative. The chapter on the panther by Maehr et al. is fascinating because it illustrates the evolution of PVAs that has caused revolutions in genetic management. Although its genetic problems are key, the way to get this feline out of its genetic corner comes down to old-fashioned habitat conservation, which will allow favorable demographics to increase population sizes away from today's bottleneck. Genetics receives some additional attention. Inbreeding effects and ways to integrate them into PVAs are nicely summarized by Allendorf and Ryman. A chapter by Hedrick, despite its broad title, is somewhat more narrowly focused on units of conservation and effective population size.

Comparative PVAs have been touted as relieving the weaknesses of precise predictions in the face of unknowable uncertainties. This is one of the themes of Hanski's nice review of metapopulation models. The virtue of comparisons comes up in several chapters. Nevertheless, error propagation in projections means that even comparative approaches based on insufficient data may turn out to be very wrong ( e.g., Bierzychudek 1999).

I appreciated some authors' more provisional approaches that made the best of sparse data through common-sense approaches. Harrison and Ray use straightforward patch-based occupancy models parameterized with minimal data on plants from serpentine seeps. Pimm and Bass consider as alternatives to models based on population dynamics, the range of catastrophic effects, and potential recovery, of Cape Sable Seaside Sparrows. This is another example of how the best mathematical tools cannot replace good knowledge of the landscape and management context. It also is another sobering reminder of humankind's weaknesses in predicting and controlling catastrophic landscape changes, even in protected areas.

A few chapters segue from PVA techniques to conservation planning and policy. Samson discusses the implementation of PVAs in conservation planning and emphasizes the tendency to punish sins of commission more than sins of omission. In the current climate of great caution with respect to the precision of PVA predictions, one must keep in mind that lack of scientific certainty should not translate to lack of action in saving species. One of my favorite chapters in the book is the refreshingly practical problem solving of Possingham et al. The chapter is critical of “too much theory” and an “obsession with accurate estimation” that could have been aimed at many of the other contributing authors. Decision theory, a sort of structured approach to analyzing various scenarios, is used to evaluate the effects of specific management actions, such as patterns of preservation and alteration of logging practices, on extinction risk. The more formal approaches are hampered by large computational requirements, but the approach is effective at integrating management and science. Following this chapter, Lacy and Miller urge ecologists to collaborate with social scientists to explicitly model human population growth and human effects. For many ecologists, it may be mind-boggling to contemplate parameterizing civil war ( and its effects on non-human species ). After these two original and optimistic assessments of future directions of PVA, the chapter on adaptive management and PVA by Ludwig and Walters was extremely pessimistic about integrating PVA into adaptive management. It also failed to alleviate my suspicion that adaptive management is, on the one hand, a long-used common-sense approach to integrating science and management and, on the other hand, an agency-driven flavor of the month that does not often accomplish new conservation goals.

Perhaps the most thought-inducing chapter avoided modeling cul-de-sacs and the limitations of case histories. Shaffer et al.'s thoughtful discussion deals with disconnects between science and society and what scientists dealing with PVAs can do to make their research both more consistent and more consistently communicated.

The book closes with Ralls et al. outlining an ambitious list of definitions and guidelines for PVAs. Many of the ideas echo those of previous sections, but the ideas on validation are interesting and practical. For example, Ralls et al. suggest that multiple time periods be used in projections because short time periods limit error propagation but cannot address long-term questions and may be misleading for long-lived species. Likewise, reasonable recommendations include using several types of models, making databases accessible, and postulating “rules of thumb” based on populations' representation, redundancy, and resiliency. This is a useful and thoughtful piece of writing, but it is unlikely to be a “consensus” in PVA as the authors hope.

Beissinger and McCullough's book has a lot of competition, including a “how-to” book packed with MATLAB routines ( Morris & Doak 2002), a proceedings volume spiced with case histories ( Sjögren-Gulve & Ebenhard 2000), phytocentric reviews ( Menges 2000; Brigham & Schwartz 2003), and more general analyses of major PVA issues (e.g., Reed et al. 2002 ). Despite a number of listless or impractical chapters, this volume has enough technical grit and new ideas to make it essential for PVA practioners, interesting for most conservation biologists, and stimulating (and challenging ) for students learning about PVA.